key: cord-0894447-tj690g5y
authors: Liu, Yongchun; Ni, Shuangying; Jiang, Tao; Xing, Shubin; Zhang, Yusheng; Bao, Xiaolei; Feng, Zeming; Fan, Xiaolong; Zhang, Liang; Feng, Haibo
title: Influence of Chinese New Year overlapping COVID-19 lockdown on HONO sources in Shijiazhuang
date: 2020-07-21
journal: Sci Total Environ
DOI: 10.1016/j.scitotenv.2020.141025
sha: 5a70df1db0dda7921e9996c3cdc93b15c02e6e98
doc_id: 894447
cord_uid: tj690g5y

Abstract Nitrous acid (HONO) is an important precursor of hydroxyl radical (OH) in the atmosphere. It is also toxic to human health. In this work, HONO concentrations were measured in Shijiazhuang using a Monitor for AeRosols and Gases in ambient Air (MARGA) from December 15, 2019 to March 15, 2020, which covered the heavy air pollution season, the Chinese New Year (CNY) vocation and the Corona Virus Disease-19 (COVID-19) lockdown period. During & after CNY overlapping COVID-19 lockdown, the air quality was significantly improved because of both the emission reduction and the increase in diffusion ability of air masses. The mean HONO concentration was 2.43 ± 1.08 ppbv before CNY, while it decreased to 1.53 ± 1.16 ppbv during CNY and 0.97 ± 0.76 ppbv after CNY. The lockdown during & after CNY reduced ~31% of ambient HONO along with ~62% of NO and ~36% of NO2 compared with those before CNY after the improvement of diffusion ability had been taken into consideration. Heterogeneous reaction of NO2 on ground surface dominated the nocturnal HONO sources, followed by heterogeneous reaction on aerosol surface, vehicle emission, reaction between NO and OH and emission from soil on pollution days throughout the observation. Except for elevated soil emission, other nighttime HONO sources and sinks decreased significantly during & after CNY. The relative importance of heterogeneous reaction of NO2 on surfaces further increased because of both the decrease in vehicle emission and the increase in the heterogeneous conversion kinetics from NO2 to HONO during & after CNY.

Nitrous acid (HONO) is a crucial atmospheric species because it is the vital precursor of hydroxyl radical (OH) (Alicke et al. 2003; Ren et al. 2006; Spataro and Ianniello 2014) , which is able to clean up primary air pollutants and produce secondary air pollutants in the atmosphere. Photolysis of H 2 O 2 , HCHO, O 3 and HONO and the reaction between NO and HO 2 are the major sources of OH radical in the atmosphere (Alicke et al. 2003; Volkamer et al. 2010) , whereas photolysis of HONO is the dominant primary OH source in the early morning when other OH sources are still weak (Alicke et al. 2003; Spataro et al. 2013; Tan et al. 2018; Tang et al. 2015; Volkamer et al. 2010) . Photolysis of HONO accounts for average up to 60 % of OH production in the boundary layer in some cases (Alicke et al. 2003; Elshorbany et al. 2009; Tan et al. 2018) . It has been found that HONO is capable of promoting secondary aerosols (Czader et al. 2015; Xing et al. 2019; Zhang et al. 2019a; Zhang et al. 2019c ) and ozone formation (Zhang et al. 2019a ). In addition, exposures to high concentration of HONO may damage mucous membranes and result into the respiratory system of asthmatics (Ohyama et al. 2019; Ohyama et al. 2010; Rasmussen et J o u r n a l P r e -p r o o f 4 al. 2014; Spataro and Ianniello 2014; Zhang et al. 2012a ). The HONO concentrations varied from a few pptv in remote areas (Beine et al. 2001; Gu et al. 2020; Honrath et al. 2002; Liao et al. 2006; Spataro et al. 2017; Zhang et al. 2012a; Zhou et al. 2001) to several ppbv in polluted urban environment Hu et al. 2002; Spataro et al. 2013; . In China, the concentration and budget of atmospheric HONO have also been extensively studied , such as in Beijing (Hendrick et al. 2014; Hu et al. 2002; Spataro et al. 2013; Wang et al. 2017; Zhang et al. 2019e ), Shanghai (Wang et al. 2013; Zhang et al. 2019b ), Guangzhou (Hu et al. 2002; Su et al. 2008a ), Hongkong , Ji'nan and Xi'an (Huang et al. 2017) . Overall, the HONO concentrations were higher in China than those observed in Europe and America. At the present time, direct emissions from combustion and soil, homogeneous reaction between NO and OH radical, heterogeneous reaction of NO 2 on aerosol and ground surfaces and photolysis reactions of nitrates have been identified as the major sources of atmospheric HONO (Spataro and Ianniello 2014), whereas their relative contributions depend on the location and the season.

For example, heterogeneous reaction of NO 2 was proposed to be an important HONO source in the night Zhang et al. 2019c ) and even in daytime in Beijing-Tianjin-Hebei (BTH) (Zhang et al. 2019c ), but it was unimportant compared with the unknown sources and homogeneous reaction between NO and OH in Ji'nan or compared with traffic emission on haze days in Beijing ). At the same J o u r n a l P r e -p r o o f 5 daytime HONO source, which is highly correlated with light intensity Michoud et al. 2014) , was frequently observed at various places. More and more studies proposed that it might be associated with photo-enhanced conversion of NO 2 Su et al. 2008b ) and photolysis of surface nitrate or particulate nitrates although an uncertainty may reduce their importance (Liu et al. 2019b) . These results mean that the study about atmospheric HONO budget is still far from closed, which requires a significant effort on both the HONO measurement and the determination of related kinetic parameters for its production pathways (Liu et al. 2019b ).

Shijiazhuang is one of the cities associated with heavy air pollution in China (Qin et al. 2017; Tan et al. 2019; Xie et al. 2019; Zhang et al. 2020) . Fine particulate matter (PM) pollution is more serious in Shijiazhuang than the neighboring areas such as Beijing (Cheng et al. 2019; Qin et al. 2017; Zhang et al. 2019d 114.6070º). The observation station ( Figure S1 ) is on a rooftop of the main teaching building (5 floors, ~23 m above the surface) which is around 250 m from the Zhujiang road. It is a typical urban observation station surrounded by traffic and residential emissions.

Mass concentration of PM 2.5 was measured by a beta attenuation mass monitor (BAM-1020, Met One Instruments) with a smart heater (Model BX-830, Met One Instruments Inc., USA) to control the RH of the incoming air to 35% and a PM 2.5 inlet (URG) to cut off the particles with diameter larger than 2.5 m. and ground surface (P ground ) Liu et al. 2019b; Wang et al. 2017 ). Photolysis of HNO 3 and nitrophenol were usually not considered in source budget analysis because they were believed as minor HONO sources ). The sinks of HONO include photolysis (L photolysis ), the homogeneous reaction with OH radical (L HONO-OH ), dry deposition (L deposition ) (Liu et al. 2019b ) and vertical and horizontal transport (T trans ) (Soergel et al. 2011) . Thus, the HONO budget can be calculated by, 

where is the observed change rate of HONO mixing ratios (ppbv h -1 ), P unknown is the production rate of HONO from the unknown sources.

In our previous work , the calculation methods for these terms have been discussed in detail. Briefly, the emission rate of HONO (E HONO , ppbv h -1 ) from soil and vehicle were calculated based on the emission flux (F HONO , g m -2 s -1 ) and the PBL height (H, m) according to the following equation,

where, α is the conversion factor (α = 

where, EI HONO is the emission inventory of HONO (g s -1 ), A is the urban area of Shijiazhuang (496 km 2 , measured based on Google map), EI NOx,vehicle is the emission inventory of NO x from vehicle exhaust (0.160 Gg day -1 in Shijiazhuang before CNY) (Qi et al. 2017 ). The daily mean EI NOx,vehicle was further converted into hourly mean emission inventory based on the hourly mean traffic index (www.nitrafficindex.com, Figure 2SA ) before CNY. During & after CNY, the hourly mean emission inventory of NO x was further calculated according to its reduction ratio from traffic emission (62 % which will be discussed in Section 3.1). The NO x emission inventories are shown in Figure S2B and C. The emission ratio of HONO to NO x (1.26 %) was estimated using a low limit correlation method (Li et al. 2012 ). This value is J o u r n a l P r e -p r o o f 9 very close to those derived values in Hongkong (1.20.4%, ) and 1.230.35% (Liang et al. 2017 )), Guangzhou (1.0%) (Li et al. 2012 ) and Beijing (1.17%, 1.3% and 1.41 %) Meng et al. 2019; Zhang et al. 2019e ). The F HONO, soil was calculated using the temperature-dependent emission flux of HONO from grassland with 35-45 % of water content (Oswald et al. 2013) . Homogeneous reaction between OH and NO was calculated based on the measured NO concentrations and the estimated OH concentrations in the light of second-order reaction. The second-order reaction rate constant (k NO-OH ) is 7.210 -12 cm 3 molecule -1 s -1 (Li et al., 2012) . The daytime OH concentration was estimated according to (4)

where, J O1D and J NO2 are the photolysis frequency of O 3 and NO 2 (s -1 ), respectively, c OH and c NO2 are the concentration of OH and NO 2 (molecules cm -3 ), respectively. The J O1D , J NO2 and J HONO (photolysis frequency of HONO) were calculated using the hourly mean solar zenith angle, the longitude and latitude of the observation station under clear sky condition using a box model, then calibrated according to the measured UV light intensity ).

The nighttime OH concentration was assumed to be 1. 

where, k het is the quasi first-order reaction rate constant for heterogeneous conversion from NO 2 to HONO (s -1 ), c HONO,corr is the corrected HONO concentration after the HONO emitted from vehicle exhaust has been subtracted (ppbv), 2 ̅̅̅̅̅̅ is the mean NO 2 concentration from t 1 to t 2 . The calculated nighttime k het was 0.0160.006 h -1 from December 15, 2019 to March 15, 2020, which is comparable with those derived in urban environment such as Guangzhou (0.016 h -1 ), Milan (0.012 h -1 ) and Kathmandu (0.014 h -1 ), and higher than that in Ji'nan (0.00680.0045 h -1 ) Xu et al. 2015) . Interestingly, the nighttime k het before CNY was 0.0120.005 h -1 , which was significantly lower than that during and after CNY (0.0170.003 h -1 , P<0.05). Therefore, the production rates of HONO from heterogeneous reaction in different periods were calculated using the corresponding k het . The contributions of aerosol and ground surfaces to heterogeneous conversion from NO 2 to HONO were further calculated based on the measured surface area to volume ratio of aerosol (S a, 0.00170.0013 m -1 ) and the estimated ground surface to volume ratio (S g, 0.00430.0018 m -1 ) according to,

The loss rates of HONO by photolysis (L photolysis ), homogeneous reaction with OH radicals (L HONO-OH ) and dry deposition (L deposition ) (Liu et al. 2019b) were calculated according to the following equations.

Where, J HONO is the photolysis rate of HONO (s -1 ), k HONO-OH is the second-order reaction rate constant between HONO and OH (610 -12 cm 3 molecule -1 s -1 ) ( 

where k dilution is a dilution rate (0.23 h −1 , including both vertical and horizontal transport) (Dillon et al. 2002) , c HONO and c HONO , background is the HONO concentration at the observation site and background site, respectively (Dillon et al. 2002) . In this work, the lowest nighttime HONO concentration was taken as the c HONO , background .

3.1. Overview of the air quality during observation. Figure 1 shows the time series of selected parameters including the concentrations of PM 2.5 , CO, NO x and HONO ( Figure 1A and B) and the meteorological parameters such as temperature, pressure, wind speed, wind direction and PBL height ( Figure 1C and D) during the observation. The CNY vacation from January 23 to February 2 was highlighted by the light purple column. The temperature increased gradually and the pressure varied from 998 to 1034 hPa during the whole J o u r n a l P r e -p r o o f 12 observation ( Figure 1C ). Before and during CNY, the frequency of stagnant whether conditions characterized by low wind speed and low PBL height was higher, while the UV light intensity was lower than those after CNY ( Figure 1D ). Five light precipitations occurred on December 15, 2019, February 14 and 15, 24 and March 8, 2020. These datasets will be ruled out in following discussion.

Six pollution events before CNY, one during CNY and another six after CNY overlapping the COVID-19 lockdown were identified according to the concentration of PM 2.5 ( Figure 1A ). After strong wind (regardless of wind direction) accompanied with relatively high PBL height cleaning up the air masses ( Figure 1D ), a pollution episode gradually built up with a typical duration of 3~5 days. Interestingly, the PM 2.5 concentration well kept pace of the reciprocal of the PBL height ( Figure S4A ), in particular, before CNY. This means that the sources of PM 2.5 should be quite stable and the mass loading of fine PM should be greatly determined by the diffusion ability of air masses in Shijiazhuang. As shown in Figure 1A , the high PM 2.5 concentration usually coincided with the high RH (>50%) which is favorable of heterogeneous conversion of gas phase precursors (Hodas et al. 2014; Wang et al. 2016; Wu et al. 2019 ). In addition, the PM 2.5 evolved synchronously with CO, especially, before CNY.

These results mean that both secondary production and primary emissions contribute to PM 2.5 accumulation in Shijiazhuang.

Before CNY, the hourly mean PM 2.5 concentration varied from 7 to 403 g m -3 with a mean value of 137.985.8 g m -3 (Figure 2A ). 70.3 % of hourly PM 2.5 concentration was higher than the daily mean air quality standard of China (75 g m -3 ) before CNY. This indicates the serious air pollution in Shijiazhuang when compared with other cities, such as J o u r n a l P r e -p r o o f from January 22 to February 1. Although the maximum PM 2.5 concentration during CNY was lower than that before CNY, the mean PM 2.5 concentration (173.9 72.7 g m -3 ) was higher than that before CNY because of the long-term favorable metrological conditions for pollutants accumulation including high RH ( Figure 1A ), low wind speed and low PBL height ( Figure 1D ). After CNY, pollution event still happened frequently. However, both the mass concentration of PM 2.5 and the frequency of pollution event decreased significantly because of both the reduction of primary emission (indicated by CO, Figure 1A ) and the increase in wind speed and PBL height ( Figure 1D ). The mean concentration of PM 2.5 was 76.7 61.4 g m -3 , and 36.1 % of hourly mean PM 2.5 concentration were higher than 75 g m -3 after CNY.

From the point view of chemical composition, the fraction of both nitrate and sulfate increased during and after CNY compared with that before CNY ( Figure S5 ). Figure S4A ). This implies that reduction of traffic emission should be prominent during CNY, while both traffic and industry sectors contribute to the emission reduction after CNY overlapping COVID-19 lockdown. In addition, higher conversion ratios of nitrate (NOR) were observed during (0.440.11) and after CNY (0.290.17) compared with that before CNY (0.170.10) ( Figure S6 ). The above results mean that air quality was greatly improved, while chemical conversion of the precursors to PM was slightly enhanced during and after CNY overlapping COVID-19 lockdown when compared with the counterpart. Figure 1B 

Hongkong , Ji'nan ) and Xi'an (Huang et al. 2017 ) as summarized in Table 1 , while it was close to these previous observations performed in Beijing (Zhang et al. 2019e ) and Shanghai (Cui et al. 2018 Figure 2E ). The reduction ratio was ~31% after the improvement of diffusion ability of air masses was subtracted. J o u r n a l P r e -p r o o f before CNY. This might be related to the weak increase in PBL height during & after CNY compared with that before CNY ( Figure 3O and P). It should be noted that the mean nighttime and daytime HONO/NO 2 ratio were 0.0950.051 and 0.0750.053, respectively, throughout the observation. These values are in the range of the reported HONO/NO 2 in literatures (Elshorbany et al. 2009; Huang et al. 2017; Liu et al. 2014; Tong et al. 2015 ), but at a high level end. Interestingly, the HONO/NO 2 ratio on both clean days and polluted days during & after CNY were slightly higher than the counterpart. This implies that chemical conversion from NO 2 to HONO should be more effective during & after CNY compared with that before CNY. These results also mean that the relative contribution of HONO sources should have changed in different periods. Figure 4 compared the budget of HONO before CNY with those during & after CNY on pollution days (with PM 2.5 concentration > 50 g m -3 and RH <90%). Table S1 summarized the mean intensities of these sources and sinks. Overall, the nighttime sources were comparable with the sinks in different periods, while significant underestimation of the sources presented in the daytime. Besides the possible unknown HONO sources, a possible reason might be related to the variation of PBL height. When we calculated the HONO sources, heterogeneous conversion from NO 2 to HONO and emissions from vehicle and soil were dependent on PBL height according to Equations (2) and (7). If these sources were more sensitive to surface HONO concentration ( Figure S4B ) than NO 2 , the increase in PBL height in daytime should underestimate their contribution to HONO sources. On the other hand, OH J o u r n a l P r e -p r o o f 20 concentration was estimated based on J O1D and J NO2 . Although the calculated OH concentrations were comparable with that observed in Beijing (Tan et al. 2018) , the uncertainty of OH concentration might also contribute the underestimation of HONO sources.

In addition, light-enhanced heterogeneous reactions on both aerosol ) and

ground surfaces have not been considered in this work. This might lead to the observed underestimation. Actually, the contribution of photolysis of nitrate became prominent at noontime, in particular, during & after CNY. This decreased the fraction of the unknown HONO sources. In the following section, we will mainly concentrate on the nighttime HONO sources. However, the unknown sources will also be taken into consideration when calculating the relative contributions if the total sinks is over the total sources.

In the night, heterogeneous reaction of NO 2 on ground surface was the largest HONO source, followed by heterogeneous reaction on aerosol surface, vehicle emission, homogeneous reaction between NO and OH and soil emission in the whole observation period (Figure 4 ). Emission from soil was a minor HONO source during our observation due to the low temperature. E soil varied from 0.00044 to 0.0091 ppbv h -1 , with a mean value of 0.00260.0014 ppbv h -1 throughout the observation. It was slightly higher during & after CNY (0.00310.0016 ppbv h -1 ) than that before CNY (0.00200.0008 ppbv h -1 ) because of the increase in temperature ( Figure 1C ). and 14.75.9% (CNY&ACNY) to HONO sources. These relative contributions were close to that in Ji'nan (12%-21%) , while they were much lower than that in Beijing (~50 %) Meng et al. 2019; Zhang et al. 2019e ). This can be well explained by the fact that the vehicle population in Shijiazhuang is much smaller than that in Beijing Except for E soil (increased 50%), the reduction ratio of all other sources and sinks ranged from 33% to 88% in the night during & after CNY when compared with that before CNY as shown in Table S1 . In the daytime, besides E soil , P nitrate and L HONO-OH increased 18 % and 67 %, respectively, whereas other sources and sinks decreased from 40% to 68%. The increase of E soil was related to increase in temperature, while it was related to increase in irradiation intensity for P nitrate and increase in OH concentrations for L HONO-OH . In the night, vehicle related sources (E vehicle and P NO-OH ) were the mostly influenced sources, while heterogeneous conversion (in particular, on ground surface) were less affected by the reduction of anthropogenic activities during and after CNY overlapping COVID-19.

Therefore, this led to an increased relative contribution of heterogeneous reaction on ground and aerosol surfaces in the night (Figure 4 ). This is consistent with the good correlation between HONO concentrations and NO, NO 2 and PM 2.5 concentrations as shown in Figure   S7 .

As pointed above, the k het during & after CNY (0.0170.003 h -1 , P<0.05) was significantly higher than that before CNY (0.0120.005 h -1 ). We further derived the uptake coefficient of NO 2 ( NO2 ) on both aerosol and ground surfaces according to, 

where, S is the total surface to volume ratio of ground and aerosols (S g + S a , m -1 ),  is the J o u r n a l P r e -p r o o f 23 mean velocity of NO 2 molecules, R is the ideal gas constant, T is the temperature (K), M is the molecular weight of NO 2 (kg mol -1 ). Figure 5A compared the derived nighttime  NO2 before CNY with that during & after CNY. It was 6.439.0210 -6 before CNY, which is significantly (P<0.05) lower than 1.201.7610 -5 during & after CNY. These values are larger than that derived in Ji'nan (1.42.410 -6 ) ) and the laboratory values (510 -9 -9.610 -6 ) on different particles (Ndour et al. 2009; Underwood et al. 1999; Underwood et al. 2001 As shown in Figure 5B , the  NO2 is well negatively correlated with the reciprocal of temperature (ln NO2 =-2.4610 3 /T-2.69, R=0.92). This means the conversion from NO 2 to HONO requires to overcome an apparent activation energy (20.5 kJ mol -1 

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Shuangying Ni contributed equally to this work and should be considered first coauthors. Yongchun Liu: Conceptualization, Methodology, Data curation, Writing-Original draft preparation; Shuangying Ni: Conceptualization, Methodology, Investigation, Writing-Original draft preparation

Xiaolei Bao: Conceptualization, Methodology, Data curation, Investigation, Resources and Writing-Original draft preparation; Zeming Feng: Investigation and Data Curation; Xiaolong Fan: Investigation and Data Curation; Liang Zhang: Investigation and Data Curation