Your browser doesn't support javascript.
loading
[VOCs Emission Inventory and Uncertainty Analysis of Industry in Qingdao Based on Latin Hypercube Sampling and Monte Carlo Method].
Xu, Wan-Ying; Fu, Fei; Lü, Jian-Hua; Li, Rui-Peng; Shao, Rui; He, Hui; Li, Shu-Fen; Zuo, Hua.
Afiliación
  • Xu WY; Qingdao Research Academy of Environmental Sciences, Qingdao 266003, China.
  • Fu F; Qingdao Research Academy of Environmental Sciences, Qingdao 266003, China.
  • Lü JH; Qingdao Research Academy of Environmental Sciences, Qingdao 266003, China.
  • Li RP; Qingdao Research Academy of Environmental Sciences, Qingdao 266003, China.
  • Shao R; Qingdao Research Academy of Environmental Sciences, Qingdao 266003, China.
  • He H; Qingdao Research Academy of Environmental Sciences, Qingdao 266003, China.
  • Li SF; Qingdao Research Academy of Environmental Sciences, Qingdao 266003, China.
  • Zuo H; Qingdao Research Academy of Environmental Sciences, Qingdao 266003, China.
Huan Jing Ke Xue ; 42(11): 5180-5192, 2021 Nov 08.
Article en Zh | MEDLINE | ID: mdl-34708957
ABSTRACT
In recent years, fine particulate matter(PM2.5) and ozone(O3) have become the main air pollutants in cities in China. Volatile organic compounds(VOCs) are one of the important precursors of PM2.5, O3, and secondary organic aerosols. The establishment of VOCs emission inventory is therefore of great significance for controlling the amount of PM2.5 and O3. To date, the coefficient method has been used, which has error transmission of activity level, parameter and model, leading to the uncertainty of emission inventory. Multivariate uncertainty quantitative analysis of VOCs emission inventory provides an accurate alternative which has not been reported in China. The bottom-up method is adopted to collect the activity level of each enterprise. The variables of pollution control measures are obtained from surveys conducted with enterprises. The VOCs emission inventory of Qingdao from industrial source is established using an optimized coefficient method. The uncertainty of the VOCs inventory on the impact of univariate and multivariate variables is simulated by combining the Monte Carlo method(MC) with Latin hypercube sampling method(LHS). The results show that the total VOCs emissions were 44700 tons from industrial sources in 2019(unoptimized coefficient

method:

31100 tons).The rubber and plastic industries, metal products, and oil/coal/other fuel processing contributed more VOCs, which accounted for 40.26% of the total emissions. The uncertainty of multivariate simulation is higher than that of single variable. The uncertainty from process(-9.72%-230.51%) and solvent using source(-14.14%-122.77%) is significantly higher than uncertainty from combustion source(-15.62%-36.41%). The main sectors affecting the uncertainty of the VOCs inventory includethe chemical, papermaking, and textile industries(emission factors); metal, automobile manufacturing, and chemical industries(removal rate, facility operating rate); industries of petroleum processing and ferrous metal smelting(too few samples). VOCs emissions are mainly distributed in the east of the West Coast New district, north of Dazhu Mountain, south of Jimo district, north of Chengyang district, northeast of Jiaozhou district, built-up area of Pingdu district, and southeast of Laixi district.
Asunto(s)
Palabras clave

Texto completo: 1 Base de datos: MEDLINE Asunto principal: Ozono / Contaminantes Atmosféricos / Compuestos Orgánicos Volátiles Tipo de estudio: Health_economic_evaluation / Prognostic_studies País/Región como asunto: Asia Idioma: Zh Revista: Huan Jing Ke Xue Año: 2021 Tipo del documento: Article

Texto completo: 1 Base de datos: MEDLINE Asunto principal: Ozono / Contaminantes Atmosféricos / Compuestos Orgánicos Volátiles Tipo de estudio: Health_economic_evaluation / Prognostic_studies País/Región como asunto: Asia Idioma: Zh Revista: Huan Jing Ke Xue Año: 2021 Tipo del documento: Article