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Industrial production is key to economic development, yet it significantly influences the water environment. Recent literature has mainly focused on economic development and water pollution separately, lacking an integrated assessment. This study aims to clarify the links between industrial production and water pollution and its driving factors in the Yangtze River Economic Belt (YREB) in 2012–2017 based on environmentally-extended input-output analysis and structural decomposition analysis, thus identifying key regions and sectors for pollution reduction. The results revealed that manufacture of foods and tobacco (MFT) and chemical industry (CI) in Anhui, Jiangsu, Jiangxi, Hunan, and processing of petroleum, coking, processing of nuclear fuel (PPCN) in Chongqing were the primary sources of total chemical oxygen demand (COD), ammoniacal nitrogen (NH 3 –N), total nitrogen (TN), and total phosphorus (TP) discharges. The structural decomposition analysis (SDA) results demonstrated that the discharge intensity effect caused a decrease of 7.91 Mt, 0.22 Mt, 0.25 Mt, and 0.03 Mt of the indirect COD, NH 3 –N, TN, and TP discharge, while the scale effect led to an increase of 1.95 Mt, 0.26 Mt, 0.24 Mt and 0.03 Mt of them in 2012–2017. According to the analysis, water pollution reduction and industrial structure modernization are needed in the YREB. The technological upgrading of highly polluting industries and the structural adjustment between traditional highly polluting industries and high-tech industries were the focus for achieving green development of the YREB, especially in Anhui, Hubei, Guizhou and Yunnan. The establishment of green industrial parks, the development of environmental regulations, and the implementation of supply-side reform policies can benefit water pollution reduction and sustainable development. [Display omitted] • The EEIO model was applied to identify key regions and sectors for water pollution. • MFT, MT, MTCS, PPCN and CI were major sectors for water pollutant discharges. • Jiangsu and Jiangxi were major contributors for water pollutant discharges. • Discharge intensity effect decrease water pollution, scale effect did the opposite. • Green development need focus on industries with high indirect pollutant discharge. [ABSTRACT FROM AUTHOR]

Abstract: The effect of roads on forests is ambiguous. Many studies conclude that building and upgrading roads increases pressure on forests but some find that new and better roads may reduce the rate of deforestation. In this paper we use satellite remote sensing images of forest cover in Jiangxi Province, China, to test whether the existence and the size of roads (ranging from expressways to tertiary roads) in 1995 affected the level of forest cover in 2000 or the rate of change between 1995 and 2000. To account for road access for each of our 1km2 (“pixel”) units of forest cover we measure whether or not and what type of roads penetrate the “watershed” in which the pixel lies. These watersheds allow more plausible measures of accessibility than do traditional “crowfly” distance measures that ignore topography. To account for possible confounding we also use 12 additional covariates: geographic and climatic variables (e.g., elevation, slope, rainfall, temperature, soil properties); demographic and economic variables (e.g., local population and GDP per square kilometer); and distance variables (e.g., distance to the nearest provincial capital). Although simple univariate OLS regressions show that forest levels are lower and deforestation rates higher either when there is a road, or when there is a higher quality road, these results are not robust. Controlling for all of the covariates and also using recently developed covariate matching techniques to estimate treatment effects, we find that roads in China’s Jiangxi Province can most safely be described as having no impact on the level of forests and no impact on the rate of deforestation. [ABSTRACT FROM AUTHOR]