key: cord-0826028-h3onnxq3
authors: Wang, Ming; Lu, Sihua; Shao, Min; Zeng, Limin; Zheng, Jun; Xie, Fangjian; Lin, Haotian; Hu, Kun; Lu, Xingdong
title: Impact of COVID-19 lockdown on ambient levels and sources of volatile organic compounds (VOCs) in Nanjing, China
date: 2020-11-20
journal: Sci Total Environ
DOI: 10.1016/j.scitotenv.2020.143823
sha: a9c1e294014b450b169222ad263a713849e096a9
doc_id: 826028
cord_uid: h3onnxq3

A lot of restrictive measures were implemented in China during January-February, 2020 to control rapid spread of COVID-19. Many studies reported impact of COVID-19 lockdown on air quality, but little research focused on ambient volatile organic compounds (VOCs) till now, which play important roles in production of ozone and secondary organic aerosol. In this study, impact of COVID-19 lockdown on VOCs mixing ratios and sources were assessed based on online measurements of VOCs in Nanjing during December 20, 2019-Feburary 15, 2020 (P1-P2) and April 15-May 13, 2020 (P3). Average VOCs levels during COVID-19 lockdown period (P2) was 26.9 ppb, about half of value for pre-lockdown period (P1). Chemical composition of VOCs also showed significant changes. Aromatics contribution during decreased from 13% during P1 to 9% during P2, whereas alkanes contribution increased from 64% to 68%. Positive matrix factorization (PMF) was then applied for non-methane hydrocarbons (NMHCs) sources apportionment. Five sources were identified, including a source related to transport and background air masses, three sources related to petrochemical industry or chemical industry (petrochemical industry#1-propene/ethene, petrochemical industry#2-C7-C9 aromatics, and chemical industry-benzene), and a source attributed to gasoline evaporation and vehicular emission. During P2, NMHCs levels from petrochemical industry#2-C7-C9 aromatics showed the largest relative decline of 94%, followed by petrochemical industry#1-propene/ethene (67%), and gasoline evaporation and vehicular emission (67%). Furthermore, ratios of OH reactivity of NMHCs versus NO2 level (R OH,NMHCs/NO2) and total oxidant production rate (P (OX)) were calculated to assess potential influences of COVID-19 lockdown on O3 formation.

From December 2019, the coronavirus disease (COVID-19) spread worldwide and caused enormous influences on international economy, industrial production, and social life. To prevent COVID-19 pandemic and protect human health, 30 provinces of China started the Level Ⅰ (particularly serious) response to public health emergencies from 23 rd to 25 th January, 2020. A lot of restrictive measures were implemented to reduce people's social contacts, such as shutting down theatres, restaurants, malls, schools, and non-essential businesses, restricting public transportation (e.g. airplane, train, and bus) and even private cars, etc. More detailed descriptions on National Emergency Response Plan for Public Emergencies can be found in the paper by . Anthropogenic sources related to human activities (e.g. traffic-related emissions, industrial emissions) were considered as the largest contributor to air pollutants in urban areas (Lelieveld et al., 2015) , and therefore COVID-19 lockdown will result in reduction of anthropogenic air pollutants emissions .

The latest research publications have reported the significant impact of many cities (Bauwens et al., 2020; Chauhan and Singh, 2020; Rodriguez-Urrego and Rodriguez-Urrego, 2020; Zangari et al., 2020) , whereas surface ozone (O 3 ) pollution was amplified (Sicard et al., 2020; Zhao et al., 2020) during COVID-19 lockdown period. Volatile organic compounds (VOCs) are important precursors of O 3 and PM 2.5 (Atkinson et al., 2006) , but variations of ambient VOCs levels caused by lockdown are still unclear until now.

Compared with inorganic air pollutants, e.g. NO X and SO 2 , ambient VOCs have various chemical composition and wide sources . It is essential to obtain accurate knowledge of VOCs sources in order to reduce their emissions and improve air quality. A few studies based on emission inventory and receptor models have been conducted to determine ambient VOCs sources in Nanjing, China Zhao et al., 2017; Wang et al., 2020a) . Transportation and industry were considered as the two largest contributors to ambient VOCs, whereas relative contributions of individual sources to VOCs showed some discrepancies among different studies. In the emission inventory built by Zhao et al. (2017) , industrial processing and solvent use were considered as the most important VOCs sources, 2020; . This provides an opportunity for us to further understand and evaluate VOCs sources in Nanjing.

The Yangtze River Delta (YRD) region started the Level Ⅰ response to public health emergencies on 00:00 of 25 th January, 2020 and then adjusted to Level Ⅱ (serious) response in 25 th February, 2020. In this study, online measurements of ambient VOCs were conducted during about 3 months to evaluate impact of COVID-19 lockdown on VOCs mixing ratios and sources in Nanjing. Temporal variations of VOCs levels were analyzed, and then ratio analysis and positive matrix factorization (PMF) model were applied for VOCs source apportionment. Changes of VOCs levels from individual sources were then investigated to evaluate impact of COVID-19 lockdown on industrial and traffic-related VOCs emissions. Furthermore, ratios for VOCs reactivity versus NO 2 levels were calculated and their implications on O 3 formation mechanism were discussed.

(Level Ⅲ response period, P3).

The NUIST site is located in the west of YRD region, about 18km north from an urban site (JEMC) in downtown area of Nanjing (Fig. 1 ). There are two expressways close to the NUIST site, especially the expressway in east with about 1km distance which has large traffic flow every day. Additionally, it should be noted that there are three large petrochemical and chemical industrial areas in east (B), northeast (A), and southeast (C) of this site, with distances of about 5km, 10km, and 20km, respectively. Therefore, this site was considered to be representative of an atmospheric environment influenced by both transportation and petrochemical/chemical industry. 

In this study, ambient mixing ratios of 102 VOC species were online measured by a cryogen-free gas chromatography system (GC) equipped with a mass spectrometer detector (MSD) and a flame ionization detector (FID) developed by Peking University. Briefly, target compounds were enriched at a ultra-low temperature of -160 C, and then they were vapored and injected into GC system for separation and detection. Two parallel channels were designed in the GC-MSD/FID system. In one channel, C2-C5 non-methane hydrocarbons (NMHCs) were trapped using a PLOT (Al 2 O 3 /KCl) column (25 cm, 0.53 mm ID). After sampling, the enrichment trap was heated to 110C and then vaporized compounds were separated by a PLOT (Al 2 O 3 /KCl) column (15 m, 0.32 mm ID) and detected by an FID. In the other channel, a deactivated quartz capillary (25 cm, 0.53 mm ID) was applied for trapping C5-C12 NMHCs, halocarbons, and oxygenated VOCs (OVOCs). A DB-624 column (30 m, 0.25 mm ID) connected with MSD was employed to separate and detect these compounds. Two commercial mixture standards with 56 C2-C12 NMHCs and 63 chemicals (Spectra Gases, U.S.) were used for calibration. To correct the drift of MSD responses, internal standards were also employed to calculate ambient mixing ratios of VOCs. More detailed introductions on this GC-MSD/FID system and quality assurance and quality control (QA/QC) procedures of VOCs measurements can be found in the paper by Wang et al. (2014) .

J o u r n a l P r e -p r o o f Journal Pre-proof

The hourly-averaged concentrations of PM 2.5 , O 3 , NO 2 , CO, and SO 2 were obtained from the real-time release platform of national urban air quality Table 1 . It can be found that temperature, WS, and visibility increased from P1 to P3, whereas RH showed a decline trend. Average concentrations for PM 2.5 , CO, SO 2 , and NO 2 during P2 decreased by 12%-48% compared with respective values for P1. However, average concentration of O 3 and total oxidants (O X =O 3 +NO 2 ) during P2 increased by 92% and 7% versus P1, respectively. Wind rose plots in Fig. S4 suggest that east was the prevailing wind direction during P1 and P2, while wind was mainly from east and southeast during P3. versus P1 were 42%, 48%, and 62%, respectively (Table 1) . m,p-Xylene and propene were chosen as representative species because they have been found to be key species in O 3 formation of Nanjing and were influenced significantly by industrial emission (Wang et al., 2020b) . was 0.073 ppb, about one quarter of value for P1. The x 0 for propene mixing ratios was 0.081 ppb during P2, lower than that for P1 by 46%. To illustrate the decline of VOCs levels during P2 versus P1 was not an accidental event, wintertime VOCs measurement results in Nanjing reported from previous studies Wang et al., 2020a) were also compared with average NMHCs mixing ratios during P2. In the study by An et al. (2017) , VOCs were measured in January-February, 2014 at the NUIST site (NUIST-2014). Another study by Wang et al. (2020a) , VOCs were observed during January-February, 2016 at the JEMC site (JEMC-2016). As shown in Table S1 and Fig C4-C5 alkanes are important constitutes of VOCs from vehicular exhaust and gasoline evaporation (Gentner et al., 2013; Song et al., 2020) . The decline of propane and n-butane fractions suggests that contributions of industrial LPG use and traffic-related sources might reduce due to COVID-19 lockdown. For C3-C5 alkanes, average fraction of pentanes (i.e. the sum of n-pentane and i-pentane) increased from 15%-16% for P1 and P2 to 27% during P3 (Fig. 4b ). This is possibly due to the relatively high temperature during P3 which is in favor of gasoline evaporation (Song et al., 2019) . Average fraction of propene in the sum of acetylene, ethene, and propene during P2 was 8%, lower than values for P1 and P3 by factors of 2-2.5 (Fig. 4c) .

Petrochemical industry is an important source of ambient propene in Nanjing (Wang et al., 2020a) , and therefore the lowest propene fraction during P2 indicates the possible decline of petrochemical industrial emissions due to COVID-19 lockdown.

Average fraction of benzene in the sum of benzene, ethylbenzene, and toluene increased from 38% for P1 to 74% for P2 (Fig. 4d) . Ratio of toluene/benzene (T/B) is often used to preliminary analyze relative importance of vehicular exhaust, industrial emission, and combustion sources (Zhang et al., 2016; Song et al., 2020) . The average value of T/B during P2 was 0.32 ppb/ppb, significantly lower than values for P1 and P2 (0.73 ppb/ppb for P1 and 0.91 ppb/ppb for P2). One possible explanation for this finding is that relative decrease of average mixing ratio for toluene during P2 versus P1 (70%) was larger than that for benzene (30%). This indicates that sources of J o u r n a l P r e -p r o o f ambient toluene and benzene during P2 possibly changed due to COVID-19 lockdown, i.e. reduction of VOCs emissions from once source rich in toluene was larger than another source rich in benzene. Furthermore, it was found that T/B values for these three periods were all lower than emission ratio of T/B from vehicular emission (1.0-2.5 ppb/ppb) (Song et al., 2020) and paints use (>3 ppb/ppb) (Mo et al., 2016) , but fell in the range of emission ratios for coal combustion and biomass burning (Zhang et al., 2016) . Actually, residential coal/biomass combustion has been forbidden in Nanjing, and therefore the lower T/B values during P1-P3 may not be related to these combustion sources. Further analysis is needed to identify another VOCs sources which are rich in benzene. ):

where x ij is the mixing ratio for j th NMHC species in i th sample; g ik is the contribution of k th factor to total mixing ratio of NMHCs in i th sample; f kj means the chemical profile of NMHCs (i.e. percentages of j th NMHC species in total mixing ratios of NMHCs) for k th factor; e ij represents the residual for j th NMHC species in i th sample.

In this study, NMHC species with high mixing ratios, low measurement uncertainty, and strong indications on emission sources were given priority in ( concentrations in the YRD region during January-March, 2020 were largely influenced by transport from North China. Therefore, F1 was identified as a source related to transport and background air masses.

As described in Section 2, the NUIST site is close to largest industrial zone in Nanjing (A in Fig. 1) . Benzene, ethene, propene, xylenes, and toluene are important products of petrochemical enterprises in this zone. Meanwhile, benzene is also used as a raw material to produce chlorobenzene and cyclohexane in a chemical enterprise.

Since these species belong to different production lines, temporal variability of their ambient mixing ratios showed significant discrepancies, and therefore they were attributed to three PMF-resolved factors. Factor 2 (F2) was characterized by high abundance of benzene, with percentages in total 35 species of 32.7% and relative contribution of 75.4% (Fig. 5b) . It was found that mixing ratios of benzene showed good correlations with cyclohexane and chlorobenzene (r = 0.77) (Fig. S10 of supplement), but showed poor correlations (r < 0.25) with other aromatics (e.g.

toluene, m,p-xylene), and therefore F2 was identified as a source mainly related to chemical industry-benzene. C2-C3 alkenes and C7-C9 aromatics were the most J o u r n a l P r e -p r o o f Journal Pre-proof abundant species in factor 3 (F3) and factor 4 (F4), respectively. F3 contributed 84.3%

and 31.5% of propene and ethene mixing ratios (Fig. 5c) , while F4 contributed 57%-83% of C7-C9 aromatics (Fig. 5d) . Light alkenes are important constitutes of NMHCs from petrochemical industry (Ryerson et al., 2003; Mo et al., 2015) , and therefore F3 was considered as petrochemical industry#1-propene/ethene. Some studies reported that C7-C9 aromatics were major constitutes of NMHCs from paints and solvent use (Yuan et al., 2010; Li et al., 2019) . However, there are few factories using a lot of solvents and paints near the NUIST site, and therefore F4 was also considered mainly related to petrochemical industry (petrochemical industry#2-C7-C9 aromatics).

Butanes and pentanes in factor 5 (F5) showed the two largest percentages in the summed mixing ratios of total 35 species, with respective values of 26.9% and 29.0% For chemical industry-benzene, its relative contribution during P2 was 25%, higher than those for P1 (13%) and P3 (6%). The relative contribution from gasoline evaporation and vehicular emission during P2 was 7%, significantly lower than those for P1 (11%) and P3 (14%).

To further discuss possible causes for changes of NMHCs sources, average NMHCs levels contributed by each individual source during P1, P2, and P3 were compared in Fig. 6e . The average NMHCs mixing ratio from transport and background air masses during P1 was 17.57.5 ppb, and decreased by 34% and 60% during P2 and P3, respectively. As shown in Table 1 NMHCs. Compared with reactive alkenes and aromatics, these long-lived species abundant in transport and background air masses were less affected by photochemical reactions. In addition, fuels (e.g. coal, natural gas, biomass) were consumed more for heating during winter. Although residential combustion of coal and biomass has been forbidden in Nanjing, these fuels were still heavily used for wintertime heating in rural areas of Jiangsu Province. Considering long-lived NMHC species could be transported a long distance (Fig. S5 of supplement) , the relatively high NMHCs levels during P1 and P2 were also possibly related to larger emissions from fuel combustion on a regional scale.

For the two sources related to petrochemical industry, their contributed NMHCs levels both showed the lowest values during P2. The relative declines of average To compare with reduction of VOCs emissions in the YRD region, changes in total NMHCs mixing ratios from three industrial sources (i.e. F2, F3, and F4) were calculated and compared with VOCs emissions from industrial processing reported by . Summed NMHCs levels from F2, F3, and F4 reduced by 56% during P2 versus P1, close to the relative reduction of VOCs emission from industrial processing (51%) during Level Ⅰ response period versus pre-response period. VOCs emissions from vehicular exhaust and gasoline evaporation reduced by 75% and 50%

during Level Ⅰ and Level Ⅱ response period, respectively . In this J o u r n a l P r e -p r o o f study, NMHCs mixing ratios from gasoline evaporation and vehicular emission reduced by 67% during P2 versus P1, which agrees well with changes of transportation-related VOCs emissions reported by .

five PMF-resolved sources during P1-P3

Ambient NMHCs and NO X are key precursors of ground-level O 3 formation, and ratios of NMHCs/NO X will influence the sensitivity of O 3 formation, i.e. non-linear relationship of O 3 formation with NMHCs and NOx (Atkinson et al., 2006; Tan et al., 2019 versus P1 was 61%, higher than that for NMHCs mixing ratios (46%). This is because radicals. More detailed descriptions on principles and assumptions of this model can be found in the paper by Zhang et al. (2014) . In this method, concentrations of HO 2 and RO 2 were assumed to be equal. Although this assumption can be acceptable in

Beijing (Liu et al., 2012) , it maybe not true in Nanjing during December, 2019-May, 2020. Another uncertainty comes from influences of transport on O 3 , NMHCs, and NO X which were not considered in this model. The production rates of OH and HO 2 radicals (P(HO X )) is an important parameter to calculate P(O X ). In this study, its value during P3 was assumed to be 14 ppb h -1 according to the result of radical budget modelling in Beijing during summer of 2007 (Liu et al., 2012) . The P(HO X ) during P1

and P2 were assumed to be 7 ppb h -1 considering seasonality of HO X abundance (Kanaya et al., 2007) . It should be point out that there is large uncertainty in assuming P(HO X ) values due to the lack of measurement and model results on HO X radicals in Nanjing.

Contour plots of P(O X ) with R OH,NMHCs and NO 2 during these three periods were compared in Fig. 7 

To assess impact of COVID-19 lockdown on ambient VOCs levels and sources, mixing ratios of speciated VOCs were online measured by a GC-MSD/FID system at the NUIST site in Nanjing during December 20, 2019-Feburary 15, 2020 and April 15-May 13, 2020. Average mixing ratio of total measured VOCs during COVID-19 lockdown period (P2) decreased by 47%. Average levels for those species with long lifetime (e.g. CFCs, ethane, acetylene, benzene) showed lower relative declines (4%-32%) during P2 versus P1, whereas reactive aromatics and alkenes exhibited higher declines (49%-92%). The differences of relative decreases for individual VOC species levels suggest possible changes of VOCs sources during P2.

The PMF model was then applied for NMHCs sources apportionment and five sources were identified, including transport and background air masses, chemical J o u r n a l P r e -p r o o f industry-benzene, petrochemical industry#1-propene/ethene, petrochemical industry#2-C7-C9 aromatics, and gasoline evaporation and vehicular emission.

Average NMHCs mixing ratios from petrochemical industry#2-C7-C9 aromatics, petrochemical industry#1-propene/ethene, and gasoline evaporation and vehicular emission all showed the lowest values during P2, with relative decreases versus P1 of 94%, 67%, and 67%, respectively. However, average NMHCs level from chemical industry-benzene did not exhibit a significant decline during P2. The relative reduction of summed NMHCs levels from these three industrial sources was 56%

during COVID-19 lockdown period, close to the result for VOCs emissions from industrial processing (51%).

Ratios of R OH,NMHCs versus NO 2 levels and P(O X ) were calculated to investigate O 3 formation regime. Average values of R OH,NMHCs /NO 2 during P1, P2, and P3 were 0.1240.175 s -1 ppb -1 , 0.0870.067 s -1 ppb -1 , and 0.0930.166 s -1 ppb -1 , respectively.

These values were lower than R OH,NMHCs /NO 2 during August, 2016 by 65%-75%, suggesting that O 3 formation tend to be more sensitive to NMHCs during P1-P3.

Contour plots of P(O X ) at noon with R OH,NMHCs and NO 2 also suggest that O 3 formation during P1-P3 fell in NMHCs-limited regime. Despite average R OH,NMHCs and NO 2 at noon during P2 dropped by 64% and 58% versus P1, P(O X ) during P2 (9.2 ppb h -1 ) was close to the value for P1 (9.3 ppb h -1 ). This suggests it is important to design a scientific reduction scheme for NMHCs and NO X in the development of O 3 control policies.

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Data Curation, Visualization, Writing -Original Draft; Lu Sihua: Validation, Investigation, Data Curation, Writing -review & editing