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首页> 外文期刊>Atmospheric Chemistry and Physics Discussions >Development of a unit-based industrial emission inventory in the Beijing–Tianjin–Hebei region and resulting improvement in air quality modeling
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Development of a unit-based industrial emission inventory in the Beijing–Tianjin–Hebei region and resulting improvement in air quality modeling

机译:京津冀地区基于单位的工业排放库存的发展,导致空气质量造型改善

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The Beijing–Tianjin–Hebei (BTH) region is a metropolitan area with the most severe fine particle (PM2.5) pollution in China. An accurate emission inventory plays an important role in air pollution control policy making. In this study, we develop a unit-based emission inventory for industrial sectors in the BTH region, including power plants, industrial boilers, steel, non-ferrous metal smelting, coking plants, cement, glass, brick, lime, ceramics, refineries, and chemical industries, based on detailed information for each enterprise, such as location, annual production, production technology/processes, and air pollution control facilities. In the BTH region, the emissions of sulfur dioxide (SO2), nitrogen oxide (NOx), particulate matter with diameter less than 10μm (PM10), PM2.5, black carbon (BC), organic carbon (OC), and non-methane volatile organic compounds (NMVOCs) from industrial sectors were 869, 1164, 910, 622, 71, 63, and 1390kt in 2014, respectively, accounting for a respective 61%, 55%, 62%, 56%, 58%, 22%, and 36% of the total emissions. Compared with the traditional proxy-based emission inventory, much less emissions in the high-resolution unit-based inventory are allocated to the urban centers due to the accurate positioning of industrial enterprises. We apply the Community Multi-scale Air Quality (CMAQ; version 5.0.2) model simulation to evaluate the unit-based inventory. The simulation results show that the unit-based emission inventory shows better performance with respect to both PM2.5 and gaseous pollutants than the proxy-based emission inventory. The normalized mean biases (NMBs) are 81%, 21%, 1%, and ?7% for the concentrations of SO2, NO2, ozone (O3), and PM2.5, respectively, with the unit-based inventory, in contrast to 124%, 39%, ?8%, and 9% with the proxy-based inventory; furthermore, the concentration gradients of PM2.5, which are defined as the ratio of the urban concentration to the suburban concentration, are 1.6, 2.1, and 1.5 in January and 1.3, 1.5, and 1.3 in July, for simulations with the unit-based inventory, simulations with the proxy-based inventory, and observations, respectively, in Beijing. For O3, the corresponding gradients are 0.7, 0.5, and 0.9 in January and 0.9, 0.8, and 1.1 in July, implying that the unit-based emission inventory better reproduces the distributions of pollutant emissions between the urban and suburban areas.
机译:北京 - 天津 - 河北(BTH)地区是中国最严重的细颗粒物(PM2.5)污染都市圈。准确的排放清单起到空气污染控制政策的制定具有重要作用。在这项研究中,我们开发了在BTH区域工业部门,包括发电厂,工业锅炉,钢,有色金属冶炼,焦化厂,水泥,玻璃,砖,石灰,陶瓷,炼油厂单元基于发射库存,并根据每个企业的详细信息,如位置,年生产,生产技术/工艺,和空气污染控制设施化工等行业。在BTH区域,二氧化硫(SO2),氮氧化物(NOx),与直径小于10μm(PM10),PM2.5,黑碳(BC),有机碳(OC)的颗粒物质,和非的排放从工业部门甲烷挥发性有机化合物(非甲烷挥发性有机化合物)分别为869,1164,910,622,71,63,和1390克拉在2014年,占各自61%,55%,62%,56%,58%,22 %,和总排放量的36%。与传统的基于代理的排放清单相比,高分辨率单元的广告资源要少得多的排放量被分配到城市中心由于工业企业的准确定位。我们应用社区多尺度空气质量(CMAQ; 5.0.2版)模型模拟​​,以评估该单元的广告资源。仿真结果表明,相对于这两个PM2.5和气态污染物超过基于代理的排放清单的单位为基础的排放清单显示了更好的性能。归一化的平均偏差(NMBS)是81%,21%,1%,和吗?SO2,NO2,臭氧(O3),和PM2.5,分别的浓度,单位为基础的库存,而相比之下7%至124%,39%,8%,且与基于代理的库存9%?;此外,PM2.5的浓度梯度,其被定义为城市浓度郊区浓度的比率,是1.6,2.1和一月1.5和1.3,1.5和1.3在七月,用于与所述单位 - 模拟库存为主,分别模拟与基于代理的库存和观察,在北京举行。为O3,相应的梯度0.7,0.5和0.9在一月和0.9,0.8和1.1在七月,这意味着该单元基于发射库存更好再现该城市和郊区之间的污染物排放的分布。

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