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Allocating Anthropogenic Pollutant Emissions Over Space: Application to Ozone Pollution Management | CLIMAS

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Allocating Anthropogenic Pollutant Emissions Over Space: Application to Ozone Pollution Management

TitleAllocating Anthropogenic Pollutant Emissions Over Space: Application to Ozone Pollution Management
Publication TypeArticles
Year of Publication2002
AuthorsDiem, J, Comrie, A
JournalJournal of Environmental Management
Volume63
Pagination425-447
Abstract

An inventory of volatile organic compound (VOC) and nitrogen oxides (NOx) emissions is an important tool for the management of ground-level ozone pollution. This paper has two broad aims: it illustrates the potential of a geographic information system (GIS) for enhancing an existing spatially-aggregated, anthropogenic emissions inventory (EI) for Tucson, AZ, and it discusses the ozone-specific management implications of the resulting spatially-disaggregated EI. The main GIS-related methods include calculating emissions for specific features, spatially disaggregating region-wide emissions totals for area sources, and adding emissions from various point sources. In addition, temporal allocation factors enable the addition of a multi-temporal component to the inventory. The resulting inventory reveals that on-road motor vehicles account for approximately 50% of VOC and NOxemissions annually. On-road motor vehicles and residential wood combustion are the largest VOC sources in the summer and winter months, respectively. On-road motor vehicles are always the largest NOxsources. The most noticeable weekday vs. weekend VOC emissions differences are triggered by increased residential wood combustion and increased lawn and garden equipment use on weekends. Concerning the EI’s uncertainties and errors, on-road mobile, construction equipment, and lawn and garden equipment are identified as sources in the most need of further investigation. Overall, the EIs spatial component increases its utility as a management tool, which might involve visualization-driven analyses and air quality modeling.