Spatiotemporal variation and influencing factors of air pollution in Anhui Province

Li, Jia; Sun, Jian; Fu, Yanfang

doi:10.1016/j.heliyon.2023.e15691

Cited by 6 publications

(8 citation statements)

References 18 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…However, the concentrations of PM10 and PM2.5 slowly increased before 2017 and then decreased, while the concentration of O3 significantly increased before 2018 and then slowly decreased. On a monthly scale, O3 shows an M-shaped variation, but the remaining five pollutants show a U-shaped variation (Jia et al, 2023). The concentration of air pollutants has been decreasing year by year in Chengdu-Chongqing urban agglomeration (CCUA) during 2015-2021.…”

Section: Comparison With Other Literaturesmentioning

confidence: 99%

“…Except for O3, five pollutants are positively correlated. But 5 pollutants are negatively correlated with O3 (Jia et al, 2023). AQI is positively correlated with PM2.5 and PM10 on multiple time scales, and positively correlated with SO2, CO, NO2, and O3 on short-term scales in CCUA (Tan et al, 2023).…”

Section: Comparison With Other Literaturesmentioning

confidence: 99%

“…Except for O3, temperature has the most prominent negative correlation effect on the five pollutants. The effect of sunlight duration on O3 is most significant in Anhui Province (Jia et al, 2023). In addition, in the short term, AQI is positively correlated with temperature and sunshine duration, and negatively correlated with humidity and rainfall in CCUA (Tan et al, 2023).The growth trend of O3 in most cities in China is mainly determined by changes in meteorological factors such as temperature and solar radiation, while the downward trend of PM2.5 is mainly determined by the emission reduction measures of PM2.5 and its precursors.…”

Section: Comparison With Other Literaturesmentioning

confidence: 99%

“…Terrain meteorology, economic development, pollution sources, and urbanization are closely related to air pollution (Bai et al, 2019). The economic growth and environmental protection policies have a positive impact on environmental governance in Anhui Province (Jia et al, 2023). Economic growth has the most important influence on PM2.5 concentration in China.…”

Section: Comparison With Other Literaturesmentioning

confidence: 99%

See 3 more Smart Citations

The Characteristics of Air Quality Changes in Hohhot City in China and their Relationship with Meteorological and Socio-economic Factors

Guo,

He,

Wang

2024

Aerosol Air Qual. Res.

View full text Add to dashboard Cite

Air pollution affects sustainable development of the natural environment and social economy. In this article, the changes in air quality index (AQI) and six air pollutants in Hohhot during 2014-2022 are analyzed. The results imply that the annual average concentrations of five air pollutants (SO2, PM10, PM2.5, NO2, and CO) and AQI values declined year by year over 2014-2022. Compared with 2014, AQI in Hohhot fell by 22.5% in 2022. However, the annual average concentrations of O3 increased year by year. PM2.5 and PM10 were the major factors in influencing AQI. Among the five types of atmospheric pollutants, the relationship between NO2 and O3 is strongest, implying that NO2 plays a significant influence in the formation of O3 and PM2.5. Meteorological and socioeconomic factors have a significant impact on air quality. The average wind speed (AWS), average pressure (AP), sulfur dioxide emissions (SOE), nitrogen oxide emissions (NOE), and particulate matter emissions (PME) have a positive effect on changes in air quality. The results provide the information of great importance for the management of air quality in Hohhot City.

show abstract

Section: Comparison With Other Literaturesmentioning

confidence: 99%

Section: Comparison With Other Literaturesmentioning

confidence: 99%

Section: Comparison With Other Literaturesmentioning

confidence: 99%

Section: Comparison With Other Literaturesmentioning

confidence: 99%

See 2 more Smart Citations

The Characteristics of Air Quality Changes in Hohhot City in China and their Relationship with Meteorological and Socio-economic Factors

Guo,

He,

Wang

2024

Aerosol Air Qual. Res.

View full text Add to dashboard Cite

show abstract

“…The researcher used various methods to analyse the distribution of pollutants in urban areas. 24,25 For example, Jin et al 1 used a satellite remote sensing inversion algorithm to study the temporal and spatial distribution of PM 2.5 in China from 2000 to 2018, indicating that PM 2.5 concentration in Northeast China was greatly influenced by population and economy. Meteorological monitoring stations are a common method for detecting PM 2.5 concentration, usually used to determine the horizontal and vertical diffusion of PM 2.5 to obtain the distribution characteristics of particles on roads.…”

Section: Literature Review and Theoretical Frameworkmentioning

confidence: 99%

Spatial distribution of PM_2.5 concentration around high-rise residential buildings during peak traffic hours in autumn and winter seasons

He,

Yang,

Liu

et al. 2023

Indoor and Built Environment

View full text Add to dashboard Cite

This research aimed to investigate the spatial distribution of PM2.5 in residential areas near major urban roads during the autumn and winter seasons. A traffic pollution distribution model was developed using ENVI-met software to predict the distribution of pollution in and around the residential area. The experimental results indicated that during peak hours, the concentration of PM2.5 inside the residential area exceeded 140 μg/m3. The simulations indicated a horizontal diffusion range of traffic pollution up to 300 m, with the most significant effects observed within a radius of 20 m where the pollutant concentration decreased from 131.6 μg/m3 to 93.5 μg/m3. The vertical diffusion of traffic pollution extended to approximately 100 m, with the highest impact observed within a distance of 22.5 m (7 floors). Furthermore, pollution diffused up to a height of 47.5 m near major urban roads, resulting in a decrease in the concentration of PM2.5 from 140 μg/m3 to 70 μg/m3. Quantitative comparisons showed that street pollution was higher in autumn than in winter, whereas pollution outside buildings near the street was higher in winter compared to autumn. Simultaneously, the impact of pollutants on human health was evaluated using the decrease in life expectancy (DLE) index. The results revealed a DLE of 13.16 years in areas with the highest pollution levels, while most residential areas had a DLE ranging between 3.2 and 3.88 years. These findings are significant in terms of raising awareness and providing valuable references for the development and planning of urban health initiatives.

show abstract

Source analysis and health risk assessment of polycyclic aromatic hydrocarbon (PAHs) in total suspended particulate matter (TSP) from Bengbu, China

Wu,

Chen,

et al. 2024

Sci Rep

View full text Add to dashboard Cite

The polycyclic aromatic hydrocarbon (PAH) concentrations in total suspended particulate matter (TSP) samples collected from October, 2021 to September, 2022 were analyzed to clarify the pollution characteristics and sources of 16 PAHs in the atmospheric TSP in Bengbu City. The ρ(PAHs) concentrations ranged from 1.71 to 43.85 ng/m3 and higher concentrations were detected in winter, followed by spring, autumn, and summer. The positive matrix factorization analysis revealed that, in spring and summer, PAH pollution was caused mainly by industrial emissions, gasoline and diesel fuel combustion, whereas in autumn and winter, it was coal, biomass and natural gas combustion. The cluster and potential source factor analyses showed that long-range transport was a significant factor. During spring, autumn, and winter, the northern and northwestern regions had a significant impact, whereas the coastal area south of Bengbu had the greatest influence in summer. The health risk assessment revealed that the annual total carcinogenic equivalent concentration values for PAHs varied from 0.0159 to 7.437 ng/m3, which was classified as moderate. Furthermore, the annual incremental lifetime cancer risk values ranged from 1.431 × 10−4 to 3.671 × 10−3 for adults and from 6.823 × 10−5 to 1.749 × 10−3 for children, which were higher than the standard.

show abstract

Spatiotemporal variation and influencing factors of air pollution in Anhui Province

Cited by 6 publications

References 18 publications

The Characteristics of Air Quality Changes in Hohhot City in China and their Relationship with Meteorological and Socio-economic Factors

The Characteristics of Air Quality Changes in Hohhot City in China and their Relationship with Meteorological and Socio-economic Factors

Spatial distribution of PM_2.5 concentration around high-rise residential buildings during peak traffic hours in autumn and winter seasons

Source analysis and health risk assessment of polycyclic aromatic hydrocarbon (PAHs) in total suspended particulate matter (TSP) from Bengbu, China

Contact Info

Product

Resources

About

Spatiotemporal variation and influencing factors of air pollution in Anhui Province

Cited by 6 publications

References 18 publications

The Characteristics of Air Quality Changes in Hohhot City in China and their Relationship with Meteorological and Socio-economic Factors

The Characteristics of Air Quality Changes in Hohhot City in China and their Relationship with Meteorological and Socio-economic Factors

Spatial distribution of PM2.5 concentration around high-rise residential buildings during peak traffic hours in autumn and winter seasons

Source analysis and health risk assessment of polycyclic aromatic hydrocarbon (PAHs) in total suspended particulate matter (TSP) from Bengbu, China

Contact Info

Product

Resources

About

Spatial distribution of PM_2.5 concentration around high-rise residential buildings during peak traffic hours in autumn and winter seasons