Calculations of the Air Pollution and Pollutants Deposition Due to a Non-Ferrous Metal Plant

2000 ◽  
pp. 767-768
Author(s):  
Dimiter Syrakov ◽  
Anna Tzenkova ◽  
Julia Ivancheva ◽  
Tatiana Spassova ◽  
Vasil Andreev ◽  
...  
Keyword(s):  
Air Pollution ◽  
Ferrous Metal

scholarly journals Development of a unit-based industrial emission inventory in the Beijing-Tianjin-Hebei region and resulting improvement in air quality modeling

2018 ◽  
Author(s):  
Haotian Zheng ◽  
Siyi Cai ◽  
Shuxiao Wang ◽  
Bin Zhao ◽  
Xing Chang ◽  
...  
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Pollution Control ◽  
Emission Inventory ◽  
Ferrous Metal ◽  
Pollutant Emissions ◽  
Air Pollution Control ◽  
Industrial Enterprises ◽  
Industrial Sectors ◽  
Bth Region

Abstract. The Beijing-Tianjin-Hebei (BTH) region is a metropolitan area with the most severe fine particle (PM2.5) pollution in China. 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, and steel, non-ferrous metal, coking, cement, glass, brick, lime, ceramics, refinery, and chemical industries, based on detailed information for each enterprise, such as location, annual production, production technology/process and air pollution control facilities. In the BTH region, the emissions of sulfur dioxide (SO2), nitrogen oxide (NOx), particulate matter with diameter less than 10 μm (PM10), PM2.5, black carbon (BC), organic carbon (OC), and non-methane volatile organic compounds (NMVOCs) from industrial sectors are 869 kt, 1164 kt, 910 kt, 622 kt, 71 kt, 63 kt and 1390 kt in 2014, respectively, accounting for 61 %, 55 %, 62 %, 56 %, 58 %, 22 % and 36 %, respectively, 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 center because of the accurate positioning of industrial enterprises. We apply the Community Multi-scale Air Quality (CMAQ) model simulation to evaluate the unit-based inventory. The simulation results show that the unit-based emission inventory gives better performance of both PM2.5 and gaseous pollutants than the proxy-based emission inventory. The normalized mean biases (NMBs) are 81 %, 21 %, 1 % and −7 % for concentrations of SO2, NO2, ozone 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 urban concentration to 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 ozone, 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.

scholarly journals Development of a unit-based industrial emission inventory in the Beijing–Tianjin–Hebei region and resulting improvement in air quality modeling

2019 ◽  
Vol 19 (6) ◽  
pp. 3447-3462 ◽  
Author(s):  
Haotian Zheng ◽  
Siyi Cai ◽  
Shuxiao Wang ◽  
Bin Zhao ◽  
Xing Chang ◽  
...  
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Pollution Control ◽  
Emission Inventory ◽  
Ferrous Metal ◽  
Pollutant Emissions ◽  
Air Pollution Control ◽  
Industrial Enterprises ◽  
Industrial Sectors ◽  
Bth Region

Abstract. 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 10 µm (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 1390 kt 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.

Air Pollution

2019 ◽  
Author(s):  
Christian Seigneur
Keyword(s):  
Air Pollution

SYSTEMIC EFFECT OF PARTICULATE AIR POLLUTION

2000 ◽  
Vol 12 (sup3) ◽  
pp. 233-244 ◽  
Author(s):  
W. MacNee, X. Y. Li, P. Gilmour, K. Do
Keyword(s):  
Air Pollution ◽  
Systemic Effect ◽  
Particulate Air Pollution
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