Effects of Rain and Snow on the Air Quality Index, PM2.5 Levels, and Dry Deposition Flux of PCDD/Fs

Received: June 30, 2021
Revised: July 21, 2021
Accepted: July 22, 2021

 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.

Cite this article:

Tian, X., Cui, K., Sheu, H.L., Hsieh, Y.K., Yu, F. (2021). Effects of Rain and Snow on the Air Quality Index, PM_2.5 Levels, and Dry Deposition Flux of PCDD/Fs. Aerosol Air Qual. Res. 21, 210158. https://doi.org/10.4209/aaqr.210158

HIGHLIGHTS

• The air quality index (AQI) before, during and after rain were investigated.
• The atmospheric PCDD/F dry deposition flux before, and after the rain were studied.
• The PM_2.5 concentration before, during and after rain were also investigated.

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

1 INTRODUCTION

In the past few decades, with the rapid development of the social economy, industrial production, vehicle exhaust emissions, coal and other energy combustion has produced a large number of pollutants, which have seriously harmed the atmospheric environment (Liu et al., 2012). Many studies have shown that air pollution is closely related to the incidence of lung cancer, cardiovascular diseases, and other diseases that seriously threaten human health (McDonnell et al., 2000; Pope et al., 2009).

The Air Quality Index (AQI) is an index that can quantitatively describe air quality and can represent the short-term air quality status and trends in variation in a city. PM_2.5 is an important factor causing haze, which has a great impact on environmental air quality (Li et al., 2015). The number of deaths caused by respiratory diseases is positively correlated with atmospheric particulate matter (PM). PM_2.5 is small in diameter, highly active, and prone to carrying toxic and harmful substances (Dai et al., 2015). Therefore, issues related to air quality are attracting increasing attention from the public (Brauer et al., 2016).

Dioxins are polyhalogenated or polychlorinated aromatic compounds with a high degree of similarity in terms of structure and properties. They comprise POPs (persistent organic compounds). There are many homologous isomers, including coplanar polychlorinated biphenyl (co-PCBs), polychlorinated dibenzo-p-dioxins (PCDDs), and polychlorinated dibenzo furans (PCDFs) (Schecter et al., 2006; Redfern et al., 2017). PCDDs are derivatives of dibenzo-p-dioxins. There are 75 compounds in total, 7 of which have strong biological toxicity. Among them, 2,3,7,8-TCDD is the most toxic compound discovered so far. Its toxicity is about 900 times that of arsenic, and it is called “the poison of the century” (Van den Berg et al., 1998; Li et al., 2016). PCDFs, derivatives of dibenzofuran, comprise 135 compounds, 10 of which are biotoxic. PCDD/Fs are mainly produced by natural factors and human activities. Natural factors include volcanic eruptions, forest fires, lightning, and photochemical reactions (Prange et al., 2002; Kim et al., 2003). Human activities include the use of large quantities of chlorinated chemicals in industrial production (Ma et al., 2019), waste incineration (Lin et al., 2014), the pharmaceutical industry, coal-based power generation, and heating (Cheruiyot et al., 2016; Zhan et al., 2019; Qiu et al., 2020). In addition, vehicles that use diesel or gasoline fuel, such as cars and motorcycles, also emit PCDD/Fs in their exhaust (Zhao et al., 2019; Chen et al., 2020). Human exposure to a high PCDD/F environment can cause facial irritation accompanied by skin and liver damage (Marinković et al., 2010). They may also cause endocrine disorders, damage the reproductive system, and may cause immune dysfunction and mental irritability, among other symptoms (Srogi et al., 2008). After PCDD/Fs are discharged into the atmosphere, they are transported, mixed, and diluted as a result of horizontal movement of the atmosphere, vertical turbulence, and diffusion movement in the atmosphere at different scales. Atmospheric transport transfers PCDD/Fs to water and soil, and eventually into the food chain and human bodies (Lohmann and Jones, 1998; Hu et al., 2009).

The removal of persistent organic pollutants occurs mainly through atmospheric subsidence. This refers to the process of atmospheric pollutants being settled on the ground or water in specific ways, which can be divided into dry and wet deposition (Brzuzy and Hites 1996; Jurado et al., 2005). It has been found that environmental pollutants such as PCDD/Fs can be removed using these processes (Huang et al., 2011). Wet deposition refers to the process of removing particulate matter from the atmosphere through rainfall, snowfall, etc. It is an effective method by which to remove atmospheric particles and trace gaseous pollutants (Moon et al., 2005; Melymuk et al., 2011). Studies have shown that rainfall can improve air quality. The larger the initial concentration of particulate matter, the better the rainfall cleaning effect is, and the clearer effect of PM₁₀ is better than that of PM_2.5 (Zhou et al., 2020). Due to the effective removal of particulate pollutants, air quality is generally improved after the precipitation process. Ambient temperature, rainfall intensity, particle size, and concentration of particulate pollutants do affect the wet deposition process (Chang et al., 2004; Wu et al., 2009; Wang et al., 2010). Dry deposition is a process of sedimentation of various particles suspended in the atmosphere at their own final velocity, which is one of the important ways for air pollutants to enter the ecosystem (Mi et al., 2012). Wind speed, ambient temperature, humidity, particle size, and the state of pollutants all affect the dry deposition flux (Chandra et al., 2015).

In this study, a total of eighteen precipitation (rain or snow) events were chosen in Jinan and Qingdao cities, respectively. They were divided into AQI reduction or AQI elevation events. The AQI PM_2.5 concentrations before precipitation, in the precipitation, and after precipitation are presented and discussed. In addition, the effects of precipitation on the dry deposition flux of total PCDD/Fs-WHO₂₀₀₅-TEQ were investigated and are discussed.

 
2 METHODS

Two cities, Jinan (36°40′N, 117°00′E) and Qingdao (36°0′N, 120°3′E) in Shandong Province, China, were selected and evaluated in this study. Data for three years (from 2018 to 2020) were obtained for both Jinan and Qingdao. The PM concentration (including daily PM_2.5 and PM₁₀), gaseous pollutants (including daily SO₂, NO₂, CO, and O₃), and daily precipitation records were obtained from local air quality monitoring stations, local weather bureaus, and the Statistics Yearbook of China.

 
2.1 PCDD/F Concentration

The total PCDD/F concentration was simulated using a regression analysis of the PM₁₀ concentrations. Tang et al. (2017) reported that there is a high correlation between PM₁₀ values and total PCDD/F mass concentrations. Their research included the following two regression equations:

where Y₁, Y₂ represent the total PCDD/F concentration (pg m^–3); x represents the PM₁₀ concentration in ambient air (µg m^–3), and where the final total PCDD/F concentration is the average of Y₁ and Y₂.

 
2.2 Dry Deposition

The dry deposition flux is composed of the addition of the diffusion of gaseous matter and the deposition of particulate matter.

where F_T is the total dry deposition flux (pg WHO₂₀₀₅-TEQ m^–2 month^–1); F_g is the diffusion of gaseous matter producing dry deposition flux (pg WHO₂₀₀₅-TEQ m^–2 month^–1); F_p is the gravitational settling of particulate matter contributing to dry deposition flux (pg WHO₂₀₀₅-TEQ m^–2 month^–1); C_T is total PCDD/F concentration in the atmosphere (pg m^–3); V_d,T is the dry deposition velocity of PCDD/Fs (gas+particle phases), 0.42 cm s^–1 (Shih et al., 2006).

C_g is the calculated PCDD/F concentration in the gas phase (pg m^–3); V_d,g is the dry deposition velocity of PCDD/Fs in gas phase, 0.01 cm s^–1 (Sheu et al., 1996); C_p is the calculated PCDD/F concentration in the particle phase (pg m^–3), and V_d,p is the dry deposition velocity of PCDD/Fs in the particle phase (cm s^–1).

 
2.3 Air Quality Index (AQI)

The air quality index (AQI) is a quantitative description of air quality data, which can represent the short-term air quality status and trends in a city. The sub-AQI of the six criteria pollutants were first calculated with the observation concentrations, as shown in Eq. (5) (Shen et al., 2017; She et al., 2017). The overall AQI represents the maximum of the sub-AQI of all pollutants, where when the AQI is higher than 50, the highest sub-AQI contributor is defined as the primary pollutant on that day, as shown in Eq. (6) (Shen et al., 2017; She et al., 2017):

where IAQI_p represents the air quality sub index for air pollutant p; C_P represents the concentration of pollutant p; C_low represents the concentration breakpoint that is ≤ C_P; C_high represents the concentration breakpoint that is ≥ C_P; I_low represents the index breakpoint corresponding to C_low, and I_high represents the index breakpoint corresponding to C_high.

The six air pollutants under consideration in this work have acute effects on human health. The daily AQIs were calculated using the 24-hour average concentrations of SO₂, NO₂, PM_2.5, PM₁₀, and CO, and the daily average 8-hour maximum concentration of O₃. The United States Environmental Protection Agency (US EPA) AQI has classified the ranges of AQI values related to air quality into six classes: Grade I: 0–50 (Good, Green); Grade II: 51–100 (Moderate, Yellow); Grade III: 101–150 (Unhealthy for Sensitive Groups; Orange); Grade IV: 151–200 (Unhealthy; Red); Grade V: 201–300 (Very unhealthy; Purple), and Grade VI: 300–500 (Hazardous; Maroon) (Hu et al., 2015; Lanzafame et al., 2015; She et al., 2017; Zhao et al., 2018a).

 
3 RESULTS AND DISCUSSION

 
3.1 Effects of Precipitation on Reductions in the AQI

In Jinan, from 2018–2020, there were a total of nine precipitation events (seven rain and two snow events) selected for the purposes of this study. In terms of the air quality index, in these nine events, for seven of them, six of which were rain, and one of which was snow, the air quality index was reduced; in other words, in these seven events, the air quality improved. In Qingdao, during the same period, there were a total nine precipitation events selected as well; six of them were rain events, and three of them were snow events. In eight of them, the air quality index was reduced. The dates, duration of precipitation, and amount of precipitation are shown in Table 1.

 
3.1.1 AQI analysis

In Jinan, the seven events for which the air quality index was reduced are shown in Table 1. The AQI before the rain ranged between 65 and 195 and averaged 124 (Figs. 1(a2–a7)), while during the rain, the AQI ranged between 38 and 152 and averaged 73 (Figs. 1(b2–b7)); however, after the rain, the values ranged from 41 to 142 and averaged 80 (Figs. 1(c2–c7)). The primary air pollutant was O₃. Comparing the AQI during the rain with that before rain, respectively, the AQI reduction during the rain ranged between 24% and 60% and averaged 41% lower than that before the rain, respectively. Regarding the AQI after rain with that before the rain, respectively, the AQI reduction after the rain was between 18% and 73% and averaged 35% lower than that before the rain, respectively. This was mainly due to the occurrence of wet deposition, the process of removing particles from the atmosphere through precipitation processes. It is an effective method by which to remove atmospheric particles and trace gaseous pollutants. Because rain depends on particles floating in the air, it falls with them to the ground, reducing the concentration of particulate pollutants in the atmosphere (Kaupp and McLachlan, 1998). Wind also dilutes the horizontal transport of pollutants. Rainfall when the wind speed is large or small, up and down, around the irregular swing, and this irregular, random swing can make other components mixed, is conducive to the dilution and diffusion of pollutants. The above results did reveal that, in Jinan, the rain improved the ambient air quality.

Fig. 1. The fractions of the six AQI categories for Jinan (a2 –7, 9) before the precipitation, (b2 –7,9) during the precipitation and (c2 –7, 9), and after the precipitation from 2018–2020 for AQI reduction events.

Fig. 1. (continued). 

Fig. 1. (continued). 

As for the one snow event in Jinan, the AQI before the snow ranged between 117 and 123 and averaged 120 (Fig. 1(a9)). During the snow, it ranged between 113 and 138 and averaged 126 (Fig. 1(b9)); however, the AQI after the snow ranged from 69 to 99 and averaged 84. The primary air pollutant was PM₁₀. Comparing the AQI during the snow with that before the snow, the AQI during the snow was 5.0% higher than that before the snow, and the value after the snow was 32% lower than that before snow. This suggests that snowfall also reduces the air quality index to a certain extent. Snow has a purifying effect on the air, because the water molecules in the air in the crystallization process of forming snowflakes, the surface area of the rapid increase, can effectively absorb the particles in the air, and in the process of snow will bring them to the ground. In fact, contaminants such as total metals can be detected in the snow to determine the level of local air pollution (Krupnova et al., 2021).

As Fig. 2. shows in Qingdao, of the eight events where the AQI was reduced (Table 1), five of them were rain events, and three of them were snow events. The AQI before the rain events (Figs. 2(a10–a11, a14, a16–a17)) ranged between 39 and 117 and averaged 75, while during the rain (Figs. 2(b10–b11, b14, b16–b17)), it ranged between 33 and 88 and averaged 69; however, the AQI after the rain (Figs. 2(c10–c11, c14, c16–17)) ranged from 37 to 66 and averaged 49. The primary air pollutant was O₃. Comparing the AQI during the rain with that before the rain, respectively, the AQI reduction in the rain ranged between –24% and 28% and averaged 7.0% lower than that before the rain, respectively. Comparing the AQI after the rain with that before the rain, respectively, the AQI reduction after the rain ranged between 14% and 47% and averaged 32% lower than that before the rain, respectively. In general, rain did improve air quality, because it scavenged the particulates or dissolved the gaseous pollutants out of the air and carried them to the ground.

Fig. 2. The fractions of the six AQI categories for Qingdao for reductions in the AQI (a10–14, 16–18) before the precipitation, (b10–14, 16–18), during the precipitation, and (c10–14, 16–18) after the precipitation for the period 2018 –2020. 

Fig. 2. (continued). 

Fig. 2. (continued).

As for the three snow events where the AQI was reduced in Qingdao (Table 1), the AQI before the snow (Figs. 2(a12–a13, a18)) ranged between 29 and 105 and averaged 70, while during the snow (Figs. 2(b12–b13, b18)), it ranged between 40 and 112 and averaged 71; however, the AQI after the snow (Figs. 2(c12–c13, c18)) ranged from 47 to 68 and averaged 59. The primary air pollutant was PM₁₀. Comparing the AQI during the snow with that before the snow, respectively, the AQI reduction in the snow ranged between –42% and 24% and averaged 8.0% higher than that before the snow event. Comparing the AQI after snow with that before snow, respectively, the AQI reduction after the snow ranged between 11% and 18% and was 15% lower than that before the snow, respectively. The air quality deteriorated during the snowfall and gradually improved after the snowfall.

As a whole, combined both in Jinan and in Qingdao, there were totally fifteen precipitation events were positively for the AQI reduction, the AQI ranged between 29 and 195 and averaged 79, compared the AQI in and after the precipitation, respectively, with that of before precipitation, the reduction fraction of AQI were 23% and 32%, respectively.

 
3.1.2 PM_2.5 concentration

Fig. 3. shows the PM_2.5 concentration variations in the events in Jinan (b–g) before the rain, during the rain, and after the rain for the period 2018–2020 when the AQI was reduced.

Fig. 3. Variations in the PM2.5 concentration for Jinan (b–g, i) before the precipitation, during the precipitation, and after the precipitation from 2018–2020 for the reduced AQI events. 

In Jinan, of the seven events where the air quality index was found to be reduced, six of them were rain events. As Fig. 3. shows, the PM_2.5 concentrations in the six rain events before the rain ranged between 28 and 146 µg m^–3 and averaged 58 µg m^–3; during the rain, they ranged between 17 and 116 µg m^–3 and averaged 39 µg m^–3, and the PM_2.5 concentrations after the rain ranged from 14 to 59 µg m^–3 and averaged 32 µg m^–3. Comparing the PM_2.5 concentration during the rain with that before the rain, respectively, the PM_2.5 concentration reduction in the rain ranged between 14% and 55% and averaged 32% lower than that before the rain, respectively. Regarding the PM_2.5 concentration after the rain with that before the rain, respectively, the PM_2.5 concentration reductions after the rain ranged between 21% and 73% and averaged 45% lower than that before the rain, respectively. During the rainfall period, the PM_2.5 concentration continued to decrease, indicating that rainfall can improve air quality to a certain extent. This due to the fact that the rain scavenged the PM_2.5 out of the air and gravity caused it to settle on the ground.

As to the one snow event where the AQI was reduced in Jinan (Fig. 3(i)), the PM_2.5 concentration before the snow ranged between 88 and 93 µg m^–3 and averaged 91 µg m^–3; during the snow, the concentration ranged between 85 and 105 µg m^–3 and averaged 95 µg m^–3 (Fig. 3(i)), and after the snow the concentration ranged from 50 to 74 µg m^–3 and averaged 62 µg m^–3 (Fig. 3(i)). The PM_2.5 concentrations during the snow were 4.0% higher than those before the snow, and were 32% lower after the snow than before the snow, respectively. Snowfall can wash away pollutants in the air to a certain extent. During the crystallization of water molecules in the air to form snowflakes, the surface area increases rapidly, so particles can be effectively absorbed in the air and brought down to the ground. This mechanism revealed that the particulates in the air were removed by the rain and resulted in a positive effect on air quality.

As shown in Figs. 4(a–e, g–i), in Qingdao, of the eight events where the air quality index was reduced, five of them were rain events. The PM_2.5 concentrations before the rain were between 18 and 38 µg m^–3 and averaged 29 µg m^–3 (Figs. 4(a–b, e, g–h)); those during the rain ranged between 11 and 38 µg m^–3 and averaged 24 µg m^–3, and those after the rain ranged from 10 to 3 µg m^–3 and averaged 18 µg m^–3. Comparing the PM_2.5 concentration during the rain with that before the rain, respectively, the PM_2.5 concentration reductions during the rain ranged between 0% and 50% and averaged 21% lower than those before the rain, respectively. Comparing the PM_2.5 concentrations after the rain with those before rain showed that the PM_2.5 concentration reduction after the rain ranged between 25% and 61% and averaged 37% lower than that before the rain. Rainfall in atmospheric particulate matter removal effect lag period, a period of time after the rain can still affect the particle concentration, this may be due to rainfall process that leads to increased atmospheric humidity, particles are more likely to collide with raindrops fusion and deposition, and rainfall is usually accompanied by strong winds, is more advantageous to aerosol particles dissipate (Guo et al., 2016).

Fig. 4. Variations in the PM 2.5 concentration in Qingdao (a –e, g–i) before the precipitation, during the precipitation, and after the precipitation from 2018 –2020 for the reduced AQI events.

For the three snow events where the air quality index was reduced in Qingdao, the PM_2.5 concentrations before the snow ranged between 17 and 84 µg m^–3 and averaged 56 µg m^–3 (Figs. 4(c–d)); during the snow, they ranged between 13 and 64 µg m^–3 and averaged 37 µg m^–3, and after the snow, they ranged from 15 to 46 µg m^–3 and averaged 33 µg m^–3. Comparing the PM_2.5 concentration during the snow with that before the snow, the PM_2.5 concentration reductions during the snow ranged between –2% and 46% and averaged 27% lower than those before the snow, respectively. Comparing the PM_2.5 concentrations after the snow with those before the snow, respectively, the reductions after the snow between 24% and 56% and averaged 37 % lower than that before the snow, respectively. The average PM_2.5 concentration in Weihai and Qingdao are lower than that in Jinan, this is related to the abundant rainfall, strong wind and fast air circulation in coastal cities, which are conducive to the wet deposition and thus accelerate the diffusion of pollutants (Zhao et al., 2018b).

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

Fig. 5. shows the dry deposition flux for the variations in the total PCDD/Fs-WHO₂₀₀₅-TEQ in Jinan, where Figs. 5(b–g) is before the rain, during the rain, and after the rain from 2018–2020 for the reduced AQI events.

Fig. 5. Variations in the dry deposition flux in the total PCDD/Fs-WHO2005-TEQ in Jinan (b–g, i) before the precipitation, during the precipitation, and after the precipitation from 2018–2020 for reduced AQI events. 

In Jinan, of the seven events where the air quality index values were reduced, six of them were rain events, and one of them was a snow event. As shown in Fig. 5., the dry deposition flux of total-PCDD/Fs-WHO₂₀₀₅-TEQ for the six rain events before the rain ranged between 388.1 and 1152 pg WHO₂₀₀₅-TEQ m^–2 day^–1 and averaged 676.7 pg WHO₂₀₀₅-TEQ m^–2 day^–1; the dry deposition flux for the total PCDD/Fs-WHO₂₀₀₅-TEQ after the rain ranged from 157.8 to 600.1 pg WHO₂₀₀₅-TEQ m^–2 day^–1and averaged 408.6 pg WHO₂₀₀₅-TEQ m^–2 day^–1. Comparing the dry deposition flux for the total PCDD/Fs-WHO₂₀₀₅-TEQ after the rain with that before the rain, the dry deposition flux for the reduction in the total PCDD/Fs-WHO₂₀₀₅-TEQ after the rain ranged between 11% and 60% and averaged 40% lower than that before the rain, respectively.

For the one snow event where the dry deposition flux for the total PCDD/Fs-WHO₂₀₀₅-TEQ reduced in Jinan (Fig. 5(i)), the dry deposition flux in the total PCDD/Fs-WHO₂₀₀₅-TEQ before the snow ranged between 904.8 and 984.1 pg WHO₂₀₀₅-TEQ m^–2 day^–1 and averaged 944.5 pg WHO₂₀₀₅-TEQ m^–2 day^–1; the dry deposition of flux in the total PCDD/Fs-WHO₂₀₀₅-TEQ after the snow ranged from 436.8 to 697.4 pg WHO₂₀₀₅-TEQ m^–2 day^–1 and averaged 558.1 pg WHO₂₀₀₅-TEQ m^–2 day^–1 (Fig. 3(i)). A comparison of the dry deposition flux in the total PCDD/Fs-WHO₂₀₀₅-TEQ after the snow indicated that the total PCDD/Fs-WHO₂₀₀₅-TEQ was 41% lower than that before the snow.

As shown in Figs. 6(a–e, g–i), in Qingdao, of the eight events where there was a reduction in the AQI, five of them were rain events, where the dry deposition flux in the total PCDD/Fs-WHO₂₀₀₅-TEQ before the rain ranged between 145.7 and 667.1 pg WHO₂₀₀₅-TEQ m^–2 day^–1 and averaged 402.3 pg WHO₂₀₀₅-TEQ m^–2 day^–1 (Figs. 6(a–b, e, g–h)); the dry deposition flux in the total PCDD/Fs-WHO₂₀₀₅-TEQ after the rain ranged from 145.7 to 548.3 pg WHO₂₀₀₅-TEQ m^–2 day^–1 and averaged 288.4 pg WHO₂₀₀₅-TEQ m^–2 day^–1. Comparing the dry deposition flux in the total PCDD/Fs-WHO₂₀₀₅-TEQ after the rain with that before the rain, the reductions after the rain ranged between 2.0% and 51% and averaged 28% lower than those before the rain.

Fig. 6. Variations in the dry deposition flux in the total PCDD/Fs -WHO2005-TEQ for Qingdao (a –e, g –i) before the precipitation, during the precipitation, and after the precipitation from 2018–2020 for reduced AQI events. 

For the three snow events where the air quality index was reduced in Qingdao, the dry deposition flux in the total PCDD/Fs-WHO₂₀₀₅-TEQ before the snow ranged between 368.8 and 726.5 pg WHO₂₀₀₅-TEQ m^–2 day^–1 and averaged 552.5 pg WHO₂₀₀₅-TEQ m^–2 day^–1 (Figs. 6(c–d, i)); after the snow, these values ranged from 333.7 to 479.3 pg WHO₂₀₀₅-TEQ m^–2 day^–1 and averaged 392.3 pg WHO₂₀₀₅-TEQ m^–2 day^–1. Comparing the dry deposition of flux in the total PCDD/Fs-WHO₂₀₀₅-TEQ after the snow with that before the snow, the reduction in the dry deposition flux in the total PCDD/Fs-WHO₂₀₀₅-TEQ after the snow ranged between 17% and 37% and averaged 29% lower than that before the snow.

As a whole, a total of fifteen precipitation events reduced the AQI, where the PCDD/F dry deposition flux ranged between 145.7 and 1152 pg WHO₂₀₀₅-TEQ m^–2 day^–1 and averaged 476.7 pg WHO₂₀₀₅-TEQ m^–2 day^–1. Comparing the above events after the precipitation with those before the precipitation, the reduction in the PCDD/Fs dry deposition fraction averaged 35%. In fact, the removal efficiency of persistent organic pollutants by snow or rain depends on the nature of human pollutants and snow, and the ambient temperature. Below 0°C, rain generally clears more organic vapors than snow, because the surface of snow has less ability to absorb these chemicals than liquid droplets. For organic macromolecule vapors with low water solubility, the change of specific surface area and particle scavenging rate of snow will make the snow removal rate stronger. Below –10°C, the more chemicals that change from gas to liquid form are present in atmospheric particles and on the surface of snow, which is more conducive to pollutant (Lei et al., 2004).

 
3.2 Effects of Precipitation on AQI Elevation

In Jinan, from 2018–2020, there was a total of nine events of precipitation (seven rain and two snow events) selected for the purposes of this study, where two events (1 and 8) exhibited elevated AQI values. In Qingdao, during the same period, there were a total of nine events of precipitation, and six rain events and three snow events were selected in this study. Among these, one (event 15) had an elevated AQI (Table 1).

 
3.2.1 AQI analysis

In Jinan, for the two events with an elevated AQI (Table 1), the AQI before the rain ranged between 125 and 130 and averaged 128 (Fig. 7(a8)). During the rain, the AQI values ranged between 55 and 93 and averaged 72 (Fig. 7(a8)), and values after the rain ranged from 121 to 139 and averaged 130 (Fig. 7(a8)). The AQI during the rain averaged 43% lower than that before the rain; and the AQI after the rain was 2.0% higher than that before the rain. This may have been due to a weak summer high wind and too little precipitation, which is not conductive to the dilution and diffusion of pollutants. On rainy days, air pollutants will be covered with water vapor, which is more likely to cause the accumulation of pollutants, increase the particulate concentration, and thus elevate the AQI.

Fig. 7. The fractions for the six AQI categories for Jinan in (a1, 8) before the precipitation, (b1, 8) during the precipitation, and (c1 , 8) after the precipitation from 2018 – 2020 for the elevated AQI events. 

In the one snow event with an elevated AQI in Jinan (Table 1), the AQI before the snow ranged between 66 and 71 and averaged 69 (Fig. 7(a1)). During the snow, the values ranged between 104 and 122 and averaged 113 (Fig. 9(a1)), and the values after the snow ranged from 110 to 147 and averaged 129. Comparing the AQI during and after the snow, the AQI values were 65% and 88% higher than those before the snow, respectively. This is because in cold winter, the wind speed is low, the atmosphere become more stable, resulting in both poor both atmospheric vertical convection and horizontal dispersion, so the AQI were elevated. At the same time, at a certain event of snowstorm, both automobile exhaust and stationary source emission increased and then result in an increase of AQI (Nidzgorska-Lencewicz et al., 2020).

In Qingdao, for the one event where the AQI was elevated (Table 1), the AQI before the rain ranged between 41 and 100 and averaged 71 (Fig. 8). During the rain, the values ranged between 24 and 46 and averaged 35. The AQI values after the rain ranged from 70 to 94 and averaged 82. The AQI values during the rain were 51% lower than those before the rain. However, the values before the rain averaged 16% higher than those before the rain.

Fig. 8. The fractions of the six AQI categories for Qingdao (a15) before the precipitation, (b15) during the precipitation, and (c15) after the precipitation from 2018–2020 for the elevated AQI event.

As a whole, a total of three precipitation events displayed the AQI elevation in Jinan and Qingdao, where the AQI ranged between 24 and 147 and averaged 91. When comparing the values during and after the precipitation with those before the precipitation, the increased AQI fractions were -18% and 28%, respectively.

 
3.2.2 PM_2.5 concentration

Fig. 9 shows the variations in the PM_2.5 concentration in Jinan in (a, h) before the precipitation, during the precipitation, and after the precipitation from 2018–2020 for the elevated AQI events.

 Fig. 9. The variations in the PM_2.5 concentration in Jinan (a, h) before the precipitation, during the precipitation, and after the precipitation from 2018–2020 for the elevated AQI events.

In Jinan, for the one rain event with an elevated AQI (Fig. 9), the PM_2.5 concentration before the rain ranged between 25 and 27 µg m^–3 and averaged 26 µg m^–3. During the rain, the concentration ranged between 19 and 48 µg m^–3 and averaged 34 µg m^–3. After the rain, it ranged from 34 to 36 µg m^–3 and averaged 35 µg m^–3. Comparing the average PM_2.5 concentration during the rain and after the rain with that before the rain, the increased fractions were 32% and 35%, respectively.

For the one snow event with an elevated AQI in Jinan (Fig. 9(a)), the PM_2.5 concentration before the snow ranged between 46 and 50 µg m^–3 and averaged 48 µg m^–3. During the snowstorm, the concentration ranged between 78 and 92 µg m^–3 and averaged 85 µg m^–3. After the snowstorm, the concentration ranged from 83 to 112 µg m^–3 and averaged 98 µg m^–3. The PM_2.5 concentration during the snow was 77% higher than that before the snow, and after the snow, the concentration was 103% higher than that before the snow. Since snowfall occurs in winter, northern cities burn coal and other resources for heating, resulting in increased PCDD/Fs emissions and air quality becomes worse (Cheruiyot et al., 2015).

In Qingdao, for one event with an elevated AQI (Fig. 10), the PM_2.5 concentration before the rain ranged between 17 and 42 µg m^–3 and averaged 30 µg m^–3. During the rain, the concentration was 4.0 µg m^–3 and also averaged 4.0 µg m^–3. The PM_2.5 concentration after the rain ranged from 20 to 28 µg m^–3 and averaged 24 µg m^–3. The PM_2.5 concentration during the rain was 86% lower than that before the rain, and the concentration after the rain was 19% lower than that before the rain.

Fig. 10. The variations in the PM_2.5 concentration in Qingdao (f) before the precipitation, during the precipitation, and after the precipitation from 2018–2020 for the elevated AQI event.

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

In Jinan, for the two events with elevated AQI values, in the one rain event shown in Fig. 11, the dry deposition flux in the total-PCDD/Fs-WHO₂₀₀₅-TEQ before the rain ranged between 444.3 and 517.4 pg WHO₂₀₀₅-TEQ m^–2 day^–1 and averaged 480.9 pg WHO₂₀₀₅-TEQ m^–2 day^–1. The flux after the rain ranged from 365.6 to 388.1 pg WHO₂₀₀₅-TEQ m^–2 day^–1 and averaged 376.8 pg WHO₂₀₀₅-TEQ m^–2 day^–1. The dry deposition flux in the total-PCDD/Fs-WHO₂₀₀₅-TEQ after the rain was 22% lower than that before the rain.

Fig. 11. Variations in the dry deposition flux in the total-PCDD/Fs-WHO₂₀₀₅-TEQ for Jinan (a, h) before the precipitation and after the precipitation from 2018–2020 for the elevated AQI events.

For the one snow event in Jinan, the dry deposition flux in the total-PCDD/Fs-WHO₂₀₀₅-TEQ before the snow ranged between 55 and 56 pg WHO₂₀₀₅-TEQ m^–2 day^–1 and averaged 527.8 pg WHO₂₀₀₅-TEQ m^–2 day^–1. The values after the snow ranged from 794.6 to 946.2 pg WHO₂₀₀₅-TEQ m^–2 day^–1 and averaged 870.4 pg WHO₂₀₀₅-TEQ m^–2 day^–1. The dry deposition flux in the total-PCDD/Fs-WHO₂₀₀₅-TEQ after the snow was 65% higher than that before the snow.

In Qingdao, for the one rain event with an elevated AQI shown in Fig. 12, the dry deposition flux in the total-PCDD/Fs-WHO₂₀₀₅-TEQ before the rain ranged between 191.3 and 371.2 pg WHO₂₀₀₅-TEQ m^–2 day^–1 and averaged 281.3 pg WHO₂₀₀₅-TEQ m^–2 day^–1. The values after the rain ranged from 270.0 to 331.9 pg WHO₂₀₀₅-TEQ m^–2 day^–1 and averaged 300.9 pg WHO₂₀₀₅-TEQ m^–2 day^–1. The dry deposition flux in the total-PCDD/Fs-WHO₂₀₀₅-TEQ after the rain was 7.0% higher than that before the rain.

Fig. 12. Variations in the dry deposition flux in the total-PCDD/Fs-WHO2005-TEQ for Qingdao (f) before the precipitation, and after the precipitation during 2018–2020 for AQI elevation events. 

As a whole, a total of three precipitation events exhibited an elevation in the AQI, where the PCDD/F dry deposition flux values ranged between 191.3 and 946.2 pg WHO₂₀₀₅-TEQ m^–2 day^–1 and averaged 473.0 pg WHO₂₀₀₅-TEQ m^–2 day^–1. Comparing these values after the precipitation with those before the precipitation, the increase in the dry deposition fraction of PCDD/Fs was 20%.

4 CONCLUSION

This study provided an investigation of the effects of eighteen precipitation events (rain or snow) in both Jinan and Qingdao in Shandong Province, China, on the air quality index, PM_2.5 concentrations, and dry deposition of PCDD/Fs. The results are summarized as follows:

1. In Jinan, in the seven precipitation events demonstrating reductions in the AQI, the AQI ranged between 38 and 195 and averaged 94. As a whole, compared to during and after the precipitation, before the precipitation, the AQI reduction fractions were 34% and 40%, respectively. In Qingdao, for the eight precipitation events demonstrating reductions in the AQI, the AQI reductions ranged between 29 and 112 and averaged 65. As a whole, compared that in and after the precipitation, respectively, with that of before the precipitation, the reductions in the AQI fractions were 2.0% and 26%, respectively.
   
   
2. For Jinan, in the two precipitation events demonstrating an elevation in the AQI, the AQI ranged between 55 and 147 and averaged 104. As a whole, compared that in and after the precipitation, respectively, with that of before the precipitation, the increase fraction of AQI were 11% and 45%, respectively. For Qingdao, the one precipitation event with a reduction in the AQI, the AQI ranged between 24 and 100 and averaged 63. As a whole, compared that in and after the precipitation, respectively, with that of before the precipitation, the increased fraction of AQI were 51% and 16%, respectively.
   
   
3. In Jinan, for the seven precipitation events demonstrating a reduction in the AQI, the PM₅ concentration ranged between 14 and 146 µg m^–3 and averaged 49 µg m^–3. As a whole, compared that in and after the precipitation, respectively, with that of before the precipitation, the reduction fraction of PM_2.5 concentration were 25% and 43%, respectively. In Qingdao, for the eight precipitation events demonstrating a reduction in the AQI, the PM_2.5 concentration ranged between 10 and 84 µg m^–3 and averaged 47 µg m^–3. As a whole, comparing the concentration after the precipitation with that before the precipitation, the reductions in the PM_2.5 concentration were 26% and -90%, respectively.
   
   
4. For the two precipitation events demonstrating an elevation in the AQI in Jinan, the PM₅ concentration ranged between 19 and 112 µg m^–3 and averaged 54 µg m^–3. Comparing the concentration after the precipitation with that before the precipitation, the increases in the PM_2.5 concentration were 57% and 81%, respectively. For Qingdao, for the one precipitation event showing an elevation in the AQI, the PM_2.5 concentration ranged between 4.0 and 42 µg m^–3 and averaged 20 µg m^–3. Comparing the concentration after the precipitation with that before the precipitation, the reductions in the PM_2.5 concentration were 87% and 20%, respectively.
   
   
5. In Jinan, for the seven precipitation events demonstrating a reduction in the AQI, the dry deposition flux in the total PCDD/Fs-WHO₂₀₀₅-TEQ ranged between 157.8 and 1152 pg WHO₂₀₀₅-TEQ m^–2 day^–1 and averaged 572.5 pg WHO₂₀₀₅-TEQ m^–2 day^–1. Comparing the fraction after the precipitation with that before the precipitation, the reduction in the PCDD/Fs dry deposition fraction averaged 39%. In Qingdao, for the eight precipitation events demonstrating a reduction in the AQI, the dry deposition flux in the total PCDD/Fs-WHO₂₀₀₅-TEQ ranged between 145.7 and 726.5 pg WHO₂₀₀₅-TEQ m^–2 day^–1 and averaged 393.0 pg WHO₂₀₀₅-TEQ m^–2 day^–1. Comparing the values after the precipitation with those before the precipitation, the reduction in the dry deposition flux was 28%.
   
   
6. For the two precipitation events demonstration an elevation in the AQI in Jinan, the dry deposition flux in the total PCDD/Fs-WHO₂₀₀₅-TEQ ranged between 365.6 and 946.2 pg WHO₂₀₀₅-TEQ m^–2 day^–1 and averaged 560.4 pg WHO₂₀₀₅-TEQ m^–2 day^–1. Comparing the flux after the precipitation with that before the precipitation, the increase in the PCDD/Fs dry deposition flux averaged 22%. In Qingdao, in the one precipitation event demonstrating an elevation in the AQI elevation, the dry deposition flux in the total PCDD/Fs-WHO₂₀₀₅-TEQ ranged between 191.3 and 371.2 pg WHO₂₀₀₅-TEQ m^–2 day^–1 and averaged 291.1 pg WHO₂₀₀₅-TEQ m^–2 day^–1. Comparing the values after the precipitation with those before the precipitation, the increase in the PCDD/Fs dry deposition flux was 7.0%.
   
   
7. The results of this study revealed that, in general, rain and snow did improve air quality. This is due to the fact that the particulates or dissolved the gaseous pollutants were scavenged out of the air and carried the aerosols down to the ground. However, in some events, after the rainy or snowy days, an increase in the source emissions and a reduction in the atmospheric vertical convection did result in an elevation of the AQI, PM₅ concentrations, and PCDD/F dry deposition in the ambient air.
   
   
8. The results of this study provided useful information for air quality management.