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首页> 外文期刊>Environmental Pollution >Anthropogenic emission inventory of multiple air pollutants and their spatiotemporal variations in 2017 for the Shandong Province, China
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Anthropogenic emission inventory of multiple air pollutants and their spatiotemporal variations in 2017 for the Shandong Province, China

机译：中国山东省山东省多次空气污染物的人为排放清单及其2017年的时空变化

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摘要

Shandong is the most populous and highly industrialized province in eastern China, and the resultant poor air quality is a cause for widespread concern. This study combines bottom-up and top-down approaches to develop a high-resolution anthropogenic emission inventory of air pollutants for 2017. The inventory was developed based on updated emission factors and detailed activity data. The emissions of sulfur dioxide (SO2), nitrogen oxides (NOx), particulate matter with aerodynamic diameters smaller than 2.5 and 10 mu m (PM2.5 and PM10, respectively), carbon monoxide (CO), volatile organic compounds (VOCs), and ammonia (NH3) were estimated to be 1387.8, 2488.6, 5281.7, 3193.0, 9250.7, 2254.7, and 1210.6 kt, respectively. Power plants were the largest contributors of SO2 and NOx emissions accounting for 43.7% and 41.9% of the total emissions, respectively. CO emissions mainly originated from industrial processes (40.1%), mobile sources (24.8%), and fossil fuel burning (21.2%). The major sources of PM10 and PM2.5 emissions were industrial processes and fugitive dust, contributing 83.0% and 86.9% of their total emissions, respectively. Industrial processes (60.0%) contributed the largest VOC emissions, followed by mobile sources (16.8%) and solvent use (14.5%). Livestock and N-fertilizers were major emitters of NH3, accounting for 69.9% and 21.2% of the total emissions, respectively. Emissions were spatially allocated to grid cells with a resolution of 0.05 degrees x 0.05 degrees based on spatial surrogates, using Geographic Information System (GIS). Heavy pollutant emissions were mainly concentrated in the central and eastern areas of Shandong, while high NH3-emissions occurred in the western region. Most pollutant emissions from industrial sectors occurred in June and July, while low emissions were recorded between January and February. Range uncertainties in emission inventory were quantified using Monte Carlo simulations. Our inventory provides effective information to understand local pollutant emission characteristics, perform air quality simulations, and formulate pollution control measures.
机译：山东是中国东部人口最多，高度工业化的省份，并将得到的空气质量差是普遍关注的一个原因。这种自下而上和自上而下的研究方法联合制定空气污染物的高分辨率人为排放清单2017年库存的​​基础上更新的排放因子和详细的活动数据发展。二氧化硫（SO 2）（NOx）的排放量，氮氧化物，具有空气动力学直径小于2.5和10微米的颗粒物M（PM2.5和PM10，分别地），一氧化碳（CO），挥发性有机化合物（VOC），和氨（NH3）被估计为1387.8，2488.6，5281.7，3193.0，9250.7，2254.7，和1210.6克拉，分别。电厂是二氧化硫和氮氧化物排放量的最大贡献者分别占43.7％和总排放量的41.9％。 CO排放主要来源于工业过程（40.1％），移动源（24.8％），和化石燃料燃烧（21.2％）。 PM10和PM2.5排放的主要来源是工业过程和扬尘，分别贡献83.0％和它们的总排放量的86.9％。工业过程（60.0％）贡献最大VOC排放，接着移动源（16.8％）和溶剂的使用（14.5％）。家畜和N-肥料是NH 3的主要排放，占69.9％和总排放量的21.2％，分别。排放量在空间上分配给网格单元具有0.05度的分辨率X 0.05度基于空间的替代物，使用地理信息系统（GIS）。重污染物排放主要集中在山东省的中部和东部地区，而高NH3排放发生在西部地区。从工业部门的大多数污染物的排放发生在六月和七月，而低排放量一月和二月间记录。在排放清单的不确定性范围内使用Monte Carlo模拟定量。我们的库存提供了有效信息，以了解当地的污染物排放的特点，进行空气质量模拟，制定污染控制措施。

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  • 来源
    《Environmental Pollution》 |2021年第11期|117666.1-117666.10|共10页
  • 作者

    Zhou Mimi; Jiang Wei; Gao Weidong; Gao Xiaomei; Ma Mingchun; Ma Xiao;

  • 作者单位

    Jinan Univ Sch Water Conservancy & Environm Jinan 250022 Peoples R China;

    Jinan Univ Sch Water Conservancy & Environm Jinan 250022 Peoples R China|Shandong Normal Univ Coll Geog & Environm Jinan 250358 Peoples R China;

    Jinan Univ Sch Water Conservancy & Environm Jinan 250022 Peoples R China;

    Jinan Univ Sch Water Conservancy & Environm Jinan 250022 Peoples R China;

    Jinan Univ Sch Civil Engn & Architecture Jinan 250022 Peoples R China;

    Jinan Univ Sch Water Conservancy & Environm Jinan 250022 Peoples R China;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);美国《生物学医学文摘》(MEDLINE);美国《化学文摘》(CA);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Regional pollutants emissions; Air pollution characteristics; High-resolution inventory;

    机译：区域污染物排放;空气污染特征;高分辨率库存;

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