Spatiotemporal heterogeneity of PM2.5 and its driving difference comparison associated with urbanization in China’s multiple urban agglomerations

Xu, Wentian; Wang, Yixu; Sun, Shuo; Yao, Lei; Li, Tong; Fu, Xuecheng

doi:10.1007/s11356-021-17929-x

Cited by 23 publications

(12 citation statements)

References 59 publications

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“…Currently, a great deal of research has been conducted on regional air pollution, with perspectives focusing on spatial-temporal evolution patterns and factors [10,11]. To broadly explore the spatial-temporal evolution of air pollution, the perspectives include emission inventories of air pollutants [12], source analysis of particulate matter [5], and spatialtemporal evolution and prediction of air pollution from differentiated data sources [11,13]. The selected research objects include single air pollutants, such as SO 2 [14,15], NO 2 [16,17], O 3 [18,19], PM 10 [20,21], and PM 2.5 [22,23], and composite indices, such as API [24] and AQI [25].…”

Section: Introductionmentioning

confidence: 99%

“…The selected research objects include single air pollutants, such as SO 2 [14,15], NO 2 [16,17], O 3 [18,19], PM 10 [20,21], and PM 2.5 [22,23], and composite indices, such as API [24] and AQI [25]. The spatial scales of the studies are mainly focused on the national scale [3], provincial scale [26], urban clusters [11], and urban scale [27]. In addition, most of the current studies focus on the factors of air pollution [10,28,29], pollution management, prevention, and control policies [30].…”

Section: Introductionmentioning

confidence: 99%

“…However, socioeconomic factors are the fundamental contributors to air pollution. Economic development [10], urbanization [11], population density [33], FDI [7], energy structure [34], and land use [35] have been investigated in examining air pollution in current studies. Relevant research methods include geographic probes [28], spatial econometric models [3,36], gray correlation models [37], machine learning [13,38], and geographically weighted regression models [30].…”

Section: Introductionmentioning

confidence: 99%

“…In recent years, most of the relevant studies have focused on PM 2.5 , with few providing a comparative analysis of the spatial-temporal patterns of multiple air pollutants and their factors [40,41]. Regarding factor analysis, current studies mainly focus on socioeconomic factors, such as economic development and urbanization, while few articles include natural environmental factors [10,11]. Moreover, the impact of industrial structure transformation on air pollution has been explored by selecting the share of secondary industry in GDP or the share of tertiary industry in GDP as the core explanatory variables [42,43].…”

Section: Introductionmentioning

confidence: 99%

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Has Industrial Upgrading Improved Air Pollution?—Evidence from China’s Digital Economy

Wang

et al. 2022

Sustainability

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Air pollution has seriously hindered China’s sustainable development. The impact mechanism of industrial upgrading on air pollution is still unclear, given the rapid digital economy. It is necessary to analyze the impact of industrial structure upgrading on air pollution through the digital economy. To investigate the impact of industrial upgrading and the digital economy on air pollution, this paper selected the industrial advanced index and the digital economy index to construct a panel regression model to explore the improvement effect of industrial upgrading on air pollution and selected China’s three typical areas to construct a zonal regression model. The concentrations of air pollutants showed a downward trend during 2013–2020. Among them, the SO2 concentration decreased by 63%, which is lower than the PM2.5 and NO2 concentrations. The spatial pattern of air pollutants is heavier in the north than in the south and heavier in the east than in the west, with the North China Plain being the center of gravity. These air pollutants have significant spatial spillover effects, while local spatial correlation is dominated by high-high and low-low clustering. Industrial upgrading has a stronger suppressive effect on the PM2.5 concentration than the suppressive effect on the SO2 and NO2 concentrations, while the digital economy has a stronger improvement effect on the SO2 concentration than its improvement effect on the PM2.5 and NO2 concentrations. Industrial upgrading has a stronger improvement effect on air pollution in the Yangtze River Delta urban agglomeration than in Beijing–Tianjin–Hebei and its surrounding areas, while the improvement in air pollution attributable to the digital economy in Beijing–Tianjin–Hebei and its surrounding areas is stronger than in the Yangtze River Delta urban agglomeration. There are significant differences in the effects of industrial upgrading and the digital economy on the various types of air pollutants.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Has Industrial Upgrading Improved Air Pollution?—Evidence from China’s Digital Economy

Wang

et al. 2022

Sustainability

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“…With the rapid economic growth, the expansion of industrialization and urbanization, and the surge in population density, urban air pollution has become increasingly serious, exposing a large number of residents to health risks (Chen and Chen 2021; Du et al 2018; Jiang and Bai 2018; Xu et al 2022).…”

Section: Introductionmentioning

confidence: 99%

Assessment of air quality before and during the COVID-19 and its potential health impacts in an arid oasis city: Urumqi, China

Sun

Aishan

Halik

et al. 2022

Preprint

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Air pollution has become one of the major environmental concerns to academia and urban residents. As a key megacity city of the "Silk Road Economic Belt", Urumqi has been listed as one of the ten most polluted cities in the world, posing a serious threat to the urban environment and residents' health. Therefore, the assessment of air pollution and its health impact on urban residents is urgently required for promoting the sustainable development of the city. This study analyzed the temporal and spatial changes in the concentration of major air pollutants in Urumqi and its response to epidemic prevention and control measures based on the data of PM2.5, PM10, SO2, NO2, CO, and O3_8h from 10 air quality monitoring stations in Urumqi from January 1, 2017, to December 31, 2021, mainly focusing on the temporal and spatial variation characteristics of PM2.5 and O3_8h concentrations, changes in pollution levels and their potential risks on human health. The results showed that the concentrations of air pollutants PM2.5, PM10, SO2, NO2, CO, and O3_8h at various air quality monitoring sites from 2017 to 2021 showed a cyclical trend, and the implementation of the government's strict COVID-19 prevention and control measures had a significant effect on the reduction of air pollutant concentrations. The mean value of ρ(PM2.5) decreased from 2017 to 2021, while ρ(O3_8h) showed a waveform change trend (increased in 2017–2018, decreased in 2018–2020, and increased after 2020 ). In terms of the distribution area, the variation of ρ(PM2.5) and ρ(O3_8h) were greater in industrial areas than in commercial and residential areas. Continuous wavelet coherence exists between AQI and PM2.5 and O3_8h at each site during the period from January 2018 to December 2020, and AQI and PM2.5 were positively correlated. The high pollution levels (grades IV and V) of air pollutants PM2.5 and O3_8h in Urumqi decreased year by year, indicating that the number of days with potential threats to residents' health is gradually decreasing. Therefore, more attention should be paid to the control and governance of air pollution in Urumqi.

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Assessment of air quality before and during the COVID-19 and its potential health impacts in an arid oasis city: Urumqi, China

Sun

Aishan

Halik

et al. 2022

Stoch Environ Res Risk Assess

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As a key node city of the “Silk Road Economic Belt” Urumqi has been listed as one of the ten most polluted cities in the world, posing a serious threat to the urban environment and residents' health. This study analyzed the air quality before and during the COVID-19 (Coronavirus disease 2019) pandemic and its potential health effects based on the data of PM 2.5 , PM 10 , SO 2 , NO 2 , CO, and O 3 _8h levels from 10 air quality monitoring stations in Urumqi from January 1, 2017, to December 31, 2021. As per the results, the concentrations of the air pollutants PM 2.5 , PM 10 , SO 2 , NO 2 , CO, and O 3 _8h in Urumqi from 2017 to 2021 showed a cyclical trend, and the implementation of COVID-19 prevention and control measures could effectively reduce the concentration(ρ) of air pollutants. The mean value of ρ(PM 2.5 ) decreased from 2017 to 2021, whereas ρ(O 3 _8h) showed a waveform change trend (increased in 2017–2018, decreased in 2018–2020, and increased after 2020). Meanwhile, the maximum annual average values of ρ(PM 2.5 ) and ρ(O 3 _8h) for the six monitoring stations during 2017–2021 occurred at sites S2 (74.37 µg m −3 ) and S6 (91.80 µg m −3 ), respectively; rapid industrialization had a greater impact on PM 2.5 and O 3 _8h concentrations compared to commercial and residential areas. In addition, the air quality index data series can characterize the fluctuation trend of PM 2.5 . The high pollution levels (Class IV and V) of the air pollutants PM 2.5 and O 3 _8h in Urumqi have been decreasing annually, and good days can account for 80–95% of the total number of days in the year, indicating that the number of days with a potential threat to residents' health is gradually decreasing. Therefore, more attention should be paid in controlling and managing air pollution in Urumqi.

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Spatiotemporal heterogeneity of PM2.5 and its driving difference comparison associated with urbanization in China’s multiple urban agglomerations

Cited by 23 publications

References 59 publications

Has Industrial Upgrading Improved Air Pollution?—Evidence from China’s Digital Economy

Has Industrial Upgrading Improved Air Pollution?—Evidence from China’s Digital Economy

Assessment of air quality before and during the COVID-19 and its potential health impacts in an arid oasis city: Urumqi, China

Assessment of air quality before and during the COVID-19 and its potential health impacts in an arid oasis city: Urumqi, China

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