Increasing social concerns over the environmental externalities associated with business activities are pushing firms to identify activities that create economic value with less environmental impact and to become more eco-efficient. Over the past two decades, researchers have increasingly used frontier efficiency models to evaluate productive efficiency in the presence of undesirable outputs, such as greenhouse gas emissions. In this paper, we identify critical flaws of existing frontier models and show that under these models eco-inefficient firms can be identified as eco-efficient. We develop a new eco-inefficiency frontier model that rectifies these problems. Our model allows us to calculate, for each firm, an eco-inefficiency score and improvements in outputs necessary to attain eco-efficiency. We demonstrate, through a Monte-Carlo experiment that our eco-inefficiency model provides a more reliable measurement of corporate eco-inefficiency than the existing frontier models. In the simulation experiment we develop a production function of multiple desirable and undesirable outputs that extends the classical Cob-Douglas function of a single output. The multi-output production function allows for greater flexibility in the simulation analysis of frontier models.

Measuring Eco-inefficiency: A New Frontier Approach

The sustainability of the Italian water sector: An empirical analysis by DEA

Landslides are affected not only by their own environmental factors, but also by the neighborhood environmental factors and the landslide clustering effect, which are represented as the neighborhood characteristics of modelling spatial datasets in landslide susceptibility prediction (LSP). This study aims to innovatively explore the neighborhood characteristics of landslide spatial datasets for reducing the LSP uncertainty. Neighborhood environmental factors were acquired and managed by remote sensing (RS) and the geographic information system (GIS), then used to represent the influence of landslide neighborhood environmental factors. The landslide aggregation index (LAI) was proposed to represent the landslide clustering effect in GIS. Taking Chongyi County, China, as example, and using the hydrological slope unit as the mapping unit, 12 environmental factors including elevation, slope, aspect, profile curvature, plan curvature, topographic relief, lithology, gully density, annual average rainfall, NDVI, NDBI, and road density were selected. Next, the support vector machine (SVM) and random forest (RF) were selected to perform LSP considering the neighborhood characteristics of landslide spatial datasets based on hydrologic slope units. Meanwhile, a grid-based model was also established for comparison. Finally, the LSP uncertainties were analyzed from the prediction accuracy and the distribution patterns of landslide susceptibility indexes (LSIs). Results showed that the improved frequency ratio method using LAI and neighborhood environmental factors can effectively ensure the LSP accuracy, and it was significantly higher than the LSP results without considering the neighborhood conditions. Furthermore, the Wilcoxon rank test in nonparametric test indicates that the neighborhood characteristics of spatial datasets had a great positive influence on the LSP performance.

/pdf/landslide-susceptibility-prediction-considering-neighborhood-t5lw2ddc.pdf

Landslide Susceptibility Prediction Considering Neighborhood Characteristics of Landslide Spatial Datasets and Hydrological Slope Units Using Remote Sensing and GIS Technologies

Window data envelopment analysis approach: A review and bibliometric analysis

Comprehensive analysis of water use and pollution management plays an important role in regional water security and sustainable socio-economic development. This study applies the environmental Kuznets curve (EKC), Gini index and elasticity coefficient methods to conduct an investigation of industrial and domestic water use and pollution management in Shandong. The results show that industrial water pollution generally displayed a coordinated relationship with socio-economic development, while an uncoordinated relationship occurred between domestic water pollution and socio-economic development. Meanwhile, the Gini index between domestic water use and population in 2017 (0.101) was superior to that of 2003 (0.165), and the Gini index of industrial water use and second industry output in 2017 (0.273) was better than that of 2003 (0.292), indicating that the allocation and equity of domestic and industrial water use in Shandong kept to a good development trend. Additionally, the industrial effect is better than the domestic effect in terms of the control of wastewater emissions and the governance of typical pollutants in wastewater. Accordingly, domestic water pollution has gradually become one of the major sources of water pollution, and the allocation of industrial and domestic water use has room to improve further in Shandong. Conjunctive use of the aforementioned three methods provides an approach to investigate the integrated management of water use and water pollution control from multiple angles.

https://www.mdpi.com/2073-4441/11/8/1630/pdf

Challenges for Water Security and Sustainable Socio-Economic Development: A Case Study of Industrial, Domestic Water Use and Pollution Management in Shandong, China

Due to the large volume of sewage in China, the efficiency of water consumption evaluated by the traditional model may be inaccurate. This paper evaluates the water consumption efficiency more scientifically. First, this paper uses the CCR model to evaluate the resource efficiency and environmental efficiency separately. The latter is generally lower than the former, which means the issue of water pollution is more serious than the problem of water resource consumption. Then, the water consumption efficiency is integrally evaluated by an eco-inefficiency model which focuses on undesirable outputs. The results are in good agreement with the results of the CCR model: (1) Only Beijing, Tianjin, and Shanghai are eco-efficient in terms of water consumption, water consumption efficiency in the southeastern coastal areas is higher than in the Midwest, and the overall water environment is bad; (2) China needs to focus on reducing industrial wastewater; (3) the output of water consumption has a lot of room for improvement; and (4) the output improvement schemes of all provinces have some similarities and are related to many features. So, this paper has made a clustering analysis of the improvement schemes and given detailed suggestions for improving the eco-efficiency of water consumption in China according to the clustering result.

Efficiency Evaluation of Water Consumption in a Chinese Province-Level Region Based on Data Envelopment Analysis

Influence of heavy rainfall and different slope cutting conditions on stability changes in red clay slopes: a case study in South China

The intensification of anthropogenic activities has led to the infiltration of enormous quantities of pollutants into rivers and lakes, resulting in significant deterioration in water quality and a more prominent occurrence of eutrophication. Poyang Lake, the largest freshwater lake in China, is facing a severe challenge related to eutrophication, which seriously threatens the delivery of the ecosystem service and the safety of drinking water. To address this challenge, Landsat-8 Operational Land Imager (OLI) data for the Poyang Lake Basin (PLB) from May 2013 to December 2020 were used. Since inland water bodies with complex optical characteristics, we developed a semi-analytical algorithm to assess the trophic state of the water based on two cruise field measurements in 2016 and 2019. Combining the semi-analytical trophic level index (TLI) with an atmospheric correction model is the most suitable model for OLI images of the PLB, this model was then applied to Landsat-8 time series observations. The trends of the trophic state of water bodies in PLB were revealed, and the annual, quarterly and monthly percentages of eutrophic water bodies were calculated. Natural and anthropogenic factors were then used to explain the changes in the trophic state of the PLB waters. The main findings are as follows: (1) From the 8-year observation results, it can be seen that the variation of trophic level of water in PLB showed obviously spatial and temporal variations, characterized by higher in the north than in the south and higher in winter than in summer. (2) Temperature promoted the growth of harmful algae and plays an essential role in affecting changes in the trophic level of the water. (3) Changes in the trophic level of water bodies in PLB were mainly affected by human activities. The results of spatial and temporal variation of the trophic level of water and the driving factors in PLB can extend our knowledge of water quality degradation and provide essential references for relevant policy-making institutions.

/pdf/estimating-effects-of-natural-and-anthropogenic-activities-2whpgef0.pdf

Estimating Effects of Natural and Anthropogenic Activities on Trophic Level of Inland Water: Analysis of Poyang Lake Basin, China, with Landsat-8 Observations

Resilient city is an ideal goal and model of urban development proposed in response to today’s complex and dynamic environmental changes. In this study, a resilient city evaluation framework of “social resilience-economic resilience-urban infrastructure and service-urban governance” was built upon the multi-dimensionality of the urban system; the entropy weight method was used to measure the level of urban resilience in Hunan Province while an obstacle degree model was used to identify any obstacle factor restricting to the development of resilience. The results show that the level of urban resilience in Hunan Province has grown slowly over the past 10 years, and there is an obvious regional difference in it. There are more and more highly resilient cities, but medium/low-resilience cities still dominate the province, forming a spatial process of evolution from “medium/high-level dispersion” to “medium/high-level aggregation” in the Changsha-Zhuzhou-Xiangtan Urban Agglomeration. The level of urban resilience is predominantly hindered by the social and economic systems; at the index layer, most obstacle factors are moving from the economic system to the social-economic-urban infrastructure and service system.

Evaluation of urban resilience level and analysis of obstacle factors: A case study of Hunan Province, China

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Papers

Efficiency Evaluation of Water Consumption in a Chinese Province-Level Region Based on Data Envelopment Analysis

Influence of heavy rainfall and different slope cutting conditions on stability changes in red clay slopes: a case study in South China

Estimating Effects of Natural and Anthropogenic Activities on Trophic Level of Inland Water: Analysis of Poyang Lake Basin, China, with Landsat-8 Observations

Evaluation of urban resilience level and analysis of obstacle factors: A case study of Hunan Province, China