Elucidating the responses of highly time-resolved PM2.5 related elements to extreme emission reductions

Kai Cheng; Yunhua Chang; Yaqiong Kuang; Rehana Khan; Zhong Zou

doi:10.1016/j.envres.2021.112624

Elucidating the responses of highly time-resolved PM_2.5 related elements to extreme emission reductions

Environ Res. 2022 Apr 15:206:112624. doi: 10.1016/j.envres.2021.112624. Epub 2021 Dec 29.

Authors

Kai Cheng¹, Yunhua Chang², Yaqiong Kuang¹, Rehana Khan¹, Zhong Zou³

Affiliations

¹ Yale-NUIST Center on Atmospheric Environment, International Joint Laboratory on Climate and Environment Change (ILCEC), School of Applied Meteorology, Nanjing University of Information Science & Technology, Nanjing 210044, China.
² Yale-NUIST Center on Atmospheric Environment, International Joint Laboratory on Climate and Environment Change (ILCEC), School of Applied Meteorology, Nanjing University of Information Science & Technology, Nanjing 210044, China. Electronic address: changy13@nuist.edu.cn.
³ Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP(3)), Department of Environmental Science and Engineering, Fudan University, Shanghai, 200433, China.

Abstract

China's unprecedented lockdown to contain the spread of the novel coronavirus disease (COVID-19) in early 2020, provided a tragic natural experiment to investigate the responses of atmospheric pollution to emission reduction at regional scale. Primarily driven by primary emissions, particulate trace elements is vitally important due to their disproportionally adverse impacts on human health and ecosystem. Here 14 trace elements in PM_2.5 were selected for continuous measurement hourly in urban representative site of Shanghai, for three different phases: pre-control period (1-23 January 2020), control period (24 January-10 February 2020; overlapped with Chinese Lunar New Year holiday) and post control period (11-26 February 2020) the city's lockdown measures. The results show that all meteorological parameters (including temperature, RH, mixing layer height et al.) were generally consistent among different periods. Throughout the study period, the concentrations of most species displayed a "V-shaped" trend, suggesting significant effects by the restriction measures imposed during the lockdown period. While this is not the case for species like K, Cu and Ba, indicating their unusual origins. As a case study, the geographical origins of Cu were explored. Seven major sources, i.e., Vehicle-related emission (including road dust; indicative of Ca, Fe, Ba, Mn, Zn, Cu; accounting for 30.1%), shipping (Ni; 5.0%), coal combustion (As, Pb; 4.2%), Se and Cr industry (24.9%), nonferrous metal smelting (Au, Hg; 7.5%) and fireworks burning (K, Cu, Ba; 28.3%) were successfully pinpointed based on positive matrix factorization (PMF) analysis. Our source apportionment results also highlight fireworks burning was one of the dominant source of trace elements during the Chinese Lunar New Year holiday. It is worth noting that 56% of the total mass vehicular emissions are affiliated with non-exhaust sources (tire wear, brake wear, and road surface abrasion).

Keywords: COVID-19 lockdown; High-frequency response; PMF model; Source; Trace elements.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Air Pollutants* / analysis
COVID-19*
China
Communicable Disease Control
Dust / analysis
Ecosystem
Environmental Monitoring
Humans
Particulate Matter / analysis
SARS-CoV-2
Trace Elements* / analysis
Vehicle Emissions / analysis

Substances

Air Pollutants
Dust
Particulate Matter
Trace Elements
Vehicle Emissions