Abstract
Over the past few decades, China’s rapid economic, energy, and industrial developments have caused serious environmental damage. However, as there are large resource, energy use, economic, and environmental damage differences across Chinese regions, the Chinese government is seeking to reduce city pollution across the country. Most previous analyses have only looked at these issues on a single level; for example, the impact of environmental pollution on health, or energy and environmental efficiency analyses, but there have been few studies that have conducted overall analyses. Further, many of the methods that have been used in previous research have employed one-stage radial or non-radial analyses without considering regional differences. Therefore, this paper developed a meta undesirable two-stage EBM DEA model to analyze the energy, environment, health, and media communication efficiencies in 31 Chinese cities, from which it was found that the productivity efficiency in most cities was better than the health treatment efficiencies, the GDP and fixed asset efficiency improvements were small, the air quality index (AQI) and CO2 efficiencies varied widely between the cities, media report and governance inputs were generally inefficient, the birth rate efficiencies were better than the respiratory disease efficiencies, and the technical gap was best in Guangzhou, Shanghai, and Lhasa. Also, it found that high-income cities have a higher technology gap than upper middle–income cities, and media reports efficiency have a high correlation with respiratory diseases and CO2.
Highlights
The World Health Organization [1] claims that air pollution affects 93% of the world’s children’s health and that it is a primary cause of respiratory diseases, especially in low- and middle-income countries
To fully analyze the effectiveness of government health expenditure inputs and media coverage in combatting the energy and environmental effects of the production/labor first stage inputs, an applied meta two-stage Epsilon-based measure (EBM) data envelopment analysis (DEA) model that includes undesirable outputs is developed in this paper to analyze the energy, health, and media reporting efficiencies in 31 mainland Chinese cities
In examinations on the effects of long-term exposure to air pollutants on human health, Loomis et al [11] found a positive correlation between lung cancer and PM exposure and other air pollution indicators, Oakes et al [12] reviewed exposure indicators for multiple pollutants, and Fischer et al [13] studied the relationship between long-term exposure to air pollution and mortality, finding that every 10 μg/m3 increase in PM10 and NO2 was significantly associated with non-accidental mortality
Summary
The World Health Organization [1] claims that air pollution affects 93% of the world’s children’s health and that it is a primary cause of respiratory diseases, especially in low- and middle-income countries. To fully analyze the effectiveness of government health expenditure inputs and media coverage in combatting the energy and environmental effects of the production/labor first stage inputs, an applied meta two-stage Epsilon-based measure (EBM) DEA model that includes undesirable outputs is developed in this paper to analyze the energy, health, and media reporting efficiencies in 31 mainland Chinese cities. As this model includes existing production efficiencies and considers the sustainability of human health, it has two main contributions. Health treatment was taken as the second stage based on health expenditure and media report inputs and birth rate and respiratory disease prevalence outputs
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