The Comprehensive Automobile Research System (CARS) – a Python-based automobile emissions inventory model
<p>The Comprehensive Automobile Research System (CARS) is an open-source Python-based automobile emissions inventory model designed to efficiently estimate high-quality emissions from motor vehicle emission sources. It can estimate air pollutant, greenhouse gas, and air toxin criteria at any s...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2022-06-01
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| Series: | Geoscientific Model Development |
| Online Access: | https://gmd.copernicus.org/articles/15/4757/2022/gmd-15-4757-2022.pdf |
| _version_ | 1811342462307794944 |
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| author | B. H. Baek R. Pedruzzi M. Park C.-T. Wang Y. Kim C.-H. Song J.-H. Woo J.-H. Woo |
| author_facet | B. H. Baek R. Pedruzzi M. Park C.-T. Wang Y. Kim C.-H. Song J.-H. Woo J.-H. Woo |
| author_sort | B. H. Baek |
| collection | DOAJ |
| description | <p>The Comprehensive Automobile Research System (CARS) is an open-source
Python-based automobile emissions inventory model designed to efficiently
estimate high-quality emissions from motor vehicle emission sources. It can
estimate air pollutant, greenhouse gas, and air toxin criteria at
any spatial resolution based on the spatiotemporal resolutions of input
datasets. The CARS is designed to utilize local vehicle activity data, such
as vehicle travel distance, road-link-level network geographic information
system (GIS) information, and vehicle-specific average speed by road type,
to generate an automobile emissions inventory for policymakers,
stakeholders, and the air quality modeling community. The CARS model adopted
the European Environment Agency's on-road automobile emissions
calculation methodologies to estimate the hot exhaust, cold start, and
evaporative emissions from on-road automobile sources. It can optionally
utilize average speed distribution (ASD) of all road types to reflect more
realistic vehicle speed variations. In addition, through utilizing high-resolution
road GIS data, the CARS can estimate the road-link-level emissions to
improve the inventory's spatial resolution. When we compared the official
2015 national mobile emissions from Korea's Clean Air Policy Support System
(CAPSS) against the ones estimated by the CARS, there is a significant
increase in volatile organic compounds (VOCs) (33 %) and carbon monoxide
(CO) (52 %) measured, with a slight increase in fine particulate matter
(PM<span class="inline-formula"><sub>2.5</sub></span>) (15 %) emissions. Nitrogen oxide (NO<span class="inline-formula"><sub><i>x</i></sub></span>) and sulfur oxide
(SO<span class="inline-formula"><sub><i>x</i></sub></span>) measurements are reduced by 24 % and 17 %, respectively, in the CARS
estimates. The main differences are driven by different vehicle activities
and the incorporation of road-specific ASD, which plays a critical role in
hot exhaust emission estimates but was not implemented in Korea's CAPSS
mobile emissions inventory. While 52 % of vehicles use gasoline fuel and
35 % use diesel, gasoline vehicles only contribute 7.7 % of total NO<span class="inline-formula"><sub><i>x</i></sub></span>
emissions, whereas diesel vehicles contribute 85.3 %. However, for VOC emissions,
gasoline vehicles contribute 52.1 %, whereas diesel vehicles are limited to
23 %. Diesel buses comprise only 0.3 % of vehicles and have the
largest contribution to NO<span class="inline-formula"><sub><i>x</i></sub></span> emissions (8.51 % of NO<span class="inline-formula"><sub><i>x</i></sub></span> total) per
vehicle due to having longest daily vehicle kilometer travel (VKT). For VOC
emissions, compressed natural gas (CNG) buses are the largest contributor at
19.5 % of total VOC emissions. For primary PM<span class="inline-formula"><sub>2.5</sub></span>, more than 98.5 %
is from diesel vehicles. The CARS model's in-depth analysis feature can
assist government policymakers and stakeholders in developing the best
emission abatement strategies.</p> |
| first_indexed | 2024-04-13T19:11:26Z |
| format | Article |
| id | doaj.art-aa0d1fc40138415b98089d7a8178dff4 |
| institution | Directory Open Access Journal |
| issn | 1991-959X 1991-9603 |
| language | English |
| last_indexed | 2024-04-13T19:11:26Z |
| publishDate | 2022-06-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | Geoscientific Model Development |
| spelling | doaj.art-aa0d1fc40138415b98089d7a8178dff42022-12-22T02:33:50ZengCopernicus PublicationsGeoscientific Model Development1991-959X1991-96032022-06-01154757478110.5194/gmd-15-4757-2022The Comprehensive Automobile Research System (CARS) – a Python-based automobile emissions inventory modelB. H. Baek0R. Pedruzzi1M. Park2C.-T. Wang3Y. Kim4C.-H. Song5J.-H. Woo6J.-H. Woo7Center for Spatial Information Science and Systems, George Mason University, Fairfax, VA, USADepartment of Sanitary and Environmental Engineering, Federal University of Minas Gerais, Belo Horizonte, BrazilDepartment of Technology Fusion Engineering, College of Engineering, Konkuk University, Seoul, Republic of KoreaCenter for Spatial Information Science and Systems, George Mason University, Fairfax, VA, USAEnergy, Climate, and Environment Program, International Institute for Applied Systems Analysis, Laxenburg, AustriaSchool of Earth and Environmental Engineering, Gwangju Institute Science and Technology, Gwangju, Republic of KoreaDepartment of Technology Fusion Engineering, College of Engineering, Konkuk University, Seoul, Republic of KoreaCivil and Environmental Engineering, College of Engineering, Konkuk University, Seoul, Republic of Korea<p>The Comprehensive Automobile Research System (CARS) is an open-source Python-based automobile emissions inventory model designed to efficiently estimate high-quality emissions from motor vehicle emission sources. It can estimate air pollutant, greenhouse gas, and air toxin criteria at any spatial resolution based on the spatiotemporal resolutions of input datasets. The CARS is designed to utilize local vehicle activity data, such as vehicle travel distance, road-link-level network geographic information system (GIS) information, and vehicle-specific average speed by road type, to generate an automobile emissions inventory for policymakers, stakeholders, and the air quality modeling community. The CARS model adopted the European Environment Agency's on-road automobile emissions calculation methodologies to estimate the hot exhaust, cold start, and evaporative emissions from on-road automobile sources. It can optionally utilize average speed distribution (ASD) of all road types to reflect more realistic vehicle speed variations. In addition, through utilizing high-resolution road GIS data, the CARS can estimate the road-link-level emissions to improve the inventory's spatial resolution. When we compared the official 2015 national mobile emissions from Korea's Clean Air Policy Support System (CAPSS) against the ones estimated by the CARS, there is a significant increase in volatile organic compounds (VOCs) (33 %) and carbon monoxide (CO) (52 %) measured, with a slight increase in fine particulate matter (PM<span class="inline-formula"><sub>2.5</sub></span>) (15 %) emissions. Nitrogen oxide (NO<span class="inline-formula"><sub><i>x</i></sub></span>) and sulfur oxide (SO<span class="inline-formula"><sub><i>x</i></sub></span>) measurements are reduced by 24 % and 17 %, respectively, in the CARS estimates. The main differences are driven by different vehicle activities and the incorporation of road-specific ASD, which plays a critical role in hot exhaust emission estimates but was not implemented in Korea's CAPSS mobile emissions inventory. While 52 % of vehicles use gasoline fuel and 35 % use diesel, gasoline vehicles only contribute 7.7 % of total NO<span class="inline-formula"><sub><i>x</i></sub></span> emissions, whereas diesel vehicles contribute 85.3 %. However, for VOC emissions, gasoline vehicles contribute 52.1 %, whereas diesel vehicles are limited to 23 %. Diesel buses comprise only 0.3 % of vehicles and have the largest contribution to NO<span class="inline-formula"><sub><i>x</i></sub></span> emissions (8.51 % of NO<span class="inline-formula"><sub><i>x</i></sub></span> total) per vehicle due to having longest daily vehicle kilometer travel (VKT). For VOC emissions, compressed natural gas (CNG) buses are the largest contributor at 19.5 % of total VOC emissions. For primary PM<span class="inline-formula"><sub>2.5</sub></span>, more than 98.5 % is from diesel vehicles. The CARS model's in-depth analysis feature can assist government policymakers and stakeholders in developing the best emission abatement strategies.</p>https://gmd.copernicus.org/articles/15/4757/2022/gmd-15-4757-2022.pdf |
| spellingShingle | B. H. Baek R. Pedruzzi M. Park C.-T. Wang Y. Kim C.-H. Song J.-H. Woo J.-H. Woo The Comprehensive Automobile Research System (CARS) – a Python-based automobile emissions inventory model Geoscientific Model Development |
| title | The Comprehensive Automobile Research System (CARS) – a Python-based automobile emissions inventory model |
| title_full | The Comprehensive Automobile Research System (CARS) – a Python-based automobile emissions inventory model |
| title_fullStr | The Comprehensive Automobile Research System (CARS) – a Python-based automobile emissions inventory model |
| title_full_unstemmed | The Comprehensive Automobile Research System (CARS) – a Python-based automobile emissions inventory model |
| title_short | The Comprehensive Automobile Research System (CARS) – a Python-based automobile emissions inventory model |
| title_sort | comprehensive automobile research system cars a python based automobile emissions inventory model |
| url | https://gmd.copernicus.org/articles/15/4757/2022/gmd-15-4757-2022.pdf |
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