Ruoxin Wang1, Kangping Cui This email address is being protected from spambots. You need JavaScript enabled to view it.1, Hwey-Lin Sheu This email address is being protected from spambots. You need JavaScript enabled to view it.2, Lin-Chi Wang3, Xueyan Liu1 

1 School of Resources and Environmental Engineering, Hefei University of Technology, Hefei 246011, China
2 Department of Environmental Engineering, Kun Shan University, Tainan 71070, Taiwan
3 Department of Environmental Engineering, Chung Yuan Christian University, Taoyuan 32023, Taiwan


Received: November 24, 2022
Revised: February 21, 2023
Accepted: February 24, 2023

 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.220417  

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Cite this article:

Wang, R., Cui, K., Sheu, H.L., Wang, L.C., Liu, X. (2023). Effects of Precipitation on the Air Quality Index, PM2.5 Levels and on the Dry Deposition of PCDD/Fs in the Ambient Air. Aerosol Air Qual. Res. 23, 220417. https://doi.org/10.4209/aaqr.220417


HIGHLIGHTS 

  • The air quality index (AQI) of Suzhou, before, during and after rain were investigated.
  • The PM2.5 concentrations in the ambient air, before, during and after rain were studied.
  • The atmospheric PCDD/F dry deposition fluxes, before and after the rain were discussed.
 

ABSTRACT


The effects of 9 precipitation events in Suzhou City in Anhui Province, China, on the air quality index (AQI), PM2.5, and dry deposition flux of PCDD/Fs (polydibenzo-p-dioxins and polydibenzofurans) were investigated. A total of 7 precipitation events were positive contributes to the reduction of AQI; among them, the AQI were between 23 and 216, with an average of 75, the PM2.5 concentrations were between 5.0 and 169 µg m–3, with an average of 25 µg m–3, while the total- PCDD/F-TEQ dry deposition flux ranged from 149 to 1034 pg WHO2005-TEQ m–2 day–1 and averaged 315 pg WHO2005-TEQ m–2 day–1. By comparing the average AQI and PM2.5, respectively, during and after rainfall with that before rainfall, the results indicated that the average reduction fractions of AQI were 26% and 44%, respectively, while those of PM2.5 were 58% and 43%. In addition, the effect of precipitation on the average reduction fraction of total PCDD/F-TEQ dry deposition flux was 31%. However, in the other 2 AQI elevation events, the AQI were between 23 and 100, and averaged 51; when comparing the average AQI and PM2.5 concentrations, during and after the rain with that before the rain, the increases in AQI were 42% and 49%, respectively, while the increases in PM2.5 concentration were 26% and 29%, respectively. The above results show that, on the whole, rain and snow improved the air quality. This is because rainwater removes particles or dissolved gaseous pollutants from the atmosphere and brings aerosols to the ground. However, in some cases, the increase of source emissions and atmospheric vertical convection, the effect of precipitation or air humidity increased the AQI and elevated the concentration of PM2.5, and dry deposition flux of PCDD/Fs. The results of this study provide useful information for both scientific communities and air quality management.


Keywords: Rain, Snow, AQI, PM2.5, PCDD/Fs, Dry deposition


1 INTRODUCTION


Around the world, the combination of increasing population density and rapid industrialization has led to a serious deterioration in the degree of air pollution (Cao et al., 2009; Jia et al., 2020), especially urban air pollution, including particulate suspended matter (PM), sulfur dioxide (SO2), nitrogen dioxide (NO2), ozone (O3), carbon monoxide (CO), and other pollutants. The air pollution in these cities is so bad that it is reducing visibility, posing a great threat to public health, and undermining cities' sustainability (Hu et al., 2015; Shah and Patel, 2021; Zhang et al., 2022).

According to previous studies, precipitation can effectively improve air quality because rainwater can take away PM2.5 and other pollutants in the air and carry away some of the particulate matter to some extent, reducing the concentration of PCDD/Fs, and thus purifying the air and improving air quality (Tian et al., 2021a; Yu et al., 2021).

Air pollution releases pollutants due to human development and other natural or anthropogenic activities into the atmosphere and causes harm to humans, other organisms, and the natural environment. Therefore, to provide data for ambient air quality management, and protect public health (Wang et al., 2018; Suman, 2021), a class of air quality indices that are easy to read and easy to understand by citizens and policymakers have been presented (Bruno and Cocchi, 2002). The Air Quality Index (AQI) is an index that quantitatively describes air quality and is used to report the hourly or daily air quality of a region (Kyrkilis et al., 2007).

In recent years, the air quality of Qingdao, Jinan, Chengdu, and other cities in China was found to be much better in 2020 than in other years (Wan et al., 2020; Xu et al., 2020). This was because the epidemic control actions greatly reduced the air pollutant emissions from both stationary and mobile sources (Zhang et al., 2020; Yu et al., 2021).

Atmospheric fine particulate matter (PM2.5) are particles less than or equal to 2.5 µm in size and they can enter the lungs through the upper respiratory tract (DeCarlo et al., 2004; Nguyen et al., 2022; Pan et al., 2022). The sources of PM2.5 are divided into natural and anthropogenic sources. The natural sources include hurricanes, forest fires, volcanic eruptions, weathering of soil and rocks, tsunamis, and biological decay, while anthropogenic sources include vehicle exhaust and industrial emissions such as those from coal power plants and industrial production (Querol et al., 2001; Mutuku et al., 2021; Wu et al., 2021).

PM2.5 has a great impact on both human health and the national economy (Fang et al., 2009; Liu et al., 2021; Zhou, 2021). In addition, it is estimated that PM2.5 caused 8.9 million deaths worldwide in 2015 (Burnett et al., 2018; Tian et al., 2021b). PM2.5 is closely related to the incidence of cardiovascular and respiratory diseases, and cancer (Apte et al., 2015; Hystad et al., 2020; Rodriguez-Urrego and Rodriguez-Urrego, 2020; Zhang et al., 2021). Since 2013, China has implemented the "Air Pollution Prevention and Control Action Plan," which is the first time that air quality has been properly monitored (Zhang et al., 2019; Xia et al., 2021). PM2.5 concentrations fell sharply between 2013 and 2017 as stringent clean-air actions were implemented (Jiang et al., 2015; Jia et al., 2020).

Dioxin (PCDD/Fs) is a group of toxic pollutants, which mainly comes from hazardous waste, medical waste, municipal solid waste, and medical waste incineration. In addition, it can also be produced in a wide range of activities, such as bleaching paper with chlorine (She et al., 2017; Lin et al., 2022). PCDD/Fs can be produced in pesticide manufacturing, automobile exhaust emissions, commercial detergents, petroleum refining, metallurgy, and other activities (Schuhmacher et al., 2000; Prange et al., 2002). The PCDDs, PCDFs, and PCBs constitute a group of persistent pollutants. These compounds have a certain structural correlation and a common mechanism of action (Van den Berg et al., 1998), because PCDD/Fs are lipophilic compounds that are difficult to degrade in nature. In addition, if humans are exposed to high concentrations of PCDD/Fs or consume contaminated food for a long time, it is likely to lead to impaired internal organ function, reduced perception, skin surface damage, and growth retardation (Chen et al., 2006; Hu et al., 2009; Ssebugere et al., 2019; Ngo et al., 2020).

POPs are mainly removed by sedimentation in the atmosphere, a process in which air pollutants settle in soil or water in a specific way, which is mainly divided into dry deposition and wet deposition (Brzuzy and Hites, 1996; Huang et al., 2011; Jeong et al., 2016). Wet deposition refers to the process of removing both particle and gaseous air pollutants in the atmosphere using snow and rainfall (Moon et al., 2005; Melymuk et al., 2011). Among them, in the process of rainfall, atmospheric temperature, humidity, rainfall, particle size and initial concentration of particles affect the process of wet deposition (Chang et al., 2004; Zhou et al., 2020). Dry deposition is the process with no rain in which particles and gases suspended in the atmosphere fall at their final speed. In addition, temperature, wind speed, humidity, and particle size affect the dry deposition flux of air pollutants (Mi et al., 2012; Suryani R et al., 2015).

In this study, a total of 9 precipitation events were selected and studied in Suzhou City, and they were divided into 7 AQI reduction events and 2 AQI increase events. The AQI and concentrations of PM2.5 before, during, and after precipitation are presented and discussed. Furthermore, the impacts of precipitation on total PCDD/Fs-WHO2005-TEQ dry deposition flux were investigated.


2 METHODS


Suzhou (33°38′N, 116°58′E) (north of the Huaihe River) is located in Anhui Province, China, in the north of Anhui Province and in the northeast of Huaibei Plain, which belongs to a warm temperate zone and semi-humid monsoon climate. The average daily temperatures were between –7°C and 31°C in 2020 and 2021 were between –7°C and 32°C and the annual average temperatures were 15.7°C and 15.8°C in 2020 and 2021, respectively.

This study discusses the AQI and PM2.5 concentrations before, during, and after precipitation (http://www.aqistudy.cn/).

 
2.1 PCDD/F Concentration

The overall concentration of PCDD/Fs was simulated using a regression analysis of PM10 concentration. The PM10 value and the total mass concentration of PCDD/Fs have a high association (Lee et al., 2016). The following two linear equations can express their relationship:

 

Y1, Y2: the total concentration of PCDD/F (pg m–3).

x: PM10 concentration in ambient atmosphere (µg m–3).

In this study, the dry deposition flux of PCDD/Fs was calculated using the technique provided by Liu’s study (Liu et al., 2022), and the necessary parameters were acquired using methods used in previous research (Shih et al., 2006).

 
2.2 Air Quality Index (AQI)

The air quality index (AQI) is a quantitative representation of air quality data that may be used to reflect a city's short-term air quality state and changes (She et al., 2017; Shen et al., 2017).

The level of air quality affects people's life and health. The air quality index is obtained from the 24-hour average concentration of PM2.5, PM10, CO, NO2, and SO2, and the daily average 8-hour maximum O3 concentration. The U.S. Environmental Protection Agency (U.S. EPA) has established six AQI levels:

Class I: 0–50, Good, Green.
Class II: 51–100, Moderate, Yellow.
Class III: 101–150, Unhealthy for sensitive groups, Orange.
Class IV: 151–200, Unhealthy, Red.
Class V: 201–300, Very unhealthy, Purple.
Class VI: 300–500, Hazardous, Maroon.

 
3 RESULTS AND DISCUSSION


 
3.1 Effects of Precipitation on the Reductions of AQI

In Suzhou, selecting 9 rainfall events of the same type, it can be found that the air quality index of 7 rainfall events decreased and the air quality index of 2 rainfall events increased, leading to deterioration of air quality. The dates, duration of precipitation, and amounts of precipitation are shown in Table 1.

 
3.1.1 AQI analysis

As shown in Fig. 1, among the top 9 precipitation events in Suzhou, 7 events showed the reduction of AQI (Table 1). The AQI before the rain (Figs. 1(a1–a8)) ranged between 42 and 216 and averaged 95; while during the rain, AQI ranged from 25 to 133 and averaged 51 (Figs. 1(b1–b8)). In addition, after the rain, AQI ranged from 39 to 118 and averaged 73 (Figs. 1(c1–c8)). Furthermore, it can be seen that during the 7 events, the main pollutant was O3. The reason for this might be that the temperature was higher and the wind speed was slower in summer, so the O3 concentration was higher. In addition, when comparing the AQI before and after the rain, the decrease in AQI during the rain ranged from 18% to 57%, with an average AQI of 44% lower than before the rain. When the AQI after the rain was compared to the AQI before the rain, the AQI reduction after the rain ranged from 2.4% to 54% and averaged 26% lower than that before the rain. As a result, rainwater would cling to the particles in the air and fall to the ground with them, reducing the concentration of particulate pollutants in the atmosphere significantly. Furthermore, the wind affected the horizontal dispersion of pollutants. When it rained, the wind speed increased or decreased and swung irregularly up and down, and left and right, causing the rest of the particles to be mixed, which was conducive to the dispersion, dilution, and diffusion of contaminants. The above phenomenon proved that rain did indeed improve air quality to a certain extent, and the removal effect of particulate matter in the air was particularly significant.

Table 1. The AQI values and precipitation intensity in Suzhou from 2020 to 2021.


Fig. 1. The proportions of the seven AQI categories for Suzhou before the rain, during the rain, and after the rain for 2020–2021 for AQI reduction events.Fig. 1. The proportions of the seven AQI categories for Suzhou before the rain, during the rain, and after the rain for 2020–2021 for AQI reduction events.

 
3.1.2 PM2.5 concentration

As shown in Fig. 2, in the 7 events in which AQI decreased, before the rain, PM2.5 concentrations ranged from 11 to 169 µg m–3 and averaged 40 µg m–3. During the rain, the PM2.5 concentrations ranged between 5.0 and 91 µg m–3 and its average concentration was 17 µg m–3, while after the rain, the PM2.5 concentrations were between 9.0 and 50 µg m–3 and averaged 23 µg m–3. Comparing the PM2.5 concentrations during the rain with those before the rain, the PM2.5 concentration reductions during the rain ranged from 13% to 67% and averaged 58% less than that before the rain, when comparing after the rain with before the rain, respectively, the PM2.5 concentration reductions after the rain were –17% to 58% and was 43% lower than that before the rain on average.

Fig. 2. variations in the PM2.5 concentrations in Suzhou (a–c, e–h) before the precipitation, during the precipitation, and after the precipitation from 2020–2021 when the AQI was reduced.Fig. 2. variations in the PM2.5 concentrations in Suzhou (a–c, e–h) before the precipitation, during the precipitation, and after the precipitation from 2020–2021 when the AQI was reduced.
 

The above phenomenon might have occurred because precipitation was mainly concentrated in summer, the atmospheric dispersion was better in summer, and the concentration of particulate matter itself was low. However, excessive precipitation in summer led to an increase in humidity. There was a certain threshold of air humidity. Under this threshold, the concentration of particulate matter increased with the increase of humidity, and once this threshold was exceeded, the concentration of particulate matter decreased with the increase of humidity. Therefore, PM2.5 might rise after rain.

 
3.1.3 Dry deposition flux of total-PCDD/Fs-WHO2005-TEQ

According to Fig. 3, Suzhou's dry deposition flux of the total PCDD/Fs-WHO2005-TEQ before the rain were between 197 and 1034 pg WHO2005-TEQ m–2 day–1, averaging 374 pg WHO2005-TEQ m–2 day–1 and ranged from 149 to 470 pg WHO2005-TEQ m–2 day–1, after the rain, averaging 257 pg WHO2005-TEQ m–2 day–1. When the dry deposition flux of total PCDD/Fs-WHO2005-TEQ after the rain was compared to those before the rain, the reductions after the rain were between –2.0% and 55% and were 31% lower than those before the rain on average.

Fig. 3. The total PCDD/Fs-WHO2005-TEQ dry deposition flux in Suzhou before and, after precipitation in 2020–2021 for reduced AQI events.Fig. 3. The total PCDD/Fs-WHO2005-TEQ dry deposition flux in Suzhou before and, after precipitation in 2020–2021 for reduced AQI events.

Overall, the rate of POPs removal by rainfall depends on human pollutants as well as ambient temperature. When the temperature is below 0°C, rainfall can effectively remove more organic vapors, thereby reducing the dry deposition flux of PCDD/Fs.

 
3.2 Effects of Precipitation on the Increment of AQI


3.2.1 AQI analysis

From 2020 to 2021, this study selected the 9 precipitation events with the largest rainfall in Suzhou, where the AQI of 2 events (Fig. 4) showed an increasing trend (Table 1).

Fig. 4. The percentages of the two AQI categories for Suzhou before, during, and after precipitation in 2020–2021 for the elevated AQI events.Fig. 4. The percentages of the two AQI categories for Suzhou before, during, and after precipitation in 2020–2021 for the elevated AQI events.
 

As shown in Fig. 4, for the 2 rainfall events in Suzhou with elevated AQI, the AQI values before the rain ranged from 29 to 80 with an average of 56, while the AQI during the rain ranged from 27 to 56 and averaged 43, and the AQI after the rain ranged from 62 to 102, with an average of 85. Furthermore, by comparing the AQI values before and during the rain, we can conclude that the AQI during the rain were 38% and 45%, respectively, and were 42% lower than those before the rain on average, while the AQI after the rain were 28% and 69%, respectively, and were 49% higher than those before the rain on average.

 
3.2.2 PM2.5 concentration

As shown in Fig. 5, in Suzhou, during the two AQI elevation events, PM2.5 concentrations before the rain ranged from 32 to 38 µg m3 with an average of 34 µg m3. During the rain, PM2.5 concentrations ranged from 7.0 to 46 µg m3, with an average of 25 µg m3; after the rain, PM2.5 concentrations were between 25 and 65 µg m–3, with an average of 44 µg m3. The PM2.5 concentrations during the rain were between –13% and 62% and were 26% higher on average than those before the rain, while after the rain compared with before the rain, the PM2.5 concentrations after the rain were between –21% and 62%, with a 29% higher average than those before the rain. This was because the heavy rain in summer effectively washed out the particulate pollutants in the air. When the rainfall lasted for a long time and the amount was large, the particulate matter in the air was washed away, and the weather was fine after the rain. After that, the PM2.5 concentrations declined. However, if the rainfall was not large enough, or the air humidity was high, the PM2.5 concentrations were higher.

Fig. 5. Proportions in the PM2.5 concentrations for Suzhou before the precipitation, during the precipitation, and after the precipitation during 2020–2021 for the elevated AQI events.Fig. 5. Proportions in the PM2.5 concentrations for Suzhou before the precipitation, during the precipitation, and after the precipitation during 2020–2021 for the elevated AQI events.

 
3.2.3 Dry deposition flux for the total-PCDD/Fs-WHO2005-TEQ

According to Fig. 6, the two events in which the AQI value increased and the dry deposition fluxes in the total PCDD/Fs-WHO2005-TEQ before the rain were between 188 and 219 pg WHO2005-TEQ m–2 day–1 with an average of 204 WHO2005-TEQ pg m–2 day–1; after the rain were between 196 and 371 pg WHO2005-TEQ m–2 day–1 and averaged 284 pg WHO2005-TEQ m–2 day–1. the increases after the rain ranged between 4.0% and 69% and were 39% higher than those before the rain on average when comparing the dry deposition flux in the total PCDD/Fs-WHO2005-TEQ after the rain with that before the rain. The above results revealed that when the AQI elevated, normally, the dry deposition of total PCDD/Fs-WHO2005-TEQ increased as well.

Fig. 6. The total PCDD/Fs-WHO2005-TEQ dry deposition flux in Suzhou before and, after precipitation in 2020–2021 for elevated AQI events.
Fig. 6. The total PCDD/Fs-WHO2005-TEQ dry deposition flux in Suzhou before and, after precipitation in 2020–2021 for elevated AQI events.


4 CONCLUSION


This study investigated the effects of 9 precipitation events on the AQI, PM2.5, and wet deposition of total PCDD/Fs-WHO2005-TEQ. The major results are summarized as follows.

  1. In Suzhou, for the 7 precipitation events, the AQI ranged from 23 to 216 and averaged 75, Comparing AQI during and after the precipitation, respectively, with that of before the precipitation, the reduction fractions in the AQI were 26% and 44%, respectively, and in two cases where the AQI index elevated, the AQI were between 23 and 100, with an average of 51. As a whole, comparing AQI during and after the precipitation, respectively, with that before the precipitation, the increased fractions of AQI were 42% and 49%.

  2. For the 7 precipitation events, the PM2.5 concentration was between 5 and 169 µg m–3, with an average of 25 µg m–3 and the reductions in the PM2.5 concentrations during and after the precipitation were 58% and 43%, respectively. In the other 2 cases, the PM2.5 concentrations were from 4.0 to 29 µg m–3, with an average of 14 µg m–3. The PM2.5 concentrations during and after the rain were 26% and 29% higher than those before the precipitation, respectively.

  3. For the 7 precipitation events demonstrating a reduction in the AQI, the dry deposition flux of total PCDD/Fs-WHO2005-TEQ in Suzhou from 2020 to 2021 were between 149 and 1034 pg WHO2005-TEQ m–2 day–1, with an average of 315 pg WHO2005-TEQ m–2 day–1. When the values after the precipitation were compared to those before the precipitation, the dry deposition flux was reduced by 31%. The dry deposition flux in the total PCDD/Fs-WHO2005-TEQ were between 188.5 and 371.2 pg WHO2005-TEQ m–2 day–1 and averaged 244 pg WHO2005-TEQ m–2 day–1 in the other 2 precipitation events. Comparing the values after the precipitation with those before the precipitation, the increase in the PCDD/Fs dry deposition flux was 39%.

  4. The results show that, in general, rainfall can improve air quality because particulate matter or dissolved gaseous pollutants are removed and aerosols are brought to the ground. This study selected the top 9 events of rainfall intensity in Suzhou, Anhui Province, and found that when the rainfall intensity is high, it can indeed reduce AQI and reduce the air pollutant concentration in the ambient air. However, in some cases, the increase of source emissions or the decrease of atmospheric vertical convection leads to the increase of AQI, PM2.5, and PCDD/Fs dry deposition fluxes in ambient air.


REFERENCES


  1. Apte, J.S., Marshall, J.D., Cohen, A.J., Brauer, M. (2015). Addressing global mortality from ambient PM2.5. Environ. Sci. Technol. 49, 8057–8066. http://doi.org/10.1021/acs.est.5b01236

  2. Bruno, F., Cocchi, D. (2002). A unified strategy for building simple air quality indices. Environmetrics 13, 243–261. http://doi.org/10.1002/env.512

  3. Brzuzy, L.P., Hites, R.A. (1996). Global Mass Balance for polychlorinated dibenzo-p-dioxins and dibenzofurans. Environ. Sci. Technol. 30, 1797–1804. http://doi.org/10.1021/es950714n

  4. Burnett, R., Chen, H., Szyszkowicz, M., Fann, N., Hubbell, B., Pope, C.A., Apte, J.S., Brauer, M., Cohen, A., Weichenthal, S., Coggins, J., Di, Q., Brunekreef, B., Frostad, J., Lim, S.S., Kan, H., Walker, K.D., Thurston, G.D., Hayes, R.B., Lim, C.C., et al. (2018). Global estimates of mortality associated with long-term exposure to outdoor fine particulate matter. PNAS 115, 9592–9597. https://doi.org/10.1073/pnas.1803222115

  5. Cao, J., Shen, Z., Chow, J.C., Qi, G., Watson, J.G. (2009). Seasonal variations and sources of mass and chemical composition for PM10 aerosol in Hangzhou, China. Particuology 7, 161–168. http://doi.org/10.1016/j.partic.2009.01.009

  6. Chang, M.C., Chow, J.C., Watson, J.G., Hopke, P.K., Yi, S.M., England, G.C. (2004). Measurement of ultrafine particle size distributions from coal-, oil-, and gas-fired stationary combustion sources. J. Air Waste Manage. Assoc. 54, 1494–1505. http://doi.org/10.1080/10473289.2004.​10471010

  7. Chen, H.L., Su, H.J., Guo, Y.L., Liao, P.C., Hung, C.F., Lee, C.C. (2006). Biochemistry examinations and health disorder evaluation of Taiwanese living near incinerators and with low serum PCDD/Fs levels. Sci. Total Environ. 366, 538–548. http://doi.org/10.1016/j.scitotenv.2005.​11.004

  8. DeCarlo, P.F., Slowik, J.G., Worsnop, D.R., Davidovits, P., Jimenez, J.L. (2004). Particle morphology and density characterization by combined mobility and aerodynamic diameter measurements. Part 1: Theory. Aerosol Sci. Technol. 38, 1185–1205. http://doi.org/10.1080/027868290903907

  9. Fang, M., Chan, C.K., Yao, X. (2009). Managing air quality in a rapidly developing nation: China. Atmos. Environ. 43, 79–86. http://doi.org/10.1016/j.atmosenv.2008.09.064

  10. Hu, J., Ying, Q., Wang, Y., Zhang, H. (2015). Characterizing multi-pollutant air pollution in China: Comparison of three air quality indices. Environ. Int. 84, 17–25. http://doi.org/10.1016/j.​envint.2015.06.014

  11. Hu, M.T., Chen, S.J., Huang, K.L., Lin, Y.C., Chang-Chien, G.P., Tsai, J.H. (2009). Characterization of polychlorinated dibenzo-p-dioxin/dibenzofuran emissions from joss paper burned in a furnace with air pollution control devices. Sci. Total Environ. 407, 3290–3294. http://doi.org/10.1016/​j.scitotenv.2009.01.037

  12. Huang, C.J., Chen, K.S., Lai, Y.C., Wang, L.C., Chang-Chien, G.P. (2011). Wet deposition of polychlorinated dibenzo-p-dioxins/dibenzofuran in a rural area of Taiwan. Aerosol Air Qual. Res. 11, 732–748. http://doi.org/10.4209/aaqr.2011.08.0123

  13. Hystad, P., Larkin, A., Rangarajan, S., AlHabib, K.F., Avezum, Á., Calik, K.B.T., Chifamba, J., Dans, A., Diaz, R., du Plessis, J.L., Gupta, R., Iqbal, R., Khatib, R., Kelishadi, R., Lanas, F., Liu, Z., Lopez-Jaramillo, P., Nair, S., Poirier, P., Rahman, O., et al. (2020). Associations of outdoor fine particulate air pollution and cardiovascular disease in 157 436 individuals from 21 high-income, middle-income, and low-income countries (PURE): A prospective cohort study. Lancet Planet. Health 4, e235–e245. https://doi.org/10.1016/S2542-5196(20)30103-0

  14. Jeong, Y., Kim, S.J., Shin, K.H., Hwang, S.Y., An, Y.R., Moon, H.B. (2016). Accumulation and temporal changes of PCDD/Fs and dioxin-like PCBs in finless porpoises (Neophocaena asiaeorientalis) from Korean coastal waters: Tracking the effectiveness of regulation. Mar. Pollut. Bull. 105, 30–36. http://doi.org/10.1016/j.marpolbul.2016.03.007

  15. Jia, H., Huo, J., Fu, Q., Duan, Y., Lin, Y., Jin, X., Hu, X., Cheng, J. (2020). Insights into chemical composition, abatement mechanisms and regional transport of atmospheric pollutants in the Yangtze River Delta region, China during the COVID-19 outbreak control period. Environ. Pollut. 267, 115612. http://doi.org/10.1016/j.envpol.2020.115612

  16. Jiang, X., Hong, C., Zheng, Y., Zheng, B., Guan, D., Gouldson, A., Zhang, Q., He, K. (2015). To what extent can China's near-term air pollution control policy protect air quality and human health? A case study of the Pearl River Delta region. Environ. Res. Lett. 10, 104006. http://doi.org/​10.1088/1748-9326/10/10/104006

  17. Kyrkilis, G., Chaloulakou, A., Kassomenos, P.A. (2007). Development of an aggregate air quality index for an urban mediterranean agglomeration: Relation to potential health effects. Environ. Int. 33, 670–676. http://doi.org/10.1016/j.envint.2007.01.010

  18. Lee, K.L., Lee, W.J., Mwangi, J.K., Wang, L.C., Gao, X., Chang-Chien, G.P. (2016). Atmospheric PM2.5 and depositions of polychlorinated dibenzo-p-dioxins and dibenzofurans in Kaohsiung area, Southern Taiwan. Aerosol Air Qual. Res. 16, 1775–1791. http://doi.org/10.4209/aaqr.​2016.04.0168

  19. Lin, X., Mao, T., Ma, Y., Zou, X., Liu, L., Yin, W., Rao, M., Ye, J., Chen, C., Yu, H., Li, X., Yan, J. (2022). Influence of different catalytic metals on the formation of PCDD/Fs during co-combustion of sewage sludge and coal. Aerosol Air Qual. Res. 22, 220268. http://doi.org/10.4209/aaqr.​220268

  20. Liu, X., Cui, K., Hsieh, Y.K., Wang, Y.F., Wang, R. (2022). Study on air quality index, atmospheric pollutants and dry deposition of PCDD/Fs in the ambient air near Southwest China. Aerosol Air Qual. Res. 22, 220160. http://doi.org/10.4209/aaqr.220160

  21. Liu, Z., Qi, Z., Ni, X., Dong, M., Ma, M., Xue, W., Zhang, Q., Wang, J. (2021). How to apply O3 and PM2.5 collaborative control to practical management in China: A study based on meta-analysis and machine learning. Sci. Total Environ. 772, 145392. http://doi.org/10.1016/j.scitotenv.​2021.145392

  22. Melymuk, L., Robson, M., Diamond, M.L., Bradley, L.E., Backus, S. (2011). Wet deposition loadings of organic contaminants to Lake Ontario: Assessing the influence of precipitation from urban and rural sites. Atmos. Environ. 45, 5042–5049. http://doi.org/10.1016/j.atmosenv.2011.02.007

  23. Mi, H.H., Wu, Z.S., Lin, L.F., Lai, Y.C., Lee, Y.Y., Wang, L.C., Chang-Chien, G.P. (2012). Atmospheric dry deposition of polychlorinated dibenzo-p-dioxins/dibenzofurans (PCDD/Fs) and polychlorinated biphenyls (PCBs) in Southern Taiwan. Aerosol Air Qual. Res. 12, 1016–1029. http://doi.org/​10.4209/aaqr.2012.07.0172

  24. Moon, H.B., Lee, S.J., Choi, H.G., Ok, G. (2005). Atmospheric deposition of polychlorinated dibenzo-p-dioxins (PCDDs) and dibenzofurans (PCDFs) in urban and suburban areas of Korea. Chemosphere 58, 1525–1534. http://doi.org/10.1016/j.chemosphere.2004.11.014

  25. Mutuku, K.J., Lee, Y.Y., Chang-Chien, G.P., Lin, S.L., Chen, W.H., Hou, W.C. (2021). Chemical fingerprints for PM2.5 in the ambient air near a raw material storage site for iron ore, coal, limestone, and sinter. Aerosol Air Qual. Res. 21, 200624. http://doi.org/10.4209/aaqr.200624

  26. Ngo, T.H., Yang, Y.H., Chen, Y.C., Pan, W.C., Chi, K.H. (2020). Continuous nationwide atmospheric PCDD/F monitoring network in Taiwan (2006-2016): Variation in concentrations and apportionment of emission sources. Chemosphere 255, 126979. http://doi.org/10.1016/j.​chemosphere.2020.126979

  27. Nguyen, G.T.H., Nguyen, T.T.T., Shimadera, H., Uranishi, K., Matsuo, T., Kondo, A. (2022). Estimating mortality related to O3 and PM2.5 under changing climate and emission in continental Southeast Asia. Aerosol Air Qual. Res. 22, 220105. http://doi.org/10.4209/aaqr.220105

  28. Pan, S.Y., Chen, H.W., Hsu, S.C., Chou, C.C.K., Lin, Y.C., Chen, Y.W., Chi, K.H. (2022). Assessment of atmospheric PM2.5 and PCDD/Fs collected by different high-volume ambient air sampling systems. Aerosol Air Qual. Res. 22, 220116. http://doi.org/10.4209/aaqr.220116

  29. Prange, J.A., Gaus, C., Päpke, O., Müller, J.F. (2002). Investigations into the PCDD contamination of topsoil, river sediments and kaolinite clay in Queensland, Australia. Chemosphere 46, 1335–1342. http://doi.org/10.1016/S0045-6535(01)00266-1

  30. Querol, X., Alastuey, A., Rodriguez, S., Plana, F., Mantilla, E., Ruiz, C.R. (2001). Monitoring of PM10 and PM2.5 around primary particulate anthropogenic emission sources. Atmos. Environ. 35, 845–858. http://doi.org/10.1016/S1352-2310(00)00387-3

  31. Rodriguez-Urrego, D., Rodriguez-Urrego, L. (2020). Air quality during the COVID-19: PM2.5 analysis in the 50 most polluted capital cities in the world. Environ Pollut 266, 115042. http://doi.org/​10.1016/j.envpol.2020.115042

  32. Schuhmacher, M., Granero, S., Rivera, J., Müller, L., Llobet, J.M., Domingo, J.L. (2000). Atmospheric deposition of PCDD/Fs near an old municipal solid waste incinerator: Levels in Soil and vegetation. Chemosphere 40, 593–600. http://doi.org/10.1016/S0045-6535(99)00292-1

  33. Shah, D.P., Patel, D.P. (2021). A comparison between national air quality index, india and composite air quality index for Ahmedabad, India. Environ. Challenges 5, 100356. http://doi.org/10.1016/​j.envc.2021.100356

  34. She, Q., Peng, X., Xu, Q., Long, L., Wei, N., Liu, M., Jia, W., Zhou, T., Han, J., Xiang, W. (2017). Air quality and its response to satellite-derived urban form in the Yangtze River Delta, China. Ecol. Indic. 75, 297–306. http://doi.org/10.1016/j.ecolind.2016.12.045

  35. Shen, F., Ge, X., Hu, J., Nie, D., Tian, L., Chen, M. (2017). Air pollution characteristics and health risks in Henan Province, China. Environ. Res. 156, 625–634. http://doi.org/10.1016/j.envres.​2017.04.026

  36. Shih, M., Lee, W.S., Chang-Chien, G.P., Wang, L.C., Hung, C.Y., Lin, K.C. (2006). Dry deposition of polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDD/Fs) in ambient air. Chemosphere 62, 411–416. http://doi.org/10.1016/j.chemosphere.2005.04.064

  37. Ssebugere, P., Sillanpaa, M., Matovu, H., Mubiru, E. (2019). Human and environmental exposure to PCDD/Fs and dioxin-like PCBs in Africa: A review. Chemosphere 223, 483–493. http://doi.org/​10.1016/j.chemosphere.2019.02.065

  38. Suman (2021). Air quality indices: A review of methods to interpret air quality status. Mater. Today: Proc. 34, 863–868. http://doi.org/10.1016/j.matpr.2020.07.141

  39. Suryani R, C., Lee, W.J., Mutiara M.P, E., Mwangi, J.K., Wang, L.C., Lin, N.H., Chang-Chien, G.P. (2015). Atmospheric deposition of polychlorinated dibenzo-p-dioxins and dibenzofurans at coastal and high mountain areas in Taiwan. Aerosol Air Qual. Res. 15, 1390–1411. http://doi.org/10.4209/aaqr.2015.04.0246

  40. Tian, X., Cui, K., Sheu, H.L., Hsieh, Y.K., Yu, F. (2021a). Atmospheric wet deposition of PCDD/Fs in the ambient air. Aerosol Air Qual. Res. 21, 210096. http://doi.org/10.4209/aaqr.210096

  41. Tian, X., Cui, K., Sheu, H.L., Hsieh, Y.K., Yu, F. (2021b). Effects of rain and snow on the air quality index, PM2.5 Levels, and dry deposition flux of PCDD/Fs. Aerosol Air Qual. Res. 21, 210158. http://doi.org/10.4209/aaqr.210158

  42. Van den Berg, M., Birnbaum, L., Bosveld, A.T., Brunström, B., Cook, P., Feeley, M., Giesy, J.P., Hanberg, A., Hasegawa, R., Kennedy, S.W., Kubiak, T., Larsen, J.C., van Leeuwen, F.X., Liem, A.K., Nolt, C., Peterson, R.E., Poellinger, L., Safe, S., Schrenk, D., Tillitt, D., et al. (1998). Toxic equivalency factors (TEFs) for PCBs, PCDDs, PCDFs for humans and wildlife. Environ. Health Perspect. 106, 775–792. https://doi.org/10.1289/ehp.98106775

  43. Wan, S., Cui, K., Wang, Y.F., Wu, J.L., Huang, W.S., Xu, K., Zhang, J. (2020). Impact of the COVID-19 event on trip intensity and air quality in Southern China. Aerosol Air Qual. Res. 20, 1727–1747. http://doi.org/10.4209/aaqr.2020.07.0364

  44. Wang, W., Cui, K., Zhao, R., Hsieh, L.T., Lee, W.J. (2018). Characterization of the air quality index for Wuhu and Bengbu Cities, China. Aerosol Air Qual. Res. 18, 1198–1220. http://doi.org/​10.4209/aaqr.2018.04.0135

  45. Wu, X., Shi, G., Xiang, X., Yang, F. (2021). The characteristics of PM2.5 pollution episodes during 2016–2019 in Sichuan Basin, China. Aerosol Air Qual. Res. 21, 210126. http://doi.org/​10.4209/aaqr.210126

  46. Xia, Y., Zhang, L., Hu, B., Yu, J., Al-Ghamdi, A.A., Wageh, S. (2021). Design of highly-active photocatalytic materials for solar fuel production. Chem. Eng. J. 421, 127732. https://doi.org/​10.1016/j.cej.2020.127732

  47. Xu, K., Cui, K., Young, L.H., Wang, Y.F., Hsieh, Y.K., Wan, S., Zhang, J. (2020). Air quality index, indicatory air pollutants and impact of COVID-19 event on the air quality near Central China. Aerosol Air Qual. Res. 20, 1204–1221. http://doi.org/10.4209/aaqr.2020.04.0139

  48. Yu, F., Cui, K., Sheu, H.L., Hsieh, Y.K., Tian, X. (2021). Sensitivity analysis for dry deposition and PM2.5-bound content of PCDD/Fs in the ambient Air. Aerosol Air Qual. Res. 21, 210118. http://doi.org/10.4209/aaqr.210118

  49. Zhang, J., Cui, K., Wang, Y.F., Wu, J.L., Huang, W.S., Wan, S., Xu, K. (2020). Temporal variations in the air quality index and the impact of the COVID-19 event on air quality in Western China. Aerosol Air Qual. Res. 20, 1552–1568. http://doi.org/10.4209/aaqr.2020.06.0297

  50. Zhang, L., Yang, L., Bi, J., Liu, Y., Toriba, A., Hayakawa, K., Nagao, S., Tang, N. (2021). Characteristics and unique sources of polycyclic aromatic hydrocarbons and nitro-polycyclic aromatic hydrocarbons in PM2.5 at a highland background site in Northwestern China. Environ. Pollut. 274, 116527. http://doi.org/10.1016/j.envpol.2021.116527

  51. Zhang, Q., Zheng, Y., Tong, D., Shao, M., Wang, S., Zhang, Y., Xu, X., Wang, J., He, H., Liu, W., Ding, Y., Lei, Y., Li, J., Wang, Z., Zhang, X., Wang, Y., Cheng, J., Liu, Y., Shi, Q., Yan, L., et al. (2019). Drivers of improved PM2.5 air quality in China from 2013 to 2017. PNAS 116, 24463–24469. https://doi.org/10.1073/pnas.1907956116

  52. Zhang, X., Han, L., Wei, H., Tan, X., Zhou, W., Li, W., Qian, Y. (2022). Linking urbanization and air quality together: A review and a perspective on the future sustainable urban development. J. Cleaner Prod. 346, 130988. http://doi.org/10.1016/j.jclepro.2022.130988

  53. Zhou, L. (2021). Environmental regulation and the growth of the total-factor carbon productivity of China's industries: Evidence from the implementation of action plan of air pollution prevention and control. J. Environ. Manage. 296, 113078. http://doi.org/10.1016/j.jenvman.​2021.113078

  54. Zhou, Y., Yue, Y., Bai, Y., Zhang, L. (2020). Effects of rainfall on PM2.5 and PM10 in the middle reaches of the Yangtze River. Adv. Meteorol. 2020, 2398146. http://doi.org/10.1155/2020/​2398146


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