Special Session on Better Air Quality in Asia (II)

Bo Huang1,4, Ting Gan2, Chenglei Pei6, Mei Li This email address is being protected from spambots. You need JavaScript enabled to view it.1,3, Peng Cheng1,3, Duohong Chen5, Ridong Cai5, Yujun Wang6, Lei Li1,3, Zhengxu Huang1,3, Wei Gao1,3, Zhong Fu4, Zhen Zhou1,3

Institute of Mass Spectrometer and Atmospheric Environment, Jinan University, Guangzhou 510632, China
Sun Yat-sen University, Guangzhou 510275, China
Guangdong Provincial Engineering Research Center for On-line Source Apportionment System of Air Pollution, Guangzhou 510632, China
Guangzhou Hexin Instrument Co., Ltd., Guangzhou 510530, China
Guangdong Environmental Monitoring Center, Guangzhou 510308, China
6 Guangzhou Environmental Monitoring Center, Guangzhou 510060, China


 

Received: November 13, 2019
Revised: April 1, 2020
Accepted: May 17, 2020

 Copyright The Author(s). This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are cited.


Download Citation: ||https://doi.org/10.4209/aaqr.2019.11.0582  

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Cite this article:

Huang, B., Gan, T., Pei, C., Li, M., Cheng, P., Chen, D., Cai, R., Wang, Y., Li, L., Huang, Z., Gao, W., Fu, Z. and Zhou, Z. (2020). Size-segregated Characteristics and Formation Mechanisms of Water-soluble Inorganic Ions during Different Seasons in Heshan of Guangdong, China. Aerosol Air Qual. Res. 20: 1961–1973. https://doi.org/10.4209/aaqr.2019.11.0582


HIGHLIGHTS

  • Increased NOR and decreased SOR were observed during pollution days.
  • The highest SOR and NOR values were found in size ranges of 0.56–1 µm.
  • NO3 in Heshan showed different formation pathways in winter and summer.
  • Size-depended SO42– formation pathways were observed.
  • Aqueous reactions accelerated by NO2 might be a possible pathway of SO42–.
 

ABSTRACT


To identify the characteristics, sources, and formation mechanisms of aerosol particles during pollution episodes in the Pearl River Delta, 24 sets of size-segregated samples were collected in Heshan during July 2014 and January 2015 using a 10-stage Micro-Orifice Uniform Deposit Impactor (MOUDI), and nine ions, viz., Na+, NH4+, K+, Mg2+, Ca2+, Cl, NO2, NO3, and SO42–, were investigated. The Na+, Mg2+, and Ca2+ were mainly distributed in the coarse particles, and were mainly from soil, dust, and sea salt. The fine-mode K+ during winter was mostly generated by biomass burning. The coarse-mode Cl originated from sea salt, whereas the fine-mode Cl resulted from the conversion of NH4Cl to the particle phase. Both the SO42– and the NO3 exhibited unimodal distributions during winter but bimodal ones during summer. The coarse-mode SO42– and NO3 arose from sea salt and heterogeneous reactions, respectively. An increase in the nitrogen oxidation ratio (NOR) and a decrease in the sulfur oxidation ratio (SOR) were observed on polluted days, with the highest values occurring in the 0.56–1 µm particle size fraction. The formation of NO3 was chiefly related toµ homogeneous gas-phase reactions during winter and nocturnal heterogeneous reactions involving N2O5 during summer, whereas the formation of SO42– was driven by gas-phase oxidation in the 0.056–0.32 µm size range and aqueous oxidation in the 0.56–3.2 µm range. Additionally, the SOR and the NO2 concentration displayed a positive correlation in the 0.056–1.8 µm particle size fraction, indicating that the potential formation of SO42– via aqueous reactions was accelerated by NO2.


Keywords: Water-soluble inorganic ions; Size distribution; Secondary formation; SOR; NOR.


INTRODUCTION


Particulate matter has been a concern of scientists for decades because it is associated with a range of effects on the atmospheric environment, visibility, human health, and the global radiation budget (Watson, 2002; Poschl, 2005; Kang et al., 2013). The chemical composition of particulate matter includes organic carbon (OC), elemental carbon (EC), elements, and water-soluble inorganic ions (WSIIs). According to previous studies, the mass concentration of WSIIs could account for over 30% of PM2.5 on an annual basis (Hua et al., 2015). Under typical weather conditions or

pollution episodes, the percentage of WSIIs in PM2.5 can reach up to 50–60% (Yue et al., 2015b). As a major component of PM2.5, WSIIs have a significant impact on the formation of the cloud condensation nuclei and aerosol acidity (Yao et al., 2003a; Shen et al., 2014); thus, the chemical composition, size distribution, sources, and formation mechanisms need to be fully understood to determine the role of aerosols during atmospheric processes (Wang and Lu, 2006).

SO42–, NO3, and NH4+ (sulfate, nitrate and ammonium ions [SNA]) are the most abundant species in WSIIs, accounting for over 40% of WSII mass concentrations (Yao et al., 2002; Yue et al., 2010; Chang et al., 2013; Yue et al., 2015b). They are mostly from secondary formation, and their formation mechanisms have been studied. The formation mechanism of SNA is relatively clear but is still not fully understood. Generally, the formation of SNA is related to its gaseous precursors (SO2, NOx and NH3), oxidant (O3), oxidation transformation rate (sulfur oxidation ratio [SOR] and nitrogen oxidation ratio [NOR] (Ohta and Okita, 1990; Wang et al., 2005), aerosol water content and acidity (Herrmann et al., 2015; Nguyen et al., 2016), and meteorological factors (Liu et al., 2019). The NO3 formation is dominated by the reactions of NO2 with OH· radical or nitric acid with NH3 during daylight, or by heterogeneous hydrolysis of N2O5 on aerosol surfaces during the night (Seinfeld and Pandis, 2006). SO42– is produced through the gas-phase oxidation of SO2 by reactions with OH· radicals, or by the aqueous uptake of SO2 on pre-existing particles or cloud droplets with dissolved H2O2 or with O2 under the catalysis of transition metals, such as Fe(III) and Mn(II) (Blitz et al., 2003; Seinfeld and Pandis, 2006). A recent study found that the aqueous oxidation of SO2 by NO2 was an efficient sulfate formation pathway on fine aerosols with high relative humidity or cloud conditions under NH3 neutralization (Wang et al., 2016). NH4+ is mostly combined with SO42– and/or NO3 (Feng and Penner, 2007).

SNA have strong hygroscopicity, and can change the atmospheric visibility significantly and the heterogeneous reactions on the particle’s surface, affecting aerosol size distribution (Liu et al., 2008; Lee and Hieu, 2013). For example, sub-mode NO3 is mostly combined with nitric acid and ammonia, coarse-mode NO3 is mainly formed by heterogeneous reactions of nitric acid or NO2 with coarse particles, such as sea salt, dust, or soil particles (Seinfeld and Pandis, 2006). Coarse-mode SO42– is mainly formed by gas-to-particle conversion, while droplet-mode SO42– is mainly attributed to cloud processing (Meng and Seinfeld, 1994). Many other studies also show that the dominant formation pathway of SNA varied with the research locations and the sampling periods (Wang et al., 2009; Ye et al., 2011).

The Pearl River Delta (PRD) region is one of the most economically developed in China. With highly intensive pollutant emissions caused by the rapid economic growth and continuous metropolitan expansion and high humidity, the PRD region has been experiencing frequent haze pollution, leading to low visibility and severe health effects. Although air quality has improved significantly in recent years, regional pollution processes still occur. There have been many studies on the WSIIs of aerosols in the PRD region. Gong et al. (2012) revealed that SO42– has the highest content in the Heshan region followed by NO3. Dai et al. (2013) found that WSIIs were over 50% of the PM2.5 in Shenzhen. He et al. (2014) found that in a haze episode in Guangzhou, SNA accounted for 76% of the total inorganic ions in the fine particles. Huang et al. (2014) investigated atmospheric particles collected in the Heshan Kaiping region in 2008 and found that SO42– and NO3 contributed 44% of the total PM2.5 due to the high emission of SO2 and NOx. Liu et al. (2019) found that the photochemical process is a critical factor affecting the formation of secondary ions in Guangzhou, and the SOR and NOR values were higher in winter than in summer. The size distribution and chemical composition of aerosols are essential to understanding the impact of their emission, migration, formation, and the conversion of secondary aerosols (Haywood et al., 2008; Liu et al., 2008; Asmi et al., 2016; Kuang et al., 2016). There has also been some research on size-resolved chemical compositions in this region. For example, Liao et al. (2015) found that SNA showed a distinct triple-peak pattern while other ions showed double- or single-peak structures in the fine-particle mode in South China. Gao et al. (2016) resolved trimodal size distributions of major chemical components using the Positive Matrix Factorization (PMF) model. They discussed the possible sources in different modes and found that secondary SO42–, engine exhaust, shipping, coal/biomass burning, and industrial sources were the main contributors to fine particles in Hong Kong. Jiang et al. (2019) compared pollution days and clean days and found that in summer and autumn, the SO42 showed higher formation rate, while the NO3 showed higher production rate in winter and spring. Moreover, different formation mechanisms were found in different size ranges and seasons. Previous studies were focused on urban areas and based on short-term monitoring in a single season. The seasonal characteristics, sources of WSIIs, and size-segregated formation mechanisms of SO42– and NO3 are still not well understood. Furthermore, previous studies on the impact of various possible factors on the formation mechanism of SNA are not adequate.

Size-segregated aerosol samples were collected at the Heshan Supersite (using a 10-stage Micro-Orifice Uniform Deposit Impactor [MOUDI]) in July 2014 and January 2015 to obtain a comprehensive understanding of the characteristics in the concentration variation, size distribution, sources, and formation mechanism of WSIIs during the pollution days in different seasons in the PRD region, which shows regional and complex air pollution characteristics. The Heshan Supersite is in the downwind area 50–100 km from the concentrated emission area of the pollution sources in Guangzhou, Foshan, and Dongguan, which is an ideal area to study the characteristics of regional air pollution. WSIIs from size-segregated aerosol particles in summer and winter were analyzed. The main aim of this study was to investigate the characteristics and sources of main inorganic ions in different size ranges and gain more knowledge on the formation pathways of SNA and the causes of pollution weather.


METHODS



Sample Collection

The sampling site is located at the Guangdong Atmospheric Supersite, a suburban site of Heshan city in the PRD region, surrounded mainly by villages and forests with no noticeable industrial sources around. The site is about 50 and 100 km southwest of Foshan and Guangzhou, respectively; both cities are densely industrial areas. The supersite is designed to monitor the air quality of the Pearl River Delta.

MOUDI (Model 110; MSP, USA) was installed on the roof of the main building of the supersite, approximately 10 m above the ground. Atmospheric particles with the size of 0.056, 0.10, 0.18, 0.32, 0.56, 1.0, 1.8, 3.2, 5.6, 10.0, and 18.0 µm were collected on 47 mm quartz fiber filters (QFFs; Whatman) preprocessed at a flow rate of 30 L min–1. The details of the filter processing method have been illustrated in published articles (Gan et al., 2015). Sampling was done from 9:00 a.m. to 8:30 a.m. of the next day in the periods July 22–August 1, 2014, and January 14–February 2, 2015 (except for January 22–24). Overall, 10 and 14 sets of samples were collected in summer and winter, respectively, and blank field membranes were also collected. Before and after sampling, the filters were kept at constant temperature (25°C) and relative humidity (RH; 50%) for 24 h before weighing. They were wrapped with annealed aluminum foil and stored in a refrigerator at –40°C until analysis.


Sample Processing and Chemical Analysis

Each sample filter was cut to a certain size and put into a centrifuge tube with 5 mL ultra-pure water and was extracted using an ultrasonic bath for 40 min. The extract was filtered using a 0.45 µm pore size filter. Then the process above was repeated. Only the ultrasonic extracted time was changed to 20 min. Both extraction solutions were mixed, resulting in a 10 mL solution, which was stored in a refrigerator until analysis. Ice was placed into the water bath to prevent the loss of ammonium due to the increase of the bath temperature. Concentrations of WSIIs were determined using the Dionex ICS-90 ion chromatogram instrument. In total, five cations (Na+, NH4+, K+, Mg2+, Ca2+) and four anions (Cl, NO2, NO3, SO42–) were analyzed. The detection limits were 0.020, 0.009, 0.005, 0.010, 0.016, 0.008, 0.007, 0.005, and 0.022 mg L–1 for Na+, NH4+, K+, Mg2+, Ca2+, Cl, NO2, NO3, and SO42–, respectively. The spike recovery test showed that recoveries of all ions were over 98% after a 60 min extraction. The precision of the analysis was calculated by duplicating the measurement of the same sample 7 times, and it yielded relative standard deviation (RSD) of 0.49%, 1.23%, 0.97%, 1.41%, 1.14%, 0.50%, 2.24, 1.73%, and 1.33% for Na+, NH4+, K+, Mg2+, Ca2+, Cl, NO2, NO3, and SO42–, respectively. The same method was used to analyze the blank membranes. The concentration of ions in the blank samples accounted for 4.33%, 4.44%, 2.85%, 5.63%, 4.49%, 0.86%, 7.83%, 1.72%, and 0.24% of the ambient samples for Na+, NH4+, K+, Mg2+, Ca2+, Cl, NO2, NO3, and SO42– in the summer samples, respectively, and the values were 7.32%, 1.31%, 1.40%, 11.71%, 4.89%, 0.37%, 3.37%, 0.24%, and 0.16% for winter samples. The blank deduction was applied for all samples before data analysis.

The ion balance was checked to evaluate the data quality and acidity of the samples following Eqs. (1)–(2) below.

 

CE (Cation Equivalent) = [Na+]/23 + [NH4+]/18 + [K+]/39 + [Mg2+]/12 + [Ca2+]/2                                       (1)

 

AE (Anion Equivalent) = [Cl]/35.5 + [NO2]/46 + [NO3]/62 + [SO42–]/48                                                    (2)

 

Because MOUDI does not have a 2.5 µm cut size, we define particles with a size range of 0.056–3.2 µm as fine particles and 3.2–10 µm as coarse particles. As shown in Fig. 1, good linear correlations were observed between cations and anions in most size ranges, indicating that the analysis method is reliable. Most fine-particle samples reached equilibrium or showed excess anions except for the two smallest size ranges, while most of the coarse samples showed excess cations, which means that fine particles were more acidic than the coarse particles. The huge gap between anions and cations in size ranges smaller than 0.18 µm might be the result of incomplete detection of ions in these size ranges.

Fig. 1. Ion balance of WSIIs in samples of different sizes.
Fig. 
1. Ion balance of WSIIs in samples of different sizes.


RESULTS AND DISCUSSION



Characteristics of WSIIs During Clean and Pollution Days of Summer and Winter

Fig. 2 shows the temporal variation of the WSII mass concentrations in summer and winter in the Heshan region. Fine particles (PM3.2) were dominant during the sampling periods, with average mass concentrations of 69.85 (± 26.45) µg m–3 and 103.4 (± 49.33) µg m–3 in summer and winter, respectively. WSIIs were mostly in fine particles, with 80.8% and 85.7% distributed in PM3.2 in summer and winter, respectively. The mass concentrations of WSIIs were 21.61 (± 5.90) µg m–3 and 59.86 (± 24.13) µg m–3 in summer and winter, accounting for 32.1 (± 8.5)% and 60.6 (± 16.4)% of the PM3.2 mass concentration. SO42–, NO3, and NH4+ were major components of WSIIs. In summer, SNA/WSIIs were 58.4 ± 10.4% and 44.7 ± 13.1% in fine and coarse particles, respectively. In winter, SNA/WSIIs were 81.3 ± 5.6% and 58.5 ± 8.1% in fine and coarse particles, respectively. SNA are mainly a result of secondary transformation (Yao et al., 2003b; Lin et al., 2012). In 2013, Yue et al. (2015a) investigated the SNA of atmospheric particles in winter in the Heshan region, finding that its mean contribution in PM2.5 was 64.3%. Liu et al. (2015) focused on the atmospheric particles in Guangzhou from 2010 to 2012 and found that in the haze episode, SNA accounts for 55% of the total mass of PM2.5. In this paper, the percentages of SNA/PM3.2 in summer and winter were 18.8 ± 5.8% and 48.8 ± 11.4%, respectively, which were lower than the two results mentioned above.

Fig. 2. Temporal variation of WSII mass concentrations in summer and winter.
Fig. 2.
 Temporal variation of WSII mass concentrations in summer and winter.

Polluting weather occurred in both seasons and the WSII composition showed significant differences in the different pollution episodes. Therefore, we separated the samples into clean days and pollution days according to the Ambient Air Quality Standard published by the Ministry of Ecology and Environment of China (2012), using 75 µg m–3 as a standard for particulate matter. As listed in Table 1, during both seasons the pollution days had higher concentrations of SO2 and O3 than the clean days and a higher temperature was observed during the former. RH was slightly higher on winter pollution days; however, it was lower on summer pollution days. Unlike SO2, the concentration of NO2 was high on winter pollution days but low on summer pollution days. Visibility significantly degraded from the summer clean days (20.4 km) to winter pollution days (6.5 km); it was accompanied by a significant increase in the proportion of SNA in WSIIs, which increased from 51% to 83%. Strong negative correlations were found between visibility and SNA, with correlation coefficients of –0.819 (p < 0.01), –0.868 (p < 0.01), and –0.911 (p < 0.01) for NO3, SO42–, and NH4+, respectively.

Table 1. Average values (mean ± std.) of PM3.2, gaseous pollutants and meteorological parameters during different periods.

Fig. 3 shows the ion composition of fine and coarse particles during different periods in the two seasons. The corresponding SOR and NOR values are also given by Eqs. (3)–(4) below.

 

SOR = [SO42–]/([SO42–] + [SO2])                                (3)

 

NOR = [NO3]/([NO3] + [NO2])                                (4)

 

As shown in Fig. 3SNA were the most abundant species in both fine and coarse particles except on clean summer days. The proportion of SO42– were significantly higher in the fine particles, while those of NO3 and crustal ions such as Na+ and Ca2+ were much higher in the coarse particles. The difference in the ion composition between the clean and pollution days showed similar trends for fine and coarse particles; however, they were distinctly different between summer and winter. In both fine and coarse particles, the proportion of SO42– increased significantly from the clean days to the pollution days in summer; in winter, the proportion of NO3 increased. In both seasons, the SOR decreased during pollution days but the concentration of SO42– still increased significantly because of the rapid increase of SO2, particularly during the summer pollution days. When the concentration of SO2 tripled, the proportion of SO42– increased significantly. The NOR showed higher values on the pollution days than on the clean days. In winter, particularly, the NOR value of 0.23 during the pollution days was almost at the same level of SOR (0.31). High NOR and NO2 concentrations during the winter pollution days resulted in a rapid rise in the concentration and proportion of NO3.

Fig. 3. Ion composition of fine and coarse particles, SOR and NOR values during different periods in different seasonsFig. 3. Ion composition of fine and coarse particles, SOR and NOR values during different periods in different seasons

Vehicle emissions and coal combustion are significant contributors to NO3 and SO42–, respectively (Huang et al., 2014). Thus, the mass concentration of NO3/SO42– has often been used to evaluate the relative contribution of vehicle emission and coal combustion to aerosol particles (Huang et al., 2016). In this study, the NO3/SO42– mass ratio in PM3.2 ranged from 0.08 to 1.76, with average values of 0.18, 0.14, 0.56, and 1.04 during the summer clean days, summer pollution days, winter clean days, and winter pollution days, respectively. The NO3/SO42– mass ratios were significantly higher in winter than in summer, indicating that a greater proportion of fine particles originated from vehicle emissions in winter. In summer, the values were much smaller than the ratios in Guangzhou (Liu et al., 2019) but were at the same level as Guangzhou in winter. This was possibly the result of different prevailing wind directions during the two seasons. Back trajectory analysis showed that marine south winds dominated in summer, bringing clean air to Heshan, resulting in low NO3/SO42– mass ratios during summer. In winter, air masses were mostly from or passed through heavily polluted areas located in the northeast or northwest of Heshan, such as Dongguan, Guangzhou, and Foshan. These cities have many cars, resulting in higher NO3/SO42– ratios in winter, particularly during the winter pollution days.


Size Distribution and Sources of WSIIs

Fig. 4 displays the size-resolved WSII composition in summer and winter. The size distribution of WSIIs showed distinct differences between the two seasons. In summer, WSIIs were bimodally distributed, with the dominant peak in the range of 0.56–1 µm, and a small peak in the range of 1.8–3.2 µm. In winter, WSIIs were unimodally distributed and peaked in the range of 0.56–1 µm. SO42– was predominant in the summer samples, while SO42– and NO3 were mainly in the winter samples. 

Fig. 4. Size-resolved WSII composition in summer and winter.
Fig. 4.
 Size-resolved WSII composition in summer and winter.

Fig. 5 shows the size distribution of single ions during different periods in summer and winter. According to the size distribution, the nine ions could be classified into three categories. The first class includes Na+, Mg2+, and Ca2+, among which Mg2+ and Ca2+ showed similar size distributions. These two ions were almost equally distributed in all size ranges in summer, with a tiny peak in the range of 3.2–5.6 µm, whereas in winter, they were mostly distributed in the coarse mode, with a single peak in size range of 3.2–5.6 µm. The two ions were strongly correlated with each other in both seasons (R > 0.8, p < 0.01), indicating the same origin from the soil or dust (Li et al., 2011). Na+ was mainly distributed in the coarse mode during the clean days of both seasons (although in summer, it had two small peaks in fine particles), while during the pollution days in both seasons, it was bimodally distributed, with the first peak appearing in size range of 0.56–1 µm, and the secondary peak in size range of 3.2–5.6 µm in winter and 5.6–10 µm in summer. The distribution pattern in the pollution days was similar to that of the previous study (Huang et al., 2016), which found a bimodal distribution of Na+, peaking at 0.43–0.65 µm and 4.7–5.8 µm. A moderate correlation was found between Na+ and Cl in size range of 5.6–10 µm (R > 0.6, p < 0.01). Back trajectory analysis indicated that 61% of the air masses during the summer sampling period were from the sea, indicating the contribution of sea salt to the coarse mode of Na+. Moreover, Na+ was strongly correlated with Ca2+ (R = 0.399, p > 0.05 in summer; R = 0.779, p < 0.01 in winter) and Mg2+ (R = 0.771, p < 0.01 in summer; R = 0.541, p < 0.05 in winter) in size range of 0.56–1 µm, indicating the crustal source of this size range.

Fig. 5. Size distribution of single ions during different periods in summer and winter.
Fig. 5.
 Size distribution of single ions during different periods in summer and winter.

The secondary class includes K+, Cl, and NO2, which were unimodally distributed during winter pollution days, peaking at the size range of 0.56–1 µm. K+ was mainly distributed in fine-mode aerosols, and it was unimodally distributed in winter and bimodally distributed in summer. K+ in fine mode is considered as a major feature of biomass burning (Arimoto et al., 1995). Furthermore, global fire maps from the NASA Moderate Resolution Imaging Spectroradiometer (MODIS) and Visible Infrared Imaging Radiometer Suite (VIIRS) (https://firms.modaps.eosdis.nasa.gov/map) showed a significant increase of the fire spots over South China and Southeast Asia during the winter sampling period, which was many times more than during the summer sampling period. Many more fire spots and a higher K+ concentration in winter suggested more serious emission of biomass burning in winter. Cl was mainly associated with fine particles during the winter pollution days with a mono-distribution peaking at 0.56–1.0 µm. However, Cl was multimodally distributed during the other three periods, with a mass concentration mostly distributed in coarse particles. Coarse-mode Cl in size ranges larger than 3.2 µm was strongly correlated to Na+ (R > 0.6, p < 0.01) and Mg2+ (R > 0.7, p < 0.01), suggesting a marine source (Li et al., 2010). Cl from the size range of 0.56–1.0 µm was highly correlated to SNA and K+, with the correlation coefficients of 0.903 (p < 0.01), 0.829 (p < 0.01), 0.760 (p < 0.01), and 0.732 (p < 0.01) for NO3, K+, SO42–, and NH4+, respectively. Previous research implied that sea salt reacting with acid gas or precursor could generate HCl (g), Na2SO4, and NaNO3. HCl (g) could possibly react with NH3, generating NH4Cl, which could be redistributed into particle phases or condensed into cloud droplets (Kulmala et al., 1995). This would result in the good correlation between Cl and SNA, and the fine mode of Cl, which was the possible formation mechanism of Cl in the size range of 0.56–1 µm in this study.

The third class consists of NO3, SO42–, and NH4+, which were typical secondarily generated ions. The three ions showed similar size distribution patterns in winter, with a single peak in size range of 0.56–1.0 µm. However, for size ranges of 0.56–1 and 1–1.8 µm, the concentration increment of NO3 was higher than those of SO42– and NH4+ during winter pollution days. This is likely due to the higher production of NO3 in these size ranges during the latter, as evidenced by significantly higher NOR values in these two size bins (Fig. 6). During the winter pollution days, the NOR in the two size ranges almost doubled more than during the winter clean days, resulting in a sharp increase of NO3 in the two size bins. Correlation analysis showed that NO3 was highly correlated to NH4+ (R > 0.837, p < 0.01) and K+ (R > 0.9, p < 0.01) in these two size ranges, indicating the possible existence of NH4NO3 and KNO3 in these size ranges in winter. The distribution pattern of NO3 in summer varied significantly compared to winter, showing a bimodal distribution, peaking at the size range of 3.2–5.6 µm and 0.56–1 µm. NH4NO3 is thermally unstable, with an average temperature of 29.8 ± 1.5°C. NH4NO3 could be dissociated into NH3 (g) and HNO3 (g); then HNO3 could be easily adsorbed on the coarse particles, which had weaker acidity than fine particles, and it could react with CaCO3 or other species in coarse particles (Huang et al., 2013). Correlation analysis showed high correlations of NO3 with Ca2+ (R = 0.855, p < 0.01) and Mg2+ (R = 0.951, p < 0.01) in this size range, which confirmed the speculation. As Fig. 6 shows, in size ranges for 0.18–3.2 µm, the NOR values were systematically higher in winter than in summer, while in size ranges of 3.2–10 µm, the NOR values showed no significant difference between the two seasons. In ultra-fine size ranges of 0.056–0.18 µm and the largest size range of 10–18 µm, the NOR values were higher in summer than in winter. This was not in agreement with previous studies (Huang et al., 2013), which discovered higher NOR values in summer for all size ranges in Beijing. In both seasons, the NOR during the pollution days were higher than during the clean days for all size ranges, which was in agreement with previous studies in Guangzhou (Liu et al., 2015) and Beijing (Huang et al., 2013). Moreover, the size distribution of NOR was different from previous researches in Guangzhou (Jiang et al., 2019), Beijing (Huang et al., 2013), and Tianjin (Yao et al., 2017). Huang et al. (2013) found a multimodal distribution of NOR in summer in Beijing. The highest NOR value appeared in the largest size range in summer, while in winter, the highest NOR was found to be in the smallest size range. Yao et al. (2017) found a trimodal distribution of the NOR during the clean days, and a bimodal distribution during the heavy pollution days, with the highest NOR in the size range of 1.1–2.1 µm. In this study, the NOR showed a bimodal distribution in both clean and pollution days in summer, with high values in size ranges of 0.56–1 µm and 3.2–5.6 µm. In winter, NOR was unimodally distributed with the highest value appearing in the size range of 0.056–1 µm.

Fig. 6. Size distribution of SOR and NOR during different periods in summer and winter.
Fig. 6.
 Size distribution of SOR and NOR during different periods in summer and winter.

The distribution of SO42– in the summer pollution days showed a bimodal pattern with peaks at 0.56–1.0 µm and 1.8–3.2 µm, while in other periods it showed a unimodal distribution with a major peak at 0.56–1.0 µm. It is reported that SO42– in the coarse mode are possibly formed by reactions with sea salt or soil (Gao et al., 2016), which might also be the source of SO42– in the size of 1.8–3.2 µm in summer in this study, considering the marine prevailing wind directions in this season. The size range of 0.56–1 µm is a typical droplet mode for SO42–, in which SO42– was mainly formed through aqueous oxidation of SO2 (Seinfeld and Pandis, 2006). Similarly, the highest SOR value appeared in this size range in both clean and pollution days in both seasons. As shown in Fig. 6, only in size ranges of 0.56–1 µm and 1–1.8 µm, the SOR values were significantly higher in winter than in summer, while in size ranges smaller than 0.56 µm and size ranges larger than 3.2 µm, the SOR values were systematically higher in summer. This was in accordance with previous research in Guangzhou (Jiang et al., 2019), which also found increasing SOR values in winter in the size range of 0.49–1.5 µm but showed different trends in Beijing (Huang et al., 2013), which discovered higher SOR values in summer for all size ranges. Unlike the NOR, which showed higher values during the pollution days in all size ranges in both seasons, SOR values decreased during the pollution days, except for the size range of 1.8–5.6 µm in summer, and the size ranges of 0.18–0.32 µm and 0.56–1.0 µm in winter. The results were consistent with previous research in Guangzhou (Liu et al., 2015), which found decreased SOR values during the haze processes, different from Beijing, which showed higher SOR values during the pollution days. The size distribution of the NOR showed different characteristics between summer and winter. In summer, smaller size ranges (0.18–1 µm) had a higher SOR, while in winter, the distribution shifted toward larger sizes. Higher SOR values were found to appear in the size range of 0.56–3.2 µm. This may indicate different formation mechanisms of the SOR in different seasons. Unlike NO3 and SO42–, NH4+ was unimodally distributed during all the monitoring periods, peaking at the size range of 0.56–1 µm. It was found to be strongly correlated with NO3 (R = 0.955, p < 0.01), SO42– (R = 0.900, p < 0.01), Cl (R = 0.784, p < 0.01), K+ (R = 0.921, p < 0.01), and Ca2+ (R = 0.513, p < 0.05).


Secondary Formation of Nitrate and Sulfate

Fig. 7 shows the relationship between the ratios of [NH4+]/[SO42–] and [NO3]/[SO42–] for all size-segregated samples. Considering [NH4+]/[SO42–] > 1.5 as ammonium-rich (AR) and [NH4+]/[SO42–] < 1.5 as ammonium-poor (AP), the summer samples were almost all ammonium-poor, with the [NH4+]/[SO42–] ratio of 1.13 ± 0.38, indicating that NH4+ in summer aerosols mainly existed in the form of NH4HSO4, and limited formation of NO3 as NH4NO3. Therefore, homogeneous gas-phase reactions should not be the main formation pathway of NO3 in the summer in Heshan. It is reported that NO3 could also be generated by heterogeneous reactions of NO3 and N2O5 during the night on the surface of aerosols under the conditions of high relative humidity and high concentration of NO2 and O3 (Wang et al., 2009). During the sampling period in summer, the concentration of NOx was 25 ± 2.6 µg m–3 at night, which was higher than 14.3 ± 6.4 µg m–3 in the daytime. Moreover, the relative humidity was 81.6 ± 4.0%, which was also significantly higher than that of 64.0 ± 5.3% during the day, making a suitable environment for the heterogeneous reactions to happen. In winter, most of the samples in the size range of 0.18–3.2 µm were ammonium-rich, accounting for 50.7% of total winter samples. NO3 was highly correlated with ammonium in these size ranges. The NOR in winter showed a strong correlation with O3 in size range of 0.056–0.56 µm (R > 0.539, p < 0.05). Therefore, the formation of NO3 in winter was most likely through homogeneous gas-phase reactions, in the form of NH4NO3, which was in accordance with the result in Guangzhou (Jiang et al., 2019).


Fig. 7. The relationship between the ratios of [NH4+]/[SO42–] and [NO3–]/[SO42–] for all size-segregated samples, as well as the proportion of ammonium-rich (AR) samples and ammonium-poor (AP) samples in different size ranges (w before the size ranges stands for “winter”).Fig. 7.
 The relationship between the ratios of [NH4+]/[SO42–] and [NO3]/[SO42–] for all size-segregated samples, as well as the proportion of ammonium-rich (AR) samples and ammonium-poor (AP) samples in different size ranges (w before the size ranges stands for “winter”).

Sulfate could be formed through gas-phase oxidation and aqueous-phase heterogeneous reactions with its precursor gas, SO2 (Zhang et al., 2015). Moreover, Wang et al. (2016) found that in China, the oxidation of SO2 by NO2 in aqueous media was an important pathway for sulfate generation, but it is pH-dependent. In this study, size-segregated Aerosol [H+]in situ were calculated using the Extended AIM Aerosol Thermodynamic Model II (http://www.aim.env.uea.ac.uk/aim/model2/model2a.php), which is an equilibrium thermodynamic model of the system H+ - NH4+ - SO42– - NO3 - H2O. pH was then calculated using Eq. (5) as follows:

 

where γ represents hydrogen activity coefficients and v represents the volume of aqueous solutions, which could all be given by the model. Average [H+]in situ in PM3.2 was 45.7 nmol m–3 in summer and 70.6 nmol m–3 in winter, with pH values of 2.3 in summer and 2.6 in winter, indicating the acidic nature of the fine particles in both seasons.

Photochemical reactions are influenced by temperature, humidity, and radiation intensity (Seinfeld and Pandis, 2006).

The SOR was found to be moderately correlated with temperature in size range of 0.056–0.32 µm (R > 0.546, p < 0.01), indicating that in this size range, the formation of SO42– was controlled by the gas-phase photochemical oxidation of SO2, which was similar to results of previous studies, which found a dominant gas-particle conversion mechanism in size ranges < 0.49 µm and 0.32–0.56 µm in Guangzhou (Jiang et al., 2019) and PRD region (Liu et al., 2008), respectively. In size ranges 0.56–1 µm, 1–1.8 µm, and 1.8–3.2 µm, the SOR showed weak positive correlation with relative humidity, with the correlation coefficients of 0.22, 0.29, and 0.18, respectively, indicating that in these size ranges, SO42– may be formed through the aqueous oxidation of SO2. The result was also similar to previous studies (Jiang et al., 2019), which attributed SO42– in the size range of 0.49–3.0 µm to the result of aqueous oxidation. However, although E-AIM gave out low pH in both seasons, a moderate correlation between SOR and NO2 was observed in the former two size ranges, with correlation coefficients of 0.545 (p < 0.01) and 0.534 (p < 0.01), respectively, which was not observed by Jiang et al. (2019). Thus, we came into the deduction that aqueous reactions accelerated by NO2 might also be a possible pathway of sulfate production in Heshan, although the pathway may not be as important as in other heavily polluted areas in China, and should be further researched in future studies.


CONCLUSIONS


To identify the differences between clean and polluted days, including their seasonal attributes, in the Pearl River Delta, this study investigated the size-resolved sources of the major WSIIs and the formation pathways of SNA in Heshan, a typical suburban site representing the complex pollution characteristics of this region. Additionally, the contribution of meteorological parameters, gaseous pollutants, and other significant factors to the formation of SO42– and NO3 was explored. The Na+, Mg2+, and Ca2+ mainly arose from soil, dust, and sea salt. The higher concentration of K+ in winter was due to the increased biomass burning during this season. The coarse-mode Cl originated from sea salt, whereas the fine-mode Cl resulted from the conversion of NH4Cl to the particle phase. The WSII composition displayed significant differences between winter and summer, with a higher proportion of NO3 on polluted days during the former and a higher proportion of SO42– on polluted days during the latter. Furthermore, increased NORs but decreased SORs were observed on the polluted days of both seasons. The 0.56–1 µm and 1.0–1.8 µm particle size ranges exhibited the highest SORs and NORs on polluted days during winter; however, the 0.056–1 µm and 1–3.2 µm fractions showed higher ratios during summer. The formation of NO3 was primarily driven by homogeneous gas-phase reactions during winter and nocturnal heterogeneous reactions involving N2O5 during summer. A moderate positive correlation between the SOR and the temperature was found for the 0.056–0.32 µm particles, indicating the predominance of gas-phase oxidation, and a weak positive correlation between the SOR and the relative humidity was found for the 0.56–3.2 µm particles, suggesting the influence of aqueous oxidation. Moreover, the SOR and the NO2 concentration displayed a positive correlation in the 0.056–1.8 µm particle size fraction, indicating that the potential formation of SO42– via aqueous reactions was accelerated by NO2. Our results, which encompass the size-resolved compositions and sources of ions as well as the seasonal characteristics of their formation pathways during polluted and clean days in Heshan, enhance our understanding of air pollution in this region and enable us to establish effective control measures according to the season. 


ACKNOWLEDGMENTS


This work was financially supported by the National Key Research and Development Program of China (2018 YFE0106900), the National Natural Science Foundation of China (No. 41827804), the Guangzhou Development District International Science and Technology Cooperation Project (No. 2018GH08), the International Science and Technology Cooperation Project (2018A050506020) and the Pearl River Nova Program of Guangzhou (Nos. 201710010006 and 201806010064).


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Aerosol Air Qual. Res. 20 :1961 -1973 . https://doi.org/10.4209/aaqr.2019.11.0582  


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