Measuring the Environmental Efficiency and Technology Gap of PM2.5 in China’s Ten City Groups: An Empirical Analysis Using the EBM Meta-Frontier Model

Abstract

Since air pollution is an important factor hindering China’s economic development, China has passed a series of bills to control air pollution. However, we still lack an understanding of the status of environmental efficiency in regard to air pollution, especially PM2.5 (diameter of fine particulate matter less than 2.5 μm) pollution. Using panel data on ten major Chinese city groups from 2004 to 2016, we first estimate the environmental efficiency of PM2.5 by epsilon-based measure (EBM) meta-frontier model. The results show that there are large differences in PM2.5 environmental efficiency between cities and city groups. The cities with the highest environmental efficiency are the most economically developed cities and the city group with the highest environmental efficiency is mainly the eastern city group. Then, we use the meta-frontier Malmquist EBM model to measure the meta-frontier Malmquist total factor productivity index (MMPI) in each city group. The results indicate that, overall, China’s environmental total factor productivity declined by 3.68% and 3.49% when considering or not the influence of outside sources, respectively. Finally, we decompose the MMPI into four indexes, namely, the efficiency change (EC) index, the best practice gap change (BPC) index, the pure technological catch-up (PTCU) index, and the frontier catch-up (FCU) index. We find that the trend of the MMPI is consistent with those of the BPC and PTCU indexes, which indicates that the innovation effect of the BPC and PTCU indexes are the main driving forces for productivity growth. The EC and FCU effect are the main forces hindering productivity growth.

Air Quality Evaluation and Improvement of China’s Three Major Urban Agglomerations Based on the Modified MetaFrontier Dynamic Slack-Based Measures Model

“…4. China has not achieved coordinated development between the environment and economic growth in the past decade (Cheng et al, 2019). This is similar to our conclusion.…”

“…Their results show that high-income cities have higher average efficiencies than uppermiddle income cities. Cheng et al (2019) estimate the environmental efficiency of PM2.5 by the epsilon-based measure (EBM) meta-frontier model. Their findings offer large differences in PM2.5 environmental efficiency between cities and city groups.…”

Performance Evaluation of Solar PV Power Plants in Taiwan Using Data Envelopment Analysis

“…Data envelopment analysis has been used for a long time and has proven to be a successful methodology for evaluating the performance of a group of homogeneous decision-making units (DMUs) based on their multiple inputs and outputs. The implementation of DEA in evaluating renewable resources performance, renewable energy studies, position in sustainability, energy efficiency, as well as other disputes related to energy and environment have been studied [5][6][7][8]. Additionally, as cited from different research, EBM is being applied to analyze production and efficiency; to compare efficiency values; to reduce emissions and for efficiency of PV industry; to see differences in carbon emissions, efficiency, and technology gap; to evaluate the process in procurement; to analyze traditional energy, to operate performance; and to measure the total factor energy efficiency.…”

Atmospheric Pollution Mapping of the Yangtze River Basin: An AQI-Based Weighted Co-Word Analysis

“…The existing studies pay more attention to explicating what contributes to atmospheric pollution of the YRB considering meteorological and human factors [26].Statistical analysis methods are frequently applied to describe the pollution sources, especially though time series analysis and spatial analysis [27,28]. Mathematical research has revealed single factors, such as spatiotemporal variation, meteorological factors, pollution sources, socioeconomic factors, etc.[29] Regarding the environmental incidents, researchers focus more on environmental quality evaluation systems in the metropolis of the YRB [30,31]. The analysis of deep causes (not only from objective data) and the interaction of factors are critical, but often-overlooked, components of air pollution, which may contribute to biased conclusions.…”

“…[29] Regarding the environmental incidents, researchers focus more on environmental quality evaluation systems in the metropolis of the YRB [30,31]. The analysis of deep causes (not only from objective data) and the interaction of factors are critical, but often-overlooked, components of air pollution, which may contribute to biased conclusions.…”