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[Influence of COVID-19 Prevention and Control Measures on PM2.5 Concentration, Particle Size Distribution, Chemical Composition, and Source in Zhengzhou, China].
Huang, Bing-Yi; Wang, Shen-Bo; He, Bing; Xue, Ruo-Yu; Gao, Geng-Yu; Zhang, Rui-Qin.
Afiliación
  • Huang BY; College of Chemistry, Zhengzhou University, Zhengzhou 450001, China.
  • Wang SB; College of Chemistry, Zhengzhou University, Zhengzhou 450001, China.
  • He B; Henan Zhengzhou Ecological Environment Monitoring Center, Zhengzhou 450007, China.
  • Xue RY; College of Chemistry, Zhengzhou University, Zhengzhou 450001, China.
  • Gao GY; College of Chemistry, Zhengzhou University, Zhengzhou 450001, China.
  • Zhang RQ; School of Ecology and Environment, Zhengzhou University, Zhengzhou 450001, China.
Huan Jing Ke Xue ; 43(6): 2840-2850, 2022 Jun 08.
Article en Zh | MEDLINE | ID: mdl-35686753
The COVID-19 lockdown was a typical occurrence of extreme emission reduction, which presented an opportunity to study the influence of control measures on particulate matter. Observations were conducted from January 16 to 31, 2020 using online observation instruments to investigate the characteristics of PM2.5 concentration, particle size distribution, chemical composition, source, and transport before (January 16-23, 2020) and during (January 24-31, 2020) the COVID-19 lockdown in Zhengzhou. The results showed that the atmospheric PM2.5 concentration decreased by 4.8% during the control period compared with that before the control in Zhengzhou. The particle size distribution characteristics indicated that there was a significant decrease in the mass concentration and number concentration of particles in the size range of 0.06 to 1.6 µm during the control period. The chemical composition characteristics of PM2.5 showed that secondary inorganic ions (sulfate, nitrate, and ammonium) were the dominant component of PM2.5, and the significant increase in PM2.5 was mainly owing to the decrease in NO3- concentration during the control period. The main sources of PM2.5 identified by the positive matrix factorization (PMF) model were secondary sources, combustion sources, vehicle sources, industrial sources, and dust sources. The emissions from vehicle sources, industrial sources, and dust sources decreased significantly during the control period. The results of analyses using the backward trajectory method and potential source contribution factor method indicated that the effects of transport from surrounding areas on PM2.5 concentration decreased during the control period. In summary, vehicle and industrial sources should be continuously controlled, and regional combined prevention and control should be strengthened in the future in Zhengzhou.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Contaminantes Atmosféricos / COVID-19 Tipo de estudio: Prognostic_studies Límite: Humans País/Región como asunto: Asia Idioma: Zh Revista: Huan Jing Ke Xue Año: 2022 Tipo del documento: Article País de afiliación: China Pais de publicación: China

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Contaminantes Atmosféricos / COVID-19 Tipo de estudio: Prognostic_studies Límite: Humans País/Región como asunto: Asia Idioma: Zh Revista: Huan Jing Ke Xue Año: 2022 Tipo del documento: Article País de afiliación: China Pais de publicación: China