A dragon eating its own tail: public control of air pollution information in China

Ravetti, Chiara; Swanson, Timothy; Jin, Yana; Mu, Qiwen; Zhang, Shiqiu

doi:10.1017/s1355770x18000414

Cited by 8 publications

(3 citation statements)

References 34 publications

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“…A further research study discovered that families relying on media controlled by the government exhibit a notable decrease in their responsiveness to periods of high pollution. This suggests that the dissemination of biased information can have an impact on the influx of labor within a municipality, extending beyond purely economic considerations [15]. In conclusion, it is evident that local governments possess a substantial responsibility in the realm of air pollution control.…”

Section: To Effectively Combat Air Pollution the General Population M...mentioning

confidence: 95%

Analyzing Public Environmental Concerns at the Threshold to Reduce Urban Air Pollution

Yang,

Yin,

Jin

2023

Sustainability

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This work focuses on the extraction and analysis of large-scale data from the Internet, specifically using panel data consisting of 273 prefecture-level cities spanning the period from 2011 to 2021. The data are processed using both the panel fixed-effect model and the panel smooth transformation model (PSTR). This study examines the relationship between public environmental concern and urban air pollution, as well as the impact of various city area divisions on public environmental concern and urban ambient air pollution. The regression analysis reveals several key findings: (1) It is observed that the impact of public participation in environmental pollution control on suppressing air pollution exhibits a lag of approximately three periods. This implies that it takes some time for the power of public participation to manifest its effect in reducing air pollution. (2) The study finds that urban public environmental concern, as measured by the Baidu Index, has a suppressive effect on air pollution once it surpasses a threshold value of 20,455.36. (3) This effect is found to be strengthened as the level of public concern increases. Lastly, it is noted that public environmental concern exhibits regional heterogeneity, which can be attributed to factors such as economic development and scientific and technological advancements. These factors influence the level of public environmental concern in different regions. The findings may be succinctly summarized as follows: geographical variations in public environmental concern can be attributed to the impact of economic growth and advancements in science and technology. Regional variability may arise from several sources, including economic growth, scientific and technical advancements, and other influences, all of which impact public environmental concerns.

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Section: To Effectively Combat Air Pollution the General Population M...mentioning

confidence: 95%

Analyzing Public Environmental Concerns at the Threshold to Reduce Urban Air Pollution

Yang,

Yin,

Jin

2023

Sustainability

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“…Des weiteren könnten Bürger, die dem Staat mistrauen, selber messen und diese Messwerte auch in denöffentlichen Prozess einbringen. Damit kann eine staatliche Beschönigung der Luftverschmutzungswerte, wie sie weitgehend vermutet wird ( [4,5]), verhindert werden. Dieser Gesichtspunkt einer demokratischen Kontrolle könnte für die Akzeptanz von Smart Cities in der Bevölkerung wichtig sein.…”

Section: Einführungunclassified

Mechanismen zur Beschaffung korrekter Daten

Faltings

Radanovic

2016

Informatik Spektrum

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Smart Cities brauchen als Grundlage für Entscheidungen grosse Mengen von Daten, die häufig nicht direkt, sondernüber andere Agenten erhoben werden. Es ist daher wichtig, die Qualität durch geeignete Anreize oder Kontrolle sicherzustellen. Bei Ausnutzung der Spieltheorie ist dies erstaunlicherweise selbst dann möglich, wenn die Korrektheit der Daten gar nicht kontrolliert werden kann. Wir zeigen neuartige Mechanismen zur Qualitätssicherung für zwei Arten von Agenten. Für rational handelnde Agenten berechnen wir die Belohnung für die Daten so, dass nur korrekte Daten einen positiven Betrag erwarten können. Für fehlerhafte oder absichlich falsche Daten zeigen wir einen neuen Mechanismus, der den negativen Einfluss auf das erzeugte Modell begrenzt.

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“…Control of China's air quality monitoring stations was centralised under the China National Centre for Environmental Monitoring (CNEMC) and the monitoring network was expanded, with >1600 monitoring stations included from 2014. The centralisation of the monitoring network helped to avoid local government data manipulation that had resulted in somewhat unreliable data [26][27][28] , although there is evidence to suggest that some manipulation may have continued beyond 2014 29,30 .…”

Section: Introductionmentioning

confidence: 99%

Reversal in China’s Air Quality Gains

Silver,

Reddington,

Chen

et al. 2024

Preprint

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China’s air quality has improved rapidly since the early 2010s, when the government launched an action plan focussed on reducing fine particulate matter (PM2.5) pollution, the pollutant species associated with the largest negative health impact. Measurements from China’s monitoring network, now consisting of >2000 surface stations, have shown a rapid fall in PM2.5 concentrations consistently over the period 2014–2019, while sulphur dioxide (SO2), carbon monoxide (CO) and nitrogen dioxide (NO2) concentrations have also significantly decreased. Concurrently there has been a rapid increase in ozone concentrations, which has been partly attributed to falling particulate matter concentrations. However, air quality data from China remains difficult to access, and recent changes in China’s economic outlook mean that the future trajectory of China’s air quality continues to be highly uncertain. Here we analyse 10 years of air quality monitoring data from May 2014 to April 2024 to assess whether China’s air quality has continued to improve in recent years, in the wake of the COVID-19 lockdowns and other economic challenges. After using an improved data cleaning algorithm to remove outliers from the dataset, we use a non-linear trend fitting technique to extract underlying trends and their uncertainties. We find that the steep negative trend in PM2.5 that was observed during 2014–2019 has now reversed, and since June 2022 there has been a significant (>95% confident) positive trend at over half of China’s air quality monitoring stations. This is mirrored by the average trend of ozone, which was positive during 2014–2019, but since December 2022 there has been a significant negative trend at almost half of monitoring stations. The increase in PM2.5 exposure has the potential to worsen air quality health impacts in China, particularly given its ageing population.

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A dragon eating its own tail: public control of air pollution information in China

Cited by 8 publications

References 34 publications

Analyzing Public Environmental Concerns at the Threshold to Reduce Urban Air Pollution

Analyzing Public Environmental Concerns at the Threshold to Reduce Urban Air Pollution

Mechanismen zur Beschaffung korrekter Daten

Reversal in China’s Air Quality Gains

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