Decrease in ambient volatile organic compounds during the COVID-19 lockdown period in the Pearl River Delta region, south China

Abstract

During the COVID-19 lockdown, ambient ozone levels are widely reported to show much smaller decreases or even dramatical increases under substantially reduced precursor NOx levels, yet changes in ambient precursor volatile organic compounds (VOCs) have been scarcely reported during the COVID-19 lockdown, which is an opportunity to examine the impacts of dramatically changing anthropogenic emissions on ambient VOC levels in megacities where ozone formation is largely VOC-limited. In this study, ambient VOCs were monitored online at an urban site in Guangzhou in the Pearl River Delta region before, during, and after the COVID-19 lockdown. The average total mixing ratios of VOCs became 19.1% lower during the lockdown than before, and those of alkanes, alkenes and aromatics decreased by 19.0%, 24.8% and 38.2%, respectively. The levels of light alkanes (C < 6) decreased by only 13.0%, while those of higher alkanes (C ≥ 6) decreased by 67.8% during the lockdown. Disappeared peak VOC levels in morning rush hours and the drop in toluene to benzene ratios during the lockdown suggested significant reductions in vehicle exhaust and industrial solvent emissions. Source apportioning by positive matrix factorization model revealed that reductions in industrial emissions, diesel exhaust (on-road diesel vehicles and off-road diesel engines) and gasoline-related emissions could account for 48.9%, 42.2% and 8.8%, respectively, of the decreased VOC levels during the lockdown. Moreover, the reduction in industrial emissions could explain 56.0% and 70.0% of the reductions in ambient levels of reactive alkenes and aromatics, respectively. An average increase in O 3 –1 h by 17% and a decrease in the daily maximum 8-h average ozone by 11% under an average decrease in NOx by 57.0% and a decrease in VOCs by 19.1% during the lockdown demonstrated that controlling emissions of precursors VOCs and NOx to prevent ambient O 3 pollution in megacities such as Guangzhou remains a highly challenging task.

Important revelations of different degrees of COVID-19 lockdown on improving regional air quality: a case study of Shijiazhuang, China

“…As shown in Fig. 7 , alkanes were the most contributing species in both lockdowns, with their share further increasing by 37.8% in lockdown II, mainly concentrated in light alkanes (C < 6) associated with evaporation emissions of LPG and gasoline (Pei et al 2022 ), consistent with the increase in propane described above. In addition, the diurnal variation in alkane concentrations was more severe in lockdown II (14.4 ~ 32.4 ppbv) than in lockdown I (16.2 ~ 19.3 ppbv), suggesting that alkane sources were characterized by heterogeneous temporal variation.…”

“…Among the above species, ethylene was the most concentrated species in lockdown I, reaching 6.45 ppbv, while in lockdown II the concentration decreased to 3.45 ppbv. Ethylene is a typical gasoline vehicle emission (Pei et al 2022 ; Zhang et al 2013 ), and the decrease in its concentration reaffirms the reduction in traffic sources in lockdown II. Propane increased by 45.6% in lockdown II, making it the most abundant species with an increase in OFP of 0.43 ppbv.…”

“…Factor 4 was identified as a traffic source, with high loads of ethylene (36.9%), acetylene (25.7%), benzene (31.4%), and toluene (38.1%), typical of petrol vehicle emissions (Pei et al 2022 ; Zhang et al 2013 ).…”

Developing the Maximum Incremental Reactivity for Volatile Organic Compounds in Major Cities of Central‐Eastern China

“…The localized MIR values were applied to quantify the Conw_OFPs for VOCs according to Equation 2 (Mo et al, 2022;Pei et al, 2022).…”

“…One of the widely used metrics is the ozone formation potential (OFP), and its definition and calculation varied among literature (Chang & Rudy, 1990;Jenkin et al, 2017;NRC, 1999;Russell et al, 1995). Currently, the OFP is usually defined as the product of incremental reactivity (IR) multiplying by emission quantity (i.e., emission-weighted OFP) (Li et al, 2019;Sha et al, 2021;Shi et al, 2022) or observation data (i.e., concentration-weighted OFP (Conw_OFP)) (Mo et al, 2022;Pei et al, 2022;Shi et al, 2022). The IR values are generally determined by model simulations (Carter, 1994a(Carter, , 1994b(Carter, , 2009(Carter, , 2010Qiu et al, 2020;Venecek et al, 2018;Zhang et al, 2021) and then can be used for the OFP calculation.…”