scholarly journals Particulate Matter emission sources and meteorological parameters combine to shape the airborne microbiome communities in the Ligurian coast, Italy

2020 ◽  
Author(s):  
Giorgia Palladino ◽  
Pietro Morozzi ◽  
Elena Biagi ◽  
Erika Brattich ◽  
Silvia Turroni ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Meteorological Parameters ◽  
Observation Time ◽  
Meteorological Conditions ◽  
Emission Sources ◽  
Relevant Factor ◽  
Industrial Emissions ◽  
Particulate Matter Emission ◽  
Compositional Structure ◽  
Ligurian Coast

AbstractHere we explore how the chemical composition of particulate matter (PM) and meteorological conditions combine in shaping the air microbiome in a heavily inhabited industrial urban settlement. During the observation time, the air microbiome was highly dynamic, fluctuating between different compositional states, likely resulting from the aerosolization of different microbiomes emission sources. This dynamic process depends on the combination of local meteorological parameters and particle emission sources, which may affect the prevalent aerosolized microbiomes. In particular, we showed that, in the investigated area, industrial emissions and winds blowing from the inlands combine with an airborne microbiome that includes faecal microbiomes components, suggesting multiple citizens’ exposure to both chemicals and microorganisms of faecal origin, as related to landscape exploitation and population density. In conclusion, our findings support the need to include monitoring of the air microbiome compositional structure as a relevant factor for the final assessment of local air quality.

scholarly journals Particulate matter emission sources and meteorological parameters combine to shape the airborne bacteria communities in the Ligurian coast, Italy

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Giorgia Palladino ◽  
Pietro Morozzi ◽  
Elena Biagi ◽  
Erika Brattich ◽  
Silvia Turroni ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Meteorological Parameters ◽  
Holistic Approach ◽  
Medium Size ◽  
Emission Sources ◽  
Industrial Emissions ◽  
Particulate Matter Emission ◽  
Compositional Structure ◽  
Wide Range ◽  
Ligurian Coast

AbstractAim of the present study is to explore how the chemical composition of particulate matter (PM) and meteorological conditions combine in shaping the air microbiome in Savona (Italy), a medium-size, heavily inhabited urban settlement, hosting a wide range of industrial activities. In particular, the air microbiome and PM10 were monitored over six months in 2012. During that time, the air microbiome was highly dynamic, fluctuating between different compositional states, likely resulting from the aerosolization of different microbiomes emission sources. According to our findings, this dynamic process depends on the combination of local meteorological parameters and particle emission sources, which may affect the prevalent aerosolized microbiomes, thus representing further fundamental tools for source apportionment in a holistic approach encompassing chemical as well as microbiological pollution. In particular, we showed that, in the investigated area, industrial emissions and winds blowing from the inlands combine with an airborne microbiome which include faecal microbiomes components, suggesting multiple citizens’ exposure to both chemicals and microorganisms of faecal origin, as related to landscape exploitation and population density. In conclusion, our findings support the need to include monitoring of the air microbiome compositional structure as a relevant factor for the final assessment of local air quality.

scholarly journals Spatial analysis of air masses backward trajectories in order to identify distant sources of fine particulate matter emission / Analiza przestrzenna wstecznych trajektorii mas powietrza w celu rozpoznania odległych źródeł emisji pyłu drobnego

2015 ◽  
Vol 41 (2) ◽  
pp. 28-35 ◽  
Author(s):  
Jolanta Godłowska ◽  
Monika J. Hajto ◽  
A. Monika Tomaszewska
Keyword(s):  
Particulate Matter ◽  
Spatial Analysis ◽  
Fine Particulate Matter ◽  
Emission Sources ◽  
Air Masses ◽  
Backward Trajectories ◽  
Particulate Matter Emission ◽  
Aggregate Information ◽  
Fine Particulate ◽  
The Impact

Abstract The paper presents a method of identifying distant emission sources of fine particulate matter PM2.5 affecting significantly PM2.5 concentrations at a given location. The method involves spatial analysis of aggregate information about PM2.5 concentrations measured at the location and air masses backward trajectories calculated by HYSPLIT model. The method was examined for three locations of PM2.5 measurement stations (Diabla Góra, Gdańsk, and Katowice) which represented different environmental conditions. The backward trajectories were calculated starting from different heights (30, 50, 100 and 150 m a. g. l.). All points of a single backward trajectory were assigned to the PM2.5 concentration corresponding to the date and the site of the beginning of trajectory calculation. Daily average concentrations of PM2.5 were used, and in the case of Gdańsk also hourly ones. It enabled to assess the effectiveness of the presented method using daily averages if hourly ones were not available. Locations of distant sources of fine particulate matter emission were determined by assigning to each grid node a mean value of PM2.5 concentrations associated with the trajectories points located within the so-called search ellipse. Nearby sources of fine particulate matter emission were eliminated by filtering the trajectories points located close to each other (so-called duplicates). The analyses covered the period of January-March 2010. The results indicated the different origin of air masses in the northern and southern Poland. In Diabla Góra and Gdańsk the distant sources of fine particulate matter emission are identified in Belarus and Russia. In Katowice the impact of the Belarusian PM2.5 emission sources was also noted but as the most important fine particulate matter emission sources were considered those located in the area of Romania, Hungary, Slovakia and Ukraine.

scholarly journals Sensitivity analysis of the surface ozone and fine particulate matter to meteorological parameters in China

2020 ◽  
Vol 20 (21) ◽  
pp. 13455-13466
Author(s):  
Zhihao Shi ◽  
Lin Huang ◽  
Jingyi Li ◽  
Qi Ying ◽  
Hongliang Zhang ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Air Quality ◽  
Meteorological Parameters ◽  
Surface Ozone ◽  
Fine Particulate Matter ◽  
Great Influence ◽  
Meteorological Conditions ◽  
Daily Maximum ◽  
Fine Particulate ◽  
Surface O3

Abstract. Meteorological conditions play important roles in the formation of ozone (O3) and fine particulate matter (PM2.5). China has been suffering from serious regional air pollution problems, characterized by high concentrations of surface O3 and PM2.5. In this study, the Community Multiscale Air Quality (CMAQ) model was used to quantify the sensitivity of surface O3 and PM2.5 to key meteorological parameters in different regions of China. Six meteorological parameters were perturbed to create different meteorological conditions, including temperature (T), wind speed (WS), absolute humidity (AH), planetary boundary layer height (PBLH), cloud liquid water content (CLW) and precipitation (PCP). Air quality simulations under the perturbed meteorological conditions were conducted in China in January and July of 2013. The changes in O3 and PM2.5 concentrations due to individual meteorological parameters were then quantified. T has a great influence on the daily maximum 8 h average O3 (O3-8 h) concentrations, which leads to O3-8 h increases by 1.7 in January in Chongqing and 1.1 ppb K−1 in July in Beijing. WS, AH, and PBLH have a smaller but notable influence on O3-8 h with maximum change rates of 0.3 ppb %−1, −0.15 ppb %−1, and 0.14 ppb %−1, respectively. T, WS, AH, and PBLH have important effects on PM2.5 formation of both in January and July. In general, PM2.5 sensitivities are negative to T, WS, and PBLH and positive to AH in most regions of China. The sensitivities in January are much larger than in July. PM2.5 sensitivity to T, WS, PBLH, and AH in January can be up to −5 µg m−3 K−1, −3 µg m−3 %−1, −1 µg m−3 %−1, and +0.6 µg m−3 %−1, respectively, and in July it can be up to −2 µg m−3 K−1, −0.4 µg m−3 %−1, −0.14 µg m−3 %−1, and +0.3 µg m−3 %−1, respectively. Other meteorological factors (CLW and PCP) have negligible effects on O3-8 h (less than 0.01 ppb %−1) and PM2.5 (less than 0.01 µg m−3 %−1). The results suggest that surface O3 and PM2.5 concentrations can change significantly due to changes in meteorological parameters, and it is necessary to consider these effects when developing emission control strategies in different regions of China.

scholarly journals Sources and atmospheric processing of winter aerosols in Seoul, Korea: insights from real-time measurements using a high-resolution aerosol mass spectrometer

2017 ◽  
Vol 17 (3) ◽  
pp. 2009-2033 ◽  
Author(s):  
Hwajin Kim ◽  
Qi Zhang ◽  
Gwi-Nam Bae ◽  
Jin Young Kim ◽  
Seung Bok Lee
Keyword(s):  
Particulate Matter ◽  
High Resolution ◽  
Real Time ◽  
Mass Spectrometer ◽  
Meteorological Conditions ◽  
Emission Sources ◽  
Aerosol Mass Spectrometer ◽  
Secondary Aerosol ◽  
Atmospheric Processes ◽  
Aerosol Mass

Abstract. Highly time-resolved chemical characterization of nonrefractory submicrometer particulate matter (NR-PM1) was conducted in Seoul, the capital and largest metropolis of Korea, using an Aerodyne high-resolution time-of-flight aerosol mass spectrometer (HR-ToF-AMS). The measurements were performed during winter, when elevated particulate matter (PM) pollution events are often observed. This is the first time that detailed real-time aerosol measurement results have been reported from Seoul, Korea, and they reveal valuable insights into the sources and atmospheric processes that contribute to PM pollution in this region. The average concentration of submicron aerosol (PM1 =  NR-PM1+ black carbon (BC)) was 27.5 µg m−3, and the total mass was dominated by organics (44 %), followed by nitrate (24 %) and sulfate (10 %). The average atomic ratios of oxygen to carbon (O / C), hydrogen to carbon (H / C), and nitrogen to carbon (N / C) of organic aerosols (OA) were 0.37, 1.79, and 0.018, respectively, which result in an average organic mass-to-carbon (OM / OC) ratio of 1.67. The concentrations (2.6–90.7 µg m−3) and composition of PM1 varied dynamically during the measurement period due to the influences of different meteorological conditions, emission sources, and air mass origins. Five distinct sources of OA were identified via positive matrix factorization (PMF) analysis of the HR-ToF-AMS data: vehicle emissions represented by a hydrocarbon-like OA factor (HOA, O / C  =  0.06), cooking activities represented by a cooking OA factor (COA, O / C  =  0.14), wood combustion represented by a biomass burning OA factor (BBOA, O / C  =  0.34), and secondary organic aerosol (SOA) represented by a semivolatile oxygenated OA factor (SV-OOA, O / C  = 0.56) and a low-volatility oxygenated OA factor (LV-OOA, O / C  =  0.68). On average, primary OA (POA = HOA + COA + BBOA) accounted for 59 % the OA mass, whereas SV-OOA and LV-OOA contributed 15 and 26 %, respectively. Our results indicate that air quality in Seoul during winter is influenced strongly by secondary aerosol formation, with sulfate, nitrate, ammonium, SV-OOA, and LV-OOA together accounting for 64 % of the PM1 mass during this study. However, aerosol sources and composition were found to be significantly different between clean and polluted periods. During stagnant periods with low wind speed (WS) and high relative humidity (RH), PM concentration was generally high (average ±1σ = 43.6 ± 12.4 µg m−3) with enhanced fractions of nitrate (27 %) and SV-OOA (8 %), which suggested a strong influence from local production of secondary aerosol. Low-PM loading periods (12.6 ± 7.1 µg m−3) tended to occur under higher-WS and lower-RH conditions and appeared to be more strongly influenced by regional air masses, as indicated by higher mass fractions of sulfate (12 %) and LV-OOA (20 %) in PM1. Overall, our results indicate that PM pollutants in urban Korea originate from complex emission sources and atmospheric processes and that their concentrations and composition are controlled by various factors, including meteorological conditions, local anthropogenic emissions, and upwind sources.

scholarly journals Sources and atmospheric processing of wintertime aerosols in Seoul, Korea: Insights from real-time measurements using a high-resolution aerosol mass spectrometer

2016 ◽  
Author(s):  
Hwajin Kim ◽  
Qi Zhang ◽  
Gwi-Nam Bae ◽  
Jin Young Kim ◽  
Seung Bok Lee
Keyword(s):  
Particulate Matter ◽  
High Resolution ◽  
Real Time ◽  
Mass Spectrometer ◽  
Organic Aerosol ◽  
Meteorological Conditions ◽  
Emission Sources ◽  
Aerosol Mass Spectrometer ◽  
Atmospheric Processes ◽  
Aerosol Mass

Abstract. Highly time-resolved chemical characterization of non-refractory submicrometer particulate matter (NR-PM1) was conducted in Seoul, the capital and largest metropolis of Korea, using an Aerodyne high-resolution time-of-flight aerosol mass spectrometer (HR-ToF-AMS). The measurements were performed during winter, when elevated particulate matter (PM) pollution events are often observed. This is the first time that detailed real-time aerosol measurement results are reported from Seoul, Korea, which reveal valuable insights into the sources and atmospheric processes that contribute to PM pollution in this region. The average concentration of submicron aerosol (PM1 = NR - PM1 + black carbon (BC)) was 27.5 µg m−3, and the total mass was dominated by organics (44 %), followed by nitrate (24 %) and sulfate (10 %). The average atomic ratios of oxygen-to-carbon (O / C), hydrogen-to-carbon (H / C), and nitrogen-to-carbon (N / C) of organic aerosol (OA) were 0.37, 1.79, and 0.022, respectively, which gives that average organic mass-to-carbon (OM / OC) ratio of 1.67. The concentrations (2.6–90.7 µg m−3) and composition of PM1 varied dynamically during the measurement period, due to the influences of different meteorological conditions, emission sources, and air mass origins. Five distinct sources of OA were identified via positive matrix factorization (PMF) analysis of the HR-ToF-AMS data: vehicle emissions represented by a hydrocarbon like OA factor (HOA; O / C = 0.06), cooking activities represented by a cooking OA factor (COA; O / C = 0.15), wood combustion represented by a biomass burning OA factor (BBOA; O / C = 0.34), and secondary organic aerosol (SOA) represented by a semi-volatile oxygenated OA factor (SV-OOA; O / C = 0.56) and a low volatility oxygenated OA factor (LV-OOA; O / C = 0.68). On average, primary OA (POA = HOA + COA + BBOA) accounted for 59 % the OA mass whereas SV-OOA and LV-OOA contributed 15 % and 26 %, respectively. Our results indicate that air quality in Seoul during winter is influenced strongly by secondary aerosol formation with sulfate, nitrate, ammonium, SV-OOA, and LV-OOA together accounting for 64 % of the PM1 mass during this study. However, aerosol sources and composition were found to be significantly different between clean and polluted periods. During stagnant periods with low wind speed (WS) and high relative humidity (RH), PM concentration was generally high (average ± 1σ = 43.6 ± 12.4 µg m−3) with enhanced fractions of nitrate (27 %) and SV-OOA (8 %), which suggested a strong influence from local production of secondary aerosol. Low PM loading periods (12.6 ± 7.1 µg m−3) tended to occurred under higher WS and lower RH conditions and appeared to be more strongly influenced by regional air masses, as indicated by higher mass fractions of sulfate (12 %) and LV-OOA (21 %) in PM1. Overall, our results indicate that PM pollutants in urban Korea originate from complex emission sources and atmospheric processes and that their concentrations and composition are controlled by various factors including meteorological conditions, local anthropogenic emissions, and upwind sources.

scholarly journals Disparities in Distribution of Particulate Matter Emission Sources by Race and Poverty Status

2018 ◽  
Vol 108 (4) ◽  
pp. 480-485 ◽  
Author(s):  
Ihab Mikati ◽  
Adam F. Benson ◽  
Thomas J. Luben ◽  
Jason D. Sacks ◽  
Jennifer Richmond-Bryant
Keyword(s):  
Particulate Matter ◽  
Emission Sources ◽  
Particulate Matter Emission ◽  
Poverty Status

scholarly journals Effectiveness evaluation of temporary emission control action in 2016 in winter in Shijiazhuang, China

2018 ◽  
Vol 18 (10) ◽  
pp. 7019-7039 ◽  
Author(s):  
Baoshuang Liu ◽  
Yuan Cheng ◽  
Ming Zhou ◽  
Danni Liang ◽  
Qili Dai ◽  
...  
Keyword(s):  
Atmospheric Pollution ◽  
Coal Combustion ◽  
Meteorological Conditions ◽  
Control Measures ◽  
Atmospheric Pollutants ◽  
Control Action ◽  
Emission Sources ◽  
Heating Period ◽  
Industrial Emissions ◽  
Potential Source

Abstract. To evaluate the environmental effectiveness of the control measures for atmospheric pollution in Shijiazhuang, China, a large-scale controlling experiment for emission sources of atmospheric pollutants (i.e. a temporary emission control action, TECA) was designed and implemented during 1 November 2016 to 9 January 2017. Compared to the no-control action and heating period (NCAHP), under unfavourable meteorological conditions, the mean concentrations of PM2.5, PM10, SO2, NO2, and chemical species (Si, Al, Ca2+, Mg2+) in PM2.5 during the control action and heating period (CAHP) still decreased by 8, 8, 5, 19, 30.3, 4.5, 47.0, and 45.2 %, respectively, indicating that the control measures for atmospheric pollution were effective. The effects of control measures in suburbs were better than those in urban area, especially for the control effects of particulate matter sources. The control effects for emission sources of carbon monoxide (CO) were not apparent during the TECA period, especially in suburbs, likely due to the increasing usage of domestic coal in suburbs along with the temperature decreasing.The results of positive matrix factorization (PMF) analysis showed that crustal dust, secondary sources, vehicle emissions, coal combustion and industrial emissions were main PM2.5 sources. Compared to the whole year (WY) and the no-control action and no-heating period (NCANHP), the contribution concentrations and proportions of coal combustion to PM2.5 increased significantly during other stages of the TECA period. The contribution concentrations and proportions of crustal dust and vehicle emissions to PM2.5 decreased noticeably during the CAHP compared to other stages of the TECA period. The contribution concentrations and proportions of industrial emissions to PM2.5 during the CAHP decreased noticeably compared to the NCAHP. The pollutants' emission sources during the CAHP were in effective control, especially for crustal dust and vehicles. However, the necessary coal heating for the cold winter and the unfavourable meteorological conditions had an offset effect on the control measures for emission sources to some degree. The results also illustrated that the discharge of pollutants might still be enormous even under such strict control measures.The backward trajectory and potential source contribution function (PSCF) analysis in the light of atmospheric pollutants suggested that the potential source areas mainly involved the surrounding regions of Shijiazhuang, i.e. south of Hebei and north of Henan and Shanxi. The regional nature of the atmospheric pollution in the North China Plain revealed that there is an urgent need for making cross-boundary control policies in addition to local control measures given the high background level of pollutants.The TECA is an important practical exercise but it cannot be advocated for as the normalized control measures for atmospheric pollution in China. The direct cause of atmospheric pollution in China is the emission of pollutants exceeding the air environment's self-purification capacity, which is caused by an unreasonable and unhealthy pattern for economic development in China.

scholarly journals NO2 Seasonal and Interannual Variability in Ukrainian Industrial Cities

2018 ◽  
Vol 64 (4) ◽  
pp. 28-35 ◽  
Author(s):  
Mykhailo Savenets ◽  
Liydmyla Nadtochii ◽  
Iryna Dyoretska
Keyword(s):  
Interannual Variability ◽  
Seasonal Variability ◽  
Meteorological Conditions ◽  
Anthropogenic Emissions ◽  
Emission Sources ◽  
Industrial Emissions ◽  
Natural Conditions ◽  
Seasonal And Interannual Variability ◽  
Tidal Forces ◽  
Industrial Cities

Abstract The paper aims to define the main features and principles of seasonal and interannual NO2 variations in Ukrainian industrial cities. Using ground-based measurements for 15-year period, it shows weak NO2 seasonal variability that could intensify in case of three regularities. These regularities depend on impact of natural conditions during anthropogenic emissions growth and redistribution between emission sources. Most industrial cities are characterized by positive trends even if stationary industrial emissions fall. NO2 interannual changes forms under variety of fluctuations. However, 6.2- and 9.3-year periods have the biggest impact and might be explained by low-frequent lunar tidal forces through its influence on meteorological conditions.

scholarly journals Composition and sources of particulate matter in an industrialised Alpine valley

2010 ◽  
Vol 10 (4) ◽  
pp. 9391-9430 ◽  
Author(s):  
N. Perron ◽  
J. Sandradewi ◽  
M. R. Alfarra ◽  
P. Lienemann ◽  
R. Gehrig ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Meteorological Conditions ◽  
Industrial Emissions ◽  
Alpine Valley ◽  
Aerosol Mass ◽  
Wood Burning ◽  
Heavy Duty Vehicle ◽  
Highly Correlated ◽  
A Site ◽  
Rhone Valley

Abstract. A three-week long field campaign was carried out under autumnal meteorological conditions at four valley floor sites in the industrialised Swiss Rhone Valley. For one week of stable meteorological conditions, particulate matter with an aerodynamic diameter below 10 μm (PM10) was analysed from daily filters using ion chromatography, X-ray fluorescence, anhydrosugars and radiocarbon analysis of the organic and elemental matter (OM and EM, respectively). Furthermore, PM1 composition along the whole campaign was monitored in Massongex (a site near industries) by a seven-wavelength aethalometer and a quadrupole aerosol mass spectrometer (Q-AMS). At all sites, PM10 secondary inorganics and non-fossil EM and OM exhibited relatively stable concentrations over the selected days. On the contrary, PM10 fossil carbonaceous fractions, mineral dust components and several trace elements showed a significant decrease on Sunday, compared to the analysed working days. Their concentrations were also highly correlated. This evidenced the role of exhaust and resuspension emissions by heavy-duty vehicle traffic to the PM10 concentrations along the valley. In Massongex, organic matter and black carbon (BC) were the main contributors to PM1 over the campaign (accounting for 45% and 18% of PM1, respectively). An optical discrimination of BC highlighted the prevalence of fossil over wood-burning sources. Three types of PM1 organics could be identified by factor analysis: primary wood-burning organic aerosol (P-WBOA) dominated the PM1 carbonaceous fraction, followed by oxygenated organics (OOA) mostly representing secondary organics, and by traffic or possibly industry-related hydrocarbon-like organics (HOA) as the smallest carbonaceous contribution. Furthermore, unusually high contributions of fine chloride were detected at all sites. They were attributed to ammonium chloride (NH4Cl) in Massongex and represented the only significant component exclusively attributable to industrial emissions.

scholarly journals Sensitivity Analysis of the Surface Ozone and Fine Particulate Matter to Meteorological Parameters in China

2020 ◽  
Author(s):  
Zhihao Shi ◽  
Lin Huang ◽  
Jingyi Li ◽  
Qi Ying ◽  
Hongliang Zhang ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Air Quality ◽  
Meteorological Parameters ◽  
Surface Ozone ◽  
Fine Particulate Matter ◽  
Absolute Humidity ◽  
Meteorological Conditions ◽  
Daily Maximum ◽  
Fine Particulate ◽  
Surface O3

Abstract. Meteorological conditions play important roles in the formation of ozone (O3) and fine particulate matter (PM2.5). China has been suffering from serious regional air pollution problems, characterized by high concentrations of surface O3 and PM2.5. In this study, the Community Multiscale Air Quality (CMAQ) model was used to quantify the sensitivity of surface O3 and PM2.5 to key meteorological parameters in different regions of China. Six meteorological parameters were perturbed to create different meteorological conditions, including temperature (T), wind speed (WS), absolute humidity (AH), planetary boundary layer height (PBLH), cloud liquid water content (CLW) and precipitation (PCP). Air quality simulations under the perturbed meteorological conditions were conducted in China in January and July of 2013. The changes in O3 and PM2.5 concentrations due to individual meteorological parameters were then quantified. T has the greatest impact on the daily maximum 8-h average O3 (O3-8 h) concentrations, which leads to O3-8 h increases by 1.7 ppb K−1 in January in Chongqing and 1.1 ppb K−1 in July in Beijing. WS, AH, and PBLH have a smaller but notable influence on O3-8 h with maximum change rates of 0.3, −0.15, and 0.14 ppb %−1, respectively. T, WS, AH, and PBLH have important effects on PM2.5 formation of in both January and July. In general, PM2.5 sensitivities are negative to T, WS, and PBLH and positive to AH in most regions of China. The sensitivities in January are much larger than in July. PM2.5 sensitivity to T, WS, PBLH, and AH in January can be up to −5 μg m−3 K−1, −3 μg m3 %−1, −1 g m−3, and +0.6 μg m−3 %−1, respectively, and in July can be up to −2 μg m−3 K−1, −0.4 μg m−3 %−1, −0.14 μg m−3 %−1, and +0.3 μg m−3 %−1, respectively. Other meteorological factors (CLW and PCP) have negligible effects on O3-8 h (less than 0.01 ppb %−1) and PM2.5 (less than 0.01 μg m−3 %−1). The results suggest that surface O3 and PM2.5 concentrations can change significantly due to changes in meteorological parameters and it is necessary to consider these effects when developing emission control strategies in different regions of China.

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