How to assess climate change mitigation potential at project-level? : an estimation based on life cycle assessment of project proposals submitted under the European Green Deal call.
Date: 2022-02-22
Institutions: Directorate-General for Research and Innovation
Subjects: EU environmental policy, carbon neutrality, climate change policy, environmental impact, greenhouse gas, reduction of gas emissions, sustainable development

How to assess climate 
change mitigation potential 
at project-level? 
An estimation based on life cycle 
assessment of project proposals 
submitted under the European 
Green Deal Call 

R&I PAPER SERIES 
WORKING PAPER 2022/01 

Valeria DE LAURENTIIS, Andrea Martino AMADEI, 
Esther SANYÉ MENGUAL, Martina KADUNC, 
Konstantinos NIAKAROS, Serenella SALA  

Research  and 
Innovation 

 
 
 
 
 
 
 
 
How  to  assess  climate  change mitigation  potential  at  project-level?  An  estimation  based on  life  cycle 

assessment of project proposals submitted under the European Green Deal Call 

European Commission 
Directorate-General for Research and Innovation 
Directorate G — Common Policy Centre 
Unit G2 — Common Programme Analysis & Regulatory Reform 

Contact  
Email  

Ann-Sofie Ronnlund – Unit G2 
RTD-G2-SUPPORT@ec.europa.eu 
RTD-ECONOMIC-ANALYSIS@ec.europa.eu 
RTD-PUBLICATIONS@ec.europa.eu 

European Commission 
B-1049 Brussels 

Manuscript completed in October 2021.  

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EUROPEAN COMMISSION 

How to assess climate change 
mitigation potential at project-level? 
An estimation based on life cycle assessment of 
project proposals submitted under the European 
Green Deal Call 

Valeria De Laurentiis, 
European Commission, Joint Research Centre 
Andrea Martino Amadei, 
European Commission, Joint Research Centre 
Esther Sanyé-Mengual, 
European Commission, Joint Research Centre 
Martina Kadunc, 
European Commission, DG Research and Innovation 
Konstantinos Niakaros 
European Commission, DG Research and Innovation 
Serenella Sala 
European Commission, Joint Research Centre 

Working paper 

2022 

      Directorate-General for Research and Innovation 

EN

 
 
 
 
 
 
 
 
 
 
 
 
TABLE OF CONTENTS 

ABSTRACT .................................................................................................. 3 

1  Introduction............................................................................................ 3 
2  Methodology to calculate net climate change mitigation potentials ................. 4 
3  Application: calculating net climate change mitigation potential of projects ..... 8 

Projects selection 

3.1 
3.2  Calculating the net climate change mitigation potential: procedure 

10 
11 
4  Results of Application: Comparing climate change mitigation potentials.......... 15 
16 
17 
5  Conclusions and recommendations ............................................................ 17 
References .................................................................................................. 20 

4.1  Results of the assessment 
4.2  Main limitations of the proposed approach 

2 

 
 
 
 
 
 
 
 
 
 
 
 
 
ABSTRACT 

With  the  ambition  to  make  Europe  the  first  climate  neutral  continent  by  2050,  the 
European Union (EU) adopted in 2019 the European Green Deal (EGD). To finance the 
EGD, the EU is markedly investing in the transition towards a climate-neutral society. 
In  this  context,  the  present  paper  suggests  an  approach  enabling  the  ex-ante 
estimation  of  lifetime  carbon  savings  from  investment  projects.  The  assessment  is 
based on the use of the Environmental Footprint (EF) method, the EU recommended 
Life Cycle Assessment (LCA) based method to quantify the environmental impacts of 
products  and  organisations.  The  suggested  approach  is  applied  in  a  novel  survey 
dataset, stemming from the EGD call, and aims to perform a plausibility check of the 
expected  climate  change  mitigation  potentials  of  investment  projects  as  reported 
through  the  survey.  For  most  of  the  projects  assessed  there  are  significant 
differences  between  the  climate  change  mitigation  potentials  estimated  by  the 
methodology  proposed  in  this  report  and  the  potentials  reported  via  the  survey, 
highlighting the need for introducing a systematic approach to assess climate change 
mitigation potentials consistently across different projects. Lessons learned from this 
assessment  are  reported  and  suggestions  are  provided  on  how  to  design  future 
surveys  to  ensure  the  relevant  data  is  collected  to  apply  the  methodology  here 
presented. This approach could be used to systematically assess tangible and visible 
solutions  towards  the  targets  of  the  Green  Deal,  thus  serving  as  a  basis  for 
recommendations  of  any  ex-ante  analysis  of  projects  serving  towards  a  net-zero 
emissions future. 

1 

Introduction 

Climate  change  and  environmental  degradation  pose  an  existential  threat  to  the 
world.  To  overcome  these  challenges,  the  EU  adopted  the  European  Green  Deal 
(EGD)  (EC,  2019)  with  the  ambition  to  make  Europe  the  first  climate  neutral 
continent by 2050. To finance the EGD, the EU is investing around €600 billion from 
its  seven-year  budget1.  However, 
the  NextGenerationEU  Recovery  Plan,  and 
budgetary  spending  is  only  the  beginning  of  the  story  on  how  Europe  combats 
climate  change.  Europe  needs  to  be  able  to  show  how  this  spending  leads  the 
transition towards a climate-neutral society. 

In  this  context,  the  present  paper  suggests  an  approach  enabling  the  ex-ante 
estimation  of  lifetime  carbon  savings  from  investment  projects.  This 
approach, which builds on the methodology introduced by Rentschler et al. (2020), is 
adopted  to  perform  a  plausibility  check  of  the  expected  climate  change  mitigation 
potentials  of  investment  projects,  through  parallel  calculations  of  the  expected 
benefits,  leveraging  on  the  approach  suggested  by  the  ‘Green  Deal  Tracking  Tool’ 
(Flachenecker et al., 2021).  

1 https://ec.europa.eu/info/strategy/priorities-2019-2024/european-green-deal_en 

3 

 
 
The proposed methodology is applied in a novel survey dataset, stemming from the 
EGD  call.  In  the  framework  of  the  EGD,  the  Directorate-General  for  Research  and 
Innovation  (DG  RTD)  launched  in  September  2020  the  EGD  call,  a  €1  billion  call  for 
research  and innovation projects  that  respond  to  the  climate  crisis  and  help protect 
Europe's  unique  ecosystems  and  biodiversity2.  The  call  received  1  550  proposals, 
expected to deliver results in ten areas3. In February 2021, subsequently to the call’s 
deadline,  DG RTD launched  a  Climate  Impact  Pilot survey  with  the aim  of  assessing 
the  expected  climate  benefits  from  projects  applying  to  the  call.  The  suggested 
methodology  is  applied  to  several  project  proposals,  and  the  resulting  estimated 
climate change mitigation potentials are compared with those reported by the survey 
respondents.  

As  a  result  of  this  assessment,  a  number  of  lessons  learned  are  reported  and 
suggestions  are  provided  on  how  to  design  future  surveys  to  ensure  the  relevant 
data  is  collected  to  apply  the  methodology  here  presented.  This  methodology  can 
serve  as  a  basis  for  recommendations  of  any  ex-ante  analysis  of  projects, 
serving towards a net-zero emissions future. 

The rest of the paper is structured as follows. Section 2 described the methodology 
used  to  calculate  net  climate  change  mitigation  potentials  of  the  project  proposals. 
Sections  3  illustrates  and  application  of  calculating  net  climate  change  mitigation 
potential  of  project  proposals  submitted  under  the  EGD.  Section  4  presents  the 
results of the application. Finally, Section 5 concludes and provides recommendations 
for improving similar exercises in the future. 

2 

Methodology to calculate net climate change mitigation potentials 

Common  approaches  for  estimating  climate  benefits  from  resource  efficiency 
projects are mainly based on emissions factors-based calculations (Rentschler et 
al., 2020). This approach allows the calculations of greenhouse gas (GHG) emissions 
of  relevant  activities,  adopting  emission  factors  that  detail  the  potential  climate 
impacts of such activities. Emission factors-based approaches have been introduced 
for GHG accounting in several guidelines and standards. The use of this approach is 
evident in the Publicly Available Specification (PAS) prepared by the British Standards 
Institution  (BSI)  (BSI,  2011),  that  specify  requirements  for  assessing  the  life  cycle 
greenhouse  gas  emissions  of  goods  and  services.  Similarly,  this  approach  is  also 
proposed  by  the  Intergovernmental  Panel  on  Climate  Change  (IPCC)  Guidelines  for 
National  Greenhouse  Gas  Inventories  (IPCC,  2006).  Emission  factors  have  been  also 
considered  for  dedicated  country-specific  assessments,  such  as  the  study  from  van 
Voet  et  al.  (2005)  concerning  the  identification  of  the  environmental  impacts 

2 https://ec.europa.eu/commission/presscorner/detail/en/ip_20_1669 
3  Eight  thematic  areas:  Increasing  the  EU’s  climate  ambition  for  2030  and  2050;  Supplying  clean,  affordable  and 
secure energy; Mobilising industry for a clean and circular economy; Building and renovating in an energy and 
resource efficient way; Accelerating the shift to sustainable and smart mobility; From ‘Farm to Fork’: designing 
a fair, healthy and environmentally-friendly food system; Preserving and restoring ecosystems and biodiversity; 
A zero pollution ambition for a toxic-free environment. 

   Two horizontal areas: Strengthening knowledge; Empowering citizens 

4 

 
 
associated  to  materials  in  the  Netherlands.  Furthermore,  the  ISO  standards  (ISO, 
2006a) detail the use of emission factors-based calculations for the monitoring and 
reporting  of  GHG  emissions  reductions  (i.e.,  quantified  decrease  in  GHG  emissions 
between a baseline scenario and a project) or removal enhancements (i.e., quantified 
increase in GHG removals between a baseline scenario and a project). In more recent 
years,  guidelines  for  the  adoption  of  emission  factors-based  approaches  have  been 
further  developed  by  the  World  Resource  Initiative  (WRI)  and  the  World  Business 
Council  for  Sustainable  Development  (WBCSD)  in  the  context  of  products  life  cycle 
accounting  and  reporting  (WBCSD  &  WRI,  2011),  but  also  for  corporate  GHGs 
accounting  and  reporting  (WBCSD  &  WRI,  2004)  and  projects  accounting  (WBCSD  & 
WRI,  2005).  The  extensive  implementation  of  emission  factors-based  accounting 
methodologies  is  also  evident  in  the  context  of  investments,  as  the  European 
Investment  Bank  (EIB)  also  applies  such  approaches  for  the  assessment  of  GHG 
emissions impacts associated to investments projects (EIB, 2014). 

The  systematic  assessment  of  climate  change  mitigation  potential  of  projects 
proposal  is  based  on  an  estimation  of  climate  change  impacts  per  unit  of 
materials  and  energy  use  derived  through  a  Life  Cycle  Assessment  (LCA) 
approach,  considering  the  life  cycle  impact  on  climate  change  caused  by  the 
production,  distribution  and  use  of  energy  and  materials  (i.e.,  from  cradle  to  gate). 
The amount of materials and energy saved or used (for replacement purposes) by a 
project (e.g., energy from grid electricity, fossil fuel consumption) is multiplied by the 
correspondent  climate  change  impact  per  unit  of  resource,  to  derive  the  associated 
climate change avoided impacts/impacts. The net climate change mitigation potential 
of  a  project  is  then  estimated  by  subtracting  the  impacts  associated  with  the 
expected uses of the substituting materials and energy from the benefits associated 
with the materials and energy savings.  

According  to  the  definition  reported  in  the  ISO  standard  (ISO,  2006b),  Life  Cycle 
Assessment  is  the  compilation  and  evaluation  of  the  inputs,  outputs,  and  the 
potential environmental impacts of a product system throughout its life cycle. LCA is 
mentioned  in  the  Better  Regulation  communication  (EC,  2015),  aimed  at  ensuring 
that political decisions are prepared in a transparent and open way, informed by the 
best available evidence as well as supported through the comprehensive involvement 
of  stakeholders.  The  Better  Regulation  Toolbox  (EC,  2017)  is  particularly  relevant 
since it covers in a technical way the LCA method, providing insights on the various 
steps  of  the  method  in  view  of  performing  economic/social  and  sustainability 
analysis. The LCA methodology (Figure 1) provides quantitative information on 
the  environmental  performance  of  goods  and  services  and  can  therefore  be 
also  a  valuable  approach  for  assessing  environmental  impacts  associated  with 
projects.  In  the  impact  assessment  phase  of  LCA,  emissions  of  substances  into  the 
environment  and  resources  used  in  the  life  cycle  of  goods  and  services,  collected 
within the life cycle inventory analysis step and therefore defined “inventory flows”, 
are associated to environmental impact categories and indicators through Life Cycle 
Impact  Assessment  (LCIA)  methods,  following  two  steps.  First  inventory  flows  are 
classified  into  midpoint  impacts  categories  (e.g.,  climate  change,  particulate  matter, 
etc.).  Second  they  are  characterized  into  common  units  to  allow  comparison  within 

5 

 
the  same  impact  category  (e.g.:  kg  CO2  equivalent).  Following  this  phase,  midpoint 
impacts  can  be  aggregated  to  endpoint  impact  categories  (e.g.,  human  health, 
ecosystem quality, etc.) and interpreted in accordance with the goal and scope of the 
LCA study. 

Figure 1. Overview of the Life Cycle Assessment method. 

In  2013,  the  establishment  of  the  Product-  and  Organisation  -  Environmental 
Footprint  methods  (respectively,  PEF  and  OEF)  represented  a  milestone  in  the 
implementation  of  LCA  (EC,  2013).  These  LCA-based  methods  aim  at  the 
quantification  of  the  environmental  impacts  of  products  and  organisations.  The 
PEF/OEF  methods  introduced  an  important  improvement  and  guidance  compared  to 
the existing LCA standards (ISO, 2006b,c) concerning key methodological choices and 
data  quality  requirements,  and  established  rules  for  the  development  of  life  cycle 
inventories,  the  so-called  Environmental  Footprint  (EF)-compliant  datasets 
(Fazio et al., 2020). PEF/OEF methods are currently under a transition phase to allow 
impact 
further  testing  and  methodological  developments 
assessment  phase  of  a  PEF/OEF  study  is  conducted  following  the  EF  impact 
assessment method, where life cycle impacts are calculated for 16 midpoint impact 
categories4. 

(EC,  2021a).  The 

The present paper focuses exclusively on the climate change impact category of the 
EF impact assessment method. A set of climate change impacts per unit of materials 
and  energy  use  is  calculated,  and  an  operational  procedure  to  calculate  the  overall 
net  climate  change  mitigation  potential  of  the  projects  that  participated  to  the  DG 

4 The  16  impact categories and the  associated  indicators of  the  EF method are: climate change  [kg  CO 2  eq.]; 
ozone  depletion  [kg  CFC-11  eq.];  human  toxicity,  cancer  [CTUh];  human  toxicity,  non -cancer  [CTUh], 
particulate  matter  [disease  incidences];  ionizing  radiation,  human  health  [kBq  U235  eq.];  photochemical 
ozone formation, human health [kg NMVOC eq.]; acidification [mol H + eq.]; eutrophication, terrestrial [mol 
N  eq.];  eutrophication,  freshwater  [kg  P  eq.];  eutrophication,  marine  [kg  N  eq.];  land  use  [points  -  pt]; 
ecotoxicity, freshwater [CTUe]; water use [m3 water eq. of deprived water]; resource use, fossils [MJ] and 
resource use, minerals and metals [kg Sb eq.]. 

6 

 
 
 
 
RTD  survey  is  provided.  To  this  end  climate  change  impacts  per  unit  of 
materials  and  energy  use  were  derived  from  life  cycle  impacts  of  EF 
compliant datasets, as illustrated in Figure 2, with the example of grid electricity. 
These  unitary  impacts  were  then  used  to  convert  the  predicted  materials  and 
energy savings into climate change avoided impacts, as illustrated in Figure 3. 
Both  visualisations  are  focused  on  climate  change  impacts  alone,  however  similar 
considerations for  the  other  15 impact  categories  of  the  EF method  are  achievable. 
For  instance,  for  tap-water  use  (Figure  3),  it  would  be  relevant  also  to  explore  the 
implications on water scarcity. 

Figure 2. Numerical example of data employed for the calculation of the EF Climate 
Change impact per unit electricity (in KWh)  

Note : The EF-compliant datasets for the inventory, and the EF impact  assessment method for the characterisation, in 
the case of grid electricity were used. 

7 

 
 
 
 
 
Figure  3.  Calculation  steps  to  convert  resource  savings  (e.g.,  electricity  or  water 
savings) into climate change avoided impacts 

Note:  Coefficients  (β,  θ)  expressing  the  climate  change  impact  per  unit  of  resource  are  used.These  coefficients  are 
resource specific and are derived from EF compliant datasets (see Figure 2). 

3 

Application: calculating net climate change mitigation potential of 
projects 

The  aim of  this  section is to provide an example  of the  application  of  the proposed 
methodology by illustrating the procedure to calculate the overall net climate change 
mitigation  potential  (in  terms  of  CO2  equivalent)  of  the  project  proposals  submitted 
under  the  EGD  call,  using  as  a  starting  point  the  data  collected  through  the  related 
survey. 

The  survey  aimed  at  gathering  general  information  on  the  projects  (e.g.,  sectors 
covered,  geographical  scope,  project’s  short  description,  reference  system,  etc.), 
together with quantitative data to assess baseline climate impacts and the expected 
projects’  life  cycle  climate  change  mitigation  potentials  in  2030.    The  respondents 
had  to  select  a  method  employed  for  the  calculation  of  the  climate  change 
mitigation potentials choosing between: (i) an approach based on avoided emissions 
(direct  emissions);  (ii)  an approach based  on life  cycle assessment;  (iii)  an approach 
based on the “Product/Organisation environmental footprint”; or (iv) other approaches 
to  be  specified.  The  selection  of  none  or  more  than  one  approach  was  possible.  To 
understand  the  main  elements  leading  to  the  climate  change  mitigation  potentials, 
disaggregated  information  was  collected  in  terms  of  materials  and  energy 
savings, such as energy sources  (e.g., savings of primary energy sources such as 
natural gas, savings of secondary energy sources such as grid electricity),  materials 
(e.g.,  savings  of  cement,  savings  of  steel),  water  (e.g.,  savings  of  tap  water)  and 
other  resources.  However,  no  questions  on  the  quantities  of  potential  substituting 
materials and energy were posed. A total of 678 unique proposals responded to the 
survey  (out  of  1550  submitted  proposals),  of  which  640  completed  the  survey  and 
566 expected to contribute to decreasing the CO 2 eq. emissions by 2030.  

8 

 
 
Most  of  the  projects  targeted  interventions  in  the  agriculture  and  forestry  sectors, 
followed by energy and by households (Figure 4), and in many cases  cross-sectorial 
initiatives  were  identified.  Most  of  the  projects  aimed  at  a  reduction  of  greenhouse 
gases  through  a  change  in  the  current  technology  used,  by  influencing  consumer 
behaviour  or  by  changing  the  consumer  behaviour,  although  most  projects  selected 
more  than  one  area  of  intervention.  (Figure  5).  The  largest  share  of  the  projects 
targeted  either  individuals/citizens  or  companies.  Less  than  a  third  of  the 
respondents had already estimated the climate mitigation potential of their 
solution  in  tonnes  of  CO2  equivalent  while  preparing  the  project  proposal.  Among 
those,  76%  chose  an  approach based on  avoided  emissions  (direct emissions), 40% 
an  approach  based  on  life  cycle  assessment,  20%  an  approach  based  on  the 
“Product/Organisation  environmental  footprint”,  and,  6%  other  approaches  (multiple 
answers were allowed). 

Figure 4. Economic sectors in scope of the surveyed projects (share % of respondents) 

Agriculture and forestry

Energy

Households

Transport and mobility

Land use

Industry

Construction and building

IT

Finance

Other

Not Answered

0

10

20

30

40

50

60

Question: In which economic sector do you expect to reduce or prevent emissions of  greenhouse gases? 
Base: 566 respondents who expected to contribute to decreasing the CO2eq emissions by 2030.     
Note: Multiple responses allowed. Economic sectors distinction was defined by the survey designers. 

9 

 
 
 
 
Figure 5. Main areas interested by the projects’ interventions (share % of respondents) 

Technology used

Consumer behaviour

Business models

Energy used

Materials used

Energy efficiency of production

Product characteristics

Other

Not Answered

0

10

20

30

40

50

60

70

Question: What does the project aim to change to reduce or prevent emissions of greenhouse gases?  
Base: 566 respondents who expected to contribute to decreasing the CO2eq emissions by 2030.     
Note: Multiple responses allowed 

3.1 

Projects selection 

To  provide  an  example  of  application  of  the  proposed  methodology,  a  subset  of  9 
projects was selected, from the original 678 unique proposals’ responses to 
the survey, and assessed in detail. The selection was performed according to the 
following criteria: 

• 

• 

• 

The  projects  indicated  the  PEF  and/or  OEF  method  as  a  methodology 
employed to calculate the climate change mitigation potential; 
The  respondent  provided  a  quantitative  information  related  to  the  climate 
change mitigation potential; 
The  respondent  provided  detailed  information  related  to  the  scope  of  the 
project  (i.e.,  geographical  scope,  project  description,  reference  system,  etc.) 
and  provided  numerical  information  on  energy  sources  (primary  and/or 
secondary),  materials  and  other  sources  savings  and  baselines  (ideally 
specifying how savings were planned to be achieved and how they had been 
estimated). 

Following  the  initial  screening  performed  on  the  678  projects,  34  projects  were 
selected  since  they  were  mentioning  the  PEF/OEF  methods  amongst  the  methods 
employed  to  calculate  climate  change  mitigation  potentials.  The  first  selection 
criterion was set as it was expected that projects following a similar approach to the 
one  here  suggested  in  estimating  climate  change  mitigation  potentials  would  more 
likely  reach  similar  results,  as  opposed  to  projects  adopting  different  approaches. 

10 

 
 
The  list  was  then  further  refined,  based  on  the  remaining  selection  criteria 
mentioned, leaving a total of 9 projects selected for further assessment (Figure 7).   

Figure 7. Overview of the screening performed to select the assessed initiatives. 

3.2  Calculating the net climate change mitigation potential: procedure 

The  net  climate  change mitigation  potential  of  each  selected  project  was  derived from 
the information obtained by the respondents on materials and energy saved (obtained by 
comparing  the  use  in  the  baseline  year  with  their  expected  use  in  2030),  and  then 
compared  with  the  climate  change  mitigation  potential  reported  by  respondents,  by 
adopting a procedure articulated in six steps (Figure 8). 

Figure 8. Overview of the six-step procedure adopted. 

11 

 
 
 
Step  1.  By  analysing  the  projects  information,  projects  were  classified  as  belonging 
to two different groups: 

•  Group  A:  projects  achieving  an  absolute  reduction  of  inputs.  Energy, 
water,  and  other  resources  are  saved  due  to  e.g.  improvements  in  the 
efficiency of materials, design, improvements due to behavioural change, etc. 
In  this  case  only  the  materials  and  energy  saved  were  recorded.  Overall,  1 
project was included in this group; 

•  Group B: projects performing at least one substitution of inputs with 
greener  alternatives.  Energy,  water  and  materials  are  saved  due  to 
substitution  with  alternative  sources  (e.g.,  renewable  energy,  rainwater 
harvesting).  In  this  case,  both  the  materials  and  energy  saved  and  the 
alternative  materials  and  energy  sources  used  were  recorded.  Overall,  8 
projects were included in this group. 

Step  2.  The  projects  were  analysed  to  identify  the  list  of  materials  and  energy  for 
which climate change impacts were needed. 

Step  3.  Relevant  EF-compliant  datasets  were  selected  for  the  materials  and  energy 
identified in Step 25. In some cases, a proxy dataset was built based on the average 
of more than one dataset6. 

The  EF  datasets  were  collected  from  EF-compliant  nodes  managed  by  several  data 
providers  (i.e.,  Thinkstep  (Thinkstep, 2021),  Blonkconsultant  (Blonkconsultant,  2021), 
Ecoinvent  (Ecoinvent,  2021)  and  Quantis  (Quantis,  2021)).  When  possible,  average 
EU datasets were prioritized. Details about each dataset (i.e., the Universally Unique 
Identifier  (UUID)  and  the  reference  unit)  were  stored  in  a  database.  An  overview  of 
the datasets used is provided in Annex 1. 

Step 4. The environmental impacts of the selected EF datasets were calculated using 
the  EF3.0  method  (Fazio  et  al.,  2018)  and  the  software  Look@LCI  (EC,  2021b), 
focusing on climate change impacts. According to the reference unit of each dataset, 
adjustments (e.g., unit conversions from KWh to MWh) were performed to adapt the 
data to the unit of measure adopted in the survey 7. 

Step  5.  Climate  change  avoided  impacts  associated  with  the  reported  savings  of 
materials  and  energy  were  derived  based  on  the  following  methodology,  further 
elaborated from Flachenecker et al. (2021). 

5 For instance, a grid electricity dataset (modelled based on the EU electricity mix and residual mix supplied to 

final consumers) was chosen to derive the emission factor for grid electricity.  

6 For instance, the average of the emissions factors derived from the EF datasets “heavy fuel oil at refinery” 

and “light fuel oil at refinery” was associated to fossil fuels. 

7 When the units of the available datasets could not be directly converted into the unit indicated in the survey, 
calculations were  performed to adapt  the results  (e.g., leveraging on  the  density of natural gas  (kg/m 3), 
results expressed as impacts per unit of mass (kg) were converted to impacts per unit of volume (m 3)). 

12 

 
 
For  projects  belonging  to  group  A  (absolute  reduction  of  inputs),  the  climate 
mitigation potential is equal to the  sum of the climate change avoided impacts 
derived  by  multiplying  the  resource-specific  climate  change  impacts,  obtained 
from  the  EF  datasets,  with  the  amounts  of  materials  and  energy  saved  (Figure 
9).  However,  if  the  reduction  of  impacts  is  achieved  by  implementing  a  new 
technology  (e.g.  increasing  the  energy  efficiency  of  a  building),  this  will  most  likely 
have some associated impacts which should be taken into account (red bar in figure 
9). An example of the calculations performed in the case of savings of grid electricity 
is reported in equation 1: 

𝐶𝑙𝑖𝑚𝑎𝑡𝑒 𝐶ℎ𝑎𝑛𝑔𝑒 𝑎𝑣𝑜𝑖𝑑𝑒𝑑 𝑖𝑚𝑝𝑎𝑐𝑡𝑠𝐺𝑟𝑖𝑑 𝑒𝑙𝑒𝑐𝑡𝑟𝑖𝑐𝑖𝑡𝑦  [𝑡𝑜𝑛 𝐶𝑂2 𝑒𝑞. ] = 

𝐸𝑛𝑒𝑟𝑔𝑦𝑆𝑎𝑣𝑖𝑛𝑔𝑠𝐺𝑟𝑖𝑑 𝑒𝑙𝑒𝑐𝑡𝑟𝑖𝑐𝑖𝑡𝑦  [𝑀𝑊ℎ]

(EQ.1) 

∗   𝐶𝑙𝑖𝑚𝑎𝑡𝑒 𝐶ℎ𝑎𝑛𝑔𝑒 𝐼𝑚𝑝𝑎𝑐𝑡𝑠 𝑝𝑒𝑟 𝑢𝑛𝑖𝑡 𝐺𝑟𝑖𝑑 𝑒𝑙𝑒𝑐𝑡𝑟𝑖𝑐𝑖𝑡𝑦   [

𝑡𝑜𝑛 𝐶𝑂2 𝑒𝑞.
𝑀𝑊ℎ

] 

For  projects  belonging  to  Group  B  (substitution  of 
inputs  with  greener 
alternatives), the impacts from the expected use of the substituting materials 
and  energy  were  also  considered  to  assess  the  net  climate  mitigation  potential. 
Therefore,  on  top  of  assessing  climate  change  avoided  impacts  by  means  of 
equation  1,  climate  change  impacts  due  to  the  substituting  materials  and  energy 
were  calculated  as  exemplified  in  equation  2,  which  provides  an  example  of  the 
calculation performed to assess the impact of the substituting materials and energy, 
in the case of electricity from solar PV. 

𝐶𝑙𝑖𝑚𝑎𝑡𝑒 𝐶ℎ𝑎𝑛𝑔𝑒 𝑖𝑚𝑝𝑎𝑐𝑡𝑠𝑃𝑉  [𝑡𝑜𝑛 𝐶𝑂2 𝑒𝑞. ] = 

𝑈𝑠𝑒 𝑜𝑓 𝑠𝑢𝑏𝑠𝑡𝑖𝑡𝑢𝑡𝑖𝑛𝑔 𝑟𝑒𝑠𝑜𝑢𝑟𝑐𝑒𝑃𝑉  [𝑀𝑊ℎ]

∗   𝐶𝑙𝑖𝑚𝑎𝑡𝑒 𝐶ℎ𝑎𝑛𝑔𝑒 𝐼𝑚𝑝𝑎𝑐𝑡 𝑝𝑒𝑟 𝑢𝑛𝑖𝑡 𝑃𝑉   [

(EQ.2) 

𝑡𝑜𝑛 𝐶𝑂2 𝑒𝑞.
𝑀𝑊ℎ

] 

Information on the quantities of each substituting material and energy used was 
not  asked  explicitly  in  the  survey.  Therefore,  for  this  exercise,  this  information 
was deduced from the other answers provided by the respondents. 
The  overall  net  climate  change  mitigation  potential  of  each  project  was  then 
calculated as the sum of the climate change avoided impacts linked to materials and 
energy  savings  minus  the  sum  of  the  additional  impacts  due  substituting  materials 
and energy use (Eq.3). 

13 

 
 
 
 
 
 
 
𝑁𝑒𝑡 𝑐𝑙𝑖𝑚𝑎𝑡𝑒 𝑐ℎ𝑎𝑛𝑔𝑒 𝑚𝑖𝑡𝑖𝑔𝑎𝑡𝑖𝑜𝑛 𝑝𝑜𝑡𝑒𝑛𝑡𝑖𝑎𝑙𝑝𝑟𝑜𝑗𝑒𝑐𝑡_𝑖  [𝑡𝑜𝑛 𝐶𝑂2 𝑒𝑞. ] = 

 ∑(𝐶𝑙𝑖𝑚𝑎𝑡𝑒 𝐶ℎ𝑎𝑛𝑔𝑒 𝑎𝑣𝑜𝑖𝑑𝑒𝑑 𝑖𝑚𝑝𝑎𝑐𝑡𝑠𝑗  [𝑡𝑜𝑛 𝐶𝑂2 𝑒𝑞. ])

(EQ.3) 

𝑗

−  ∑(𝐶𝑙𝑖𝑚𝑎𝑡𝑒 𝐶ℎ𝑎𝑛𝑔𝑒 𝑖𝑚𝑝𝑎𝑐𝑡𝑠𝑘 [𝑡𝑜𝑛 𝐶𝑂2 𝑒𝑞. ]

) 

𝑘

Figure  9  illustrates  the  conceptual  framework  for  assessing  net  climate  change 
mitigation potential for group A projects, in the case of a project aiming at reducing 
the  use  of  electricity  and  water  due  to  improvements  in  efficiency.  Figure  10 
illustrates the conceptual framework for assessing the net climate change mitigation 
potential for  group  B projects, with  the  example of  a project aiming at  replacing all 
the electricity taken from the grid with electricity from solar PV. 

Figure 9. Conceptual framework for assessing net climate change mitigation  
potential for group A projects. 

14 

 
 
 
 
 
 
Figure  10.  Conceptual  framework  for  assessing  net  climate  change  mitigation 
potential for group B projects. 

Step  6.  The  resulting  net  climate  mitigation  potential  estimated  by  means  of  EF-
compliant  datasets  was  compared  with  climate  mitigation  potential  reported  by  the 
respondents.
survey 

4 

Results  of  Application:  Comparing  climate  change  mitigation 
potentials 

Each  of  the  9  projects  selected  was  analysed  in  detail  and  the  net  climate  change 
mitigation  potential  were  derived  based  on  the  climate  change  impacts  per  unit  of 
materials  and  energy  derived  from  EF  datasets,  following  equations  1  to  3.  The 
complete list of climate change impacts considered for the analysis of the projects is 
provided in Annex 2. 

Most  of  the  projects  expected  to  achieve  savings  in  electricity  production 
(especially  grid  electricity  or  electricity  from  natural  gas)  and  proposed 
substitutions  with  greener  alternatives  such  as  electricity  production  from 
photovoltaic  or  hydrogen,  while  the  most  common  material  savings  were 
related to steel and cement as well as tap water. 
In  several  of  the  projects  analysed,  assumptions  had  to  be  taken  to  deal  with  data 
gaps  or  issues  related  to  potentially  different  interpretations  of  the  information 
provided by the survey respondents. These pending issues should ideally be checked 
with the survey respondents to complete/refine the assessment. 

15 

 
 
 
 
 
 
 
4.1  Results of the assessment 

A synthetic overview of the results of the assessment is reported in Table 1. 

Table  1.  Comparison  of  the  climate  change  mitigation  potentials  reported  and 
estimated  and  project  categorization.  The  column  "Type  of  the  project"  refers  to 
Group  A  projects  (absolute  reduction  of  input)  and  Group  B  (substitution  of  inputs 
with greener alternatives) projects. 

Note:  Arrow  in  third  column  indicates  whether  the  estimated  change  using  EF-datasets  was  higher  or  lower 
than the reported one (second column). 

8  out  of  9  projects  were  categorized  as  proposing  substitutions  of  inputs  with 
greener  alternatives  (Group  B,  Section  2),  whilst  one  project  aimed  at  achieving  an 
absolute  reduction  of  inputs  (Group  A,  Section  2).  Notably,  two  projects  (project 
codes:  P8  and  P9)  were  classified  as  “Group  B  (substitution)”  from  the  information 
provided,  even  though  the  respondents  did  not  provide  enough  information  to 
quantify the substitution.  

Overall,  large  discrepancies  were  found  between  the  climate  change  mitigation 
potentials reported by the respondents and those estimated in this work. The 
largest  variations  were  found  for  project  P6,  with  estimated  mitigation  potentials 
three  orders  of  magnitude  lower  than  the  reported  ones,  and  for  project  P1,  with 
estimated mitigation potential four orders of magnitude higher than those reported. 
The  calculated  EF-based  net  climate  change  mitigation  potentials  were  higher  than 
the  corresponding  climate  change  mitigation  potentials  reported  in  only  two  cases 
(project  codes:  P1,  P5).  In  all  the  remaining  cases,  the  calculated  EF-based  net 
climate change mitigation potentials were lower than the climate change mitigation 
potentials  provided  by  the  survey  respondent.  The  highest  agreement  between  the 
two  estimates  was  found  in  the  case  of  project  P3  (EF-based  climate  change  net 
mitigation  potential  62%  lower  than  the  reported  climate  change  mitigation 
potential)  and  in  the  case  of  project  P4  (EF-based  climate  change  mitigation 
potential 83% lower than the reported climate change mitigation potential). 

16 

 
 
In  general,  the  comparison  between  the  net  climate  change  mitigation  potentials 
estimated  in  this  work  and  those  reported  in  the  survey  showed  significant 
differences for most of the projects assessed. This might be due to: 

•  not  considering  “substitution”  effects  in  the  case  of  Group  B  projects 
(reporting the climate change mitigation potential rather than the net climate 
change mitigation potential); 

•  different underlying modelling approaches that might limit  the comparability 

of the results; 

•  different  underlying  data  and  data  assumptions,  in  particular  regarding  the 
climate  change  impacts per  unit  of  materials  and  energy  (respondent  might 
have used country-specific coefficients, whilst EU datasets were used in the 
estimation of climate change mitigation potentials conducted in this work); 
•  differences  in  the  results  due  to  the  selection  of  the  datasets  used  to 
calculate  climate  change  impacts  per  unit  of  materials  and  energy  (in  case 
the technology used in the project is not well represented by the EF-datasets, 
modelled considering the average product on the market); 

•  even  if  the  survey  was  launched  after  the  call’s  deadline  and  it  was  clearly 
communicated  that  it  had  no  impact  on  the  call’s  evaluation,  respondents 
might  have  presented  a  favourable  image  of  the  potential  of  their  projects 
(Van de Mortel, 2008). 

4.2  Main limitations of the proposed approach 

This  work  is  affected  by  two  main  limitations.  As  the  survey  did  not  explicitly 
distinguish projects achieving an absolute reduction of inputs from projects achieving 
energy  and  material  savings  by  replacing  them  with  alternative  greener  materials 
and energy, there were no questions on the amounts of materials and energy used in 
replacement.  Therefore,  deductions  were  made  to  fill  this  data  gap  and  assess  the 
impacts  of  the  substituting  technologies,  adding  a  level  of  uncertainty  to  the 
estimation  of  the  net  climate  benefits  of  the  projects,  which  might  further  explain 
the  differences  between  the  reported  climate  change  mitigation  potentials  and  the 
ones  estimated  in  this  report.  Furthermore,  when  selecting  the  EF-compliant 
datasets,  it  was  not  always  possible  to  collect  datasets  directly  related  to  the 
materials and energy saved by the projects. In these cases, proxies of datasets were 
necessary (e.g., built based on the average of more than one dataset).  

5 

Conclusions and recommendations 

This paper suggests a novel methodology to assess the expected net climate change 
mitigation  potential  of  project  proposals.  To  this  end,  information  on  savings  of 
materials and energy achievable through a project and on substituting materials and 
energy (if relevant) should be collected through a survey and used as input to derive 
net  climate  change  mitigation  potentials  through  a  life  cycle  approach.  The 
assessment  is  based  on  the  use  of  the  Environmental  Footprint  method,  the  EU 
recommended  Life  Cycle  Assessment  based  method  to  quantify  the  environmental 

17 

 
impacts of products and organisations. The method suggested could serve as a basis 
for recommendations of any  ex-ante analysis of projects  serving towards a net-
zero emissions future. 

The  proposed  methodology  allows  for  a  consistent  approach  for  calculating  net 
climate  change  mitigation  potential  of  projects  proposals,  and  could  be  used  to 
systematically assess  tangible and visible solutions  towards the targets of the 
Green  Deal.  This  methodology  would  also  potentially  be  suitable  for  covering  the 
full list of 16 EF impact categories, enabling a more comprehensive overview o f the 
effects  of  projects  across  different  environmental  dimensions  and  highlighting 
potential trade-offs between different environmental dimensions caused by the 
project  implementation  (i.e.,  situations  in  which  a  technological  change  might  cause  a 
reduction in the impacts on certain environmental dimensions and at the same time an 
increase in the impacts on other environmental dimensions). 

The methodology was tested by application to 9 selected project proposals submitted 
under the EGD call, and the resulting estimated climate change mitigation potentials 
were  compared  with  those  reported  by  the  survey  respondents.  Projects  were 
categorized  in  two different  groups, detailing  those achieving an  absolute  reduction 
of  inputs  (Group  A  -  1  in  total)  and  those  performing  at  least  one  substitution  of 
inputs  with  (assumed)  greener  alternatives  (Group  B  -  8  in  total).  For  most  of  the 
projects  assessed  there  were  significant  differences  (as  high  as  three  order  of 
magnitudes)  between  the  climate  change  mitigation  potentials  estimated  by  the 
methodology  proposed  in  this  report  and  the  potentials  reported  via  the  survey, 
highlighting  the  need  for  the  introduction  of  a  systematic  approach  to  assess 
climate  change  mitigation  potentials  consistently  across  different  projects.  The 
distinction between Group A/B was not explicitly covered by a specific question of the 
survey  and  specific  assumptions  were  therefore  necessary  to  fill  these  data  gaps 
and  assess  the  impacts  of  the  substituting  technologies,  adding  a  level  of 
uncertainty to the estimation of the net climate benefits of the projects . 

The  assessment  performed  in  this  exercise  allowed  to  identify  some  potential 
solutions  to  improve  the  estimation  of  the  expected  climate  change  mitigation 
potential  of  projects  proposals.  To  this  end,  suggestions  are  provided  on  how  to 
harmonize the estimation of climate change mitigation potentials of projects and on 
how  to  design  future  surveys  to  ensure  the  relevant  data  is  collected  to  apply  the 
methodology here presented. 

1.  Future  surveys  should  be  designed  to  ensure  that  projects  are 
categorized  according  to  whether  they  aim  at  achieving  an  absolute 
reduction  of  inputs  (in  terms  of  energy  and  materials)  or  they  aim  at 
replacing at least one input with a low-impact alternative. This would 
allow  to  better  calculate  net  climate  change  mitigation  potentials  and  to 
identify  and  assess  trade-offs.  This  categorization  could  be  performed 
through  a  specific  question  dedicated  to  the  presence  of  substitution  of 
inputs  with  greener  alternatives.  Based  on  the  answer  provided  by  the 

18 

 
respondents to this question, the following survey questions could be tailored 
to  ask  more  details  on  the  amounts  of  substituting  energy  and  materials 
used, in case of Group B projects. 

2.  A possible approach to  harmonize the calculations  of net climate change 
mitigation  potentials  would  be  the  development  of  a  calculator  enabling 
the  applicants  to  estimate  the  expected  net  climate  change 
mitigation potential based on the estimated savings and additional use of 
materials and energy. To perform such calculations, the tool would use in the 
background  climate  change  impacts  per  unit  of  materials  and  energy 
obtained from EF datasets (either considering EU averaged datasets, or even 
country-specific  datasets).  Unless  a  calculator  was  provided  to  harmonize 
the estimation, future surveys should include questions specifically related to 
the  adopted  methodology  for  calculating  total  climate  change  mitigation 
potential. This would greatly improve the quality of any potential comparison 
and  the  analysis  of  the  provided  answers.  It  would  be  relevant  to  ask  more 
details  regarding  the  sources  used  for  estimating  the  avoided  impacts  (e.g., 
literature, pilot scale data, own assumptions, estimates, etc.). 
It  would  be  useful  to  provide  insights  related  to  other  environmental 
impacts  beyond  climate  change,  e.g.  responding  to  the  zero  pollution 
ambitions of the Green Deal. This information could be directly calculated 
by  the  abovementioned  calculator,  which  could  assess  net  avoided  impacts 
for  the 16  environmental dimensions  covered  by  the  EF method.  This would 
allow  for  a  more  comprehensive  overview  of  the  effects  of  projects  across 
different environmental dimensions and highlight potential trade-offs caused 
by the project implementation. 

3. 

4.  Future surveys should clearly state what is meant by baseline use of energy 
and materials and savings calculated against such baseline, and what is the 
timeframe  to  which  the  reported  savings  are  referred  to.  They  should  also 
stress  the  importance  of  using  the  correct  unit  of  measure  when  providing 
quantities  of  energy  and  resources  saved  and  should  avoid  referring  to 
aggregated  categories  of  resources  to  reduce  uncertainty  of  the  estimations. 
Moreover,  to  allow  comparability  between  different  surveys,  international 
taxonomy  systems  should  be  used  (e.g.  NACE  for  the  economic  sectors).

19 

 
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at: 
doi:10.2760/424613. 

European  Commissions.  Available 

Luxembourg, 

• 

21 

 
 
Annex 1 – List of the EF datasets considered for the calculations 

The table below summarizes the main information of the EF datasets considered for the calculations. 

DATASET 
SHORT NAME 

Electricity  grid 
mix – EU - 1kv-
60kv 
Residual 
mix - EU 
Natural gas mix 

grid 

AND 

MATERIAL 
ENERGY 
CATEGORY 
(TABLE 2)  

DATASET 
INFORMATION 

UNIVERSALLY 
(UUID) 

UNIQUE 

IDENTIFIER 

COMMENT 

Electricity – grid 
mix  

Electricity - 3.6 MJ 

34960d4d-af62-43a0-aa76-
adc5fcf57246 

The  average  of  these  datasets  was 
considered. 

Natural gas 

Electricity  from 
natural gas 

Electricity – natural 
gas 

Electricity - 3.6 MJ 

8fb75312-431d-42f6-9a4f-22fa886f7fe3 

gas, 

Natural 
at 
consumer  EU+EFTA  - 
1kg  
Electricity - 3.6 MJ 

6af14cd2-fd8b-408c-a149-
849b0d10c195 

12b5890a-16ef-4a6d-b8c2-
660e3d11be48 

The  density  of  natural  gas 
(0.668 
kgCH4/m3  at  20°C,  1  atm)  was  considered 
to convert the result in m3. 
- 

Hard coal mix 

Hard coal mix 

Hard coal, at consumer 
EU+EFTA - 1kg  

c62a4166-221b-45f1-8aeb-
c29c863ee8bd 

Steel 

Fossil fuel 

Electrolytic 
chromium 
coated steel 

Heavy fuel oil at 
refinery 
Light  fuel  oil  at 
refinery 

tin-free 

steel 
Steel 
(Electrolytic 
chrome-
coated  steel,  ECCS)  - 
1kg 
Heavy  fuel  oil 
wt.% S) - 1kg 
Light fuel oil - 1kg 

(1.0 

9d2754ad-5813-47e0-9803-
87b437a75ee7 

0d3757fb-e445-4315-be99-
94410c05a7b1 
386821c2-309d-4019-8972-
04a072082ef5 

22 

- 

- 

The  average  of  these  datasets  was 
considered. 

 
 
 
 
Electricity  from 
biomass (solid) 

Electricity – solid 
biomass 

Electricity - 3.6 MJ 

b292e936-e4bb-428d-b79b-
1ed63f455e07 

c96f250b-599f-458b-a274-
75d043da6289 

The  average  energy  content  of  biomass 
(18 MJ/kg) was considered to convert the 
result in kg. 
This  dataset  was  used  as  a  proxy  for 
biomass (expressed as mass). 

Wood chips 

Biomass (wood 
chips production) 

Portland cement 

Cement 

Tap water 

Tap water 

Hydrogen 
production 

Electricity - 
hydrogen 

Chips 
production_production 
mix_at 
plant_EU-
28+3_S - 1kg 

plant_EU-

Portland 
cement_production 
mix_at 
28+3_S - 1kg 
Tap  water_technology 
mix_at 
user_EU-
28+3_S - 1kg 
hydrogen - 1kg 

bc7c60d0-2315-424b-a486-
ec312f11e3cb 

The  density  of  water  (0.001  kgH2O/m3) 
was  considered  to  convert  the  result  in 
m3. 

212b8494-a769-4c2e-8d82-
9a6ef61baad7 

- 

10cbb5b5-453b-4492-8ac6-
5ba35a6d2759 

To calculate the kg quantity of H2 needed 
to  generate  1  kWh  of  electricity,  it  was 
considered  the  Lower  Heating  Value 
(LHW) of thermochemical H2 (33 kWh/kg) 
and the processes efficiency (59%). With 
1kg  thermochemical  H2  it  is  possible  to 
generate  19.5  kWh  [category  for  climate 
change 
fuel 
production’]. 
- 

‘Hydrogen 

factor: 

e40d497e-59d6-4e53-ba3e-
d7bcc15b421a 
e40d497e-59d6-4e53-ba3e-
d7bcc15b421a 
ec9ca75e-abdb-4d2e-9e18-
ca1f5709a76d 

23 

- 

- 

The  average  of  these  datasets  was 
considered. 

Electricity - 3.6 MJ 

f84ba014-38d8-49a0-8cdb-3aef6cb7bc5e 

Electricity  from 
PV 
Electricity  from 
biogas 
Electricity  from 
biogas 
Injection 
moulding 

Electricity - 
photovoltaic 
Electricity - biogas 

Electricity - 3.6 MJ 

Electricity - biogas 

Electricity - 3.6 MJ 

Plastic 

Plastic 
(unspecified) - 1kg 

part 

 
 
 
bottle 

PET 
(Transparent) 
Plastic 
(body HDPE8) 
Plastic 
(body PP9) 

can 

can 

Plastic tray 

Diesel  mix  at 
refinery 
Lignite mix 

Electricity  from 
geothermal 

PET bottle, transparent 
- 1kg 
Plastic can, body HDPE 
- 1kg 
Plastic  can,  body  PP  - 
1kg 
Plastic tray (PP) - 1kg 

Diesel 

Diesel - 1kg 

Lignite 

Lignite EU+EFTA - 1kg 

Geothermal 

Electricity - 3.6 MJ 

7d518e67-59cd-4f12-a5af-8f158aa3fa1f 

bc8c10af-6e3b-44a9-925d-
181d1d4f605b 
446b8c18-677a-453e-a905-
360796366951 
c7351530-88fa-47b9-bd46-
a0d2047f8f10 
da248653-790b-44bf-9e43-
d4ae66cafbe1 
299a40cf-678e-49f2-9e5c-b48fffa20492 

4639f269-d45d-4b3b-a848-
d0f046888ac7 

- 

- 

- 

8 High-density polyethylene 
9 Polypropylene 

24 

 
 
 
 
 
 
 
Annex  2  –  Complete  list  of  climate  change  impacts  per  unit  of 
materials and energy considered for the analysis of the projects  

The  below  table  illustrates  the  complete  list  of  climate  change  impacts  per  unit  of 
materials and energy derived from EF datasets considered in the calculations of net 
climate  change  mitigation  potential.  Additional  information  on  the  EF  datasets  is 
reported in Annex 1. 

MATERIAL  AND 
ENERGY 
CATEGORY 

CLIMATE 
CHANGE  IMPACT 
PER  UNIT  OF 
MATERIAL  AND 
ENERGY  

UNIT 
[TON CO2 EQ./UNIT] 

4.57E-01 

ton CO2 eq./MWh 

IN  WHICH 

PROJECTS 
THE 
CLIMATE  CHANGE  IMPACTS  PER 
UNIT  OF  MATERIAL  AND  ENERGY 
THE 
ARE 
USED 
CALCULATION 
CLIMATE 
CHANGE MITIGATION POTENTIAL 
P1; P2; P3; P4; P5; P6; P7; P8; P9 

FOR 

OF 

– 

– 

Electricity  -  grid 
mix 
Electricity 
natural gas 
Natural gas 
Hard coal mix 
Steel 
Fossil fuel 
Electricity 
solid biomass 
Biomass  (wood 
chips 
production) 
Cement 
Tap water 
Electricity 
hydrogen 
Hydrogen 
production 
Electricity 
photovoltaic 
Electricity 
biogas 
Plastic 
Diesel 
Lignite 
Geothermal 

fuel 

- 

- 

- 

5.03E-01 

ton CO2 eq./MWh 

P1; P2; P4; P7 

4.03E-04 
3.70E-01 
2.94E+00 
5.09E-01 
4.73E-02 

ton CO2 eq./m3 
ton CO2 eq./ton 
ton CO2 eq./ton 
ton CO2 eq./ton 
ton CO2 eq./MWh 

P5; P6 
P8 
P4; P5; P6 
P2; P7 
P6; P7 

8.19E-03 

ton CO2 eq./ton 

P4 

8.59E-01 
3.26E-04 
8.98E-02 

ton CO2 eq./ton 
ton CO2 eq./m3 
ton CO2 eq./MWh 

P4; P5; P6 
P3; P4; P5; P6 
P6 

1.75E+00 

ton CO2 eq./ton 

P2 

4.91E-02 

ton CO2 eq./MWh 

P1; P2; P4; P5; P6 

2.46E-01 

ton CO2 eq./MWh 

P2; P6 

2.10E+00 
5.73E-01 
3.33E-02 
6.32E-02 

ton CO2 eq./ton 
ton CO2 eq./ton 
ton CO2 eq./ton 
ton CO2 eq./MWh 

P2 
P5; P6 
P8 
P2 

25 

 
 
 
 
 
 
 
 
 
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26 

 
 
 
 
 
 
 
The present paper suggests an approach enabling the ex-ante 
estimation of lifetime carbon savings from investment projects. 
The assessment is based on the use of the Environmental Footprint 
(EF) method, the EU recommended Life Cycle Assessment (LCA) 
based method to quantify the environmental impacts of products 
and organisations. The suggested approach is applied in a novel 
survey dataset, stemming from the European Green Deal call, and 
aims to perform a plausibility check of the expected climate 
change mitigation potentials of investment projects as reported 
through the survey. For most of the projects assessed there are 
significant differences between the climate change mitigation 
potentials estimated by the methodology proposed in this report 
and the potentials reported via the survey, highlighting the need 
for introducing a systematic approach to assess climate change 
mitigation potentials consistently across different projects. 
Lessons learned from this assessment are reported and 
suggestions are provided on how to design future surveys to 
ensure the relevant data is collected to apply the methodology 
here presented. 

Studies and reports