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<p>Disparities in air pollution exposure and heterogeneous health responses jointly contribute to systemic health inequalities and their socioeconomic outcomes. This study expands conventional income inequality frameworks by integrating air pollution, population health, and individual effort to systematically examine the mechanisms through which health losses and reduced effort exacerbate income inequality due to atmospheric pollutants. By matching city-level data of air pollution with individual-level data of health and income from the Chinese General Social Survey (CGSS) 2010–2015, a simultaneous equations model of income, effort, and health was constructed to explore how air pollution affects income and income inequality, even if all individuals made their maximum effort. Based on two counterfactual incomes with the same and different health effects of air pollution, Gini coefficient and Theil’s T index were used to decompose income inequalities of rural, urban, and five birth-year cohorts. Results show that vulnerable groups in the poor and the rural area were more likely to fall into the “low health-low effort-low income-low health” trap caused by severe air pollution. When the maximum effort was made, income gaps were narrowed by 24%-43%, but the maximum effort threshold of the rural and lower-middle income dropped due to air pollution, thereby substantially hindering individual effort to reduce income inequality.</p>

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Air pollution, individual effort, and income inequality: evidence from China

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年5月7日

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  • Peipei He,
  • Wenjing Li,
  • Junbiao Zhang

摘要

Disparities in air pollution exposure and heterogeneous health responses jointly contribute to systemic health inequalities and their socioeconomic outcomes. This study expands conventional income inequality frameworks by integrating air pollution, population health, and individual effort to systematically examine the mechanisms through which health losses and reduced effort exacerbate income inequality due to atmospheric pollutants. By matching city-level data of air pollution with individual-level data of health and income from the Chinese General Social Survey (CGSS) 2010–2015, a simultaneous equations model of income, effort, and health was constructed to explore how air pollution affects income and income inequality, even if all individuals made their maximum effort. Based on two counterfactual incomes with the same and different health effects of air pollution, Gini coefficient and Theil’s T index were used to decompose income inequalities of rural, urban, and five birth-year cohorts. Results show that vulnerable groups in the poor and the rural area were more likely to fall into the “low health-low effort-low income-low health” trap caused by severe air pollution. When the maximum effort was made, income gaps were narrowed by 24%-43%, but the maximum effort threshold of the rural and lower-middle income dropped due to air pollution, thereby substantially hindering individual effort to reduce income inequality.