ICOS Science Conference 2022: Day 2, Session 7

1. Spatial variability of local carbon emissions
and sinks in Helsinki
Minttu Havu1
, Liisa Kulmala2,3
, and Leena Järvi1,4
1Institute for Atmospheric and Earth System Research /Physics, University of Helsinki, Helsinki, Finland.
2Finnish Meteorological Institute, Helsinki, Finland.
3Institute for Atmospheric and Earth System Research /Forest, University of Helsinki, Helsinki, Finland.
4Helsinki Institute of Sustainability Science, University of Helsinki, Helsinki, Finland.
1
14/09/22
Spatial variability of local carbon emissions and sinks in Helsinki

2. Introduction
➢
Several cities have taken actions to strive for
carbon neutrality in the coming decades
➢
Atmospheric observations can be used to
monitor CO2 emissions from cities but they
often do not provide information on sources
➢
Modelling tools are needed to separate the
different CO2 components and assist with the
monitoring of anthropogenic emissions in
cities
ICOS associated ecosystem station FI-Kmp
in Helsinki, Finland
Spatial variability of local carbon emissions and sinks in Helsinki 14/09/22 2

3. Aim
Estimate the spatial variability of different carbon
cycle components
Estimate the magnitude of
biogenic components and human metabolism
compared to local anthropogenic emissions
in the city of Helsinki, Finland
Spatial variability of local carbon emissions and sinks in Helsinki 14/09/22 3
CO2
flux components in urban areas (Oke, 2018)
FCO2
= Net CO2
exchange
C = Combustion from traffic and building heating
P = CO2
uptake by photosynthesis
R = Vegetation and soil respiration
Human metabolism
ΔS = Storage change (not considered)

4. Methods – SUEWS model
➢
Used model is the Surface Urban Energy
and Water balance Scheme
(SUEWS, Järvi et al., 2019)
➢
Simulates surface energy and water
balances and CO2 surface exchange with
meteorological variables and surface
information
Surface types in SUEWS (Sun et al., 2018)
Spatial variability of local carbon emissions and sinks in Helsinki 14/09/22 4
➢
The model is run in Helsinki for year 2019 with hourly
resolution
➢
Modelling domain is divided into 250x250 m2 grids
City of Helsinki (©Kaupunkimittausosasto, 2021)

5. Methods – Human metabolism
In SUEWS, input data needed to simulate
human metabolism are
➢ population density
➢ CO2 release per person
(120-280 umol CO2 s-1 cap-1 Ward et al., 2013,
Moriwaki and Kanda 2004)
➢ population profile for weekdays and
weekends
Population densities and profiles for each
250x250 m2 grids are obtained from a 24-
hour population distribution dataset based on
mobile phone data for Helsinki (Bergroth et
al., 2022) Bergroth et al., 2022
Spatial variability of local carbon emissions and sinks in Helsinki 14/09/22 5

6. The CO2 uptake by photosynthesis is modelled with
canopy conductance model
➢
depends on solar radiation, air temperature,
humidity and soil moisture
Vegetation and soil respiration
➢
depend exponentially on air temperature
In our study, both submodules used the local simulated
2 m air temperatures (Tang et al., 2021)
Vegetation cover is divided into urban forests, street
trees and parks depending on the dominant vegetation
type in each grid
Each vegetation cover having their own parametrisation
Spatial variability of local carbon emissions and sinks in Helsinki 14/09/22 6
Urban
forest
Street
trees
Park
areas
Methods – Biogenic CO2
exchanges

7. Methods – Anthropogenic emissions
Traffic emissions
➢
mean daily traffic rate
➢
Unit emission factor for traffic
Mean traffic rates for each grid obtained
from city of Helsinki database
Spatial variability of local carbon emissions and sinks in Helsinki 14/09/22 7
CO2 emissions from building heating
➢
population density
➢
heating degree days and temperature-related
coefficients
➢
fraction of local heating that causes CO2 emissions
(e.g. wood burning)
➢
emission factor for fuels used in building energy use
In this study, we consider only local emissions, not
single-point sources such as power plants and
industrial activities
In Helsinki, most buildings use district heating, only
38 % of the detached houses use firewood for
heating
Daily traffic rates in Helsinki (©City of Helsinki)

8. CO
2
flux
(umol
m
-2
s
-1
)
SUEWS has been shown to perform well in Helsinki
Evaluated against
➢ Eddy covariance
measurements
(Järvi et al., 2019)
➢ Tree level
measurements
(Havu et al., 2022)
Time (h)
Summer 2012 Kumpula
Summer 2012 Torni
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9. Results – Spatial variability of net CO2
exchange
Cumulative annual sums for different
components for the whole city of
Helsinki in 2019
Total 91.3
kt C year-1
Local
%
Net
%
Photosynthesis -193.1
-30.1 -25 -5
Respiration 163.0
Metabolism 54.3 45 9
Traffic 67.0 55 11
Buildings 0.1 0* 80
Spatial variability of local carbon emissions and sinks in Helsinki 14/09/22 9
*0.08%
Emissions from power plants in Helsinki 470 kt C ekv.

10. Spatial variability of local carbon emissions and sinks in Helsinki 14/09/22 10
Traffic Human metabolism
Building heating Net biogenic CO2
CO2
exchange of different
components
➢
Traffic emissions
concentrated on the ring
road
➢
Building heating emissions
concentrated in residential
areas
➢
Emissions from human
metabolism concentrated in
the city centrum
➢
Net biogenic exchange
strongest in urban forests

11. Results – Spatial variability
How the CO2 emissions from human metabolism and vegetation compare
to the emissions from traffic and building heating
Spatial variability of local carbon emissions and sinks in Helsinki 14/09/22 11
CO2
emissions/sinks from vegetation
compared to anthropogenic emissions
CO2
emissions from human metabolism
compared to anthropogenic emissions

12. Results – Spatial variability
Spatial variability of local carbon emissions and sinks in Helsinki 14/09/22 11
CO2
emissions/sinks from vegetation
compared to anthropogenic emissions
CO2
emissions from human metabolism
compared to anthropogenic emissions
How the CO2 emissions from human metabolism and vegetation compare
to the emissions from traffic and building heating

13. Conclusions
➢
The spatial variability of different carbon cycle components were
estimated with SUEWS in the city of Helsinki
➢ The CO2 emissions from human metabolism were 45 % of the local
anthropogenic emissions
➢ The net biogenic CO2 exchange was 25 % compared to the local
anthropogenic emissions
Spatial variability of local carbon emissions and sinks in Helsinki 14/09/22 12

14. Thank you!
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Spatial variability of local carbon emissions and sinks in Helsinki
Bergroth, Claudia, et al. "A 24-hour population distribution dataset based on mobile phone data from Helsinki Metropolitan Area, Finland." Scientific data 9.1 (2022):
1-19.
Havu, Minttu, et al. "Carbon sequestration potential of street tree plantings in Helsinki." Biogeosciences 19.8 (2022): 2121-2143.
Järvi, Leena, et al. "Spatial modeling of local-scale biogenic and anthropogenic carbon dioxide emissions in Helsinki." Journal of Geophysical Research:
Atmospheres 124.15 (2019): 8363-8384.
Moriwaki, R., and M. Kanda. "Seasonal and diurnal fluxes of radiation, heat, water vapor, and carbon dioxide over a suburban area." Journal of Applied Meteorology
43.11 (2004): 1700-1710.
Tang, Yihao, et al. "Urban meteorological forcing data for building energy simulations." Building and Environment 204 (2021): 108088.
Ward, H. C., Jonathan G. Evans, and Christine Susan B. Grimmond. "Multi-season eddy covariance observations of energy, water and carbon fluxes over a
suburban area in Swindon, UK." Atmospheric Chemistry and Physics 13.9 (2013): 4645-4666.
Contact: minttu.havu@helsinki.fi