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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.
Afiliação
  • 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 em Zh | MEDLINE | ID: mdl-35686753
ABSTRACT
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 Coleções: 01-internacional Contexto em Saúde: 1_ASSA2030 / 2_ODS3 / 4_TD Base de dados: MEDLINE Assunto principal: Poluentes Atmosféricos / COVID-19 Tipo de estudo: Prognostic_studies Limite: Humans País/Região como assunto: Asia Idioma: Zh Revista: Huan Jing Ke Xue Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Contexto em Saúde: 1_ASSA2030 / 2_ODS3 / 4_TD Base de dados: MEDLINE Assunto principal: Poluentes Atmosféricos / COVID-19 Tipo de estudo: Prognostic_studies Limite: Humans País/Região como assunto: Asia Idioma: Zh Revista: Huan Jing Ke Xue Ano de publicação: 2022 Tipo de documento: Article