Abstract
China has become the second-largest economy in the world; however, the price of its rapid economic development has been a rise in serious environmental pollution, with air quality being a major public issue in many regions. However, few previous energy and environmental sustainability studies have included the Air Quality Index (AOI) and in particular CO2 and PM2.5 emissions in their calculations and few have included regional differences, as these are difficult to describe using radial and non-radial methods. In this paper, DEA (Data Envelopment Analysis) is used to assess the energy and economic efficiencies of Chinese provinces and cities, in which the environmental pollution source variable is CO2, and the main methods applied are radial (CCR or BCC) and non-radial SBM (Slacks Based Measures). Different from past studies, this study used both a Meta Undesirable EBM (Epsilon-Based measure) method to overcome the radial and non-radial errors and geographical differences and AQI environmental pollution indicators to accurately assess the economic, energy, and environmental efficiencies. It was found that: (1) Guangzhou and Shanghai had the best four-year efficiencies, (2) the energy efficiency differences in each city were large and there was a significant need for improvements, (3) the GDP efficiencies in each city were high, indicating that all cities had strong economic development, (4) the CO2 efficiencies indicated that around half the cities had had sustained improvements, (5) the AQI efficiencies in each city were low and there was a significant need for improvement, and (6) the technological differences between the cities were large, with the efficiencies in the high-income cities being much higher than in the low-income cities.
Highlights
From 2010 to 2015, China’s Gross domestic production (GDP) output grew at an annual rate of 8%, and even though it declined in 2015, it managed to achieve an annual growth of 6%
Some previous energy and environmental research works have focused on energy or environmental efficiency [2,3,4,5,6,7,8,9,10,11,12,13,14], some have focused on the factors affecting energy efficiency [15,16,17,18,19,20,21,22], some have explored the environmental impacts of CO2 emissions [23,24,25,26] and some have considered SO2, NO2 or other pollutants as the undesirable outputs for energy and environmental efficiency assessments [27,28,29,30,31,32,33]
This paper considers CO2 and the AQI, which includes particulate matter (PM2.5 and PM10), sulfur dioxide (SO2), ozone (O3), and carbon monoxide (CO)
Summary
From 2010 to 2015, China’s GDP output grew at an annual rate of 8%, and even though it declined in 2015, it managed to achieve an annual growth of 6%. Some previous energy and environmental research works have focused on energy or environmental efficiency [2,3,4,5,6,7,8,9,10,11,12,13,14], some have focused on the factors affecting energy efficiency [15,16,17,18,19,20,21,22], some have explored the environmental impacts of CO2 emissions [23,24,25,26] and some have considered SO2, NO2 or other pollutants as the undesirable outputs for energy and environmental efficiency assessments [27,28,29,30,31,32,33] These earlier analyses were usually based on radial (CCR or BCC), non-radial (SBM) or Directional Distance function models; these three models have been known to over and/or underestimate the efficiency values. This paper, considers other air pollutants and adopts a meta-undesirable EBM DEA model to explore the energy and economic efficiencies in 31 cities in China.
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