Eco-Efficiency Assessment of Japanese Municipalities Based on Environmental Impacts and Gross Regional Product

Abstract

Governments at different levels need to appreciate the environmental impacts of socioeconomic activities within their boundaries. They also need to decide relevant environmental policies after carefully examining future pathways based on the relationship between the environment and the economy. This study focuses on Japanese basic administrative divisions (i.e., municipalities) and attempts to quantify the annual environmental efficiency of processes and socioeconomic activities within each of these divisions using life-cycle impact assessment (LCIA) concepts. A key element of the LCIA is the integration of different environmental loads across various impact categories, such as global warming, air pollution, and land use, and their representation through a simple indicator. First, we conduct annual environmental impact assessments for all Japanese municipalities based on reliable, verifiable, and comparable statistical information. Next, we estimate the environmental efficiency of socioeconomic activities within each division by dividing the gross regional product (GRP) with the environmental damage amounts calculated through LIME2, an LCIA-based tool tailored for Japan. Assessment results for each municipality are visualized on maps of Japan in order to highlight the spatial distribution of the values for each indicator. The findings of this study can aid local, regional, and national governments in Japan to inform environmental policy design and decision-making at different spatial levels.

Efficiency Evaluation of Regional Environmental Management Systems in Russia Using Data Envelopment Analysis

“…In environmental management, the decision process plays a vital role in implementing policies to promote development based on eco-efficient economic growth [18][19][20][21][22][23][24]. In this regard, for benchmarking and environmental performance assessment different approaches are used, which include parametric (stochastic frontier analysis) [25][26][27][28], nonparametric (data envelopment analysis), and multicriteria decision-making (MCDM) [29][30][31][32][33] approaches.…”