대기질 예측 시스템 구축 I

Abstract

In order to properly estimate changes in air quality associated to national, regional, urban, and local development plans and to correctly explain the source-receptor relationship as of now, it is required to prepare most updated inputs to air quality modeling assessment or prediction. In current air quality assessment plans, it is not intensively considered to estimate the environmental capacity based on total amounts of aggregated emissions rates for a modeling region of interest. However it is necessary in the near future to assess or calculate environmental capacity to introduce an aggregated regulation on emissions rates for a targeted region in response to a future plan. In addition to predict impacts of secondary air pollutants such as ozone or Particular Matter on local air quality in Preliminary Environmental Review System (PERS) and Environmental Impact Assessment (EIA), it needs to predict three-dimensional meteorological filed of the local area, and, by using its result that, in turn, helps calculate emissions amounts and build a photochemical reaction model to predict their influences on air quality. At this moment the Clean Air Policy Support System (CAPSS; Korea emission inventory, 2001, 2002, 2003 released by the Ministry of Environment) becomes available to apply on the air quality modeling works for the exercise explained above. However, the CAPSS itself can not be used directly as inputs for air quality models. Thus it becomes urgent and important to develop a new tool which allows users to use the emissions inventory for their purposes. In this project, we have developed Korea Environment Institute-Emissions Inventory Preparation System (KEI-EIPS) to generate air quality model-ready emissions data with SMOKE (Sparse Matrix Operator Kernel for Emissions) using the Ministry of Environment’s emissions inventory data, maintained under the Clean Air Policy Support System (CAPSS) database. To utilize the SMOKE system, CAPSS SCCs were linked to US EPA’s SMOKE default SCCs to the best match profiles for the chemical speciation, and the cross-reference tables and profiles for temporal and spatial allocations since it is difficult to develop these internal databases in a short time characterizing all the SCCs used in the CAPSS. After examining emissions amounts for each source type, it is suggested to update internal databases for the top 10 SCCs for area and point sources and top 5 SCCs for on-road mobile sources first to minimize uncertainties during the emissions processing. Characterization on emissions sources should be carried out for a selected modeling region because each region presents different emissions patterns associated with different industrial, residential, and traffic environments.