Screening risk assessment of organic pollutants and environmental impacts from sewage sludge management : study to support policy development on the Sewage Sludge Directive (86/278/EEC).
Date: 2022-10-10
Institutions: Joint Research Centre
Subjects: antimicrobial resistance, directive (EU), environmental impact, environmental risk prevention, health risk, organic pollution, report, risk management, sewage sludge, wastewater

ISSN 1831-9424 

Screening risk assessment of organic 
pollutants and environmental impacts 
from sewage sludge management 

Study to support policy 
development on the Sewage 
Sludge Directive (86/278/EEC) 

Huygens D., García-Gutierrez P., Orveillon G., 
Schillaci C., Delre A., Orgiazzi A., Wojda P., Tonini 
D., Egle L., Jones A., Pistocchi A., Lugato E. 

2022 

EUR 31238 EN 

 
 
 
This  publication  is  a  Science  for  Policy  report  by  the  Joint  Research  Centre  (JRC),  the  European  Commission’s  science  and  knowledge 
service. It aims to provide evidence-based scientific support to the European policymaking process. The contents of this publication do not 
necessarily  reflect  the  position  or  opinion  of  the  European  Commission.  Neither  the  European  Commission  nor  any  person  acting  on 
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authorities, or concerning the delimitation of its frontiers or boundaries. 

Contact information  
European Commission, Joint Research Centre 
Directorate B – Growth and Innovation 
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Edificio Expo, c/ Inca Garcilaso, 3, E-41092 Seville, Spain 
E-mail: JRC-WASTE-RESEARCH@ec.europa.eu 
Telephone: +34 95 44 88 139 

EU Science Hub 
https://joint-research-centre.ec.europa.eu 

JRC129690 

EUR 31238 EN 

PDF 

ISBN 978-92-76-57322-7 

ISSN 1831-9424 

doi:10.2760/541579  KJ-NA-31-238-EN-N 

Luxembourg: Publications Office of the European Union, 2022  

© European Union, 2022  

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How to cite this report: Huygens D., García-Gutierrez P., Orveillon G., Schillaci C., Delre A., Orgiazzi A., Wojda P., Tonini D., Egle L., Jones A., 
Pistocchi A. & Lugato E, Screening risk assessment of organic pollutants and environmental impacts from sewage sludge management - 
Study to support policy development on the Sewage Sludge Directive (86/278/EEC), Publications Office of the European Union, 
Luxembourg, 2022, doi:10.2760/541579, JRC129690

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Contents 

Abstract .................................................................................................................................................................... 1 

Key messages ........................................................................................................................................................ 2 

Executive summary ........................................................................................................................................... 3 

1 

2 

3 

General objective and structure of the report ................................................................................................................................................. 6 

Background on sewage sludge management in the EU ........................................................................................................................ 7 

Screening risk assessment for chemical pollutants in sludge ...................................................................................................... 11 

3.1 

3.2 

Objectives and scope .......................................................................................................................................................................................... 11 

Methodology ............................................................................................................................................................................................................... 11 

3.2.1 

3.2.2 

Exposure assessment tool ............................................................................................................................................................... 11 

A stepwise approach ............................................................................................................................................................................. 12 

3.3 

Human health assessment ........................................................................................................................................................................... 15 

3.3.1 

3.3.2 

3.3.3 

3.3.4 

Step 1 results ............................................................................................................................................................................................... 15 

Step 2 results ............................................................................................................................................................................................... 18 

Impact of sludge treatments ........................................................................................................................................................ 22 

Prioritisation of pollutants ............................................................................................................................................................... 23 

3.4 

Assessment for soil organisms ................................................................................................................................................................. 23 

3.4.1 

3.4.2 

Results ................................................................................................................................................................................................................. 23 

Prioritisation of pollutants ............................................................................................................................................................... 25 

3.5 

3.6 

3.7 

Availability of measurement standards ........................................................................................................................................... 26 

Impacts of wastewater treatment processes ............................................................................................................................. 28 

Risk screening assessment conclusions and recommendations............................................................................... 28 

4 

Other contaminants present in sludge ................................................................................................................................................................ 30 

4.1 

4.2 

4.3 

Antimicrobial resistance .................................................................................................................................................................................. 30 

Biological pathogens ........................................................................................................................................................................................... 31 

Microplastics contamination ........................................................................................................................................................................ 32 

5 

Soil nitrogen, carbon and phosphorus cycling .............................................................................................................................................. 34 

5.1 

5.2 

5.3 

5.4 

5.5 

5.6 

Objective and scope............................................................................................................................................................................................. 34 

Modelling approach .............................................................................................................................................................................................. 34 

Results .............................................................................................................................................................................................................................. 35 

Climate change adaptation .......................................................................................................................................................................... 38 

Phosphorus cycling ............................................................................................................................................................................................... 39 

Conclusions .................................................................................................................................................................................................................. 39 

6 

Impacts on climate change mitigation ................................................................................................................................................................ 40 

6.1 

6.2 

Objectives and scope .......................................................................................................................................................................................... 40 

Methodology ............................................................................................................................................................................................................... 40 

i 

 
 
 
 
6.3 

6.4 

6.5 

6.6 

Results (average values) ................................................................................................................................................................................. 41 

Uncertainty analysis ............................................................................................................................................................................................ 44 

Impacts of upstream wastewater treatment processes .................................................................................................. 45 

Relative importance of sewage sludge management for climate change ..................................................... 46 

6.7 
Supplementary potential for energy recovery from sludge from digestion and incineration with 
energy recovery .............................................................................................................................................................................................................................. 46 

6.8 

Conclusions .................................................................................................................................................................................................................. 47 

7 

Limitations and recommendations for further work .............................................................................................................................. 48 

7.1 

7.2 

Issue #1: Compare and discuss risk screening approach with other information sources ............. 48 

Issue #2: Address uncertainty on organic pollutant concentrations present in sewage sludge 48 

7.3 
Issue #3: Improve database on ecotoxicological, toxicological and physico-chemical properties 
of organic contaminants ........................................................................................................................................................................................................ 49 

7.4 
and mixtures thereof ................................................................................................................................................................................................................. 49 

Issue #4: Need for an in-depth risk assessment for identified organic priority contaminants 

7.5 

7.6 

7.7 

Issue #5: Assess environmental and health impacts from metals ........................................................................ 50 

Issue #6: Assess innovative sludge management technologies ............................................................................... 50 

Overall considerations and policy recommendations.......................................................................................................... 50 

8 

9 

10 

11 

12 

General conclusions ............................................................................................................................................................................................................... 51 

References ...................................................................................................................................................................................................................................... 52 

List of abbreviations.............................................................................................................................................................................................................. 67 

List of figures ............................................................................................................................................................................................................................... 69 

List of tables ................................................................................................................................................................................................................................. 71 

Annexes ................................................................................................................................................................... 74 

13 

Supplementary information – screening risk assessment ................................................................................................................ 75 

13.1 

Risk screening model calculations ......................................................................................................................................................... 75 

13.1.1 

Soil model ........................................................................................................................................................................................................ 75 

13.1.2  Water model .................................................................................................................................................................................................. 79 

13.1.3 

Human via food intake ........................................................................................................................................................................ 82 

13.2  Model input data for results reported in main text ............................................................................................................... 88 

13.3 

Results – Step 2 risk assessment ........................................................................................................................................................... 90 

13.3.1 

Perfluoroalkyl substances (PFAS) ............................................................................................................................................. 90 

13.3.2 

Polyaromatic hydrocarbons (PAH) ............................................................................................................................................ 95 

13.3.3 

PCDD/Fs and dioxin-like PCBs ....................................................................................................................................................... 99 

13.3.4 
(HBCDD), and organophosphate compounds) ....................................................................................................................................... 104 

Flame retardants (polybrominated diphenyl ethers (PBDEs), hexabromocyclododecane 

13.3.5 

Alkylphenols ................................................................................................................................................................................................ 110 

13.3.6 

Polychlorinated alkanes .................................................................................................................................................................. 113 

13.3.7 

Polychlorinated naphthalenes (PCNs) ................................................................................................................................ 117 

13.3.8 

Organotin compounds ....................................................................................................................................................................... 120 

13.3.9 

Phthalate acid esters ......................................................................................................................................................................... 122 

ii 

 
 
13.3.10  Polydimethylsiloxanes ...................................................................................................................................................................... 126 

13.4 

Supplementary information - measurement standards for priority pollutants ...................................... 129 

14 

Supplementary Information – soil biogeochemical modelling .................................................................................................. 131 

14.1  Model approach .................................................................................................................................................................................................... 131 

14.2 

Results ........................................................................................................................................................................................................................... 133 

14.2.1 

Spatially explicit CH emission from the use-on-land of sludge ............................................................... 133 

14.2.2 

Carbon sequestration in soils as a function of time for soils in the EU Member States.. 134 

15 

Supplementary information – life cycle assessment ......................................................................................................................... 135 

15.1  Model input parameters ............................................................................................................................................................................... 135 

iii 

 
 
Abstract 

Sewage  sludge  is  the  residue  following  the  treatment  of  wastewaters.  It  contains  valuable  agricultural 
resources, but also contaminants and pollutants that may pose risks to human health and the environment. 
Therefore, sewage sludge  spreading on agricultural land is a controversial issue, and the occurrence of this 
practice varies widely amongst EU Member States. This study aims to assess impacts on the environment and 
human  health  from  main  sludge  management  routes occurring  in  the  EU.  For  use  in  agriculture,  it  is found 
that  a  relatively  small  set  of  organic  pollutants  may  cause  significant  risks  to  both  humans  and  soil 
organisms  following  landspreading  when  present  in  concentration  levels  typically  documented  for  sewage 
sludge. These organic priority contaminants are persistent in soils and have a bioaccumulative and toxic effect 
on  humans  and  soil  organisms.  Secondly,  it  is  indicated  that  sewage  sludge  management,  other  than 
landfilling,  has  a  small  impact  on  the  overall  global  warming  potential,  and  that  the  enforcement  of  best 
sludge management practices will only limitedly offset impacts resulting from wastewater treatment. Thirdly, 
sound  management  of  sludge  could  partly  contribute  to  reducing  the  depletion  of  the  critical  raw  material 
rock  phosphate.  Also  options  other  than  landspreading  can  return  a  significant  share  of  the  phosphorus 
contained  in  sludge  to  agricultural  land  in  a  plant-available  form.  Altogether,  it  is  indicated  that  a  mix  of 
sludge management routes, adapted to the local settings and needs, may be required to maximise benefits 
and minimise adverse impacts across the different sustainability dimensions affected by sludge management 
within the EU. 

1 

 
 
Key messages  

 

The risk screening assessment shows for a (relatively small) set of organic contaminants that these 
potentially cause significant risks to both humans and soil organisms, when present in concentrations 
levels typically documented for sewage sludge. 

  A number of data gaps are identified for several contaminants that render their risk characterisation 
through modelling techniques incomplete. It can therefore not be excluded that risks potentially exist 
for further substances.  

  Humans are found to be a more vulnerable end-point than soil organisms for the priority pollutants 
as unacceptable risk levels are reached for humans at lower pollutant loads due to bioaccumulation 
within the food chain. 

  Only  incineration  at  high  temperatures  ensures  that  all  organic  priority  pollutants  are  effectively 
removed. Alternative risk mitigation measures involve setting sludge quality parameters and limiting 
sludge application rates, or a combination thereof. Sludge applications outside areas used in the food 
chain could also be further studied. 

 

 

 

 

Sewage  sludge  management  has  a  small  impact  on  the  overall  global  warming  potential,  and  the 
enforcement of best sludge management practices will only limitedly offset impacts resulting from 
wastewater treatment. The global warming assessment of sewage sludge management routes has a 
high degree of uncertainty for all pathways. With the exception of landfilling, routes (landspreading, 
anaerobic  digestion,  composting,  and  incineration)  are  not  significant  different  in  terms  of  global 
warming  potential.  Landfilling  shows  the  worst  performance,  having  at  all  times  a  net  positive 
contribution to global warming due to methane leakages. 

Supplementary electric energy (estimated at maximum 4.4 TWh per year; or 0.16% of the total net 
electricity generation in the EU) could be recovered by subjecting sludge to anaerobic digestion and 
incineration with energy recovery. 

The landspreading of untreated and stabilised sludge returns phosphorus, a critical raw material, and 
nitrogen  to  agricultural  land.  Phosphorus  can  also  be  recovered  from  sewage  sludge  mono-
incineration  ashes,  a  material  that  can  now  be  used  as  a  secondary  raw  material  in  mineral 
phosphate  fertiliser  production  processes.  Nitrogen  and  phosphorus  that  could  additionally  be 
recovered from sewage using resource efficient sludge management options are reduced compared 
to  other  nutrient  inputs  onto  agricultural  fields  (<2%  and  <6%  for  nitrogen  and  phosphorus  in 
mineral fertilisers, respectively). 

Sewage sludge has potential to contribute to climate change adaptation as higher levels of organic 
matter  help  to  retain  moisture  and  limit  runoff,  but  organic  matter  contents  in  sewage  sludge  are 
one to two orders of magnitude lower compared to other sources (manure, bio-waste).  

  Guidelines to sewage sludge management have to carefully consider a risk versus resource efficiency 
trade-off. This suggests that a mix of sludge management options, able to adapt to the local settings 
and needs, may be required to maximise benefits and minimise adverse impacts across the different 
sustainability dimensions affected by sludge management within the EU.  

 

The  study  identified  a  number  of  recommendations  for  further  work,  mostly  in  relation  to  better 
quantifying  the  concentrations  and  risks  of  organic  contaminants  present  in  sludge  as  well  as  to 
elucidate the importance of sludge relative relative to other soil inputs (e.g. atmospheric deposition) 
as drivers for soil pollution. 

2 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Executive summary 

Policy context 
Sewage sludge is the residue following the treatment of  wastewater. It mainly consists of water (>90% for 
undewatered  sludge)  and organic  matter,  which  can  contain  a  range  of  chemicals.  Some  of  the  substances 
that are found in sewage sludge can be recovered  or used as soil amendments (e.g. nutrients) while others 
may  raise  environmental  and  health  concerns.  In  the  EU,  between  6  and  9  million  tonnes  of  dry  sewage 
sludge  is  generated  annually.  Options  to  manage  this  sludge  and  derived  materials  involve  spreading  on 
agricultural land and forests, backfilling (i.e. refill an excavation with sludge), or disposal (e.g. co-incineration 
and landfilling). Some of the reuse and disposal techniques allow energy to be recovered from sewage sludge.   

The objective of this study is to consolidate the technical and scientific knowledge base on the impacts  and 
risks  of  sewage  sludge  management  on  the  protection  of  human  health,  natural  resources  and  the 
environment.  With  respect  to  pollutants,  this  study  mainly  focusses  on  organic  compounds,  thus  excluding 
metals.  A  well-developed  scientific  evidence  base  on  these  aspects  is  important  to  support  the  policy 
framework on the EU’s Sewage Sludge Directive (Council Directive 86/278/EEC)1.   

Screening risk assessment  
This assessment presents evidence to identify and prioritise organic pollutants in sludge that may pose risks 
to  soil  organisms  and  human  health  when  applied  to  agricultural  land.  The  methodology  starts  with  a 
characterisation  of  more  than  1350  chemicals  found  in  wastewaters  and  sludge.  The  long-list  of 
contaminants  includes  well-known  contaminants  that  have  been  identified  since  long  in  scientific  literature 
and  legislation  as  being  of  concern  (e.g.  polyaromatic  hydrocarbons  (PAHs),  perfluorinated  alkyl  substances 
(PFAS))  as  well  as  contaminants  of  more  emerging  concern  (e.g.  chlorinated  paraffins,  pharmaceuticals, 
personal care products, specialty industrial chemicals).   

A  risk  screening  model  is  developed  that  calculates  the  concentrations  of  numerous  contaminants  in  soil, 
surface  waters,  and  food  following  intermittent  sewage  sludge  applications  over  various  time  intervals. 
Subsequently,  human  exposure  from  food  consumption  is  estimated  using  modelled  concentrations  of 
contaminants in fish, root and leaf crops, meat, milk, and drinking water. The estimated exposures are then 
compared to predicted contaminant levels that are considered safe for soil organisms and humans. A number 
of data gaps are identified for several contaminants that render their risk characterisation through modelling 
techniques  unviable  for  many  compounds.  While  the  conclusions  of  this  work  are  based  on  our  current 
understanding  and  characterisation  of  contaminants,  it  cannot  be  excluded  that  certain  contaminants  have 
been overlooked in this work.  

The outcomes of the modelling show that a relatively small set of pollutants may cause significant risks to 
both  humans  and  soil  organisms,  when  present  in  concentrations  levels  typically  documented  for  sewage 
sludge. Polychlorinated dibenzofuran and dioxins, PAH, long-chain PFAS, short and mid-chain polychlorinated 
paraffins,  and  to  a  lesser  extent,  alkylphenols,  polychlorinated  naphthalenes  and  phthalate  acid  esters  are 
identified  as  priority  pollutants.  These  include  chemicals  that  are  intentionally  manufactured  for  household 
and industrial applications, as well as unintentionally released substances, for instance, from the combustion 
of wastes.  

Common features of these pollutants are that they:  

(i) persist and accumulate over time in the environment (mostly in soil),  
(ii) have a high potential to bioaccumulate along food webs, and  
(iii) are toxic to the environment and to humans, even at very low concentration levels.  

Most of the priority pollutants are already subject to use restrictions and release reduction provisions under 
the chemicals legislation, including the POPs2 and REACH3 Regulation. In addition to impacts from chemicals, 

1 Council Directive 86/278/EEC of 12 June 1986 on the protection of the environment, and in particular of the soil, when sewage sludge 

is used in agriculture 

2 Regulation (EU) 2019/1021 of the European Parliament and the Council of 20 June 2019 on persistent organic pollutants 
3  Regulation  (EC)  No  1907/2006  of  the  European  Parliament  and  of  the  Council  of  18  December  2006  concerning  the  Registration, 

Evaluation, Authorisation and Restriction of Chemicals (REACH), establishing a European Chemicals Agency. 

3 

 
 
 
 
  
 
 
 
 
                                           
the use of untreated and biologically treated sludge on land may cause risks and adverse impacts due to the 
presence of microplastics and antimicrobial resistant genes in the sludge.  Based on the available data, other 
substances,  including  most  pharmaceuticals  and  personal  care  products,  are  considered  of  limited  concern, 
even  at  high  application  loads  of  sewage  sludge.  The  study  shows  that  humans  are  a  more  sensitive  end-
point  than  soil  organisms  for  the  priority  pollutants  as  unacceptable  risk  levels  are  reached  for  humans  at 
lower pollutant loads. 

Sludge treatment is often proposed as a risk mitigation measure. However, commonly used techniques (e.g. 
drying, lime stabilisation, composting, anaerobic digestion) do not necessarily ensure the reduction of priority 
pollutants  to  safe  levels.  Some  pollutants,  such  as  PFAS,  are  very  resistant  to  biological  and  even  thermal 
degradation.  Only  incineration  at  high  temperatures  ensures  that  all  priority  pollutants  are  effectively 
removed.  Because  risks  are  linearly  correlated  to  contaminant  loads,  risk  mitigation  measures  that  involve 
setting  sludge  quality  parameters  and  limiting  sludge  application  rates,  or  a  combination,  could  also  be 
explored. In addition, sludge applications outside areas used in the food chain could be further studied. Such 
investigations would benefit from recent measurements of priority pollutant concentrations in different types 
of  sludges  (e.g.  tertiary  versus  secondary  sludge;  untreated  versus  treated  sludge;  sludge  originating  from 
rural versus industrial areas). This may be important to better capture the effects of recent legislative release 
reduction measures for relevant pollutants.  

Environmental and climate change impacts  
The  aim  of  this  assessment  is  to  assess  different  sewage  sludge  management  routes  in  terms  of  their 
potential  to  contribute  to  climate  change  mitigation  and  adaptation,  as  well  as  resource  efficiency. 
Selected management routes involved land spreading of untreated, lime stabilised, composted, and digested 
sludge, as well as landfilling and co-incineration followed by ash use/disposal outside agriculture. In addition, 
the  emerging  practice  of  sludge  mono-incineration  followed  by  the  re-use  of  the  ashes  to  manufacture  a 
mineral  phosphate  fertiliser  is  studied  because  of  its  potential  to  increase  the  circularity  of  phosphorus,  a 
critical raw material. The analysis considers the impacts from sludge processing and from the use- of sludge 
on land.  

The ranking the routes on their climate change mitigation performance in a universal manner across the EU is 
impossible  due  to  the  large  uncertainties  associated  with  the  technologies  applied  and  emission  variations 
across  local  geographic  contexts.  In  general,  landspreading  untreated  and  treated  sludges  leads  to  net 
negative  global  warming  impacts  because  sludge  can  partially  displace  mineral  fertiliser  and  energy 
production, in addition to increasing carbon sequestration in soils. These savings are greater than the burdens 
to  global  warming  resulting  from  sludge  processing  and  greenhouse  gases  directly  emitted  during  sludge 
processing,  storage  and  use-on-land.  Disposal  routes  that  include  sludge  incineration  result  in  estimated 
neutral  net  global  warming  impacts,  but  net  savings  or  burdens  could  be  observed  across  technology 
configurations. This also holds true for incineration ashes that are used for fertiliser production as well as for 
their  use  outside  agriculture.  Finally,  landfilling  shows  the  worst  performance,  having  at  all  times  a  net 
positive contribution to global warming due to methane leakages.  

In absolute terms, the study estimates that impacts from current sewage sludge management across the EU 
have a net positive effect on global warming (+1 million tonnes CO2-eq per year). The application of optimum 
sewage sludge management routes across the EU may result in a net removal of CO2 from the atmosphere (-
2 million tonnes CO2-eq per year), that could only to a limited extent offset the estimated upstream emissions 
from wastewater collection and treatment (25-30 million tonnes CO2-eq per year).  

When  applied  to  agricultural  land,  sewage  sludge  also  has  potential  to  contribute  to  climate  change 
adaptation as higher levels of organic matter help to retain moisture and limit runoff. The amounts of organic 
matter in sewage sludge are, however, one to two orders of magnitude lower compared to other sources, such 
as  manure  and  bio-waste.  Nonetheless,  sewage  sludge  may  be  a  valuable  organic  asset  locally  (e.g.  in  EU 
regions with a more extensive livestock production system or on soils characterised by a low organic matter 
content).   

Phosphorus  is  a  critical  raw  material,  and  its  finiteness  and  criticality  for  EU  agriculture  warrants  an 
assessment of how sewage sludge management could contribute to closing the biogeochemical phosphorus 
cycle and improving resource efficiency. Phosphorus in sewage sludge equals about 12% of the total mineral 
fertiliser inputs (8% relative to overall inputs including feed), but at present it is estimated that less than half 
of this amount ends up on agricultural land. Hence, more than 50% of the phosphorus from sewage sludge is 

4 

 
 
 
  
 
 
 
 
irreversibly  lost  after  co-incineration  and  landfilling.  The  implementation  of  innovative  techniques,  such  as 
phosphorus recovery from mono-incineration ashes, is still limited. 

It  is  indicated  that  the  climate  change  and  resource  efficiency  assessment  generally  supports  the  waste 
hierarchy that promotes recycling over recovery and disposal. However, the overall environmental impacts of 
the management routes may vary based on local  conditions, including technologies applied and agricultural 
needs for nutrients and organic matter of the land close to wastewater treatment plants.  

Conclusions  
Sludge  management  has to  consider different sustainability dimensions, including risks for the environment 
and  human  health  from  organic  and  inorganic  chemicals  and  pathogens  when  sludge  is  further  reused, 
resource  use  efficiency  and  impacts  on  climate  change  mitigation  and  adaptation.  This  study  shows  a  risk 
versus environmental trade-off across sludge management routes. Limited processing generally has a better 
environmental performance than sludge incineration and landfilling, but may not be fully effective in reducing 
pollutant loads, especially when high amounts of sludge are intensively landspread on a limited agricultural 
land area. Disposal and more intensive sludge processing options typically will not fully contribute to resource 
efficiency  and  addressing  climate  change,  but  may  reduce  environmental  and  health  risks  from  food 
consumption.  Innovative  options,  such  as  sludge  mono-incineration  followed  by  ash  acidulation  to  retain 
phosphorus  in  a  plant-available  form,  can  deliver  middle-ground  impacts.  Overall,  it  is  concluded  that  the 
application of a mix of established and innovative techniques, as a function of local settings and needs, may 
help to maximise benefits and minimise adverse impacts on the different sustainability dimensions affected 
by sludge management within the EU.   

5 

 
 
 
  
 
 
 
1  General objective and structure of the report 

The  general  objective  of  this  report  is  to  support  policy  development  on  the  Sewage  Sludge  Directive 
(86/278/EEC;  hereafter  SSD)4  by  providing  techno-scientific  evidence  on  (i)  risks  from  organic  pollutants, 
contaminants  of  emerging  concern  and  pathogens  in  sludge  applied  to  agricultural  land,  and  (ii) 
environmental  impacts  arising  from  sewage  sludge  management  in  the  EU,  including  climate  change  and 
resource  depletion.  The  report  aims  to  increase  the  techno-scientific  knowledge  base  on  those  issues  that 
have been identified in previous works and policy documents as relevant for further policy development.  

The  report  contains  six  main  sections.  Section  2  brings  forward  a  brief  introduction  to  sewage  sludge 
management  in  the  EU.  The  risk  screening  assessment  for  chemical  substances  is  developed  in  section  3 
using  a  model-based  calculation  approach.  This  aspect  is  further  complemented  by  a  qualitative  review  of 
risks from other contaminants of emerging concern, such as antimicrobial resistance genes and microplastics 
(section  4).  Section  5  assesses  the  impacts  of  the  use  of  land  of  sludge  and  treated  sludge  on  the  soil 
biogeochemical carbon (C), nitrogen (N) and phosphorus (P) cycles. The result thereof are plugged into a life 
cycle  assessment  model  that  compares  the  global  warming  potential  of  different  sludge  treatment  and 
management  options  (section  6).  The  limitations  of  our  work  and  further research  recommendation  to  take 
this work forward are provided in section 7. Finally, section 8 develops the general conclusions of this study. 
This  report  is  annexed  by  sections  9-15  that  provide  supplementary  information  on  the  methodology  and 
results of the assessment.  

4 Council Directive 86/278/EEC of 12 June 1986 on the protection of the environment, and in particular of the 
(https://eur-lex.europa.eu/legal-

agriculture 

when 

used 

in 

is 

soil, 
sewage 
content/EN/TXT/?uri=CELEX:31986L0278) 

sludge 

6 

 
 
 
 
 
                                           
2  Background on sewage sludge management in the EU 

Sludge is defined in the SSD (86/278/EEC) as: 

(i) 

residual sludge from sewage plants treating domestic or urban wastewaters and from other sewage 

plants treating wastewaters of a composition similar to domestic and urban wastewaters; 
(ii)  residual sludge from septic tanks and other similar installations for the treatment of sewage; 
(iii)  residual sludge from sewage plants other than those referred to in (i) and (ii); 

According  to  Eurostat5,  between  5.2  and  8.6  million  tonnes  of  dry  matter  of  sewage  sludge  have  been 
managed  yearly  between  2004  and  2016  in  the  EU  (Wood  E&I  GmbH,  2021)  (Figure  1).  The  Eurostat 
terminology  ‘sludge  disposal’  involves  sludge  management  options  agricultural  use,  landfill,  incineration, 
compost and other applications, and other.  

Figure 1: Eurostat data on the amounts of sewage sludge (dry matter) disposed for the period  2004  – 2016 (reprinted 
from Wood E&I GmbH, 2021).. 

For the  year 2016,  Member  States  (MS)  reporting  data  on  the  implementation  of  the  SSD indicated  a  total 
volume of about 6.7 million tonnes of sludge (dry matter). These numbers are similar to Eurostat data of the 
year  2016,  but  the  latter  data  are  incomplete  as  no  information  is  available  for  certain  MS,  such  as  Italy, 
Belgium, and Denmark. After gap filling with data from the period 2010-20115, the updated Eurostat 2016 
indicate  a  tonnage  of  about  7.5  million  of  tonnes  sludge  (dry  matter).  Sludge  management  routes  for  this 
dataset involve agricultural use (35%), incineration (31%), compost and other applications (12%), landfilling 
(12%) and other uses (10%). Main uncertainties exist related to the final end use of the categories “compost 
and other applications” and “other uses” (Anderson et al., 2021). Nonetheless, these data largely align to the 
conclusions  of  the  report  of  Wood  E&I  GmbH  (2021)  who  indicated  that  the  total  percentage  of  sewage 
sludge used in agriculture falls between around 35% and 50% of the total sewage sludge produced (roughly 
2.6 – 3.8 million tonnes (dry matter); based on a total estimated volume of 7.5 million tonnes being disposed). 
Incineration is also a  main sludge  management  route, with estimated volumes corresponding to  2.3 million 
tonnes (dry matter).  

Large differences in the proportional contribution of sewage sludge disposal routes exist among MS for the 
fate of sewage sludge (Figure 2). Countries with a high population and livestock density, and strict restrictions 
on  landfilling,  incinerate  high  proportions  of  their  sewage  sludge  (e.g.  Netherlands,  Belgium,  Germany;  82-
98%). Other Member States (e.g. Ireland, Spain; >80%) apply large amounts of the sewage sludge directly on 
land. Finally, Member States as Greece, Italy, Romania, and Croatia landfill significant amounts of sludge (28-
86%) (Figure 2).  

5 

Eurostat,  Sewage 
(http://appsso.eurostat.ec.europa.eu/nui/show.do?lang=en&dataset=env_ww_spd) 

production 

accessed 

disposal, 

sludge 

and 

on  28  September  2021 

7 

 
 
 
 
 
  
 
 
                                           
Figure 2: Relative importance of sludge management options within different EU Member States (based on Eurostat 2016 
data, with gap filling performed for some Member States based on 2010 – 2015 data). 

In addition to primary treatment (e.g. thickening, dewatering), sludge can undergo biological, chemical or heat 
treatment, long-term storage or any other appropriate process as a secondary treatment so as significantly to 
reduce its fermentability and the health hazards resulting from its use (‘treated sludge’ according to the SSD) 
(Kacprzak  et  al.,  2017).  Common  techniques  that  enable  further  use  in  agriculture  involve  lime  treatment, 
solar  and  thermal  drying,  anaerobic  digestion  and  composting  (Table  1).  In  addition,  a  mineral  phosphate 
fertiliser can be manufactured from mono-incinerated sludge after acidulation, with a chemical composition 
that is similar to a rock phosphate-derived mineral fertiliser (Kabbe, 2017; Huygens et al., 2019; Tonini et al., 
2019).  Common  sludge  disposal  options  co-incineration  and  landfilling  do  not  return  organic  matter  and/or 
nutrient to agricultural land. Finally, sludge is used at occasions for other purposes such as backfilling and use 
in forestry. Hydrothermal carbonisation and pyrolysis are other alternative routes, but minor sludge volumes 
are  currently  processed  through  these  pathways.  This  report  will  compare  and  analyse  different  sludge 
management options, with a focus on sludge management techniques that remove of biological and chemical 
pollutants present in sewage sludge. 

8 

 
 
 
 
 
 
 
 
 
 
  
 
Table  1:  Overview  of  main  secondary  treatment  (e.g.  lime  stabilisation,  composting,  anaerobic  digestion,  P-fertiliser 
production  from  mono-incineration  ash)  and  final  end  uses  of  the  resulting  materials  (e.g.  use-on-land,  landfill,  use  as 
construction material of co-incinerated ash) 

Sludge 
treatment/management 
technique 

Description of technique 

Main objectives 

stabilisation 
Lime 
(Wong  and  Selvam,  2006; 
Farzadkia and Bazrafshan, 
2014;  Teoh  and  Li,  2020; 
Anderson et al., 2021) 

Lime  treatment  is  a  sludge  stabilisation  technique 
that  involves  the  addition  of  CaO  or  Ca(OH)2  to 
sludge. The European Lime Association recommends 
addition  of  50%  -  90%  CaO  per  unit  dry  solids  for 
75 min to treat sludge at >55°C and pH > 12, or the 
addition  of  20%-40%  CaO  or  equivalent  Ca(OH)2 
per unit dry solids for 3 months.  

Composting  

(Guardabassi  et  al.,  2003; 
Uçaroğlu and Alkan, 2016; 
Anderson et al., 2021) 

digestion 
Anaerobic 
(Ruffino  et  al.,  2020; 
Anderson et al., 2021) 

P-fertiliser  production 
from mono-incineration 
ash  (Kabbe  et  al.,  2015; 
Huygens et al., 2019) 

Composting  is  an  aerobic  process  during  which 
microorganisms convert organic substrates, such as 
sewage  sludge  or  other  organic  materials,  into 
stabilized  organic  matter  with  production  of  heat. 
Different  groups  of  microorganisms  develop  and 
become predominant during the different phases of 
composting  (mesophilic  phase,  thermophilic  phase 
and  the  maturation  phase).  A  composing  process 
normally  takes  several  weeks,  with  temperatures 
that  may  range  between  45°C  and  80°C.  Several 
configurations  for  composting  exist  (e.g.  windrow 
systems,  aerated  static  pile  systems,  enclosed  (in-
vessel) systems.  

Anaerobic  digestion  is  the  bacterial  breakdown  of 
organic materials in the absence of oxygen resulting 
in  the  production  of biogas.  The  anaerobic  digester 
is  mostly  operated  at  the  mesophilic  temperature 
range  (35-40°C),  whereas  thermophilic  digestion 
involves higher temperatures (up to > 55-70°C).  

Innovative  production  processes  exist  to  transform 
the  phosphorus  present  in  sewage  sludge  into  a 
mineral P-fertiliser. The most common process is a 
two-stage  manufacturing  process  that  starts  with 
the  mono-incineration  of  sewage  sludge  at 
temperature  of  >  850°C  -  900°C,  typically  in  a 
fluidised  bed  reactor.  Afterwards,  most  processes 
acidulate  (fly)  ashes,  and  the  mixture  is  then 
potentially  purified  and/or  mixed  with  other  P-rich 
materials.  A  high  recovery  (>  80  -  98%)  of  the 
phosphorus  present  in  sewage  sludge  can  be 
achieved,  but  nitrogen  and  organic  carbon  are 
destroyed 
process. 
Alternative manufacturing processes exist based on 
thermal processing steps instead of acidulation. 

incineration 

during 

the 

 

 

 

 

 

 

 

 

 

 
 

 

 

 
 

of 

stabilisation 
Sludge 
(hygienisation and reduction 
of  biological  pathogens; 
odour nuisance reductions)  
Increased  acid  neutralising 
capacity 
receiving 
for 
agricultural soils; 
Decreased  mobility 
metals. 
stabilisation 
Sludge 
(hygienisation and reduction 
of  biological  pathogens; 
odour nuisance reductions)  
and  moisture 
Volume 
reduction; 
Improvement  of  physical 
(e.g.  aeration, 
properties 
water 
the 
receiving soil 
Partial  removal  of  certain 
non-persistent 
organic 
contaminants. 

retention)  of 

energy 

Renewable 
production, heat recovery;  
Sludge 
stabilisation 
(hygienisation and reduction 
of  biological  pathogens; 
odour nuisance reductions)  
Volume reduction; 
Partial  removal  of  certain 
non-persistent 
organic 
contaminants. 

energy 

Renewable 
production, heat recovery;  
Sourcing  of  secondary  raw 
for  P-fertiliser 
materials 
production 
Sludge volume reduction; 
Sludge  decontamination,  as 
chemical 
biological 
and 
are 
contaminants 
largely 
completely 
destroyed 
the 
process. 

or 
during 

  Microplastics removal  

Use-on-land 

Untreated  and  treated  (e.g.  composted,  digested, 
lime  stabilised)  sludges  and  P-fertilisers  derived 
from  sewage  sludge  can  be  used  on  agricultural 
land  as  a  nutrient  source  (fertiliser),  and/or  to 
improve  the  soil  environment  for  crop  growth  (soil 

 
 

Crop growth 
Increase  resource  efficiency 
and  decrease  reliance  on 
primary  raw  materials  (e.g. 
mineral fertilisers, peat). 

9 

 
 
 
 
 
Co-incineration 
(Svoboda et al., 2006) 

Landfilling 
2021) 

(Stauffer, 

improver or liming material)  

Co-incineration is a sludge disposal technique where 
sewage  sludge  is  thermally  oxidised  together  with 
other  materials  (mostly  municipal  solid  waste,  but 
possibly  also  fossil  fuels  or  minerals  for  cement 
production). The resulting fly and bottom ashes are 
either  used  in  construction  materials  or  discarded, 
resulting in the permanent removal and destruction 
the 
of  nutrients  and  organic  matter 
biogeochemical cycle. 

from 

A  landfill  is  an  engineered  pit,  in  which  layers  of 
waste  are  filled,  compacted  and  covered  for  final 
disposal.  Engineered  landfills  consist  of  a  lined 
bottom; a leachate collection and treatment system; 
groundwater  monitoring;  gas  extraction  (the  gas  is 
flared  or  used  for  energy  production)  and  a  cap 
system. 

 

 

 

Soil  restoration  and  organic 
matter recycling 

Renewable 
production, heat recovery;  
Sewage sludge disposal. 

energy 

 

 

Renewable 
production, heat recovery;  
Sewage sludge disposal. 

energy 

10 

 
 
3  Screening risk assessment for chemical pollutants in sludge 

3.1  Objectives and scope 

The objective of this section is: 

 

 

To  develop  a  methodology  that  enables  the  identification  of  relevant  chemical  pollutants  that 
are present in sewage sludge and that pose environmental or human health risks when applied 
on  agricultural  land.  Specifically,  the  methodology  will  enable  to  assess  impacts  of  sewage 
sludge  applications  on  soil  organisms  and  humans  via  the  intake  of  food  grown  on  sewage-
sludge amended soils; 
To  apply  the  methodology  to  bring  forward  evidence  to  be  able  to  identify  relevant  organic 
pollutants that are  present in sewage sludge and that pose risks related to the use  of sewage 
sludge as well as a prioritisation of those pollutants that cause most risk. 

Although the same method can be applied to assess environmental and health risks from metals, the current 
study exclusively focuses on identifying relevant organic pollutants because these are currently considered in 
the  SSD.  Metals  are  already  considered  as  relevant  pollutants  for  sludge  applied  on  agricultural  land,  and 
covered under the SSD. For relevant organic pollutants, information on baselines of soil conditions relevant to 
sludge applications will  be  presented, as well as an estimate of the removal those  pollutants may typically 
undergo during the most common sludge treatment processes. Finally, the availability of screening methods 
for  sampling  and  analysis  of  relevant  pollutants  (e.g.  international  and  national  standards,  technical 
standards) in sewage sludge is reviewed.  

The  scope  of  this  study  is  limited  to  soil  organisms  and  human  health  impacts  resulting  from  indirect 
exposure via the environment through the consumption of fish, root and leaf crops, meat, milk, drinking and 
water.  The  impacts  on  surface  water  organisms  will  not  be  considered  in  this  study  as  the  contribution  of 
relevant sludge contaminants to waters is for most substances small compared to contaminant loads that are 
present in wastewater treatment effluent, and soil organism act as the primary species impacted by use-on-
land of sludges. Also, risks for sediment organisms and ground water quality were not directly studied in this 
work.  

3.2  Methodology 

The present report provides a provisional modelling assessment as to whether selected organic contaminants 
in  sewage  sludge  could  potentially  pose  a  risk  to  soil  ecosystems  after  soil  amendment.  It  should  by  no 
means be considered an exhaustive assessment that extensively covers all substances that could possibly end 
up in sewage sludge. The selection of substances under assessment is based on a set of criteria, assumptions, 
availability of ecotoxicity data and the fate of substances in the environment.  

3.2.1  Exposure assessment tool 

The environmental or health risk of a substance is assumed to be determined by the application rate of the 
substance on agricultural land, its stability and physico-chemical properties within the atmosphere-soil-plant-
water continuum, and its (eco)toxicology that indicates the sensitivity of biota and humans to exposure.  

The  assessment  of  the  local  environmental  exposure  was  carried  out  based  on  a  tool  developed  by  the 
European  Crop  Protection  Association  (ECPA)  that  has  been  further  adapted  and  validated  by  the  JRC  (see 
section 13.1). The Local Environment Tool (LET)6 is referred to in the REACH R.16 guidance document to fine-
tune models developed by the European Union System for the Evaluation of Substances (EUSES) as these do 
not  account  for  direct  intermittent  releases  to  soil  in  a  local  assessment.  Conceptually,  a  treated  1  ha 
agricultural field with an adjacent shallow waterbody is simulated. The LET uses the calculations described in 
the REACH R.16 (2016) guidance, as well as the “Step 2” calculation approach for surface water devised by 
the  Forum  for  the  Co-ordination  of  pesticides  fate  models  and  their  use  (FOCUS,  2003).  Based  on  EUSES 
guidelines (REACH R.16), a sludge application rate to agricultural land is assumed of 5 tonnes dry weight ha-1 
yr-1.  This  assumed  value  a  realistic  high-end  sludge  application  rate  in  the  EU  (Collivignarelli  et  al.,  2019). 

6 The ECPA-LET tool is freely available at http://www.ecpa.eu/information-page/regulatory-affairs/reach. 

11 

 
 
 
 
 
 
                                           
Impacts are assessed in the short (after a single year), mid- (after 10 years of continuous applications), and 
long-term (after 100 years of continuous applications). 

To assess the impact on soil organisms, the ECPA-LET model calculates average contaminant concentrations 
in the top soil layer (20 cm depth), averaged over a 30-day period following sludge applications. The model 
departs  from  the  contaminant  application  loads,  and  takes  into  consideration  contaminant  losses  via 
volatilisation,  leaching  and  biodegradation  in  soil.  All  calculations  are  outlined  in  section  13.1.  To  assess 
impacts on soil organisms, standard tests on different trophic levels are available for the soil compartment, 
including  a  functional  test  with  soil  microorganisms  (nitrogen  transformation,  28-day;  OECD  216)  and 
ecotoxicological tests with soil dwelling invertebrates (Collembola; OECD 232), earthworm/enchytraeid; OECD 
222) and plant species (terrestrial plants; OECD 208). In practice, however, data on no-effect concentrations 
for  soil  organisms  are  hardly  ever  available  for  most  contaminants.  However,  it  can  be  assumed  that 
contaminant  uptake  by  soil  organisms  occurs  via  the  soil  and  its  pore  water,  and  that  aquatic  and  soil 
organisms  are  equally  sensitive.  Therefore,  a  predicted  no-effect  concentrations  for  soil  organisms  is 
calculated from aquatic organism toxicity data using default methods (equilibrium partitioning).   

The  daily  human  intake  resulting  from  indirect  exposure  via  the  environment  is  estimated  using  modelled 
concentrations  of  the  contaminant  in  fish,  root  and  leaf  crops,  meat,  milk,  drinking  and  water,  based  on  a 
standard diet (Figure 3). To derive human intake of fish, food crops, meat, milk and water, the  contaminant 
concentrations in these media were estimated based on average soil and surface water concentration over a 
180-day  period  after  sludge  application,  thus  accounting  for  biodegradation,  volatilisation  and  leaching  in 
soils as well as for biodegradation and water renewal in surface water.  

It is noted that these “human via the environment” calculations show a degree of conservatism as it assesses 
the impact of exclusive and continuous intake of produce from soils amended with sewage sludge at a yearly 
application rate of 5 tonnes of sewage sludge per hectare as a worst-case scenario. If one would assume that 
sewage  sludge  is  homogeneously  applied  across  all  agricultural  land  in  the  EU,  the  “average  EU  produce” 
consumed by the EU population would have been grown on soils receiving a sewage sludge application rate 
that is about 2 orders of magnitude lower. Still, it cannot be excluded that some people consume a high share 
of food products from geographic EU areas receiving higher than average sewage sludge loads; this justifies 
the use of an additional safety assessment factor. Moreover, many  data used in this screening assessment 
have  been  collected  based  on  data  extrapolation  (e.g.  equilibrium  partitioning  methods)  and  from  data 
repositories; in such case, another additional safety assessment factor to account for data quality is justified. 
Altogether, the approach is considered valid to identify the most relevant pollutants in sewage sludge.    

3.2.2  A stepwise approach 

A  two-step  approach  is  applied  for  exposure  assessment  (Figure  3).  As  the  first  step,  the  exposure  to  a 
contaminant  is  estimated  in  order  to  target  those  compounds  that  might  pose  an  environmental  or  health 
concern  based  on  conservative  assumptions.  If  the  estimated  exposure  exceeds  ecotoxicological  or 
toxicological reference values, a more accurate method of dietary exposure assessment is used; if it is below 
the reference value, no further assessment is conducted.  

Step 1 consists out of a broader screening step that models the exposure of soil organisms and humans to 
sludge-derived  contaminants, using data that  were  retrieved  using semi-automated  data collected  methods 
(Figure 3). Step 2 then involves the verification and updating of the model input data based on state-of the-
art literature, complemented with most recent data on contaminant concentrations in soils and waters (Figure 
3).  Such  “background  concentrations”  may  originate  from  sources  other  than  sewage  sludge  such  as 
atmospheric  deposition,  municipal  and  industrial  wastewater  treatment  effluents  discharged  in  surface 
waters, and other fertilising materials applied to soils.   

12 

 
 
 
 
 
 
 
Figure  3:  Applied  step-wise  approach  for  the  exposure  assessment.  Step  1  involves  a  local  assessment  based  on  the 
exclusive application of sewage sludge to agricultural soils that is mainly based on data retrieved from data repositories 
in a semi-automated manner (depectived in green). If the estimated exposure exceeds a risk characterisation ratio above 
1, a Step 2 refinement is executed where model input data is further corroborated and background concentrations of the 
respective contaminant in soils and water bodies is taken into consideration (depicted in orange). 

3.2.2.1  Step 1  

An extensive list of 1350 potential contaminants in sewage sludge was set up, based on an initial list of 1196 
contaminants  identified  in  Urban  Wastewater  Treatment  Plants  (UWWTPs).  This  initial  list  was  based  on 
regulated  substances  (and  relevant  for  wastewater),  monitoring  data  from  UWWTPs7  and  other  substances 
identified as substances of concern by experts or national authorities (e.g. persistent, mobile and toxic). This 
initial list of contaminants was further complemented with >150 additional entries that were identified from 
complementary sources, including (national) legislation on sewage sludge land application, as well as techno-
scientific  publications,  reports  and  public  databases  that  focus  on  contaminants  of  emerging  concern  in 
sewage sludge (Kinney et al., 2006; Smith, 2009; Clarke and Smith, 2011; Danish Ministry of the Environment, 
2012; Mailler et al., 2014; Petrie et al., 2015; Deleebeeck et al., 2021; Rigby et al., 2021). 

Available physico-chemical and (eco)toxicological properties required as input parameters were retrieved from 
data  repositories.  When  available,  measured  data  were  prioritised  over  estimated  data  using  e.g.  QSAR 
software. To that purpose, in addition to the same literature references and datasets used for setting up the 
initial list, a total of 8 extra databases were used to extract relevant data on properties and toxicity data of 
the contaminants (when available): 

COMPTOX (US-EPA) database; 

- 
-  Norman EMPODAT; 
- 
ECOTOC; 
- 
Envirotox; 
- 
IRIS (US-EPA); and 
-  OpenFOODTOX (EFSA).  

Efforts were undertaken to extract the following parameters: 

- 
- 
- 

contaminant concentration in sludge before and after treatment; 
n-octanol/water partition coefficient (Kow); 
organic carbon-water partition coefficient for organic compounds (Koc); 

7 Based on data from the Helsinki Commission (HELCOM), Dutch monitoring on micro-pollutants in influent 
and effluent from wastewater treatment plants (WATSON) and Helmholtz Centre for Environmental Research 
(UFZ) 

13 

 
 
 
 
 
                                           
solubility in water; 
vapour pressure; 

- 
- 
-  molar weight; 
- 
- 
- 

biodegradation half-life; 
Predicted No-Effect Concentrations (PNEC) for surface waters; and 
Human toxicity data (Reference Dose, Tolerable Daily Intake, Acceptable Daily Intake, etc.). 

The PNECterrestrial (predicted no-effect concentrations for the terrestrial soil compartment) were estimated from 
the well-documented PNECsurface water values using the equilibrium partitioning method.8  

Preliminary data analysis indicated that data extraction was generally successful for most parameters, with 
the exception of safe limit values for human consumption and contaminant concentration values in sludge. To 
address these issues, safe limit values for human consumption were retrieved on a case-by-case search, with 
a  focus  on  (i)  contaminants  that  had  been  identified  in  the  techno-scientific  literature  and  by  national 
competent authorities (in legislation) as relevant, and (ii) contaminants for which total daily intake by humans 
was highest (approx. above 0.01 mg day-1). The derivation of safe limit values for contaminants based on a 
detailed review of toxicological data and studies is beyond of the scope of this study. Moreover, for many of 
the  long-listed  contaminants,  it  may  simply  be  impossible  to  develop  safe  limit  values  for  human 
consumption  based  on  the  current  state  of  toxicological  knowledge  and  studies  available.  Missing 
contaminant concentration values in sludge were estimated from their concentrations in wastewaters and the 
application of sludge-water partitioning coefficients (cfr. SimpleTreat modelling). In sum, a hybrid approach is 
applied that enables to focus on the “usual suspects” that have been identified in previous work as being of 
possible concern, and contaminants of unknown concern within landspreaded sewage sludge that may have 
been overlooked in previous studies.  

Risk  characterisation  ratios  (RCR)  were  then  calculated  after  a  period  of  10  years  of  continuous  sludge 
applications  on  agricultural  land.  This  mid-term  period  enables  to  consider  the  possible  accumulation  of 
persistent compounds in soil. 

RCRsoil 10 years = PECsoilsoil 10 years /PNECsoil 

Risk  Characterisation  Ratio  for  the  soil  compartment,  estimated  after  a 

With:  
RCRsoil 10 years = 
period of 10 years of continuous sludge applications on agricultural land (-);  
Predicted  Environmental  Concentrations  for  the  contaminant  (mg  kg-1)  in 
PECsoil 10 years = 
the soil compartment, estimated after a period of 10 years of continuous sludge applications on agricultural 
land;  
PNECsoil = 
terrestrial soil compartment. 

Predicted  No-Effect  Concentrations  for  a  contaminant  (mg  kg-1)  in  the 

RCRhuman 10 years = (Total Daily Intake 10 years / Body Weight) / SLHC 

With: 
RCRhuman 10 years =    
years of continuous sludge applications on agricultural land (-);  
Total Daily Intake10 years =   
a period of 10 years of continuous sludge applications on agricultural land (-);  
Body Weight = 
SLHC =   

Default value, 70 kg  
Safe Limit for Human Consumption (mg kg-1 body way day-1) 

Daily contaminant intake from food and water (mg day-1), estimated after 

Risk Characterisation Ratio for humans (-) estimated after a period of 10 

Risk  characterisation  ratios  above  1  indicate  the  presence  of  a  potential  concern,  after  which  data  for 
identified  contaminants  are  verified  and  potentially  updated  based  on  a  manual  literature  search  in  Step  2 
(see section 3.2.2.2). 

8 PNECterrestrial = Ksoil-water /RHOsoil x PNECsurface  water x 1000; with PNECterrestrial = predicted no-effect concentrations 
in  soil  [mg  kg-1];  RHOsoil  =  bulk  density  of  wet  soil  [1700  kg  m-3];  PNECsurface  water  =  predicted  no  effect 
concentration in water [mg L-1] 

14 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
  
 
                                           
The default model (section 13.1) uses Kow to assess the distribution of the contaminant in the environment 
and  the  food  chain.  For  fish,  root  crops,  leaf  crops,  meat  and  milk,  EUSES  estimates  the  concentrations  in 
these food products using methods that rely on log Kow as equivalent measured accumulation factors are not 
straightforwardly  accessible  or  existent  for  many  substances.  For  non-ionisable  organic  contaminants  that 
accumulate  primarily  in  fat  tissue,  these  assumptions  are  generally  accepted  as  valid.  Instead,  acids  and 
bases dissolve in water and, because they increase the concentration of either protons or hydroxide ions, they 
suppress water self-ionization. With the possible exception of bases, these compounds are mostly partitioned 
to  the  water  phase,  and  show  generally  a  lower  potential  to  bioaccumulate  in  fish,  soil  fauna  and  plant 
biomass. For such substances, log Kow is a conservative estimate of the lipid partitioning because the overall 
partitioning for all of its species (neutral + ionic) may be considerably less when the compound’s potential to 
ionise is taken into account (ECOTOC, 2013). This implies that our step 1 model will overestimate the human 
intake of ionisable substances from food crops, meat and dairy.  

3.2.2.2  Step 2 

Starting  from  Step  1  results,  the  Step  2  analysis  verifies  and  updates  model  input  data  using  a  targeted 
literature search for compounds that were considered as posing a potential risk to human health. In addition, 
data  were  collected  on  concentrations  in  soils  and  surface  water  under  conditions  without  sewage  sludge 
applications on land (“background concentrations”), where possible. This enables an  initial assessment of the 
relative  contribution  of  sewage  sludge  to  the  contamination  issue  that  is likely  the  result  of  pollution  from 
multiple sources (e.g. atmospheric deposition, industrial and municipal wastewater treatment effluents, other 
fertilising materials). |n case such analysis confirms the importance of the respective contaminant present in 
sewage  sludge  as  contributing  to  the  risk  for  human  health, a  further  assessment  of  the  impact  of  sludge 
processing as well as the availability of standardised measurement methods is executed.  

3.3  Human health assessment  

3.3.1  Step 1 results 

3.3.1.1  Data comprehensiveness 

RCRhuman 10 years could be estimated for a total of 173 contaminants. For 619 additional contaminants for which 
sewage sludge concentrations could be retrieved, no RCRhuman 10 years could be calculated, mostly because of 
the absence of a Safe Limit for Human Consumption (SLHC). Since targeted efforts  were undertaken  to list 
SLHC  when  daily  human  intake  was  above  0.01  mg  day-1  (see  section  3.2.2.1),  these  substances  should, 
however,  be  highly  toxic  to  humans  (SLHC  <  1.4E-04  mg  kg-1  body  weight  day-1)  to  be  of  human  health 
concern. Therefore, a likelihood exists that these highly toxic substances have already been identified as being 
of concern, and its SLHC is already listed in the data repositories consulted.  

The  173  entry  list  of  organic  contaminants  assessed  for  human  health  risks  belong  to  different  substance 
categories that have been identified in scientific literature as of possible environmental and/or health concern 
(Kinney et al., 2006; Smith, 2009; Clarke and Smith, 2011; Danish Ministry of the Environment, 2012; Mailler 
et  al.,  2014;  Petrie  et  al.,  2015;  Deleebeeck  et  al.,  2021;  Rigby  et  al.,  2021).  Specifically,  the  list  covers 
substances  that  classify  as 
(long-chain  PFAS),  polyaromatic 
hydrocarbons  (PAH),  polychlorinated  dibenzo-p-dioxin  and  furans  (PCDD/Fs)  and  polychlorinated  biphenyls 
retardants,  alkylphenols, 
(PCBs),  polybrominated  diphenyl  ethers 
polychlorinated  alkanes/paraffins,  polychlorinated  naphthalenes,  organotin  compounds,  chlorobenzenes, 
pesticides  and  biocides,  synthetic  musks,  phthalate  acid  esters,  polydimethylsiloxanes,  antibiotics  and  other 
drugs, steroids, surfactants, quaternary ammonium compounds, etc. 

long-chain  perfluoroalkyl  susbtances 

(PBDEs),  organophosphate  flame 

3.3.1.2  Prioritised substances for step 2 assessments 

RCRhuman 10 years greater than 1 were detected for different compounds belonging to a wide variety of chemical 
and use classes in the step 1 analysis of the assessment (Table 2). 

15 

 
 
 
 
 
 
 
Table 2: Chemical substances identified in the Step 1 screening risk assessment as having a RCRhuman 10 years greater than 1, 
the 10 classes above the horizontal black line will be taken forward for a more detailed analysis. 

Substance name 

Benzo[a]pyrene and other polyaromatic hydrocarbons (PAH) 

class 

PAH 

2,3,7,8-TCDD  and  other  polychlorinated  dibenzo-p-dioxins  (PCDDs)  and  furans 
(PCDFs), and dioxin-like polychlorinated biphenyls (dl-PCBs) 

PCDD/F + dl-PCBs 

PFOA, PFOS and other long-chain PFAS 

Nonylphenol and octylphenol, their ethoxylates. 

Short- and mid-chain parrafins  

Tributyltin, dibutyltin 

Di(2-ethylhexyl)phthalate (DEHP) 

1,2,3,4,5,6,7-HpCN (PCN-73) 

Tris(2-ethylhexyl)  phosphate 
retardants 

long-chain PFAS 

Alkylphenols 

Polychlorinated alkanes 

Organotin compounds 

Phthalate acid esters 

Polychlorinated naphthalenes 

(TEHP)  and  other  organophosphate  flame 

Organophosphate compounds 

Decamethylcyclopentasiloxane (D5) and other polydimethylsiloxanes 

Polydimethylsiloxanes 

Aldrin, dieldrin, heptachlor, DDT, and other organochlorine pesticides (e.g. 

Organochlorine pesticides 

3,3',4,4',5,5'-hexabromobifenyl (PBB-153) 

Bromobiphenyls 

4,4',4''-(1-Methyl-1-propanyl-3-ylidene)tris 
phenol 

2-(1,1-dimethylethyl)-5-methyl-

Phenolic compounds 

With  a  view  to  prioritise  efforts,  it  was  decided  to  take  10  classes  forward  in  the  assessment  for  step  2 
analysis  (indicated  in  bold  in  above  horizontal  line  in  Table  2).  Relevant  contaminants  for  each  class  have 
been  selected  based  on  occurrence  data  in  sewage  sludge,  relevance  for  human  health,  and  availability  of 
toxicological and physico-chemical data to perform the risk modelling.  

3.3.1.3  Substances that are not taken forward in the assessment 

In  spite  of  their  estimated  RCRhuman  10  years  >  1  during  step  1,  organochlorine  pesticides,  bromobiphenyls and 
4,4',4''-(1-Methyl-1-propanyl-3-ylidene)tris 2-(1,1-dimethylethyl)-5-methyl-phenol were not taken forward to 
step  2.  The  reasons  involve  relate  to  a  prioritisation  of  the  available  resources  for  this  study,  as  well  as 
technical  reasons.  Organochlorine  pesticides  have  been  phased  out  since  long  the  EU,  and  the  available 
dataset on sludge concentrations lacks data of recent measurements. For polybrominated biphenyls (PBBs), 
the EFSA CONTAM Panel concluded that the risk to the European population from exposure to PBBs through 
the  diet  is  of  no  concern  (EFSA  Panel  on  Contaminants in  the  Food  Chain,  2010).  Since  PBBs are  no  longer 
produced  or  used  in  Europe  and  taking  into  account  low  and  declining  environmental  concentrations,  the 
CONTAM Panel concluded that PBBs are a low priority for further research or monitoring efforts  (EFSA Panel 
on Contaminants in the Food Chain, 2010). For phenolic compounds, such as 4,4',4''-(1-Methyl-1-propanyl-3-
ylidene)tris 2-(1,1-dimethylethyl)-5-methyl-phenol, no measured concentration data in sewage sludges could 
be collected, limiting possibilities for a more in-depth step 2 assessment. 

Many substances could not be assessed because no information on safe limit values for human consumption 
could  be  retrieved  within  the  limitations  and  scope  of  this  work  (see  section  3.3.1.1).  Hence,  RCRhuman  10  years 
could  not  be  calculated  for  compounds  that  are  associated  to  high  daily  intakes  by  humans,  including 
amongst others tetrabutyl ethylidenebisphenol (AO22E46), 3,5-Bis(1,1-dimethylethyl)-4-hydroxy-, 2,4-bis(1,1-

16 

 
 
 
 
 
  
 
dimethylethyl)phenyl ester benzoic acid, traseolide, N-methyldodecylamine, tris(4-tert-butylphenyl) phosphate, 
4,4'-Thiobis(6-tert-butyl-m-cresol), and many sterols (e.g. cholesterol, campesterol, stigmasterol).  

Compounds  that  could  be  assessed  and  were  associated  to  a  RCRhuman  10  years  lower  than  1  were  not  taken 
forward to the step 2 assessment. The results of compounds having an RCRhuman  10  years in between 0.1 and 1 
are presented in Figure 4. These compounds encompass a large number of pharmaceuticals and personal care 
products  (PCPPs),  including  three  different  synthetic  musks  and  pharmaceuticals  such  as  miconazole  and 
atorvastatin (Figure 4). It is reiterated that the data used in this assessment originates from data repositories, 
and  has  not  been  verified  by  JRC  on  a  case-by-case  basis,  introducing  additional  uncertainties  to  the 
outcomes presented (see section 3.2.2.1 on methodology).  

Figure 4: Contaminants present in sewage sludge that showed a RCRhuman  10  years ratio in between 0.1 and 1 (model input 
values applied to derive the values presented as Supplementary Information (Table 9)).  

In  addition,  results  are  presented  for  compounds  selected  on  an  ad-hoc  basis  that  belong  to  contaminant 
classes that  have  been  referred  in  certain  scientific  publications  and  by  particular  stakeholders  as  being  of 
concern  (Figure  5).  These  involve  for  instance  quaternary  ammonium  compounds  (benzalkonium  chloride), 
pesticides  (glyphosate),  oestrogens  (17-estradiol),  and  common  personal  care  products  (triclocarban),  and 
pharmaceuticals  (e.g.  ibuprofen,  diclofenacy,  acetaminophen)  and  antimicrobial  substances  (e.g.  ofloxacin) 
found in sewage sludge (Figure 5). It is reiterated that even though the information of specific contaminants 
provides  a  preliminary  indication  for  a  wider  class  of  substances,  contaminants  should  be  evaluated  on  a 
case-by-case  basis  as  even  within  the  same  class  of  substances  variations  in  physico-chemical  and 
toxicological properties may exist.    

17 

 
 
 
 
 
 
 
Figure 5: RCRhuman  10  years values for ad-hoc selected contaminants, identified by some stakeholders as being of potential 
concern  when  present  in  sewage  sludge  (model  input  values  applied  to  derive  the  values  presented  as  Supplementary 
Information (Table 9) (PCPP: Pharmaceuticals and Compounds and Personal Care.   

The main reasons for the low RCRhuman 10 years for these contaminants is that most of them show either (i) a low 
concentrations in sewage sludge (usually below 1 mg kg-1 dry matter), (ii) a low potential to adsorb to the soil 
matrix and to bioaccumulate in the trophic chain, and (iii) high degradation rates in the (soil) environment.  

3.3.2  Step 2 results  

3.3.2.1  Identification and characterisation of pollutants of concern 

The results of the Step 2 analysis has been performed for 10 different priority organic  contaminant classes, 
encompassing 29 priority substances in total. Full results for all contaminants, as well as input data applied 
for the modelling, are presented in section 9.  

The  refined  assessment  indicated  that  relevant  substances  classified  as  PAH,  PCDD/F+dl-PCB,  long-chain 
PFAS,  alkylphenols,  polychlorinated  alkanes  (short-  and  mid-chain  chlorinated  paraffins;  SCCPs/MCCPs), 
polychlorinated naphthalenes (PCNs), and phthalate acid esters were associated to an RCR human 10 years above 1 
(Figure 6). For the other contaminants that were taken forward, the refined analysis indicated that RCRhuman 10 
years  for  representative  compounds  of  polybrominated  diphenyl  ethers  (PBDEs),  hexabromocyclododecane 
(HBCDD), organophosphate compounds, organotin compounds, and polydimethylsiloxanes were smaller than 1 
(Figure 6).  

For many priority pollutants, data on representative9 present-day concentrations in soils and waters could be 
retrieved (“background concentrations”) that add further up to the RCRhuman. This holds particularly true for for 
long-chain  PFAS,  PCDD/F  +  dl-PCBs,  and  PAH,  where  high  background  concentrations  in  soils  have  been 
observed (Figure 6).  

The  pollutants  that  cause  human  health  risks  when  present  in  sewage  sludge  include  both  unintentionally 
produced substances (e.g. resulting from combustion and incineration plants) such as PAH, PCDD/F and PCNs 
as  well  as  intentionally  produced  substances  that  end  up  in  sewage  sludge  (long-chain  PFAS,  alkylphenols, 
phthalate  acid  esters,  and  SCCPS/MCCPs).  With  the  exception  of  MCCPs,  the  production  and  use  of  these 
pollutants is banned and/or restricted (release reduction provisions) to a variable degree under the POPs10 and 

9  It  is  recognised  that  background  concentrations  in  EU  soils  may  vary  widely  depending  on  a  manifold  of 
factors, including the presence of industrial nearby sites. Hence, any outcomes based on these data should 
be  interpreted  with  the  necessary  degree  of  caution.  Moreover,  for  many  compounds  no  representative 
environmental background data could be collected. 

10 REGULATION (EU) 2019/1021 OF THE EUROPEAN PARLIAMENT AND OF THE COUNCIL of 20 June 2019 
 on 
content/EN/TXT/PDF/?uri=CELEX:32019R1021&rid=3) 

persistent 

pollutants 

(https://eur-lex.europa.eu/legal-

organic 

18 

 
 
 
 
 
 
 
 
                                           
 
REACH11  Regulation.  For  MCCPs,  the  procedure  for  a  restriction  is  ongoing.  Nonetheless,  pollutants  may  be 
restricted to a  variable degree for which  continued releases to  sewage sludge could  take place. In addition, 
some pollutants have been phased out recently, and given their long life span, releases to sewage sludge may 
therefore continue to occur during the use or end-of-life phase of articles that contain these pollutants.  

Common  characteristics across the  pollutants of  most  concern are their potential to bioaccumulate in lipids 
(correlated to their octanol-water partitioning coefficient Kow), their affinity for adsorption to the soil matrix 
(correlated  to  their  soil-water  partition  coefficient  Koc;  with  the  exception  of  long-chain  PFAS),  their  low 
biodegradation potential in soils, and their high toxicity for humans (see section 13.2). Compounds that share 
these characteristics and end up in sewage sludge are anyway potential hazards for human health.  

11 REGULATION (EC) No 1907/2006 OF THE EUROPEAN PARLIAMENT AND OF THE COUNCIL 
of  18  December  2006  concerning  the  Registration,  Evaluation,  Authorisation  and  Restriction  of  Chemicals 
(REACH) (https://eur-lex.europa.eu/legal-content/en/TXT/HTML/?uri=CELEX:02006R1907-20210215) 

19 

 
 
 
                                                                                                                                    
 
(see next page for Figure caption) 

20 

 
 
 
Figure 6: RCRhuman values (logarithmic scale) for contaminants that were evaluated in step 2 of the assessment (blue bars 
indicate RCRhuman estimated following the exclusive application of sewage sludge as a sole contamination source; the end 
of  the  red  bar  indicates  the  RCRhuman  values  when  -  in  addition  to  sewage  sludge  applications  -  background 
concentrations  of  the  respective  contaminants  from  other  sources  (e.g.  atmospheric  deposition)  have  been  taken  into 
consideration;  when  certain  contaminants  are  associated  to  a  group  safe  limit  value  for  human  consumption,  these 
compound  are  represented  jointly;  ∑PCN:  sum  of  naphthalene  congeners  66/67  (mixture  of  1,2,3,4,6,7-HxCN  and 
1,2,3,5,6,7-HxCN)  and  73  (1,2,3,4,5,6,7-HpCN).;  ∑phthalate  acid  esters:  bis(2-ethylhexyl)phthalate  (DEHP),  and  di-
isononylphthalate  (DINP);  ∑organotin:  dibutyltins  (DBT),  tributyltins  (TBT),  and  triphenyltins  (TPT),  ∑SCCPs:  sum  of  short-
chain chlorinated paraffins; ∑MCCPs: sum of mid-chain chlorinated paraffins; BDE-209: decabromodiphenyl ether; BDE-47: 
2,2',4,4'-Tetrabromodiphenyl  ether;  BDE-99:  2,2',4,4',5-Pentabromodiphenyl  ether;  HBCDD:  hexabromocyclododecane); 
TEHP:  tris(2-ethylhexyl)  phosphate,  EHDPP:  2-ethylhexyl  diphenyl  phosphate;  TCPP:  tris(1-chloro-2-propyl)  phosphate 
∑PCDD/F + dl-PCBS: Polychlorinated dibenzo-p-dioxin and furans (PCDD/Fs) and dioxin-like polychlorinated biphenyls (dl-
PCBs), with values presented for 2,3,7,8-TCDD used as a reference compound); ∑PAH: sum  of benzo[a]pyrene, chrysene, 
benz[a]anthracene and benzo[b]fluoranthene; ∑PFAS: sum of perfluorooctane sulfonic acid (PFOS), perfluorooctanoic acid 
(PFOA), Perfluorohexane sulfonic acid (PFHxS), and perfluorononanoic acid (PFNA); see section 4 and 13.2 for model input 
data values). 

Risk assessment models that estimate the daily human intake of contaminants consider drinking water, fish, 
crops, meat and dairy as sources. Contaminant concentrations in the water bodies are the driver for fish and 
drinking  water,  whereas  contaminant  concentrations  in  soils  determine  the  contaminant  intake  from  crops, 
meat,  and  dairy.  Therefore,  assessing  the  relative  contribution  of  drinking  water,  fish,  and  crops/meat/dairy 
sheds further light on the mechanisms that give rise to human health risks.  

3.3.2.2  Contribution of food sources to human health risks 

It  was  indicated  that  for  most  compounds  (∑PAH,  ∑PCDD/F  +  PCB,  4-octylphenol,  ∑MCCPs,  ∑phthalate  acid 
esters,  ∑PCN),  the  intake  of  food  grown  on  agricultural  land  was  the  main  source  (Figure  7).  This  was, 
however, this is not the case for long-chain PFAS considered in this study. For these, fish intake was the main 
contributor  (76%)  to  the  observed  risk  (Figure  7).  Hence,  for  the  long-chain  PFAS,  the  model  calculations 
indicate  that  their  concentrations  in  water  bodies  appear  to  be  a  principal  driver  to  the  observed  human 
health  risk.  This  is  remarkable  since  this  model  only  considers  runoff,  erosion,  and  drainage  from  sewage 
sludge amended soils as inputs to water bodies; other inputs (e.g.  wastewater treatment plant effluents) are 
not considered in these results presented. PFAS ions show a high affinity for the water phase and most PFAS, 
including the short-chain PFAS, are partitioned to the effluent at wastewater treatment plants (Arvaniti et al., 
2014;  Brendel  et  al.,  2018).  It  should  be  stressed  that,  while  threshold  concentrations  for  PFAS  in  aquatic 
ecosystems and drinking water could be identified, we could not retrieve any SLHC for short-chain PFAS (e.g. 
perfluoroheptanoic  acid  and  perfluorobutanoic  acid).  Human  health  concerns  related  to  short-chain  PFAS  in 
sludge are smaller than for long-chain PFAS because of their reduced adsorption potential to sludges, reduced 
bioaccumulation potential and ecotoxicity (Brendel et al., 2018). As a matter of fact, short-chain PFAS will be 
partitioned  preferentially  towards  the  effluent  phase  at  wastewater  treatment  plants,  and  the  presently 
observed  low  concentrations  of  short-chain  PFAS  in  sludges  would  only  result  in  limited  short-chain  PFAS 
contents  in  crops,  meats,  and  milk  according  to  our  model  calculations.  Any  short-chain  PFAS  in  soil-grown 
food is likely resulting from the biodegradation of long-chain PFAS that were present in sludges  (Brendel et 
al., 2018). 

Therefore, it is likely that PFAS losses to the environment via effluents are the main contributor to the total 
human health risks. PFAS in sludge may further enhance risks, but a detailed source contribution analysis that 
considers also wastewater treatment effluents is critical to develop effective mitigation strategies that tackle 
the root of the contamination issue.  

21 

 
 
 
 
 
 
 
 
 
 
Figure  7:  Estimation  of  the  relative  contribution  of  fish  (blue),  crop/meat/dairy  (orange)  and  drinking  water 
(grey)  to  the  total  human  intake  of  selected  contaminants  resulting  from  the  exclusive  assessment  of 
contaminants present in sewage sludge (“no background modelling scenario”) (from inner to outer ring: ∑PFAS, 
∑PAH, ∑PCDD/F + PCB, 4-octylphenol, ∑MCCPs, ∑phthalate acid esters, ∑PCN; for full abbreviations: see  Figure 
6).  

At  present,  different  EU  initiatives  are  focusing  on  limiting  PFAS  pollution  to  the  environment  and  water 
bodies. A phased restriction on a broader subset of around 200 linear and branched perfluorocarboxylic acids 
(PFCAs) substances, a PFAS sub-group, containing 9-14 carbon atoms, their salts and related substances, has 
been  adopted  in  August  2021  (Regulation  (EU)  2021/1297  amending  Annex  XVII  to  Regulation  (EC)  No 
1907/2006). The latter Regulation limits C9-C14 PFCAs in substances and mixtures to concentrations below 
0.025  mg  kg-1.  Restrictions  will  begin  to  take  affect  as  of  February  2023  under  Annex  XVII  of  REACH. 
Regulation  (EU)  2019/102  on  persistent  organic  contaminants  includes  prohibitions  for  the  manufacturing, 
placing on the market and use of intentionally produced substances. For PFAS, the prohibitions also apply to 
substances, mixtures and articles that have PFAS as an unintentional trace contaminant. In addition, the 2019 
Fitness Check of EU Water Law, which covered the Water Framework Directive together with the Directive  on 
Environmental Quality Standards, the Ground Water Directive and the Floods Directive, confirmed the need to 
review  the  lists  in  the  light  of  scientific  developments.  The  fitness  check  concluded  that,  in  relation  to 
chemical  pollution,  the  legislation  focuses  on  some  less  relevant  older  contaminants  while  not  sufficiently 
addressing a number of contaminants of emerging concern, including PFAS. The recast of the Drinking Water 
Directive that entered into force on January 2021 includes a limit of 0.5 µg/l for all PFAS. This is in line with a 
grouping  approach  for  all  PFAS.  Finally,  the  new  European  Chemicals  Strategy  has  announced  the  EU’s 
ambitious plans to ban all non-essential uses of PFAS. 

3.3.3 

Impact of sludge treatments  

A detailed overview of the impact of biological (anaerobic digestion and composting) and thermal oxidation 
(incineration) is given for all relevant  pollutants in section 13.3. Other sludge processing techniques such as 
lime  stabilisation,  drying  and  dewatering  are  not  projected  to  have  a  main  impact  on  chemical  pollutants 
present  in  sludge,  and  were  therefore  not  evaluated.  Finally,  thermal  processing  techniques  other  than 
incineration (e.g. pyrolysis, gasification, hydrothermal carbonisation) have not been considered due to a lack of 
a well-developed knowledge and information database related to the removal of relevant pollutants. 

In  general  terms,  it  is  indicated  that  biological  treatment  is  unable  to  cause  significant  removals  for  some 
pollutants that cause most risk for human health (e.g. PCDD/F, long-chain PFAS). For others priority pollutants 
(e.g.  PAH,  alkylphenols),  biological  treatment  has  some  potential  to  decrease  pollutant  loads,  but  removal 
efficiencies are non-consistent in literature and still insufficient to decrease concentrations to below values of 

22 

fishcrop/meat/dairydrinking water∑PFAS  (10 yr)∑PAH  (10 yr)4-octylphenol (10 yr)∑PCN  (10 yr) 
 
 
 
 
 
concern. Incineration, on the other hand, is an effective treatment options that will remove the overall share 
of  the  organic  pollutants  present  in  the  sewage  sludge.  However,  in  order  to  completely  destroy  the 
thermoresistant PFAS substances, good operational conditions and minimum temperatures in the range 1000 
- 1100°C are required (Winchell et al., 2021). In addition, incineration has to be executed in line with modern 
industrial  standards  in  the  EU  to  avoid  ashes  becoming  contaminated  with  e.g.  PAH  and  PCDD/F  generated 
during the incineration process. 

3.3.4  Prioritisation of pollutants 

is  projected  that  PAH,  PCDD/F+dl-PCB, 

It 
long-chain  PFAS,  alkylphenols,  polychlorinated  alkanes 
(SCCPs/MCCPs), polychlorinated naphthalenes (PCNs), and phthalate acid esters are present in sewage sludges 
at  levels  that  may  induce  human  health  risks,  and  therefore  these  compounds  may  cause  most  risks  to 
human health.  Even if a less conservative approach were to be applied that assumes  lower pollutant loads 
and  a  more  regional  distribution  of  the  available  sewage  sludge  produced  in  the  EU  (see  notes  in  section 
3.2.1),  PAH,  PCDD/F+dl-PCB,  long-chain  PFAS,  and  SCCPs/MCCPs  will  still  have  risk  characterisation  ratios 
above  1.  This  suggest  that  the  presence  of  these  pollutants  in  sewage  sludge  currently  causes  significant 
human  health  risks  and  should  receive  absolute  priority  in  view  of  risk  mitigation.  Particularly  relevant 
compounds  are  MCCPs  since  the  use  of  these  intentionally  produced  substances  in  the  EU  is  not  (yet) 
restricted. At the same time, it is remarked that sewage sludge is not the sole source of soil contamination 
and  that  a  more  in-depth  source  contribution  analysis  is  required  to  develop  effective  risk  mitigation 
strategies that tackle the core drivers of pollution.  

Other  persistent  pollutants,  especially  these  for  which  RCRhuman  ratios  between  0.1  and  1.0  such  as 
organophosphate and organotin compounds, seem to be of a lower concern, but additional peer-review and 
verification  by  other  stakeholders/experts  in  the  field  of  risk  assessment  may  further  reinforce  these 
conclusions.  

The  conclusions  of  this  work  align  to  recent  results  from  Deleebeeck  et  al.  (2021)  that  assessed  risk  three 
different  organic  compounds  present  in  fertilising  materials.  It  was  indicated  that  PFAS  and  PCDD/Fs  are 
priority pollutants that may induce human health risks, even when fertilising materials are considered the sole 
source  of  environmental  contamination.  Similar  to  our  results,  diclofenac  -  the  model  pharmaceutical 
compound used in Deleebeeck et al. (2021) - was associated to a low risk characterisation ratio in that study. 

3.4  Assessment for soil organisms 

3.4.1  Results 

RCRsoil  10  years  was  calculated  for  715  contaminants  that  cover  susbtances  across  a  very  broad  spectrum  of 
chemicals. Nonetheless, for about 80 additional substances for which sewage sludge concentrations could be 
retrieved, no RCRsoil 10 years could be calculated. In addition, the assessment is incomplete because data on PNEC 
for  soil  organisms  is  only  limitedly  available  and  mostly  estimated  based  on  extrapolation  of  results  for 
aquatic  organisms.  Hence,  whereas  this  assessment  provides  insights  on  estimated  risks  to  soil  organisms, 
the  results  should  be  interpreted  with  the  necessary  degree  of  caution  and  it  is  possible  that  certain 
substances that may be of concern to soil organisms have not been identified in this assessment. 

RCRsoil  10  years  were  above  1  for about  30  contaminants  (Figure  8;  Figure  9).  It  is observed  that  many  of  the 
contaminants  that  had  been  identified  as  being  a  concern  for  human  health  (taken  forward  for  Step  2 
analysis), showed RCRsoil  10  years > 1. Specifically, these involve PAH (e.g. coronene, dibenzo[a,h]perylene), long-
chain  PFAS  (e.g.  PFOA,  PFOS),  PCDD/F  (e.g.  2,3,7,8-TCDD),  alkylphenols  (4-Nonylphenol  monoethoxylate), 
short-  and  mid-chain  paraffins,  as  well  as  organochlorine  and  organophosphate  pesticides  (dieldrin, 
heptachlor,  p-DDT,  ethyl  azinphos).  Organochlorine  and  organophosphate  pesticides  have  been  phased  out 
since long the EU and the available dataset on sludge concentrations lacks data of recent measurements. The 
data  indicate  that  RCRsoil  ratios  for  these  compounds  increase  as  a  function  of  time  following  continuous 
applications of sewage sludge on agricultural land (Figure 8). The risks after a few years of  sewage sludge 
application are minimal, but gradually increase over time to significant levels in the mid- and long-term. This 
observations points towards the urgency to minimise the inputs of these persistent  contaminants in the soil 
so as to ensure soil quality and continued ecosystem functioning in the long-term.     

23 

 
 
 
 
 
 
 
Figure  8:  RCRsoil  estimated  after  1,  10,  and  100  years  of  continuous  sewage  sludge  applications  for  contaminants 
belonging  to  classes  that  had  been  identified  as  being  of  concern  to  human  health  (SCCP:  short-chain  chlorinated 
paraffins,  MCCP:  mid-chain  chlorinated  paraffins;  model  input  values  applied  to  derive  the  values  presented  as 
Supplementary Information (Table 11)). 

In  addition,  the  compounds  represented  in  Figure  9  were  identified  as  having  a  RCRsoil  10  years  above  1.  Most 
compounds included in the list can be classified as pharmaceuticals and personal care products. In addition, 
plant sterols, a quaternary ammonium compound and its transformation product, a surfactant and a pesticide 
degradation period were identified (Figure 9). RCRsoil 10 years varied from approximately 1 to about 100 for most 
compounds, with the exception for dipyridamol with of 339.   

Figure  9:  Pollutants  present  in  sewage  sludge  that  showed  a  RCRsoil  10  years  ratio  above  1  (model  input  values applied  to 
derive the values presented as Supplementary Information (Table 11)). 

The presence of pharmaceuticals in sewage sludge may give rise to their presence in soils shortly after sludge 
land application. Potential risks for soil organisms have been identified based on the concentration averaged 
over a 30-day period after the (intermittent) application of sewage sludge. At the same time, it is important to 

24 

0.010.1110100CoronenePerfluorononanoic acid (PFNA)Perfluorooctane Sulfonate (PFOS)Benzo[ghi]peryleneDibenzo[a,h]pyrene2,3,7,8-TCDDMCCPsSCCPsDibenzo[a,l]pyreneRCRsoilRCR soil 100 yearsRCR soil 10 yearsRCRsoil 1 year1101001000OxipurinolFipronil sulfoneTraseolide (ATII)Lauryl diethanolamideCiprofloxacin (CFC)N,N-DimethyldodecylamineOfloxacin (OFC)PermethrinTriclocarbanBeta-sitosterolCampesterolCandersartanBenzalkonium chlorideStigmasterolTelmisartanCholesterolDipyridamolRCRsoil 10 years 
 
 
 
 
 
 
 
 
 
stress  that  most  pharmaceuticals  are  (readily)  biodegradable12,  and  therefore  no  accumulation  of  these 
pollutants is expected and observed in agricultural soils (i.e. RCRsoil 10 years = RCRsoil 1 year). This is also the case for 
dipyridamol  (readily  biodegradable),  telmisartan  (readily  biodegradable,  failing  10-day  window),  and 
candersartan (readily biodegradable), the pharmaceuticals characterised by the highest RCRsoil 10 years within this 
class.  Biological  sludge  treatment  options,  including  both  anaerobic  digestion  and  composting,  are  able  to 
remove a share of these pollutants from the sludge (Carballa et al., 2007; Haiba et al., 2016; Thomas et al., 
2020). Nonetheless, these compounds might still be present in detectable and removal rates are compound 
and  process-specific,  with  e.g.  high  removal  rates  (>90%)  observed  for  triclosan/triclocarbans  but  minimal 
removal for some other substances (Carballa et al., 2007; Haiba et al., 2016; Thomas et al., 2020). Thermal 
treatment (incineration) will effective remove pharmaceuticals, and no residues are expected to be present in 
sewage sludge ashes that may be used a source material for P-fertiliser production.  

Plant  sterols  are  compounds  of  eukaryotic  cells  present  in  a  range  of  plant  foods  such  as  beans,  lentils, 
cereals,  vegetable  oils,  seeds  and  nuts.  Sterols  are  also  food  additives  added  to  many  foodstuffs  to  lower 
cholesterol levels in humans. These are labile compounds that are degraded in soils, presumably due to the 
action of soil arthropods (Puglisi et al., 2003). No reports have been found that highlight the potential toxicity 
of  plant  sterols  for  soil  microorganisms.  Therefore,  the  low  PNECsoil  values  derived  fro  PNECwater  using  the 
equilibrium  partition  method  are likely underestimated. Hence,  these compounds are  not considered a main 
concern when present in sewage sludge. 

The  widespread  global  use  of  polycyclic  musk,  their  high  log  Kow  values  and  persistence  has  resulted  in 
widespread  occurrence  in  sewage  sludge.  It  is  surprising  that  the  assessment  identified  traseolide  as  the 
musk of  main concern, whereas no  risks for the  soil compartment was identified for  other synthetic musks 
such as galaxolide and tonalide. The PNECaqua and PNECsoil value for traseolide (6.9 E-04 µg L-1) is much lower 
than  for  other  musks.  Musks  typically  have  a  half-life  in  soils  around  100-150  days,  and  show  limited 
potential for accumulation in soils under yearly sludge application scenarios (Balk and Ford, 1999). Therefore, 
a provisional assessment of the risk of 2 polycyclic musks showed that long term risk to the soil environment 
as  a  result  of  normal  sludge  application  is  unlikely  (Danish  Ministry  of  the  Environment,  2012).  In  this 
assessment, the RCRsoil 10 years for traseolide is just above 1.  

Bactericidal cationic surfactants such as quaternary ammonium compounds (QACs) are widely detected in the 
environment.  Although  individual  QACs  are  amenable  to  biodegradation,  it  is  possible  that  persistence  is 
increased for mixtures of QACs with varying structure (Khan et al., 2015). Moreover, toxic degradation for soil 
microorganisms,  have  been  identified  (Khan  et  al.,  2015).  Hence,  QACs,  and  particularly  benzalkonium 
chloride,  may  potentially  be  a  risk  for  soil  organisms  and  soil  quality,  for  which  reason  a  more  in-depth 
assessment  of  these  compounds  may  be  required.  For  the  second  surfactant,  lauryl  diethanolamide,  no 
relevant information related to risks for soil organisms could be retrieved but its low biodegradation potential 
points towards a potential concern for this substance.  

Fipronil is a common insecticide, often used to de-flea household pets such as dogs and cats. Fipronil is not 
authorised for use in animals for the food chain as it has potential toxicity to humans. The RCRsoil 10 years for this 
substance is only just above 1. Moreover, fipronil sulfone is classified as a readily biodegradable compound, 
and seems therefore of a reduced concern in view of soil quality.  

The detailed results of the step 2 analysis (e.g. RCRsoil after 1 and 100 years of application) for compounds 
relevant for human health (see section 3.3.1) are given in section 13.3. No step 2 analysis were performed for 
pollutants that are characterised by an RCRsoil 10 years above 1, but a RCRhuman 10 years below 1. 

3.4.2  Prioritisation of pollutants 

In our view, the pollutants that classify as toxic and persistent in the soil environment could be considered as 
priority pollutants. The assessment brought forward that particular pollutants identified as being a concern to 
human health (PAH,  long-chain PFAS, PCDD/F, alkylphenols, and short- and mid-chain  paraffins) are also of 
concern for soil quality and biodiversity  protection. In our view, these pollutant classes are most relevant in 

12  Readily  biodegradable  is  defined  as  the  ability  of  a  product  to  biodegrade  quickly  and  completely  within  28 

days suing a standard test procedure (≥ 60% by OECD 301A-F/ASTM D7373 testing). 

25 

 
 
 
 
 
 
 
  
                                           
view of soil protection due to the high residence times in soils. Consecutive  sewage  sludge applications are 
modelled to result in a further build-up of these pollutants in soils, up to levels that impair soil biodiversity 
and ecological and socio-economic ecosystem functions of agricultural land.  

In  addition,  a  reduced  set  of  pollutants  (benzalkonium  chloride  and  its  degradation  products,  and  lauryl 
diethanolamide,  traseolide)  has  been  identified  in  this  ecological  screening  assessment  that  could  be 
prioritised for a more in-depth ecological assessment. 

3.5  Availability of measurement standards 

Measurement standards for the priority list of pollutants presented in previous sections have been identified 
in the European Standard (EN) and International Organization for Standardization (ISO) databases (Table 3).  

For most of the  priority  pollutants, at least one measurement standard (either EN or  ISO) was identified as 
relevant  (Table  3).  This  was  the  case  for  polycyclic  aromatic  hydrocarbons;  dioxins,  furans  and  dioxin-like 
polychlorinated  biphenyls;  alkylphenols;  short-  and  medium-chain  polychlorinated  alkanes  (no  EN  standard 
identified but one ISO standard relevant), and phthalate acid esters. 

Nevertheless,  for  per-  and  polyfluoroalkyl  substances,  polychlorinated  naphthalenes;  benzalkonium  chloride 
and its degradation products (as well as other quaternary ammonium compounds); lauryl diethanolamide (and 
N-acyl amines or fatty amides), and traseolide (synthetic musks), no relevant measurement standards  could 
be identified, neither in the EN nor in the ISO database (Table 3). 

Table 3: Identified measurement CEN and ISO standards relevant for the priority list of pollutants in sludge or soil. 

Relevant 
ISO 
standards 

ISO 
13859:2014 

ISO 
18287:2006 

ISO standard title 

Soil 
— 
quality 
Determination  of  polycyclic 
hydrocarbons 
aromatic 
(PAH) 
gas 
by 
chromatography  (GC)  and 
high  performance 
liquid 
chromatography (HPLC) 

Soil 
— 
quality 
Determination  of  polycyclic 
hydrocarbons 
aromatic 
(PAH) 
Gas 
— 
chromatographic  method 
with  mass  spectrometric 
detection (GC-MS) 

Priority pollutants 

Relevant  EN 
standards 

EN standard title 

Polycyclic  aromatic 
hydrocarbons 
(PAHs) 

EN 
16181:2018 

EN 
17322:2020 

prEN 17503 

Soil,  treated  bio-waste  and 
sludge  -  Determination  of 
polycyclic 
aromatic 
hydrocarbons  (PAH)  by  gas 
chromatography (GC) and high 
performance 
liquid 
chromatography (HPLC) 

Environmental Solid Matrices - 
of 
Determination 
biphenyls 
polychlorinated 
(PCB)  by  gas  chromatography 
-  mass  selective  detection 
(GC-MS)  or  electron-capture 
detection (GC-ECD) 

Soil, sludge, treated bio-waste 
and  waste  -  Determination  of 
polycyclic 
aromatic 
hydrocarbons  (PAH)  by  gas 
chromatography (GC) and high 
liquid 
performance 
chromatography 
- 
Determination  of  polycyclic 
aromatic  hydrocarbons  (PAH) 
by  gas  chromatography  (GC) 
and  high  performance  liquid 
chromatography (HPLC) 

(HPLC) 

Dioxins,  furans  and 
dioxin-like 
polychlorinated 
biphenyls (PCDD/Fs, 

EN 
16190:2018 

Sludge,  treated  bio-waste  and 
soil - Determination of dioxins 
and  furans  and  dioxin-like 
polychlorinated  biphenyls  by 

ISO 
13876:2013 

26 

quality 

Soil 
Determination 
polychlorinated 
by 
(PCB) 

— 
of 
biphenyls 
gas 

 
 
 
 
 
 
 
 
 
 
 
PCBs) 

gas chromatography with high 
resolution  mass 
selective 
detection (HR GC-MS)  

ISO 
13914:2013 

ISO/DIS 
13914 

chromatography  with  mass 
selective  detection  (GC-MS) 
and  gas  chromatography 
with 
electron-capture 
detection (GC-ECD) 

Soil 
— 
quality 
Determination  of  dioxins 
and  furans  and  dioxin-like 
biphenyls 
polychlorinated 
chromatography 
by  gas 
with  high-resolution  mass 
selective 
detection 
(GC/HRMS) 

Soil,  treated  bio-waste  and 
sludge  —  Determination  of 
dioxins  and  furans  and 
dioxin-like  polychlorinated 
gas 
biphenyls 
chromatography  with  high 
resolution  mass  selective 
detection (HR GC-MS) 

by 

- 

- 

- 

and 

Per- 
Polyfluoroalkyl 
substances (PFAS) 

- 

Alkylphenols 
(APs/NPs/OPs) 

CEN/TS 
16182:2012  

- 

- 

and 

Short- 
Medium-chain 
polychlorinated 
alkanes (S/MCCPs) 

Sludge  treated  bio-waste  and 
of 
-  Determination 
soil 
and 
nonylphenols 
and 
nonylphenol-mono- 
diethoxylates 
gas 
chromatography  with  mass 
selective detection (GC-MS)  

using 

(NP) 

ISO/TS 
13907:2012 

ISO 
18635:2016 

(NP) 

quality 

— 
Soil 
of 
Determination 
and 
nonylphenols 
nonylphenol-mono- 
and 
diethoxylates  —  Method  by 
gas  chromatography  with 
mass  selective  detection 
(GC-MS) 

— 
Water 
quality 
short-
Determination  of 
polychlorinated 
chain 
alkanes 
in 
(SCCPs) 
sediment,  sewage  sludge 
and suspended (particulate) 
matter — Method using gas 
chromatography-mass 
spectrometry  (GC-MS)  and 
electron  capture  negative 
ionization (ECNI) 

Polychlorinated 
naphthalenes 
(PCNs) 

- 

- 

- 

- 

Phthalate 
acid 
esters (DEHP/DINP) 

CEN/TS 
16183:2012  

- 

its 

Benzalkonium 
chloride  and 
degradation 
products 
(Quaternary 

ISO 
13913:2014 

Sludge,  treated  bio-waste  and 
of 
-  Determination 
soil 
selected 
using 
phthalates 
capillary  gas  chromatography 
spectrometric 
with  mass 
detection (GC-MS)  

Soil 
— 
quality 
Determination  of  selected 
phthalates  using  capillary 
gas  chromatography  with 
spectrometric 
mass 
detection (GC/MS) 

- 

- 

- 

27 

 
 
 
 
 
 
 
 
ammonium 
compounds) 

Lauryl 
diethanolamide  (N-
amines  & 
acyl 
fatty amides) 

Traseolide 
(Synthetic musks) 

- 

- 

- 

- 

- 

- 

- 

- 

3.6 

Impacts of wastewater treatment processes 

The assessment in the previous sections is based on observed  contaminants concentrations as measured in 
sewage  sludges,  mostly  originating  from  wastewater  treatment  plants  across  the  EU.  At  present,  the 
implementation  of  advanced  (quaternary)  wastewater  treatment  is  limited,  for  which  reason  the  current 
database  on  sludge  quality  does  not  capture  the  effect  of  such  innovative  wastewater  treatment 
configurations.    

Advanced  wastewater  treatment  typically  entails  adsorption  and  oxidation  processes,  most  often  through 
activated carbon and ozonation respectively. Activated carbon can be dosed in powdered form (PAC) directly in 
the  bioreactors of  biological  treatment  plants,  or  in  a  separate  reactor  downstream.  Alternatively, it  can  be 
provided in the form of a granular bed (GAC) through which the effluents of biological treatment are passed.   

In the case of direct dosing in the bioreactor, PAC remains enmeshed in the surplus sludge and, because of its 
characteristics and potentially high concentration of microcontaminants, it makes the sludge unfit for reuse in 
agriculture due to the high capacity of the PAC to adsorb and strongly bind a wide spectrum of contaminants. 
The  chemical  composition  of  PAC-enriched  sludge  and  its  dynamics  in  soils  with  respect  to  contaminant 
release are at present unknown. At the same time, the enmeshed PAC enhances the energy content of sludge 
when  it  comes  to  incineration.  The  dosing  of  PAC  in  the  bioreactor  can  be  a  cheap  option  for  advanced 
treatment in many cases. The use of PAC is the sole process where there is a transfer of contaminants from 
the effluents to the sludge, and is therefore applicable only when direct sludge reuse is not contemplated. Its 
most logical implementation is in cases with sludge incineration, and it could improve the energy balance of 
incineration.  

When  PAC  is  used  in  a  separate  reactor,  or  in  the  case  of  GAC,  the  surplus  sludge  of  biological  treatment 
processes is unaltered. Exhaust PAC or GAC in these cases form a separate waste stream. 

Ozonation  works  on  the  effluents and  does not  alter the  quality  of  the  sludge.  Usually, ozonation  does not 
lead to complete mineralization of micropollutants and yields reaction products that are less stable than the 
parent molecules, but potentially reactive and harmful. It is therefore recommended to couple ozonation with 
a  further  adsorption  stage  (a  sand  filter,  GAC  or  PAC).  In  any  case,  the  waste  from  these  processes  is  not 
expected to mix with the surplus sludge of biological treatment, and is therefore irrelevant in terms of sludge 
quality. 

Hence, it is concluded that the possible implementation of more advanced (quaternary) wastewater treatment 
under the UWWTD with a view to improve effluent quality is not expected to alter the quality of (primary and 
secondary) sludge brought to agricultural land. However, it may result in an increased proportion of the sludge 
being incinerated to the detriment of sludge landspreading. Therefore, it is important to minimise contaminant 
inputs  upstream  to  wastewater  treatment  plants  (e.g.  through  product  design,  limiting  inflow  of  certain 
industrial wastewaters) when sludge is targeted for land application.  

3.7  Risk screening assessment conclusions and recommendations 

Based on the available data and techno-scientific understanding, this work identified a set of pollutants that 
are present in sludge at levels that could induce environmental and human health risks. Risk characterisation 
ratios over 100 were observed, indicating that under a ‘reasonable worst-case’ scenario – significant risks for 

28 

 
 
 
 
 
 
  
 
 
human  health  and  the  environment  may  be  present.  The  pollutants  that  were  considered  to  be  of  most 
concern  for  human  health  are  PAH,  PCDD/F+dl-PCB,  long-chain  PFAS,  SCCPs/MCCPs,  and  to  a  lesser  extent 
alkylphenols,  PCNs,  and  phthalate  acid  esters.  These  pollutants  are  highly  toxic  to  humans,  show  a  high 
bioaccumulation potential and are persistent in the soil for long periods due to their lack of mobility in the soil 
matrix  and  low  biodegradation  potential.  In  addition,  pollutants  such  as  PFAS  may  end  up  in  water  bodies, 
where it can further contribute to risks to water quality and fish consumers. The pollutants associated to the 
greatest risks are already subject to actions and restrictions under the POPs and REACH Regulation. 

Most of the pollutant groups identified as being of concern for human health are also associated to risks for 
soil  organisms.  Humans  are,  however, the  most  sensitive  endpoints  for these  substances  for  which  risks  to 
humans  may  even  occur  at  lower  pollutant  concentration  levels  in  sludges.  Therefore,  risk  mitigation 
strategies  that  aim  to  protect  human  health  will  also  decrease  risks  to  soil  organisms  and  soil  quality. 
However,  in  addition  to  the  more  persistent  pollutants  identified  above,  benzalkonium  chloride  and  its 
degradation products, and lauryl diethanolamide, traseolide were also  identified as possibly posing a risk to 
soil organisms.    

Risk  mitigation  options  may  involve  limiting  the  concentration  of  pollutants  of  concern  in  sewage  sludge. 
Biological  sludge  treatment  options  such  as  composting  and  anaerobic  digestion,  may  not  be  effective  to 
remove  the  persistent  pollutants  of  concern  to  below  levels  of  concern.  On  the  other  hand,  incineration  in 
modern plants has the potential to effectively lower pollutant levels to low or negligible concentrations, after 
which the ashes could be used as an intermediate in P-fertiliser manufacturing processes. An alternative risk 
mitigation option is to reduce the volumes of sewage sludge spread on land relative to the modelling scenario 
of  5  tonnes  dry  matter  ha-1  yr-1  applied  in  this  assessment.  For  instance,  an  application  scenario  with  a 
maximum  load  of  2  tonnes  of  dry  matter  per  ha  every  3  years  would  already  reduce  pollutant  loads  by 
approximately a factor 10. Finally, hybrid options could be envisaged to ensure full environmental and health 
protection from the effects of organic pollutants. 

29 

 
 
 
 
 
4  Other contaminants present in sludge 

Apart  from  chemical  substances,  sewage  sludge  contains  other  compounds  of  concern  to  humans  and  the 
environment. This section focusses on antimicrobial resistance, biological pathogens, and microplastics.  

4.1  Antimicrobial resistance 

Antimicrobial  Resistance  (AMR)  occurs when  bacteria,  viruses,  fungi  and  parasites  change  over  time  and  no 
longer  respond  to  medicines  making  infections  harder  to  treat  and  increasing  the  risk  of  disease  spread, 
severe illness and death. As a result of drug resistance, antibiotics and other antimicrobial medicines become 
ineffective and infections become increasingly difficult or impossible to treat. 

Although  wastewater  goes  through  numerous  treatment  and  cleaning  processes,  some  antibiotic  residues 
cannot be removed by these methods (Chen et al., 2016). While treatments can remove or reduce the load of 
AMR  bacteria,  AMR  genes  (ARGs)  have  been  detected  at  all  stages  of  the  municipal  wastewater  treatment 
process,  including  in  sludge.  Both  Fouz  et  al.  (2020)  and  Nguyen  et  al.  (2021)  have  analysed  extensive 
evidence base to highlight the contribution of wastewater to the emergence, persistence and transmission of 
AMR  under  different  settings.  However  they  also  note  inconsistencies  in  reporting  and  monitoring  data, 
compounded  by  a  lack  of  standardised  protocol  for  determining  AMR  gene  removal  via  wastewater 
treatments, and the inability to support appropriate risk assessment. 

Numerous AMR genes including types and subtypes of almost all common antibiotics have been detected in 
wastewater influent, effluent and biosolids or sludge. During the treatment process, a large proportion of AMR 
bacteria and ARGs are removed from the water phase and partitioned into the sludge phase, resulting in high 
concentrations of ARGs in sludges and biosolids. It is noteworthy that not all ARGs pose the same risk level to 
human health. The likelihood of AMRG introduction into human pathogens should be assessed based on their 
hosts (ARB), rather than the ARGs themselves (Vaz-Moreira et al., 2014) 

Over the last years, the application of molecular biology techniques has considerably improved the capability 
to identify AMR bacteria and quantify  AMR  genes both in  wastewater and soil. This offers the  possibility to 
monitor the  risk of  AMR outbreaks. As part of  2018 LUCAS Soil survey, the JRC selected 1,000 locations to 
investigate  taxonomical  and  functional  diversity  in  soil  by  means  of  metagenomics  and  metabarcoding 
(Orgiazzi et al., 2015). At the end of sampling campaign, 885 (out of 1,000) fresh soil samples were collected 
and  analysed  for  biodiversity  (metabarcoding).  Bacteria  were  among  the  targeted  organisms  for  diversity 
assessment. The generated dataset may allow the identification of potential ARB. Indeed, most potential ARB 
belong  to  Proteobacteria,  Firmicutes,  and  Bacteroidetes  phyla,  which  are  dominant  bacterial  phyla  in 
wastewater and sludge (Su et al., 2017). Their presence and relative abundance in EU agricultural soils can be 
easily assessed through LUCAS Soil Biodiversity dataset. 

Moreover, out of the 885 samples, 630 were also analysed for functional (metagenomics) aspects, including 
an investigation of the distribution of AMR genes. These 630 samples are mainly from cropland areas, where 
amenDMents are applied and, thus, the likelihood of an outbreak of antimicrobial resistance events is higher. 
The JRC is currently carrying out the identification and distribution of AMR genes across EU agricultural soils. 
The dataset potential is high as, in principle, it allows to identify any AMR genes, with the possibility to focus 
on genes with higher levels of risk to human health conferring resistance to the most widespread antibiotics 
(e.g. animal and human health). 

Furthermore, each LUCAS point is also well characterized by a large set of ancillary data (e.g. land cover, land 
use, soil physico-chemical properties, heavy metals, climate and topography). This allows the investigation of 
how each of these parameters (or a combination thereof) can affect the distribution of AMRG. Furthermore, it 
might be  possible to identify genes that  can  be  considered as indicators for specific  agricultural land  cover 
types  (e.g.  orchards),  or  specific  soil  properties  (e.g.  low/high  pH,  low/high  carbon  content).  Once  developed, 
these  indicators  may  be  considered  for  inclusion  into  the  progress  assessment  and  review  process  of  EU 
environmental  (e.g.  Sewage  Sludge  Directive  and  Biodiversity  Strategy  for  2030),  and  agricultural  (e.g. 
common agricultural) policies. 

30 

 
 
 
 
 
 
 
 
 
4.2  Biological pathogens 

Pathogens are any organisms that can produce a disease. Biological pathogens include microorganisms such 
as bacteria, viruses, protozoa, prions and fungi, and their associated toxins. Pathogens can also be carried by 
larger organisms. They have the ability to adversely affect human and environmental health in a variety of 
ways, ranging from relatively mild, allergic reactions and serious medical conditions to death. 

Raw  sewage  may  contain  a  wide  variety  of  pathogenic  microorganisms  reflecting  the  health  of  the 
community and industrial processes (e.g. hospitals, meat-processing facilities, abattoirs, tanneries). Pathogens 
of  concern  (simply  an  indicative  subset)  include  Astrovirus,  Hepatitis  A,  Salmonella,  Cryptosporidium  and 
Taenia saginata (tapeworm). Advances in analytical techniques and changes in consumer habits means that 
new  pathogens  are  recognized  and  the  impact  of  others  reduce.  Microorganisms  can  mutate  to  reflect 
changes in their environment. In addition, many  pathogens are  viable but non-culturable, which  means that 
actual  concentrations  in  sludge  are  probably  underestimated.  Thus,  no  assessment  of  the  risks  associated 
with  the  land  application  of  sewage  sludge  can  ever  be  considered  to  be  complete  when  dealing  with 
microorganisms.  As  new  agents  are  discovered  and  a  greater  understanding  of  their  ecology  is  developed. 
Treatment  of  sewage  sludge  by  anaerobic  or  aerobic  digestion  or  dewatering  will  reduce  the  number  of 
pathogens, but significant numbers can remain or regrow after storage. 

While  there  are  several  studies  addressing  pathogens  in  sewage  sludge  (Dumontet  et  al.,  2001),  they  are 
often based on a limited number of samples. In addition, many studies are based on laboratory bioreactors 
with  controlled  operating  conditions  (temperature,  aeration,  and effluent  flow), which  may  not  be  typical  of 
actual  environments.  Measures should  be  applied  in  order to  avoid  contamination  of  crop  plants  by  human 
pathogens (Major et al., 2020). The emergence of molecular techniques should allow a better characterization 
of  microbial  structure  and  functions  directly  in  the  environment  (i.e.,  soil  and  plant).  As  for  antimicrobial 
resistance  genes  and  bacteria,  LUCAS  Soil  Biodiversity  survey  offers  several  possibilities  for  detecting  the 
presence and distribution of human pathogens across agricultural soils in the EU. Nonetheless, their eventual 
source (e.g. sewage sludge application) would require additional investigations. 

Knowledge on the effects of sewage sludge on plant pathogens is still poor. Some studies seem to  show a 
no-effect  of  sludge  application  on  soil  suppressiveness  (i.e.,  soil  capability  to  naturally  suppress  a  plant 
pathogen  due  to  its  microbial  makeup)  to  plant  pathogens  (Ghini  et  al.,  2007).  Furthermore,  there  are 
evidences  that  the  application  of  sludge  may  contribute  to  the  suppression  of  some  plant  pathogens 
(Cotxarrera et al., 2002). 

An interesting recent development has been the sampling of untreated wastewater to assess the scale of the 
SARS-CoV-2 virus in a population (the virus that causes COVID-19). SARS-CoV-2 is shed in feces of infected 
individuals  and  can  be  measured  in  wastewater.  Increased  cases  of  COVID  in  the  community  is  associated 
with  increased  levels  of  SARS-CoV-2  in  wastewater,  thus  complementing  our  understanding  of  the 
transmission  of  COVID-19  in  the  community.  The  process  looks  for  the  non-infectious  RNA,  not  the  viable 
virus.  There  are  no  known  cases  of  transmission  resulting  from  exposure  to  wastewater.  The  JRC  recently 
published  a  report13  that  assessed  the  feasibility  of  a  European  Sewage  Sentinel  System  for  SARS-CoV-2 
based  on  the  experience  of  several  Member  States  and  a  laboratory  exercise.  There  is  evidence  of  the 
presence  of SARS-CoV-2  virus  in  primary  sewage  sludge,  which  implies  a  risk  to  wastewater  treatment 
workers  or  those  working  on  sewage  systems  containing  untreated  effluent.  Conventional  wastewater 
treatment provides only partial removal of SARS-CoVs, thus safe disposal or reuse of sludge will depend on 
the efficacy of final disinfection (Bogler et al., 2020). 

There is also growing concern on plant related diseases. Sewage sludge is also a source for the dissemination 
of alien plant species if seeds are excreted by humans and retained in the process. 

13 https://publications.jrc.ec.europa.eu/repository/handle/JRC125065 

31 

 
 
 
 
 
 
 
 
 
 
                                           
4.3  Microplastics contamination 

While  plastic  pollution  has  been  extensively  documented  for  aquatic  ecosystems,  less  is  known  about  the 
state and impacts of plastic in the terrestrial environment, especially in soil. Plastic debris on land is generally 
the result of three main pathways. These include:  

• 
debris gradually degrade into smaller pieces through wear, weathering and other disintegration processes; 

agricultural  practices  (e.g.  poly-tunnels,  mulching  substances,  baled  silage),  where  large  pieces  of 

• 

• 

through waste streams (e.g. landfills, bio-waste, sewage, litter); 

airborne deposition as a result of industrial processes.  

The term microplastics are loosely defined as particles of any type of “polymers” with a diameter of less than 
5  mm,  although  they  are  predominantly  composed  of  polyethylene  and  polyethylene  terephthalate. 
Microplastics  are  considered  to  be  primary  when  relating  to  any  fragment  that  are  already  5  mm  or  less 
before  entering  the  environment  (e.g.  microfibers  from  clothing,  microbeads,  and  plastic  pellets).  Secondary 
microplastics arise from the breakdown of larger pieces that are already in the environment through natural 
weathering processes (often referred to as macroplastics). For the purposes of this report, the emphasis is on 
primary microplastics. The new Regulation (EU) 2019/1009 on fertilisers says that macroscopic impurities are 
above 2 mm, from 16 July 2026, the presence of plastics above 2 mm within shall be no more than 2,5 g/kg 
dry  matter.  By  16  July  2029  the  limit-value  of  2,5  g/kg  dry  matter  for  plastics  above  2  mm  shall  be  re-
assessed in order to take into account the progress made with regards to separate collection of bio-waste. 

Recent  attention  has shown  that  microplastics are  present  in  sewage  sludge.  Wastewater  Treatment  Plants 
are receptors for microplastics derived from a range of sources (e.g. industry, domestic wastewater, surface 
drainage) that inevitably are mixed together. Through the settlement processes of wastewater treatment, the 
majority  of  microplastic  particles  becoming  entrained  in  sewage  sludge.  Differences  in  water  treatment 
technologies allow for small particles to pass through treatments within solid materials or sludge, which when 
applied to land, provides a significant pathway to soil. 

An  interesting  aspect  to  note  are  studies  that  show  that  microplastics  in  biological  wastewater  treatment 
systems  reduce  the  effectiveness  of  the  treatment  as  they  reduce  the  abundance  of:  nitrifying  bacteria;  
denitrifying  bacteria  with  nitrogen  and  phosphorus  removal  function;  heterotrophic  nitrification-aerobic 
denitrifying bacteria; and bacteria capable of degrading phenolic compounds (McCormick et al., 2014). 

Nizzeto et al. (2016) estimated that between 125 and 850 tons of microplastics/million inhabitants  could be 
ending  up  annually  on  agricultural  soils  that  will  receive  urban  sewage  sludge.  For  example,  the  study 
assumes that between 10-90% of microplastics produced from road wear and debris from building coating 
are  collected  by  WWTP  sewers,  which  means  that  360  and  1980  tons  microplastics  could  reach  municipal 
wastewater treatment plants every year.  

An unpublished report by the JRC of a recent pilot study to test the feasibility of analysing plastic particles in 
samples  collected  during  the  2018  LUCAS  Survey  found  on  average  58.3  microplastic  particles  in  1  g  of 
cultivated soil from 50 samples collected across 7 Member States (standard deviation: 146). –Work is ongoing 
to identify whether the locations sampled were subjected to possible applications of sewage sludge. Rolsky et 
al. (2020)  undertook a literature search on microplastics  in sewage sludge, including  six EU  Member States 
(Italy, Germany, Finland, Sweden, Ireland, Netherlands). They reported average  particle counts of 12.8 ±  5.2 
microparticles/g  globally  (34  microplastics/g  for  EU  MS, but  ranging  from  0.45 ± 0.2 microplastics  g−1  in  the 
Netherlands  to  113 ± 57 microplastics g−1  in  Italy).  In  addition,  the  paper  reported  that  the  most  common 
particle  morphology  was  fiber  (present  in  100%  of  the  sample),  followed  by  fragment  (71%),  and  sphere 
(35%).  

Van  Den  Berg  et  al.  (2020)  showed  that  the  plastic  loads  in  eastern  Spain  increased  by  280  light  density 
microplastics  kg-1  and  430  heavy  density  microplastics  kg-1  with  each  successive  application  of  sewage 
sludge.  

These  varying  outcomes  probably  reflect  differences  in  soil  physical  (e.g.  soil  structure)  and  chemical  (e.g. 
nutrient  status)  properties,  which  in  turn  can  have  an  impact  on  the  composition  of  microbial  communities 
and reaction to the plastic material. In addition, most studies focus on single species or groups rather than the 

32 

 
 
 
 
 
 
 
 
complex food webs that exist in reality where changes in a group of soil organisms can have consequences on 
the abundance, diversity and functioning of other groups.  

One factor that hampers the assessment of microparticles in sludge is the lack of recognised standards for 
the extraction and analytical techniques used to isolate and identify microplastics. This may lead to notable 
differences in the efficiency  to recover plastic particles and reporting of numbers.  Density separation is the 
most  common  technique  to  separate  plastic  particles  from  sludge  while  Fourier-Transform  InfaRed 
spectroscopy is widely used for their identification. 

Further work is needed to assess the fate and transport  of plastic  particles in soil, especially as a result of 
sludge disposal. 

Microplastics in soil are an increasing  source of concern  from both an ecotoxicological and pedological (soil 
formation and evolution) perspective. Changes in soil characteristics and function due to an accumulation of 
plastic  particles  can  change  particle  size  distribution  and  bulk  density,  while  negatively  affecting  the  water 
holding  capacity.  Another issue of concern  reflects their persistence, leading to a continued accumulation in 
soil over time.  

Most  studies  generally  show  that  microplastics  have  a  negative  impact  on  soil  organisms  but  with  some 
uncertainties  regarding  outcomes.  Laboratory  studies  have  shown  that  the  addition  of  polyester  fibres  can 
have both positive or negative effects on soil microbial activity (de Souza Machado et al., 2018), while Lin et 
al. (2020) showed that microplastics negatively affect soil fauna but stimulate microbial activity. On the other 
hand,  other  studies  have  reported  harmful  effects  in  some  groups  of  soil  fauna  following  the  ingestion  of 
microplastics  (Huerta  Lwanga  et  al.,  2016)  or  through  disruption  to  the  habitat  of  soil  microarthropods  by 
closing soil pores (Kim and An, 2019). In addition, the degradation of plastics can both release additives that 
are  contained  within  plastics  (e.g.  PBDEs,  phthalate  esters)  while  also  providing  a  platform  for  attracting 
contaminants (e.g. PAH, PCB, metals) due to their large surface area and adsorption characteristics. The latter 
aspect  is  of  particular  concern  given  the  previous  discussion  on  contaminants  of  concern  that  are  found 
routinely in sewage sludge. Finally, Li et al  (2020) reported the accumulation of microplastics in wheat and 
lettuce  plants  in  a  laboratory  setting.  Humans  are  exposed  to  microplastics  through  ingestion  of  food  and 
drink. Risks are currently considered as uncertain, and their understanding will increase significantly over the 
next decades because it will be further studied (European Chemicals Agency -ECHA, 2019) 

33 

 
 
 
 
 
 
 
 
5  Soil nitrogen, carbon and phosphorus cycling 

5.1  Objective and scope 

This  section  aims  to  assess  the  impact  of  sewage  sludge  applications  on  the  soil  biogeochemical  cycles  of 
carbon  and  nitrogen  to  characterise  the  potential  of  carbon  sequestration  and  related  greenhouse  gas 
emissions  from  soil  using  a  modelling  approach.  In  addition,  the  possible  contribution  from  sewage  sludge 
management to addressing the EU dependence on phosphate rock imports from abroad will be discussed in a 
qualitative manner (see section 5.5).  

5.2  Modelling approach 

Biogeochemical models, such as CENTURY/DAYCENT, simulate the behaviour of C and N within and across the 
atmosphere, vegetation, and soil, whereas the hydrological compound is able to simulate the spatial dynamics 
of the N compounds (i.e. the loss through leaching based on soil properties and soil humidity patterns). The 
models  simulate  soil  and  hydrological  processes  based  on  daily  maximum/minimum  air  temperature  and 
precipitation,  surface  soil  texture  class,  and  land  cover/use  data  (e.g.  vegetation  type,  cultivation/planting 
schedules, amount and timing of nutrient amenDMents) at small spatial scale, that are loaded from available 
spatially explicit databases. In addition to providing data on net primary productivity, biogeochemical models 
provide information on other aspects brought forward by Member States such as greenhouse gas emissions 
and  soil  organic  matter  balances.  The  main  strength  of  biogeochemical  modelling  techniques  lies  in  the 
possibility to make use of well-calibrated models to simulate the long-term material C and N dynamics and 
the resulting plant and environmental responses under the full set of EU agroecosystems that vary in plant 
types, soil types, climate conditions, and fertilisation management practices.  

The composition of sewage sludge has been developed from available techno-scientific literature (Fuentes et 
al.,  2004;  Walter  et  al.,  2006;  Alvarenga  et  al.,  2007;  Smith  et  al.,  2008;  Tarrasón  et  al.,  2008;  Fytili  and 
Zabaniotou,  2008;  Tambone  et  al.,  2010;  Ferreiro-Domínguez  et  al.,  2012;  Kelessidis  and  Stasinakis,  2012; 
Koutroubas et al., 2014; Krüger et al., 2014; Samolada and Zabaniotou, 2014; ISPRA, 2015; Rigby et al., 2016; 
Orzi et al., 2018; Cristina et al., 2019; Di Capua et al., 2020; Campo et al., 2021; Gianico et al., 2021), as well 
as information  sources  obtained  from  experts  and  organisations  (e.g.  EurEau).  Finally, and  in  order  to  align 
with  the  closed  mass-balance  approach  for  the  life  cycle  assessment  (see  section  6),  information  from  a 
process-based  understanding  of  emissions  and  transformation  processes  that  take  place  during  the 
composting  and  anaerobic  digestion  of  sewage  sludge  were  taken  into  account.  The  compositions  of  the 
dewatered, composted and anaerobically digested sludge are given in Table 4. The uncertainty for dewatered, 
as observed from the literature (17 peer review papers), indicated a coefficient of variation of 21-30% across 
the different properties. For the modelling exercises, a coefficient of variation aligned to this spectrum (25%) 
was assumed for all parameters and sludge types (Table 4).  

34 

 
 
 
 
 
 
Table 4: Assumed chemical composition of the selected materials used for biogeochemical modelling (TOC: total organic 
carbon; TN: total nitrogen, Min N: mineral nitrogen; P: phosphorus, K: potassium; stdev: standard deviation). 

Dewatered sludge  Digested 

Composted sludge 

dewatered sludge 

average 

stdev 

average 

stdev 

average 

stdev 

TOC (%, dry matter) 

31.2 

7.8 

26.0 

TN (%, dry matter) 

3.1 

0.78 

10.1 

2.5 

12 

1.8 

0.4 

23 

3 

0.45 

0.1 

6 

69 

5.2 

5.0 

32 

2.6 

0.7 

23 

- 

6.6 

1.1 

1.5 

8 

21.1 

3.0 

7.0 

12 

0.54 

3.2 

0.1 

6 

- 

0.5 

60 

- 

5.3 

0.8 

1.7 

3 

0.8 

0.1 

15 

- 

TOC:TN (-) 

Min N:TN (%) 

P (%, dry matter) 

K (%, dry matter) 

dry matter (%) 

methane  potential  (m3  CH4 
/tonne volatile solids) 

277 

The  approach  applied  here  is  developed  in  such  manner  that  equal  crop  yields  are  simulated.  Hence,  the 
scenarios  where  (treated)  sewage  sludge  is  applied  to  agricultural  land  have  a  proportionate  reduction  in 
mineral fertilisers under the assumption that sewage sludge partially displaces mineral fertilisers. One kg of 
nitrogen  in  sewage  sludge  is  assumed  to  replace  about  0.75  kg  of  mineral  N  fertiliser.  All  results  are 
expressed  as  a  net  difference  of  the  sewage  sludge  treatment  (sludge  treatment)  and  the  corresponding 
treatment with higher inputs of mineral fertiliser, but absence of sewage sludge in the fertilising mix applied 
(reference treatment).  

The  carbon  and  nitrogen  dynamics  were  modelled  for  three  types  of  sludges  (dewatered,  composted  and 
digested  sludge),  under  two  different  application  scenarios  (1  tonne  dry  matter  ha-1  yr-1  and  5  dry  matter 
tonne ha-1 yr-1). In the absence of spatially explicit data on sewage sludge applications, it was assumed that 
sewage sludge applications take place on every spatial point of the LUCAS soil database (22 000 data points 
in  total),  and  data  are  presented  as  such.  It  is important  that  point  emission  data  should  be  interpreted  as 
values for fields amended with sewage sludge, but that data cannot be summed at a wider spatial scale. To 
obtain aggregated data (e.g. at MS level or EU-wide), the generated sewage sludge volumes at MS level need 
to  be  considered  (see  section  6.3  for  such  an  approach  developed  at  EU  scale).  The  model  was  run  over  a 
simulation period of 32 years. 

Three different processes are important to determine the climate change impacts from sludge applications on 
agricultural  land: nitrous oxide  (N2O)  emissions,  methane  (CH4)  emissions, and  carbon  sequestration  in  soils 
that  is  accounted  for  as  a  carbon  removal  strategy.  Results  are  expressed  as  emission  factors  for  nitrous 
oxide (N2O) emissions (kg N2O per kg N applied in the (treated) sludge), methane emissions (kg CH4 per kg of 
C  applied  in  the  (treated)  sludge),  and  carbon  sequestration  (kg  C  sequestered  per  kg  of  C  applied  in  the 
(treated) sludge) in agricultural soils.  To  calculate and present the  carbon sequestration factors in soils, the 
supplementary carbon sequestration from the sludge treatment relative to the reference treatment after 32 
years of continuous sludge applications was divided by the number of applications (32). 

5.3  Results 

EU-wide average values for the absolute greenhouse gas emissions and carbon sequestration in soils after 32 
years  are  presented  in  Table  5.  It  is  indicated  that  greenhouse  gas  emissions  factors  are  higher  for  the 
scenarios with the higher sewage sludge applications of 5 tonnes ha-1 yr-1, especially for N2O emissions. This 
observation is because changes in soil organic C turnover feed back into the N cycle, with soils that are more 

35 

saturated  by  soil  organic  carbon  content  showing  greater  N2O  emissions  (Lugato  et  al.,  2018).  The  N2O 
emission factors are highest for digested sludge, followed by dewatered and composted sludge (Table 5); this 
observation may relate to the higher  mineral N to total  N ratios in digestates that  give  rise to greater N2O 
emissions  from  nitrification-denitrification  pathways  (Häfner  et  al.,  2021).  N2O  emission  factors  for  the 
1 tonne  ha-1  yr-1  scenario  are  generally  well-aligned  to  the  default  IPCC  emission  factor  for  the  storage  of 
dewatered (>20%) organic materials of 0.5%.   

In spite of a 5 times higher sewage sludge application rate, carbon sequestration in soils is only marginally 
higher for the 5 tonnes ha-1 yr-1
 as sequestration under high application scenarios may be limited by the soil 
organic  carbon  saturation  capacity  (Lugato  et  al.,  2014a).  Expressed  relative  to  the  carbon  present  in  the 
(treated) sludges applied to land, the carbon sequestration is higher for digested and composted sludge than 
for  dewatered  sludge  (Table  5).  The  labile  carbon  fractions  are  partly  removed  during  biological  sludge 
treatment,  for  which  higher  carbon  sequestration  can  be  achieved  per  unit  of  carbon  applied  in  composted 
and digested sludges due to the higher proportion of recalcitrant C added (Torri et al., 2014; Möller, 2015). At 
the same time, it has to be  taken into consideration that biological sludge  processing methods significantly 
reduce  the  carbon  loads  of  the  materials  applied  to  land  (with  up  to  more  than  50%  of  the  total  carbon 
present in the mixed sludge being removed). Therefore, the potential for carbon sequestration is still larger for 
untreated sewage sludge than for composted and digested sludge (see section 6).     

Table 5: Average CH4 and N2O emission factors and C sequestration rates for EU-28. 

Parameter 

Type of sludge 

Scenario 1 tonne ha-1 yr-1 

Scenario 5 tonnes ha-1 
yr-1 

0.0055 

0.0049 

0.0060 

0.00100 

0.00093 

0.00149 

0.21 

0.28 

0.26 

0.014 

0.012 

0.036 

0.0012 

0.0014 

0.0015 

0.25 

0.36 

0.30 

N2O emissions 

dewatered sludge 

(kg  N2O  per  kg  N  applied  in 
the (treated) sludge) 

composted sludge 

digested sludge 

CH4 emissions 

dewatered sludge 

(kg CH4 per kg of C applied in 
the (treated) sludge) 

composted sludge 

digested sludge 

Carbon sequestration 

dewatered sludge 

(kg C sequestered per kg of C 
applied 
(treated) 
sludge) 

the 

in 

composted sludge 

digested sludge 

36 

Due to the high global warming potential of N2O (265–298 times that of CO2 for a 100-year timescale), N2O 
emissions  are  the  most  important  contributor  the  carbon  footprint  of  the  use-on-land  phase  of  sewage 
sludge. The N2O emission factors for the 1 tonne ha-1 yr-1 treatment vary across MS, with soils from northern 
MS characterised by somewhat lower N2O emissions following continued applications of (treated) sludge land 
(Figure 11) compared to soils located in other MS such as Italy. Similar to the N2O emissions, CH4 emissions 
vary markedly between northern and southern countries (see section 14.2; not depicted in the main text given 
their more limited impacts on the total carbon footprint). 

Figure  10:  Estimated  N2O  emissions  across  EU  Member  States  for  assumed  sewage  sludge  application  scenarios  of  1 
tonne ha-1 yr-1 (top row) and 5 tonnes ha-1 yr-1 (bottom row). 

37 

 
A  North-South  gradient  is  observed  from  the  biogeochemical  modelling  results  that  estimate  carbon 
sequestration from sewage sludge applications in soils (Figure 12). Across the different types of sludges, soils 
from northern  countries  (e.g.  PL,  DK)  show  the  lowest  potential  to  sequestrate  additional  carbon  relative  to 
the reference scenario of mineral fertiliser applications. A greater potential was observed for  soils from  MS 
located at southern and intermediate latitudes (e.g. PT, southern FR, RO, BG), likely due to their lower present-
day organic C contents that are well-below the soil C saturation capacity (Lugato et al., 2014a).  

Figure 12: Spatially explicit carbon sequestration factors (kg CO2 sequestered per kg C in (treated) sludge) as estimated 
using biogeochemical modelling for application scenarios of 1 tonne ha-1 yr-1 (top row) and 5 tonnes ha-1 yr-1 (bottom row) 
for composted sewage sludge (left hand side), dewatered sewage sludge (middle), and digested sludge (right hand side). 

5.4  Climate change adaptation 

Soil organic matter improves the soil’s water retention capacity enhancing the drought tolerance by crops and 
improves  infiltration-diminishing  runoff  avoiding  that  soil  particles  will  be  transported  with  water  and  wind 
(Altieri  and  Nicholls,  2017).  Higher  levels  of  soil  organic  carbon  increases  biological  diversity  which  in  turn 

38 

creates  the  conditions  that  are  hospitable  to  plant  roots,  allowing  the  development  of  strong,  healthy  and 
resilient crops (Altieri and Nicholls, 2017). For all these reasons, carbon sequestration in soil is recognised as 
an effective climate change adaptation strategy. 

To assess the potential of sewage sludge to contribute to the climate adaptation potential, it may be relevant 
to compare organic C inputs from sludge relative to other sources of organic matter for agriculture. The total 
manure  production  from  pigs,  cattle  and  chicken  in  the  EU  amounts  approximately  1,381  million  tonnes of 
manure (Foged et al., 2011; Flotats et al., 2013). Solid manure fractions, with an assumed dry matter content 
of 25%-30%, alone account for about 719 million tonnes, thus equalling about 198 million tonnes expressed 
on a dry matter basis with an organic carbon content similar to sewage sludge. Food waste is estimated at 
about 88 million tonnes in the EU, but the (growing) share of municipal waste composted and digested in the 
EU  was  only  18%  (16  million  tonnes)  in  2018  (EEA,  2020).  Hence,  in  comparison  with  other  sources,  the 
potential of sewage sludge to deliver organic matter to soils at the EU-wide scale (presently about 2.5 million 
tonnes  out  of  a  total  of  approximately  7.5  million  tonnes  produced)  is  relatively  small.  Nonetheless, 
particularly  in  EU  regions  with  a  more  extensive  livestock  production  system or  for  soils characterised  by  a 
low organic matter content (e.g. in southern Europe), sewage sludge may be an important source of organic 
matter and contribute as such to climate change adaptation (Figure 12). 

5.5  Phosphorus cycling 

The EU is dependent on the input of rock phosphate and finished phosphorus (P) inputs from foreign nations, 
mostly from Western Sahara and Russia (only <15% of the P originates from mines located in the (north) EU). 
Moreover,  phosphorus  is  a  critical  raw  material  that  is  finite.  This  makes  the  EU  particularly  sensitive  to 
economic scarcity and price  shocks. At  present, the annual EU imports about 1.1  million tonnes (Mt) of P in 
mineral  fertilisers,  and  about  0.5  Mt  P  yr-1  in  feed  and  food  for  local  consumption  (net  imports,  thus 
substracting e.g. food exports) (Van Dijk et al., 2016). Phosphorus ending up in sewage sludge is estimated at 
about 0.13 Mt P yr-1, of which less than half ends up on agricultural land. Hence, P in sewage sludge equals 
about 8% of the primary total P consumed in the EU as fertilisers and feed. Therefore, the recycling of P from 
sewage sludge is particularly important for the EU in its objective to increase resource efficiency and strategic 
autonomy. 

Sludge  management  routes  that  return  P  to  agricultural  land  involve  the  landspreading  of  untreated  or 
(biologically) stabilised sludge, as well mono-incineration followed by P-recovery from the resulting ashes. The 
agronomic  P  efficiency  of  sludge  spread  on  land  is  typically  lower  than  for  P  present  in  mineral  fertilisers, 
even  though  this is  dependent  on  the  degree  of  complexation  with  Fe  and Al  polymers  used  in  wastewater 
treatment plants (Wilfert et al., 2015). Phosphorus recovery can also take place upstream during wastewater 
treatment (e.g. precipitation of phosphate salts such as struvite), and this process will affect the P-content of 
sludge and thus the environmental performance of sludge treatment. 

5.6  Conclusions 

Greenhouse gas emission and carbon sequestration from the use-on-land phase of sewage sludge may jointly 
contribute to the carbon footprint of sewage sludge management options.  In addition, phosphorus  return to 
agricultural land is a critical point to be considered during the assessment of the environmental performance 
of  sewage  sludge  management.  The  biogeochemical  modelling  results  indicate  that  (i)  biological  sludge 
treatment  impacts  upon  the  climate  change  mitigation  potential  of  the  use-on-phase  of  (treated)  sewage 
sludge,  and  (ii)  local  climate  and  soil  conditions  largely  influence  the  carbon  footprint  of  sludge  land 
application. The biogeochemical modelling data obtained will be further used in section  6 that compares the 
global warming potential of different sewage sludge management options using a life cycle perspective. 

With  respect  to  climate  change  adaptation,  it  is  indicated  that  sewage  sludge  is  a  small  source  of  organic 
matter  compared  to  e.g.  manure  and  separately  collected  bio-waste,  Nonetheless,  under  some  regional 
settings and for some soils, sludge may locally be an important organic matter input that can contribute to 
the  build-up  of  soil  organic  C  and  resilience  to  climate  change.  The  proper  management  of  P  contained  in 
sewage  sludge  is  important  of  view  of  reducing  the  EUs  dependence  on  imported  P  fertilisers  and  rock 
phosphate. 

39 

6 

Impacts on climate change mitigation 

6.1  Objectives and scope 

The  objective  of  this  section  is  to  assess  and  compare  the  global  warming  impacts  from  different  sludge 
management options via a life cycle assessment approach (LCA).  

This LCA allows comparing the environmental performance from a climate change mitigation perspective of 
different sludge management options. In addition, it allows bringing forward an absolute estimate of the net 
global warming potential (kg CO2-eq per year) associated to sewage sludge management within the EU. 

6.2  Methodology 

The functional unit of the study is the management of 1 tonne (dry matter) of  sewage sludge produced at a 
wastewater treatment plant. The assessment of the environmental aspects and potential impacts associated 
with  a  product  was  performed  following  ISO  standards  for  LCA  (ISO,  2006a,  2006b).  A  zero  burden  global 
warming  potential  is  assumed  for  the  C  present  in  sewage  sludge,  a  short-lived  and  wasted  biomass  of 
biogenic  origin.  A  consequential  approach  was  applied  to  capture  the  environmental  consequences  of  the 
displacement of conventional market products (e.g. NPK fertilisers and electricity) (Weidema, 2003; Tonini et 
al., 2019). Hence, system expansion has been performed in order to ensure equivalence of functions across 
scenarios.  The  impacts  resulting  from  the  transformation  of  carbon,  and  nutrients  (N,  P  and  K)  were 
considered using a closed mass balance approach in the foreground system of this LCA, focused on Climate 
Change as the sole impact category (Forster et al., 2007). The temporal scale boundary – especially relevant 
for long-term processes such as greenhouse gas losses  at landfills and carbon sequestration in soils  – was 
set to a period of about 30 years. The assessment was carried out with the LCA tool EASETECH (Clavreul et 
al., 2014).  

The  system boundaries start from mixed sludge generated at  wastewater treatment  plants and expire with 
the  final  use  of  sludge  or  derived  materials  on  agricultural  land  or  elsewhere.  The  life  cycle  stages  thus 
involve  primary  processing  at  wastewater  treatment  plants  (e.g.  dewatering,  thickening),  secondary  sludge 
treatment (lime stabilisation, anaerobic digestion, composting, co-incineration, mono-incineration followed by 
ash acidulation to manufacture a P-fertiliser), transport from wastewater treatment plants to other facilities 
and agricultural land, sludge storage prior to use on agricultural land, and final use of derived materials (use-
on-land,  construction  material,  landfilling).  The  life  cycle  approach  takes  into  account  both  climate  burdens 
(e.g. from energy requirement for sludge processing, chemicals, greenhouse gas emissions during processing 
and use-on-land) and savings (e.g. substitution of energy, mineral fertilisers, sequestration of sludge-derived 
carbon  in  agricultural  soils).  Internal  waste  heat  recovery  was  assumed  to  increase  the  efficiency  of  the 
process and promoting process savings (e.g. for sludge heating and drying). The results from the use-on-land 
phase of (treated) sewage sludge as developed in section 5 have been plugged into the LCA model (results of 
1 tonne ha-1 yr-1 application scenarios). Greenhouse gas emissions and carbon sequestration from the use-on-
land  phase  of  sludge  are  already  expressed  as  the  net  impacts  relative  a  scenario  with  equal  crop  yields 
following mineral fertiliser application. 

Departing  from  the  assumed  sludge  composition  as  outlined  in  section  5,  7  different  scenarios  have  been 
selected  for  this  modelling  exercise  (Figure  13),  aiming  to  represent  some  main  important  sludge 
management options that take place in the EU (see section 2). The options selected are not representing all 
sludge  management  options  or  combination  thereof  that  could  take  place.  Nonetheless,  it  is  believed  that 
assessing these pathways sheds light on the key processes and life cycle stages that contribute to the overall 
global  warming  potential.  They  include  options  that  involve  use-on-land  of  sludges,  possibly  followed  after 
chemical  or  biological  treatment.  Also,  the  option  of  the  use-on-land  of  acidulated  sewage  sludge  mono-
incineration ashes (in the form of a mineral P-fertiliser) is considered. Finally, two pathways that result in the 
removal  of  nutrients  and  organic  carbon  from  the  biogeochemical  cycle  are  considered:  co-incineration 
followed by landfilling and use as a construction material of the ashes, and sludge landfilling (Figure 13). Our 
entire assessment is based on present-day "scenario analysis modelling", and the results are neither timeless 
nor exhaustive nor specific to particular manufacturers, industry sectors or situation-specific settings. Rather, 
this work  intends to  assess the  possible  impacts  of  sludge  management  options  in  general, and  to  provide 
numerical data that may help to better conceptualise and understand possible impacts from sewage sludge in 

40 

 
 
 
 
 
 
the  broader  context.  Uncertainties  related  to  assumed  parameter  values  is  discussed  (section  6.4).  Model 
input data for the different processes applied are given in the Annexes to this report (section 15.1) 

Figure  13:  Schematic  and  simplified  representation  of  the  seven  modelling  scenarios  (UOL:  use-on-land,  LS:  lime 
stabilisation,  COM:  composting,  AD:  anaerobic  digestion,  MI:  mono-incineration,  AC:  acidulation,  CI:  co-incineration  in 
municipal solid waste incineration plant, CM: use as construction material, LF: landfilling). 

6.3  Results (average values) 

Net average results sum burdens (positive values) and savings (negative values) vary from  -268 to 1650 kg 
CO2-eq / tonne sewage sludge DM) (Figure 14).  

41 

use on land  ADADincacidcompostAD + UOLLFMI + AC +UOLCI + CMCOM + UOLincLS + UOLUOLlandfillconstruction materiallime stabilisationP-fertiliser 
 
 
 
 
 
 
Figure 14: LCA results for the Global Warming Potential for selected pathways (see Figure 13 for pathway description). 

The best performing pathways in this analysis are direct use of untreated or lime stabilised sewage sludge on 
agricultural land. The use-on-land of anaerobically digested and composted sludge, as well as incineration are 
intermediately  ranked  options,  whereas  landfilling  is  the  worst  performing  pathway  associated  to  a  large 
positive value (Figure 14). 

The  difference  in  global  warming  potential  between  land  application  of  unprocessed  and  lime  stabilised 
sludge is minimal  given that the  production and  use of lime to sludge has a  minimal carbon footprint, and 
other  emissions  were  assumed  equal  in  the  absence  of  a  well-developed  dataset.  The  processes  that 
contribute  to  the  observed  net  negative  removal  of  CO2  through  these  pathways  are  the  credits  from  the 
avoided  production,  transport  and  use  of  mineral  fertilisers  and  carbon  sequestration  in  soils  (Figure  14). 
Emissions  occur  from  the  storage  and  transport  as  well  as  to  a  smaller  extent  from  the  initial  processing 
(primary  treatment  such  as  dewatering  and  thickening)  of  sewage  sludge  (Figure  14).  Nonetheless,  since 
savings are greater than burdens, a net negative carbon footprint is indicated for both pathways (Figure 14). 

Biologically  stabilised  sludges  obtained  following  composting  and  anaerobic  digestion  also  have  a  negative 
global warming potential (Figure 14). Since a significant share of the carbon and nitrogen present in sludge is 
lost  during  the  composting  process,  the  savings  from  the  use-on-land  of  composted  sludge  are  smaller 
compared to use-on-land of untreated sewage sludge. The losses during storage and use-on-land of compost 
are  also  smaller  compared  to  that  pathway  due  to  the  increased  stabilisation  of  the  sludge,  but  the 
processing stage shows an opposite trend due to the additional energy requirements and greenhouse gases 
emitted. Anaerobic digestion followed by the use on land of the resulting digestate is the pathway that shows 
the  highest  savings  in  the  form  of  summed  fertiliser  credits,  energy  credits  and  soil  carbon  sequestration. 
Fertiliser credits are higher than for compost as N is largely retained during digestion and the slightly higher 
nitrogen fertiliser displacement value of the mineral nitrogen-rich digestate (Möller, 2015). Nonetheless, the 
burdens for this pathway are also high due to the methane leakage at anaerobic digesters, as well as higher 
N2O losses during the use-on-land phase of the ammonium-rich digestates (see section 5.3). 

42 

 
 
 
 
 
 
The net impacts of the co-incineration are close to zero as the greenhouse gas emissions (N2O) (Gutierrez et 
al., 2005) and energy requirements for the incinerator (e.g. fossil fuels for start-up) are largely compensated 
by renewable energy production at modern combined heat and power plants (CHP) (Figure 14). Energy credits 
obtained  from  energy  recovery  during  incineration  are  significant,  and  could  be  further  improved  in  case 
sludge  is  dried  using  low  impact  systems  (e.g.  with  waste  heat  from  other  industrial  neighbouring 
installations, solar drying). 

The emissions from the scenario of P-fertiliser manufacturing from mono-incinerated sewage sludge through 
acidulation  are  similar  to  those  from  co-incineration.  The  main  process  contributing  to  the  burdens  are  the 
significant N2O emissions that have been observed as N2O emissions concentrations in the off-gasses ranging 
from approx. 50 to 200 mg N2O m-3 (average value assumed of 125 mg N2O m-3; slightly higher than for co-
incineration  (75  mg  N2O  m-3)  due  to  the  slightly  lower  temperature  and  air  to  fuel  ratio  for  fluidised  bed 
incineration relative to grate incineration) (Svoboda et al., 2006; Gutierrez et al., 2005; Korving et al., 2010). 
The  fertiliser  credits  are  lower  compared  to  the  pathways  that  apply  (treated)  sludge  due  to  the  loss  of  N 
during incineration. On the other hand, the P-fertiliser credits are higher compared to other pathways because 
the increased P availability of the produced (mineral) fertiliser (Oenema et al., 2012; Wilfert et al., 2015). 

Landfilling is the worst performing pathway from a global warming perspective due to high methane losses, 
even in modern facilities (Figure 14).  

43 

 
 
 
 
  
6.4  Uncertainty analysis  

Section 6.3  provides results  based on assumed average  values for process  parameters, but  it is recognised 
that process parameters vary across industrial facilities and that greenhouse gas emissions may depend on 
e.g. storage conditions, electricity mix used, sludge fertiliser equivalency. Assumed parameter values used in 
this  uncertainty  assessment  are  given  in  section  15.1.  The  uncertainty  analysis  indicates  that  the  carbon 
footprint  of  a  single  pathway  may  fluctuate  substantially  (Figure  15),  and  that  the  performance  ranking 
across pathways can  be altered.  Figure 15  provides an overview of the parameters that most contribute to 
the observed uncertainty as well as the expected impacts of their variability. 

a)  use-on-land (no treatment) 

b)      use-on-land (lime stabilised) 

c)    use-on-land (composted) 

d)     use-on-land (digested) 

e)     use-on-land (P-fertiliser from ash) 

f)       co-incineration 

Figure  15:  Sensitivity  analysis  on  the  global  warming  potential  for  the  selected  pathways  investigated.  The  red  bar 
represents the global warming potential for the maximum value of each parameter. The blue bar represents the global 
warming potential for the minimum value of each parameter. 

For untreated and lime stabilised sludges used on land, most of the uncertainty originates from  greenhouse 
gas losses during the use-on-land phase and the storage phase. N2O emissions from the use-on-land phase 
vary  widely  across  EU  regions      as  a  function  of  soil  and  climate  type  (see  section  5.3).  Storage  can  be 
minimised to very low levels when applying best available techniques (e.g. covering, creating a well-aerated 
environment)  and  limited  storage  times  (Willén,  2016;  Willén  et  al.,  2016;  Giner  Santonja  et  al.,  2017; 
Samuelsson  et  al.,  2018),  and  this  may  further  reduce  the  global  warming  potential  of  this  pathway  by 
approximately 200 kg CO2-eq / tonne sewage sludge DM. The carbon sequestration potential of sludge varies 
across  the  EU  and  may  further  impact  upon  the  pathway  performance,  as  well  as  mineral  fertiliser 

44 

 
 
 
 
 
 
 
 
 
 
 
 
 
equivalence of the sludge (Figure 15 a/b). The phosphorus fertiliser equivalence relative to mineral fertilisers 
is highly dependent on the Al and Fe content, with sludges characterised by a high (Al+Fe)/P ratio showing a 
lower  plant  availability  of  phosphorus  than  e.g.  sludge  produced  at  biological  wastewater  treatment  plants 
(Oenema et al., 2012; Wilfert et al., 2015). 

The  uncertainty  related  to  the  global  warming  potential  for  the  compost  pathway  is  the  lowest  across  all 
pathways analysed (Figure 15  c).  Greenhouse gas emissions from the storage and  use-on-land phase  vary, 
but to a smaller extent compared to other pathways given the increased stability of the compost.  The main 
parameter that influences the compost pathway are the N2O emissions from the use-on-land phase as well 
as  the  electricity  mix.  In  case  an  energy  mix  with  a  higher  carbon  footprint  (more  fossil  fuels)  is  applied 
(ventilation,  mixing  at  composting  facilities),  the  carbon  footprint  of  the  pathway  may  show  a  net  positive 
value (Figure 15.c). Also, emissions from storage are important, but to a smaller extent relative to direct use-
on-land  of  sludge  as  total  losses  from  storage  are  lower  for  the  more  stabilised  compost.  Composts 
characterised by a higher fertilising value show a better performance (Figure 15). Finally, N2O emissions from 
compost  are  important,  with  much  higher  greenhouse  gas  emissions  from  outdoor  windrow  composting 
systems than from controlled aerated systems (Vergara and Silver, 2019). 

For  anaerobic  digestion,  the  methane  leakages  from  digestion  plants  are  key  to  the  overall  impact  of  this 
pathway. Methane leakages has been  documented to  range from 0.1% to  6%  (IAEA Bioenergy Task, 2017), 
and  the  net  impact  of  best  versus  worst  performing  pathways  is  about  500  kg  CO2-eq  tonne-1  dry  matter. 
When  leakages  are  minimised,  the  performance  of  this  pathway  is  even  better  than  direct  use-on-land  of 
untreated  sewage  sludge,  whereas  net  emissions  will  turn  positive  when  sludge  is  being  digested  in  plants 
characterised  by  high  methane  leakages  (Figure  15.d).  Again,  N2O  emissions  from  the  use-on-land  are  an 
important contributor to the observed pathway variability. 

For mono-incineration plants, the critical factor to the overall emissions for this pathway are the nitrous oxide 
emissions  during  the  incineration  process  (Figure  15.e).  Concentrations  of  N2O  in  off-gases  have  been 
documented to range from 2 to 400 mg N2O/Nm3 gas (Korving et al., 2010; Svoboda et al., 2006). It may be 
important to corroborate if these ranges still apply to modern mono-incineration facilities as emissions may 
have reduced over time, e.g.  due to  higher temperature applied in the afterburner chamber  (Neuwahl et al., 
2019). In case the N2O emissions from mono-incinerators were minimal, the global warming potential of the 
pathway that involves the acidulation of mono-incinerated ash to produce a P-fertiliser would be close to zero 
(Figure 15). Co-incineration technologies typically have much lower N2O losses than mono-incineration (IGES 
for the IPPC, 2002). In addition, the moisture content of the sludge has a large impact on the performance of 
the  incineration  pathway.  In  case  sludge  is  dried  using  low  energy  demanding  techniques  (e.g.  solar  drying, 
application of waste heat) the performance of the pathway would further increase (Figure 15).  

6.5 

Impacts of upstream wastewater treatment processes 

The Urban Wastewater Treatment Directive (91/271/EEC; UWWTD) requires nitrogen removal between 70 and 
80%  of  influent  loads  in  specifically  designed  sensitive  zones.  The  current  state-of-the-art  with  biological 
WWTPs allows a removal of 80%, and a removal of 90% could be achieved with well-targeted and accurate 
plant operation. Policy options for the UWWTD include an increase of N removal efficiency to more than 80%. 
When  this  is  the  case,  the  carbon  present  in  the  influent  needs  to  be  preserved  for  the  stoichiometry  of 
denitrification,  for  which  reason  we  expect  a  reduction  of  carbon  in  the  sludge  and,  as  a  consequence,  a 
possible reduction of the potential to produce CH4 through anaerobic digestion or energy through incineration. 
While  in  well-balanced  wastewater  treatment  processes  an  energy-positive  anaerobic  digestion  is  possible 
also with high denitrification, it should be well understood that it is not possible to maximize at the same time 
denitrification  and  downstream  renewable  energy  production  from  sludge  treatment.  In  terms  of  global 
warming potential, the abatement of N2O emissions due to partial denitrification at the wastewater treatment 
is  expected  to  have  a  greater  impact  than  the  downstream  energy  credits  from  sludge  processing  on  the 
overall  balance.  Moreover,  enhanced  denitrification  brings  benefits  in  terms  of  water  quality.  All  this 
considered,  enhanced  denitrification  upstream  should  be  regarded  as  a  priority  over  renewable  energy 
production from downstream sludge management.  

45 

 
 
 
 
 
 
 
 
6.6  Relative importance of sewage sludge management for climate change 

Based  on  gap-filled  Eurostat  2016  data  (see  section  2),  it  is  assumed  that  roughly  7.5  million  of  tonnes 
sludge (dry matter) are generated and used directly or after digestion in agriculture (35%), incinerated (31%), 
composted  (12%),  landfilling  (12%)  or  managed  otherwise  (10%).  Main  uncertainties  to  these  data  exist 
(Wood E&I GmbH, 2021), but a further assessment of sludge management pathways falls beyond the scope 
of this work. To frame the absolute global warming impacts, we will approximate a scenario where 100% of 
the generated sludge is managed according to one of the pathways evaluated above, as follows:    

-  Direct use in agriculture: 30%; 
-  Use-on-land after anaerobic digestion: 11%  
-  Use-on-land after composting: 12%  
- 
Co-incineration: 25%; 
-  Mono-incineration: 10% 
- 

Landfilling: 12% 

Based  on  this  simplified  approach  and  acknowledging  the  uncertainties  associated  to  the  dataset  and 
limitations of the approach applied, sludge management leads to a net emission of about 0.67 million tonnes 
CO2-eq  per  year.  The  absolute  footprint  from  sewage  sludge  management  is  relatively  small  relative  to 
operations  that  take  place  at  upstream  (sewage  system  and  wastewater  treatment  plants),  estimated  at 
around  25-30  million  tonnes  of  CO2-eq  per  year  (unpublished  data  from  JRC  policy  report  on  the  Urban 
Wastewater  Treatment  Directive).  The  agricultural  sector  as  a  whole  produced  426  million  tonnes  of  CO 2 
equivalent of greenhouse gases in 2015, about 10% of the EU's total greenhouse gas emissions (excluding 
Land Use, Land Use Change and Forestry net removals) for that year (Eurostat, 2021). 

Nonetheless, a worst case alternative scenario with 88% of sludge being incinerated, and 12% of the sludge 
being landfilled, would increase the global warming potential to about 1.5 million tonnes CO2-eq per year. In a 
best possible scenario where all sludge is being applied directly on agricultural land would minimise emission 
to -2.0 million tonnes per year. Hence, the application of sustainable sludge management has a potential to 
reduce the global warming footprint with up to  3.5 million tonnes CO2-eq per year. It is therefore concluded 
that  sustainable  sewage  sludge  management  is  important  to  reduce  the  carbon  footprint  of  the  entire 
wastewater  treatment  system,  including  sludge  management.  Sludge  management  can  be  applied  as  net 
carbon removal strategy and offset as such a part of the carbon footprint of upstream wastewater collection 
and collection processes. 

6.7  Supplementary  potential  for  energy  recovery  from  sludge  from  digestion 

and incineration with energy recovery 

Sludge processing techniques such as anaerobic digestion and incineration have the potential to recover part 
of  the  energy  contained  in  the  sludge.  Estimations  on  the  potential  are  highly  dependent  on  assumptions, 
including  methane  potential  and  lower  heating  values,  technology  configurations,  and  sludge  volumes  that 
subject  to  these  treatments.  The  European  Biogas  Association  estimated  that  in  2019  about  4642  GWh  of 
gross electricity was produced from the methanation of wastewater treatment plant sludge, with a dominant 
contribution  from  plants  located  in  Germany14.  The  main  method  of  taking  up  biogas  energy  is  producing 
electricity  in  CHP  or  other  plants.  Assuming  an  electric  efficiency  of  35%,  this  would  correspond  to  about 
1625  GWHel  per  year  from  sewage  sludge.  Under  the  assumption  that  an  additional  30%  of  the  sludge 
volumes could be subject to anaerobic digestion (2.25 million tonnes dry matter; see above), and an electric 
energy generation potential of 1500 kWh per tonne dry matter from sludge digestion, about 3375 GWh el of 
additional renewable gross energy could be produced. Energy production from sludge incineration is subject to 
high  uncertainties because  pre-treatments,  including  sludge  drying  techniques, have  widely  differing  energy 
intensities (e.g. solar drying versus rotating drums). Under the assumption of a potential of diverting 1 million 
tonnes  of  sludge  dry  matter  from  treatments  without  energetic  valorisation  (e.g.  from  landfilling  without 
energy recovery) to incineration with energy recovery, and an electric energy recovery potential of about 1020 
KWh  per  tonne  dry  matter  sludge  for  incineration,  1020  GWh  additional  renewable  gross  energy  could  be 
produced. Hence, a reasonable high end potential for additional energy recovery from the anaerobic digestion 
and incineration of sludge equals about 4.4 TWhel, or 0.16% of the EUs 2020 total net electricity generation. 

14 See “2020 Biogas Barometer” report available at: https://www.eurobserv-er.org/biogas-barometer-2020/ 

46 

 
 
 
 
 
                                           
6.8  Conclusions 

Different  sewage  sludge  management  options  give  rise  to  net  emissions  of  CO2-eq  that  range  from  net 
negative  emissions  for  direct  land  application  of  untreated  sludge  (-268  kg  CO2-eq  /  tonne  sewage  sludge 
DM), over values closer to zero for biologically treated sewage sludge applied on land and co-incineration, to 
relatively high net emission values for landfilling (1485 kg CO2-eq / tonne sewage sludge DM). The results for 
all  the  different  pathways  vary  substantially  depending  on  technological  implementation  (e.g.  methane 
leakage from digesters, N2O losses from incinerators, coverage at sludge storage facilities) as well as on local 
agricultural  conditions  (e.g.  N2O  losses  from  sludge  use-on-land,  mineral  fertiliser  equivalence  of  (treated) 
sludge).  The  absolute  impacts  from  sludge  management  within  the  EU  are  small  relative  to  e.g.  upstream 
emissions  from  wastewater  collection  and  treatment.  However,  the  application  of  best  versus  performance 
techniques  for  sludge  management  across  the  entire  EU  would  result  in  a  net  greenhouse  gas  emissions 
savings of about 3.5 million tonnes CO2-eq. Therefore, it is important to consider climate change impacts from 
sludge  management  in  tandem  with  other  social,  environmental  and  economic  impacts  when  developing 
sustainable sludge management strategies. 

47 

 
 
 
 
7  Limitations and recommendations for further work 

The aim of this work is to increase the techno-scientific knowledge base on (i) risks from pollutants and other 
contaminants  of  emerging  concern  in  sludge  applied  to  agricultural  land,  and  (ii)  environmental  impacts 
arising from sewage sludge management in the EU. Quantitative and qualitative results on these aspects are 
presented in the sections 3 - 6 of the report. 

The level of analysis is framed within the constraints of the available time, resources and data for this study. 
This section provides an overview of the limitations that were associated to our work and conclusions, as well 
as recommendations for complementary work to support policy development on the SSD.   

7.1 

Issue  #1:  Compare  and  discuss  risk  screening  approach  with  other 
information sources 

Background  and  observed  limitation:  Prioritisation  of  chemical  pollutants  is  needed  so  actions  first  address 
chemicals that drive environmental and human health risks. The outcomes generally align to works of similar 
nature that have assessed a reduced subset of the pollutants (Norwegian Committee for Food Safety, 2009; 
Clarke and Smith, 2011; Deleebeeck et al., 2021). However, this is the foremost extensive screening study on 
risks  from  chemicals  in  sludge  on  the  basis  of  currently  available  data.  Modelling  data  input  is  mostly 
obtained from data repositories and often based on default assumptions and estimations. The data presented 
in this report have thus been collected in line with existing scientific standards and judgements. However, the 
authors  of  this  study  have  mostly  a  background  in  environmental  engineering,  and  complementary  views 
from other angles of incidence and scientific domains (e.g. (eco)toxicology) could further enrich this work.  

Recommendation:  Whereas  we  are  confident  on  our approach  undertaken,  additional, independent  points of 
comparison  (e.g.  studies  and  expert  opinions)  and  complementary  technical  discussions  with  experts  in  the 
field of risk assessment would further increase the robustness of this study. Such action could be organised 
e.g.  in  the  form  of  a  dedicated  workshop  and/or  via  the  monitoring  of  newly  published  techno-scientific 
literature on this topic.  

7.2 

Issue #2: Address uncertainty on organic pollutant concentrations present in 
sewage sludge 

Background and observed limitation: This work invested substantial efforts to chemically characterise sewage 
sludge in an as broad as possible manner. The methodology was developed to spot so-called contaminants of 
emerging  concern  for  which  reason  an  a  priori  selection  of  contaminants  for  assessment  was  omitted. 
However, it  is  noted  that  a  bias is  possible  as  measurements of  contaminants in  wastewaters and  sewage 
sludges  could  have  overlooked  certain  contaminants  and/or  inventorised  concentrations  that  are  not 
representative for all situations within the EU. This may be particularly important as the present database on 
contaminants in sludge may have been unable to capture (i) the latest trends for certain contaminants, e.g. in 
response  to  the  latest  technological  developments  (‘newly  developed  chemicals’)  and/or  legislation  on 
chemicals  (e.g.  REACH  restrictions  to  chemicals  in  consumer  products),  and  (ii)  regional  and/or  local 
differences in sludge quality (e.g. distinction between sludge from plants located in rural versus industrialised 
areas).  Finally,  for  some  pollutants  in  sludge  (e.g.  polychlorinated  paraffins)  measurement  standards  are 
missing. 

Recommendation:  Promote  further  efforts  in  the  monitoring  and  measurement  of  organic  contaminants  in 
sewage sludge to acquire actual data on sewage sludge quality and variations therein as a function of local 
conditions within the EU. This could possibly take place in the form of a renewed measurement campaign and 
effect-based methods on sewage sludge samples collected across the EU (similar to Tavazzi et al., 2012) or 
through  the  promotion  of  such  research  in  EU  and  national  research  programmes.  In  addition,  the 
development of measurement standards for key priority pollutants identified could be envisaged if these are 
not yet available. 

48 

 
 
 
 
 
 
 
7.3 

Issue  #3:  Improve  database  on  ecotoxicological,  toxicological  and  physico-
chemical properties of organic contaminants 

Background  and  observed  limitation:  The  collection  of  accurate,  up-to-date  and  comparable  data  is  a 
prerequisite  for  informed  risk  assessment  and  for  risk  management  decisions.  A  complete  database 
containing  data  on  (i)  on  the  sensitivity  of  the  organisms  and/or  endpoint  under  study  to  the  contaminant 
(‘predicted no-effect concentrations’), and (ii) physico-chemical data to model the dynamics and exposure of 
the  contaminant  in  across  different  environmental  compartments  is  needed.  As  indicated  in  section  3.3.1.1 
and  3.4  such  data  is  not  available  for  all  contaminants  that  are  present  in  sewage  sludge.  For  instance, 
standard tests to assess impacts on different trophic levels of soil organisms are hardly available, and more 
than 600 contaminants for which sewage sludge concentrations could be retrieved, could not be assessed in 
the risk assessment due to missing model input data. Hence, in spite of a well-developed database for many 
recognised  contaminants,  including  those  identified  in  techno-scientific  literature  as  being  of  concern  for 
sludge, the risk assessment remains incomplete. 

Recommendation:  Support  stakeholder  engagement,  and  calls  for  data  that  aim  at  characterising  and 
inventorying  contaminants  in  terms  of  (eco)toxicological  and  physico-chemical  properties,  as  well  as  data 
sharing.  This  recommendation  is  likely  not  limited  to  sewage  sludge  as  a  carrier  for  contaminants  to  the 
environment,  and  should  thus  be  framed  within  a  horizontal  initiative  to  support  action  programmes  on 
chemicals,  e.g.  aligned  to  the  zero-pollution  action  plan.  For  instance,  the  European  Partnership  for  the 
Assessment  of  Risks  from  Chemicals  (PARC)  already  seeks  to  develop  next-generation  chemical  risk 
assessment, incorporating both human health and the environment in a "One Health" approach. 

7.4 

Issue  #4:  Need  for  an  in-depth  risk  assessment  for  identified  organic 
priority contaminants and mixtures thereof 

Background and observed limitation: The risk assessment is carried out in a stepwise procedure starting from 
a wider spectrum of potential contaminants to identify pollutants of most concern. The exposure assessment 
in  aims  at  ‘reasonable  worst-case’  results  by  applying  unfavourable,  but  not  unrealistic,  standard  exposure 
scenarios  and,  as  much  as  possible,  mean,  median  or  typical  parameter  values.  If  the  outcome  of  the 
reasonable  worst  case  risk  characterisation  indicates  that  the  substance  is  “not  of  concern”,  the  risk 
assessment  for  that  substance  can  be  stopped.  If,  in  contrast,  the  outcome  is  that  the  substance  is  “of 
concern”, the assessment must, if possible, be refined in a subsequent phase. Moreover, the “screening step” 
has been executed in this study assesses risks to soil organisms and humans following indirect intake of food 
grown on sewage-sludge amended soils. Other end-points (e.g. aquatic organisms, sediment organisms, birds, 
other small mammals) were not considered in this assessment. With respect to aquatic organisms and water 
bodies, it is expected that the impact from sewage sludge applications on agricultural land is small relative to 
the  contaminant  load  entering  water  bodies  via  wastewater  treatment  effluents.  Contaminants  that  are 
partitioned to the sludge within the treatment process, rather than to the effluent, show a high affinity for the 
organic (solid) phase. Therefore, these contaminants are expected to be largely retained within the soil matrix 
instead of being lost via runoff or leaching. Soil organisms could be a proxy for risks to aquatic organisms and 
to broader wild life (higher organisms such as  birds) for  compounds that do not bioaccumulate in the  food 
chain. Humans are considered in this assessment as the top predator that ingest multiple food sources (fish, 
crops, meat, and drinking water). The results for this end point also could at a maximum be a first proxy for 
predators that consume fish, plants and soil organisms (e.g. mammals and/or birds), and thus for secondary 
food  poisoning  via  the  aquatic  and  terrestrial  food  chain.  Finally,  the  analysis  had  a  limited  focus  on 
degradation products of the chemicals that were measured in sewage sludge. 

Recommendation: This risk screening assessment points towards priority pollutants that cause most risk when 
present in sewage sludge. Dependent on the final objective of the risk study, a refined assessment for all or a 
subset of these priority compounds could be undertaken that further develops and updates this work amongst 
others with information collected in response to issues #1- #3. Such assessment must in a subsequent step (i) 
further develop the assessment for additional end points (e.g. aquatic organisms and and top predators (birds, 
fish  of  higher  trophic  levels)  for  bioaccumulative  compounds),  (ii)  update  results  by  the  results  of  other 
models (of a higher Tier level) judged to be more suitable for the pollutants under investigation or for certain 
critical  end-points,  (iii)  perform  a  detailed  analysis  of  degradation  products,  (iv)  assess  the  risks  from 
chemical  mixtures  containing  priority  compounds,  and  (v)  advance  the  source  contribution  analysis  by 
considering inputs from e.g. contaminants present in atmospheric deposition and other fertilising products at 

49 

 
 
 
 
 
the regional scale. Such analysis may ultimately bring forward limit values for a reduced set of pollutants to 
limit environmental and health risks to acceptable levels. 

7.5 

Issue #5: Assess environmental and health impacts from metals 

Background and observed limitation: Albeit their prevalence in sewage sludge has declined in recent decades, 
metals  are  key  substances  of  concern  in  sewage  sludge  due  to  their persistence  in  soils and toxicity  in  the 
environment  and  food  products.  The  scope  of  the  risk  screening  assessment  excluded  metals,  and  focused 
exclusively  on  organic  chemicals  of  concern  as  the  knowledge  base  on  this  group  of  substances  is  less 
developed compared to metals.  

Recommendation:  Assess which  metals are of concern in  view of the  reduced  metal contamination in food-
chain and based on the revised health recommendations on metals in food products since the entry into force 
of the Directive.   

7.6 

Issue #6: Assess innovative sludge management technologies  

Background and observed limitation: This assessment of climate change impacts has principally focused on 
sludge management routes that are commonly applied within the EU, and thus jointly determine the overall 
climate  change  impacts  from  sewage  sludge  management  across  the  EU.  Innovative  sludge  processing 
technologies,  sludge  pre-and  post-treatments,  and  combinations  thereof  are  numerous.  Common  sludge 
processing  technologies  are  continuously  being  refined  and  optimised  with  a  view  to  increase  process 
efficiency and minimise adverse environmental outcomes. Rationally, we have been unable to assess each of 
the individual configurations and facilities that process sewage sludge. 

Recommendation:  It  could  be  further  evaluated  if  market-competitive  technologies  exist  that  show  a 
disruptive potential to lower the carbon footprint of sludge management. Feedback may be requested from 
stakeholders to corroborate model data input values (averages and ranges reported in this study) in the light 
of new technological developments.  

7.7  Overall considerations and policy recommendations 

This  study  provides  an  initial  evaluation  of  the  environmental  and  health  impacts  and  risks  associated  to 
sewage sludge management. It is essential that the reader and users of the results presented understand the 
inherent limitations of the estimation methods and, finally, to correctly interpret the results. In our view, the 
results are  useful to  complement the evaluation of the effectiveness of the SSD. In addition, they could  be 
used  as  a  starting  point  to  develop  and  evaluate  possible  future  options  and  instruments  to  support  policy 
development  on  the  Sewage  Sludge  Directive.  Aligned  to  this,  it  is equally  important  to  further  develop  the 
understanding  of  the  actual  impacts,  risks  and  contributions  of  sewage  sludge  to  the  wider  environmental 
pressures and food safety issues. Such information may help to better understand the hazards and risks from 
sewage sludge that are acceptable to stakeholders (e.g. on risks to soil organisms, from microplastics), as well 
the targeted level of ambition for future policies on sewage sludge.   

50 

 
 
 
 
 
 
8  General conclusions 

This report further increased the knowledge base on social and environmental impacts from sewage sludge 
management in the EU.  

Firstly,  our  results  on  risks  from  organic  pollutants  and  the  environmental  performance  of  sewage  sludge 
management  options  indicate  apparent  trade-offs.  Thermal  (incineration)  and  to  a  smaller extent  biological 
(composting  and  anaerobic  digestion)  sludge  treatment  options  may  completely  or  partially  remove  the 
chemical  pollutants  as  well  as  microplastics  and  antimicrobial  resistance  genes  that  may  cause  risks  to 
human  health and the environment (e.g. PAH, PCDD/F+dl-PCB, long-chain PFAS, SCCPs/MCCPs.)  Nonetheless, 
seizing  greater  human  and  soil  health  benefits  from  sludge  treatment  may  –  generally  speaking  –  induce 
opposite impacts on the  environmental performace of sewage  sludge management. For instance, the  direct 
use-on-land of  untreated  or  lime  stabilised  sewage  sludge  has  a  net  negative  carbon  footprint  and  returns 
organic  matter  phosphorus  to  agricultural  land,  and  can  therefore  act  as  a  climate  change  abatement 
strategy.  In  contrast,  sludge  disposal  pathways  such  as  landfilling  cause  a  loss  of  phosphorus  and  higher 
greenhouse  gas  emissions  without  causing  risks  to  the  food  chain.  Innovative  options,  such  as  mono-
incineration followed by P recovery from the ashes, show an intermediate performance when considering all 
sustainability dimensions.  

Secondly,  it  is  shown  that  climate  change  impacts  as  well  as  risks  from  the  use-on-land  phase  of  sewage 
sludge may vary spatially across the EU. The use-on-land phase of the sludge contributes significantly to the 
overall results on global warming potential across different sewage sludge management options, and a great 
spatial  variability  is  observed  for  the  emissions  as  a  function  of  soil  and  climate  types.  Additionally, 
environmental  and  health  risks  from  chemical  pollutants  in  sewage  sludge  applied  to  land  are  linearly 
correlated to sludge application rates. Hence, cost-benefit ratios may be higher for EU regions characterised 
by a high ratio of agricultural land to population and livestock equivalents than for EU regions where sewage 
sludge  can  be  applied  at  lower  application  rates,  aligned  to  carbon  and  nutrient  needs  of  soils  close  to 
wastewater  treatment  plants.  This  points  towards  the  importance  of  considering  flexibility  to  implement 
sewage sludge management options as a function of the local context.  

Thirdly,  it  is  indicated  that  best  practices  and  management  techniques  may  have  an  impact  on  the  global 
warming  potential,  and  to  a  smaller  extent  on  the  removal  of  chemical  compounds  from  sludge.  Circular 
sludge  management  options,  including  mono-incineration  followed  by  acidulation  to  manufacture  a  sludge-
derived P fertiliser and anaerobic digestion, can have a neutral to negative global warming impact when best 
management  techniques  (e.g.  high  incineration  temperatures  to  reduce  N2O  emissions  from  thermal 
processing,  reducing  leakages  at  digestion  plants,  sludge  storage  with  coverage,  minimising  transport 
distances)  are  implemented.  The  application  of  good  practices  and  best  available  techniques  for  sludge 
treatment  may  also  help  to  further  reduce  pollutants  from  sludge  (e.g.  increased  chemical  removal  when 
stricter time-temperature profiles are applied during biological and thermal sludge treatment). 

Conclusions specific to the different topics in this study are outlined in the respective sections. 

51 

 
 
 
 
 
 
 
 
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66 

 
 
10  List of abbreviations 

AMR 
AMRG 
AP 
b.w. 
C 
D5 
DBT 
DEHP 
DINP 
dl-PCB 
DM 
ECD 
ECPA-LET 
EFSA 
EHDPP 
EN 
EUSES 
GAC 
GC 
HBCDD 
HELCOM 
HPLC 
IPCC 
ISO 
JRC 
Koc 
Kow 
LCA 
LUCAS Soil 
MCCP 
MS 
N 
NP 
OP 
P 
PAC 
PAH 
PBB 
PBDE 
PCB 
PCDD 
PCDF 
PCN 
PCPP 
PEC 
PFAS 
PFHxS 
PFNA 
PFOA 
PFOS 
PNEC 
POP 
QAC 
RCR 
REACH 

Antimicrobial Resistance 
Antimicrobial Resistance Gene 
AlylPhenol 
body weight 
Carbon 
Decamethylcyclopentasiloxane 
DiButylTins 
Di(2-ethylhexyl)phthalate 
Di-IsoNonylPhthalate 
dioxin-like PolyChlorinated Biphenyl 
Dry matter 
Electron-Capture Detection 
European Crop Protection Association (ECPA) - Local Environment Tool (LET) 
European Food Safety Authority 
2-EthylHexyl Diphenyl Phosphate 
European Standard 
European Union System for the Evaluation of Substances 
Granular Activitated Carbon 
Gas Chromatography 
HexaBromoCycloDoSecane 
Helsinki Commission 
High Performance Liquid Chromatography 
Intergovernmental Panel on Climate Change 
International Organization for Standardization 
Joint Research Centre 
Organic carbon-water partition coefficient 
Octanol-water partitioning coefficient 
Life Cycle Assessment 
Land Use/Cover Area frame statistical Survey Soil 
mid-chain chlorinated paraffins 
Member Sates 
Nitrogen 
NonylPhenol 
OctylPhenol 
Phosphorus 
Powdered Activitated Carbon 
PolyAromatic Hydrocarbons 
PolyBrominated Biphenyl 
PolyBrominated Diphenyl Ether 
PolyChlorinated Biphenyl 
PolyChlorinated Dibenzo-p-Dioxins 
PolyChlorinated DibenzoFurans 
Polychlorinated Naphthalenes 
Pharmaceuticals and Personal Care Products  
Predicted Environmental Concentrations 
PerFluoroAlkyl Susbtances 
PerFluoroHexane Sulfonic acid 
PerFluoronoNanoic Acid 
PerFluoroOctanoic Acid 
PerFluoroOctane Sulfonic acid 
Predicted No-Effect Concentration 
Persistent Organic Pollutant 
Quaternary Ammonium Compound 
Risk Characterisation Ratios 
Registration, Evaluation, Authorisation and Restriction of Chemicals 

67 

 
 
 
 
SCCP 
SLHC 
SSD 
TBT 
TEHP 
TOC 
TPT 
UFZ 
UWWTD 
UWWTP 
WATSON 

Short-chain chlorinated paraffins 
Safe Limit for Human Consumption 
Sewage Sludge Directive (86/278/EEC) 
TriButylTins 
Tris(2-EthylHexyl) Phosphate 
Total Organic Carbon 
TriPhenylTins 
Helmholtz Centre for Environmental Research 
Urban Wastewater Treatment Directive (91/271/EEC) 
Urban Wastewater Treatment Plant 
Dutch monitoring on micro-pollutants in influent and effluent from wastewater 
treatment plants 

68 

 
 
 
 
 
 
 
11  List of figures 

Figure 1: Eurostat data on the amounts of sewage sludge (dry matter) disposed for the period 2004 – 2016 
(reprinted from Wood E&I GmbH, 2021).. ............................................................................ 7 

Figure 2: Relative importance of sludge management options within different EU Member States (based on 
Eurostat 2016 data, with gap filling performed for some Member States based on 2010 – 2015 data). ...... 8 

Figure 3: Applied step-wise approach for the exposure assessment. Step 1 involves a local assessment based 
on the exclusive application of sewage sludge to agricultural soils that is mainly based on data retrieved from 
data repositories in a semi-automated manner (depectived in green). If the estimated exposure exceeds a risk 
characterisation ratio above 1, a Step 2 refinement is executed where model input data is further 
corroborated and background concentrations of the respective contaminant in soils and water bodies is taken 
into consideration (depicted in orange). ..............................................................................13 

Figure 4: Contaminants present in sewage sludge that showed a RCRhuman 10 years ratio in between 0.1 and 1 
(model input values applied to derive the values presented as Supplementary Information (Table 9)). .......17 

Figure 5: RCRhuman 10 years values for ad-hoc selected contaminants, identified by some stakeholders as being of 
potential concern when present in sewage sludge (model input values applied to derive the values presented 
as Supplementary Information (Table 9) (PCPP: Pharmaceuticals and Compounds and Personal Care. ........18 

Figure 6: RCRhuman values (logarithmic scale) for contaminants that were evaluated in step 2 of the 
assessment (blue bars indicate RCRhuman estimated following the exclusive application of sewage sludge as a 
sole contamination source; the end of the red bar indicates the RCRhuman values when - in addition to 
sewage sludge applications - background concentrations of the respective contaminants from other sources 
(e.g. atmospheric deposition) have been taken into consideration; when certain contaminants are associated to 
a group safe limit value for human consumption, these compound are represented jointly; ∑PCN: sum of 
naphthalene congeners 66/67 (mixture of 1,2,3,4,6,7-HxCN and 1,2,3,5,6,7-HxCN) and 73 (1,2,3,4,5,6,7-
HpCN).; ∑phthalate acid esters: bis(2-ethylhexyl)phthalate (DEHP), and di-isononylphthalate (DINP); ∑organotin: 
dibutyltins (DBT), tributyltins (TBT), and triphenyltins (TPT), ∑SCCPs: sum of short-chain chlorinated paraffins; 
∑MCCPs: sum of mid-chain chlorinated paraffins; BDE-209: decabromodiphenyl ether; BDE-47: 2,2',4,4'-
Tetrabromodiphenyl ether; BDE-99: 2,2',4,4',5-Pentabromodiphenyl ether; HBCDD: hexabromocyclododecane); 
TEHP: tris(2-ethylhexyl) phosphate, EHDPP: 2-ethylhexyl diphenyl phosphate; TCPP: tris(1-chloro-2-propyl) 
phosphate ∑PCDD/F + dl-PCBS: Polychlorinated dibenzo-p-dioxin and furans (PCDD/Fs) and dioxin-like 
polychlorinated biphenyls (dl-PCBs), with values presented for 2,3,7,8-TCDD used as a reference compound); 
∑PAH: sum of benzo[a]pyrene, chrysene, benz[a]anthracene and benzo[b]fluoranthene; ∑PFAS: sum of 
perfluorooctane sulfonic acid (PFOS), perfluorooctanoic acid (PFOA), Perfluorohexane sulfonic acid (PFHxS), 
and perfluorononanoic acid (PFNA); see section 4 and 13.2 for model input data values). .....................21 

Figure 7: Estimation of the relative contribution of fish (blue), crop/meat/dairy (orange) and drinking water 
(grey) to the total human intake of selected contaminants resulting from the exclusive assessment of 
contaminants present in sewage sludge (“no background modelling scenario”) (from inner to outer ring: ∑PFAS, 
∑PAH, ∑PCDD/F + PCB, 4-octylphenol, ∑MCCPs, ∑phthalate acid esters, ∑PCN; for full abbreviations: see Figure 
6). .......................................................................................................................22 

Figure 8: RCRsoil estimated after 1, 10, and 100 years of continuous sewage sludge applications for 
contaminants belonging to classes that had been identified as being of concern to human health (SCCP: short-
chain chlorinated paraffins, MCCP: mid-chain chlorinated paraffins; model input values applied to derive the 
values presented as Supplementary Information (Table 11)). .....................................................24 

Figure 9: Pollutants present in sewage sludge that showed a RCRsoil 10 years ratio above 1 (model input values 
applied to derive the values presented as Supplementary Information (Table 11)). .............................24 

Figure 10: Estimated N2O emissions across EU Member States for assumed sewage sludge application 
scenarios of 1 tonne ha-1 yr-1 (top row) and 5 tonnes ha-1 yr-1 (bottom row). ................................37 

Figure 11: Spatially explicit N2O emission factors (kg N2O per kg N in (treated) sludge) as estimated using 
biogeochemical modelling for application scenarios of 1 tonne ha-1 yr-1 (top row) and 5 tonnes ha-1 yr-1 
(bottom row) for composted sewage sludge (left hand side), dewater sewage sludge (middle), and digested 
sludge (right hand side). ..............................................................................................37 

Figure 12: Spatially explicit carbon sequestration factors (kg CO2 sequestered per kg C in (treated) sludge) as 
estimated using biogeochemical modelling for application scenarios of 1 tonne ha-1 yr-1 (top row) and 5 

69 

 
 
tonnes ha-1 yr-1 (bottom row) for composted sewage sludge (left hand side), dewatered sewage sludge 
(middle), and digested sludge (right hand side). ....................................................................38 

Figure 13: Schematic and simplified representation of the seven modelling scenarios (UOL: use-on-land, LS: 
lime stabilisation, COM: composting, AD: anaerobic digestion, MI: mono-incineration, AC: acidulation, CI: co-
incineration in municipal solid waste incineration plant, CM: use as construction material, LF: landfilling). ....41 

Figure 14: LCA results for the Global Warming Potential for selected pathways (see Figure 13 for pathway 
description). ............................................................................................................42 

Figure 15: Sensitivity analysis on the global warming potential for the selected pathways investigated. The red 
bar represents the global warming potential for the maximum value of each parameter. The blue bar 
represents the global warming potential for the minimum value of each parameter. ...........................44 

Figure 16: Flow chart showing the datasets utilized and their spatial resolution, the inputs derived and the 
model integration. ................................................................................................... 131 

Figure 17: Organic (above) and total N input (below) rates in the baseline. The boxplots represents the values 
distribution (median and interquartile ranges) of all simulated points with the average in red diamond 
symbols. .............................................................................................................. 132 

Figure 18: Spatially explicit CH4 emission factors (kg CH4 per kg C in (treated) sludge) as estimated using 
biogeochemical modelling for application scenarios of 1 tonne ha-1 yr-1 (top row) and 5 tonnes ha-1 yr-1 
(bottom row) for composted sewage sludge (left hand side), dewater sewage sludge (middle), and digested 
sludge (right hand side). ............................................................................................ 134 

Figure 19: Carbon sequestration (12, 22, 32, 37 years after distribution) in Member States for the scenarios of 
1 tonne ha-1 yr-1 (left panels) and, 1 tonne ha-1 yr-1 (right panels), Composted SS (comp) – baseline (base) 
scenario showed a decrease over time of the C sequestration throughout the time. .......................... 134 

70 

 
 
 
 
 
12  List of tables 

Table 1: Overview of main secondary treatment (e.g. lime stabilisation, composting, anaerobic digestion, P-
fertiliser production from mono-incineration ash) and final end uses of the resulting materials (e.g. use-on-
land, landfill, use as construction material of co-incinerated ash) ................................................. 9 

Table 2: Chemical substances identified in the Step 1 screening risk assessment as having a RCRhuman 10 years 
greater than 1, the 10 classes above the horizontal black line will be taken forward for a more detailed 
analysis. ................................................................................................................16 

Table 3: Identified measurement CEN and ISO standards relevant for the priority list of pollutants in sludge or 
soil. .....................................................................................................................26 

Table 4: Assumed chemical composition of the selected materials used for biogeochemical modelling (TOC: 
total organic carbon; TN: total nitrogen, Min N: mineral nitrogen; P: phosphorus, K: potassium; stdev: standard 
deviation). ..............................................................................................................35 

Table 5: Average CH4 and N2O emission factors and C sequestration rates for EU-28. ..........................36 

Table 6: Inferred surface water degradation rates at 20°C reported in the LET on basis of biodegradability 
screening results and FOCUSsw guidance ...........................................................................75 

Table 7: Inferred soil degradation rates at 20°C reported in the LET on basis of biodegradability screening 
results and FOCUSsw guidance .......................................................................................76 

Table 8: Default BMF values for organic susbtances (ECHA R.16 guidance R.16.5.3.5) ..........................82 

Table 9: Input data used to calculate the data presented in Figure 4 and Figure 5 (section 3.3.1.3). (Kow = 
octanol –water partitioning coefficient; Koc = partition coefficient organic carbon – water, DT50 = estimated 
half-life from laboratory degradation tests; SLHC = Safe limit for human consumption) .......................88 

Table 10: Input data used to calculate the data presented in Figure 6 (section 3.3.2) (Kow = octanol –water 
partitioning coefficient; Koc = partition coefficient organic carbon - water, DT50 = estimated half-life from 
laboratory degradation tests; SLHC = Safe limit for human consumption; BDE-209: decabromodiphenyl ether; 
BDE-47: 2,2',4,4'-Tetrabromodiphenyl ether; BDE-99: 2,2',4,4',5-Pentabromodiphenyl ether; HBCDD: 
hexabromocyclododecane); TEHP: tris(2-ethylhexyl) phosphate, EHDPP: 2-ethylhexyl diphenyl phosphate; TCPP: 
tris(1-chloro-2-propyl) phosphate; PCN 66/67: naphthalene congeners 667/67 (mixture of 1,2,3,4,6,7-HxCN 
and 1,2,3,5,6,7-HxCN); PCN-73: 73 (1,2,3,4,5,6,7-HpCN).; DEHP: bis(2-ethylhexyl)phthalate DINP: di-
isononylphthalate; ∑SCCPs: sum of short-chain chlorinated paraffins; ∑MCCPs: sum of mid-chain chlorinated 
paraffins) ...............................................................................................................89 

Table 11: Input data used to calculate the data presented in Figure 9 (section 3.3.2). (Kow = octanol –water 
partitioning coefficient; Koc = partition coefficient organic carbon - water, DT50 = estimated half-life from 
laboratory degradation tests) .........................................................................................90 

Table 12: Physico-chemical and toxicological data used for risk modelling purposes for the selected 
perfluoroalkyl substances. ............................................................................................91 

Table 13: Environmental and human health risk screening assessment of the exclusive application of PFAS 
present in sewage sludge to agricultural soils (PEC: predicted environmental concentration, RCR: risk 
characterisation ratio) .................................................................................................93 

Table 14: Environmental and human health risk screening assessment for PFAS, based on its present 
background concentrations observed in the environment along with sewage sludge applications to agricultural 
land (PEC: predicted environmental concentration, RCR: risk characterisation ratio) .............................94 

Table 15: Physico-chemical and toxicological data used for risk modelling purposes for the selected 
polyaromatic hydrocarbons. ..........................................................................................96 

Table 16: Environmental and human health risk screening assessment of the exclusive application of PAH 
present in sewage sludge to agricultural soils (PEC: predicted environmental concentration, RCR: risk 
characterisation ratio; BaP: benzo[a]pyrene, CHR: chrysene, BaA: benz[a]anthracene, BbFA: 
benzo[b]fluoranthene). ................................................................................................97 

Table 17: Environmental and human health risk screening assessment for PAH, based on its present 
background concentrations observed in the soil along with sewage sludge applications to agricultural land 

71 

 
 
(PEC: predicted environmental concentration, RCR: risk characterisation ratio; BaP: benzo[a]pyrene, CHR: 
chrysene, BaA: benz[a]anthracene, BbFA: benzo[b]fluoranthene). Note: due to the absence of EU-representative 
background PAH values in surface waters, no source contribution analysis could be done for this ecosystem 
compartment. ..........................................................................................................98 

Table 18: Physico-chemical and toxicological data used for risk modelling purposes for the selected PCDD/Fs 
and dioxin-like PCBs. ................................................................................................ 100 

Table 19: Environmental and human health risk screening assessment of the exclusive application of 2,3,7,8-
TCDD present in sewage sludge to agricultural soils (PEC: predicted environmental concentration, RCR: risk 
characterisation ratio) ............................................................................................... 101 

Table 20: Environmental and human health risk screening assessment for 2,3,7,8-TCDD, based on its present 
background concentrations observed in the soil along with sewage sludge applications to agricultural land 
(PEC: predicted environmental concentration, RCR: risk characterisation ratio) ................................. 102 

Table 21: Safe limit values for human consumption used for risk modelling purposes for the selected flame 
retardants. ........................................................................................................... 104 

Table 22: Physico-chemical and toxicological data used for risk modelling purposes for the selected flame 
retardants. ........................................................................................................... 105 

Table 23: Environmental and human health risk screening assessment of the exclusive application of flame 
retardants present in sewage sludge to agricultural soils (PEC: predicted environmental concentration, RCR: 
risk characterisation ratio; BDE-209: decabromodiphenyl ether, BDE-47: 2,2',4,4'-Tetrabromodiphenyl ether, 
BDE-99: 2,2',4,4',5-Pentabromodiphenyl ether and HBCDD: hexabromocyclododecane; TEHP: tris(2-ethylhexyl) 
phosphate; EHDPP: 2-ethylhexyl diphenyl phosphate TCPP: tris(1-chloro-2-propyl) phosphate (TCPP)) ...... 108 

Table 24: Physico-chemical and toxicological data used for risk modelling purposes for the selected 
alkylphenols. ......................................................................................................... 110 

Table 25: Environmental and human health risk screening assessment of the exclusive application of flame 
retardants present in sewage sludge to agricultural soils (PEC: predicted environmental concentration, RCR: 
risk characterisation ratio) .......................................................................................... 112 

Table 26: Physico-chemical and toxicological data used for risk modelling purposes for the selected 
polychlorinated alkanes. ............................................................................................ 114 

Table 27: Environmental and human health risk screening assessment of the exclusive application of short- 
and long-chain polychlorinated paraffins (SCCPs and MCCPs, respectively) present in sewage sludge to 
agricultural soils (PEC: predicted environmental concentration, RCR: risk characterisation ratio) ............. 115 

Table 28: Environmental and human health risk screening assessment for short- and long-chain 
polychlorinated paraffins (SCCPs and MCCPs, respectively), based on its present background concentrations 
observed in the environment along with sewage sludge applications to agricultural land (PEC: predicted 
environmental concentration, RCR: risk characterisation ratios) ................................................. 116 

Table 29: Physico-chemical and toxicological data used for risk modelling purposes for the selected 
polychlorinated naphthalene congeners 667/67 (mixture of 1,2,3,4,6,7-HxCN and 1,2,3,5,6,7-HxCN) and 73 
(1,2,3,4,5,6,7-HpCN). ................................................................................................ 117 

Table 30: Environmental and human health risk screening assessment of the exclusive application of the 
selected polychlorinated naphthalene (congeners 667/67 (mixture of 1,2,3,4,6,7-HxCN and 1,2,3,5,6,7-HxCN) 
and 73 (1,2,3,4,5,6,7-HpCN), respectively) present in sewage sludge to agricultural soils (PEC: predicted 
environmental concentration, RCR: risk characterisation ratio) .................................................. 119 

Table 31: Physico-chemical and toxicological data used for risk modelling purposes for the selected organotin 
compounds. .......................................................................................................... 120 

Table 32: Environmental and human health risk screening assessment of the exclusive application of the 
organotins Triphenyltin (TPT), Dibutyltin (DBT), Tributyltin (TBT) present in sewage sludge to agricultural soils 
(PEC: predicted environmental concentration, RCR: risk characterisation ratio) ................................. 122 

Table 33: Physico-chemical and toxicological data used for risk modelling purposes for bis(2-
ethylhexyl)phthalate (DEHP), and di-isononylphthalate (DINP). .................................................. 123 

72 

 
 
Table 34: Environmental and human health risk screening assessment of the exclusive application of bis(2-
ethylhexyl)phthalate (DEHP), and di-isononylphthalate (DINP) present in sewage sludge to agricultural soils 
(PEC: predicted environmental concentration, RCR: risk characterisation ratio) ................................. 125 

Table 35: Environmental and human health risk screening assessment for bis(2-ethylhexyl)phthalate (DEHP), 
and di-isononylphthalate (DINP) based on its present background concentrations observed in the environment 
along with sewage sludge applications to agricultural land (PEC: predicted environmental concentration, RCR: 
risk characterisation ratios) ......................................................................................... 126 

Table 36: Physico-chemical and toxicological data used for risk modelling purposes for the selected 
polydimethylsiloxanes. .............................................................................................. 127 

Table 37: Environmental and human health risk screening assessment of the exclusive application of 
decamethylcyclopentasiloxane (D5) present in sewage sludge to agricultural soils (PEC: predicted 
environmental concentration, RCR: risk characterisation ratio) .................................................. 128 

Table 38: Default parameter values and ranges applied for the uncertainty analysis of the life cycle 
assessment presented in section 6.4. .............................................................................. 135 

Table 39: Input-output disaggregated inventory for anaerobic digestion, including utilisation of the biogas in 
the gas engine. DM: dry matter. Values are expressed on a wet weight basis, unless otherwise stated (source: 
Tonini et al. (2019) .................................................................................................. 136 

Table 40: Substance mass transfer for dewatering process. TS: total solids; VS: volatile solids; Values are 
expressed on a wet weight basis, unless otherwise stated (source: Yoshida et al., 2015) ..................... 137 

Table 41: Input-output disaggregated inventory for dewatering of digestate/sludge. DM: dry matter. Values are 
expressed on a wet weight basis, unless otherwise stated (source: Yoshida et al., 2015) ..................... 137 

Table 42: Input-output disaggregated inventory for thermal treatment (mono- and co-incineration with 
municipal solid waste). CO-INC: co-incineration with MSW; DM: dry matter; MO-INC: mono-incineration. Values 
are expressed on a wet weight basis, unless otherwise stated (source: Tonini et al., 2019) .................. 138 

Table 43: Input-output disaggregated inventory for acidulation and other post-processing of the ash. DM: dry 
matter. Values are expressed on a wet weight basis, unless otherwise stated (source: Tonini et al., 2019) . 139 

Table 44: Input-output disaggregated inventory for composting. DM: dry matter. Values are expressed on a 
wet weight basis, unless otherwise stated (source: Tonini et al., 2019; electricity consumption from Boldrin et 
al., 2009). ............................................................................................................ 139 

Table 45: Input-output disaggregated inventory for lime stabilisation of sludge. DM: dry matter. Values are 
expressed on a dry weight basis, i.e. per t DM, unless otherwise stated (source: Teoh and Li, 2020) ........ 140 

Table 46: Input-output disaggregated inventory for landfill construction and operation. DM: dry matter. Values 
are expressed on a wet weight basis, unless otherwise stated (source: Olesen and Damsgaard, 2014). .... 140 

Table 47: Input-output disaggregated inventory for landfill gas oxidation in top cover over 20 years. DM: dry 
matter. Values are expressed on a wet weight basis, unless otherwise stated (source: Olesen and Damsgaard, 
2014).. ................................................................................................................ 141 

Table 48: Input-output disaggregated inventory for landfill leachate treatment. DM: dry matter. Values are 
expressed on a wet weight basis, unless otherwise stated (source: Olesen and Damsgaard, 2014).. ........ 142 

Table 49: Input-output disaggregated inventory for landfill gas combustion in gas engine. DM: dry matter. 
Values are expressed on a wet weight basis, unless otherwise stated (source: Olesen and Damsgaard, 2014)..
 ........................................................................................................................ 144 

Table 50: Substance mass transfer for open storage of biosolids. TS: total solids; VS: volatile solids; Values are 
expressed on a wet weight basis, unless otherwise stated (Holly et al., 2017 Willén eta l., 2016; source: Delre 
et al., 2019) .......................................................................................................... 145 

Table 51: .Input-output disaggregated inventory for use on farmland of digestate, sludge and compost. DM: 
dry matter. Values are expressed on a wet weight basis, unless otherwise stated (source: Tonini et al., 2019).
 ........................................................................................................................ 145 

73 

 
 
 
Annexes   

74 

 
 
 
13  Supplementary information – screening risk assessment 

13.1  Risk screening model calculations 

13.1.1  Soil model 

13.1.1.1  Initial concentration in soil after a single application 

Explanation of symbols 
DEPTHsoil 

Mixing depth of soil 

RHOsoil 

Bulk density of wet soil 

Application rate 

Application rate for the pollutant 

10 000 

Csoilinitial 

Area of 1 ha 

Initial concentration in soil 

13.1.1.2  Pollutant losses in soil 

[m] 

[kg mwwt

-3] 

[g ha-1] 

[m2] 

[mg kgwwt

-1] 

Equation 1 

0.20 

1700 

Input 

Equation 2 

Explanation of symbols 
kbiosoil 

First  order  rate  constant  for  biodegradation  in 
bulk soil 

[d-1] 

DT50soil20°C 

Half-life  for  biodegradation  of  the  pollutant  in 
soil at 20°C 

[d] 

The inferred degradation at 20°C for surface water and soil is given in Table 6 and Table 7 

Table  6:  Inferred  surface  water  degradation  rates  at  20°C  reported  in  the  LET  on  basis  of 
biodegradability screening results and FOCUSsw guidance 

Test result 
Readily biodegradable 
Readably  biodegradable,  failing  10  day 
window 
Inherently biodegradable 
Not biodegradable 

DT50 (Half-life, days) 
7.91 
26.36 

79.09 
10000 

75 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Table  7:  Inferred  soil  degradation  rates  at  20°C  reported  in  the  LET  on  basis  of  biodegradability 
screening results and FOCUSsw guidance 

Kpsoil (L kg-1) 

Readily 
biodegradable 
(DT50, days) 

< 100 

15.82 

> 100, < 1000 

158.2 

1000, 

> 
10000 

< 

1000 

Readably 
biodegradable, 
failing  10  day 
window 
(DT50, 
days) 
47.46 

474.6 

1000 

Inherently 
biodegradable 
(DT50, days) 

Not 
biodegradable 
(DT50, days) 

158.2 

1000 

1000 

1000 

1000 

1000 

Kpsoil = Koc * fraction organic carbon in standard soil (0.02) 

Equation 3 

Explanation of symbols 

kaslair 

kaslsoil 

Partial  mass  transfer  coefficient  at  air-side  of 
the air-soil interface 

[m d-1] 

90.72 

Partial  mass  transfer  coefficient  at  soil-side  of 
the air-soil interface 

[m d-1] 

ECHA 

See 
guidance 
Equation R.16-59 

R.16 
(2016), 

Kair-water 

Air-water equilibrium distribution constant 

[m3 m-3] 

Equation 12 

Ksoil-water 

Soil-water partitioning coefficient 

[m3 m-3] 

Equation 10 

DEPTHsoil 

Mixing depth of soil 

kvolat 

Pseudo first-oder rate constant for volatilisation 
from soil 

0.20 

[m] 

[d-1] 

Equation 4 

Explanation of symbols 

F infsoil 

RAINrate 

Fraction of rain water that infiltrates into soil 

[-] 

0.25 

Rate of wet precipitation (700 mm year-1) 

[m d-1] 

1.925E-03 

Ksoil-water 

Soil-water partitioning coefficient 

[m3 m-3] 

Equation 10 

DEPTHsoil 

Mixing depth of soil 

kleach 

Pseudo  first-order  rate  constant  for  leaching 
from soil layer 

0.20 

[m] 

[d-1] 

76 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Equation 5 

Explanation of symbols 
kvolat 

Pseudo first-oder rate constant for volatilisation 
from soil 

[d-1] 

1/Equation 3 

kleach 

kbiosoil 

k 

Pseudo  first-oder  rate  constant  for  leaching 
from soil layer 

[d-1] 

Equation 4 

First  order  rate  constant  for  biodegradation  in 
bulk soil 

[d-1] 

Equation 2 

First  order  rate  constant  for  removal  from  top 
soil 

[d-1] 

13.1.1.3  Maximum concentration in soil after multiple applications 

Equation 6 

Explanation of symbols 
Csoilinitial 

Initial concentration in soil 

[mg kgwwt

-1] 

Equation 1 

k 

Napp 

Csoilmax 

First  order  rate  constant  for  removal  from  top 
soil 

[d-1] 

Equation 5 

Number of application events  

[-] 

1, 10, or 100 

Maximum concentration in soil 

[mg kgwwt-1] 

13.1.1.4  Time-weighted average concentration in soil 

Equation 7 

Explanation of symbols 
Csoilmax 

Maximum concentration in soil 

[mg kgwwt

-1] 

Equation 6 

k 

t 

First  order  rate  constant  for  removal  from  top 
soil 

[d-1] 

Equation 5 

Time period  

[d] 

Soil organisms: 30; 
human  food intake 
180(1) 

77 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
TWACsoil(t) 

Time  weighted  average  concentration  in  soil, 
over a period t 

[mg kgwwt-1] 

(1)  In accordance with the EU-TGD (2003) and REACH R.16 guidance (2016), the time weighted average 
of 30 days has been considered, whereas for the modelling of pollutant transfer from soils to crops 
for human intake a 180 day period is used.  

13.1.1.5  Porewater concentration 

Where: 

Equation 8 

Equation 9 

Equation 10 

Equation 11 

Equation 12 

Equation 13 

Explanation of symbols 
VP(TEMPenv) 

Vapour  Pressure  at  environmental  temperature 
(12°C) 

[Pa] 

Input 

SOL(TEMPenv) 

Solubility in water at environmental temperature 
(12°C) 

[mg L-1] 

Input 

MW 

R 

TEMP 

Koc 

Focsoil 

Fairsoil 

Molecular weight 

Gas constant 

[g mol-1] 

Input 

[Pa  m³  mol-1 
K-1] 

8.314 

Temperature at the air-water interface 

[K] 

Partition coefficient organic carbon-water 

[L kg-1] 

Fraction organic carbon in the soil  

Fraction air in soil 

285 

Input 

0.02 

0.2 

0.2 

0.2 

[-] 

[-] 

[-] 

[-] 

Fwatersoil 

Fraction water in soil 

Fsolidsoil 

Fraction solid in soil 

RHOsolid 

HENRY 

Bulk density of solids 

Henry’s law constant 

[kg m-3] 

2500 

[Pa m3 mol-1] 

78 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Kair-water 

Kpsoil 

Ksoil-water 

Air-water partitioning coefficient 

Solids-water partition coefficient in soil 

Soil-water partitioning coefficient 

[-] 

[L kg-1] 

[mg m-3] 

The concentration in porewater is then calculated. 

Equation 14 

Explanation of symbols 
Clocalcrop transfer 

Time  weighted  average  concentration  in  soil 
(180 days) 

[mg kgwwt

-1] 

Equation 9 

RHOsoil 

Ksoil-water 

Cliq 

Bulk density of solids 

[kg m-3] 

1700 

Soil-water partitioning coefficient 

[mg m-3] 

Equation 10 

Concentration in soil porewater 

[mg L-1] 

13.1.2  Water model 

13.1.2.1  Input into surface water via runoff/drainage/erosion 

As in the FOCUS Step 2 model, the LET runoff/drainage/erosion event is driven by a rainfall event four days 
after the final application. 

Equation 15 

Explanation of symbols 
Application rate 

Pollutant application rate 

[g ha-1] 

Input 

DT50soil 

Half-life of the pollutant in soil 

[days] 

Input 
13.1.1.2) 

(section 

Eq  Rate  Runoff 
Event 

Equivalent  rate  for  runoff  at  the  time  of  the 
runoff event 

[g ha-1] 

Equation 16 

Explanation of symbols 
Eq  Rate  Runoff 
Event 

Equivalent  rate  for  runoff  at  the  time  of  the 
runoff event 

[g ha-1] 

Equation 15 

79 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Runoff % 

Runoff percentage 

FW Ratio 

Ratio of field to waterbody 

Input Runoff 

Input via runoff 

[%] 

[-] 

[mg m-2] 

Default 5% 

10 

Equation  16  calculates  the  amount  of  co-formulant  that  will  be  inputted  into  the  waterbody  via 
runoff/drainage/erosion  following  a  rainfall  event.  However,  the  fraction  of  co-formulant  entering  the 
waterbody in the water phase and in the sediment phase will be dependent on the soil adsorption (KOC) of 
the  substance.  The  fraction  entering  the  waterbody  in  the  water  phase  via  runoff/drainage/erosion  is 
calculated according to the soil adsorption (Koc) of the substance. 

Explanation of symbols 
Water Depth 

Depth of the surface water 

[cm] 

Eff Sed Depth 

Effective sediment depth of the surface water 

[cm] 

RHOsed 

Sediment bulk density 

Sediment organic carbon content 

[kg L-1] 

[%] 

OC 

Koc 

Partition coefficient organic carbon - water 

[L kg-1] 

User input 

Equation 17 

30 

1 

0.8 

5 

Fwaterphaserunoff 

Fraction  of  substance  entering  in  water  phase 
via runoff 

[-] 

The total loading to the waterbody entering in the water phase is calculated.  

Equation 18 

Explanation of symbols 

Fwaterphaserunoff 

Fraction  of  substance  entering  in  water  phase 
via runoff 

[-] 

Equation 17 

Input Runoff 

Total input via runoff 

[mg m-2] 

Equation 16 

Input Runoffsw 

Runoff input via water phase 

[mg m-2] 

Finally, the maximum local concentration in surface water is calculated. 

Equation 19 

Explanation of symbols 

80 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Input Runoffsw 

Runoff input via water phase 

[mg m-2] 

Equation 18 

Water Depth 

Depth of the surface water 

[cm] 

30 

Cwaterinitial 

Local concentration in surface water after initial 
application 

[µg L-1] 

To  calculate  the  pollutant  by  fish  in  the  surface  water,  it  is  assumed  the  diet  of  the  aquatic  predator  is 
continuously exposed to the 180-day time weighted average following the runoff/erosion event at day 4 after 
sludge  application.  Both  surface  water  residence  time  and  (bio)degradation  contribute  to  removal  of  the 
element/substance from surface water.  

Equation 20 

Explanation of symbols 

DT50biowater 

Half-life  for  biodegradation  in  water-sediment 
phase 

[d-1] 

Input 

kres 

ktotal 

First  order  rate  constant  for  residence  time  in 
water body 

[d-1] 

0.025 
[default 
residence  time  of 
40 days] 

first order rate constant for removal from water 
phase 

[d-1] 

Equation 21 

Explanation of symbols 
Cwaterinitial 

Initial concentration in soil 

[µg L-1] 

Equation 19 

k 

First  order  rate  constant  for  removal  from  top 
soil 

[d-1] 

Equation 20 

Napp 

Number of application events  

[-] 

input 

Cwatermax 

Maximum concentration in soil 

[µg L-1] 

Equation 22 

Explanation of symbols 
Cwatermax 

Maximum concentration in soil 

[µg L-1] 

Equation 19 

ktotal 

First order rate constant for removal from water 
phase 

[d-1] 

Equation 20 

81 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
t 

Time period  

[d] 

human  food intake 
180 

TWACwater 

Time weighted average concentration in surface 
water, over a period of 180 days 

[µg L-1] 

13.1.3  Human via food intake 

13.1.3.1  Fish concentration 

The  bioconcentration  factor  (BCFfish)  and  the  biomagnification  factor  (BMF)  are  used  to  estimate  the 
concentration  of  a  pollutant  in  the  food  (fish)  of  fish-eating  predators,  that  in  turn  are  assumed  to  be  the 
human  food  source.  When  a  measured  BCFfish  is  available  (e.g.  for  some  pollutants  assessed  in  step  2 
analysis),  it  is  used  directly.  If  experimental  data  are  not  available,  the  BCFfish  can  be  predicted  from  the 
relationship between Kow and BCF derived by Veith et al. (1979).  
For substances with a log Kow in between 2 and 6: 

For substances with a log Kow higher than 6:  

Equation 23 

Equation 24 

Explanation of symbols 
Kow 

Octanol-water partitioning coefficient 

[-] 

input 

BCFfish 

Bioconcentration for fish on wet weight basis 

[L kgwet fish -1] 

The  biomagnification  factor  in  fish  (BMF)  is  determined  from  the  measured  BCF  (if  available)  or  Kow  with 
default values summarised in  

Table 8: Default BMF values for organic susbtances (ECHA R.16 guidance R.16.5.3.5) 

Log Kow 

<4.5 

4.5-5 

5-8 

8-9 

>9 

BCFfish 

<2000 

2000 – 5000 

> 5000 

2000 – 5000 

< 2000 

BMF 

1 

2 

10 

3 

1 

It is then assumed that 50% of the predator’s diet comes from the local scale and 50% is assumed to come 
from the regional area.  

82 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Equation 25 

Explanation of symbols 
TWACwater 

Time weighted average concentration in surface 
water, over a period of 180 days 

[µg L-1] 

Equation 22 

PECregional 

BCFfish 

BMF 

Cfish 

Regional  background  concentration  in  surface 
water 

[µg L-1] 

input 

Bioconcentration for fish on wet weight basis 

[L kgwet fish -1] 

Biomagnification factor in fish 

Table 8 

Concentration in fish 

[µg kgwwt-1] 

13.1.3.2  Biotransfer from soil to plants  

The approach applied is described in the EU technical guidance document on risk assessment  (ECHA, 2003). 
Plant products form a  major part of the  food products for humans and  cattle. Contamination of  plants will 
therefore have significant influence on the exposure of humans. When trying to predict concentrations in plant 
tissues, one will immediately encounter several important conceptual problems: 

• there are hundreds of different plant species forming the heterogenous group of food crops. 

Furthermore, varietal differences can also account for large differences; 

• different tissues from plants are consumed (roots, tubers, fruit, leaves); 

• crops differ in pollutant exposure, many crops are for instance grown in greenhouses; 

•  crops  can  be  exposed  through  uptake  from  the  soil,  but  also  through  gas  uptake  and  aerial 
deposition. 

From  the  above  it  may  be  clear  that  a  modelling  approach  can  only  give  a  rough  approximation  of  the 
concentrations in  plants. To  account for the predicted variety in plant products, it is  proposed to  distinguish 
between tuberous plants and leaf crops. 

Uptake from soil is, in general, a passive process governed by the transpiration stream of the plant (in case of 
accumulation in leaves) or physical sorption (in case of roots). Uptake into the leaves from the gaseous phase 
can be viewed as a passive process, in which the leaves components (air, water, lipids) equilibrate with the air 
concentration.  Kow  and  Kaw  (the  air-water  partitioning  coefficient)  are  used  to  assess  the  distribution 
between the air and the plant. It is proposed to use the modelling approach of Trapp and Matthies (1995) to 
estimate levels in leaves and roots due to uptake from soil and air. 

It should be noted that the applied model is a simplified, generic representation of plant uptake. This model 
cannot give more than an indication for levels that may occur in plants in the field. Only the concentrations in 
leaf and root tissue are estimated, fruit is not accounted for. Several plant- specific parameters are required 
for  the  model.  As  there  are  many  different  plant  species  acting  as  food  crops  for  humans  and  cattle,  an 
average  or  typical  plant  definition  is  not  scientifically  feasible.  Aerosol  deposition  is  not  considered  in  the 
model. 

The partitioning between water and plant tissue is a key property for the fate of compounds in the soil-plant-
air  system.  This  partitioning  is  assumed  to  be  based  on  hydrophobic  sorption  to  plant  lipids.  The  Kow  is 
corrected  slightly  for  the  differences  between  plant  lipids  and  octanol.  The  Kplant-water  can  than  be 
calculated. 

Equation 26 

83 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Explanation of symbols 
Fwater 

Volume fraction water in plant tissue 

Flipid 

Kow 

b 

Volume fraction lipids in plant tissue 

Octanol-water partitioning coefficient 

Correction  for  differences  between  plant  lipid 
and octanol 

[-] 

[-] 

[-] 

[-] 

0.65 

0.01 

input 

0.95 

Kplant-water 

partition  coefficient  between  plant  tissue  and 
water  

[(mg.m plant-3)/(mg.m water-3)] 

When a measured biotransfer factor is available (e.g. for  some pollutants assessed in  step 2 analysis), it is 
used directly. Otherwise, concentration in root tissue is mainly governed by physical sorption, and is computed. 

Equation 27 

Explanation of symbols 
Kplant-water 

partition  coefficient  between  plant  tissue  and 
water  

[(mg.m  plant-
3)/(mg.m 
water-3)] 

Equation 26 

Cliq 

RHOplant 

Croot 

Concentration in soil porewater 

[mg L-1] 

Equation 14 

Bulk density of plant tissue 

[kg m-3] 

700 

Concentration in root tissue of plant 

[µg kgwwt-1] 

When a measured biotransfer factor is available (e.g. for  some pollutants assessed in  step 2 analysis), it is 
used directly. Otherwise, the concentration in leaf crops is computed. 

Equation 28 

[-] 

[-] 

input 

Equation 14 

Explanation of symbols 
Kow 

Octanol-water partitioning coefficient 

Air-water partitioning coefficient 

Kaw 

Cliq 

Cleaf 

Concentration in soil porewater 

[mg L-1] 

Equation 14 

Concentration in leaf tissue of plant 

[µg kgwwt-1] 

84 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
13.1.3.3  Drinking water 

Drinking water can be prepared from surface water or from groundwater. Groundwater can be contaminated 
through leaching from the soil surface, surface water can be polluted through direct or indirect emission. The 
drinking  water  module  in  the  present  model  assumes  a  complete  removal  of  suspended  particles  from 
surface water. 

Equation 
29 

Explanation of symbols 
Fpur 

Purification factor for surface water 

[-] 

10 (default value) 

TWACwater(180 
days) 

Time weighted average concentration in surface 
water, over a period of 180 days 

[µg L-1] 

Equation 22 

Cdrw 

Concentration in drinking water (wet weight) 

[mg L-1] 

13.1.3.4  Biotransfer to meat and milk 

Lipophilic substances are known to accumulate in meat, and can be subsequently transferred to milk. Cattle 
can  be  exposed  to  substances  in  grass  (or  other  feed)  with  adhering  soil,  drinking  water,  and  through 
inhalation of air. When a measured Biotransfer factor is available (e.g. for some pollutants assessed in step 2 
analysis),  it  is  used  directly.  Biotransfer  factors  can  be  defined  as  the  steady-state  concentration  in  meat, 
divided by the daily intake of the substance. Travis and Arms (1988) calculated biotransfer factors for cow's 
meat and milk by log-linear regression on a number of substances (28 for milk and 36 for beef). Even though 
the theoretical background is limited, these factors provide a useful tool in risk assessment. It is proposed to 
use the same exposure estimates for air and crops which have been derived for human exposure for cattle, 
and the same soil concentration as for plants. It should be noted that no distinction is made between different 
milk products like cheese or yoghurt. For all dairy products, the concentration in milk is used. 

The  estimation  can  be  used  for  substances  with  a  log  Kow  range  of  1.5  -  6.5.  Outside  this  range,  the 
maximum or minimum Kow value should be used. 

Equation 30 

Explanation of symbols 
Kow 

Octanol-water partitioning coefficient 

[-] 

input 

BTFmeat 

Biotransfer factor for meat 

[(mg kg-1)/(mg d-1)] 

The BTF for milk was derived on data of 28 organic compounds. It should be noted that the uncertainty in this 
estimation  is  considerable.  The  estimation  can  be  used  for  substances  with  a  log  Kow  range  of  3  -  6.5. 
Outside this range, the maximum or minimum Kow value should be used. 

85 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Explanation of symbols 
Kow 

Octanol-water partitioning coefficient 

[-] 

input 

BTFmilk 

Biotransfer factor for milk 

[(mg kg-1)/(mg d-1)] 

Equation 31 

The concentrations in meat and milk can be calculated by applying the biotransfer factors and summing the 
contributions from soil, grass, and drinking water (air contributions have been assumed to be absent). 

Equation 32 

Equation 33 

Explanation of symbols 
BTFmeat 

Biotransfer factor for meat 

BTFmilk 

Biotransfer for milk 

[(mg  kg-1)/(mg 
d-1)] 

Equation 30 

[(mg  kg-1)/(mg 
d-1)] 

Equation 31 

Cgrass 

ICgrass 

Concentration in grass (wet weight) 

[mg kgwet weight -1]  Equation 28 

Daily intake of grass 

[kg d-1] 

67.6 

TWACsoil(180 days) 

Concentration in soil (wet weight) 

[mg kgwet weight -1]  Equation 9 

ICsoil 

Cdrw 

ICdrw 

Cmeat 

Cmilk 

Daily intake of grass 

[kg d-1] 

0.46 

Concentration in drinking water (wet weight) 

[mg L-1] 

Equation 29 

Daily intake of drinking water 

[L d-1] 

55 

concentration in meat (wet weight) 

[mg kgwet weight-1] 

concentration in milk(wet weight) 

[mg kgwet weight-1] 

13.1.3.5  Aggregated consumer intake 

If concentrations in the intake media are calculated, the total daily intake of humans can be estimated from 
the daily intake rate of each medium by summing the contribution of each medium. 

Equatio
n 34 

Explanation of symbols 

Cfish 

Concentration in fish 

[µg kgwwt-1] 

Equation 25 

86 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Ifish 

Croot 

Iroot 

Cleaf 

Ileaf 

Cmeat 

Imeat 

Cmilk 

Imilk 

Cdrw 

Idrw 

bw 

Daily human intake of fish 

[kgwwt d-1] 

0.115 

Concentration in root 

[µg kgwwt-1] 

Equation 27 

Daily human intake of root vegetables 

[kgwwt d-1] 

0.384 

Concentration in leaf  

[µg kgwwt-1] 

Equation 28 

Daily human intake of leaf vegetables 

[kgwwt d-1] 

1.2 

concentration in meat (wet weight) 

[µg kgwwt-1] 

Equation 32 

Daily human intake of meat 

[kgwwt d-1] 

0.301 

Concentration in milk 

[µg kgwwt-1] 

Equation 33 

Daily human intake of milk 

[kgwwt d-1] 

0.561 

Concentration in drinking water  

[mg L-1] 

Equation 29 

Daily human intake of drinking water 

[L d-1] 

2 

70 

Body weight adult 

Human Intake 

Total daily human intake 

[mg d-1] 

[mg kg-1] 

87 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
13.2  Model input data for results reported in main text 

The  model  input  data  used  to  calculate  the  data  presented  in  Figure  4  and  Figure  5  (section  3.3.1.3)  is 
presented in Table 9. The data used in this assessment originates from data repositories, and has not been 
verified by JRC on a case-by-case basis, introducing additional uncertainties to the outcomes presented (see 
section 1.2.2.1 on methodology). 

Table 9: Input data used to calculate the data presented in Figure 4 and Figure 5 (section 3.3.1.3). (Kow = octanol –water 
partitioning  coefficient;  Koc  =  partition  coefficient  organic  carbon  –  water,  DT50  =  estimated  half-life  from  laboratory 
degradation tests; SLHC = Safe limit for human consumption) 

The model input data used to calculate the data presented in Figure 9 (section 3.3.2) is presented in Table 11. 
The  data  used  in  this assessment  originates from  data  repositories,  and has not  been  verified  by  JRC  on  a 
case-by-case  basis,  introducing  additional  uncertainties  to  the  outcomes  presented  (see  section  1.2.2.1  on 
methodology). 

88 

 
 
 
 
 
 
 
 
 
Table 10: Input data used to calculate the data presented in  Figure 6 (section 3.3.2) (Kow = octanol –water partitioning 
coefficient;  Koc  =  partition  coefficient  organic  carbon  -  water,  DT50  =  estimated  half-life  from  laboratory  degradation 
tests;  SLHC  =  Safe 
limit  for  human  consumption;  BDE-209:  decabromodiphenyl  ether;  BDE-47:  2,2',4,4'-
Tetrabromodiphenyl ether; BDE-99: 2,2',4,4',5-Pentabromodiphenyl ether; HBCDD: hexabromocyclododecane); TEHP: tris(2-
ethylhexyl)  phosphate,  EHDPP:  2-ethylhexyl  diphenyl  phosphate;  TCPP:  tris(1-chloro-2-propyl)  phosphate;  PCN  66/67: 
naphthalene  congeners  667/67  (mixture  of  1,2,3,4,6,7-HxCN  and  1,2,3,5,6,7-HxCN);  PCN-73:  73  (1,2,3,4,5,6,7-HpCN).; 
DEHP:  bis(2-ethylhexyl)phthalate  DINP:  di-isononylphthalate;  ∑SCCPs:  sum  of  short-chain  chlorinated  paraffins;  ∑MCCPs: 
sum of mid-chain chlorinated paraffins) 

89 

concentration in sludge [mg kg-1 dw]Water solubility [mg L-1]Vapour Pressure [Pa]Log Kow [-]Koc [L kg1]DT50 in soil [days]SLHC [mg kg-1 body weight day-1]Perfluorooctanoic acid (PFOA)0.0037895004.25.3114.8154527292.46.29E-07Perfluorohexansulfonic acid (PFHxS)0.000625230058.95.173981.072527292.46.29E-07Perfluorononanoic acid (PFNA)0.0026464.085.12.4245.4709527292.46.29E-07Perfluorooctane Sulfonate (PFOS)0.046465200.000336.436309.573527292.41.57E-07benzo(b)fluoranthene1.9190.00120.0000676.12140000012410.000034chrysene2.020.0028.4E-075.7320000012410.000034Benzo[a]pyrene1.4750.00387.3E-076.589000012410.000034Benzo[a]anthracene1.8320.0140.0000285.6179000012410.0000342,3,7,8-TCDD0.000010.01932E-076.8398107236502.86E-10BDE-2090.50.0625.9E-099.714000008610.68BDE-470.10.0250.0000636.579800003426.88E-05BDE-990.10.250.0000157.39800003421.68E-06HBCDD0.10.00863.3E-065.47220000639.79E-05TEHP1.25.10.000199.4262000043200.1EHDPP0.510.000345.7395003000.036TCPP116000.272.68580475200.014-nonylphenol105.70.35.419.116.50.0054-nonylphenol ethopxylates11.050.0000185.30103251016.50.0134-octylphenol112.60.234.10037110000146.7E-08SCCPs1000.330.0216.7336511.6527292.40.0023MCCPs1000.0160.000277.2855066.7527292.40.036Triphenyltin0.150.83.716667501187.2527292.40.00025Dibutyltin0.3200.161.5641686.941200.00025Tributyltin0.15.348.54.06333331622.78527292.40.00025DEHP500.0030.0000347.51650001470.05DINP300.00060.000068.83100003000.05Decamethylcyclopentasiloxane (D5)10.80.01722.78.09147910.812.60.25PCN-65/660.000000040.000110.0016.7336511.636502.86E-10PCN-730.0000000680.000040.000266.6279254.436502.86E-10 
 
 
Table 11: Input data used to calculate the data presented in  Figure 9 (section 3.3.2). (Kow = octanol –water partitioning 
coefficient;  Koc  =  partition  coefficient  organic  carbon  -  water,  DT50  =  estimated  half-life  from  laboratory  degradation 
tests) 

13.3  Results – Step 2 risk assessment 

13.3.1  Perfluoroalkyl substances (PFAS) 

13.3.1.1  Background and selection of compounds 

Perfluoroalkyl substances (PFAS) are a  group of widely  used man-made organic chemical substances. PFAS 
are  released  into  the  environment  from  direct  and  indirect  sources,  for  example,  from  professional  and 
industrial  facilities using  PFAS, during  use  of  consumer  products  (e.g.  cosmetics,  clothing  or  ski  waxes)  and 
from food contact materials. 
PFAS contain alkyl groups on which all or many of the hydrogen atoms have been replaced with fluorine. Well 
known PFAS contain fully fluorinated carbon chains of various chain lengths attached to a functional group, 
like carboxylic or sulfonic acids. 
The fluorine-carbon bonds are extremely stabile conferring these substances with very high chemical stability. 
Even if all releases of PFAS would cease tomorrow, they would continue to be present in the environment, and 
humans, for generations to come. Certain PFAS are  known to accumulate in the bodies of living things and 

90 

Substance nameconcentration in sludge [mg kg-1 dw]Water solubility [mg L-1]Vapour Pressure [Pa]Log Kow [-]Koc [L kg1]DT50 in soil [days]PNECsoil [mg kg-1]Coronene2.5E-011.0E-101.9E-107.51.0E+055272924.6E-04Perfluorononanoic acid (PFNA)2.6E-03464.085.1E+002.42.5E+025272921.0E-05Perfluorooctane Sulfonate (PFOS)4.6E-025.2E+023.3E-046.46.3E+035272922.2E-04Benzo[ghi]perylene3.5E-015.0E-043.7E-084.44.1E+045272923.0E-03Dibenzo[a,h]pyrene2.3E-011.0E-105.6E-097.34.3E+055272922.2E-032,3,7,8-TCDD1.0E-051.9E-022.0E-076.84.0E+0636502.2E-07MCCPs1.0E+021.6E-022.7E-047.28.6E+055272921.2E+00SCCPs1.0E+023.3E-012.1E-026.73.4E+055272921.2E+00Dibenzo[a,l]pyrene5.9E-021.0E-105.4E-097.51.9E+055272929.5E-04Oxipurinol1.6E+021.0E-107.9E-07-1.31.5E+02161.6E-01Fipronil sulfone3.9E-025.4E-012.9E-072.51.7E+02163.4E-05Traseolide (ATII)3.4E-011.0E-106.0E-035.65.4E+031586.9E-04Lauryl diethanolamide3.4E+011.0E-101.9E-053.21.3E+03162.3E-02Ciprofloxacin6.2E+007.5E+011.0E-070.13.1E+02164.0E-03N,N-Dimethyldodecylamine1.2E+012.6E+005.6E-014.92.7E+03165.3E-03Ofloxacin1.2E+003.8E+029.8E-06-0.24.8E+02165.1E-04Permethrin3.3E-015.5E-032.1E-066.16.3E+0415824.5E-04Triclocarban1.1E+017.4E-013.2E-073.24.1E+03161.3E-03Beta-sitosterol7.1E+015.8E-023.3E-064.65.9E+045272921.0E-01Campesterol1.0E+021.0E-107.9E-068.99.6E+045272929.5E-02Candersartan0.8532905580.144.97E-074.5719.679163.96E-05Benzalkonium chloride1.0E+022.0E+043.9E-082.74.0E+045272926.4E-02Stigmasterol3.2E+021.0E-102.5E-068.996996.85272920.082168Telmisartan8.8E+009.0E-025.9E-094.71.3E+0547461.2E-03Cholesterol9.0E+021.0E-109.9E-068.39.4E+045272921.4E-01Dipyridamol5.9E+001.0E-106.3E-082.31.9E+02161.8E-05 
 
 
 
cause  toxic  effects.  Certain  PFAS  are  toxic  for  reproduction  and  can  harm  the  development  of  foetuses. 
Several PFAS have been demonstrated to cause cancer. Some PFAS are also suspected of interfering with the 
human endocrine (hormonal) system (ECHA, 2021). 
They can be  divided into the groups of perfluorinated  sulfonic acids (PFSAs), perfluorinated carboxylic acids 
(PFCAs),  fluorotelomer  alcohols,  high-molecular  weight  fluoropolymers  and 
low-molecular  weight 
perfluoroalkanamides. Perfluorooctane sulfonic acid (PFOS) and perfluorooctanoic acid (PFOA), often referred 
to  as  reference  or  key  substances  for  the  first  two  groups,  have  been  most  intensively  studied  from  a 
toxicological standpoint.  
Since  2009,  PFOS  and  its  derivatives  have  been  included  in  the  international  Stockholm  Convention  to 
eliminate  their  use.  PFOS  has  already  been  restricted  in  the  EU  for  more  than  10  years,  under  the  EU’s 
Persistent  Organic  Pollutants  Regulation.  In  addition,  the  Stockholm  Convention  regulates  the  global 
elimination  of  PFOA,  its  salts  and  PFOA-related  compounds.  PFOA  has  been  banned  under  the  POPs 
Regulation since July 2020. Perfluorohexane sulfonic acid (PFHxS), its salts and PFHxS-related compounds are 
being considered for inclusion in the Stockholm Convention and consequent global elimination. 

13.3.1.2  Safe limit values for human consumption 

Safe limit values for PFAS have recently (2020) been revised and further reinforced by EFSA. Compared to the 
previous assessment in 2012, tolerable daily intake values for PFAS have been reduced by approximately two 
to three orders of magnitude. Based on several similar effects in animals, toxicokinetics and observed levels 
in  human  blood,  the  EFSA  Panel  on  Pollutants  in  the  Food  Chain  (CONTAM  Panel)  performed  a  recent  risk 
assessment for the sum of four PFASs: PFOA, perfluorononanoic acid (PFNA), PFHxS and PFOS ((EFSA CONTAM 
Panel)  EFSA  Panel  on  Contaminants  in  the  Food  Chain  et  al.,  2020).  Longer  chain  PFCAs  (C9-C14)  are  not 
known to be intentionally used in the EU, though they can be present as impurities during the manufacture of 
other  PFAS.  The  above-mentioned  four  PFAS  made  up  approximately  half  of  the  lower  bound  exposure  to 
those  PFASs  for  which  occurrence  data  were  available,  the  remaining  contribution  being  primarily  from 
perfluorobutyrate  and  perfluorohexanoic  acid,  two  PFAS  with  a  short  half-life.  Since  physico-chemical  and 
toxicological data are available for these compounds, these 4 PFAS (hereafter PFAS 4: PFOA, PFNA, PFHxS and 
PFOS) have been selected for the screening risk assessment. 
A tolerable weekly intake (TWI) of 4.4 ng/kg bw per week was established for the sum of PFOA, PFNA, PFHxS 
and PFOS ((EFSA CONTAM Panel) EFSA Panel on Contaminants in the Food Chain et al., 2020). Hence, a safe 
limit of value of 0.63 ng/kg bw per day has been used for PFAS4 in this assessment 

13.3.1.3  Concentrations observed in sludge 

The median PFOA (3.8 µg kg-1 DM), PFNA (2.6 µg kg-1 DM) and PFOS (46.5 µg kg-1 DM) concentrations reported 
by Tavazzi et al. (2012) have been retained in the assessment. These values fall within the ranges of studies 
of other studies (Gómez-Canela et al., 2012; Brambilla et al., 2016; Blytt and Stang, 2018; Fernandes et al., 
2019;  Kärrman  et  al.,  2019;  Rigby  et  al.,  2021).  The  concentration  value  for  PFHxS  (0.62  µg  kg-1  DM)  was 
taken from Gómez-Canela et al. (2012).  

13.3.1.4  Model input values 

Table  12:  Physico-chemical  and  toxicological  data  used  for  risk  modelling  purposes  for  the  selected  perfluoroalkyl 
substances. 

PFOA 

PFHxS 

PFNA 

PFOS 

Concentration  in  sludge 
(mg-1 kg-1 dry matter)(1) 

6.7e-3 

1.4e-3 

4.6e-3 

66.4e-3 

(Tavazzi et al., 
2012) 

(Gómez-Canela 
et al., 2012) 

(Tavazzi et al., 
2012) 

(Tavazzi et al., 
2012) 

Molecular weight (g mol-1) 

414.07 

400.11 

464.08 

500.13 

(ECHA, 2013) 

(ECHA, 2017a) 

(core database) 

(core database) 

91 

 
 
 
 
 
 
 
 
 
 
Water solubility (mg L-1) 

9500 

2300 

0.88 

520 

(ECHA, 2013) 

(ECHA, 2017a) 

(core database) 

(ECHA, 2017a) 

Vapour pressure (Pa) 

4.2 

58.9 

5.1 

3.3e-4 

(ECHA, 2013) 

(ECHA, 2017a) 

(core database) 

(ECHA, 2017a) 

Kow (log 10) 

5.3 

5.17 

2.4 

6.43 

(ECHA, 2013) 

(ECHA, 2017a) 

(ECHA, 2017a) 

(ECHA, 2017a) 

Koc (L kg-1) 

114.8 

3981 

245 

6310 

(ECHA, 2017a) 

(ECHA, 2017a) 

(ECHA, 2017a) 

(ECHA, 2017a) 

PNECaqua (µg L-1) 

0.1 

0.87 

0.58 

0.002 

(Ankley et al., 
2021) 

(core database) 

(core database) 

PNECsoil (mg kg-1 ww) 

1.13e-2 

1.13e-2 

1.13e-2 

2.61e-3 

(based on 
NOEC of 1 mg 
kg-1 wet soil 
(Ankley et al., 
2021), 
assessment 
factor of 100) 

(based on 
NOEC of 1 mg 
kg-1 wet soil 
(Ankley et al., 
2021), 
assessment 
factor of 100) 

(based on 
NOEC of 1 mg 
kg-1 wet soil 
(Ankley et al., 
2021), 
assessment 
factor of 100) 

(core database) 

0.63e-6 for the sum of PFOA, PFHxS, PFNA, and PFOS 

(EFSA Panel on Pollutants in the Food Chain et al., 2020) 

limit  values 

Safe 
human 
body weight day-1)  

for 
intake  (mg  kg-1 

Half-life in soil (days) 

not 
biodegradable 

not 
biodegradable 

not 
biodegradable 

not 
biodegradable 

Half-life 
(degradation, days) 

in 

water 

not 
biodegradable 

not 
biodegradable 

not 
biodegradable 

not 
biodegradable 

(ECHA, 2017a) 

(ECHA, 2017a) 

Regional  background  in 
soil (mg kg-1 dry matter)(2) 

Regional  background  in 
surface water (µg L-1) 

Atmospheric 
deposition (mg m-2 d-1) 

dry 

0.86e-3 

0 

0.62e-3 

1.2e-3 

(Göckener et al., 2021) 

6.5e-2 

5.3e-4 

1.45e-3 

1.4e-2 

(EMPODAT, 2021) 

1.55 

1.66 

0.34 

7.1 

(Johansson et al., 2018) 

Atmospheric 
deposition (ng L-1) 

wet 

0.57 

0.79 

0.79 

0.59 

(Johansson et al., 2018) 

BCFfish-water (L kg-1ww) 

87 

257 

4570 

1862 

(Burkhard, 2021) 

92 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
(mg  kg-1 
BCFshoot-soil 
plant  ww)/(mg  kg-1  soil 
ww)(3) 

(mg  kg-1 
BCFroot-soil 
plant  ww)/(mg  kg-1  soil 
ww)(3) 

BTFmeat-grass  (day  kg-1 
dry matter) 

BTF-milk-grass  (day  kg-1 
dry matter) 

2.02E-02 

2.74E-01 

9.69E-03 

2.02E-02 

(Yoo et al., 2011) 

2.24E-01 

2.53E-01 

1.79E-01 

1.11E-01 

(Wen et al., 2014) 

0.012 

0.041 

0.302 

0.071 

(Kowalczyk et al., 2013; Vestergren et al., 2013) 

0.01122 

0.0007 

0.0155 

0.0213 

(Vestergren et al., 2013; Takaki et al., 2015) 

(1)The  PFOA,  PFNA  and  PFOS  concentrations  reported  by  Tavazzi  et  al.  (2012)  have  been  retained  in  the 
assessment.  These  values  fall  within  the  ranges  of  studies  of  other  studies  (Gómez-Canela  et  al.,  2012; 
Brambilla et al., 2016; Blytt and Stang, 2018; Fernandes et al., 2019; Kärrman et al., 2019; Rigby et al., 2021). 
The concentration value for PFHxS (0.62 µg-1 kg-1 DM) was taken from Gómez-Canela et al. (2012).   
(2)Reported values for regional background concentrations in soils were taken from ten sites across Germany 
(Göckener et  al.,  2021),  and  are  thus representative  for  industrialised  countries.  These  values are,  however, 
one order of magnitude lower compared to global mean values reported by Brusseau et al. (2020). 
(3)Values indicated on a dry matter basis have been transformed into values on a wet mass basis (mg kg-1 
plant ww)/(mg kg-1 soil ww) assuming a water content in soil of 20vol% (EUSES default, conversion factor for 
soil concentration wet-dry weight soil of 1.13), and a water content in roots of 65vol%, and a bulk density of 
plants of 700 kg/m3 (EUSES default), 

13.3.1.5  Estimated environmental and health exposure and risks from sludge application 

The  outcome  of  the  risk  screening  assessment  resulting  from  the  application  of  PFAS  present  in  sewage 
sludge  to  agricultural  soils  (without  ‘background’  concentrations  of  water  and  soils)  indicated  that  risk 
characterisation  ratios  were  above  1  for  soils  (PFOS,  after  10  and  100  years  of  sludge  application)  and 
human  health  (all  time  periods)  (Table  13).  The  long-chain  PFNA  and  PFOS  contributed  most  to  the  total 
∑PFAS4  uptake,  with  values  that  were  2-3  orders  of  magnitude  greater than  the  contributions  of  PFOA  and 
PFHxS. The RCR were not exceeded to for surface waters, although the value was only marginally below 1 for 
PFOS (Table 13). 

It  was  indicated  that  the  fish  consumption  is  the  primary  driver  human  health  risks,  with  an  average 
contribution of fish total human intake of 74% after 10 years) (Table 13). In turn, the PFAS concentrations in 
surface water are the primary driver for PFAS uptake by fish. 

Table  13:  Environmental  and  human  health  risk  screening  assessment  of  the  exclusive  application  of  PFAS  present  in 
sewage sludge to agricultural soils (PEC: predicted environmental concentration, RCR: risk characterisation ratio) 

PFOA 

PFHxS 

PFNA 

PFOS 

∑PFAS4 

Soil 

PECyear 1/10/100 (mg kg-1 wet soil) 

RCRyear 1/10/100 (-) 

5.5E-06 / 
1.5E-05 / 
1.9E-05 

2.5E-02/ 
7.0E-02/ 
8.6E-02 

9.2E-07/ 
9.3E-06/ 
4.6E-05 

1.5E-05/ 
1.5E-04/ 
7.5E-04 

3.8E-06/ 
1.5E-05/ 
1.9E-05 

1.4E-03/ 
5.8E-03/ 
7.3E-03 

6.8E-05/ 
7.3E-04/ 
5.5E-03 

3.1E-01/ 
3.3E+00/ 
2.5E+01 

Surface 
water 

PECyear 1 (µg L-1) 

1.4E-03 

4.1E-05 

8.2E-04 

2.1E-03 

RCR year 1 (-) 

1.37E-02 

4.7E-05 

1.4E-03 

1.0E+00 

Human 

Total daily intakeyear 1/10/100 (mg 
day-1) 

8.6E-06/ 

9.4E-07/ 

1.9E-04/ 

1.1E-04/ 

3.1E-04/ 

9.7E-06/ 

6.5E-06/ 

1.9E-04/ 

1.9E-04/ 

4.0E-04/ 

93 

 
 
 
  
 
 
 
 
 
 
 
 
 
 
1.0E-05 

3.1E-05 

1.9E-04 

7.9E-04 

1.0E-03 

Relative contribution of fish 
consumption10 years (%) 

Relative contribution of crop, meat 
and dairy consumption10 years (%) 

Relative contribution of drinking 
water10 years (%) 

RCRyear 1/10/100 

77 

22 

1 

4 

96 

0 

99 

1 

0 

51 

49 

0 

74 

26 

0 

2.8E+01/ 

3.6E+01/ 

9.3E+01 

13.3.1.6  Source contribution analysis 

Risks  from  PFAS  are  further  augmented  when  regional  background  concentrations  (surface  water,  soil)  and 
inputs from atmospheric  deposition are considered, with  a further increase in calculated risk ratios for  soils 
(Table  14).  Risk  characterisation  ratios  for  PFOS  are  now  also  exceeded  in  surface  water  bodies.  Given  the 
assumed residence time of 40 days in water bodies and single application per year, the PEC in surface water 
remains largely constant in the long-term. Risks for human health are also further augmented (Table 14) due 
to increases in PFAS concentrations in crops, dairy products and meat as a result of PFAS soil concentrations.  
Sludge-derived  PFAS  are  a  relatively  small  source  of  contamination  relative  to  existing  background  levels 
observed in soils for PFOA and PFNA (maximum 3% after 100 years) (Table 14). For PFOS, the sludge-derived 
contribution to total soil contamination is more significant, especially in the mid- (10 year, 38%) to long-term 
(100 year, 82%). For PFHxS, background concentrations in soils have been found to be negligible and sludge is 
considered to be the sole source of contamination in this study (Table 14).   
The PFAS concentrations in water are the sum of local inputs from the sewage sludge amended agricultural 
field  (through  runoff,  erosion  and  drainage)  and  regional  background  concentrations  observed  in  surface 
waters  (e.g.  effluents  from  wastewater  treatment  plants,  industrial  effluents).  Sludge-derived  PFAS  are  a 
rather  small  source  of  surface  water  contamination,  with  estimated  contributions  to  surface  water  varying 
from 3% to 17% for PFOA, PFHxS and PFOS, in the 30-day period following application on agricultural land 
(Table 14). The  contribution  of PFNA is  somewhat higher, but still not a  dominant source (44%) (Table  14). 
These findings are generally in line with literature observations. Arvaniti et al.  (2014) indicated that no more 
than  48%  (PFOS)  and  11%  (PFOA)  in  wastewaters end  up  in  sludge  faction  (mix  of  primary  and  secondary 
sludge, either digested or undigested). These values are expected to be lower for short-chain PFAS that are 
mainly transferred to the effluent during  wastewater treatment (Arvaniti et al., 2014). After land application 
the  overall  share  (>95%)  of  the  PFAS  remain  in  soils  (Costello  and  Lee,  2020;  confirmed  by  our  modelling 
assessment). These observations corroborate the relatively low contribution of sludge-derived PFAS to surface 
waters,  as  well  as  the  conservative  nature  of  our  risk  assessment  methodology  (local  scale  assessment, 
assessing  risks  in  surface  waters  surrounding  an  agricultural  fields amended  with  sewage  sludge  at  a  high 
application rate) at a more regional scale.  
In  sum,  our  findings  indicates  that  sludge  may  be  a  relevant,  but  not  the  principal,  source  of  PFAS 
contamination for surface waters. Whereas sludge may be a source of PFAS contamination of surface water 
and induce as such human health risks, other sources including  wastewater treatment effluents, need to be 
tackled simultaneously. 

Table  14:  Environmental  and  human  health  risk  screening  assessment  for  PFAS,  based  on  its  present  background 
concentrations  observed  in  the  environment  along  with  sewage  sludge  applications  to  agricultural  land  (PEC:  predicted 
environmental concentration, RCR: risk characterisation ratio) 

PFOA 

PFHxS 

PFNA 

PFOS 

∑PFAS4 

Soil 

PECyear 1/10/100 (mg kg-1 wet soil) 

Contribution of sludge to total 
concentration (%) 

RCRyear 1/10/100 (-) 

8.6E-04 / 
8.7E-04 / 
8.8E-04 

9.2E-07 / 
9.3E-06 / 
4.6E-05 

6.2E-04 / 
6.4E-04 / 
6.4E-04 

1.3E-03/ 
1.9E-03/ 
6.7E-03 

1/2/2 

100/100/100 

1/2/3 

5/38/82 

4.0E+00/ 
4.1E+00/ 
4.1E+00 

1.5E-05/ 
1.5E-04/ 
7.5E-04 

2.4E-01/ 
2.4E-01/ 
2.5E-01 

5.7E+00/ 
8.7E+00/ 
3.0E+01 

94 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Surface 
water 

PECyear 1 (µg L-1) 

3.4E-02 

3.1E-04 

1.5E-03 

9.1E-03 

Contribution of sludge to total 
concentration (%) 

3 

10 

44 

17 

RCR year 1 (-) 

3.4E-01 

3.5E-04 

2.7E-03 

4.5E+00 

Human 

Total daily intakeyear 1/10/100 (mg 
day-1) 

9.7E-04/ 
9.8E-04/ 
9.8E-04 

9.2E-06/ 
1.5E-05/ 
3.9E-05 

1.0E-03/ 
1.0E-03/ 
1.0E-03 

1.8E-03/ 
1.9E-03/ 
2.5E-03 

3.8E-03/   3.9E-
03/   4.5E-03 

RCRyear 1/10/100 

3.4E+02/ 
3.5E+02/ 
4.1E+02 

13.3.1.7  Effect of sludge treatment 

including  composting  and  anaerobic  digestion 

PFAS are known as ‘forever chemicals’ due to their persistence in the environment. They are resistant to biotic 
degradation  processes, 
(Lindstrom  et  al.,  2011; 
Lakshminarasimman et al., 2021). Thermal oxidation processes  can  be applied to incinerate sewage sludge, 
after which the fly ashes can be used as a rock phosphate substitute to develop a nutrient-dense P fertiliser. 
In  the  EU,  especially  fluidised  bed  incinerators  are  commonly  used  for  this  purpose.  Incineration,  mainly 
fluidised bed incineration characterised by extreme turbulence and long-residence times of the gas phase, at 
least remove an important share of the PFAS (see recent review of Winchell et al. (2021), and studies cited 
herein). However, complete  destruction of PFAS in thermal processes may require temperatures at 1000°C-
1100°C (Winchell et al., 2021). Nonetheless, Khan et al. (2020) calculated a PFOS half-life of 0.2 s at 726°C. 
MacGregor (2020) reported PFAS is being destroyed through a fluidised-bed sewage sludge mono-incinerator 
(830°C for 8 s). Wohlin and Karmann (2020) indicated that PFAS concentrations in fly ashes are lower than 
for bottom-ashes. Hence, uncertainty gaps exist related to the removal of PFAS during incineration (Winchell 
et  al.,  2021)  that  need  to  be  filled.  This  holds  especially  true  in  view  of  the  revised  2020  EFSA  guidelines 
pointing  towards  human  health  risks  at  extremely  low  levels  of  PFAS  intake.  Removal  of  PFAS  (95-99%) 
during  pyrolysis  has also  recently  been  observed  (Buss,  2021), although  the  knowledge  base  and minimum 
operational conditions for pyrolysis processes remains thin.  

13.3.2  Polyaromatic hydrocarbons (PAH) 

13.3.2.1  Background and selection of compounds 

PAHs are a natural component of coal and oil, which have historically been used in wood preservatives and tar 
products.  They  are  mainly  formed  by  incomplete  combustion  of  organic  material,  such  as  coal,  petrol  and 
wood,  and  are  commonly  released  into  the  atmosphere  as  small  particulates  (Abdel-Shafy  and  Mansour, 
2016).  Sources  of  PAHs  into  the  European  environment  include  the  production  and  processing  of  metals, 
vehicle exhausts, coal-fired power generation, domestic heating and forest fires. Atmospheric emissions have 
been reduced in Europe since the 1980s.  
The PAH substance group comprises a large number of substances with different toxicities and environmental 
fates.  Environmental  quality  standards  s  have  been  set  for  seven  of  the  most  toxic  PAHs,  which  act  as 
representatives  of  the  whole  group.  Three  of  these  are  separately  listed  (anthracene,  fluoranthene  and 
naphthalene) while the other five are grouped, with the 'lead substance' being benzo(a)pyrene. 
PAHs  are  extensively  metabolised  in  mammals  and  but  not  bioaccumulate.  Most  PAHs  that  enter  the  body 
leave  within  a  few  days,  primarily  in  the  feces  and  urine.  Different  metabolic  pathways  can  lead  to  highly 
reactive intermediates involved in the mutagenic/carcinogenic process of PAHs. 

13.3.2.2  Safe limit values for human consumption 

Based on the currently available data relating to occurrence and toxicity, the CONTAM Panel concluded that 
the sum of the high molecular weight PAH benzo[a]pyrene (BaP), chrysene (CHR), benz[a]anthracene (BaA) and 
benzo[b]fluoranthene (BbFA) (PAH4) is the most suitable indicators of PAHs in food (EFSA, 2008). These PAH, 
with 4 to 5 aromatic rings in their structure, have been indicated belong to the class of PAH compounds that 
show the highest persistency in soils, water and sediment (ECHA, 2008a). Together these PAH4 make up 32% 

95 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
out  of  total  PAH  mass  (19  PAH  compounds)  identified  and  measured  in  the  JRC  report  on  sewage  sludge 
(Tavazzi et al., 2012). 
The CONTAM Panel calculated BMDL10 values for PAH4 using a range of statistical models, and selected the 
lowest benchmark dose (lower confidence limit with a benchmark response of 10%, BMDL10) of 0.34 mg kg-1 
body weight day-1 from the statistical models that adequately fit the data (EFSA, 2008). A minimum Margin of 
Exposure  (MOE)  of  10,000  was  indicated  by  the  EFSA  Scientific  Committee  to  ensure  the  absence  of  a 
potential  concern  for  consumer  health  and  a  possible  need  for  risk  management  action  (EFSA,  2008).  This 
MOE was based based on the bench mark dose lower confidence limit for a 10% increase in the number of 
tumour  bearing  animals  compared  to  control  animals.  Therefore,  a  conservative  value  of  3.4E-05  mg  kg-1 
body weight day-1 is applied in this assessment to flag a potential concern for human health.  

13.3.2.3  Concentrations observed in sludge 

The  PAH  concentrations  reported  in  Tavazzi  et  al.  (2012)  were  used  for  modelling.  Reported  PAH 
concentrations  in  more  recent  studies  are  generally  in  line  or  slightly  lower  compared  to  these  values 
(Torretta and Katsoyiannis, 2013; Suciu et al., 2015; Poluszyńska et al., 2017; Rorat et al., 2019; Wluka et al., 
2021). 

13.3.2.4  Model input data 

Table  15:  Physico-chemical  and  toxicological  data  used  for  risk  modelling  purposes  for  the  selected  polyaromatic 
hydrocarbons. 

Benzo(b)fluoranthene 

Chrysene 

Benzo(a)pyrene 

Benzo(a)anthracene 

Concentration  in  sludge 
(mg-1 kg-1 dry matter) 

1.92E+00 

2.02E+00 

1.48E+00 

1.83E+00 

(Tavazzi et al., 2012) 

Molecular weight (g mol-1) 

252.32 

228.3 

252.32 

228.3 

(core database) 

Water solubility (mg L-1) 

0.0012 

0.002 

0.0038 

0.014 

(WHO, 1998a) 

(ECHA, 2017b) 

(WHO, 1998a) 

(WHO, 1998a) 

Vapour pressure (Pa) 

6.7E-05 

8.4E-07 

7.3E-07 

2.8E-05 

(WHO, 1998a) 

(ECHA, 2017b) 

(WHO, 1998a) 

(WHO, 1998a) 

Kow (log 10) 

6.12 

5.73 

6.50 

5.61 

Koc (L kg-1) 

1.4E+06 

2.0E+05 

8.9E+05 

7.9E+05 

(WHO, 1998a) 

(ECHA, 2017b) 

(WHO, 1998a) 

(WHO, 1998a) 

(core database) 

(core database) 

(WHO, 1998a) 

(WHO, 1998a) 

PNECaqua (µg L-1) 

3.5E-02 

3.0E-02 

7.0E-02 

1.3E-02 

PNECsoil (mg kg-1 ww) 

2.56E-01 

1.08E-01 

1.10E+00 

4.59E-02 

(core database) 

Safe 
human 

limit  values 

for 
intake  (mg  kg-1 

(equilibrium partitioning method, based on PNECaqua)(1) 

0.34 e-4 mg kg-1 body weight day-1 for the sum of 4 PAH (benzo(a)pyrene, 
benzo(a)anthracene, chrysene, benzo(b)fluoranthene) 

96 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
body weight day-1)  

Half-life in soil (days) 

Half-life 
(degradation, days) 

in 

water 

(EFSA, 2008) 

1241 

(1) 

527 292 

(2) 

Regional  background  in 
soil (mg kg-1 dry matter)(2) 

0.106 

0.077 

0.089 

0.056 

(UK Environment Agency, 2007; average values of documented for the the UK and Norway, 
assumed to be representative for the EU; Nam et al., 2008) 

Regional  background  in 
surface water (µg L-1) 

Not applied(3) 

(1)PAH degrade slowly in soil with half-lives that vary from about 100 days to a couple of years (Smith et al., 
1997; WHO, 1998a; Roslund et al., 2018). In this study, the maximum values of the ranges (1.15 – 3.4 years) 
documented by the UK Environment Agency (UK Environment Agency, 2007) were applied 
(2)PAH degrade slowly in surface waters, especially at greater depth where photolysis is absent  (Tansel et al., 
2011)(ECHA, 2017b). Conservative default half-life values (263 646 days) for non-biodegradable substances 
(527  292  days)  have  been  used  in  the  assessment.  In  any  event,  the  main  removal  pathway  from  surface 
would be dilution with inflowing waters (surface water residence time: 40 days)  
(3)Background  concentrations  in  surface  waters  for  PAH  have  sparsely  been  documented.  No  data  are 
available in the JRC IPCHEM database. In the NORMAN EMPODAT (EMPODAT, 2021), reported data vary from 
below  detection  limit  (majority  of  the  samples)  to  two  digit  values  expressed  as  µg  L -1.  These  observations 
indicate that background concentrations are highly variable as a function of location, neighbouring industrial 
activities,  and  point-source  releases.  Therefore,  no  assessment  could  be  made  to  assess  the  impact  of 
regional background concentrations in surface water.  

13.3.2.5  Estimated environmental and health exposure and risks from sludge application 

The outcome of the risk screening assessment resulting from the application of PAH present in sewage sludge 
to  agricultural  soils  (without 
‘background’  concentrations  of  water  and  soils)  indicated  that  risk 
characterisation ratios below 1 for soils and surface waters. For human health, RCRs above 1 were indicated 
for the entire time period under study, up to a value of 6.1E+01 indicating significant risks in the long-term 
(100 years) (Table 16). In the long-term, the contribution of BaP, CHR, and BbFa was on average one order of 
magnitude greater than the contribution to human risks for BaA (Table 16). 
Based on a weighted average of different food sources to total PAH human uptake, it was indicated that crop, 
meat and dairy were the  main sources of PAH  uptake (82%), with lower contributions from fish (18%) and 
drinking  water  (0.2%).  This  can  be  explained  by  the  observed  persistence  and  reduced  mobility  and  strong 
adsorption of PAH in soils (Smith et al., 1997), causing rather small PAH losses to surface waters. 

Table  16:  Environmental  and  human  health  risk  screening  assessment  of  the  exclusive  application  of  PAH  present  in 
sewage  sludge  to  agricultural  soils  (PEC:  predicted  environmental  concentration,  RCR:  risk  characterisation  ratio;  BaP: 
benzo[a]pyrene, CHR: chrysene, BaA: benz[a]anthracene, BbFA: benzo[b]fluoranthene). 

Soil 

PECyear 1/10/100 (mg kg-1 wet soil) 

2.8E-03 

3.0E-03/ 

2.2E-03/ 

2.7E-03/ 

BbFA 

CHR 

BaP 

BaA 

∑PAH4 

1.9E-02 

2.0E-02/ 

1.5E-02/ 

1.8E-02/ 

2.8E-02 

3.2E-02 

2.3E-02 

2.9E-02 

RCRyear 1/10/100 (-) 

3.2E-03/ 

2.8E-02/ 

2.0E-03/ 

1.5E-02/ 

2.1E-02/ 

1.9E-01/ 

1.3E-02/ 

1.0E-01/ 

3.3E-02 

3.0E-01 

2.1E-02 

1.6E-01 

97 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Surface 
water 

PECyear 1 (µg L-1) 

4.3E-04 

3.1E-03 

5.2E-04 

7.2E-04 

RCR year 1 (-) 

1.2E-02 

1.0E-01 

7.4E-03 

5.6E-02 

Human 

Total daily intakeyear 1/10/100 (mg 
day-1) 

4.1E-03/ 

1.2E-02/ 

8.6E-03/ 

2.1E-03/ 

2.7E-02/ 

9.0E-03/ 

1.2E-02/ 

1.1E-01/ 

2.2E-03/ 

1.3E-01/ 

9.8E-03 

1.2E-02 

1.2E-01 

2.3E-03 

1.5E-01 

Relative contribution of fish 
consumption10 years (%) 

Relative contribution of crop, meat 
and dairy consumption10 years (%) 

Relative contribution of drinking 
water10 years (%) 

RCRyear 1/10/100 

18 

82 

0.2 

1.1E+01/ 

5.6E+01/ 

6.1E+01 

13.3.2.6  Source contribution analysis 

Risks  from  PAH  are  further  augmented  when  regional  background  concentrations  (surface  water,  soil)  and 
inputs from atmospheric  deposition are considered, with  a further increase in calculated risk ratios for  soils 
(Table 17). Risk characterisation ratios for chrysene now exceeds the critical ratio of 1 in soils after a period 
of 100 years. Risks for human health are also further augmented due to increases in PFAS concentrations in 
crops, dairy products and meat as a result of PFAS soil concentrations. Risk characterisation ratios for surface 
water remain below estimated limit values that may be of concern to aquatic organisms. 
Sludge-derived  PAH  become  a  significant  contributor  to  total  PAH  concentrations  in  the  soil  in  the  mid-  to 
long-term (14% - 34% across all PFAS following 10-100 years of continuous sludge applications) (Table 17). 
It  should  be  remarked  that  these  simulations  are  likely  overestimated  as  future  inputs  from  other  sources 
have not been considered in our assessment.  
In sum, our findings indicates that sludge may be a relevant source of PAH contamination in soils, that may 
cause human health risks based on our conservative modelling approaches.  

Table  17:  Environmental  and  human  health  risk  screening  assessment  for  PAH,  based  on  its  present  background 
concentrations  observed  in  the  soil  along  with  sewage  sludge  applications  to  agricultural  land  (PEC:  predicted 
environmental concentration, RCR: risk characterisation ratio; BaP: benzo[a]pyrene, CHR: chrysene, BaA: benz[a]anthracene, 
BbFA: benzo[b]fluoranthene). Note: due to the absence of EU-representative background PAH values in surface waters, no 
source contribution analysis could be done for this ecosystem compartment.  

Soil 

PECyear 1/10/100 (mg kg-1 wet soil) 

1.1E-01/ 

8.0E-02/ 

9.1E-02/ 

5.9E-02/ 

BbFA 

CHR 

BaP 

BaA 

∑PAH4 

Contribution of sludge to total 
concentration (%) 

1.2E-01/ 

9.7E-02/ 

1.0E-01/ 

7.4E-02/ 

1.3E-01 

1.1E-01 

1.1E-01 

8.5E-02 

3/ 15/ 21 

4/ 21 /29 

2/ 14/ 21 

5/ 25/ 34 

RCRyear 1/10/100 (-) 

1.3E-01/  

7.6E-01/  

8.3E-02/  

3.2E-01/  

1.4E-01/  

9.2E-01/  

9.4E-02/  

4.1E-01/  

1.6E-01 

1.0E+00 

1.0E-01 

4.7E-01 

PECyear 1/10/100 (µg/L) 

4.3E-04 

3.1E-03 

5.2E-04 

7.2E-04 

RCRyear 1/10/100 (-) 

1.2E-02 

1.0E-01 

7.4E-03 

5.6E-02 

Total daily intakeyear 1/10/100 (mg 
day-1) 

1.3E-02/ 

1.3E-02/ 

1.3E-01/ 

2.3E-03/ 

1.6E-01/ 

1.4E-02/ 

1.3E-02/ 

1.5E-01/ 

2.4E-03/ 

1.8E-01/ 

RCRyear 1/10/100 

6.8E+01/ 

1.5E-02 

1.3E-02 

1.6E-01 

2.4E-03 

1.9E-01 

Surface 
water 

Human 

98 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
7.5E+01/ 

8.1E+01 

13.3.2.7  Effect of sludge treatment 

Composting  has  potential  to  reduce  PAH  concentrations  in  sewage  sludge  (Poluszyńska  et  al.,  2017),  with 
removal rates of 64% to 83% for PAH with 4 to 5 aromatic rings, such as as PFAS4. A recent review article on 
composting  compiled  information  of  about  15  studies  for  different  organic  materials, and  indicated  similar 
removal  rates varying  from  47% to 100% removal  (Lü et al., 2021). The  partial degradation of PAH during 
mesophilic and thermophilic anaerobic digestion of sludge has also observed (Chang et al., 2003; Trably et al., 
2003; Benabdallah El-Hadj et al., 2006; Bernal-Martinez et al., 2009; Zhang et al., 2019). El-Hadj et al. 2006 
reported  removal  efficiencies  ranging  from 51%  to  65%  in  thermophilic  conditions  and  from 36  to  43%  in 
mesophilic conditions for the sum of 16 PAH. Moreover, according to Trably et al. 2003 the removal rate of 
the  sum  of  13  PAH  (about  50%)  was  directly  linked  to  total  solids  removal  rate.  It  is  concluded  that,  on 
average, biological treatments of sewage sludge are able to reduce PAH concentrations by a factor 2 to 10, 
but that the removal efficiency is dependent on process conditions applied and PAH compounds under study. 
Incineration of at high temperatures ranging from 870◦C to 1200◦C effectively destructs PAHs, with removal 
efficiencies  in  the  99.0  -  99.9%  range  (Renoldi  et  al.,  2003;  Gan  et  al.,  2009;  Van  Caneghem  and 
Vandecasteele, 2014). In the boiler and fly ash of industrial facilities, PAHs were not present in concentrations 
above the detection limit (<0.01 mg kg-1 ash) following sewage sludge incineration. This indicates that the ash 
does not contain PAHs remaining from the waste nor PAHs adsorbed from the gas phase under well-operated 
conditions  that  comply  with  the  European  Directive  on  Industrial  Emissions  (Directive  2010/75/EU)  (Van 
Caneghem and Vandecasteele, 2014). The absence of PAH in incinerator fly ash from waste materials other 
than  sewage sludge  was also observed  by Wheatley and Sadhra  (2004). PAH concentrations in  bottom ash 
above the detection limit (<0.3 mg kg-1 ash) have been observed (Van Caneghem and Vandecasteele, 2014), 
but  this  fraction  is  generally  not  used  for  the  manufacturing  of  P-fertilisers  from  ah  through  acidulation 
processes.  Incineration  has  the  potential  to  achieve  high  PAH  removal  efficiencies,  but  it  is  critical  that  the 
process is well-controlled so as to avoid contamination of the fly ashes by de novo produced PAH during the 
incineration process (Huygens et al., 2019).  

13.3.3  PCDD/Fs and dioxin-like PCBs 

13.3.3.1  Background and selection of compounds 

Polychlorinated  dibenzo-p-dioxin  and  furans  (PCDD/Fs)  are  two  groups  of  tricyclic  planar  compounds. 
Dependent  on  the  number  of  chlorine  atoms  and  their  positions  at  the  rings,  75  PCDDs  and  135  PCDFs, 
termed ‘congeners’, can occur (EFSA Panel on Pollutants in the Food Chain et al., 2018). Only 17 of these are 
relatively  persistent  in  animals  and  humans  and  therefore  considered  relevant.  They  contain  at  least  four 
chlorines  and  at  positions  2,  3,  7  and  8.  Dioxin-like  polychlorinated  biphenyls  (dl-PCBs)  congeners  that  are 
non-ortho or mono-ortho chlorine substituted and contain at least four chlorine substituents can easily adopt 
a coplanar structure and show toxicological properties similar to tetrachlorodibenzo-p-dioxin (TCDD) and other 
PCDD/Fs (EFSA Panel on Pollutants in the Food Chain et al., 2018). 
PCDD/Fs  have  never  been  produced  on  an  industrial  scale  and  have  no  technological  use.  They  are  formed 
unintentionally in a number of industrial and thermal processes. In contrast to PCDD/Fs, PCBs had widespread 
use  in  open  and  closed  systems,  generally  in  the  form  of  complex  technical  mixtures.  They  were  produced 
with an estimated total world production of 1.2–1.5 million tonnes between 1929 and the end of the 1970s, 
when their production was abandoned in the majority of countries (EFSA Panel on Pollutants in the Food Chain 
et  al.,  2018).  Atmospheric  PCDD/F  emissions  have  also  been  reduced  significantly  over  the  last  decades, 
amongst others due to the enforcement of stricter EU limits to for industrial facilities (metal industries, waste 
incineration, etc.) as regulated in the IED.  
Due  to  their  lipophilic  properties and poor degradation,  PCDD/Fs  and  dl-PCBs  accumulate  in  the  food  chain. 
Animal  derived  food, including fish, contributes most to  human exposure, due to the accumulation of these 
pollutants in fatty tissues and liver (EFSA Panel on Pollutants in the Food Chain et al., 2018).  

99 

 
 
 
  
13.3.3.2  Safe limit values for human consumption 

A recent risk assessment by the European Food Safety Authority (EFSA) resulted in a lowering of the Tolerable 
Weekly Intake (TWI) from 14 to 2 pg TEQ/kg body weight (bw) per week, based on effects on sperm quality 
observed in humans (EFSA Panel on Pollutants in the Food Chain et al., 2018). This translates into a safe limit 
value of 2.9E-10 mg kg-1 body weight day-1 applied in this assessment 
Across  PCDD/Fs  and  PCBs,  17  congeners  show  different  toxic  potencies,  which  are  expressed  as  toxic 
equivalency  factors  (TEFs)  assigned  to  them  based  on  in  vivo  and  in  vitro  studies.  The  toxic  potency  of  a 
sample is expressed as  toxicity equivalents (TEQ) according to the WHO recommended  methodology as the 
sum of the individual congener concentrations multiplied by their respective TEFs( Van den Berg et al., 2006). 
The  use  of  TEFs  provides  opportunities  to  extrapolate  the  findings  for  a  single  compound  (2,3,7,8-
Tetrachlorodibenzo-p-dioxin,  TCDD)  and  to  extrapolate  the  findings  for  the  broader  group  of  PCDD/Fs  and 
PCBs. The most toxic congener, 2,3,7,8-tetrachlorodibenzop-dioxin (TCDD) is used as the reference compound 
with an assigned TEF of 1 and good data availability for physico-chemical and toxicological properties. 

13.3.3.3  Concentrations observed in sludge 

Today, the dioxin contamination of sewage sludge without specific industrial contributions is generally below 
10 ng TEQ/kg DM in Europe (Bayerisches Landesamt für Umwelt, 2011; Elskens et al., 2013; Zennegg et al., 
2013; Weber et al., 2018), that have decreased significantly relative to previous years and decades (Oleszek-
Kudlak et al., 2005; Vacha et al., 2005). Still it cannot be excluded that specific industrial sludges contain high 
amounts  of  PCDD/F  and  PCBs,  e.g.  following  accidental  spillage  (Fuentes  et  al.,  2007  up  to  7000  ng  kg-1 
sludge; Balasubramani and Rifai, 2015). In this assessment, we assumed a PCDD/F + dl-PCB concentration of 
20 ng WHO-TEQ kg-1 sludge dry matter, corresponding to a net mass of  10 ng kg-1 sludge for 2,3,7,8-TCDD 
used as reference compound. 

13.3.3.4  Model input data 

Table 18: Physico-chemical and toxicological data used for risk modelling  purposes for the selected PCDD/Fs and dioxin-
like PCBs. 

2,3,7,8-tetrachlorodibenzo p-dioxin 
(TCDD) 

Concentration in sludge (mg-1 
kg-1 dry matter) 

10E-06 

(see main text) 

Molecular weight (g mol-1) 

321.98 

(EQS dossier, 2011a) 

Water solubility (mg L-1) 

1.93E-02 

(EQS dossier, 2011a) 

Vapour pressure (Pa) 

2.0E-07 

(EQS dossier, 2011a) 

Kow (log 10) 

6.80 

(EQS dossier, 2011a) 

Koc (L kg-1) 

3.98E+06 

(Walters et al., 1989) 

PNECaqua (µg L-1) 

3.1E-09 

                 (EQS dossier, 2011a) 

100 

 
 
 
 
 
 
 
PNECsoil (mg kg-1 ww) 

1.73E-07 

Safe  limit  values  for  human 
intake  (mg  kg-1  body  weight 
day-1)  

       (equilibrium partitioning method) 

2.9E-10 

         (EFSA  Panel  on  Pollutants  in  the       
Food Chain et al., 2018) 

Half-life in soil (days) 

3650 

              (EQS  dossier,  2011a;  Qiu  et  al., 
2015) 

Half-life in water (degradation, 
days) 

263 646 

Regional  background  in  soil 
(mg kg-1 dry matter) 

Regional 
surface water (µg L-1) 

background 

in 

                                 (1) 

2.3E-06(2) 

(Elskens et al., 2013) 

10.5E-09 

           (Deleebeeck et al., 2021) 

(1)Conservative  default  half-life  values  (263  646  days)  for  non-biodegradable  substances  (527  292  days) 
have been used in the assessment. In any event, the main removal pathway from surface would be dilution 
with inflowing waters (surface water residence time: 40 days) 
(2)Average levels for PCDD/F in Belgium agricultural soils 

13.3.3.5  Estimated environmental and health exposure and risks from sludge application 

The  risk  screening  assessment  resulting  from  the  application  of  2,3,7,8-TCDD  present  in  sewage  sludge  to 
agricultural soils (without ‘background’ concentrations of water and soils) indicated that RCRs were above 1 
for soils after 100 years of continuous application (Table 19). The RCR ratios for human health were above 1 
and 100 in the short (1 year) and longer-term (>10 years).   
Across the different food sources to total PAH human uptake, it was indicated that crop, meat and dairy were 
the  main  sources  of  2,3,7,8-TCDD  uptake  (100%,  Table  19,  with  negligible  contributions  from  fish  and 
drinking water due to the strong 2,3,7,8-TCDD adsorption capacity of the soil.  

Table  19:  Environmental  and  human  health  risk  screening  assessment  of  the  exclusive  application  of  2,3,7,8-TCDD 
present in sewage sludge to agricultural soils (PEC: predicted environmental concentration, RCR: risk characterisation ratio) 

Soil 

PECyear 1/10/100 (mg kg-1 wet soil) 

RCRyear 1/10/100 (-) 

PECyear 1 (µg L-1) 

RCR year 1 (-) 

Surface 
water 

Human 

Total daily intakeyear 1/10/100 (mg 
day-1) 

2,3,7,8-TCDD 

1.5E-08 

1.4E-07 

4.1E-07 

6.7E-02 

6.2E-01 

1.9E+00 

7.8E-10 

2.5E-01 

5.5E-08/  

6.2E-06/  

7.0E-06 

101 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Relative contribution of fish 
consumption10 years (%) 

Relative contribution of crop, meat 
and dairy consumption10 years (%) 

Relative contribution of drinking 
water10 years (%) 

RCRyear 1/10/100 

0% 

100% 

0% 

2.7E+00 

3.1E+02 

3.5E+02 

13.3.3.6  Source contribution analysis 

When  regional  background  concentrations  (surface  water,  soil)  and  inputs  from  atmospheric  deposition  are 
considered, risk characterisation ratios for soils are exceeded after a single application in year 1 (Table 20), 
due to the  high 2,3,7,8-TCDD background concentrations observed in soils. Risks for  human health are also 
further augmented due to increases in PFAS concentrations in crops, dairy products and meat as a result of 
PFAS  soil  concentrations.  Risk  characterisation  ratios  for  surface  water  exceed  limit  values  that  may  be  of 
concern to aquatic organisms. 
Sludge-derived PAH become  an important  contributor to total 2,3,7,8-TCDD concentrations in the  soil in the 
mid-  to  long-term  (6%  -  15%  across  all  PFAS  following  10-100  years  of  continuous  sludge  applications; 
assuming no further inputs from other sources such as atmospheric deposition) (Table 20).  
In sum, our findings indicates that sludge may be a relevant source of  2,3,7,8-TCDD contamination in soils, 
that may cause human health risks based on our conservative modelling approaches.  

Table 20: Environmental and human health risk screening assessment for 2,3,7,8-TCDD, based on its present background 
concentrations  observed  in  the  soil  along  with  sewage  sludge  applications  to  agricultural  land  (PEC:  predicted 
environmental concentration, RCR: risk characterisation ratio) 

Soil 

PECyear 1/10/100 (mg kg-1 wet soil) 

Contribution of sludge to total concentration (%) 

Surface 
water 

RCRyear 1/10/100 (-) 

PECyear 1 (µg L-1) 

RCR year 1 (-) 

Human 

Total daily intakeyear 1/10/100 (mg day-1) 

RCRyear 1/10/100 

2,3,7,8-TCDD 

2.3E-06/  

2.4E-06/  

2.7E-06 

1/ 6/ 15 

1.1E+01/ 

1.1E+01/ 

1.2E+01 

6.0E-09 

1.9E+00 

7.5E-06/ 

7.9E-06/ 

8.7E-06 

3.7E+02/ 

3.9E+02/ 

4.4E+02 

13.3.3.7  Impact of sludge treatment 

The  impact  of  biological  treatment  (composting  and  anaerobic)  on  PCDD/F  and  PCB  removal  is  minimal  to 
absent  (Disse  et  al.,  1995;  Lü  et  al.,  2021).  Because  PCDD/Fs  do  not  have  high  thermal  stability,  thermal 
treatment is a viable method for PCDD/Fs and dl-PCB destruction. Similar to PAH, incineration in line with the 
established conditions for waste incineration in the IED has the potential to remove >99% PCDD/F (Vehlow et 

102 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
al., 2006). Nonetheless, well-designed and state-of-the-art technologies are critical as PCDD/F and PCBs could 
de  novo  be  produced  during  high-temperature  processing  during  incineration,  especially  under conditions  of 
incomplete  combustion  or  re-adsorption  gas  particles on  solid  material  in  poorly  designed  thermal  reactors 
(Huygens et al., 2019).  

103 

 
 
  
13.3.4  Flame 

ethers 
(polybrominated 
hexabromocyclododecane (HBCDD), and organophosphate compounds) 

retardants 

diphenyl 

(PBDEs), 

13.3.4.1  Background and selection of consumption 

Flame retardants are mixtures of man-made chemicals that are added to a wide variety of products, including 
for  industrial  use,  to  make  them  less  flammable.  They  are  used  commonly  in  plastics,  textiles  and 
electrical/electronic equipment.  
Since  the  1970s,  the  primary  flame  retardants  used  were  the  polybrominated  diphenyl  ethers  (PBDEs)  and 
hexabromocyclododecane  (HBCDD).  However,  due  to  concerns  regarding  their  persistence,  toxicity  and 
bioaccumulative  potential,  these  compounds  have  been  added  to  the  Stockholm  Convention  on  Persistent 
Organic  Pollutants,  including  the  most  recent  addition  of  deca-BDE  (also  called  BDE-209,  referring  to  the 
PBDE  with  10  bromines)  in  2017.  However,  because  of  their  persistence  in  the  environment  there  are  still 
concerns about the risks these chemicals pose to public  health.  In addition, decabromodiphenyl ether (BDE-
209)  acts  as  a  slow-release  reservoir  for  lower  brominated,  more  toxic  PBDEs,  via  abiotic  and  biotic 
transformation processes. As a result, human populations and biota worldwide are exposed to BDE-209 and 
other  PBDEs  in  combination.  Flame  retardants,  whether  in  use  or  waste-derived,  can  leach  into  the 
environment and contaminate the air, soil and water. These pollutants may then enter the food chain where 
they  mainly  occur  in  food  of  animal  origin,  such  as  fish,  meat,  milk  and  derived  products.  In  addition, 
discontinued  flame  retardants  have  been  substituted  by  alternative  substances  such  as  novel  brominated, 
chlorinated  and  organophosphate  compounds.  Some  of  these  substitutes  are  suspected  of  being  of  health 
and  environmental  concern,  although  robust  toxicological  data  are  often  missing  to  perform  a  sound  risk 
assessment (van der Veen and de Boer, 2012; Hendriks and Westerink, 2015). 
To  select  substances  belonging  to  the  class  of  flame  retardants,  preliminary  evidence  indicated  high  daily 
intake  for  the  legacy  flame  retardants  decabromodiphenyl  ether  (BDE-209),  2,2',4,4'-Tetrabromodiphenyl 
ether  (BDE-47),  2,2',4,4',5-Pentabromodiphenyl  ether  (BDE-99)  and  hexabromocyclododecane  (HBCDD)  as 
well  as  for  tris(2-ethylhexyl)  phosphate  (TEHP)  and  2-ethylhexyl  diphenyl  phosphate  (EHDPP).  For  all  these 
compounds  information  on  sludge  concentrations  and  safe  limit  values.  In  addition,  also  data  for  tris(1-
chloro-2-propyl)  phosphate  (TCPP)  could  be  retrieved.  These  compounds  were  taken  forward  in  the 
assessment. 
Other  flame  retardants  were,  such  as  tetrabromobipshenol  A,  were  not  taken  forward  in  a  more  in-dept 
assessment because the high safe limit values and associated low risk characterisation ratios observed in the 
prioritisation step (see section 3.3.1) (EFSA Panel on Pollutants in the Food Chain, 2011) 

13.3.4.2  Safe limit values for human consumption 

Safe limit values for the selected compound were obtained from a variety of sources (EFSA, ECHA, US-EPA). 

Table 21: Safe limit values for human consumption used for risk modelling purposes for the selected flame retardants. 

Substance 

Safe limit values 

Value (mg kg-1 
body weight day-1) 

Source 

BDE-209 

BDE-47 

BDE-99 

HBCDD 

TEHP 

EHDPP 

Chronic human intake associated with the 
body burden calculated at the benchmark 
dose (lower confidence limit) (BMDL), 
divided by a minimum Margin of Exposure 
(MOE) of 2.5 

Chronic human intake associated with the 
body burden calculated at the lowest 
observed adverse effect level (LOAEL), 
divided by a minimum Margin of Exposure 
(MOE) of 24 

Reference dose 

Derived No Effect Level (oral route), based 
on repeated dose toxicity as most 
sensitive endpoint and an assessment 
factor of 200 

104 

6.80E-01 

6.88E-05 

1.68E-06 

(EFSA CONTAM Panel, 2011) 

(EFSA CONTAM Panel, 2011) 

(EFSA CONTAM Panel, 2011) 

9.79E-05 

(EFSA CONTAM Panel, 2021) 

1.00E-01 

3.60E-2 

(U.S. EPA, 2017; Gbadamosi et 
al., 2021) 

ECHA registration dossier for 2-
ethylhexyl diphenyl phosphate 

 
 
 
 
TCPP 

Reference dose 

1.00E-02 

(U.S. EPA, 2017; Gbadamosi et 
al., 2021) 

13.3.4.3  Concentrations observed in sludge 

Öberg  et  al.  (2002)  indicated  that  BDE  concentrations  were  in  the  range  not  detected  to  450  µg  kg-1  wet 
weight.  Eljarrat  (2008)  showed  PBDE  concentrations  in  sewage  sludge  from  different  locations  throughout 
Spain ranging from 197 to 1185 µg kg-1 dry matter, being deca-BDE-209 the predominant congener. Kupper 
et al. (2008) indicated  mean concentrations  for samples  from Switzerland of 310, 149, and 95  μg  kg -1  dry 
matter  for  BDE-209,  HBCD,  penta-BDE  (including  BDE-49  and  BDE-99  as  most  abundant  congeners), 
respectively. The ranges from Sweden, Denmark, the Netherlands, reported in the review study of Law et al. 
(2006)  are  generally  aligned  to  these  results.  The  PBDE  concentrations  in  sewage  sludge  samples from  11 
German wastewater treatment plants had average concentrations of 48 μg kg-1 dry matter (BDE-47), 54 μg 
kg-1 dry matter (BDE-99), and 429 (BDE-209) μg kg-1 dry matter (Knoth et al., 2007). Average values of 44 μg 
and 35 μg kg−1 DS for the same congeners BDE-47 and BDE-99 were measured by (Rigby et al., 2021). Gorga 
et al. (2013) reported PBDE concentrations for Spanish sewage sludges that ranged between 20.7 and 2326 
µg kg-1 with a median value of 298 µg kg-1. BDE values in German sewage sludge were below 50 µg kg-1 for 
all congeners (Wiechmann et al., 2013). The most abundant PBDE congener in these samples was BDE-209 
with concentration levels ranging from not detected to 2303 µg kg-1. For HBCD, Kupper et al. (2008) indicated 
average values of 149 µg kg-1, whereas average values of 18 µg kg-1 (with a maximum of 98 µg kg-1) were 
reported by Gorga et al. (2013). Recently, Rigby et al. (2021) reported HBCB concentrations between 33 and 
45 μg kg−1 DS for UK samples. In this assessment, sludge concentration values of 500 µg kg-1 dry matter was 
assumed  for  BDE-209,  whereas  for  BDE-47,  BDE-99  and  HBCD  a  value  of  200  µg  kg-1  dry  matter  was 
assumed. For the assessment, sludge concentration values of 0.5 mg kg-1 dry matter was assumed for BDE-
209, whereas for BDE-47, BDE-99 and HBCD a value of 0.21 mg kg-1 dry matter was assumed.  
Concentrations  values  are  hardly  reported  for  PBDE  replacement  chemicals  in  sludge.  Rigby  et  al.  (2021) 
showed  that  tris(1-chloro-2-propyl)  phosphate  (TCPP)  was  the  most  abundant  organophosphate  flame 
retardant in sewage sludges, with concentrations up to almost 1.0 mg kg-1. These values are very similar to 
trends  among  organophosphate  flame  retardants  and  maximum  values reported  for  TCPP  by  Cristale  et  al. 
(2016). Maximum concentrations for TEHP and EHDPP reported in the same study were 1.2 mg dry matter kg-
1, and 0.5 mg dry matter kg-1 matter, respectively. Given the reduced data availability, these maximum values 
were retained in this assessment. 

13.3.4.4  Model input data 

The applied model for human intake is for most susbtances based on substance-specific bioconcentration and 
biotransfer factors as deriving the latter parameters based on Kow values results in an overestimated of daily 
intake, especially for BDEs characterised by a high Kow value (Kow>7). 

Table 22: Physico-chemical and toxicological data used for risk modelling purposes for the selected flame retardants. 

Concentration 
in  sludge  (mg-1 
kg-1 dry matter) 

Molecular weight 
(g mol-1) 

Water  solubility 
(mg L-1) 

BDE-209 

BDE-47 

BDE-99 

HBCDD 

TEHP 

EHDPP 

TCPP 

0.5 

0.1 

0.1 

0.1 

1.2 

0.5 

1.0 

(see main 
text) 

(see main 
text) 

(see main 
text) 

(see main 
text) 

(Rigby et 
al., 2021) 

(Cristale 
et al., 
2016) 

(Cristale 
et al., 
2016) 

959.17 

485.8 

564.69 

641.7 

434.65 

362.4 

327.59 

(core 
database) 

(core 
database) 

(core 
database) 

(core 
database) 

(core 
database) 

(Brooke et 
al., 2009) 

(core 
database) 

6.2E-02 

2.5E-02 

2.5E-01 

8.6E-03 

5.1E+00 

1.0E+00 

1.6E+03 

(core 
database) 

(core 
database) 

(core 
database) 

(core 
database) 

(core 
database) 

(Brooke et 
al., 2009) 

(core 
database) 

105 

 
 
 
 
 
 
Vapour 
pressure (Pa) 

5.9E-09 

6.3E-05 

1.5E-05 

3.3E-06 

1.9E-04 

3.4E-4 

2.7E-01 

(core 
database) 

(core 
database) 

(core 
database) 

(core 
database) 

(core 
database) 

(Brooke et 
al., 2009) 

(core 
database) 

Kow (log 10) 

9.70 

6.57 

7.30 

5.47 

9.42 

5.73 

2.68 

(deBruyn et 
al., 2009) 

(deBruyn et 
al., 2009) 

(deBruyn et 
al., 2009) 

(EFSA 
CONTAM 
Panel, 2021) 

(Sühring 
et al., 
2020) 

(Brooke et 
al., 2009) 

(Sühring 
et al., 
2020) 

Koc (L kg-1) 

1.4E+06 

9.8E+05 

9.8E+05 

2.2E+05 

6.2E+05 

9.5E+03 

5.8E+02 

(EQS 
Dossier, 
2011) 

(EQS 
Dossier, 
2011) 

(EQS 
Dossier, 
2011) 

(EQS dossier, 
2011b) 

(core 
database) 

(Brooke et 
al., 2009) 

(core 
database) 

PNECaqua  (µg 
L-1) 

0.13 

0.049 

0.049 

0.31 

6.7E+00 

0.18 

59.16 

(core 
database) 

(EQS 
Dossier, 
2011) 

(EQS 
Dossier, 
2011) 

(EQS dossier, 
2011b) 

(core 
databse) 

(Brooke et 
al., 2009) 

(Xing et 
al., 2019) 

PNECsoil 
kg-1 ww) 

(mg 

98 

8.47E-01 

8.47E-01 

1.20E+00 

7.33E+01 

3.02E-02 

6.12E-01 

ECHA 
registration 
dossier 

(equilibrium 
partitioning 
method) 

(equilibrium 
partitioning 
method) 

(equilibrium 
partitioning 
method) 

(equilibriu
m 
partitionin
g method) 

(equilibriu
m 
partitionin
g method) 

(equilibriu
m 
partitionin
g method) 

6.80E-01 

6.88E-05 

1.68E-06 

9.79E-05 

1.00E-01 

3.60E-02 

1.00E-02 

(EFSA 
CONTAM 
Panel, 2011) 

(EFSA 
CONTAM 
Panel, 2011) 

(EFSA 
CONTAM 
Panel, 2011) 

(EFSA 
CONTAM 
Panel, 2021) 

(U.S. 
EPA, 
2017; 
Gbadamo
si et al., 
2021) 

ECHA 
registratio
n dossier 
for 2-
ethylhexyl 
diphenyl 
phosphate 

(U.S. 
EPA, 
2017; 
Gbadamo
si et al., 
2021) 

861 

342 

342 

63 

4320 

300 

47520 

limit 
Safe 
for 
values 
human 
intake 
(mg  kg-1  body 
weight day-1)  

Half-life  in  soil 
(days) 

(Andrade et 
al., 2017) 

(Andrade et 
al., 2017) 

(Andrade et 
al., 2017) 

(Davis et al., 
2005) 

(Sühring 
et al., 
2020) 

(Brooke et 
al., 2009) 

(Sühring 
et al., 
2020) 

in 

263 646 

263 646 

263 646 

263 646 

240 

50 

3270 

Half-life 
water 
(degradation, 
days) 

(default value 
non-
biodegradabl
e) 

(default value 
non-
biodegradabl
e) 

(default value 
non-
biodegradabl
e) 

(default value 
non-
biodegradabl
e) 

(Sühring 
et al., 
2020) 

(Brooke et 
al., 2009) 

(Sühring 
et al., 
2020) 

Regional 
background 
soil 
dry matter)(2) 

in 
(mg  kg-1 

Not 
considered 

1.0E-03 

1.0E-3 

Not considered 

0.1 

Not 
considere
d 

Not 
considere
d 

(Osteras et 
al., 2014; Kim 
et al., 2017) 

(Osteras et 
al., 2014; Kim 
et al., 2017)  

(Kurt-
Karakus et 
al., 2018) 

Regional 
background 

in 

Not 
considered 

2.50E-05 

2.50E-05 

5.00E-05 

Not 
considere

Not 
considere

Not 
considere

106 

 
 
 
 
 
 
 
 
 
 
 
 
surface  water 
(µg L-1) 

BCFfish-water 
(L kg-1ww) 

BTFshoot-soil 
(mg  kg-1  plant 
kg-1 
ww)/(mg 
soil ww)(3) 

BTFroot-soil 
(mg  kg-1  plant 
kg-1 
ww)/(mg 
soil ww)(3) 

BTFmeat-grass 
(day  kg-1  dry 
matter) 

BTF-milk-grass 
(day  kg-1  dry 
matter) 

(Rauchbüchl, 
2015) 

(Rauchbüchl, 
2015) 

(Rauchbüchl, 
2015) 

d 

d 

d 

50 

3.5E+04 

1.4E+04 

1.8E+04 

5.01E+01 

1.8E+04 

3.6E+00 

(U.S. 
Department 
of Health & 
Human 
Services, 
n.d.) 

(EQS 
Dossier, 
2011) 

(EQS 
Dossier, 
2011) 

(EQS dossier, 
2011b) 

(4) 

(4) 

(default 
value 
estimated 
based on 
Kow) 

4.04E-03 

1.21E-02 

1.21E-02 

2.02E-02 

7.18E-03 

7.75E-03 

5.17E-02 

(1)(EFSA 
CONTAM 
Panel, 2011) 

(1) 

(1) 

(default 
calculation) 

(B. Hu et 
al., 2021) 

(B. Hu et 
al., 2021) 

(B. Hu et 
al., 2021) 

4.04E-03 

1.21E-02 

1.21E-02 

1.11E-01 

1.05E-02 

8.07E-03 

4.60E-01 

(1) 

(1) 

(1) 

(default 
calculation) 

(B. Hu et 
al., 2021) 

(B. Hu et 
al., 2021) 

(B. Hu et 
al., 2021) 

7.08E-02 

1.26E-03 

1.26E-03 

7.41E-03 

7.73E+01 

1.35E-02 

9.7E-06 

(3) 

(Takaki et al., 
2015)(2)

(Takaki et al., 
2015)(2) 

(default value 
estimated 
based on 
Kow) 

(McKone, 
1994)(4) 

(default 
value 
estimated 
based on 
Kow) 

(McKone, 
1994) (4) 

2.14E-02 

1.26E-03 

1.26E-03 

2.34E-03 

2.4E+01 

4.27E-03 

3.8E-06 

(3) 

(Takaki et al., 
2015)(2) 

(Takaki et al., 
2015)(2) 

(default value 
estimated 
based on 
Kow) 

(McKone, 
1994) (4) 

(default 
value 
estimated 
based on 
Kow) 

(McKone, 
1994) (4) 

Biomagnificatio
n 

1 

10 

1 

10 

1 

10 

1 

(default value 
based on 
Kow) 

(default value 
based on 
Kow) 

(UNEP, 2006) 

(default value 
based on 
Kow) 

(default 
value 
based on 
Kow) 

(default 
value 
based on 
Kow) 

(default 
value 
based on 
Kow) 

(1)Reported  BCFplant-soil  are  invariably  below  1  and  usually  in  the  range  of  0.1-0.01  (EFSA  CONTAM  Panel, 
2011)(Dobslaw et al., 2021), and are inversely related to Kow (She et al., 2013). Based on the Kow values and 
the values reported by (She et al. (2013), values of BCF values 0.05 (BDE-209), 0.15 (BDE-47 and BDE-99) on 
a dry matter basis were selected. Values indicated on a dry matter basis have been transformed into values 
on  a  wet  mass  basis  (mg  kg-1  plant  ww)/(mg  kg-1  soil  ww)  assuming  a  water  content  in  soil  of  20vol% 
(EUSES default, conversion factor for soil concentration wet-dry weight soil of 1.13), and a water content in 
roots of 65vol%, and a bulk density of plants of 700 kg/m3 (EUSES default), 

107 

 
 
 
 
 
 
 
 
 
 
 
 
 
 (2)BTFmeat-grass data available for BDE-49, assumed to be equal for BDE-99. Gicen that BDE levels in milk and 
dairy products are on average below these of meat (EFSA CONTAM Panel, 2011), the same BTF factors were 
applied to model BDE grass to milk transfer as a conservative estimate. 
(3)Default values based on Kow were retained as a conservative estimate for BTF 
(4)EPI  data  obtained  from 
(https://rais.ornl.gov/cgi-bin/tools/TOX_search?select=chemspef) 

Information  System,  University  of  Tennessee 

the  Risk  Assessment 

13.3.4.5  Estimated environmental and health exposure and risks from sludge application 

The outcome of the risk screening assessment resulting from the application of PAH present in sewage sludge 
to  agricultural  soils  (without 
‘background’  concentrations  of  water  and  soils)  indicated  that  risk 
characterisation  ratios  below  1  for  soils,  surface  waters  and  human  health  (Table  23).  The  risk  screening 
analysis  indicated  that  RCR  ratios  for  soil,  surface  water  and  human  health  were  generally  below  1.  The 
greatest health concerns were associated to to BDE-99 and to a smaller extent to TEHP (with RCR values of 
2.1.E-01, and 2.3E-01 after 100 years, respectively; see Table 23).    
For  BDE-99,  fish  (63%)  and  crop/grass/meat  (37%)  contributed  most  to  total  human  intake,  in  line  with 
observations  that  fish  is  the  food  source  for  total  BDE-99  intake  by  the  population  (EFSA  CONTAM  Panel, 
2011).  The  contribution  of  food  sources to  total  intake  for  flame  retardants,  other than  BDE-99,  should  be 
interpreted with the necessary caution as (i) no data refinements were performed given the low RCR ratios for 
human health, (ii) intake values are rather low. Nonetheless, it is clear that the fish bioconcentration factors 
documented across the range of flame retardants varies markedly in literature (see section 13.3.4.4). 

Table  23:  Environmental  and  human  health  risk  screening  assessment  of  the  exclusive  application  of  flame  retardants 
present in sewage sludge to agricultural soils (PEC: predicted environmental concentration, RCR: risk characterisation ratio; 
BDE-209: decabromodiphenyl ether, BDE-47: 2,2',4,4'-Tetrabromodiphenyl ether, BDE-99: 2,2',4,4',5-Pentabromodiphenyl 
ether and HBCDD: hexabromocyclododecane; TEHP: tris(2-ethylhexyl) phosphate; EHDPP: 2-ethylhexyl diphenyl phosphate 
TCPP: tris(1-chloro-2-propyl) phosphate (TCPP)) 

BDE-209 

BDE-47 

BDE-99 

HBCDD 

TEHP 

EHDPP 

TCPP 

Soil 

PECyear 1/10/100 (mg kg-1 
wet soil) 

7.3E-04/ 

1.4E-04/ 

1.4E-04/ 

1.3E-04/ 

1.8E-03/ 

7.2E-04/ 

1.5E-03/ 

4.2E-03/ 

4.4E-04/ 

4.4E-04/ 

1.5E-04/ 

1.7E-02/ 

1.9E-03/ 

1.1E-02/ 

5.7E-03/ 

5.4E-04 

5.5E-04 

1.7E-04 

5.7E-02/ 

2.4E-03 

1.9E-02 

RCRyear 1/10/100 (-) 

7.5E-06/ 

1.7E-04/ 

1.7E-04/ 

1.1E-04/ 

2.4E-05/ 

2.4E-02/ 

2.4E-03/ 

4.2E-05/ 

5.2E-04/ 

5.2E-04/ 

1.3E-04/ 

2.3E-04/ 

6.5E-02/ 

1.8E-02/ 

5.8E-05 

6.4E-04 

6.4E-04 

1.4E-04 

7.8E-04 

8.0E-02 

3.1E-02 

Surface 
water 

PECyear 1 (µg L-1) 

1.1E-04 

3.2E-05 

3.2E-05 

1.9E-04 

1.2E-03 

3.3E-02 

5.6E-01 

RCR year 1 (-) 

8.6E-04 

6.5E-04 

6.5E-04 

6.1E-04 

1.8E-04 

1.8E-01 

9.5E-03 

Human 

Total daily intakeyear 
1/10/100 (mg day-1) 

Relative contribution of 
fish consumption10 years 
(%) 

Relative contribution of 
crop, meat and dairy 
consumption10 years (%) 

Relative contribution of 
drinking water10 years (%) 

5.3E-05/ 

2.8E-04 

1.4E-05 

8.8E-04 

2.0E-01 

8.1E-02/ 

4.4E-04 

1.2E-04/ 

2.9E-04 

2.0E-05 

8.8E-04 

5.5E-01 

8.1E-02/ 

2.6E-03 

1.6E-04 

2.9E-04 

2.2E-05 

8.8E-04 

1.9E+00 

8.1E-02 

4.6E-03 

3 

98 

63 

100 

0 

100 

17 

97 

0 

2 

0 

37 

0 

0 

0 

100 

0 

0 

0 

81 

2 

RCRyear 1/10/100 

1.1E-06/ 

5.9E-02 

1.2E-01 

1.3E-01 

2.9E-02 

3.2E-02/ 

6.3E-04 

2.5E-06/ 

6.0E-02 

1.7E-01 

1.3E-01 

7.8E-02 

3.2E-02/ 

3.8E-03 

3.5E-06 

6.1E-02 

1.8E-01 

1.3E-01 

2.7E-01 

3.2E-02 

6.5E-03 

108 

 
 
 
 
 
 
 
 
 
 
 
 
 
13.3.4.6  Source contribution analysis 

Given  the  low  risk  ratios  for  most  flame  retardants,  the  source  contribution  was  focused  on  the  three 
compounds that showed the highest RCR ratio, being BDE-99, BDE-47, HBCDD and TEHP (Table 23). Results 
indicated  that  the  observed  RCR  values  for  human  health  were  slightly  higher  compared  to  the  exclusive 
sludge  modelling  results,  but  even  in  the  long-term  all  below  1.  RCR  values  after  100  years  were  2.1E-01, 
6.0E-1, 1.0E-1 and 6.3E-1 for BDE-47, BDE-99, HCBDD, and TEHP, respectively.    

13.3.4.7  Impact of sludge processing 

Given  the  recalcitrance  of  the  BDEs  and  HCBDD  under  aerobic  and  anaerobic  conditions  under  lower 
temperatures, it  seems  unlikely  that  microbial  degradation  during  composting  and  anaerobic  digestion  may 
remove  significant  shares  of  these  compounds.  Some  microbial  degradation  has  been  observed  for 
organophosphorus compounds (Singh and Walker, 2006), but the efficiency of microbial processes to remove 
organophosphate compounds has not been documented (Lü et al., 2021). Incineration is effective to remove 
BDEs (Wang et al., 2010), HCBDD (Mark et al., 2015), and organophosphate compounds (Korobeinichev et al., 
1997) to low concentrations ranges in ashes, mainly fly ashes.  

109 

 
 
13.3.5  Alkylphenols 

13.3.5.1  Introduction and selection of compounds 

Nonylphenol  is  used  in  the  manufacture  of  antioxidants,  lubricating  oil  additives  and  the  production  of 
nonylphenol  ethoxylates  surfactants.  Nonylphenol  ethoxylates  are  highly  cost  effective  surfactants  with 
exceptional performance and consequently used widely in industrial, institutional, commercial and household 
applications  such  as  detergents,  emulsifiers,  wetting  and  dispersing  agents,  antistatic  agents,  demulsifiers 
and solubilisers (Soares et al., 2008). 
Nonylphenols  and  nonylphenol  ethoxylates  are  included  in  the  Annex  XVII  of  the  REACH  Regulation  (REACH 
restricted substances). 4-nonylphenol ethoxylated, branched and linear, and octylphenol are  also included in 
the  "Authorisation  List"  of  the  Annex  XIV  of  REACH.  This  annex  lists  substances  for  which  authorization  is 
necessary  in  order  to  be  able  to  place  them  on  the  market  within  the  European  Union  (concerning  uses 
covered by the REACH Regulation). Octylphenols and nonylphenols are on the list of priority substances of the 
Water Framework Directive. Nonylphenol ethoxylates are now being replaced by other surfactants in Europe, 
mainly by alcohol ethoxylates.  
Nonylphenol  persists  in  aquatic  environments  and  is  moderately  bioaccumulative.  It  is  not  readily 
biodegradable, and it can take months or longer to degrade in surface waters, soils, and sediments. Ranges 
for octylphenol are one order of magnitude lower (Bolz et al., 2001). 

13.3.5.2  Safe limit values for human consumption 

For  nonylphenol,  a  LOAEL  for  increased  incidence  of  renal  tubular  degeneration  and/or  dilation  in  a  three-
generation  study  on  rats  was  15  mg  kg-1  body  weight  (bw)  day-1  (NTP,  1997),  and  a  total  safety  factor  of 
3000, a safe limit value of 5 µg kg-1 bw day-1 was set, whereas for NPEO a value of 13 µg kg-1 bw day-1 was 
derived (Nielsen et al., 2000). Based on the LOAEL for sperm tail abnormalities in rats (20 ng kg-1 bw) (Blake 
et al., 2004) and a safety factor 300, a tolerable intake was assumed 0.067 ng kg-1 bw day-1 was used for 
octylphenol.  

13.3.5.3  Sludge concentrations 

The alkylphenol concentrations reviewed in the 2012 JRC study (Tavazzi et al., 2012) and earlier works (Bolz 
et  al.,  2001;  Abad  et  al.,  2005;  Fountoulakis  et  al.,  2005;  Krogh  et  al.,  2007)  mostly  indicate  average 
nonylphenol and nonylphenol etoxylate concentration values in the range 10 - 100 mg kg-1 dry weight. Ranges 
for octylphenol are one order of magnitude lower (Bolz et al., 2001). Data on actual compositions, following 
the  implementation  of  new  legislation  that  restricts  the  use  of  alkylphenols,  are  scarce.  Nonetheless, 
preliminary evidence suggests that concentrations of alkylphenols have decreased in last years as a result fo 
regulatory  actions  (Veenaas  et  al.,  2018).  Lamastra  et  al.  (2018)  indicated  concentration  values  for 
nonylphenols and nonylphenol ethoxylates that vary from 1.32 to 103 mg kg−1 DM, with a median of 6.24 mg 
kg−1 DM). Veenas et al. (2018) indicated a maximum concentration observed of 0.73 mg kg-1 for octyphenol in 
sewage  sludge  from  Sweden.  Based  on  these  data, a  value  of  10  mg  kg-1  DM  for  nonylphenol/nonylphenol 
ethoxylate and 1 mg kg-1 DM for octylphenol is applied in this study. 

13.3.5.4  Model input data 

Table 24: Physico-chemical and toxicological data used for risk modelling purposes for the selected alkylphenols. 

4-nonylphenol 

4-nonylphenol 
ethoxylated (NP2EO) 

4-tert-
Octylphenol 

Concentration  in  sludge 
(mg-1 kg-1 dry matter) 

10 

10 

1 

Molecular weight (g mol-1) 

220.4 

308.5  

206.32 

110 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Water solubility (mg L-1) 

5.7 

1.05 

12.6 

(core databse) 

(UNEP, 2017a) 

Vapour pressure (Pa) 

3.0E-01 

1.8E-05 

2.3E-1 

Kow (log 10) 

5.4 

5.3 

4.1 

(UNEP, 2017a) 

Koc (L kg-1) 

1.91E+01 

2.51E+03 

1E+04 

PNECaqua (µg L-1) 

0.33 

0.33 

0.33 

(UNEP, 2017a) 

(Swedish Chemicals 
Agency, 2013) 

(Swedish Chemicals 
Agency, 2013) 

(Swedish Chemicals 
Agency, 2013) 

PNECsoil (mg kg-1 ww) 

1.2 

1.2 

1.2 

limit  values 

Safe 
human 
body weight day-1)  

for 
intake  (mg  kg-1 

Half-life in soil (days) 

(Swedish Chemicals 
Agency, 2013) 

(Swedish Chemicals 
Agency, 2013) 

(Swedish Chemicals 
Agency, 2013) 

5.00E-03  

1.30E-02 

6.70E-08 

(2) 

16.5 

16.5 

14 

(Swedish Chemicals 
Agency, 2013) 

(Swedish Chemicals 
Agency, 2013) 

(Langdon et al., 2011) 

Half-life 
(degradation, days) 

in 

water 

37 

37 

50 

(Swedish Chemicals 
Agency, 2013) 

(Swedish Chemicals 
Agency, 2013) 

(UNEP, 2017a) 

BCFfish-water (L kg-1ww) 

3.14E+03 

3.40E+01 

4.70E+02 

(UNEP, 2017a) 

(UNEP, 2017a) 

(UNEP, 2017a) 

(1)4-Nonylphenol has a dissociation constant of approximately or or 10, indicating ionic properties. Log Kow is 
a  conservative  estimate  of  the  lipid  partitioning:  when  the  compound’s  potential  to  ionise  is  taken  into 
account, the overall partitioning for all of its species (neutral + ionic) may be considerable considerably less 
(ECETOC, 2013). A general rule is to assume that the ionised species will not be available for partitioning to 
air or organic material, and is thus entirely present in the dissolved phase (ECETOC, 2013). 
(2) For nonylphenol, a LOAEL for increased incidence of renal tubular degeneration and/or dilation in a three-
generation study on rats was 15 mg kg-1 bw day-1 (NTP, 1997), and a total safety factor of 3000, a safe 
limit value of 5 µg kg-1 bw day-1 was set, whereas for NPEO a value of 13 µg kg-1 bw day-1 was derived 
(Nielsen et al., 2000).Based on the LOAEL  for sperm tail abnormalities in rats (20 ng kg-1 bw) (Blake et al., 
2004)  and  a  safety  factor  300,  a  tolerable  intake  was  assumed  0.067  ng  kg-1  bw  day-1  was  used  for 
octylphenol. 
(3)In the absence of a well-developed database on the transfer of alkylphenols from soil to plant, the values 
reported  by Sjöström et al.  (2008) for sewage  sludge amended  soils were  used to  model plant  uptake. The 
reported  value  of  0.71  on  a  dry  matter  basis  was  converted  towards  a  wet  mass  basis  (mg  kg-1  plant 
ww)/(mg kg-1 soil ww) assuming a water content in soil of 20vol% (EUSES default, conversion factor for soil 
concentration  wet-dry  weight  soil  of  1.13),  and  a  water  content  in  roots  of  65vol%,  and  a  bulk  density  of 
plants  of  700  kg/m3  (EUSES  default),.  These  values  are  used  for  all  alkylphenols  under  study.  The 

111 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
concentrations  in  root  were  multiplied  with  a  factor  2  to  account  for  the  observed  enrichment  of  shoots 
versus  roots  (Y.  Hu  et  al.,  2021).  Further  transfer  to  meat  and  milk  was  modelled  using  the  default  model 
based on Kow. 

13.3.5.5  Estimated environmental and health exposure and risks from sludge application 

The results of the assessment that consider the exclusive sludge applications on agricultural land indicates an 
exceedance of RCR  for  surface water (4-nonylphenol) and  human  health in the  short- and long-term  for  4-
nonylphenol  and  4-tert-octylphenol.  Significant  concerns  have  been  observed  for  the  former,  whereas 
moderate  concerns  are  indicated  for  the  latter.  Due  to  relatively  fast  degradation  of  alkylphenols  in  soils 
(Langdon et al., 2011; Swedish Chemicals Agency, 2013), the RCR ratios do not increase over time.  

Table  25:  Environmental  and  human  health  risk  screening  assessment  of  the  exclusive  application  of  flame  retardants 
present in sewage sludge to agricultural soils (PEC: predicted environmental concentration, RCR: risk characterisation ratio) 

4-
nonylphenol 

4-nonylphenol 
ethoxylated (NP2EO) 

4-tert-
octylphenol 

Soil 

PECyear 1/10/100 (mg kg-1 wet soil) 

RCRyear 1/10/100 (-) 

PECyear 1 (µg L-1) 

RCR year 1 (-) 

Surface 
water 

Human 

Total daily intakeyear 1/10/100 (mg 
day-1) 

Relative contribution of fish 
consumption10 years (%) 

Relative contribution of crop, meat 
and dairy consumption10 years (%) 

Relative contribution of drinking 
water10 years (%) 

RCRyear 1/10/100 

8.9E-03 / 

8.9E-03/ 

8.9E-03 

7.4E-03/ 

7.4E-03/ 

7.4E-03 

3.4E+00 

1.0E+01 

1.8E+00/ 

1.8E+00/ 

1.8E+00 

17 

83 

0 

5.2E+00/ 

5.2E+00/ 

5.2E+00 

1.1E-03/ 

1.1E-03/ 

1.1E-03 

8.9E-04/ 

9.0E-04/ 

9.0E-04 

8.1E-02 

2.5E-01 

2.1E-03/ 

2.1E-03/ 

2.1E-03 

2 

98 

0 

2.3E-03 

2.3E-03 

2.3E-03 

1.0E-03/ 

1.0E-03/ 

1.0E-03 

8.4E-04/ 

8.4E-04/ 

8.4E-04 

2.4E-02 

7.2E-02 

2.0E-04/ 

2.0E-04/ 

2.0E-04 

92 

7 

1 

4.2E+01/ 

4.2E+01/ 

4.2E+01 

13.3.5.6  Source contribution analysis 

No  source  contribution  analysis  has  been  performed  since  data  on  background  concentrations  in 
environmental compartments is expected to decrease over time due to regulatory actions, and the relatively 
low residence times of alkylphenols in soils and waters. Therefore, relevant data could not be acquired. 

13.3.5.7  Impact of sludge processing 

The  recent  review  paper  of  Lü  et  al.  (2021)  investigated  the  levels  and  removal  of  nonylphenol  and 
nonylphenol ethoxylates during sludge composting. During sludge composting, the degradation of nonylphenol 
ethoxylates could form nonylphenol, leading to slightly higher concentrations of nonylphenol and the sum of 
(nonylphenol + nonylphenol ethoxylates) in sludge composts than in untreated sludge (González et al., 2010). 
On  the  other  hand,  a  considerable  removal  (64–95%)  of  nonylphenol  and  nonylphenol  ethoxylates  was 
recorded during sludge composting in other works (Pakou et al., 2009; Priac et al., 2017; Zheng et al., 2018). 

112 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Anaerobic  digestion  has  been  observed  to  remove  roughly  50%  of  alkylphenols  in  sludge  (Paterakis  et  al., 
2012).  No  data  on  the  fate  of  nonylphenols  by  incineration  have  been  identified,  but  most  probably  the 
substances would be nearly 100% destroyed by the incineration process, based on similarities with other non-
persistent substances (Environment, 2013). 

13.3.6  Polychlorinated alkanes 

13.3.6.1  Introduction and selection of compounds 

Polychlorinated  alkanes  represent  a  large  class  of  compounds  that  are  typically  classified  according  to 
structural characteristics such as carbon chain length and degree of chlorination. Polychlorinated alkanes are 
also  classified  according  to  the  variety  of  feedstocks  from  which  they  are  manufactured  (polychlorinated 
paraffins  and  polychlorinated  olefins,  for  example, are  two  such  categories).  Especially  paraffins  are  stable 
compounds, and short-chain chlorinated paraffins (SCCPs) are listed as persistent organic pollutants under the 
Stockholm Convention (EFSA Panel on Contaminants in the Food Chain et al., 2020). Because of regulations 
and  concerns  about  SCCPs,  the  use  of  mid-chain  chlorinated  paraffins  (MCCPs)  has  increased  and  has 
represented the majority of production over the last decades (Glüge et al., 2018). An estimate derived from 
the  addition  of  each  individual  registrant  volumes  from  the  ECHA  shows  that  the  amount  of  CPs 
manufactured  and/or  imported  in  the  European  Economic  Area  is  around  10,000–100,000  tonnes  per  year 
(EFSA Panel on Contaminants in the Food Chain et al., 2020). 

Polychlorinated  alkanes  have  been  produced  since  the  1930s  for  a  variety  of  purposes  (van  Mourik  et  al., 
2015; EFSA Panel on Contaminants in the Food Chain et al., 2020). They are used as additives in lubricants 
and cutting fluids in the metal industry and are also used as flame retardants in the rubber industry, in PVC 
plastics  and  in  sealants  for  use  in  building,  automotive  and  industrial  applications,  and  the  longer  chain 
mixtures are also  used as plasticisers in paints and other materials.  Of particular relevance for this work is 
that they are consumed in the textile industry for the production of flame-resistant, water repellent and rot-
preventing textile finishes. 

13.3.6.2  Safe limit values for human consumption 

The  recent assessment of EFSA on  polychlorinated  paraffins  selected as reference  points a  BMDL10 of 2.3 
mg/kg bw per day for increased incidence of nephritis in male rats, and of 36 mg/kg bw per day for increased 
relative  kidney  weights  in  male  and  female  rats  for  SCCPs  and  MCCPs,  respectively  (EFSA  Panel  on 
Contaminants in the Food Chain et al., 2020). For long-chain chlorinated paraffins, a reference point relevant 
for  humans  could  not  be  identified.  The  Panel  also  concluded  that  a  Margin  of  Exposure  (MoS)  higher than 
1000 might indicate that there is no health concern. Therefore, the safe limit values for human consumption 
were set at 2.3E-3 mg/kg bw per day and 36E-3 mg/kg bw per day for SCCPs and MCCPs, respectively.  

13.3.6.3  Concentrations observed in sludge 

Recent concentration data for sludges generated in the EU are difficult to collect. Rigby et al. (2021) indicated 
summed polychlorinated alkane concentrations, including SCCPs and MCCPs and likely other substances, of 6 
and  140  mg  kg-1  dry  matter  for  two  sewage  sludges  from  the  UK.  With  specific  reference  to  SCCPs  and 
MCCPs, Thomas et al. (2011) reported average concentration for sewage sludges from Norway of 12 mg kg-1 
(SCCPs)  and  7  mg  kg-1  (MCCPs).  Sewage  sludge  from  Swedish  WWTPs  collected  between  2004  and  2010 
showed  a  median  concentration  for  SCCPs  of  1.1  mg/kg  dry  weight  (dry  matter)  and  for  MCCPs  a  median 
concentration of 3.8  mg/kg dry matter (Olofsson et al., 2012). Values in sludge from  wastewater treatment 
plants  in  the  Czech  Republic  (0.4  and  2.3  mg  kg-1  dry  matter  for  SCCPs  and  MCCPs,  respectively)  and 
Switzerland  (0.5  -1.2  and 0.1  -  80  mg  kg-1  dry  matter  for SCCPs and MCCPs, respectively)  (Přibylová  et  al., 
2006;  Bogdal  et  al.,  2015).  Older  studies  indicated  on  average  higher  concentrations  (Clarke  and  Smith, 
2011), with for instance SCCPs measured in two German sludge samples, which contained 65 and 47 mg kg−1 
dry matter of SCCPs (Rieger and Ballschmiter, 1995). Concentrations of MCCPs in samples of digested sludge 
from  the  UK  were  in  the  range  1.8  to  93  mg  kg−1  dry  matter  (Nicholls  et  al.,  2001).  In  another  UK  survey, 
SCCPs and MCCPs concentrations were between 7–200 mg kg−1 dry matter and 30–9700 mg kg−1 dry matter, 
respectively (Stevens et al., 2003). Comparison of  data from the limited amount of information available is 
difficult  and  further  complicated  by  the  lack  of  standardised  measurement  methods  for  SCCPs and  MCCPs. 

113 

 
 
 
 
 
 
For this study, high-end values (aligned to the recent observations from Rigby et al. (2021))  of 100 mg kg−1 
dry  matter  were  assumed  for  both  SCCPs  and  MCCPs.  Actual  and  standardised  data  on  polychlorinated 
alkanes in sewage sludge is required to fine-tune the assessment.  

13.3.6.4  Model input data 

Table  26:  Physico-chemical  and  toxicological  data  used  for  risk  modelling  purposes  for  the  selected  polychlorinated 
alkanes. 

SCCPs(1) 

MCCPs(1) 

Concentration in sludge (mg-1 kg-1 dry matter) 

100 

100 

(see main text) 

(see main text) 

Molecular weight (g mol-1) 

320-500 (410) 

300 - 600 (450) 

Water solubility (mg L-1) 

0.15 - 0.47 (0.33) 

0.005 - 0.027 (0.016) 

(ECHA, 1999) 

(UK Environment Agency, 2019) 

(ECHA, 1999) 

(UK Environment Agency, 2019) 

Vapour pressure (Pa) 

2.1E-2 

2.7E-4 

(ECHA, 1999) 

(UK Environment Agency, 2019) 

Kow (log 10) 

4.4 – 8.0 (6.7) 

4.7 – 8.3 (7.2) 

(ECHA, 1999) 

(UK Environment Agency, 2019) 

Koc (L kg-1) 

3.4E+05 

8.5E+05 

(derived from Kow)(2) 

(derived from Kow)(2) 

PNECaqua (µg L-1) 

0.5 

0.87 

(ECHA, 1999) 

(UK Environment Agency, 2019) 

PNECsoil (mg kg-1 ww) 

5.2 

10.6 

(equilibrium partitioning method) 

(UK Environment Agency, 2019) 

Safe limit values for human intake  

2.3E-03 

3.6E-02 

(mg kg-1 body weight day-1)  

(EFSA Panel on Contaminants 
in the Food Chain et al., 2020) 

(EFSA Panel on Contaminants in 
the Food Chain et al., 2020) 

Half-life in soil (days) 

Unknown (default value for not 
biodegradable, 527292 days) 

Unknown (default value for not 
biodegradable, 527292 days) 

Half-life in water (degradation, days) 

Not readily or inherently 
biodegradable (1000) 

(ECHA, 1999) 

1-9300 (1000) 

(Glüge et al., 2018; UK 
Environment Agency, 2019) 

Regional  background 

in  soil  (mg  kg-1  dry 

1.0E-03 

3.0E-02 

114 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
matter)(2) 

(Halse et al., 2015) 

(Glüge et al., 2018) 

Regional background in surface water (µg L-1) 

Not available 

0.13 

(Glüge et al., 2018) 

(1)In contrast to other well-defined substances, SCCPs and MCCPs are complex industrial chemicals with the 
molecular formula CnH2n+2−xClx are a mixture of different compounds with varying carbon chain length and 
degree  of  chlorination  that  may  have  different  physicochemical  and  toxicological  properties.  The  values 
presented  here  are  therefore  not  representative  for  one  specific  compound,  but  rather  aim  to  provide  a 
general  group  estimate.  Ranges are  given  for  the  different  parameters,  with  the  values  used  for  modelling 
indicated in between brackets. 
(2)Based on EUSES default for hydrophobic substances: log Koc = 0.81 x log Kow + 0.1  

13.3.6.5  Estimated environmental and health exposure and risks from sludge application 

The outcome of the risk screening assessment resulting from the application of SCCPs and MCCPs present in 
sewage sludge to agricultural soils (without ‘background’ concentrations of water and soils) indicated that risk 
characterisation ratios below 1 for soils after 100 years of continuous sludge application. For human health, 
RCRs  above  1  were  indicated  for  the  entire  time  period  under  study,  up  to  a  value  of  1.6E+03  indicating 
significant risks in the long-term (100 years) (Table 27). Soil grown crops, dairy and meat products were the 
exclusive  sources  that  contributed  to  SCCPs  and  MCCPs  intake,  whereas  contaminant  transfer  to  drinking 
water and fish were negligible (Table 27). 

Table  27:  Environmental  and  human  health  risk  screening  assessment  of  the  exclusive  application  of  short-  and  long-
chain  polychlorinated  paraffins  (SCCPs  and  MCCPs,  respectively)  present  in  sewage  sludge  to  agricultural  soils  (PEC: 
predicted environmental concentration, RCR: risk characterisation ratio) 

Soil 

PECyear 1/10/100 (mg kg-1 wet soil) 

RCRyear 1/10/100 (-) 

PECyear 1 (µg L-1) 

RCR year 1 (-) 

Surface 
water 

Human 

Total daily intakeyear 1/10/100 (mg 
day-1) 

Relative contribution of fish 
consumption10 years (%) 

Relative contribution of crop, meat 
and dairy consumption10 years (%) 

Relative contribution of drinking 
water10 years (%) 

RCRyear 1/10/100 

SCCPs 

1.5E-01/ 

1.6E+00/ 

1.3E+01 

1.2E-01 

1.3E+00 

1.1E+01 

9.3E-02 

1.9E-01 

4.0E+00 

3.3E+01 

2.6E+02 

0 

100 

0 

2.5E+01 

2.1E+02 

1.6E+03 

MCCPs 

1.5E-01/ 

1.6E+00/ 

1.3E+01 

1.2E-01 

1.3E+00 

1.1E+01 

3.7E-02 

4.2E-02 

2.6E+01/  

2.9E+02/  

2.4E+03 

0 

100 

0 

1.0E+01/  

1.1E+02/  

9.4E+02 

115 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
13.3.6.6  Source contribution analysis 

Information  on  background  concentrations  in  soils  and  waters  for  SCCPs  and  MCCPs is scarce  (Halse  et  al., 
2015;  Glüge  et  al.,  2018),  and  measured  data  may  show  a  high  degree  of  variability  due  to  the  lack  of 
standardised measurement methods for these complex industrial mixtures and high total number of possible 
congeners therein. Given the importance of soil-derived food materials to total human intake, soil background 
concentration  are  central  whereas  background  concentrations  in  water  will  not  influence  the  results.  For 
SCCPs,  the  model  predicted  no  increase  in  RCRsoil  or  RCRhuman  compared  to  model  results  that  only  consider 
sewage sludge applications, whereas for MCCPs, the inclusion of soil background concentrations in the model 
resulted  in  marginally  higher  RCRsoil  and  RCRhuman  (Table  28).  This  is  because  the  observed  background 
concentrations in soils were more than order of magnitude higher for MCCPs than for SCCPs. Acknowledging 
the  uncertainty  to  the  dataset,  the  source  contribution  analysis  should  therefore  be  interpreted  with  the 
necessary degree of caution. Still, it could be observed that for both SCCPs and MCCPs, sludge was a much 
greater contributor to the total pollutant concentrations in soils than the background (Table 28). This suggests 
that sludge could be a main source of pollution for SCCPs and MCCPs. 

Table 28: Environmental and human health risk screening assessment for short- and long-chain polychlorinated paraffins 
(SCCPs and MCCPs, respectively), based on its present background concentrations observed in the environment along with 
sewage  sludge  applications  to  agricultural  land  (PEC:  predicted  environmental  concentration,  RCR:  risk  characterisation 
ratios) 

Soil 

PECyear 1/10/100 (mg kg-1 wet soil) 

SCCPs 

1.5E-01/ 

1.6E+00/ 

1.3E+01 

MCCPs 

1.8E-01/ 

1.6E+00/ 

1.3E+01 

Contribution of sludge to total concentration (%) 

99/ 100/ 100 

83/ 98/ 100 

Surface 
water 

RCRyear 1/10/100 (-) 

PECyear 1 (µg L-1) 

RCR year 1 (-) 

Human 

Total daily intakeyear 1/10/100 (mg day-1) 

RCRyear 1/10/100 

1.2E-01 

1.3E+00 

1.1E+01 

4.0E+00 

3.3E+01 

2.6E+02 

2.5E+01 

2.1E+02 

1.6E+03 

1.5E-02/ 

1.4E-01/ 

1.1E+00 

3.5E+01/ 

2.9E+02/ 

2.4E+03 

1.4E+01/ 

1.2E+02/ 

9.5E+02 

13.3.6.7  Impact of sludge processing 

With few studies that focused on SCCPs and MCCPs in sewage sludge, it is unexpected that little information 
is available on their removal potential through sludge processing. Microbial degradation processes, involving 
composting and anaerobic digestion, seem to be vary as a function of the individual susbtances that make up 
the  chloroalkane  mixtures,  and  the  relative  positions  of  the  chlorine  atoms  (Heath  et  al.,  2006).  Specific 
aerobic microorganisms have been documented to remove until about 50% of the SCCPs in periods of weeks 
(Lu, 2013). Mo information could be retrieved on their degradation under anaerobic conditions during sludge 
digestion processes. Rigby et al. (2021) indicated generally low total polychlorinated alkane concentrations in 
incinerated waste materials,  but it  remains  unclear if these are the direct  result of the incineration process 
itself  or  their  low  occurrence  in  the  feedstock  applied.  However,  nearly  complete  dehydrochlorination 
processes in the temperature range 300–600°C have been reported for polychlorinated alkanes (Camino and 
Costa, 1980) as well as low to negligible concentrations in incinerations char and ash residues above 500°C 

116 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
(Xin et al., 2018). These observations suggest that thermal oxidation is effective in removing the overall share 
of the polychlorinated alkanes present in sewage sludge.  

13.3.7  Polychlorinated naphthalenes (PCNs) 

13.3.7.1  Background and selection of compounds 

Polychlorinated naphthalenes (PCNs) comprise of 75 possible congeners in eight homologue groups with one 
to eight chlorine atoms substituted around the planar aromatic naphthalene molecule. The basic structure of 
the PCNs has the molecular formula C10H8-nCln, where n=1-8 (UNEP, 2017b). Physical-chemical properties 
vary  considerably  due  to  the  degree  of  chlorine  substitution.  The  physical  state  ranges  from  thin  liquids  to 
hard  waxes.  Tri-  through  octa-CNs  are  very  lipophilic  with  high  log  Kow  (>5)  and  their  water  solubility  and 
vapour pressure decrease with the degree of chlorination (UNEP, 2017b). 

Polychlorinated naphthalenes (PCNs) have been commercially produced and used mainly in electrical devices, 
but also for impregnation of wood, paper, paints, and textiles to attain waterproofness, flame resistance and 
protection  against  insects,  molds and  fungi  (Jakobsson  and  Asplund, 2000).  Many  of  these  intentional  uses 
have  ceased  to  take  place  due  to  increasing  health  concerns  of  PCNs  (UNEP,  2017b).  Polychlorinated 
naphthalenes  are,  however,  also  present  and  occurring  unintentionally  during  industrial  manufacturing 
processes (e.g. in technical PCB mixtures,  the  production  of chlorinated solvents,  and  chlorine  via chloralkali 
electrolysis).  In  addition,  PCNs  are  formed  together  with  PCDD/PCDFs  in  thermal  processes  such  as 
incineration or metal industries (UNEP, 2017b).  

13.3.7.2  Safe limit values for human consumption 

In the framework of Articles 23 and 33 of Regulation (EC) No 178/2002 EFSA has received from the European 
Commission  a  mandate  (M-2010-0374),  EFSA  is  currently  collecting  data  on  PCNs  EFSA’s  for  scientific 
opinions and reports on pollutants in food and feed. 

Li  et  al.  (2020)  proposed  toxicity  equivalence  factors (TEFs)  relative  to  2,3,7,8-TCDD.  The  TEFs  reported  for 
certain hexa- and penta-CNs (0.002 – 0.004) are about 2-3 orders of magnitude higher for penta- and octa-
CNs. Therefore, it is proposed (i) to apply the limit value for the related PCDD/F compounds of 2.9E-10 mg kg-
1 body weight day-1, and (ii) to focus the assessment on selected hexa- and penta-CNs (PCN-66/67 and PCN 
73) that are known to mostly accumulate in the human body (Agunbiade et al., 2020). 

13.3.7.3  Concentrations observed in sludge 

Polychlorinated naphthalene concentrations in sludge have been reported by a limited set of studies (Harrison 
et al., 2006; Clarke and Smith, 2011; Rigby et al., 2021). The study of Rigby et al. (2021) provides likely the 
most  comprehensive  PCN  dataset  available.  The  average  calculated  values  for  three  UK  sewage  sludge, 
expressed as toxicity equivalents, of 40 and 68 pg kg-1 dry matter, for respectively PCN-66/67 and PCN-73 
were retained in this assessment.  

13.3.7.4  Model input data 

Table  29:  Physico-chemical  and  toxicological  data  used  for  risk  modelling  purposes  for  the  selected  polychlorinated 
naphthalene congeners 667/67 (mixture of 1,2,3,4,6,7-HxCN and 1,2,3,5,6,7-HxCN) and 73 (1,2,3,4,5,6,7-HpCN). 

PCN 66/67 

PCN 73 

(mg-1 
Concentration 
2,3,7,8-TCDD  toxicity  equivalents 
kg-1 dry matter) 

in  sludge 

4.0E-8 

6.8E-8 

117 

 
 
 
 
 
 
 
 
 
 
 
 
 
Molecular weight (g mol-1) 

335 

369.5 

Water solubility (mg L-1) 

0.11E-3 

0.04E-3 

Vapour pressure (Pa) 

0.001 

2.6E-4 

Kow (log 10) 

6.7 (1) 

6.6 (1) 

Koc (L kg-1) 

3.4E+05 

2.8E+05 

(Puzyn and Falandysz, 2005)(Puzyn and Falandysz, 
2007)(Chayawan and Vikas, 2015) 

PNECaqua (µg L-1) 

1.0E-03 

(2) 

(3) 

1.0E-3 

PNECsoil (mg kg-1 ww) 

5.94E-03 

4.93E-03 

Safe  limit  values  for  human  intake 
(mg kg-1 body weight day-1)  

(derived from PNECaqua) 

4.0E-09 for the sum of PCNs 

(WHO, 1998b) 

Half-life in soil (days) 

3650 

3650 

(4) 

Half-life 
days) 

in  water 

(degradation, 

263646 

263646 

(default value for non-biodegradable substances) 

(1)Congener-specific  estimated  Kow  values,  derived  through  the  extrapolation  of  measured  Kow  values  for 
other congeners, have been retained in this assessment.  
(2) Based on EUSES default for hydrophobic substances: log Koc = 0.81 x log Kow + 0.1 
(3)The  ECOSAR-predicted  chronic  toxicity  of  hepta-CNs  to  fish  and  daphnids  is  in  the  low  μg/L  range 
(Environment  Canada,  2011).  An  assessment  factor  of  1000  has  been  applied  to  derived  the  values 
presented. 
(4)Järnberg  et  al.  (1999)  did  not  find  any  measurable  change  in  the  congener  composition  of  tetra-  to 
hexachlorinated  naphthalenes  in  a  28-day  aerobic  degradation  experiment.  Half-lifes  up  to  10  years  in 
sewage sludge amended soils were reported by Meijer et al. (2001). 
(5)Meijer et al. (2001) analysed rural soils in the United Kingdom dating back to the 1940s. They found a peak 
level of 12 µg/kg dry weight in the 1960s, falling to 0.5–1 µg/kg in 1990. 

13.3.7.5  Estimated environmental and health exposure and risks from sludge application 

The  outcome  of  the  risk  screening  assessment  resulting  from  the  application  of  PCN  66/67  and  PCN-73 
present  in  sewage  sludge  to  agricultural  soils  (without  ‘background’  concentrations  of  water  and  soils) 
indicated  that  risk  characterisation  ratios were  well  below  1  for  soils,  surface  waters  and humans  after  10 
years of sewage sludge application (Table 34. However, when considering a longer time frame of 100 years 
of application, the ratio was  marginally above 1 (1.1E+00, Table 34). The total human daily intake after 10 
years of consecutive sludge applications, expressed as PCDD TEQs, for the selected PCNs is about 3 orders of 
magnitude lower than for 2,3,7,8-TCDD (see section 13.3.3). Previous work measured low PCN concentrations 

118 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
in  food  (including  fish,  vegetables,  meat  and  dairy  products),  at  levels  that  do  not  not  pose  toxicological 
concerns (Fernandes et al., 2010). Hence, the incidence of a human health risks from PCNs in sewage sludge 
seems to a borderline case, and further detailed analysis will have to shed further light in view of ensuring 
health protection. 

Table  30:  Environmental  and  human  health  risk  screening  assessment  of  the  exclusive  application  of  the  selected 
polychlorinated naphthalene (congeners 667/67 (mixture of 1,2,3,4,6,7-HxCN and 1,2,3,5,6,7-HxCN) and 73 (1,2,3,4,5,6,7-
HpCN), respectively) present in sewage sludge to agricultural soils (PEC: predicted environmental concentration, RCR: risk 
characterisation ratio) 

Soil 

PECyear 1/10/100 (mg kg-1 wet soil) 

RCRyear 1/10/100 (-) 

PECyear 1 (µg L-1) 

RCR year 1 (-) 

Surface 
water 

Human 

Total daily intakeyear 1/10/100 (mg 
day-1) 

Relative contribution of fish 
consumption10 years (%) 

Relative contribution of crop, 
meat and dairy consumption10 
years (%) 

Relative contribution of drinking 
water10 years (%) 

RCRyear 1/10/100 

PCN 66/67 

5.9E-11 

4.6E-10 

9.0E-10 

9.9E-09 

7.8E-08 

1.5E-07 

3.7E-11 

3.7E-08 

1.0E-09 

5.1E-09 

9.5E-09 

8 

92 

0 

5.1E-02 

2.6E-01 

4.8E-01 

PCN 73 

1.0E-10 

7.9E-10 

1.6E-09 

2.0E-08 

1.6E-07 

3.2E-07 

7.6E-11 

7.6E-08 

1.6E-09 

6.6E-09 

1.2E-08 

13 

87 

0 

7.9E-02 

3.3E-01 

6.1E-01 

SUM PCN-2 

2.6E-09 

1.2E-08 

2.2E-08 

1.3E-01 

5.9E-01 

1.1E+00 

13.3.7.6  Source contribution analysis 

No  sludge  contribution  analysis  could  be  performed  as  no  reliable  background  concentrations  in  soils  and 
waters could be retrieved. The most harmful PCN congeners; CNs 66, 67, 73, and 52 were mostly found in all 
their  food  samples  (Fernandes  et  al.,  2010).  The  dioxin-like  toxicity  (PCN  TEQ)  associated  with  these 
concentrations is 1−2 orders of magnitude lower than those reported for chlorinated dioxins or PCBs in food 
(Fernandes et al., 2010). 

13.3.7.7  Impact of sludge processing 

The impact of sludge processing options on PCNs has not been performed. Nonetheless, given the similarities 
in chemical characteristics with PCBs, a similar behaviour is expected during biological and thermal treatment 
processes. 

119 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
13.3.8  Organotin compounds 

13.3.8.1  Introduction and selection of compounds 

Organotin compounds that are used in the preparation of polyvinylchloride (PVC) plastics. They have also been 
widely used as general biocides in paints, leather, textiles, the production of paper and as wood preservatives 
and slimicides. The most important source of exposure of the general population is from food (in particular 
fish  and  other  seafood).  Food  contamination  is  primarily  caused  by  the  use  of  tri-substituted  organotin 
compounds  as  biocides,  components  of  antifouling  paints  and  as  agricultural  pesticides.  However,  tri-
substituted organostannic compounds have been banned for use as biocides under Directive 98/8/EC.  Water 
basins, especially those with a low water exchange, may  also accumulate OTC due to boating activities and 
agricultural runoff, with subsequent accumulation in the food chain.  

The  assessment  of  environmental  and  human  health  risks  caused  by  the  organotins  is  difficult.  The  large 
number  of  compounds  with  very  different  properties  in  the  group  makes  it  difficult  to  make  general 
conclusions. Sludge concentration values have often been reported for dibutyltins (DBT), tributyltins (TBT), and 
triphenyltins (TPT), where these have been identified as compounds of concern (e.g. Clarke and Smith, 2011). 
Safe limit values for human consumption of these compounds is available, for which reason these compounds 
were taken forward.  

13.3.8.2  Safe limits for human consumption 

An  EFSA  assessment  on  organotin  compounds  focused  on  the  most  toxic  organotin  compounds:  DBT,  TBT, 
Dioctyltins  (DOT),  and  TPT.  A  group  TDI  of  0.25  μg  kg-1  body  weight  day-1  for  DBT,  TBT,  DOT  and  TPT 
compounds was established by EFSA (EFSA, 2004). This value was used in this assessment, with the caveat 
that only three compounds were assumed to contribute to the group safe limit value for human consumption. 

13.3.8.3  Sludge concentrations 

The ranges reported from mono-, di and tributyltin by Voulvoulis et al. (2006) all had similar ranges from 0.3 
to  values  above  8  mg  kg-1  dry  matter.  Values  for  TPT  documented  in  the  review  paper  of  Harrison  et  al. 
(2006) ranged from 0.3 to 3.4 mg kg-1 dry matter, whereas for TBT (up to 297 mg kg-1 dry matter) and DBT 
(up to 8.6 mg kg-1 dry matter) higher values were reported based on older studies.  

Since  2010,  EU  restrictions  for  the  use  of  certain  organotin  compounds  is  further  extended  to  cover  many 
consumer products (e.g. including clothes, hygiene products, PVCs) by Decision 2009/524/EC. Therefore, it can 
reasonably  be  assumed  that  organotin  concentrations  reported  in  sludge  before  2010  may  not  be 
representative for current-day situations. This is partially confirmed by studies after that date that generally 
reported  much  lower  values  compared  to  previous  periods.  Wiechmann  et  al.  (2013)  indicated  organotin 
concentrations below 1 mg kg-1 dry matter for DBT (0.22 mg kg-1 dry matter), TBT (0.03 mg kg-1 dry matter), 
and DOT (0.06 mg kg-1 dry matter). Similarly, Oloffson et al. (2012) indicated values for summed organotin 
compounds of 0.15 mg kg-1 dry matter. Mailler et al. (2014) reported values below 0.05 mg kg-1 dry matter 
for TPT and TBT, whereas DBT has maximum concentration values of about 0.3 mg kg-1 dry matter.  

In this assessment, concentration values of 0.3 mg kg-1 dry matter were assumed for DBT, whereas for TBT, 
and  TPT  a  value  of  0.1  mg  kg-1  dry  matter  was  assumed.  DOT  is  not  considered  in  this  assessment  due 
because the single value reported for sewage sludge was very low. Hence, the assessment will only cover the 
joint contribution of the DBT, TBT, and TPT for the wider group of organotins. 

13.3.8.4  Model input data  

Table 31: Physico-chemical and toxicological data used for risk modelling purposes for the selected organotin compounds. 

Triphenyltin (TPT) 

Dibutyltin (DBT) 

Tributyltin (TBT) 

Concentration in sludge (mg-1 

0.1 

0.3 

0.1 

120 

 
 
 
 
 
 
 
 
 
 
 
 
kg-1 dry matter) 

(see main text) 

(see main text) 

(see main text) 

Molecular weight (g mol-1) 

350 

249 

280.9 

Water solubility (mg L-1) 

Vapour pressure (Pa) 

Kow (log 10) 

5 

0.8 

3.7 

(van Herwijnen, 2012) 

20 

(van Herwijnen, 2012) 

0.16 

(van Herwijnen, 2012) 

1.6 

(van Herwijnen, 2012) 

5.3 

48.5 

4.1 

Koc (L kg-1) 

5.0E+05 

4.2E+04 

3.2E+04 

(van Herwijnen, 2012) 

PNECaqua (µg L-1) 

2.6E-02 

1.9E-02 

2.6E-02 

(Scientific Committee on Health and Environmental Risks, 2006) 

PNECsoil (mg kg-1 ww) 

1.2E-01 

1.9E-02 

1.1E-02 

Safe  limit  values  for  human 
intake  (mg  kg-1  body  weight 
day-1)  

(equilibrium partitioning method) 

0.25 μg kg-1 body weight day-1 for the sum of DBT, TBT, DOT and TPT  

(EFSA, 2004) 

Half-life in soil (days) 

527292 

120 

527292 

(default value in the absence of 

biodegradation data) 

(van Herwijnen, 2012) 

(default value in the absence of 
biodegradation data) 

Half-life in water (degradation, 
days) 

263646 

263646 

263646 

Regional  background  in  soil 
(mg kg-1 dry matter)(2) 

Regional 
surface water (µg L-1) 

background 

in 

(default value in the absence of 

(default value in the absence of 

biodegradation data) 

biodegradation data) 

(default value in the absence of 
biodegradation data) 

1.0E-02 

3.0E-02 

1.0E-02 

(Sternbeck et al., 2006) 

(Sternbeck et al., 2006) 

(Sternbeck et al., 2006) 

1.0E-02 

5.0E-02 

1.0E-01 

(Sternbeck et al., 2006) 

(Sternbeck et al., 2006; 
Cavalheiro et al., 2016) 

(Sternbeck et al., 2006; 
Cavalheiro et al., 2016) 

(1)There  are  no  measured  data  available  for  the  physical  and  chemical  properties  for  all  these  substances. 
Physico-chemical  (e.g.  Kow)  used  in  this  assessment  are  average  values  for  different  compounds  that  fall 
under  the  respective  organotin  group  (averages  for  bis(tributyltin)oxide,  tributyltin  chloride,  and  tributyltin 
hydride for organotin referred to as tributyltin).  

121 

 
 
 
 
 
 
 
 
 
 
 
13.3.8.5  Estimated environmental and health exposure and risks from sludge application 

The outcome of the risk screening assessment resulting from the application of organotins present in sewage 
sludge  to  agricultural  soils  (without  ‘background’  concentrations  of  water  and  soils)  indicated  that  risk 
characterisation ratios were well below 1 for soils and humans (maximum up of 6.6E-01 for RCRsoil year 100 for 
TBT, 1E-03 for RCRhuman  100  year) (Table 32. This high differences compared to the step 1 assessment is due to 
the reduced sludge concentration values that was observed in recent literature (0.1 mg kg-1 versus a value > 
100 mg kg-1 applied in the Step 1 assessment).  

Table  32:  Environmental  and  human  health  risk  screening  assessment  of  the  exclusive  application  of  the  organotins 
Triphenyltin  (TPT),  Dibutyltin  (DBT),  Tributyltin  (TBT)  present  in  sewage  sludge  to  agricultural  soils  (PEC:  predicted 
environmental concentration, RCR: risk characterisation ratio) 

Triphenyltin (TPT) 

Dibutyltin (DBT) 

Tributyltin (TBT) 

Soil 

PECyear 1/10/100 (mg kg-1 wet 
soil) 

RCRyear 1/10/100 (-) 

Surface 
water 

PECyear 1 (µg L-1) 

RCR year 1 (-) 

Human 

Total daily intakeyear 1/10/100 
(mg day-1) 

Relative contribution of fish 
consumption10 years (%) 

Relative contribution of 
crop, meat and dairy 
consumption10 years (%) 

Relative contribution of 
drinking water10 years (%) 

RCRyear 1/10/100 

1.5E-04/ 

1.6E-03/ 

1.3E-02 

6.4E-04/ 

6.9E-03/ 

5.7E-02 

6.2E-05 

2.4E-03 

4.7E-07/ 

5.9E-07/ 

1.6E-06 

76% 

23% 

1% 

4.2E-04/ 

6.2E-04/ 

7.5E-04 

3.0E-02/ 

4.4E-02/ 

5.4E-02 

2.2E-03 

1.1E-01 

4.5E-07/ 

4.6E-07/ 

4.7E-07 

50% 

9% 

41% 

1.5E-04/ 

1.5E-03/ 

9.5E-03 

1.0E-02/ 

1.1E-01/ 

6.6E-01 

9.7E-04 

3.7E-02 

1.4E-05/ 

1.4E-05/ 

1.6E-05 

97% 

2% 

1% 

1.5E-05/ 

1.5E-05/ 

1.8E-05 

8.5E-04 

8.7E-04 

1.0E-03 

13.3.8.6  Source contribution analysis 

A source contribution analysis has not been performed due to the low RCR observed from the application of 
organotins present in sewage sludge to agricultural soils.  

13.3.8.7  Impact of sludge processing 

No assessment has been undertaken to assess the impact of sludge processing given to the low RCR observed 
from the application of organotins present in sewage sludge to agricultural soils. 

13.3.9  Phthalate acid esters 

13.3.9.1  Background  

Phthalate esters are colorless sticky liquids and widely used as important additives which impart flexibility in 
polyvinylchloride  resins.  Phthalate  esters  have  been  widely  used  in  plastic  manufacturing  since  the  1930s, 

122 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
and they can also be found as a common additive in paints, lubricants, adhesives, insecticides, packaging, and 
cosmetics (Gao and Wen, 2016). Phthalate esters are also gradually released from industrial products during 
manufacturing,  storage,  use,  and  disposal  (Gao  and  Wen,  2016).  Degradation  rates  of  these  pollutants  are 
very slow under natural conditions 

The EU has restricted six phthalates in toys and childcare articles since 1999. EU Regulation (EU) 2018/2005 
further expands the restrictions for phthalates that apply as per Annex XVII to Regulation (EC) No 1907/2006 
to any products placed on the market, and further tightens the identity of phtalates that should meet the limit 
value of 0.1%. 

13.3.9.2  Safe limit values for human consumption 

The EFSA Panel on Food Contact Materials, Enzymes and Processing Aids (CEP) confirmed the tolerable daily 
intake values of 0.01, 0.5 and 0.05 mg kg-1 dry sludge based on reproductive effects for DBP, BBP, and DEHP, 
respectively (EFSA CEP Panel, 2019). In addition, the EFSA Panel indicated a group TDI for four phtalates di-
butylphthalate (DBP), butylbenzylphthalate (BBP), bis(2-ethylhexyl)phthalate (DEHP), and di-isononylphthalate 
(DINP) of 50 µg kg-1 bw day-1, expressed as DEHP equivalents (EFSA CEP Panel, 2019). The relative potency 
factors  (RPFs)  are  1  for  DEHP,  5  for  DBP,  0.1  for  BBP  and  0.3  for  DINP  when  including  the  additional 
assessment factor of 3.3. 

13.3.9.3  Sludge concentrations 

For  DEHP,  Lamastra  et  al.  (2018)  indicated  DEHP  concentrations  varying  from  1.32  to  103  mg  kg−1  DM 
(median  6.24  mg  kg−1  DM)  and  from  0.602  to  148  mg  kg−1  DM  (median  11.1  mg  kg−1  DM),  respectively. 
Fromme et al. (2002) reported median DEHP values of 67.3 mg kg−1 DM. These values are slightly lower than 
the  values  reported  by  Tavazzi  et  al.  (2012).  Lithuanian  sewage  sludge  samples  collected  in  2019  showed 
DEHP values of 3.8 – 95 mg kg-1 DM (Anne and Paulauskiene, 2021). Based on these data, a value of 50 mg 
kg-1 DM was applied in this assessment. DINP concentrations reported by Rigby et al. (2021) are around 100 
mg kg-1 DM. Concentrations for DBP and BBP were much lower, with average values of around 1 mg kg -1 dry 
weight (VKI, 1996; Boutrup et al., 1998; Fromme et al., 2002; European Chemicals Bureau, 2007; Dargnat et 
al., 2009). Therefore, only DEHP and DINP were retained in this assessment, with concentration values of 50 
mg  kg-1 dry matter and 100 mg kg-1  dry  matter, corresponding to  50  mg kg-1 and 30 mg kg-1  dry  matter 
DEHP Equivalents. 

13.3.9.4  Model input data  

Table 33: Physico-chemical and toxicological data used for risk modelling purposes for bis(2-ethylhexyl)phthalate (DEHP), 
and di-isononylphthalate (DINP). 

Concentration 
DEHP equivalents kg-1 dry matter) 

in  sludge 

(mg-1 

DEHP 

50 

DINP 

30 

Molecular weight (g mol-1) 

390.56 

420.6 

Water solubility (mg L-1) 

3.0E-03 

6.E-04 

(Gao and Wen, 2016) 

(Gao and Wen, 2016) 

Vapour pressure (Pa) 

3.4E-05 

6.0E-05 

(ECHA, 2008b) 

(INERIS, 2003) 

Kow (log 10) 

7.5 

8.8 

(ECHA, 2008b; Gao and 
Wen, 2016) 

(INERIS, 2003) 

123 

 
 
 
 
 
 
 
 
 
 
Koc (L kg-1) 

1.65E+05 

3.1E+05 

PNECaqua (µg L-1) 

Not available(1) 

Not available(1) 

(ECHA, 2008b) 

(INERIS, 2003) 

PNECsoil (mg kg-1 ww) 

13 

30 

(ECHA, 2008b) 

(INERIS, 2003) 

(ECHA, 2008b) 

(INERIS, 2003) 

Safe  limit  values  for  human  intake 
(mg kg-1 body weight day-1)  

0.05 mg s DEHP Equivalents kg-1 body weight day-1 

(EFSA CEP Panel, 2019) 

Half-life in soil (days) 

147 

300 

(Roslev et al., 1998) 

(INERIS, 2003; Gao and 
Wen, 2016) 

Half-life 
days) 

in  water 

(degradation, 

14 

50 

(Gao and Wen, 2016) 

(INERIS, 2003; Gao and 
Wen, 2016) 

Regional  background  in  soil  (mg 
kg-1 dry matter)(2) 

0.02 

0.02 

(Gawlik and Bidogli, 2006) 

(Gawlik and Bidogli, 2006) 

Regional  background 
water (µg L-1) 

in  surface 

Not considered 

Not considered 

BCFfish-water (L kg-1ww) 

840 

(4) 

4000 

BCFshoot-soil 
ww)/(mg kg-1 soil ww)(3) 

(mg 

kg-1  plant 

1.00E+00(2) 

1.00E+00(3) 

(ECHA, 2008b) 

(ECHA, 2008b) 

BTFroot-soil (mg kg-1 plant ww)/(mg 
kg-1 soil ww)(3) 

1.00E+00(2) 

1.00E+00(3) 

(ECHA, 2008b) 

(4) 

BTFmeat-grass 
matter)  

(day  kg-1  dry 

(ECHA, 2008b) 

9.95-01 

(3) 

BTF-milk-grass 
matter) 

(day 

kg-1  dry 

3.15E-01 

(4) 

9.95E-01 

(4) 

3.15E-01 

(3) 

(4) 

(1) INERIS (2003) concluded that DINP does not have adverse effects towards aquatic or benthic organisms at 
the limit of water solubility in laboratory tests, no PNECs could be derived. 
(2)  Based  on  BCF  values  of  9.2  (shoot-soil)  and  12.4  (root-soil)  as  reported  by  EFSA  (ECHA,  2008b).  Values 
expressed on a dry basis have been transformed into values on a wet mass basis (mg kg-1 plant ww)/(mg kg-
1 soil ww) assuming a water content in soil of 20vol% (EUSES default, conversion factor for soil concentration 
wet-dry  weight  soil  of  1.13),  and  a  water  content  in  roots  of  65vol%,  and  a  bulk  density  of  plants  of  700 
kg/m3 (EUSES default), 

124 

 
 
 
 
 
 
 
 
 
 
 
 
 
(3)EPI  data  obtained  from 
(https://rais.ornl.gov/cgi-bin/tools/TOX_search?select=chemspef).  
(4)DINP-specific  data  could not be retrieved.  In the absence of available data for DINP, the  DEHP  data were 
used an an approximation. 

Information  System,  University  of  Tennessee 

the  Risk  Assessment 

13.3.9.5  Estimated environmental and health exposure and risks from sludge application 

The outcome of the risk screening assessment resulting  from the application of phthalate esters present in 
sewage sludge to agricultural soils (without ‘background’ concentrations of water and soils) indicated that risk 
characterisation ratios were well below 1 for soils, but above 1 for humans (Table 34). Values for RCRhuman 
after 10 years were for instance estimated at a value of 1.4E+02. In addition, it is noted that risks may be 
underestimated  due to lack  of bioconcentration data through  plants available for DINP.  In this exercise, the 
data available for DEHP were applied, but bioconcentration factors for DINP may be higher due to increased 
Kow observed for this compound. Crops, meat and dairy were the dominant food sources contributing to the 
the total human intake (Table 34). 

Table  34:  Environmental  and  human  health  risk  screening  assessment  of  the  exclusive  application  of  bis(2-
ethylhexyl)phthalate (DEHP), and di-isononylphthalate (DINP) present in sewage sludge to agricultural soils (PEC: predicted 
environmental concentration, RCR: risk characterisation ratio) 

Soil 

PECyear 1/10/100 (mg DEHP 
equivalents kg-1 wet soil) 

RCRyear 1/10/100 (-) 

Surface 
water 

PECyear 1 (µg L-1) 

∑DEHP + DINP 

DEHP 

7.1E-02 

1.2E-01 

1.4E-01 

5.9E-03 

9.8E-03 

1.2E-02 

9.3E-02 

DINP 

4.3E-02 

1.1E-01 

1.4E-01 

1.4E-03 

3.7E-03 

4.6E-03 

3.0E-02 

RCR year 1 (-) 

Not applicable 

Not applicable 

Human 

Total daily intakeyear 1/10/100 
(mg day-1) 

Relative contribution of fish 
consumption10 years (%) 

Relative contribution of 
crop, meat and dairy 
consumption10 years (%) 

Relative contribution of 
drinking water10 years (%) 

RCRyear 1/10/100 

1.5E+00 

2.5E+00 

3.1E+00 

0 

0 

0 

1.0E+00 

2.6E+00 

3.2E+00 

0 

100 

0 

2.5E+00 

5.0E+00 

6.3E+00 

7.2E-01 

1.4E+00 

1.8E+00 

13.3.9.6  Source contribution analysis 

The source contribution analysis indicated that sludge can be a main contributor the observed phthalate ester 
concentrations in soils, even shortly after application (Table 35). RCRhuman values further increased with values 
>1.0E+00 now also being observed after a single sludge application (year 1).   

125 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Table  35:  Environmental  and  human  health  risk  screening  assessment  for  bis(2-ethylhexyl)phthalate  (DEHP),  and  di-
isononylphthalate (DINP) based on its present background concentrations observed in the environment along with sewage 
sludge applications to agricultural land (PEC: predicted environmental concentration, RCR: risk characterisation ratios) 

Soil 

PECyear 1/10/100 (mg kg-1 wet soil) 

DEHP 

9.1E-02 

1.4E-01 

1.6E-01 

DINP 

6.3E-02 

1.3E-01 

1.6E-01 

∑DEHP + DINP 

Contribution of sludge to total concentration 
(%) 

78/ 85/ 88 

68/ 85/ 87 

RCRyear 1/10/100 (-) 

Surface 
water 

PECyear 1 (µg L-1) 

7.6E-03 

1.1E-02 

1.4E-02 

1.4E-01 

2.1E-03 

4.4E-03 

5.3E-03 

8.0E-02 

RCR year 1 (-) 

Not applicable 

Not applicable 

Human 

Total daily intakeyear 1/10/100 (mg day-1) 

2.0E+00 

3.0E+00 

3.6E+00 

1.6E+00 

3.1E+00 

3.7E+00 

RCRyear 1/10/100 

3.6E+00 

6.1E+00 

7.3E+00 

1.0E+00 

1.7E+00 

2.1E+00 

13.3.9.7  Impact of sludge processing 

Anaerobic  digestion  has  been  shown  to  cause  the  partial  removal  of  phthalate  acid  esters  (Gavala  et  al., 
2003; Fountoulakis et al., 2006). Phthalate degradation under aerobic conditions is much higher. Marttinen et 
al.  (2003)  observed  that  32%  of  DEHP  in  sewage  was  removed  during  anaerobic  digestion  of  the  sludge. 
Sludge composting could significantly decrease the levels of the pollutants, with removal percentages ranging 
from 32% to 91% (Lü et al., 2021). For DEHP, removal percentages varied between < 50% to 99% have been 
observed (Lü et al., 2021). Thermal oxidation results in close to a 100% loss of phthalates at temperatures of 
around 400-500°C (Aouachira et al., 2014). 

13.3.10 

Polydimethylsiloxanes 

13.3.10.1 Background 

Polydimethylsiloxanes  are  are  a  group  of  organosilicon  substances  that  are  used  in  personal  care  products 
such as shampoos, cosmetics, and deodorants and in industrial applications such as dry-cleaning solvents and 
industrial cleaning fluids (Mackay et al., 2015). Following the  

13.3.10.2 Safe limit values for human consumption 

A  NOAEL  for  increased  liver  weight  of  25  mg  kg  bw-1  day-1  were  reported  for  female  rats  (SCCS,  2010). 
Therefore, a human toxicological standard was calculated using this lowest NOAEL and an assessment factor 
of  100,  giving  a  safe  limit  value  for  human  consumption  of  0.25  mg  kg-1  body  weight  day-1  (Sahlin  and 
Agerstrand, 2018). 

13.3.10.3 Concentrations observed in sludge 

Few  studies  have  reported  on  polydimethylsiloxanes  in  sewage  sludge.  Tavazzi  et  al.  (2012)  indicated  that 
decamethylcyclopentasiloxane (D5) was the dominant siloxane observed in sewage sludge. These results are 

126 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
  
 
 
 
aligned  to  2004  monitoring  data  from the  Swedish  national  screening  programme  (Kaj  et  al., 2005).  In  the 
absence  of  any  further  data,  the  D5  concentration  value  of  10.8  mg  kg-1  dry  matter  is  retained  in  this 
assessment. 

restriction 

European  Union’s 

The 
and 
decamethylcyclopentasiloxane  (D5)  in  rinse-off  cosmetic  products  entered  into  force  on  1  February  2020. 
Under  the  REACH  Regulation,  companies  can  no  longer  add  the  siloxanes  in  a  concentration  equal  to  or 
greater  than  0.1%  by  weight  of  the  product.  It  is  expected  that  this  measure  may  result  in  substantial 
decreases in D5 concentrations in sewage sludges. 

octamethylcyclotetrasiloxane 

(D4) 

use 

the 

on 

of 

13.3.10.4 Model input data 

Table 36: Physico-chemical and toxicological data used for risk modelling purposes for the selected polydimethylsiloxanes. 

Concentration  in  sludge  (mg-1 
kg-1 dry matter) 

Molecular weight (g mol-1) 

decamethylcyclopentasiloxane (D5) 

10.8 

370.8 

(Mackay et al., 2015) 

Water solubility (mg L-1) 

1.7E-02 

(Mackay et al., 2015) 

Vapour pressure (Pa) 

22.7 

Kow (log 10) 

Koc (L kg-1) 

PNECaqua (µg L-1) 

(Mackay et al., 2015) 

8.09 

(Mackay et al., 2015) 

5.17 

(Mackay et al., 2015) 

0.044 

(Sahlin and Agerstrand, 2018) 

PNECsoil (mg kg-1 ww) 

1.15E-01 

Safe  limit  values  for  human 
intake  (mg  kg-1  body  weight 
day-1)  

Half-life in soil (days) 

Half-life  in  water  (degradation, 
days) 

0.25 

(SCCS, 2010) 

12.6 

(Mackay et al., 2015) 

70.4 

(Mackay et al., 2015) 

127 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
Regional  background 
(mg kg-1 dry matter)(2) 

in  soil 

3.5E-2 

(Sánchez-Brunete et al., 2010) 

Regional 
surface water (µg L-1) 

background 

in 

BCFfish-water (L kg-1ww) 

BCFshoot-soil  (mg  kg-1  plant 
ww)/(mg kg-1 soil ww)(3) 

BCFroot-soil 
ww)/(mg kg-1 soil ww)(3) 

(mg  kg-1  plant 

BTFmeat-grass  (day  kg-1  dry 
matter)  

BTF-milk-grass (day kg-1 dw) 

- 

(Kaj et al., 2005) 

4920 

(Gobas et al., 2015a) 

8.07E-02 

(1) 

8.07E-02 

(1) 

3.09E+00 

(2) 

9.77E-01 

(2) 

(1)Gobas et al. (2015a), Gobas et al. (2015b) and Fairbrother et al. (2015) reviewed in detail the potential for 
D5  to  bioaccumulate  or  biomagnify  in  aquatic  or  terrestrial  food  webs  and  concluded  that  the  risk  of 
biomagnification  was  negligible.  Briefly,  D5  is  a  very  hydrophobic  organic  substance  with  a  low  affinity  for 
organic  carbon  relative  to  its  Kow.  In  terrestrial  ecosystems,  it  is likely  that  the  high  rate  of  loss  of  D5  via 
exhalation (as a result of its relatively low octanol-air partition coefficient) and rapid metabolism ensure that 
D5 depuration rates exceed dietary uptake rates. As such, biomagnification in terrestrial food webs does not 
occur. Therefore, the values applied for BCFshoot-soil and BCFroot-soil were set to 1 on a dry weight basis. 
Values  expressed  on  a  dry  basis  have  been  transformed  into  values  on  a  wet  mass  basis  (mg  kg-1  plant 
ww)/(mg kg-1 soil ww) assuming a water content in soil of 20vol% (EUSES default, conversion factor for soil 
concentration  wet-dry  weight  soil  of  1.13),  and  a  water  content  in  roots  of  65vol%,  and  a  bulk  density  of 
plants of 700 kg/m3 (EUSES default). 
(2)Default values based on Kow, likely being an overestimation due to the low bioaccumulation potential of D5. 

13.3.10.5 Estimated environmental and health exposure and risks from sludge application 

The outcome of the risk screening assessment resulting from the application of D5 present in sewage sludge 
‘background’  concentrations  of  water  and  soils)  indicated  that  risk 
to  agricultural  soils  (without 
characterisation ratios were well below 1 for soils, surface waters and humans (Table 34).  

Table  37:  Environmental  and  human  health 
the  exclusive  application  of 
decamethylcyclopentasiloxane  (D5)  present  in  sewage  sludge  to  agricultural  soils  (PEC:  predicted  environmental 
concentration, RCR: risk characterisation ratio) 

risk  screening  assessment  of 

decamethylcyclopentasiloxane (D5) 

Soil 

PECyear 1/10/100 (mg DEHP 
equivalents kg-1 wet soil) 

RCRyear 1/10/100 (-) 

7.8E-03/ 

7.8E-03/ 

7.8E-03 

6.8E-02/ 

6.8E-02/ 

6.8E-02 

128 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
Surface 
water 

PECyear 1 (µg L-1) 

RCR year 1 (-) 

Human 

Total daily intakeyear 1/10/100 
(mg day-1) 

Relative contribution of fish 
consumption10 years (%) 

Relative contribution of 
crop, meat and dairy 
consumption10 years (%) 

Relative contribution of 
drinking water10 years (%) 

RCRyear 1/10/100 

1.8E-02 

4.1E-01 

2.3E-02/ 

2.3E-02/ 

2.3E-02 

33 

67 

0 

1.3E-03/ 

1.3E-03/ 

1.3E-03 

13.3.10.6 Source contribution analysis 

A source contribution analysis has not been performed due to the  low RCR observed from the application of 
D5 present in sewage sludge to agricultural soils.  

13.3.10.7 Impact of sludge processing 

No assessment has been undertaken to assess the impact of sludge processing given to the low RCR observed 
from the application of organotins present in sewage sludge to agricultural soils. 

13.4  Supplementary information - measurement standards for priority pollutants 

The  available  measurement  standards  (and  technical  specifications,  and  technical  reports)  that  may  be 
relevant for the determination of priority pollutants in sewage sludge were searched in both databases: the 
European  Standard  (EN)  database  and  the  International  Organization  for  Standardization  (ISO)  database. 
Standards containing the word ‘sludge’ or ‘biosolid’ were extracted. In addition, a targeted search, looking for 
priority pollutant in the standards’ title, was also performed. When no relevant standards were found for the 
determination of a priority pollutant in sludge, the relevant standard for the determination of priority pollutant 
the 
in  soil  was  also  considered.  Standards  for 
detection/determination of other  pollutants not reported as priority in this report, such  as trace elements or 
metals, nutrients, other pollutants, were not considered for the identification of relevant standards. 

the  characterisation  of  sludge  properties  or 

The list of priority pollutants used for this exercise was based on the list presented in section 3. 

 
 
 
 
 
 
 
 
 
 

polycyclic aromatic hydrocarbons (PAHs); 
dioxins, furans and dioxin-like polychlorinated biphenyls (PCDD, PCDFs and dl-PCBs); 
per- and polyfluoroalkyl substances (PFAS); 
alkylphenols, nonylphenols, octylphenols (APs, NPs and Ops); 
short- and medium-chain polychlorinated alkanes (SCCPs and MCCPs); 
polychlorinated naphthalenes (PCNs); 
phthalate acid esters (DEHP and DINP); 
benzalkonium chloride and its degradation products (quaternary ammonium compounds); 
lauryl diethanolamide (N-acyl amines and fatty amides); and 
traseolide (synthetic musks). 

 

 

 Identified as priority after human health risk assessment (see section 3.3) 

 Identified as priority after soil organisms risk assessment (see Section 3.4) 

129 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
The results of the identified available measurement standards are presented in Section 3.5. 

In  addition,  other  standards  covering  sampling,  sample  preparation  or  the  leaching  properties  may  also  be 
relevant, as for example: 

 
 
 
 

 

 
 

 

 

 

 

‘Sludge, treated bio-waste and soil - Guidance for sample pretreatment’ (EN 16179:2012); 
‘Characterization of sludges - Protocol for preparing synthetic suspensions’ (CEN/TR 16394:2014); 
‘Characterization of sludges - Laboratory chemical conditioning procedure’ (EN 14742:2015); 
‘Sludge  recovery,  recycling,  treatment  and  disposal  —  Laboratory  chemical  conditioning  procedure’ 
(ISO/DTR 23594l) 
‘Water quality  - Sampling - Part 1: Guidance on the design of sampling  programmes and sampling 
techniques’ (EN ISO 5667-1:2006); 
‘Water quality - Sampling - Part 13: Guidance on sampling of sludges’ (EN ISO 5667-13:2011); 
‘Water  quality  -  Sampling  -  Part  15:  Guidance  on  the  preservation  and  handling  of  sludge  and 
sediment samples’ (EN ISO 5667-15:2009); 
‘Characterisation of waste - Leaching - Compliance test for leaching of granular waste materials and 
sludges - Part 1: One stage batch test at a liquid to solid ratio of 2 l/kg for materials with high solid 
content and with particle size below 4 mm (without or with size reduction)’ (EN 12457-1:2002); 
‘Characterisation of waste - Leaching - Compliance test for leaching of granular waste materials and 
sludges - Part 2: One stage batch test at a liquid to solid ratio of 10 l/kg for materials with high solid 
content and with particle size below 4 mm (without or with size reduction)’ (EN 12457-2:2002); 
‘Characterisation of waste - Leaching - Compliance test for leaching of granular waste materials and 
sludges - Part 3: Two stage batch test at a liquid to solid ratio of 2 l/kg and 8 l/kg for materials with 
high  solid  content  and  with  particle  size  below  4  mm (without  or  with  size  reduction)’  (EN  12457-
3:2002); and 
‘Characterisation of waste - Leaching - Compliance test for leaching of granular waste materials and 
sludges - Part 4: One stage batch test at a liquid to solid ratio of 10 l/kg for materials with particle 
size below 10 mm (without or with size reduction)’ (EN 12457-4:2002). 

Finally, other standards on the management of sewage sludge and use in agriculture may also be of interest, 
but these were not considered as measurement standards, as for example: 

 
 

 

 

‘Characterization of sludges - Good practice for utilisation in agriculture’ (CR 13097:2001); 
‘Characterization  of  sludges  -  Sludge  management  in  relation  to  use  or  disposal’  (CEN/TS 
13714:2013); 
‘Sludge recovery, recycling, treatment and disposal — Beneficial use of biosolids — Land application’ 
(ISO 19698:2020); and 
‘Characterisation of sludges - Guide to risk assessment especially in relation to use and disposal of 
sludges’ (CEN/TR 15584:2007). 

130 

 
 
 
 
 
 
 
14  Supplementary Information – soil biogeochemical modelling 

14.1  Model approach 

The  JRC  has  developed  a  state-of-the-art  process-based  European  biogeochemical  modelling  platform  that 
simulates carbon (C) and nitrogen (N) flows within soil and between soil, the atmosphere and vegetation.  

Key sub-models include decomposition of organic input and soil organic matter, mineralisation of nutrients, N 
gas  emissions  from  nitrification  and  denitrification,  soil  water  content  and  temperature  by  layer,  plant 
production and allocation of net primary production (NPP) and CH4 oxidation in non-saturated soils and CH4 
production is flooded soils. Flows of C and N between the different soil organic matter pools are controlled by 
the  size  of  the  pools,  C/N  ratio  and  lignin  content  of  material,  and  abiotic  water/temperature  factors.  Plant 
production  is  a  function  of  genetic  potential,  phenology,  nutrient  availability,  water/temperature  stress,  and 
solar  radiation.  NPP  is  allocated  to  plant  components  (e.g.  roots  vs.  shoots)  based  on  vegetation  type, 
phenology, and water/nutrient stress. Nutrient concentrations of plant components vary within specified limits, 
depending on vegetation type, and nutrient availability relative to plant demand. Decomposition of litter and 
soil organic matter and nutrient mineralization are functions of substrate availability, substrate quality (lignin 
%, C/N  ratio), and water/temperature stress. N gas fluxes from nitrification and denitrification are driven by 
soil NH4 and NO3 concentrations, water content, temperature, texture, and labile C availability (Parton et al., 
2001). 

In this project, DayCent is run on a 1 km2 grid using the following data (Figure 16):  

 

 
 

soil  properties  available  for  ESDAC  and  derived  from  spatial  interpolation  of  LUCAS  soils 
(https://esdac.jrc.ec.europa.eu/); 
land cover from the CORINE LAND COVER 1990, 2000, 2006, 2012; 
official statistics (EUROSTAT, FAO, Farm Structure Survey) and spatial datasets, which were used to 
describe  the  current  management  (i.e.  crop  rotation,  mineral  and  organic  N  fertilization,  tillage, 
irrigation, cover crop, etc.); 

  meteorological data from the E-OBS gridded dataset (http://www.ecad.eu). The dataset provided daily 
data of maximum and minimum temperature and precipitation on a grid of 0.1° resolution (v22). For 
the  climatic  projection,  we  used  the  general  circulation  model  CNRM-CM541  run  with  a  RCP4  and 
downscaled with the RCM CCLM4-8-17, available at the WCR-CORDEX portal. 

Figure  16:  Flow  chart  showing  the  datasets  utilized  and  their  spatial  resolution,  the  inputs  derived  and  the  model 
integration. 

131 

 
 
 
 
 
 
As inputs, the amount and timing of nutrient amenDMents is required. The current (baseline) N fertilization 
was characterised as follow (Figure 17):  

  Mineral N fertiliser: it was partitioned in two applications at planting (30%) and standing crops (70%). 
In  each  fertilisation  the  proportion  of  NH4  and  NO3  was  assumed  to  be  equal  to  75  and  25%, 
respectively; 

  Organic: applied  generally after harvest or during standing crop in highly  demanding crops such as 
maize. The territorial rates calculated was limited to the maximum rate of 170 kg/ha of N per year. 

Figure 17: Organic (above) and total N input (below) rates in the baseline. The boxplots represents the values distribution 
(median and interquartile ranges) of all simulated points with the average in red diamond symbols.  

Model  outputs  include  daily  N  fluxes  (N2O,  NOx,  N2,  NO3
  leaching),  CO2  flux  from  heterotrophic  soil 
respiration, soil organic C, NPP (portioned into residues, grains and harvested root crops). The model takes into 
account  land  management  and  cropping  practices.  As  it  is  driven  by  a  range  of  climate  scenarios,  as 
simulated by Global Climate Models, the model can provide long-term policy perspectives. 

-

132 

 
 
 
 
 
 
 
-  leaching  has  been 
The  ability  of  DAYCENT  to  simulate  NPP,  soil  organic  carbon,  N2O  emissions,  and  NO3
tested with data from various native and managed systems (e.g. Del Grosso et al., 2001, 2006). The DAYCENT 
model  is  currently  being  used  by  the  United  States  Environmental  Protection  Agency,  United  States 
Department  of  Agriculture  and  Colorado  State  University  to  develop  a  national  inventory  of  N2O  emissions 
inventory  will  be  compared  and  contrasted  with  the  existing 
from  U.S.  agricultural  soils.  This 
Intergovernmental Panel on Climate Change (IPCC) agricultural N2O emissions inventory for the USA. 

The  JRC  has  developed  and  continuously  improved  the  modelling  framework  in  the  EU  in  the  last  decade, 
initially using CENTURY (the model monthly version) and then DayCent (the model daily version), running both 
at  LUCAS  point  and  gridded  1  km  level.  This  framework  was  used  for  many  scientific  studies  and  policy 
scenarios,  receiving  a  scientific  recognition.  For  more  information  on  the  general  architecture,  model 
performances  and  different  scenarios  and  agricultural  management  simulated,  we  refer  to  previous 
publications (Lugato et al., 2014b, 2018; Lugato and Jones, 2015; Borrelli et al., 2016; Scarlat et al., 2019; 
Quemada et al., 2020). 

14.2  Results  

14.2.1  Spatially explicit CH emission from the use-on-land of sludge 

133 

 
 
 
 
 
 
Figure 18: Spatially explicit CH4 emission factors (kg CH4 per kg C in (treated) sludge) as estimated using biogeochemical 
modelling  for  application  scenarios  of  1  tonne  ha-1  yr-1  (top  row)  and  5  tonnes  ha-1  yr-1  (bottom  row)  for  composted 
sewage sludge (left hand side), dewater sewage sludge (middle), and digested sludge (right hand side). 

14.2.2  Carbon  sequestration  in  soils  as  a  function  of  time  for  soils  in  the  EU  Member 

States 

Figure 19: Carbon sequestration (12, 22, 32, 37 years after distribution) in Member States for the scenarios of 1 tonne ha-
1 yr-1 (left panels) and, 1 tonne ha-1 yr-1 (right panels), Composted SS (comp) – baseline (base) scenario showed a decrease 
over time of the C sequestration throughout the time. 

134 

 
 
 
 
 
 
 
15  Supplementary information – life cycle assessment 

15.1  Model input parameters 

Table 38: Default parameter values and ranges applied for the uncertainty analysis of the life cycle assessment presented 
in section 6.4. 

Parameters that are common to all pathways 

Electricity mix 

Incineration 

Dry matter content of sludge prior to incineration 

Lower heating value of de-watered sludge 
(MJ/kg TS) 

N2O emissions – mono-incineration (mg N2O 
/m3) 

Anaerobic digestion 

Biogas leak (%) 

CH4 in biogas (% vol.) 

Electrical efficiency AD 

Biogas yield (%) 

Composting and liming  

N2O emissions during composting (% N 
transformed) 

Storage and transport 

CH4 emissions storage - compost (kg/kg total C) 
CH4 emissions storage - sludge and digestate 
(kg/kg total C) 
N2O emissions storage (kg/kg total N) 

Use-on -and 

N2O emissions use-on-land - compost (kg/kg N) 

N2O emissions use-on-land - dewatered sludge 
(kg/kg N) 
N2O emissions use-on-land - digestate (kg/kg 
N) 
Carbon storage in soil - compost (%) 

Carbon storage in soil - dewatered sludge (%) 

Carbon storage in soil - digestate (%) 

K bio-availability (%) 

N bio-availability - digestate (%) 

N bio-availability - compost and dewatered 
sludge (%) 

P bio-availability (%) 

Average EU 
mix 

High share of 
renewables in the 
mix: 73% 

Low share of 
renewables in the 
mix: 15% 

24% 

22.4 

200 

2.8 

63% 

30% 

70% 

75% 

20% 

50 

0.1 

70% 

18% 

-20% 

400 

expert knowledge and 
consultations 

(IGES for the IPPC, 2002; 
Korving et al., 2010; 
Neuwahl et al., 2019) 

6 

50% 

(IAEA Bioenergy Task, 
2017) 
(Liu et al., 2018) 

Default x 1.2 

Default x 0.8 

Default x 1.2 

Default x 0.8 

1.4 

Default x 1.3 

Default x 0.7 

0.001 

0.002 

0 

0.001 

0.001 

0.001 

0.01 

0.02 

0.013 

0.015 

0.015 

0.015 

(Willén et al., 2016; 
Samuelsson et al., 2018) 

(own results; see section 
5.3) 

Default x 1.2 

Default x 0.8 

Default x 1.2 

Default x 0.8 

Default x 1.2 

Default x 0.8 

1 

1 

0.95 

0.9 

0.8 

0.5 

0.5 

0.4 

(Oenema et al., 2012; 
Wilfert et al., 2015) 

0.003 

0.01 

0.005 

0.0049 

0.0055 

0.006 

28 

21 

26 

1 

0.85 

0.8 

0.55 

135 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Table  39:  Input-output  disaggregated  inventory  for  anaerobic  digestion,  including  utilisation  of  the  biogas  in  the  gas 
engine. DM: dry matter. Values are expressed on a wet weight basis, unless otherwise stated (source: Tonini et al. (2019) 

Unit 

Anaerobic digestion 

Inputs 
Feedstock-quantity 

Diesel 

Electricity 

Heat 

Outputs 
Digestate 

Biogas-Electricity 

Air emissions (fugitive) 
CH4  

CO2 biogenic 

Air emissions  
(gas-engine)c 

CH4 

N2O 

NOx 

SOx 

t (DM) 
L t-1 
kWh t-1 
kWh t-1 

kg (DM) t-1 
kWh t-1 

kg t-1 
kg t-1 

g MJ-1 
g MJ-1 
g MJ-1 
g MJ-1 
kg t-1 

1 

0.291 

6.18 

0a 

23.2 
43.2b 

0.28 

0.55 

0.434 

0.202 

0.0016 

0.434 

44 

CO2 biogenic 
a It is assumed that the waste-heat from the gas engine is reused internally to heat the 
reactor (no external heat source required).  
b Assuming 30% electrical efficiency 

136 

 
 
 
  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Table 40: Substance mass transfer for dewatering process. TS: total solids; VS: volatile solids; Values are expressed on a 
wet weight basis, unless otherwise stated (source: Yoshida et al., 2015) 

Total mass 
Water 
TS 
VS 
Ash 
Cbio 
K 
N 
P 

Dewatered sludge (%) 

10.17% 
8.70% 
80.78% 
80.29% 
81.82% 

90.72% 
68.99% 
65.00% 
72.07% 

Centrate (%) 
89.83% 
91.30% 
19.22% 
19.61% 
18.38% 

9.28% 
31.01% 
35.00% 
27.93%* 

*Assuming biological wastewater treatment 

Table 41: Input-output disaggregated inventory for dewatering of digestate/sludge. DM: dry matter. Values are expressed 
on a wet weight basis, unless otherwise stated (source: Yoshida et al., 2015) 

Inputs 
Feedstock-type 
Feedstock-quantity 

Acrylonitrile 

Electricity 

Outputs 
Centrate 

Dewatered 

Unit 

Dewatering 

t (DM) 
kg t-1 
kWh t-1 

Digestate 

0.45 

Sludge 
1 

2.31E-03 
2.2 

2.31E-03 
2.2 

kg (DM) t-1 
kg (DM) t-1 

7.59 

32.32 

9.8 

40.2 

137 

 
 
 
  
 
  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Table  42:  Input-output  disaggregated  inventory  for  thermal  treatment  (mono-  and  co-incineration  with  municipal  solid 
waste).  CO-INC:  co-incineration  with  MSW;  DM:  dry  matter;  MO-INC:  mono-incineration.  Values  are  expressed  on  a  wet 
weight basis, unless otherwise stated (source: Tonini et al., 2019) 

Unit 

MO-INC 

CO-INC 

Inputs 
Feedstock-type 
Feedstock-quantity 
Feedstock-energy 

Activated carbon 

CaOH2 

CaCO3 

Electricity 

HCl 

NaOH 

NH3 25% 
Polyethylene high 
density 
TMT15 

Water 

Outputs 
Ashes 

Electricity  

Air emissions 
As 

Cd 

CO 

CO2 non-fossil  

Cr 

Cu 

Dioxins 

HCl  

HF  

Hg 

Ni 

N2O 

NOx 

Pb 

PM10 

SOx 

t (DM) 
MJ 
kg t-1 
kg t-1 
kg t-1 
kWh t-1 
kg t-1 
kg t-1 
kg t-1 

kg t-1 

kg t-1 
kg t-1 

kg t-1 
kWh t-1 

kg t-1 
kg t-1 
kg t-1 
kg t-1 
kg t-1 
kg t-1 
kg t-1 
kg t-1 
kg t-1 
kg t-1 
kg t-1 
kg t-1 
kg t-1 
kg t-1 
kg t-1 
kg t-1 
kg t-1 

Digestate 
0.38 
3358 

1 

1.04 

5.7 

70 

Sludge 
0.84 
13520 

1 

1.04 

5.7 

70 

5.60E-03 

5.60E-03 

2.40E-02 

2.40E-02 

1.53 

1.53 

6.00E-04 

6.00E-04 

0.395 

39.7 

0.395 

39.7 

94 
92a 

56 
197a 

1.17E-05 

6.27E-06 

2.40E-07 

1.28E-07 

3.31E-02 

3.30E-02 

2.60E+02 

4.54E+02 

1.83E-05 

9.79E-06 

3.75E-05 

2.00E-05 

1.81E-11 

1.80E-11 

5.32E-03 

5.29E-03 

3.92E-04 

3.90E-04 

3.10E-06 

1.65E-06 

1.87E-05 

9.96E-06 

0.79E+00 

0.51E+00 

1.15E-01 

1.15E-01 

5.58E-05 

2.98E-05 

3.01E-02 

3.00E-02 

1.22E-02 

1.22E-02 

1.43E-04 

138 

Zn 
a Electricity recovery efficiency 15.7%. 

2.68E-04 

 
 
  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Table  43:  Input-output  disaggregated  inventory  for  acidulation  and  other  post-processing  of  the  ash.  DM:  dry  matter. 
Values are expressed on a wet weight basis, unless otherwise stated (source: Tonini et al., 2019) 

Inputs 
Feedstock-type 
Feedstock-quantity 

Ash-P 

Diesel 

Electricity 

H2SO4 

Heat 

Natural gas 

Outputs 
P (granulated) 

Unit 

Ash acidulation 

t  
kg P t-1 
kg t-1 
kWh t-1 
kg t-1 
MJ t-1 
MJ t-1 

Ash 
0.149 

158.93 

2.1 

172 

710.4 

29.8 

38 

kg P t-1 

158.86 

Table  44:  Input-output  disaggregated  inventory  for  composting.  DM:  dry  matter.  Values  are  expressed  on  a  wet  weight 
basis, unless otherwise stated (source: Tonini et al., 2019; electricity consumption from Boldrin et al., 2009). 

Inputs 
Feedstock-type 
Feedstock-quantity 

Diesel 

Electricity 

Outputs 
Compost 

Unit 

Composting  

t (DM) 
L t-1 (DM) 
kWh t-1 

Sludge 
0.84 

1 

50 

kg t-1 (DM) 

502.1 

Dinitrogen monoxide 

Air emissions (biofilters) 
kg t-1 
Ammonia 
Carbon dioxide, non-fossil  kg t-1 
kg t-1 
kg t-1 
kg t-1 
kg t-1 
kg t-1 

Nitrogen 
Terpenes 

Methane, non-fossil 

Hydrogen sulfide 

3.72E-02 

5.18E-01 

6.85E-02 

2.16E-05 

9.91E-03 

6.23E-03 
1.37E-04 

139 

 
 
  
 
 
 
 
 
 
 
 
 
 
 
 
 
  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Table 45: Input-output disaggregated inventory for lime stabilisation of sludge. DM: dry matter. Values are expressed on a 
dry weight basis, i.e. per t DM, unless otherwise stated (source: Teoh and Li, 2020) 

Inputs 
Feedstock-type 
Feedstock-quantity 

Lime 

Outputs 
Stabilised sludge 

Unit 

t 
kg t-1 

kg t-1 

Lime 
stabilisation 

Sludge 
0.732 

300 

0.732 

Table  46:  Input-output  disaggregated  inventory  for  landfill  construction  and  operation.  DM:  dry  matter.  Values  are 
expressed on a wet weight basis, unless otherwise stated (source: Olesen and Damsgaard, 2014). 

Unit 

Landfill construction 

Inputs 
Feedstock-quantity 

Aluminium 

Clay 

Copper 

Diesel 

Electricity 

Gravel 
Polyethylene, high 
density 
Polypropylene 

Polyvinylchloride 

Steel 

t (DM) 
kg t-1 
kg t-1 
kg t-1 
L t-1 
kWh t-1 
kg t-1 

kg t-1 

kg t-1 
kg t-1 
kg t-1 

0.838 

5.80E-11 

8.20E-05 

9.87E-12 

0.24 
8 
1.80E-04 

2.30E-07 

4.00E-11 

1.00E-08 

1.40E-07 

140 

 
 
 
 
 
  
 
 
 
 
 
 
 
 
 
 
 
 
 
  
 
 
 
 
 
 
 
Table  47:  Input-output  disaggregated  inventory  for  landfill  gas  oxidation  in  top  cover  over  20  years.  DM:  dry  matter. 
Values are expressed on a wet weight basis, unless otherwise stated (source: Olesen and Damsgaard, 2014).. 

Unit 

Landfill gas oxidation 

Emissions to air 
Feedstock-quantity 

1,2-Dichlorobenzene 
Benzene 
Carbon dioxide, non-
fossil 
Carbon tetrachloride 

CFC-11 
CFC-113 

CFC-12 
Chloroform 

Cumene 
Ethylbenzene 

HCC-30 

HCFC-21 
HCFC-22 

Hydrogen sulfide 

Mercury 

Methane, non-fossil 

Monochloroethane 

NMVOC 

Phenol 

R-10 

R-40 

Toluene 

Trichloroethylene 

Vinyl chloride 

Xylene 

t (DM) 
kg t-1 
kg t-1 

kg t-1 

kg t-1 
kg t-1 
kg t-1 
kg t-1 
kg t-1 
kg t-1 
kg t-1 
kg t-1 
kg t-1 
kg t-1 
kg t-1 
kg t-1 
kg t-1 
kg t-1 
kg t-1 
kg t-1 
kg t-1 
kg t-1 
kg t-1 
kg t-1 
kg t-1 
kg t-1 

0.838 

3.963E-04 
5.606E-04 

3.062E+01 

7.652E-04 

4.430E-05 

4.027E-05 

3.423E-04 

1.667E-05 

1.450E-04 
1.321E-03 

9.988E-04 

5.638E-04 
1.933E-04 

2.900E-03 

8.055E-08 

1.984E+01 

5.638E-04 

1.692E-03 

6.283E-05 

2.255E-06 

1.498E-05 

6.911E-03 

2.320E-04 

2.030E-04 

2.642E-03 

141 

 
 
  
 
 
 
 
 
 
 
 
Table 48: Input-output disaggregated inventory for landfill leachate treatment. DM: dry matter. Values are expressed on a 
wet weight basis, unless otherwise stated (source: Olesen and Damsgaard, 2014).. 

Unit 

Leachate treatment 

Inputs 
Feedstock-quantity 

Electricity 

Water 

Emissions to air 
Ammonium, ion 

Arsenic 

Arsenic, ion 

Barium 

Benzene 

BOD5 

CaDMium 

CaDMium, ion 

Calcium, ion 
Carbon dioxide, non-
fossil 
Carbon tetrachloride 

Chloride 

Chlorine 
Chlorobnzene 

Chloroform 

Chromium VI 

COD 

Copper 

Copper, ion 

Cumene 

Dioctylphthalate 
Ethylbenzene 

HCC-30 

Iron 

Iron, ion 

Lead 

Magnesium 

Mercury 

Monochloroethane 

Nickel 

Nickel, ion 

Nitrogen 

Phenol 

Phosphate 

R-10 

t (DM) 
kWh t-1 
kg t-1 

kg t-1 
kg t-1 
kg t-1 
kg t-1 
kg t-1 
kg t-1 
kg t-1 
kg t-1 
kg t-1 

kg t-1 

kg t-1 
kg t-1 
kg t-1 
kg t-1 
kg t-1 
kg t-1 
kg t-1 
kg t-1 
kg t-1 
kg t-1 
kg t-1 
kg t-1 
kg t-1 
kg t-1 
kg t-1 
kg t-1 
kg t-1 
kg t-1 
kg t-1 
kg t-1 
kg t-1 
kg t-1 
kg t-1 
kg t-1 
kg t-1 

0.838 

0.44 

3.19E-05 

7.64E-02 

6.61E-06 

7.45E-06 

1.19E-04 

8.96E-07 

1.42E-02 

2.94E-06 

8.06E-07 

1.60E-01 

-9.74E+01 

9.86E-07 

4.03E-01 

4.03E-04 

5.92E-07 

1.55E-08 

4.74E-07 

1.15E-01 

2.83E-05 

4.53E-06 

3.95E-07 

1.10E-06 
3.98E-06 

8.48E-07 
8.33E-02 

2.19E-02 

1.33E-05 

8.20E-02 

8.49E-08 
8.42E-07 

1.42E-05 

1.87E-05 

3.08E-01 

7.08E-07 

1.53E-04 

3.95E-08 

142 

 
 
  
 
 
 
 
 
 
 
Selenium 

Silver 

Silver, ion 

Sodium, ion 

Sulfur dioxide 

Toluene 

Trichloroethylene 

Xylene 

Zinc 

Zinc, ion 

kg t-1 
kg t-1 
kg t-1 
kg t-1 
kg t-1 
kg t-1 
kg t-1 
kg t-1 
kg t-1 
kg t-1 

2.34E-06 

1.59E-05 

2.11E-06 

1.25E-01 

1.39E-02 

7.89E-06 
1.15E-06 

3.98E-06 

6.24E-04 

1.24E-04 

143 

 
 
 
 
 
 
Table  49:  Input-output  disaggregated  inventory  for  landfill  gas  combustion  in  gas  engine.  DM:  dry  matter.  Values  are 
expressed on a wet weight basis, unless otherwise stated (source: Olesen and Damsgaard, 2014).. 

Inputs 
Feedstock-quantity 

Outputs 
Landfill gas-Electricity 

Air emissions (gas-engine) 

1,2-Dichlorobenzene 
Benzene 

Carbon dioxide, non-fossil 

Carbon monoxide, non-fossil 

CFC-11 

CFC-113 

CFC-12 

Chloroform 

Cumene 

Dioxins 
Ethylbenzene 

HCC-30 

HCFC-21 

Hydrogen chloride 

Hydrogen fluoride 

Hydrogen sulfide 

Mercury 

Methane, non-fossil 

Monochloroethane 

Nitrogen oxides 

NMVOC 

PAH 

Particulates2.5-10 

Phenol 

Polychlorinated biphenyls 

R-10 

R-40 

Sulfur dioxide 

Tetrachloroethylene 

Toluene 

Trichloroethylene 

Xylene 
a Assuming 30% electrical 
efficiency 

Unit 

t (DM) 

kWh t-1 

kg t-1 
kg t-1 
kg t-1 
kg t-1 
kg t-1 
kg t-1 
kg t-1 
kg t-1 
kg t-1 
kg t-1 
kg t-1 
kg t-1 
kg t-1 
kg t-1 
kg t-1 
kg t-1 
kg t-1 
kg t-1 
kg t-1 
kg t-1 
kg t-1 
kg t-1 
kg t-1 
kg t-1 
kg t-1 
kg t-1 
kg t-1 
kg t-1 
kg t-1 
kg t-1 
kg t-1 
kg t-1 

Landfill gas 
combustion  

0.838 

342.3a 

5.59E-05 

7.45E-05 

7.01E+01 

3.05E-01 

4.69E-06 

2.35E-06 

2.35E-05 

1.41E-06 

1.86E-05 

1.30E-10 
1.86E-04 

9.38E-05 

4.69E-05 

1.44E-03 

1.44E-03 

7.51E-05 

6.70E-08 

2.58E-01 

6.57E-05 

2.95E-01 

5.63E-05 

3.60E-05 

6.48E-03 

9.32E-06 

3.60E-05 

2.35E-07 

1.41E-06 

1.10E-02 

4.69E-05 

1.02E-03 

1.88E-05 

3.73E-04 

144 

 
 
  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Table 50: Substance mass transfer for open storage of biosolids. TS: total solids; VS: volatile solids; Values are expressed 
on a wet weight basis, unless otherwise stated (Holly et al., 2017 Willén eta l., 2016; source: Delre et al., 2019) 

To air (%) 

To farmland 
(%) 

8.68 
7.10 
0.00 
15.78 
0.00 
0.00 
15.78 
0.00 

91.32 
92.90 
100.00 
84.22 
100.00 
100.00 
84.22 
100.00 

C bio 
N 
Water 
VS 
P 
K 
TS 
Ash 

Table 51: .Input-output disaggregated inventory for use on farmland of digestate, sludge and compost.  DM: dry matter. 
Values are expressed on a wet weight basis, unless otherwise stated (source: Tonini et al., 2019). 

Unit 

Use on land 

Inputs 
Feedstock-type 
Feedstock-quantity 

Diesel 

t (DM) 
L t-1 (DM) 

Digestate 
0.341 

6.30E-01 

Sludge  Compost 
0.732 

0.449 

6.30E-01 

6.30E-01 

Emissions to air 
Carbon dioxide, non-
fossil 
Carbon dioxide, fossila 
Methane, non-fossilb 
Dinitrogen monoxidec 

Ammonia 

kg t-1 

kg t-1 
kg t-1 
kg t-1 
kg t-1 

a From data derived by JRC  
b From data derived by JRC  
c From data derived by JRC  

2.38E+02 

3.39E+02 

2.98E+02 

-8.38E+01 

-9.03E+01 

-1.16E+02 

1.75E-01 

4.48E-01 

1.44E+00 

1.58E-01 

8.70E-02 

9.12E-01 

1.41E-01 

1.32E-01 

1.54E+00 

145 

 
 
  
 
 
 
  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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