Research on adaption to air pollution in Chinese cities: Evidence from social media-based health sensing

Ji, Huimin; Wang, Juan; Meng, Bin; Cao, Zheng; Yang, Tong; Zhi, Guoqing; Chen, Siyu; Wang, Shaohua; Zhang, Jingqiu

doi:10.1016/j.envres.2022.112762

Cited by 29 publications

(18 citation statements)

References 56 publications

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“…According to the long-term interim targets 1 and 2 (the annual average PM 2.5 concentrations of 35 μg/m 3 and 25 μg/m 3 , respectively) recommended by the WHO global air quality guidelines, 31 PARs in this research were divided into three categories: PARs with good air quality (an annual average PM 2.5 concentration of lower than 25 μg/m 3 ), PARs with moderate air quality (an annual average PM 2.5 concentration of between 25 and 35 μg/m 3 ) and PARs with poor air quality (an annual average PM 2.5 concentration of higher than 35 μg/m 3 ) [ 26 ].…”

Section: Resultsmentioning

confidence: 99%

“…Short-term studies cannot reveal variations of social media postings with the rapid changes in air pollution in China in recent years. Moreover, studies have shown that there are some differences in the public’s sensitivity to major air pollutants (PM 2.5 , PM 10 , CO, O 3 , SO 2 and NO 2 ) across China [ 26 ]. Therefore, a longer-duration study including data on concentrations of different pollutants and related microblogs is needed in order to understand the long-term effects of air pollution through social media postings.…”

Section: Introductionmentioning

confidence: 99%

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Public Concern about Air Pollution and Related Health Outcomes on Social Media in China: An Analysis of Data from Sina Weibo (Chinese Twitter) and Air Monitoring Stations

Krishnan

Jia

2022

IJERPH

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To understand the temporal variation, spatial distribution and factors influencing the public’s sensitivity to air pollution in China, this study collected air pollution data from 2210 air pollution monitoring sites from around China and used keyword-based filtering to identify individual messages related to air pollution and health on Sina Weibo during 2017–2021. By analyzing correlations between concentrations of air pollutants (PM2.5, PM10, CO, NO2, O3 and SO2) and related microblogs (air-pollution-related and health-related), it was found that the public is most sensitive to changes in PM2.5 concentration from the perspectives of both China as a whole and individual provinces. Correlations between air pollution and related microblogs were also stronger when and where air quality was worse, and they were also affected by socioeconomic factors such as population, economic conditions and education. Based on the results of these correlation analyses, scientists can survey public concern about air pollution and related health outcomes on social media in real time across the country and the government can formulate air quality management measures that are aligned to public sensitivities.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Public Concern about Air Pollution and Related Health Outcomes on Social Media in China: An Analysis of Data from Sina Weibo (Chinese Twitter) and Air Monitoring Stations

Krishnan

Jia

2022

IJERPH

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“…By adjusting the learning rate and the number of iterations, the overall accuracy of the classifier by BERT was over 86%. More detailed information can be found in the research [27]. Finally, all the Weibo data in the study area were input into BERT and 21,372 Weibo items in total relating to APRH were obtained in the study area.…”

Section: Deriving the Real-time Expressed Aprh Based On Weibo Datamentioning

confidence: 99%

“…The monthly active users of Weibo reached 511 million in September 2020 [26]. It has been widely used to identify the health status and explore the sensitivity to air pollution [27,28].…”

Section: Introductionmentioning

confidence: 99%

Spatial Distribution of Urban Parks’ Effect on Air Pollution-Related Health and the Associated Factors in Beijing City

Wang

Zhu

et al. 2022

IJGI

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Urban parks play an essential role in mitigating the effects of air pollution on human health in a healthy city construction process. However, due to the data limitations, little is known about the spatial distribution of real-time expressed air pollution-related health (APRH) across different urban parks and the contribution of the associated factors. To fill this research gap, this research was conducted based on social media Weibo data (Chinese Twitter) and other geographical data using semantic analyses and the Geo-Detector method by taking 169 urban parks in Beijing as the study area. The results showed that there were more Weibo items relating to APRH clustered within the third ring road and decreasing outward along the ring road. A total of 16 factors in three categories were introduced to analyze the driving forces of this spatial distribution. Accessibility was outstanding with a q-value of the number of subway stations (X14) as high as 0.79, followed by built environment and finally park attributes. Distinguished from those reports based on the traditional statistical data, this research demonstrated that although the urban parks improved the APRH, the exposure to air pollution also increased the health risks when visiting the urban park. It also provides a geographical understanding of the urban parks’ effect on APRH and theoretical guidance for urban park planning and construction.

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“…Rapid urbanization and industrialization, deteriorating the air quality of most Chinese cities have resulted in adverse impacts on public health [1][2][3]. According to the World Health Organization [WHO] standards, only 1% of Chinese megacities meet the safe city criteria in terms of air quality [4].…”

Section: Introductionmentioning

confidence: 99%

Spatiotemporal characterization of aerosols and trace gases over the Yangtze River Delta region, China: impact of trans-boundary pollution and meteorology

et al. 2022

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Background The spatiotemporal variation of observed trace gases (NO2, SO2, O3) and particulate matter (PM2.5, PM10) were investigated over cities of Yangtze River Delta (YRD) region including Nanjing, Hefei, Shanghai and Hangzhou. Furthermore, the characteristics of different pollution episodes, i.e., haze events (visibility < 7 km, relative humidity < 80%, and PM2.5 > 40 µg/m3) and complex pollution episodes (PM2.5 > 35 µg/m3 and O3 > 160 µg/m3) were studied over the cities of the YRD region. The impact of China clean air action plan on concentration of aerosols and trace gases is examined. The impacts of trans-boundary pollution and different meteorological conditions were also examined. Results The highest annual mean concentrations of PM2.5, PM10, NO2 and O3 were found for 2019 over all the cities. The annual mean concentrations of PM2.5, PM10, and NO2 showed continuous declines from 2019 to 2021 due to emission control measures and implementation of the Clean Air Action plan over all the cities of the YRD region. The annual mean O3 levels showed a decline in 2020 over all the cities of YRD region, which is unprecedented since the beginning of the China’s National environmental monitoring program since 2013. However, a slight increase in annual O3 was observed in 2021. The highest overall means of PM2.5, PM10, SO2, and NO2 were observed over Hefei, whereas the highest O3 levels were found in Nanjing. Despite the strict control measures, PM2.5 and PM10 concentrations exceeded the Grade-1 National Ambient Air Quality Standards (NAAQS) and WHO (World Health Organization) guidelines over all the cities of the YRD region. The number of haze days was higher in Hefei and Nanjing, whereas the complex pollution episodes or concurrent occurrence of O3 and PM2.5 pollution days were higher in Hangzhou and Shanghai. The in situ data for SO2 and NO2 showed strong correlation with Tropospheric Monitoring Instrument (TROPOMI) satellite data. Conclusions Despite the observed reductions in primary pollutants concentrations, the secondary pollutants formation is still a concern for major metropolises. The increase in temperature and lower relative humidity favors the accumulation of O3, while low temperature, low wind speeds and lower relative humidity favor the accumulation of primary pollutants. This study depicts different air pollution problems for different cities inside a region. Therefore, there is a dire need to continuous monitoring and analysis of air quality parameters and design city-specific policies and action plans to effectively deal with the metropolitan pollution.

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Research on adaption to air pollution in Chinese cities: Evidence from social media-based health sensing

Cited by 29 publications

References 56 publications

Public Concern about Air Pollution and Related Health Outcomes on Social Media in China: An Analysis of Data from Sina Weibo (Chinese Twitter) and Air Monitoring Stations

Public Concern about Air Pollution and Related Health Outcomes on Social Media in China: An Analysis of Data from Sina Weibo (Chinese Twitter) and Air Monitoring Stations

Spatial Distribution of Urban Parks’ Effect on Air Pollution-Related Health and the Associated Factors in Beijing City

Spatiotemporal characterization of aerosols and trace gases over the Yangtze River Delta region, China: impact of trans-boundary pollution and meteorology

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