key: cord-0803432-7ac2z40g
authors: Ding, Jing; Dai, Qili; Li, Yafei; Han, Suqin; Zhang, Yufen; Feng, Yinchang
title: Impact of meteorological condition changes on air quality and particulate chemical composition during the COVID-19 lockdown
date: 2021-02-25
journal: J Environ Sci (China)
DOI: 10.1016/j.jes.2021.02.022
sha: 719d4c535b8ce52e5e1329a1f2230c578ad240f9
doc_id: 803432
cord_uid: 7ac2z40g

Stringent quarantine measures during the Coronavirus Disease 2019 (COVID-19) lockdown period (January 23, 2020 to March 15, 2020) have resulted in a distinct decrease in anthropogenic source emissions in North China Plain compared to the paralleled period of 2019. Particularly, 22.7% decrease in NO(2) and 3.0% increase of O(3) was observed in Tianjin, nonlinear relationship between O(3) generation and NO(2) implied that synergetic control of NO(x) and VOCs is needed. Deteriorating meteorological condition during the COVID-19 lockdown obscured the actual PM(2.5) reduction. Fireworks transport in 2020 Spring Festival (SF) triggered regional haze pollution. PM(2.5) during the COVID-19 lockdown only reduced by 5.6% in Tianjin. Here we used the dispersion coefficient to normalize the measured PM(2.5) (DN-PM(2.5)), aiming to eliminate the adverse meteorological impact and roughly estimate the actual PM(2.5) reduction, which reduced by 17.7% during the COVID-19 lockdown. In terms of PM(2.5) chemical composition, significant NO(3)(−) increase was observed during the COVID-19 lockdown. However, as a tracer of atmospheric oxidation capacity, odd oxygen (O(x) = NO(2) + O(3)) was observed to reduce during the COVID-19 lockdown, whereas relative humidity (RH), specific humidity and aerosol liquid water content (ALWC) were observed with noticeable enhancement. Nitrogen oxidation rate (NOR) was observed to increase at higher specific humidity and ALWC, especially in the haze episode occurred during 2020SF, high air humidity and obvious nitrate generation was observed. Anomalously enhanced air humidity may response for the nitrate increase during the COVID-19 lockdown period.

Jing Ding 1,3 , Qili Dai 2,3, Yafei Li 2,3 , Suqin Han 1,3,* , Yufen Zhang 2,3,** , Yinchang Feng 2,3 

The Coronavirus Disease 2019 broke out in January 2020, the nationwide quarantine measures including social distancing, suspension of public transport and industry were taken to alleviate the spread of the epidemic started from the Spring Festival (SF) holiday (January 23, 2020), almost all cities were lockdown. These stringent measures have wrought an unprecedented plummet in anthropogenic emissions. Satellite images from NASA show how pollution has cleared over China, NO 2 emission reduction was particularly remarkable (https://earthobservatory.nasa.gov, Airborne Nitrogen Dioxide Plummets Over China). After the extended Spring Festival holiday, industries in China began to resume production in an orderly manner from mid-March.

Many studies have assessed the air quality variation across of China during this period, concentrations of different atmospheric pollutants varied with substantial differences. Silver et al. (2020) found that the largest reductions occurred in NO 2 , with concentrations 27.0% lower on average across China during the lockdown period. Mean PM 2.5 and PM 10 across China were respectively 10.5% and 21.4% lower during the lockdown period, but there were no significant impacts on O 3 . Result in work of Kim et al. (2020) also showed that the reduction in NO 2 concentrations across China in lockdown period was deeper and longer than in normal years, and PM 2.5 reduced by 30 % compared with normal years, by contrast, SO 2 emissions had not be affected significantly by the pandemic. In Eastern China, satellite observation displayed that CO and NO 2 showed the most obvious decrease (20% and 30%), since they were closely associated with energy consumption and transport restrictions (Filonchyk et al., 2020) . In the Chinese "epicenter" of COVID-19, Wuhan, compared with the period before the lockdown, NO 2 and PM 2.5 during the lockdown period decreased by approximately 53.3% and 36.9%, whereas O 3 increased by 116.6% (Lian et al., 2020) . Apparently, as an indicator of emissions in the transportation sector, large NO 2 emission reduction demonstrated that quarantine measures were well implemented.

Although enormous pollutants emission has been reduced, the severe haze episodes still occurred during the lockdown period. The emission reduction control measures were questioned by the public. Actually, in the North China Plain (NCP), pollutants emissions largely exceed the atmospheric environment capacity. Except for SO 2 , the actual emissions of other pollutants exceeded the environmental capacity by more than 50%, the emission intensity reached twice to five times the national average, and increased by 30% during the heating season (http://www.mee.gov.cn/xxgk2018/). Therefore, haze episodes occur once the adverse synoptic system covers the NCP, which obscures the actual emission reduction effect.

Most particularly, the atmospheric pollution sources associated livelihood did not shut down during the COVID-19 lockdown period, especially in northern China, such as heating. Dai et al. (2020) investigated the changes in source contributions to ambient PM 2.5 after the outbreak of COVID-19 in Tianjin using the dispersion normalized positive matrix factorization (DN-PMF) model, which can help to reduce the influence of meteorology. Compared to the conventional constrained PMF results, the constrained DN-PMF highlights the contribution of traffic emissions, coal combustion, firework and residential burning to PM 2.5 .

In addition to the drop in pollutants concentration, the particulate chemical composition has also significantly altered. In Shanghai, Chen et al. (2020) found that PM 2.5 reduction was mainly attributed to decreasing concentrations of nitrate. However, another sight showed that much higher secondary aerosol fraction in PM 2.5 were observed during the Spring Festival holiday of 2020 (73%) than 2019 (59%) in Shanghai, the synergistic effects of long-range transport and atmospheric chemistry resulted in the efficient conversion of NO x to particulate nitrate (Chang et al., 2020) . With the WRF-Chem simulation, Huang et al. (2020) found that in eastern China, the near-surface O 3 was enhanced due to the emission reduction during the COVID-19 lockdown, which enhanced the atmospheric oxidation capacity and further facilitated the secondary aerosol formation. In Beijing, primary aerosol species associated with traffic, cooking and coal combustion emissions during the Spring Festival holiday reduced by 30%-50% on average, whereas secondary aerosol species decreased by a much small part (5%-12%) (Sun et al., 2020) . These results preliminarily point out that current emission reduction measures can exert distinct particulate chemical composition, yet in general terms, the reduction measures during the COVID-19 lockdown obviously reduce the primary species but may not suppress secondary aerosol formation efficiently.

In this work, we compared the meteorological parameters, gaseous pollutants and PM 2.5 chemical composition during the COVID-19 lockdown period of 2020 (January 23, 2020 to March 15, 2020) with the same period of 2019 in Tianjin, and the possible reasons for the changes were analyzed. Dispersion coefficient normalized PM 2.5 concentration was calculated to show the actual reduction during the lockdown period of 2020.

Tianjin is located in the eastern region of the NCP, and faces Bohai Bay in the east (Fig. S1) .

The sampling site involving PM 2.5 chemical components, as well as meteorological parameters and atmospheric pollutants matched PM 2.5 chemical components in the Section 3.3 is the Air Quality Research Supersite at Nankai University (NKUS, 3859'N and 117°20'E), which is located in the south of Tianjin, is an urban-rural marginal area approximately 20 km from downtown Tianjin and 50 km from Bohai Bay. Vertical meteorological parameters were obtained at the Atmospheric Boundary Layer Observation Station of the China Meteorological Administration, which is located south of Tianjin (39°04′N, 117°12′E).

Ground-based temperature (T), relative humidity (RH), wind speed (WS) and wind direction (WD) were observed by an automatic weather station. Total solar radiation was measured by a pyranometer (CMP21, Kipp & Zonen, Netherlands), respectively. The mixing layer height (MLH) was simulated by Weather Research and Forecasting Model (WRF, V3.8).

Vertical distribution of T, RH, WS were measured with an automatic weather station installed on a meteorological tower at 15 platform heights (5, 10, 20, 30, 40, 60, 80, 100,120, 140, 180, 200, 220 and 250 m 

The dispersion coefficient (DC) began to be used to assess air quality changes in the 1970s (Leahey, 1972 , Kleinman et al., 1974 , 1976 . The dispersion coefficient (m 2 /sec) was defined as the product of the MLH height and the mean wind speed in the MLH (Eq. (1)).

Theoretically, the mean wind speed in the MLH should be calculated by integrating wind speed at different heights of the MLH (Huang et al., 2018) . In this work, wind speed at the surface was used to replace the mean wind speed in the MLH in the Eq. (1) due to the absence of wind speed at different height. At a given dispersion coefficient, the normalized PM 2.5 concentration can be calculated by Eq.

(2) and could be used to assess the impact of dispersion condition on PM 2.5 growth.

where, C DN,i (μg/m 3 ) and C i (μg/m 3 ) is the dispersion coefficient normalized PM 2.5 mass concentration and the measured PM 2.5 mass concentration during period i, DC i (m 2 /sec) is the corresponding dispersion coefficient during period i, and DC mean (m 2 /sec) is the average dispersion coefficient for a long period, DC mean during the COVID-19 lockdown period in 2020 and the same period in 2019 was 806 and 862 m 2 /sec. Noted that surface wind speed and mean wind speed in MLH can generate large discrepancy in dispersion coefficient, however, in Eq. (2), both DC i and DC mean are calculated using the surface wind speed, thus, it will not have a significant impact on the C DN,i .

The normalized particulate concentration was originally used to eliminate the meteorological effects, thereby making the relative impact of the various emission sources observable (Kleinman et al., 1976) . At polluted period when DC i is low, the measured PM 2.5 mass concentration is generally much high due to the poor dispersion. Thus, we scale the concentrations down to that they would have had if the MLH and wind speed were equal to the mean DC value. During the clean period when DC i is high, the normalized PM 2.5 mass concentration will be scaled upward.

In this work, the thermodynamic model ISORROPIA-II (Nenes et al., 1998) growth. By comparison, PM 2.5 reduction in Shijiazhuang, Jinan and Zhengzhou was obviously larger than other cities, which may explain the O 3 increase in these cities.

In Tianjin, NO 2 and SO 2 mass concentration all showed a drop at different polluted levels during the COVID-19 lockdown period than the same period in 2019 (Fig. S3) . On the contrary, O 3 displayed a slight increase at all polluted levels during the COVID-19 lockdown period and PM 2.5 was comparable in these two periods. The wind dependent map showed that SO 2 in the northeast obviously decreased (Fig. S4) , which may due to the diminution of pollutant transport in the northeast, such as from Tangshan, a city owns heavy industry. NO 2 and CO reduction mainly occurred companied by the wind speed lower than 2.0 m/sec, implying that NO 2 and CO reduction mainly came from local emission reduction such as vehicle emission.

Lockdown among global cities provided an unprecedented opportunity to investigate environmental restoration process, global analyzation in air quality changes in the pandemic has drawn much attention ( showed an opposite variation (Chu et al., 2020; Pei et al., 2020) . In northern China, emissions from residential heating and major industries were uninterrupted during the COVID-19 lockdown, which may offset the NO x reduction from traffic emission. PM 2.5 also varied by different degrees with much reduction in southern China while less reduction or even increase in northern China (Chu et al., 2020) . The United States (US), India, and Europe are the regions with much higher COVID-19 infections, recommended rather than mandatory quarantine measures were implemented in these areas. In India, the maximum reduction was in particulate matters (Mahato et al., 2020; Sharma et al., 2020) . By the contrary, in US, NO 2 was witnessed the most significant decline, whereas PM 2.5 was observed with little decrease (Berman and Ebisu, 2020; Zangari et al., 2020) , indicating the different atmospheric polluted characters in India and US. Emission reduction in Brazil and Spain was similar with US, CO and NO 2 displayed the most significant reductions, which closely associated with vehicle emission (Baldasano, 2020; Dantas et al., 2020) . In areas where mass concentrations of particulate matter are already low, such as US and some Europe countries, it is difficult to largely reduce them even over a long period of lockdown.

As mentioned above, nationwide NO 2 decrease and O 3 increase during the COVID-19 lockdown suggested O 3 formation is highly nonlinear with NO x . Previous studies generally attributed the anticorrelation between PM 2.5 and O 3 to the solar radiation variation induced by aerosol radiative effect (Zhang et al., 2015; Wu et al., 2020) , and the particle sink for hydroperoxy radicals was also weakened as the PM 2.5 mass concentration decreased (Li et al., 2019) . Moreover, Sicard et al. (2020) and Le et al. (2020) proposed that reduction of fresh NO (Chang et al., 2020; Duan et al., 2020; Ma et al., 2019) . As shown in the Fig. 2 , O x during the COVID-19 lockdown was 9.2% averagely lower than the same period in 2019, specifically, almost no difference in O x was observed between these two periods when PM 2.5 ≤ 75 μg/m 3 . Whereas when PM 2.5 > 75 μg/m 3 , O x was 19.9% averagely lower during the COVID-19 lockdown, and was much significant in the daytime (21.5%-27.3%). Another key factor in photochemistry, solar radiation, was also observed with no obvious difference during these two periods, and was only slightly lower when PM 2.5 > 75 μg/m 3 in the COVID-19

lockdown. In the case of large drop in NO 2 and little increase in O 3 , the atmospheric oxidation capacity did not enhance that much.

Little change in PM 2.5 mass concentration in Tianjin during the COVID-19 lockdown period was partly attributed to adverse meteorological condition. During the COVID-19 lockdown period, mean MLH in daytime was 647 m, slightly lower than that in the same period in 2019 (691 m) (Fig. 3) , whereas nocturnal MLH during the COVID-19 lockdown period was higher than that in the same period in 2019. The frequency of breeze (WS < 1.5 m/sec) during the COVID-19 lockdown period increased by 16.9% while the frequency of WS with 1.5-3.5 m/sec reduced by 12.4%. In addition, WS above 50 m was also lower during the COVID-19 lockdown period, with the mean decrease was 7.8% (Fig. 4) . Accordingly, mean dispersion coefficient during the COVID-19 lockdown period (806 m 2 /sec) was lower than the same period in 2019 (862 m 2 /sec). The most noticeable change was in RH, ground mean RH during the COVID-19 lockdown period was 62% ± 23%, significantly higher than the 43%±22% during the same period in 2019, with the mean increase below 250 m was 49.2% (Fig. 4) . The temperature was 9.7% higher during the COVID-19 lockdown period. Higher temperature and RH suggested that the water vapor content was much more abundant during the COVID-19 lockdown period than the same period in 2019, which exerted an impact on the aerosol chemical composition and will be discussed in Section 3.3.

The mean measured PM 2.5 mass concentration and dispersion coefficient normalized PM 2.5 (DN-PM 2.5 ) mass concentration was 67.5 and 45.6 μg/m 3 during the COVID-19

lockdown period (Fig. 5) 

In addition to the changes in gaseous pollutants mass concentration, PM 2.5 chemical composition also showed an obvious change (Fig. 6a) . The most obvious change was the increase of NO 3 -, mean NO 3 fraction in PM 2.5 was 20.2% during the COVID-19 lockdown period compared to the 14.5% in the same period in 2019. OM, EC and Cl -, however, were observed to show a decline. In terms of the proportion of each ion in total ions, mean NO 3 -mass fraction in total ions significantly elevated, with 46.6% during the COVID-19 lockdown period (Fig. 6b) Air humidity may be an important factor on nitrate formation. Specific humidity (q, one of the indexes of absolute humidity) was calculated by the equation recommended by the extrapolated Wexler's formula (Wexler, A., 1976; Bolton, D., 1980) . As shown in Fig. 7a were much similar with NOR (Fig. S7) . Collectively, these results demonstrated that anomalously high air humidity played a key role in nitrate formation during the COVID-19

lockdown.

Formation mechanism of nitrate has drawn much of concern in recent years, yet the explicit pathways for nitrate formation were still controversial. Current consensus about nitrate formation was that: in the daytime, photochemistry dominates the formation of nitrate.

Recently, several works have demonstrated that photochemistry was active in winter polluted condition Lu et al., 2019; Tan et al., 2018) , O 3 and OH productions are sufficiently high to facilitate fast gas-phase and heterogeneous conversion of NO x to nitrate.

In the nighttime, N 2 O 5 heterogeneous hydrolysis is an important source of particulate nitrate (Wang et al., 2017a (Wang et al., , 2017b Wang et al., 2018) . Liu reported that in NCP, N 2 O 5 heterogeneous hydrolysis dominates the nighttime HNO 3 production (83.6%) and also contributed 10.1% of HNO 3 production during daytime Increased ALWC induced by 1 μg/m 3 water-soluble salts (donated as ALWC/Ion mass ) aided more hydrogen ion (H air + ) was released, thereby enhances the aerosol acidity (Fig. S8) . Mean PM 2.5 pH during the COVID-19 lockdown period was 4.5±0.4, slightly lower than the 4.8±0.6

during the same period in 2019. Reaction rates of SO 4 2production though aqueous oxidation pathways depend on the initial aerosol acidity. Sulfate production under acidic conditions is largely limited by the amount of SO 2 that can partition to the aqueous phase (Pye et al., 2020; Seinfeld and Pandis, 2016) . PM 2.5 pH drop during the COVID-19 lockdown period may inhibit the reaction rate of SO 4 2production more or less. Considering the competition between sulfate and nitrate formation for ammonia, once the sulfate formation is suppressed, the nitrate formation will be conspicuous. Aerosol pH has been reported as a major factor affect the partitioning of HNO 3 →NO 3 -, at a constant ALWC, more NO 3 was measured at higher pH (Guo et al., 2017) , similar results were also found in Tianjin of China (Shi et al., 2019) .

Setting off fireworks in some northern cities are not strictly regulated, instantaneous large emission superimposes adverse meteorological conditions will generate regional air pollution.

During the 2020SF, atmospheric dispersion condition was much worse than that in 2019 SF.

In Tianjin, mean WS and MLH in daytime in 2020 SF was 0.8 m/sec and 443 m, respectively, comparing to that 1.9 m/sec and 647 m in 2019 SF, atmospheric stratification tended to be more stable, which was extraordinarily conducive to the persistent of air pollution. The polluted period (period wherein PM 2.5 mass concentration was continuously larger than 75 μg/m 3 ) in 2020SF and 2019SF lasted for 88 and 24 hr, respectively, with mean PM 2.5 mass concentration was 186±61 μg/m 3 (peak: 333 μg/m 3 ) and 189±76 μg/m 3 (peak: 369 μg/m 3 ).

The averaged T, RH and q was 1.0℃, 72% and 2.8 k/kg in 2020SF, comparing to that -3.2℃, 44% and 1.4 k/kg in 2019SF (Fig. 9) , which was closely associated with secondary aerosol formation.

Compared to the sharp raise and drop of PM 2.5 on New Year's Eve of 2019 (4 February, 2019), no obvious PM 2.5 increase was observed on 2020 New Year's Eve (24 January 2020), the air quality deteriorated begin from noon of 25 January 2020 and the increase tendency was much mild (Fig. 9) . In early morning of 25 January, 2020, PM 2.5 mass concentration in large area was higher than 500 μg/m 3 , especially in northeastern China (Fig. S9) , the simultaneous air quality in Tianjin, however, was clean. Fig. S10 showed that air masses arriving in Tianjin had passed the northeastern China, affected by the pollutants transport, air quality in Tianjin deteriorated subsequently. Apparently, the PM 2.5 increase on 2019 New

Year's Eve was mainly attributed to the local fireworks setting offs, whereas the air pollution on the following days after 2020 New Year's Eve was mainly affected by the regional transport.

In 9 ). In the meanwhile, Cl -/CO_5h and contribution of Clalso showed an obvious upward tendency. In contrast, NO 3 -/CO_5h only slightly increased and NOR increased to 0.36 from 0.15, NO 3 contribution in ions was observed to keep constant compared to the obvious SO 4 2increase, implying that sulfate raised faster than nitrate. In the light of the obvious pollution regional transport induced by fireworks, the growth of sulfate may result from both the primary emission and aged process during the transport.

During the second accumulation stage of 2020SF (AS-II, 2020/1/26 20:00~2020/1/28 10:00), water vapor content was obviously higher than AS-I, the specific humidity and RH was higher than 3 g/kg and 85%, respectively, resulting in the ALWC increase (112±45 μg/m 3 ) compared to the 80±66 μg/m 3 during AS-I. NO 3 -/CO_5h was observed to steadily step up, NOR further increased to 0.43, NO 3 fractional contribution to total ion climbed to 49.0% from 30.0%, demonstrating the efficient conversion of nitrate formation, yet no obvious diurnal variation pattern was observed. If we scale the hourly variation rate of NO 3 mass concentration to the CO variation rate, approximately 25% NO 3 growth was attributed to the secondary transformation during the AS-II, which reached ~40% in the early morning of 28 January, 2020, wherein the corresponding NO 2 mass concentration, ALWC and specific humidity were all higher. Therefore, higher air humidity may elevate the contribution of aqueous reaction to nitrate formation in AS-II. SO 4 2-/CO_5h during the AS-II stage was observed to change slightly, variation of Cl -/CO_5h was much similar to the SO 4 2-/CO_5h.

Average fractional contribution of SO 4 2in total ions was 25.4%±1.5%, the smaller standard deviation also indicated a mild change in SO 4 2-, implying that the growth of SO 4 2mass concentration largely resulted from the accumulation.

During the COVID-19 lockdown (January 23, 2020 to March 15, 2020), PM 10 , SO 2 , NO 2 reductions in NCP was much pronounced than PM 2.5 and CO, whereas O 3 showed an upward tendency in varying degrees. Specifically, PM 10 , SO 2 , NO 2 , CO mass concentration in Tianjin reduced by 18.3%, 32.7%, 22.7% and 17.8% during the COVID-19 lockdown period compared to the same period in 2019. In contrast, PM 2.5 mass concentration only reduced by 5.6% and O 3 increased by 3.0%. Slight O 3 increase and NO 2 decrease implied that O 3 generation may be VOCs-limited in Tianjin, synergetic control of NO x and VOCs is needed.

The deteriorating meteorological condition during the COVID-19 lockdown period obscured the actual reduction of PM 2.5 . Compared to the 2019SF, air quality in 2020SF of Tianjin was much deteriorated due to the stable meteorological conditions and regional transport induced by fireworks. Here the dispersion coefficient was used to normalize the measured PM 2.5 , aiming to eliminate the adverse meteorological impact and roughly estimate the actual PM 2.5 reduction, the normalized PM 2.5 reduced by 17.7% during the COVID-19 lockdown period.

As a tracer of atmospheric oxidation capacity, O x during the COVID-19 lockdown was 9.2% averagely lower than the same period in 2019, and it was 19.9% averagely lower at polluted condition. Solar radiation was observed with no obvious difference during these two periods.

However, air humidity elevated notably, mean RH, specific humidity and ALWC was 62%, 

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. (mass ratio) and (d) PM 2.5 pH at different PM 2.5 loading levels during the COVID-19 lockdown (2020*) and the same period in 2019 (2019*). At each PM 2.5 level, the left column was the data during 2019*, the right column was the data during 2020*.

Specific humidity (q) and aerosol liquid water (ALWC) at different PM 2.5 levels. At each PM 2.5 level, the right column was the data during the COVID-19 lockdown (2020*), the left column was the data during the same period in 2019 (2019*). lockdown period (2020*) and the same period in 2019 (2019*). At each PM 2.5 level, the left column was the data during 2019*, the right column was the data during 2020*.

Specific humidity (q) and aerosol liquid water (ALWC) at different PM 2.5 levels. At each PM 2.5 level, the right column was the data during the COVID-19 lockdown (2020*), the left column was the data during the same period in 2019 (2019*). components in 2019 Spring Festival (2019/2/4~2019/2/10) and 2020 Spring Festival (2020/1/24~2020/1/29).

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