Improving energy use and mitigating pollutant emissions across Three Regions and Ten Urban Agglomerations: A city-level productivity growth decomposition

Analyzing green transformation of energy use and pollutant emissions in China's Three Regions and Ten Urban Agglomerations (TRTAs) allows effectively promoting sustainable development in the country. This paper applies Data Envelopment Analysis, namely the Bounded-adjusted Measure (BAM) relying on the additive structure, to measure the technical inefficiency and productivity change across TRTAs in China. The technical inefficiency and productivity change observed for TRTAs are 0.29 and 2.29% respectively. The decomposition results indicate that industrial energy consumption, industrial sulfur dioxide (SO2), and industrial soot & dust emissions are the main variables causing TRTAs' industrial operation inefficiency. Spatially, environmental inefficiency of the above-mentioned three variables in North China Urban Agglomeration (NA) is higher than those in Northwest, Yangtze and Pearl River Delta Urban Agglomerations (NWA, YRDA, and PRDA respectively). Decomposition of the Gini coefficient shows that the performance associated with the three variables varies among the regions with intra-regional differentiation of the PRDA being the highest. Given the regional patterns in productivity change, more efforts should be directed towards improving technical progress on industrial energy conservation in NWA. Furthermore, regulations on industrial air pollutant emissions, joint mitigation and monitoring of the key indicators in PRDA should also be emphasized.

Automated summary

This paper uses Data Envelopment Analysis to measure technical inefficiency and productivity change in China's Three Regions and Ten Urban Agglomerations, finding that industrial energy consumption, industrial sulfur dioxide, and industrial soot & dust emissions are the main variables causing industrial inefficiency across regions. Spatially, there are differences in environmental performance and productivity change patterns among different urban agglomerations.