Influence of meteorological conditions on PM2.5 concentrations across China: A review of methodology and mechanism.

China is suffering severe ambient air pollution in recent decades and particulate matter (PM) has become the major pollutant, especially for PM2.5 and PM10, which have highly raised scholars and policy-makers’ attention in last few years. The existing research has focused on the characteristics of PM2.5 and PM10, respectively, or analyzed the correlation between the two pollutants, while the ratio of PM2.5 to PM10 has been taken less consideration. In this study, daily mean PM2.5 and PM10 mass concentrations in 31 provincial capitals from 2014 to 2016 were used to present the temporal variations and spatial distribution of PM2.5/PM10 ratios among eight economic regions. And then, statistical method and correlation analysis were adopted to investigate the relationship between the ratios and AQI, the rate of change on the ratios, and the impact of meteorological parameters on the ratios. The results indicated that PM2.5/PM10 ratios showed an increasing trend from northwest to southeast due to different economic development and industrial types. The highest values were observed in winter among all regions, and the ratios on weekends were higher than that of on weekdays in most of the regions. Besides, domestic heating in northern China had a significant contribution to the ratios. Moreover, ratios had less changes, and the rate of change was stable in summer. As for air quality, the higher the ratio, the larger the possibility of high AQI so that the air pollution will be more severe. In terms of meteorological factors, the results demonstrated that relative humidity, precipitation, and pressure were the most important factors and had significantly positive impacts, while sunshine duration, temperature, and wind speed had negative effects on the ratios. The findings could identify the pollution sources among PM10 and be helpful for making regulation locally to reduce emission which considers anthropogenic sources and meteorological diffusion simultaneously.

https://downloads.hindawi.com/journals/amete/2019/5295726.pdf

PM2.5/PM10 Ratios in Eight Economic Regions and Their Relationship with Meteorology in China

Northeast China experiences severe atmospheric pollution, with an increasing occurrence of heavy haze episodes. However, the underlying forces driving haze formation during different seasons are poorly understood. In this study, we explored the spatio-temporal characteristics and causes of haze events in Northeast China by combining a range of data sources (i.e., ground monitoring, satellite-based products, and meteorological products). It was found that the ‘Shenyang-Changchun-Harbin (SCH)’city belt was the most polluted area in the region on an annual scale. The spatial distribution of air quality index (AQI) values had a clear seasonality, with the worst pollution occurring in winter, an approximately oval-shaped polluted area around western Jilin Province in spring, and the best air quality occurring in summer and most of the autumn. The three periods that typically experienced intense haze events were Period I from mid-October to mid-November (i.e., late autumn and early winter), Period II from late-December to February (i.e., the coldest time in winter), and Period III from April to mid-May (i.e., spring). During Period I, strong PM2.5 emissions from seasonal crop residue burning and coal burning for winter heating were the dominant reasons for the occurrence of extreme haze events (AQI > 300). Period II had frequent heavy haze events (200 < AQI < 300) in the coldest months of January and February, which were due to high PM2.5 emissions from coal burning and vehicle fuel consumption, a lower atmospheric boundary layer, and stagnant atmospheric conditions. Haze events in Period III, with high PM10 concentrations, were primarily caused by the regional transportation of windblown dust from degraded grassland in central Inner Mongolia and bare soil in western Jilin Province. Local agricultural tilling could also release PM10 and enhance the levels of windblown dust from tilled soil. Better control of coal burning, fuel consumption, and crop residue burning in winter and autumn is urgently needed to address the haze problem in Northeast China.

Regional Characteristics and Causes of Haze Events in Northeast China

PM2.5 samples were collected in Beijing between February 24 and March 12 of 2014, and analyzed to examine chemical compositions and origins of the PM2.5 at pollution levels of clean (PM2.5 250 µg m–3). The mean PM2.5 concentration was 137.7 ± 124.8 µg m–3 during the observation period, accounting for 66% of PM10. As all aerosol species concentrations increased with the pollution level, the contributions of secondary inorganic aerosols (SIA) to PM2.5 continuously increased while the contributions of OC and EC decreased, indicating a substantial contribution from secondary formation to the elevation of PM2.5 pollution. The acidity of PM2.5, the ratio of anion microequivalent concentration to cation, increased from 0.96 to 1.08 as pollution levels increased. Using a PMF model, secondary inorganic aerosols, industrial emissions, soil dust, traffic emissions, and coal combustion and biomass burning were identified as contributors to the PM2.5, and on average accounted 46%, 20%, 10%, 6% and 18% of the PM2.5, respectively, in the observation period. Industrial emissions were the dominant PM2.5 source during the clean period (60%). Except for traffic emission, sources of PM2.5 at the light-medium level were consistent, accounting for 17%–29%. Secondary inorganic aerosols were the largest origin of PM2.5 at heavy and severe pollution levels, accounting for 40% and 78%, respectively. In addition, the 48 h transport distances of air masses decreased from 2000 km (clean) to 300 km (severe level) and the proportion of air masses from south pollution areas in the total air masses at each pollution level increased from 0% to 97%, indicating that the stability of near surface air and the northerly transport of pollutants from the south at local and regional scales played a the key role in the PM2.5 elevation.

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Variations of Chemical Composition and Source Apportionment of PM2.5 during Winter Haze Episodes in Beijing

Based on data from ground-based air quality stations, space–time variations of six principal atmospheric pollutants, such as particulate matter (PM2.5 and PM10) and gas pollutants (SO2, NO2, СО, and O3), obtained from January 1, 2014 to December 31, 2017 in the city of Lanzhou, have been studied. Average total concentrations of PM2.5 and PM10 were 53.2 ± 26.91 and 124.54 ± 82.33 µg/m3, respectively; however, the results showed that in 75.53% and 84.85% days, concentrations of these pollutants exceeded Chinese National Ambient Air Quality Standard and in 100% days exceeded World Health Organization guidelines standards. Daily mean values of aerosol optical depth and Angstrom exponent based on data, received by satellite Moderate Resolution Imaging Spectroradiometer, show a broad range of values for aerosol optical depth (from 0.018 to 1.954) and Angstrom exponent (from 0.003 to 1.8). Results of principal components analysis revealed three factor loadings. Thus, Factor 1 has the relevant loadings for PM2.5, PM10, CO, SO2, and NO2 (36%) and closely associated with transport emissions and industrial sources, which contribute to air pollution in Lanzhou. Factor 2 was heavily loaded with temperature and visibility (16.94%). Factor 3 consisted of relative humidity (14.11%). Cluster analysis revealed four subgroups: cluster 1 (PM2.5, NO2, SO2), cluster 2 (CO), cluster 3 (PM10) and cluster 4 (relative humidity, visibility, temperature, O3, wind speed), which were compliant with results, obtained from principal components analysis. Positive correlation was found among all pollutants, other than O3. According to processed backward trajectories obtained by Hybrid Single-Particle Lagrangian Integrated Trajectory model, it was found that movement of air masses occur from north, northwest, and west directions—the location of principal natural sources of aerosols.

The characteristics of air pollutants during different seasons in the urban area of Lanzhou, Northwest China

To study the pollution characteristics of PM_(2.5) during the haze period in October 2014, the hourly automatic monitoring data and 22-h atmospheric PM_(2.5) samples were collected in Changchun city. According to the statistical results of the hourly average PM_(2.5) concentration, heavy pollution occurred from October 13 to November 1 in 2014 in Changchun city. The daily concentration of PM_(2.5) during this period was 53.18 μg m^(-3) to 450.69 μg m^(-3). In addition, the PM_(2.5) concentration was higher at night and lower during the daytime on haze days, which is affected by pollutant emission and meteorological conditions. The Pearson correlation coefficient between PM_(2.5) and CO was high (r = 0.745), which implies that the concentration suddenly increased, probably because of the combustion of fossil fuels and other organic matter. The meteorological condition investigation shows that the wind speed, temperature and pressure are low and that the RH value is relatively high on haze days. In addition, stable weather during haze days makes the pollution heavier. The analysis of water-soluble inorganic ions (WSIIs) suggests that WSIIs constituted up to 21-56% of PM_(2.5), and the total ions, anions and cations showed a significant correlation. During the haze days, the NO_3^-/SO_4^(2-) ratio was substantial (3.7-4.6), except at the CP and JZP stations, which suggests that the pollutants in the atmosphere are from a mixture of stationary emission and mobile emission. The NOR and SOR values were more than 0.1 at most sampling stations, so serious secondary pollution occurs in the atmosphere on haze days, and secondary ion formation is enhanced by the atmospheric conditions and emissions of gaseous SO_2 and NO_2.

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Pollution Characteristics of PM2.5 Aerosol during Haze Periods in Changchun, China

To study the air quality changes during the Corona Virus Disease 2019 (COVID-19) lockdown in Changchun, we analyzed the changes in pollution of six major pollutants (PM2.5, PM10, SO2, NO2, O3, CO) and correlated them with meteorological parameters, using meteorological data and pollutants concentration data. Regional transport pathways and potential source areas of pollutants were analyzed using the Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model and Potential Source Contribution Function (PSCF). The results showed that the concentrations of PM2.5, PM10, SO2, NO2, CO were 30.5%–53.8% lower in the Level I period and 49.4%–65.0% lower in the Level II period than in the pre-lockdown period, respectively. Conversely, O3 increased 59.6% and 58.1% during Level I and Level II, respectively, compared to the pre-lockdown period. During the 55-day lockdown, daily average concentrations of each pollutant were lower than in previous years on 36-55 days, while O3 was higher on 35 days. The pollutants that decreased in concentration during the lockdown also showed an increase during the Level III period (up to 188.5%). The maximum daily growth rate of PM2.5 during the lockdown period in 2020 was 16.0%, which was higher than this value in the same period of previous years (21.8%, 21.4%, 17.4%). This shows that the change trend of pollutants during the lockdown period is smoother than in previous years. Temperature and O3 were positively correlated before the lockdown and during Level I and weakly negatively correlated during Level II and Level III. Despite the prevalence of northwest winds in winter, a high percentage of trajectories from other directions (up to 36.8%) was observed during the lockdown. Simultaneously, the lockdown reduced the potential source area for PM2.5 (WPSCF ≥ 0.000007), but rebounded after the lockdown was lifted. In conclusion, the lockdown only temporarily reduced the air pollution in Changchun. © 2021, AAGR Aerosol and Air Quality Research. All rights reserved.

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Analysis of air quality changes and influencing factors in changchun during the covid-19 pandemic in 2020

In recent years, with the continuous advancement of China’s urbanization process, regional atmospheric environmental problems have become increasingly prominent. We selected 12 cities as study areas to explore the spatial and temporal distribution characteristics of atmospheric particulate matter in the region, and analyzed the impact of socioeconomic and natural factors on local particulate matter levels. In terms of time variation, the particulate matter in the study area showed an annual change trend of first rising and then falling, a monthly change trend of “U” shape, and an hourly change trend of double-peak and double-valley distribution. Spatially, the concentration of particulate matter in the central and southern cities of the study area is higher, while the pollution in the western region is lighter. In terms of social economy, PM2.5 showed an “inverted U-shaped” quadratic polynomial relationship with Second Industry and Population Density, while it showed a U-shaped relationship with Generating Capacity and Coal Output. The results of correlation analysis showed that PM2.5 and PM10 were significantly positively correlated with NO2, SO2, CO and air pressure, and significantly negatively correlated with O3 and air temperature. Wind speed was significantly negatively correlated with PM2.5, and significantly positively correlated with PM10. In terms of pollution transmission, the southwest area of Taiyuan City is a high potential pollution source area of fine particles, and the long-distance transport of PM2.5 in Xinjiang from the northwest also has a certain contribution to the pollution of fine particles. This study is helpful for us to understand the characteristics and influencing factors of particulate matter pollution in coal production cities.

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Study on the Spatial and Temporal Distribution Characteristics and Influencing Factors of Particulate Matter Pollution in Coal Production Cities in China

The central Liaoning urban agglomeration is an important heavy industry development base in China, and also an important part of the economy in northeast China. The atmospheric environmental problems caused by the development of heavy industry are particularly prominent. Trajectory clustering, potential source contribution (PSCF), and concentration weighted trajectory (CWT) analysis are used to discuss the temporal and spatial pollution characteristics of PM2.5 and ozone concentrations and reveal the regional atmospheric transmission pattern in central Liaoning urban agglomeration from 2015 to 2020. The results show that: (1) PM2.5 in the central Liaoning urban agglomeration showed a decreasing trend from 2015 to 2020. The concentration of PM2.5 is the lowest in 2018. Except for Benxi (34.7 µg/m3), the concentrations of PM2.5 in other cities do not meet the standard in 2020. The ozone concentration in Anshan, Liaoyang, and Shenyang reached the peaks in 2017, which are 68.76 µg/m3, 66.27 µg/m3, and 63.46 µg/m3 respectively. PM2.5 pollution is the highest in winter and the lowest in summer. The daily variation distribution of PM2.5 concentration showed a bimodal pattern. Ozone pollution is the most serious in summer, with the concentration of ozone reaching 131.14 µg/m3 in Shenyang. Fushun is affected by Shenyang intercity pollution, and the ozone concentration is high. (2) In terms of spatial distribution, the high values of PM2.5 are concentrated in monitoring stations in urban areas. On the contrary, the concentration of ozone in suburban stations is higher. The high concentration of ozone in the northeast of Anshan, Liaoyang, Shenyang to Tieling, and Fushun extended in a band distribution. (3) Through cluster analysis, it is found that PM2.5 and ozone in Shenyang are mainly affected by short-distance transport airflow. In winter, the weighted PSCF high-value area of PM2.5 presents as a potential contribution source zone of the northeast trend with wide coverage, in which the contribution value of the weighted CWT in the middle of Heilongjiang is the highest. The main potential source areas of ozone mass concentration in spring and summer are coastal cities and the Bohai Sea and the Yellow Sea. We conclude that the regional transmission of pollutants is an important factor of pollution, so we should pay attention to the supply of industrial sources and marine sources of marine pollution in the surrounding areas of cities, and strengthen the joint prevention and control of air pollution among regions. The research results of this article provide a useful reference for the central Liaoning urban agglomeration to improve air quality.

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Temporal and Spatial Analysis of PM2.5 and O3 Pollution Characteristics and Transmission in Central Liaoning Urban Agglomeration from 2015 to 2020

Pollution caused by PM2.5 and O3 are common environmental problems which can easily affect human health. Chengdu is a major central city in Western China, and there is little research on the regional emissions and health effects of air pollution in Chengdu. According to the Multi-resolution Emissions Inventory of the Chinese Model, 2017 (MEIC v1.3), this study compiled the air pollutant emission inventory of Chengdu. The results show that the pollutant emission of Chengdu is generally higher in winter than in summer. The southeast area of Chengdu is the key area where emissions of residential and industrial sectors are dominant. Through air quality simulation with a Weather Research and Forecasting model, coupled with the Community Multiscale Air Quality (WRF-CMAQ), the health effects of PM2.5 and O3 in winter and summer in Chengdu of 2017 were investigated. The primary pollutant in winter is PM2.5 and O3 in summer. PM2.5 pollution accounted for 351 deaths in January and July 2017, and O3 pollution accounted for 328 deaths in the same period. There were 276 deaths in rural areas and 413 in urban areas. In January and July 2017, the health economic loss caused by PM2.5 accounted for 0.0974% of the gross regional product (GDP) of Chengdu in 2017, and the health economic loss caused by O3 accounted for 0.0910%.

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Ju Wang

Papers

Pollution Characteristics of PM2.5 Aerosol during Haze Periods in Changchun, China

Analysis of air quality changes and influencing factors in changchun during the covid-19 pandemic in 2020

Study on the Spatial and Temporal Distribution Characteristics and Influencing Factors of Particulate Matter Pollution in Coal Production Cities in China

Temporal and Spatial Analysis of PM2.5 and O3 Pollution Characteristics and Transmission in Central Liaoning Urban Agglomeration from 2015 to 2020

Characteristics of Air Pollutants Emission and Its Impacts on Public Health of Chengdu, Western China