Declining precipitation acidity from H2SO4 and HNO3 across China inferred by OMI products

Atmospheric Environment 224 (2020) 117359

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Atmospheric Environment journal homepage: http://www.elsevier.com/locate/atmosenv

Declining precipitation acidity from H2SO4 and HNO3 across China inferred by OMI products Xiuying Zhang a, *, Limin Zhao a, b, Junfeng Xu c, Dongmei Chen d, Xiaodi Wu a, Miaomiao Cheng e a

International Institute for Earth System Science, Nanjing University, Nanjing, 210023, China Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing, 210023, China c Institute of Remote Sensing and Earth Science, Hangzhou Normal University, Hangzhou, 311121, China d Department of Geography and Planning, Queen’s University, Kingston, ONK7L 3N6, Canada e State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Science, Beijing, 10012, China b

H I G H L I G H T S

� Eastern China has higher PA than Western China. � PA in China is mainly contributed from SO24 deposition. � PA reaches the maximum in 2007 in eastern China, while in 2012 in western China. � The PA values in NC, PRD, and SCB decreased, but slightly increased in YRD. A R T I C L E I N F O

A B S T R A C T

Keywords: Precipitation acidity OMI SO2 and NO2 columns China

The long-term trend of precipitation acidity (PA) resulting from H2SO4 and HNO3 is analysed across China from 2005 to 2016 based on Ozone Monitoring Instrument (OMI) SO2 and NO2 columns, measured precipitation amounts, and ground measurements of SO24 and NO3 concentrations in precipitation. PA showed substantial variations across China, exhibiting an average of 0.88 keq ha 1 yr 1 in 2016. The spatial variation in SO24 deposition than that in NO3 deposition was closer to the spatial variation in PA, contributing 78.7% of the PA throughout China. Eastern China had significantly higher PA values than western China with four hotspots in the Yangtze River Delta (YRD) and Pearl River Delta (PRD), northern China (NC) and the Sichuan Basin (SCB). In eastern China, the PA values increased by 5.0% between 2005 and 2007 and then decreased by 34.3% in 2016, while the PA values in western China increased by 14.7% between 2005 and 2012 and then decreased by 2.0% in 2016. For the four hotspots, the SO24 to NO3 ratio (S/N) decreased; moreover, the PA decreased in NC, PRD and SCB but slightly increased in the YRD.

1. Introduction Nitrogen dioxide (NO2) and sulphur dioxide (SO2) are the main precursors of acid rain in the atmosphere. The increased acid deposition and the subsequent precipitation acidity (PA) both directly and indi­ rectly influence the ecological environment (Bouwman et al., 2002; Vet et al., 2014). This situation is particularly true in China due to its rapid industrial development and urbanization in recent years (Bouwman et al., 2002; Guo et al., 2010; Vet et al., 2014; Yang et al., 2015). Therefore, it is important to accurately quantify wet SO24 and NO3 deposition and the induced acidity across China.

A series of policies have been implemented by the Chinese govern­ ment since the 1980s to control acid pollution and improve air quality. A policy for controlling and decreasing SO2 emissions was proposed at the start of the 9th Five-Year Plan. However, no obvious improvement in acid rain was achieved; this was attributable mainly to rapid industrial development and increased NOx emissions contributing more than decreased SO2 to PA (Tang et al., 2010; Zhao et al., 2009). Therefore, policies were enacted to jointly reduce SO2 and NOx emissions in the 12th Five-Year Plan. These policies and the corresponding actions decreased SO2 emissions after 2006 (Duan et al., 2016; Fang et al., 2013) and NOx emissions after 2012 at the national scale (Wang et al., 2014).

* Corresponding author. E-mail addresses: [email protected], [email protected] (X. Zhang). https://doi.org/10.1016/j.atmosenv.2020.117359 Received 2 October 2019; Received in revised form 11 February 2020; Accepted 15 February 2020 Available online 18 February 2020 1352-2310/© 2020 Elsevier Ltd. All rights reserved.

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However, the resulting inconsistent trends of SO2 and NOx emissions changed the PA composition from being SO24 -dominated to NO3 -dominated (Wang and Xu, 2009). Compared with ground measurements of wet acid deposition, sat­ ellite remotely sensed data have the advantages of global coverage and long-term monitoring (Zhang et al., 2018a; Zyrichidou et al., 2013). Numerous satellite sensors, such as the Global Ozone Monitoring Experiment-2 (GOME 2)/European Remote-Sensing Satellite-2 (ERS-2), Scanning Imaging Absorption Spectrometer for Atmospheric Chartog­ raphy (SCIAMACHY)/Environmental Satellite (ENVISAT), and Ozone Monitoring Instrument (OMI)/Aura sensors, provide both SO2 and NO2 columns. These data products have been used to evaluate the effects of related policies on the spatiotemporal variations in atmospheric SO2 and NO2 concentrations (de Foy et al., 2016; Krotkov et al., 2016; Lamsal et al., 2015; Song and Yang, 2014; van der A et al., 2017). Although it was noted that SO2 and NO2 columns could reflect variations in the SO24 and NO3 concentrations in precipitation (Zhang et al., 2012), changes in wet acid deposition have rarely been studied using remotely sensed data. Atmospheric NO2 and SO2 columns have been used to estimate bulk NO3 and wet SO24 depositions across China (Liu et al., 2017; Zhang et al., 2018c). The rationale behind these studies is that NO2 reacts with O2 to produce NO3 and then N2O5, both of which are soluble and diluted by precipitation (Barrie, 1985). Similarly, the principle leveraged to use SO2 columns to estimate wet SO24 deposition is based on the chemical reaction between SO2 and SO24 (Seinfeld and Pandis, 1998). The scav­ enging effect on nitrate (N) and sulphate (S) compounds occurs at the top precipitation height, which should be used to calculate the deposi­ tion of NO3 and wet SO24 (Racette et al., 1996); however, it is not easy to simulate precipitation height. Accordingly, studies conducted to es­ timate the deposition of both NO3 and SO24 with precipitation using OMI products used tropospheric SO2 and planetary boundary layer (PBL) NO2 columns. This approach is a valid alternative mainly because the related N and S components deposited with precipitation are within primarily the PBL (Wang et al., 2019b). Hence, the use of SO2 and NO2 columns to estimate NO3 and SO24 deposition from remotely sensed data provides the potential to study the temporal variations in PA. The purpose of this study is to detect the long-term PA changes resulting from H2SO4 and HNO3 across China from 2005 to 2016 using OMI SO2 and NO2 columns. First, the models for estimating the yearly wet SO24 and NO3 depositions across China are constructed based on PBL SO2 and NO2 columns and precipitation amounts; second, the spatial variations in the combined acidity resulting from H2SO4 and HNO3 in precipitation are studied; third, the long-term trends of PA are evaluated; and finally, the spatial variations in the PA changes and the long-term PA trends at hotspots are evaluated.

SO2 exists mostly in the PBL. SO2 was retrieved using principal component analysis (PCA) in regions with no significant SO2 for capturing radiance (Li et al., 2013). Although some studies have shown that PCA-based SO2 columns exhibit systematic errors for sources located at high elevations and that the observations provided by multi-axis differential optical absorption spectroscopy (MAX-DOAS) in Beijing are higher than the PCA SO2 retrievals (Fioletov et al., 2016; Yan et al., 2016), this SO2 product has the potential to detect regional SO2 emissions and pollution (Krotkov et al., 2016; Li et al., 2017). The SO2 retrievals contained some outliers due to noise in the measured radiance data; therefore, these outliers were first removed from the daily SO2 columns according to the criteria suggested by the OMI product manual. Then, negative values were removed from the daily measurements, which were then combined into one data set within one month. There were only one or several pixel gaps in the SO2 columns from February to October; thus, an inverse distance weighting method was used to estimate the SO2 values in the gaps. No data were available in the areas north of 43.8� N in December and north of 45.9� N in November and January; consequently, the values from the regions adjacent to these areas were used to fill the gaps that existed. 2.2. Ground measurements of SO24 and NO3 concentrations in precipitation Ground measurements of SO24 and NO3 depositions in precipitation were used to construct and assess the acid deposition models. Precipi­ tation samples were collected at 60 sites from 2005 to 2016. The amount of precipitation was measured when the samples were collected, and the concentrations of SO24 and NO3 were subsequently measured using ion chromatography. The sample acquisition, chemical analyses, and related data assurance and quality control procedures were conducted based on the routine acid precipitation monitoring technique (HJ/T165, 2004). According to this standard, each sample was measured more than three times; the relative standard deviation was less than 5% for each ion, and the relative bias was lower than 10% (Li et al., 2019). The observation stations were unevenly distributed, with many more stations located in eastern China (EC) than in western China (WC) (Fig. 1). The “Hu Line,” which stretches from Heihe in northeastern China to Tengchong in southwestern China, was utilized to divide China into EC and WC (Shan, 2009). EC and WC have similar area sizes but exhibit striking contrasts in their population and economic development (Wang et al., 2019a). The long-term trends of PA were further compared in these two regions to determine the influences of human activities on the observed PA variations. The annual wet SO24 and NO3 depositions were summed by the depositions for each precipitation event within the year. Since only a few

2. Materials and methods 2.1. Tropospheric NO2 and SO2 columns from the OMI The OMI sensor on board the Aura satellite is a nadir-oriented, UV–visible spectrometer (Levelt et al., 2006). The OMI NO2 and SO2 column products from January 1, 2005 to December 31, 2016 across China were used to estimate wet NO3 and SO24 depositions in this study. The NO2 column data (v2.0) have a spatial resolution of 0.125� � 0.125� and units of molec. cm 2 (http://www.temis.nl/). This version of the NO2 column product was retrieved by the improved Dutch OMI NO2 (DOMINO) algorithm based on improved air mass factors and a correction for across-track stripes (Boersma et al., 2011). The product was demonstrated to have relatively low errors in urban regions and high errors in remote areas, but the error is generally within �20% (Lamsal et al., 2014). The level-3 total SO2 column density data have a spatial resolution of 0.25� � 0.25� and are expressed in Dobson units (DU). The PBL SO2 product consists of total column retrievals based on the assumption that

Fig. 1. Spatial distribution of the stations with ground measurements of SO24 and NO3 concentrations. 2

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sites had collected all of the samples from 2005 to 2016, 270 data of annual wet SO24 and NO3 depositions were acquired. Among them, 216 data sets (80% of the total number of annual acid depositions) were randomly selected to construct the acid estimation models, while the remaining data were used to assess the performances of the constructed models. The determination coefficient (R2) of the simulated model, the correlation coefficient (R) between the estimations and observations, and the root mean square error (RMSE) were used to indicate the per­ formances of the constructed models.

fixed error derived from the long-term measurements, and NA is Avo­ gadro constants, which is equal to 6.02 � 1023. A value of 100 was used to convert the units of C/NA into mol ha 1 yr 1. The parameters W and ε were estimated using a linear least-squares method based on the ground observations of wet deposition, the pre­ cipitation amount, and the SO2 or NO2 columns for the pixel where the ground measurement was located. The statistical significance of the resulting linear relationship was assessed using the F-test, and the sig­ nificance levels of W and ε were assessed using the t-test. When sulphates and nitrates are entrained into precipitation, they form acidic ions. The PA value was calculated as follows:

2.3. Precipitation amounts

PA ¼ WDS � 2 =1000 þ WDN =1000

The daily precipitation amounts at the 824 stations across China can be downloaded at http://data.cma.cn/. The annual precipitation was calculated by summing all the data within one year, after which the gridded annual precipitation across China was obtained using thin-plate smoothing splines (Hutchinson, 1995). The simulated spatial distribu­ tions of precipitation from 2005 to 2016 had a spatial resolution of 0.25� � 0.25� .

where PA has units of keq ha 1 yr 1 and WDS and WDN are the SO24 and NO3 depositions, respectively. A value of 1000 was used to convert mol ha 1 yr 1 into keq ha 1 yr 1. 3. Results and discussion 3.1. Assessment of the annual SO24 and NO3 deposition accuracy

SO24

2.4. Estimation of annual wet and NO3 depositions and calculations of precipitation acidity

The constructed models and scatter plots of the estimated and measured wet SO24 and NO3 depositions are shown in Fig. 2. The wet SO24 and NO3 depositions showed significant correlations with the precipitation amount and the SO2 and NO2 columns (Fig. 2(a) and (b)). The constructed models were statistically significant at the 0.01 level (p < 0.01) with R2 values of 0.66 and 0.65 for the wet SO24 and NO3 de­ positions, respectively. These results indicate that the constructed models are reliable for estimating both SO24 and NO3 depositions. Additionally, the precipitation presented similar scavenging effects on the SO24 and NO3 columns with similar correlation coefficients (0.29 for SO24 deposition and 0.23 for NO3 deposition) for the constructed models. The average estimated wet SO24 deposition for the data used to assess the performance of the constructed model was 450.80 mol ha 1 yr 1, close to the ground observation of 422.39 mol ha 1 yr 1. Similar

The wet SO24 and NO3 deposition (WD) was estimated by: WD ¼ W � P � C

(3)

(1)

where W is the scavenging ratio, P is the precipitation amount in mm yr 1, and C indicates either the SO2 or the NO2 concentration in the atmosphere (Sakata et al., 2006), that is, the tropospheric SO2 and NO2 columns (1013 molec. cm 2 yr 1) in this study. To use the NO2 and SO2 columns to estimate wet acid deposition, equation (1) was changed to: � � �� C WD ¼ W � P � (2) þε 100 � NA where WD represents the wet SO24 or NO3 deposition derived from the ground measurements in mol ha 1 yr 1, ε includes the random error and

Fig. 2. Constructed models of the wet (a) SO24 and (b) NO3 depositions based on 80% of the ground measurements of SO24 or NO3 depositions, OMI PBL SO2 or NO2 columns, and precipitation amounts derived from ground measurements (black points) and scatter plots of the OMI-derived and groundmeasured wet (c) SO24 and (d) NO3 de­ positions (purple points) using the remain­ ing 20% of ground measurements. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)

3

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results were obtained for the NO3 depositions (342.93 and 314.07 mol ha 1 yr 1, respectively, for the estimated and ground-measured de­ positions). Furthermore, the estimated wet depositions had strong linear correlations with the observations (R ¼ 0.88 and RMSE ¼ 147.20 mol ha 1 yr 1 for the wet SO24 depositions and R ¼ 0.83 and RMSE ¼ 149.37 mol ha 1 yr 1 for the wet NO3 depositions). These results indicate that the constructed models are capable of obtaining reliable estimations of SO24 and NO3 depositions, but these models overestimate the values on the national scale. Ten stations with more than 6 years of observations were selected to test whether the estimations could reflect the long-term trends of the observed wet SO24 and NO3 depositions. Significant correlation co­ efficients were discovered between the estimated and observed acid depositions at all five sites in EC (Fig. 3). For WC, the wet SO24 and NO3 deposition estimates were significantly correlated with the observations at four sites; however, a non-significant correlation was found at station XJ due to the SO24 and NO3 depositions (only 75.45 and 25.20 mol ha 1 yr 1, respectively) that were much lower than the average ground ob­ servations across China (477.40 and 332.28 mol ha 1 yr 1, respec­ tively). Since the OMI products contained relatively high uncertainties in the regions possessing low SO2 and NO2 levels (Zhang et al., 2018b), the constructed models for estimating the SO24 and NO3 depositions did not perform well in such areas. These results reveal that although the constructed models could perform well in reflecting the long-term trends of the observed wet SO24 and NO3 depositions in both EC and WC, the models indeed demonstrate higher uncertainties in WC than in EC.

River Delta (PRD), which were both connected to a large area with PA values exceeding 2.0 keq ha 1 yr 1. This large area with PA values higher than 1.0 keq ha 1 yr 1 extended west to the highly populated Sichuan Basin (SCB) and north to northern China (NC) and northeast China. These hotspots were also reported by previous studies (Larssen et al., 2006; Liu et al., 2016c, 2016d). For most of WC, the PA values were lower than 0.5 keq ha 1 yr 1. The SO24 and NO3 depositions averaged 0.69 and 0.19 keq ha 1 1 yr , respectively, across China in 2016, and both showed higher values in EC than in WC. The spatial variation in SO24 deposition was similar to that in PA and contributed 78.7% to the observed PA. To assess the estimated contributions of SO24 and NO3 depositions to PA, the average contributions of the SO24 to NO3 ratio (S/N) were calculated at the sites with ground observations and estimations, and the two averages were close (3.15 and 3.27, respectively). This result indicates that the esti­ mated S/N values could be used to reflect the same ratio of ground measurements. The contribution of S/N to PA across China averaged 3.45 and showed strong spatial variations (Fig. 4(b)). High contributions from SO24 depositions were observed mainly in southeastern China and northeastern China, while the remaining areas had relatively low con­ tributions. Comparing the spatial variations in the contributions of SO24 and NO3 to PA, the average S/N value in WC was 2.57, which was much lower than that of 4.46 in EC. 3.3. Temporal variations in precipitation acidity across China from 2005 to 2016 The annual averages of the PA and of the SO24 and NO3 depositions from 2005 to 2016 in EC and WC are described in Fig. 5. All three values in 2009 in both EC and WC were obviously lower than those in their neighbouring years, mainly due to the relatively low SO2 and NOx concentrations and precipitation amount in that year (Fig. S2). A global financial crisis occurred in 2007–2008, stunting industrial development and decreasing SO2 and NOx emissions. The rate of increase in the value added by industry (VAI) in 2009 was much lower than the rates in 2008 and 2010 (http://www.stats.gov.cn/tjsj/ndsj/). The relatively low vi­ talities of industrial activity reduced the SO2 column in 2009 (0.32 DU), while the averages for both 2007–2008 and 2010–2011 were 0.35 DU. Furthermore, the precipitation amount in 2009 was lower than the average (581 mm) from 2005 to 2016 (Fig. S2). Both the low atmo­ spheric SO2 and NO2 concentrations and the low precipitation amount resulted in low SO24 and NO3 depositions and small PA values in 2009. Increases in PA and in the SO24 and NO3 depositions were also discovered in 2016 following decreasing trends preceding 2016. These increases were caused mainly by a high precipitation amount (684 mm) since the SO2 and NO2 columns in 2016 were lower than those in 2015 (Fig. S2). If the data in 2009 were not considered, the trends of the PA and the SO24 and NO3 depositions in both EC and WC presented parabolic curves. In EC, the years of the peak PA and the peak SO24 and NO3 depositions were in 2007, 2007, and 2012, respectively. The inconsis­ tent changes in SO24 and NO3 depositions resulted first in an increase in PA of 5.0% from 2005 to 2007 and then in a decrease of 34.3% in 2016 compared with the peak year. The trends of the PA and the SO24 and NO3 depositions reflected the improvements in acid pollution achieved by the implementation of air quality policies. The 11th Five-Year Plan proposed a clear aim of reducing the SO2 emissions in 2010 by 10% of those in 2005; consequently, a series of measures were taken, including the closure of small power generating units and inefficient industrial facilities and equipping 82.6% of thermal power plants with flue-gas desulphurization (FGD) technology (Ministry of Environmental Protection of the People’s Republic of China, 2011). These actions have decreased SO24 deposition in EC since 2007. However, although the 11th Five-Year Plan declared that the increasing tendency of NOx should be controlled, no specific objective was established to decrease NOx emissions. Subsequently, the 12th Five-Year Plan proposed to

3.2. Spatial distribution of precipitation acidity across China The PA values in 2016 ranged from 0.29 to 4.11 keq ha 1 yr 1 with an average and standard deviation of 0.88 and 0.65 keq ha 1 yr 1, respectively (Fig. 4). The PA was higher in EC than WC, taking the Hu Line as an obvious differentiator. Considering the processes responsible for transforming SO2 and NOx emissions into SO24 and NO3 depositions with precipitation, PA was determined by the spatial variations in the SO2 and NO2 concentrations and precipitation amount. The precipita­ tion amount decreased gradually from southeastern China to north­ western China (Fig. S1), which resulted in higher PA values in the former than in the latter. The average PA in EC was 1.54 keq ha 1 yr 1, which was approximately three times that in WC (0.50 keq ha 1 yr 1). More­ over, as the main source of SO2 and NOx emissions, the amount of coal consumed in EC in 2016 was 3.52 � 1012 kg, which was approximately five times that in WC (http://www.stats.gov.cn/tjsj/ndsj/). In EC, hotspots occurred in the Yangtze River Delta (YRD) and Pearl

Fig. 3. Correlation coefficients between the OMI-derived and observed SO24 and NO3 depositions at ten sites in China. 4

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Fig. 4. Spatial distribution of the OMI-derived (a) PA, (b) contribution of S/N to PA, (c) SO24 deposition, and (d) NO3 deposition in 2016 across China.

Fig. 5. Temporal variations in the OMI-derived annual averages of PA and the SO24 and NO3 depositions across China from 2005 to 2016: (a) PA in EC, (b) SO24 and NO3 depositions in EC, (c) PA in WC, and (d) SO24 and NO3 depositions in WC.

jointly reduce NOx and SO2 emissions in 2015 compared with those in 2010 and particularly aimed to reduce SO2 and NOx emissions by 12% and 13%, respectively, in the 13 key regions in 2015. For this purpose, selective catalytic reduction (SCR) equipment was required for

installation, and stricter emission standards for traffic were imple­ mented (Liu et al., 2016a; Wu et al., 2017). These actions have decreased NO2 emissions since 2012 and have continued to decrease SO2 emissions throughout EC (van der A et al., 2017). 5

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In WC, the years of peak PA and of the peak SO24 and NO3 de­ positions were 2012, 2011, and 2012, respectively, which were later than those in EC. The increases in SO24 and NO3 depositions from 2005 to 2012 were influenced mainly by the national energy and industrial development strategy to relocate the energy industries towards north­ western China and the tendency of economic development to migrate westward into WC (Deng and Bai, 2014; Zhu and Ruth, 2015). These actions resulted in increased SO2 and NOx emissions and higher corre­ sponding concentrations in the atmosphere (Cui et al., 2016; Ling et al., 2017). Moreover, the planning indicators for the prevention and control of SO2 emissions in the 11th and 12th Five-Year Plans were 0 for most of the provinces in WC, even with an increasing rate of SO2 emissions for Gansu and Qinghai Provinces. However, the areas of Gansu and Ningxia (4.33 � 104 km2) and of Xinjiang (3.15 � 104 km2) were included in the 13 key regions to prevent and control air pollution. The air quality policies for the 13 key regions obviously decreased the SO2 and NO2

emissions during the 12th Five-Year Plan. In total, the PA increased by 14.7% from 2005 to 2012 and then decreased by only 2.0% in 2016 compared with the peak value in WC. 3.4. Spatial variations in the changing precipitation acidity between 2005 and 2016 across China To evaluate the effects of the air quality policies issued in the 11th and 12th Five-Year Plans on PA, the differences in the PA values and in the SO24 and NO3 depositions before and after these two five-year plans are compared (Fig. 6). The national average PA values in 2005 and 2016 were close (0.89 and 0.88 keq ha 1 yr 1, respectively), indicating that the PA increased due to industrial development and then decreased after the two five-year plans were implemented. However, the difference in the PA values in the two years showed considerable spatial variations. For most of the areas in WC and southeastern China, the PA values were

Fig. 6. Spatial distribution of the changes in the OMI-derived (a) PA, (b) SO24 deposition, and (c) NO3 deposition across China in 2016 compared with those in 2005. 6

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higher in 2016 than in 2005, indicating that acid pollution became heavier in these areas. The regions of NC connected to the SCB, PRD, and small areas of the YRD and northwestern China had lower PA values in 2016 than in 2005. The regions with decreased PA accounted for 27.1% of the nation, indicating that the abovementioned policies helped reduce acid pollution in some areas. In total, compared with the PA in 2005, the PA value in EC decreased by 5.8% in 2016, while it increased by 11.7% in WC, demonstrating that acid pollution was better alleviated in the well-developed regions of EC than in the less-developed areas of WC. The spatial variations in the changes in SO24 and NO3 depositions in 2016 and 2005 reveal that the change in SO24 deposition dominated the change in PA (Fig. 6(b) and (c)). The areas with decreased SO24 depo­ sition were in accordance with the spatial distribution of the decreased PA; the areas with decreased SO24 deposition accounted for 28.9% of the nation. Substantially different from the spatial variations in the change in SO24 deposition, the largest area with decreased NO3 depo­ sition was in NC, and some small areas were noted in the SCB, YRD, and PRD; these areas accounted for 14.3% of the nation. Four hotspot regions (NC, SCB, YRD, and PRD) with serious acid pollution in 2005 were selected to study the changes in PA (Fig. 7). In 2016, the PRD exhibited PA values in excess of 2.50 keq ha 1 yr 1, approximately two times higher than those in the SCB and NC (1.27 and 1.53 keq ha 1 yr 1, respectively). Compared with those in 2005, the PA values in 2016 in the SCB, NC, and the PRD decreased by 31.5%, 34.6%, and 11.7%, respectively, while the PA value increased slightly in the YRD. The ground observations in Nanjing and Shanghai, both of which are located in the YRD, showed that SO24 depositions decreased while NO3 depositions increased in 2014 and 2016, respectively, compared with those in 2005 (Li and Wang, 2016; Zhang et al., 2018b). These results indicate that the SCB, the PRD, and NC experienced decreased acid pollution after the 11th and 12th Five-Year Plans, while the PA values in the PRD and YRD maintained relatively high acid pollution levels. Considering the contribution of S/N to PA, the SCB had the highest S/N value, while the YRD had the lowest S/N value, and the NC and PRD had moderate values. The contributions of SO24 to PA decreased in the four hotspot areas from 2005 to 2016; during this period, the S/N values in the SCB and NC rapidly decreased by 36.7% and 42.3%, respectively, and those in the PRD and YRD decreased by 7.7% and 27.6%, respec­ tively. Decreased S/N values were also observed from the ground mea­ surements in some local areas of China, including Jinyunshan in southwestern China during 2003–2013 (Liu et al., 2016b), Beijing in NC from 2003 to 2014 (Pu et al., 2017), Guangzhou in southeastern China over the most recent 30 years (Fang et al., 2013), and Henan Province from OMI observations (Zhang et al., 2017). The decreased S/N values in

the SCB, NC, and the PRD were caused mainly by decreasing rates of SO24 deposition that were higher than those of NO3 deposition, while the decreased S/N values in the YRD were due mainly to increasing NO3 deposition since SO24 deposition remained stable. 3.5. Uncertainties and limitations This study used OMI SO2 and NO2 columns, measured precipitation amounts, and ground observations of wet SO24 and NO3 depositions to calculate the PA values across China and assessed the influences of air quality policies on PA. However, some uncertainties might exist in the data sources, calculation process, and trend detection method employed herein. The uncertainties in satellite-based NO2 and SO2 columns are dominated by air mass factors, which have been discussed in detail in a number of previous studies (Boersma et al., 2004; Nowlan et al., 2014; Zyrichidou et al., 2013). Specifically, the values of SO2 and NO2 were relatively low in WC, and the errors of the SO2 and NO2 columns were high. Moreover, the processes responsible for generating the negative SO2 columns in the daily SO2 products would cause the monthly SO2 columns to be overestimated. There were many negative values in the SO2 daily products; these values might have been derived from noise in the measured radiance data or small biases in the retrievals. Considering the relatively even distribution of these negative values across China, the monthly SO2 columns would be overestimated evenly if all of these negative values were removed from the daily SO2 product. However, the key factors in estimating wet SO24 depositions were W and ε, which were estimated based on a statistical regression model involving SO2 columns. Therefore, the uncertainties induced by removing negative SO2 columns might be offset in the estimated wet SO24 depositions. Another uncertainty in the estimates from the satellite-based NO2 and SO2 columns is that no valid OMI SO2 or NO2 data were acquired under cloudy/rainy conditions. This led to a mismatch between the OMI observations and wet depositions. Under such conditions, the con­ structed models utilized to estimate the wet SO24 and NO3 depositions for individual precipitation events could not perform well. Since this study was conducted at the yearly scale, the uncertainties induced by these factors would be smaller than the uncertainties for individual precipitation events. In addition, the models used to estimate wet depositions considered only the SO2 and NO2 columns and the precipitation amounts. This model involved mainly below-cloud scavenging on the related acid content in the atmosphere; however, the observed acid depositions could also originate from in-cloud scavenging. Therefore, long-range transport might be considered in the estimated acid deposition (Pan et al., 2013). Moreover, failing to incorporate S/N and its related water-soluble constituents in the atmosphere, as well as meteorological factors such as the precipitation type and wind, would result in addi­ tional uncertainties in the estimated acid depositions (Barrie, 1985; Kurzyca and Frankowski, 2019; Seinfeld and Pandis, 1998). This situa­ tion is particularly important for estimating individual precipitation events. Uncertainties in precipitation maps could result from measurement errors, systematic errors in the interpolation method and stochastic er­ rors due to the random nature of rainfall (Tao et al., 2009). Although the interpolation method of thin-plate smoothing splines has some advan­ tages for generating precipitation maps, this technique can lead to un­ certainties in estimated precipitation maps. Nevertheless, the monthly differences between the estimated and observed precipitation amounts were lower than 2.2%. A detailed description of the uncertainties in precipitation data can be found in the study by Zhang et al. (2018b). Equation (1) principally represents a process model for estimating wet acid deposition. However, it is not easy to observe or measure the values of the washout ratio (W) and of NO3 and SO24 in the particle phase (C) for each pixel. Instead, we used NO2 and SO2 columns in equation (1) since the relationships between NO2 and NO3 and between

Fig. 7. OMI-derived PA values and the contributions of the SO24 to NO3 ratio (S/N) to PA in 2005 and 2016 in the SCB, the PRD, the YRD, and NC. 7

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SO2 and SO24 are known. Additionally, W was estimated using a linear least-squares method using the ground measurements of NO3 and SO24 depositions. Therefore, this process model for estimating wet acid deposition in this study is a statistical model, and the estimated W values contain information on the washout ratios of NO3 and SO24 in the particle phase via precipitation and the conversions between NO2 and NO3 and between SO2 and SO24 . The method used to estimate W assumes that the errors in the in­ dependent variables are zero or are strictly controlled and thus negli­ gible (Fuller, 1987). However, these errors are non-negligible, resulting in an R2 lower than 1. Therefore, although the regression models passed the 1% significance level, uncertainties still exist in the calculated SO24 and NO3 depositions. Moreover, ground measurements of wet SO24 and NO3 depositions were used to construct the models employed to esti­ mate the spatial distributions of wet SO24 and NO3 depositions. Therefore, the limited number of precipitation events, the spatial dis­ tribution of the monitoring sites, different land uses, and other factors could have influenced the accuracy of the model estimations. Finally, this study considered only the PA resulting from H2SO4 and HNO3; in contrast, organic acid was not involved due to its minor contribution to PA (Stavrakou et al., 2012; Willey et al., 2011). Addi­ tionally, this study discussed mainly the changes in H2SO4 and HNO3 in precipitation, but neutralization should be fully considered when the precipitation pH is studied in the future.

Acknowledgments We acknowledge the free use of OMI NO2 column (http://www. temis.nl/), OMI SO2 column (https://disc.gsfc.nasa.gov/), and precipi­ tation data (http://data.cma.cn/). This study is supported by the Na­ tional Natural Science Foundation of China (No. 41471343 and 41601457), and National research program for key issues in air pollu­ tion control (Grant No. DQGG0101-02). Appendix A. Supplementary data Supplementary data to this article can be found online at https://doi. org/10.1016/j.atmosenv.2020.117359. References Barrie, L.A., 1985. Scavenging ratios, wet deposition, and in-cloud oxidation-an application to the oxides of sulfur and nitrogen. J. Geophys. Res. Atmos. 90, 5789–5799. Boersma, K.F., Eskes, H.J., Brinksma, E.J., 2004. Error analysis for tropospheric NO2 retrieval from space. J. Geophys. Res. Atmos. 109. 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4. Conclusions On the basis of OMI SO2 and NO2 columns, precipitation amounts, and ground measurements of wet acid depositions, the PA due to H2SO4 and HNO3 across China is estimated, and its long-trend trend from 2005 to 2016 is analysed. Models for estimating the annual SO24 and NO3 depositions are constructed, and accuracy assessments show that these models can obtain reliable results. The spatial distribution of PA and its changes from 2005 to 2016 are determined mainly by SO24 depositions across China. PA values are higher in EC than in WC. The PA values in both EC and WC show parabolic curves from 2005 to 2016, with the inflection points (from increasing to decreasing trends) in EC occurring earlier than those in WC. This temporal variation in PA reflects differences in the levels of economic development and air quality policies. The nationally averaged PA values in 2016 are close to those in 2005; controversial trends of decreasing PA are observed in EC, while increasing PA trends are discovered in WC. These results indicate that air quality policies have alleviated the PA in EC since 2012, but acid pollution in WC should be further addressed. Moreover, S/N has decreased in the four hotspot areas of NC and the PRD, SCB, and YRD, indicating a decreasing contribution of sulphur to PA. However, PA has decreased in NC, the PRD, and the SCB, but not the YRD due to increased NO3 deposition. Therefore, the relatively high nitrogen deposition in the YRD should be further addressed. Declaration of competing interest 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. CRediT authorship contribution statement Xiuying Zhang: Conceptualization, Methodology, Formal analysis, Writing - original draft, Funding acquisition. Limin Zhao: Methodology, Formal analysis. Junfeng Xu: Conceptualization, Resources. Dongmei Chen: Conceptualization, Writing - review & editing. Xiaodi Wu: Formal analysis. Miaomiao Cheng: Conceptualization, Funding acquisition.

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