期刊
ATMOSPHERIC ENVIRONMENT
卷 181, 期 -, 页码 20-33出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.atmosenv.2018.03.013
关键词
High-resolution emission inventory; Multi-level source category; Primary air pollutants; Multi-parameter regression equations; Emission intensity
资金
- Trail Special Program of Research on the Cause and Control Technology of Air Pollution under the National Key Research and Development Plan of China [2016YFC0201501]
- National Natural Science Foundation of China [21777008, 21377012, 21177012]
- National Science and Technology Support Program of the Ministry of Science and Technology of China [2014BAC23B02, 2014BAC06B05]
A high resolution regional emission inventory of typical primary air pollutants (PAPs) for the year 2012 in Beijing and the surrounding five provinces (BSFP) of North China is developed. It is compiled with the combination of bottom-up and top-down methods, based on city-level collected activity data and the latest updated specific emission factors for different sources. The considered sources are classified into 12 major categories and totally 36 subcategories with respect to their multi-dimensional characteristics, such as economic sector, combustion facility or industrial process, installed air pollution control devices, etc. Power plant sector is the dominant contributor of NOX emissions with an average contribution of 34.1%, while VOCs emissions are largely emitted from industrial process sources (33.9%). Whereas, other stationary combustion sources represent major sources of primary PM2.5, PM10 and BC emissions, accounting for 22.7%, 30.0% and 33.9% of the total emissions, respectively. Hebei province contributes over 34% of the regional total CO emissions because of huge volume of iron and steel production. By comparison, Shandong province ranks as the biggest contributor for NOX, PM10, PM2.5, SO2, VOCs and OC. Further, the BSFP regional total emissions are spatially distributed into grid cells with a high resolution of 9 km x 9 km using GIS tools and surrogate indexes, such regional population, gross domestic product (GDP) and the types of arable soils. The highest emission intensities are mainly located in Beijing-Tianjin-Tangshan area, Jinan-Laiwu-Zibo area and several other cities such as Shijiazhuang, Handan, and Zhengzhou. Furthermore, in order to establish a simple method to estimate and forecast PAPs emissions with macroscopic provincial-level statistical parameters in China, multi-parameter regression equations are firstly developed to estimate emissions outside the BSFP region with routine statistics (e.g. population, total final coal consumption, area of cultivated land and possession of civil vehicles) using the software 1stOpt. We find the estimated PAPs emissions of 31 provinces show close correlation with the well-recognized MEIC inventory. This high resolution multi-pollutants inventory provides necessary input data for regional air quality models that could help to identify and appoint the major influence sources, better understand the complex regional air pollution formation mechanism, and benefit for developing the corresponding joint prevention and control policies of regional complex air pollution in North China.
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