The Comprehensive Automobile Research System (CARS) – a Python-based automobile emissions inventory model

• Published in: Geoscientific Model Development Vol. 15; no. 12; pp. 4757 - 4781
• Main Authors: Baek, Bok H, Pedruzzi, Rizzieri, Park, Minwoo, Wang, Chi-Tsan, Kim, Younha, Song, Chul-Han, Woo, Jung-Hun
• Format: Journal Article
• Language: English
• Published: Katlenburg-Lindau Copernicus GmbH 21.06.2022; Copernicus Publications
• Subjects: Air; Air pollution; Air quality; Air quality models; Automobiles; Automotive emissions; Buses; Buses (vehicles); Carbon monoxide; Cold starts; Combustion products; Compressed gas; Datasets; Depth perception; Diesel; Diesel engines; Diesel fuels; Emission inventories; Emissions; Estimates; Exhaust emission; Gasoline; Geographic information systems; Geographical information systems; Geography; Greenhouse gases; Information systems; Inventory control; Mathematical models; Modelling; Motor vehicles; Natural gas; Nitrogen compounds; Nitrogen oxide; Nitrogen oxides; Organic compounds; Particulate emissions; Particulate matter; Particulate matter emissions; Photochemicals; Pollutants; Remote sensing; Resolution; Roads; Spatial discrimination; Spatial resolution; Sulfur; Sulfur oxides; Sulphur; Support systems; Suspended particulate matter; Toxins; Traffic speed; Travel; User needs; Vehicle emissions; Vehicles; Velocity; VOCs; Volatile organic compounds; United States > US; South Korea
• DOI: 10.5194/gmd-15-4757-2022
• ISSN: 1991-9603; 1991-959X; 1991-962X

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 (PM2.5) (15 %) emissions. Nitrogen oxide (NOx) and sulfur oxide (SOx) 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 NOx 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 NOx emissions (8.51 % of NOx 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 PM2.5, 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.