scholarly journals The Temporal And Spatial Changes Of Beijing’s Pm 2.5 Concentration And Its Relationship With Meteorological Factors From 2015 To 2020

2021 ◽  
Vol 14 (3) ◽  
pp. 73-81
Author(s):  
Guo Peng ◽  
A. B. Umarova ◽  
G. S. Bykova
Keyword(s):  
Particulate Matter ◽  
Air Quality ◽  
Urban Areas ◽  
Meteorological Factors ◽  
Ambient Air ◽  
Average Concentration ◽  
Annual Average ◽  
Daily Average ◽  
Annual Average Concentration ◽  
Temporal And Spatial

Currently, Beijing is facing increasing serious air quality problems. Atmospheric pollutants in Beijing are mainly composed of particulate matter, which is a key factor leading to adverse effects on human health. This paper uses hourly data from 36 environmental monitoring stations in Beijing from 2015 to 2020 to obtain the temporal and spatial distribution of the mass concentration of particulate matter with a diameter smaller than 2.5 μm (PM2.5). The 36 stations established by the Ministry of Ecology and Environment and the Beijing Environmental Protection Monitoring Center and obtain continuous real-time monitoring of particulate matter. And the 36 stations are divided into 13 main urban environmental assessment points, 11 suburban assessment points, 1 control point, 6 district assessment points, and 5 traffic pollution monitoring points. The annual average concentration of PM2.5 in Beijing was 60 μg/m3 with a negative trend of approximately 14% year-1. In urban areas the annual average concentration of PM2.5 was 59 μg/m3, in suburbs 56 μg/m3, in traffic areas 63 μg/m3, and in district areas 62 μg/m3. From 2015 to 2020, in urban areas PM2.5 decreased by 14% year-1, in suburbs by 15% year -1, in traffic areas by 15% year-1, and in district areas by 12% year-1. The quarterly average concentrations of PM2.5 in winter andspring are higher than those in summer and autumn (64 μg/m3, 59 μg/m3, 45 μg/m3, 55 μg/m3, respectively). The influenceof meteorological factors on the daily average value of PM2.5 in each season was analysed. The daily average PM2.5 in spring, summer, autumn and winter is significantly negatively correlated with daily average wind speed, sunshine hours, and air pressure, and significantly positively correlated with daily average rainfall and relative humidity. Except for autumn, the daily average PM2.5 is positively correlated with temperature. Although Beijing’s PM2.5 has been declining since the adoption of the‘Air Pollution Prevention and Control Action Plan’, it is still far from the first level of the new ‘Ambient Air Quality Standard’(GB309S-2012) formulated by China in 2012.

Evaluation and Management of Ambient Air Quality, with Special Reference to China

1980 ◽  
Vol 7 (3) ◽  
pp. 223-228 ◽  
Author(s):  
Yao Zhi-Qi
Keyword(s):  
Air Quality ◽  
Geometric Mean ◽  
Monitoring And Evaluation ◽  
Ambient Air ◽  
Average Concentration ◽  
Quality Indices ◽  
Ambient Air Quality ◽  
Annual Average ◽  
Hygienic Standard ◽  
Annual Average Concentration

Monitoring and evaluation of air quality in urban and industrial areas are essential for air quality management. For evaluating the composite air-quality in the concomitant presence of several pollutants in the atmosphere, many air quality indices have been developed. This paper presents two indices, the ‘composite air-quality index (I1)’ and ‘the standard-exceeding index of air pollution (I2)’ together with their respective sub-indices, for the pollutants monitored and for use in combination.The first index, I1, is based on the annual average concentration measured in a year for each pollutant; it measures the overall composite air-quality. By relating the annual average concentration (Ci) of each pollutant to its hygienic standard (Si), as many (Ci/Si) values as the number of pollutant parameters monitored are found, whereupon I1 is computed as the geometric mean of the maximum and average of all (Ci/Si) values. A greater value of I1 means worse composite air-quality. It is simpler to compute than those more sophisticated ones in the literature, and holds the unique characteristic of considering, and yet not overemphasizing as formula (3) does (Nemerow, 1974), the maximum (Ci/Si) value.

scholarly journals Long-Term Atmospheric Visibility Trends and Characteristics of 31 Provincial Capital Cities in China during 1957–2016

Atmosphere ◽  
2018 ◽  
Vol 9 (8) ◽  
pp. 318 ◽  
Author(s):  
Weicong Fu ◽  
Ziru Chen ◽  
Zhipeng Zhu ◽  
Qunyue Liu ◽  
Jinda Qi ◽  
...  
Keyword(s):  
Air Quality ◽  
Socioeconomic Factors ◽  
Urban Areas ◽  
Meteorological Factors ◽  
Ambient Air ◽  
Ambient Air Quality ◽  
Capital Cities ◽  
The Public ◽  
Provincial Capital

Millions of pulmonary diseases, respiratory diseases, and premature deaths are caused by poor ambient air quality in developing countries, especially in China. A proven indicator of ambient air quality, atmospheric visibility (AV), has displayed continuous decline in China’s urban areas. A better understanding of the characteristics and the factors affecting AV can help the public and policy makers manage their life and work. In this study, long-term AV trends (from 1957–2016, excluding 1965–1972) and spatial characteristics of 31 provincial capital cities (PCCs) of China (excluding Taipei, Hong Kong, and Macau) were investigated. Seasonal and annual mean values of AV, percentage of ‘good’ (≥20 km) and ‘bad’ AV (<10 km), cumulative percentiles and the correlation between AV, socioeconomic factors, air pollutants and meteorological factors were analyzed in this study. Results showed that annual mean AV of the 31 PCCs in China were 14.30 km, with a declining rate of −1.07 km/decade. The AV of the 31 PCCs declined dramatically between 1973–1986, then plateaued between 1987–2006, and rebounded slightly after 2007. Correlation analysis showed that impact factors (e.g., urban size, industrial activities, residents’ activities, urban greening, air quality, and meteorological factors) contributed to the variation of AV. We also reveal that residents’ activities are the primary direct socioeconomic factors on AV. This study hopes to help the public fully understand the characteristics of AV and make recommendations about improving the air environment in China’s urban areas.

scholarly journals Ischemic Heart Disease and Ambient Air Pollution of Particulate Matter 2.5 in 51 Counties in the U.S.

2007 ◽  
Vol 122 (5) ◽  
pp. 626-633 ◽  
Author(s):  
Lina Balluz ◽  
Xiao-Jun Wen ◽  
Machell Town ◽  
Jeffrey D. Shire ◽  
Judy Qualter ◽  
...  
Keyword(s):  
Heart Disease ◽  
Particulate Matter ◽  
Air Quality ◽  
Ischemic Heart Disease ◽  
Ambient Air ◽  
Ischemic Heart ◽  
Ambient Air Pollution ◽  
Annual Average ◽  
Particulate Matter 2.5 ◽  
The U.S

Objective. Ischemic heart disease (IHD) is one of the most common health threats to the adult population of the U.S. and other countries. The objective of this study was to examine the association between exposure to elevated annual average levels of Particulate matter 2.5 (PM2.5) air quality index (AQI) and IHD in the general population. Methods. We combined data from the Behavioral Risk Factor Surveillance System and the U.S Environmental Protection Agency air quality database. We analyzed the data using SUDAAN software to adjust the effects of sampling bias, weights, and design effects. Results. The prevalence of IHD was 9.6% among respondents who were exposed to an annual average level of PM2.5 AQI >60 compared with 5.9% among respondents exposed to an annual average PM2.5 AQI ≤60. The respondents with higher levels of PM2.5 AQI exposure were more likely to have IHD (adjusted odds ratio 5 1.72, 95% confidence interval 1.11, 2.66) than respondents with lower levels of exposure after adjusting for age, gender, race/ethnicity, education, smoking, body mass index, diabetes, hypertension, and hypercholesterolemia. Conclusions. Our study suggested that exposure to relatively higher levels of average annual PM2.5 AQI may increase the likelihood of IHD. In addition to encouraging health-related behavioral changes to reduce IHD, efforts should also focus on implementing appropriate measures to reduce exposure to unhealthy AQI levels.

Evaluation of Air Pollution by NO2, SO2, PM10 in Bucharest

2018 ◽  
Vol 69 (1) ◽  
pp. 105-111
Author(s):  
Carmen Otilia Rusanescu ◽  
Cosmin Jinescu ◽  
Marin Rusanescu ◽  
Mihaela Begea ◽  
Olimpia Ghermec
Keyword(s):  
Air Pollution ◽  
Particulate Matter ◽  
Air Quality ◽  
Sulfur Dioxide ◽  
Urban Areas ◽  
Average Concentration ◽  
Limit Set ◽  
Temperature Influence ◽  
Wind Regime ◽  
Pm 10

In this paper is analysed the air quality in urban areas in Bucharest, the analysis was based on the monitoring of the average concentration of particulate matter PM 10, nitrogen oxides, NO2, and sulfur dioxide, SO2 in Bucharest between 2009-2015. The analysis refers to the maximum concentration of 24 h and the occurrence of overruns beyond the limit set. It also looked at the wind regime, air quality and temperature influence on air pollution in Bucharest between 2009-2015.

scholarly journals Impact of COVID-19 on Extremely Polluted Air Quality and Trend Forecast in Seven Provinces and Three Cities of China

2021 ◽  
Vol 9 ◽  
Author(s):  
Xiaoying Pan ◽  
Yonggang Zhao ◽  
Meng Wang
Keyword(s):  
Air Quality ◽  
Air Pollutants ◽  
Average Concentration ◽  
Air Pollutant ◽  
Chinese Government ◽  
Annual Average ◽  
Epidemic Period ◽  
The World ◽  
Before And After ◽  
Annual Average Concentration

At the beginning of 2020, COVID-19 broke out. Because the virus is extremely contagious and the mortality rate after infection is extremely high, China and many countries in the world have imposed lockdowns. Air pollutants during the epidemic period have attracted the attention of many scholars. This research is to use predictive models to describe changes in extreme air pollutants. China is the first country in the world to enter the lockdown state. This study uses data from 2015-2020 to compare and predict the concentration of extreme pollutants before and after the lockdown. The results show that the lockdown of the epidemic will reduce the annual average concentration of PM2.5, and the annual average concentration of O3 will increase first and then decrease. Through analysis, it is concluded that there is a synergistic decrease trend between PM2.5 and O3. With the various blockade measures for epidemic prevention and control, the reduction of extreme air pollutant concentrations is sustainable. The assessment of China’s air quality in conjunction with the COVID-19 can provide scientific guidance for the Chinese government and other relevant departments to formulate policies.

scholarly journals Analyzing Characteristics of Particulate Matter Pollution in Open-Pit Coal Mines: Implications for Green Mining

Energies ◽  
2021 ◽  
Vol 14 (9) ◽  
pp. 2680
Author(s):  
Huaiting Luo ◽  
Wei Zhou ◽  
Izhar Mithal Jiskani ◽  
Zhiming Wang
Keyword(s):  
Particulate Matter ◽  
Wind Speed ◽  
Temperature Difference ◽  
Meteorological Factors ◽  
Coal Mines ◽  
Ambient Air ◽  
Average Concentration ◽  
Open Pit ◽  
Particulate Pollution ◽  
The Impact

The particulate pollution in the open-pit coal mines of China is particularly severe in winter. The aim of this study is to understand the pollution characteristics of particulate matter (PM) in winter and provide a basis for the prevention and control of particulate pollution. We took the problem of PM concentration at the bottom of the Haerwusu Open-pit Coal Mine (HOCM) as the research object. Dust monitoring equipment at two measurement points at different heights were positioned for continuous monitoring of the PM concentration. The data for three months were gathered. Statistical analyses were performed to analyze the variation characteristics of the PM and its relationship with meteorological factors. The results show that the average PM concentration in the study area is below the average daily limit of the China National Ambient Air Quality Standard (GB 3095-2012). However, the average concentration of PM10 exceeded the national limit in December. The order of PM concentration is observed as December > January > February. The correlation of PM is found to be positive with humidity and negative with wind speed. Temperature is found to be positively correlated with PM in December, while it is negative in January. At the same time, the temperature difference in December is negatively correlated with PM concentration. Under the combined action of multiple meteorological factors, the magnitude of the impact on the PM concentration at the bottom of the pit in winter is humidity > temperature > wind speed > temperature difference (inverse temperature intensity). In conclusion, PM2.5 is found to be more sensitive to environmental factors. The results of this study are particularly useful to progress in green mining.

scholarly journals The influence of residential wood combustion on the concentrations of PM<sub>2.5</sub> in four Nordic cities

2019 ◽  
Author(s):  
Jaakko Kukkonen ◽  
Susana López-Aparicio ◽  
David Segersson ◽  
Camilla Geels ◽  
Leena Kangas ◽  
...  
Keyword(s):  
Air Quality ◽  
Urban Areas ◽  
Atmospheric Dispersion ◽  
Ambient Air ◽  
Nordic Countries ◽  
City Centre ◽  
Wood Combustion ◽  
Annual Average ◽  
Extensive Evaluation ◽  
The City

Abstract. Residential wood combustion (RWC) is an important contributor to air quality in numerous regions worldwide. This study is the first extensive evaluation of the influence of RWC on ambient air quality in several Nordic cities. We have analyzed the emissions and concentrations of PM2.5 in cities within four Nordic countries: the metropolitan areas of Copenhagen, Oslo and Helsinki, and Umeå. We have evaluated the emissions for the relevant urban source categories and modelled atmospheric dispersion on regional and urban scales. The emission inventories for RWC were based on local surveys, the amount of wood combusted, combustion technologies and other relevant factors. The accuracy of the predicted concentrations was evaluated based on urban concentration measurements. The predicted annual average concentrations ranged spatially from 4 to 7 μg/m3 (2011), from 6 to 10 μg/m3 (2013), from 4 to more than 13 μg/m3 (2013) and from 9 to more than 13 μg/m3 (2014), in Umeå, Helsinki, Oslo and Copenhagen, respectively. The higher concentrations in Copenhagen were mainly caused by the higher long-range transported background. The annual average fractions of PM2.5 concentrations attributed to RWC within the considered urban regions ranged spatially from 0 to 15 %, from 0 to 20 %, from 8 to 30 % and from 0 to 60 % in Helsinki, Copenhagen, Umeå and Oslo, respectively. In particular, the contributions of RWC in central Oslo were larger than 40 % as annual averages. In Oslo, wood combustion was used mainly for the heating of larger blocks of flats. On the contrary, in Helsinki, RWC was solely used in smaller detached houses. In Copenhagen and Helsinki, the highest fractions occurred outside the city center in the suburban areas. In Umeå, the highest fractions occurred both in the city centre and its surroundings. Stricter and more efficient emission regulations should be set in the Nordic countries with respect to RWC, especially in urban areas, for the protection of human health.

scholarly journals Benzo[a]pyrene in the Ambient Air in the Czech Republic: Emission Sources, Current and Long-Term Monitoring Analysis and Human Exposure

Atmosphere ◽  
2020 ◽  
Vol 11 (9) ◽  
pp. 955
Author(s):  
Markéta Schreiberová ◽  
Leona Vlasáková ◽  
Ondřej Vlček ◽  
Jana Šmejdířová ◽  
Jan Horálek ◽  
...  
Keyword(s):  
Czech Republic ◽  
Local Heating ◽  
Monitoring Network ◽  
Kendall Test ◽  
Ambient Air ◽  
Average Concentration ◽  
Annual Average ◽  
The Czech Republic ◽  
Residential Heating ◽  
Annual Average Concentration

This paper provides a detailed, thorough analysis of air pollution by benzo[a]pyrene (BaP) in the Czech Republic. The Czech residential sector is responsible for more than 98.8% of BaP, based on the national emission inventory. According to the data from 48 sites of the National Air Quality Monitoring Network, the range of annual average concentration of BaP ranges from 0.4 ng·m−3 at a rural regional station to 7.7 ng·m−3 at an industrial station. Additionally, short-term campaign measurements in small settlements have recorded high values of daily benzo[a]pyrene concentrations (0.1–13.6 ng·m−3) in winter months linked to local heating of household heating. The transboundary contribution to the annual average concentrations of BaP was estimated by the CAMx model to range from 46% to 70% over most of the country. However, the contribution of Czech sources can exceed 80% in residential heating hot spots. It is likely that the transboundary contribution to BaP concentrations was overestimated by a factor of 1.5 due to limitations of the modeling approach used. During the period of 2012–2018, 35–58% of the urban population in the Czech Republic were exposed to BaP concentrations above target. A significant decreasing trend, estimated by the Mann-Kendall test, was found for annual and winter BaP concentrations between 2008 and 2018.

Air quality standard exceedance and management in an Indian mining area

2003 ◽  
Vol 30 (3) ◽  
pp. 266-273 ◽  
Author(s):  
S.K. Chaulya
Keyword(s):  
Particulate Matter ◽  
Air Quality ◽  
Ambient Air ◽  
Mining Area ◽  
Quality Standard ◽  
Effective Control ◽  
Residential Areas ◽  
Annual Average ◽  
Industrial Areas ◽  
Respirable Particulate

Detailed studies are essential in India to evaluate air quality and implement measures for effective control of mining in sensitive locations. A study for this purpose was carried out in the Basundhara area of the Ib Valley coalfield in Orissa State, India. The 24-hr average concentrations of suspended particulate matter (SPM), respirable particulate matter (RPM), sulphur dioxide (SO2) and oxides of nitrogen (NOx) were determined at regular intervals throughout one year at seven monitoring stations in residential areas and two stations in mining/industrial areas. The 24-hr average SPM and RPM concentrations were 312.7–598.4 μg m−3 and 100.2–199.6 μg m−3 in industrial areas, and were 95.6–275.7 μg m−3 and 28.5–86.8 μg m−3 in residential areas. During the study period, 24-hr and annual average SPM and RPM concentrations exceeded the respective standards set in the Indian national ambient air quality standard (NAAQS) protocol in certain residential and industrial areas. However, 24-hr and annual average concentrations of SO2 (residential: 20.5–24.3 μg m−3, industrial: 15.3–30.8 μg m−3) and NOx (residential: 19.7–25.3 μg m−3, industrial: 14.3–33.5 μg m−3) were well within the prescribed limit of the NAAQS in both residential and industrial areas. The temporal variations of SPM and RPM fitted polynomial trends well and on average in the mining area 31.38% of the SPM was RPM. The linear regression correlation coefficients between SPM and RPM and between NOx and SO2 were 0.90 and 0.52, respectively. The kriging technique determined that maximal concentrations of SPM and RPM occurred within the mining site. A management strategy is formulated for effective control of air pollution at source, and mitigative measures should include implementation of green belts around the sensitive areas where the concentration of air pollutants exceeds the standard limit.

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