Emission estimates on anational scale - experiencesof Nordic countries
IPCC Expert meeting on Short-Lived Climate Forcers
Geneva 28 May 2018
Karin Kindbom

Outline of the presentation
Project framework

Important sources of BC and PM2.5
Residential wood combustion– Emission factors and emission measurements– Activity data – collection of data

Nordic SLCP project: Improved emission
inventories of Short-Lived Climate Pollutants
2013-2015: Background analysis and identification of knowledge gaps
(TN2015:523)

2015-2017: Emission factors for SLCP emissions from residential wood
combustion in the Nordic countries (TN2017:570).
2016-2018: Potentials for reducing the health and climate impacts ofresidential biomass combustion in the Nordic countries (TN2018:530)

2017-2018: Measures to reduce emissions of Short-Lived Climate
Pollutants (SLCP) in the Nordic countries (TN2018:533)– Karin Kindbom, Tina Skårman, Erik Fridell, Ingrid Mawdsley, Sweden– Ole-Kenneth Nielsen, Morten Winther, Denmark– Kristina Saarinen, Maija Lappi, Heikki Lamberg, Finland– Kári Jónsson, Páll Valdimar Kolka Jónsson, Iceland– Kristin Aasestad, NorwayNordic emission inventories and projections
Residential wood combustion is a major source of PM2.5 and BC in
the Nordic countries (Denmark, Finland, Norway, Sweden)
Depending on country, emission estimates include more or lessuncertainty, need for better knowledge
25140

PM2.5

Agriculture, waste,
product use

BC120
20

100
80

60

Residential combustion(+agr, forestry, fishing))
Off-road transport

Emissions of BC (Gg)

Emissions of PM2.5 (Gg)Industrial Processes

151040Road Transport
2002005 2010 2015 2020 2025 2030

Energyproduction+combustion
in industry+fugitive em

502005 2010 2015 2020 2025 2030

Factors influencing estimated emissions fromresidential wood burning
Emission factors
Emission measurement method for deriving emission factors
Combustion technology, e.g. older or modern
Operation and handling, ”bad firing habits” gives higher emissions

Fuel quality, e.g. moisture. Influences combustion efficiency andemission level
Activity data

Fuel amount used /combustion technology
Share of fuel combusted under ”bad combustion conditions”

Measurement program: Emission factors
Residential wood combustion
Residential biomass appliances representative for the Nordic countries
EC, OC, PM2.5, CH4, NMVOC
Test methods (operational conditions and firing schemes):– Boilers: EN standard 303-5– Room heaters/stoves: EN 16510 series– Norwegian standard NS 3058

Sampling: Dilution tunnel
Additional test cases to simulate ”bad combustion behaviour”– Part load, high load, moist fuel, dry fuelTechnologies grouped for emission factors to be useful in inventories

The boiler population
P1 Inverse combustion and λ-probe
ModernP2 Inverse combustion and flue gas fan
P3 Inverse combustion and flue gas fan
P4 Inverse combustion and natural draught

Old

P5 "Simple" boiler
P6 Old combination boiler (oil+wood)
P7 Traditional pellet burner in an oil or combination boilerPellets

P8 Advanced pellets burner in boiler designed for pellet firing
P9 Pellet boiler with integrated grate burner
P10 Wood chip boiler

A1 Simple

A4 Cast iron stove

A2 Modern

A3 State-of-the-art
A9 Sauna

A5 Tiled stove

A8 Pellets
A6 Slow heat releaseResults from measurement program
Older technologies generally higher emission levels than modern”Bad combustion” can increase emission levels significantly
Important to take ”bad combustion” into account in the nationalemission factors

EC
EC and PM2.5 do not correlate (no ”fixed” share EC/PM2.5)
EC least affected by ”bad combustion conditions”

Technology important!

Pellets

Old

ModernEmission factors from measurements:
Individual boilers, standard conditions

Firing habits important!
Emission factors from measurements:
Technology groups stoves, different combustion conditions

Blue=standard conditions
Red=moist fuelGreen=part load

SLW=standard fuelMLW=moist fuelPart=part load

Emissionfactors
technology
groups:STOVES

NominalN:Sload:
minStandard fuelModern stoves(incl state-of-the-art)

PM2.5 (mg/MJ)
EC (mg/MJ)
OC (mg/MJ)
CH4 (mg/MJ)
NMVOC (mg/MJ)
Older stove*

Ratio moist
fuel tostandard
fuel
N:M/N:S

Ratio part
load tonominal
load
P:S/N:S

5.0
1.0
8.0
2.0
5.0

2.0
1.0
2.5
1.5
2.0(8)
84
20
2490
76

60
3631
19

106
42
39
153
144

(1)

PM2.5 (mg/MJ)

147

2.5

EC (mg/MJ)

13

1.0

OC (mg/MJ)

47

3.5

CH4 (mg/MJ)

49

3.0

NMVOC (mg/MJ)

132

2.5

Tiled and masonry stovePM2.5 (mg/MJ)
EC (mg/MJ)
OC (mg/MJ)
CH4 (mg/MJ)
NMVOC (mg/MJ)
Pellet stove*

N:S =Nominal load:Standard fuel
N:M =Nominal load:Moist fuel
P:S =Part load:Standard fuel

N:Smax

(2)
140
72
51
114
181

82
223161
133

198
122
70
167
229

1.0
1.0
1.0
1.0
1.0

2.0
1.5
2.0
2.0
1.0(1)

PM2.5 (mg/MJ)

100

1.5

EC (mg/MJ)

10

1.0

OC (mg/MJ)

6

1.0

CH4 (mg/MJ)

12.5

NMVOC (mg/MJ)

43.5

Sauna stove*
PM2.5 (mg/MJ)
EC (mg/MJ)
OC (mg/MJ)
CH4 (mg/MJ)
NMVOC (mg/MJ)

(1)
104
52
15
43

1.5
1.0
2.0
2.0

85

2.0

”Bad combustion” in emission factors
Emissions = AD * EF
– AD = fuel use in the specific technology or technology group (MJ)

– EF = emission factor for a pollutant (mg/MJ)

To take bad combustion conditions into account in the emission
factor (EF), the following equation can be used (Savolahti et al.,2016):
EF = EFNormal * SNormal + RatioBad/Good * EFNormal * SBad
– S = share of fuel used– Ratio = factor for bad combustion

Savolahti M., Karvosenoja N., Tissari J., Kupiainen K., Sippula O. & Jokiniemi J. (2016).
Atmospheric Environment 140 (2016) 495–505. https://doi.org/10.1016/j.atmosenv.2016.06.023

Activity data:
Residential wood combustion
Combustion technologies
Fuel consumption (type and amount for each technology)
User behaviour (share of ”bad combustion”)

Current activity data collection in
Sweden, Denmark and Finland (1)Combustion technology:– Regular or intermittent surveys/questionnaires, sometimes incombination with modelling based on expected lifetimes of equipment.
– Depending on country, rather good understanding of present
technologies, OR difficult to get good enough data, low response rates insurveys, questions not detailed enough/do not cover all informationneeded.

Fuel consumption:– Regular surveys– Sometimes low response rates. Depending on country assignment of fuelto technology based on studies OR not yet done (assumptions).
– Solid data requires surveys potentially coupled with energy demandmodelling.

Current activity data collection in
Sweden, Denmark and Finland (2)User behaviour:– Emission factors for “bad combustion” based on measurement data
– Share of “bad combustion” estimated based on expert judgement,dedicated studies, interviews with chimney sweepers etc.
– OR no assumptions made regarding user behaviour, the default EFs
from EMEP/EEA Guidebook assumed to be representative average.

Activity data in Nordic inventories
Denmark, 10 technology types. New
stoves and pellet boilers/stoves use
the largest quantities of biomass fuel.

Finland, 13 technology types. Biomass
fuel use is more evenly distributed on
several technologies.
Norway, 3 technology types.
Approximately equal amounts ofbiomass used in old and newtechnology stoves.
Sweden, 5 technology types.
Wood boilers >50% of biomass
fuel use.

Blue=biomass fuelRed= PM2.5 emissions

Conclusions residential wood combustion
Emission inventories of residential wood combustion sensitive to user
behaviour and combustion technology
Measurement program has provided SLCP and PM2.5 emission factors
for several types of residential wood combustion technologies
representative for the Nordic countries
User behaviour – important to take into accountEC (BC) least affected by behaviour
EC and PM2.5 do not correlate

Activity data collection challenging - need to combine information fromdifferent sources, and make assumptions

Thank you for your attention!
karin.kindbom@ivl.seEmission measurement methods influences emission
factors for particulate matter (PM)Sampling– In hot flue gases– In diluted flue gases at lower temperature

Semivolatile organic compounds created in inefficient combustion (forexample at poor user practices)– Exist in gas phase in hot flue gas measurements, not as PM– Partly condensed as additional PM in diluted sampling (lower temperatures)

Measurement methods thus give different results regarding amount ofPM
Reported differences in the order of 2-10 times

Emission
factors
technology
groups:BOILERS

Nominal load:
Standard fuel
(N:S)
Modern log wood boilers

N:SmaxRatio moist
fuel tostandard fuel
N:M/N:S

Ratio part
load tonominal load
P:S/N:S(6)

PM2.5 (mg/MJ)

35

2445

1.5

EC (mg/MJ)

6

215

1.0

OC (mg/MJ)

15

1019

1.0

CH4 (mg/MJ)

15432

1.5

NMVOC (mg/MJ)

85

32141

1.5

320
25120
75
470

317
1996
47462

320
27138
103
477

1.5>1.5>1.5>1.5>1.5PM2.5 (mg/MJ)

3515573.0

EC (mg/MJ)

6114

1.5

OC (mg/MJ)

106113.5

CH4 (mg/MJ)

2145.0NMVOC (mg/MJ)

159226.0

Traditional log wood boilers(2)

PM2.5 (mg/MJ)
EC (mg/MJ)
OC (mg/MJ)
CH4 (mg/MJ)
NMVOC (mg/MJ)
Pellet-fired boilers

N:S =Nominal load:Standard fuel
N:M =Nominal load:Moist fuel
P:S =Part load:Standard fuel

N:SminWood chip boiler*
PM2.5 (mg/MJ)
EC (mg/MJ)
OC (mg/MJ)
CH4 (mg/MJ)
NMVOC (mg/MJ)

4.0
1.0>4.0
>3.0
>3.0

(3)

(1)
50
220
550

1.5
5.0
1.5
3.0
2.0

5.0
6.0
5.0
15.0
15.0