Sie befinden Sich nicht im Netzwerk der Universität Paderborn. Der Zugriff auf elektronische Ressourcen ist gegebenenfalls nur via VPN oder Shibboleth (DFN-AAI) möglich. mehr Informationen...
Development of a unit-based industrial emission inventory in the Beijing–Tianjin–Hebei region and resulting improvement in air quality modeling
Ist Teil von
Atmospheric chemistry and physics, 2019-03, Vol.19 (6), p.3447-3462
Ort / Verlag
Katlenburg-Lindau: Copernicus GmbH
Erscheinungsjahr
2019
Quelle
EZB Electronic Journals Library
Beschreibungen/Notizen
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.