资源环境科技发展态势分析平台

The study proposes an approach to quantify necessary emission reductions of various related pollutants to meet national PM2.5 air quality standard (AQS). Many scenarios of emission reductions are simulated to establish the relationships between the reduction ratios of air pollutants and improvements of atmospheric PM2.5 concentration for specific air basins in Taiwan. The air pollutants include primary PM2.5 and secondary PM2.5 precursor species, such as nitrogen oxides (NOx), sulfur oxides (SOX), volatile organic compounds (VOCs), and ammonia (NH3). These relationships were used to estimate the required amounts of emission reduction for various pollutants to achieve the national PM2.5 AQS of annual average with 15 mu g m(-3). Three air basins of KPAB, YCNAB and CTAB with severe PM2.5 pollution in Taiwan were selected as case studies. The results follow: (1) The primary PM2.5 emission reductions and the PM2.5 concentration improvements exhibit linear relationships, and its effects are relatively significant. (2) Among the secondary PM2.5 precursor species, emission reductions of NOx and NH3 will have greater effectiveness, but higher proportions (>50%) of emission reductions are needed. (3) In terms of mitigating PM2.5 pollution, the priorities for pollutant emission control should be in the order of primary PM2.5, NOx, and SOx, while NMHC and NH3 should not currently be a focus. (4) If three air basins of KPAB, YCNAB and CTAB with high PM2.5 levels are required to meet the AQS, it is necessary to reduce primary PM2.5, NOx and SO, emissions simultaneously in case that LRT effect remains constant. Under the premise of meeting the AQS for the three air basins, the reduction of primary PM2.5, NOx and SOx emission in Taiwan should be up to 76%, 93% and 20% respectively. Fortunately, many efforts have been and will be done to improve the PM2.5 concentration in China. Those efforts will mitigate significantly the loading of emission reduction and AQS should be more possible to achieve for all air basins in Taiwan. (C) 2017 Elsevier B.V. All rights reserved.