Mapping CO2 traffic emissions within local climate zones in Helsinki
被引:2
|
作者:
Al-Jaghbeer, Omar
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h-index: 0
机构:
Univ Helsinki, Inst Atmospher & Earth Syst Res Phys, Fac Sci, Helsinki 00014, FinlandUniv Helsinki, Inst Atmospher & Earth Syst Res Phys, Fac Sci, Helsinki 00014, Finland
Al-Jaghbeer, Omar
[1
]
Fung, Pak Lun
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h-index: 0
机构:
Univ Helsinki, Inst Atmospher & Earth Syst Res Phys, Fac Sci, Helsinki 00014, Finland
Univ Helsinki, Helsinki Inst Sustainabil Sci HELSUS, Fac Sci, Helsinki 00014, FinlandUniv Helsinki, Inst Atmospher & Earth Syst Res Phys, Fac Sci, Helsinki 00014, Finland
Fung, Pak Lun
[1
,2
]
Paunu, Ville-Veikko
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h-index: 0
机构:
Finnish Environm Inst Syke, FI-00790 Helsinki, FinlandUniv Helsinki, Inst Atmospher & Earth Syst Res Phys, Fac Sci, Helsinki 00014, Finland
Paunu, Ville-Veikko
[3
]
Jarvia, Leena
论文数: 0引用数: 0
h-index: 0
机构:
Univ Helsinki, Inst Atmospher & Earth Syst Res Phys, Fac Sci, Helsinki 00014, Finland
Univ Helsinki, Helsinki Inst Sustainabil Sci HELSUS, Fac Sci, Helsinki 00014, FinlandUniv Helsinki, Inst Atmospher & Earth Syst Res Phys, Fac Sci, Helsinki 00014, Finland
Jarvia, Leena
[1
,2
]
机构:
[1] Univ Helsinki, Inst Atmospher & Earth Syst Res Phys, Fac Sci, Helsinki 00014, Finland
[2] Univ Helsinki, Helsinki Inst Sustainabil Sci HELSUS, Fac Sci, Helsinki 00014, Finland
[3] Finnish Environm Inst Syke, FI-00790 Helsinki, Finland
Carbon dioxide;
Local climate zone;
Traffic emission;
Land use regression model;
Urban form;
Look-up table;
MODELING APPROACH;
URBAN;
TRANSPORT;
ROADS;
D O I:
10.1016/j.uclim.2024.102171
中图分类号:
X [环境科学、安全科学];
学科分类号:
08 ;
0830 ;
摘要:
Road traffic is one of the major emitters of carbon dioxide (CO2) to the atmosphere. Besides detailed carbon emission calculations, methods to upscale the emissions are needed, particularly in areas where good-quality data to calculate CO2 emissions are lacking. To support this need, this study aims to quantify traffic-related CO2 emissions within Local Climate Zones (LCZs) in Helsinki, Finland, and build a regression-based look-up table for the CO2 emissions. To build the model, we use CO2 emission data together with the variables, namely building surface area, asphalt surface area, population, traffic light, and road type. The median CO2 emissions from the built LCZs are 1.8 times higher than those from land cover LCZs. The original classification of the LCZ framework is insufficient to describe traffic CO2 emissions. The most critical variables in describing traffic CO2 emissions are road type and asphalt area. We then build a generalized model applicable across LCZs, which can describe on average 55 % of the emissions. Based on the model, we introduce a look-up table for LCZ-specific traffic CO2 emissions. This look-up table offers a practical solution for locations with limited resources to estimate traffic emissions. Crucially, this approach circumvents the need for traffic data, and minimizes computational resource requirements.