Elucidating contributions of volatile organic compounds to ozone formation using random forest during COVID-19 pandemic: A case study in China.

Ozone has been reported to increase despite nitrogen oxides reductions during the COVID-19 pandemic, and ozone formation needs to be revisited using volatile organic compounds (VOCs), which are rarely measured during the pandemic. Here, a total of 98 VOCs species were monitored in an economy-active city in China from January 2021 to August 2022 to assess contributions to ozone formation during the pandemic. Total VOCs concentrations were 35.55 ± 21.47 ppb during the entire period, among which alkanes account for the largest fraction (13.78 ppb, 38.0%), followed by aromatics (6.16 ppb, 16.8%) and oxygenated VOCs (OVOCs, 5.69 ppb, 15.7%). Most VOCs groups (e.g., alkenes, OVOCs) and individual species (e.g., isoprene, methyl vinyl ketone) display obvious seasonal and diurnal variations, which are related to their sources and reactivities. No weekend effects of VOCs suggest limited influences from traffic emissions during pandemic. Aromatics and alkenes are the major contributors (39% and 33%) to ozone formation potential, largely driven by o/m/p-xylene (21%), ethylene (15%), toluene (9%). Secondary organic aerosol formation potential is dominated by toluene (>50%) despite its low proportion (5%). Further inclusion of VOCs and meteorology in the Random Forest model shows good ozone prediction performance (R2 = 0.77-0.86, RMSE = 11.95-19.91 µg/m3, MAE = 8.89-14.58 µg/m3). VOCs and NO2 contribute >50% of total importance with the largest difference in importance ratio of VOCs/NO2 in the summer and winter, implying ozone formation regime may vary. No seasonal variations in importance of meteorology are observed, while importance of other variables (e.g., PM2.5) is highest in the summer. This work identifies critical VOCs groups and species for ozone formation during the pandemic, and demonstrates the feasibility of machine learning algorithms in elucidation of ozone formation mechanisms.

Application of homemade portable gas chromatography coupled to photoionization detector for the detection of volatile organic compounds in an industrial park.

Traditional offline detection of volatile organic compounds (VOCs) requires complex and time-consuming pre-treatments including gas sampling in containers, pre-concentrations, and thermal desorption, which hinders its application in rapid VOCs monitoring. Developing a cost-effective instrument is of great importance for online measurement of VOCs. Recently, photoionization detectors (PID) are received great attention due to their fast response time and high sensitivity. This study a portable gas chromatography coupled to PID (pGC-PID) was developed and optimized experimental parameters for the application in online monitoring of VOCs at an industrial site. The sampling time, oven temperature and carrier gas flow rate were optimized as 80 s, 50 °C and 60 ml·min-1, respectively. The sampling method is direct injection. Poly tetra fluoroethylene (PTFE) filter membranes were selected to remove particulate matter from interfering with PID. The reproducibility and peak separation were good with relative standard deviations (RSD) ≤ 7%. Good linearities of 27 VOCs standard curves were achieved with R2 ≥ 0.99, and the detection limits were ≤10 ppb with the lowest being 2 ppb for 1,1,2-Trichloroethane. Finally, the pGC-PID is successfully applied in online VOCs monitoring at an industrial site. A total of 17 VOCs species was detected and their diurnal variations were well obtained, indicating pGC-PID is well suited for online analysis in field campaign.

Three-dimensional spatiotemporal variability of CO2 in suburban and urban areas of Shaoxing City in the Yangtze River Delta, China.

Metropolitan areas are the most anthropogenically active places but there is a lack of knowledge in carbon dioxide (CO2) spatial distribution in suburban and urban areas. In this study, the CO2 three-dimensional distributions were obtained from 92 times vertical unmanned aerial vehicle (UAV) flight observations in Shaoxing suburbs and 90 times ground mobile observations in Shaoxing urban areas from Nov. 2021 to Nov. 2022. The vertical distribution showed that CO2 concentrations gradually decreased from 450 to 420 ppm with altitude from 0 to 500 m. CO2 vertical profile concentrations can be influenced by transport from multiple regions. Based on the vertical observation data combining a potential source contribution function (PSCF) model, Shaoxing suburban CO2 were to be derived from urban areas in spring and autumn, while in winter and autumn were mainly from the long-transports from neighboring cities. Further the CO2 concentrations of urban horizontal distribution were observed in the range of 460-510 ppm through the mobile campaigns. Urban CO2 were partly emitted from traffic exhausts and residential combustion. Overall, CO2 concentrations were observed to be lower in spring and summer due to the CO2 uptake by plant photosynthesis. This uptake was initially quantified and accounted for 4.2 % of total CO2 in suburbs and 3.3 % in urban areas by calculating the decrease in CO2 concentration from peak to trough in the daytime. Compared with the CO2 observed in the Lin'an background station, the maximum regional CO2 enhancement in Shaoxing urban areas reached to 8.9 % while the maximum in suburbs only 4.4 %. The contribution differences between urban and suburban areas to regional CO2 were relatively constant at 1.6 % in four seasons may be mainly ascribed to the contribution of long-range CO2 transport to the suburbs.