Dirty skies lower subjective well-being

  • Lu Cheng
  • , Zhifu Mi*
  • , Yi Ming Wei
  • , Shidong Wang
  • , Klaus Hubacek
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Self-reported life satisfaction of China's population has not improved as much as expected during the economic boom, which was accompanied by a significant decline in environmental performance. Is environmental pollution the culprit for the lagging subjective well-being? To explore this issue, this paper adopts sentiment analysis to construct a real-time daily subjective well-being metric at the city level based on the big data of online search traces. Using daily data from 13 Chinese cities centred on Beijing between August 2014 and December 2019, we look at the corelation between subjective well-being and air pollution and the heterogeneity in this relationship based on two separate identification strategies. We find that air pollutants are negatively correlated with subjective well-being, and well-being tends to decline more from pollution during hot seasons. In addition, residents in wealthier regions tend to be more sensitive to air pollution. This result may be explained by the differences in the subjective perception of air pollution and personal preferences at different levels of income. These findings provide information about concerns of the public, thereby helping the government to take appropriate actions to respond to the dynamics of subjective well-being.

Original languageEnglish
Article number134380
JournalJournal of Cleaner Production
Volume378
DOIs
Publication statusPublished - 10 Dec 2022
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy
  2. SDG 11 - Sustainable Cities and Communities
    SDG 11 Sustainable Cities and Communities
  3. SDG 12 - Responsible Consumption and Production
    SDG 12 Responsible Consumption and Production

Keywords

  • Air pollution
  • Big data
  • Sentiment analysis
  • Subjective well-being

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