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Industrial wastewater discharge in China is increasing with the country′s economic development and it is worthy of concern. The discharge is primarily relevant to the direct discharge coefficient of each sector of the economy, its direct input coefficient and the final demand in input-output models. In this study, we calculated the sensitivity of the reduction in the Chinese industrial wastewater discharge using the direct input coefficients based on the theory of error-transmission in an input-output framework. Using input-output models, we calculated the direct and total industrial wastewater discharge coefficients. Analysis of 2007 input-output data of 30 sectors of the Chinese economy and of 30 provincial regions of China indicates that by lowering their direct input coefficients, the manufacturers of textiles, paper and paper products, chemical products, smelting and metal pressing, telecommunication equipment, computers and other electronic equipment will significantly reduce their amounts of industrial wastewater discharge. By lowering intra-provincial direct input coefficients to industrial sectors themselves of Jiangsu, Shandong and Zhejiang, there will be a significant reduction in industrial wastewater discharge for the country as a whole. Investment in production technology and improvement in organizational efficiency in these sectors and in these provinces can help lessen the direct input coefficients, thereby effectively achieving a reduction in industrial wastewater discharge in China via industrial restructuring.

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Ecosystem vulnerability in the Yellow River Basin (YRB) is a prominent concern. An in-depth exploration of net primary productivity (NPP) serves as an important aspect of assessing and protecting ecosystem health. We explored spatiotemporal changes and influencing factors of NPP in the YRB from 2000–2015, using a range of spatial analysis techniques, and cutting-edge computing-intensive variable importance decomposition methods. We found that NPP showed a fluctuating growth trend over time, ranging from 181.0–259.1 gC∙m ∙a , as well as a clear negative south-north spatial gradient. Significant spatial clustering patterns were observed, with Low-Low and High-High clusters being the dominant area classifications at grid cell, county, and city scales in the study area. We also found that NPP was statistically significantly affected by both natural factors (including climate and topography), and human activities, whilst meteorological factors were the most important factor and explained, on average, roughly 66% of the variability in NPP. Although the impact of human activities on NPP was relatively low when compared to natural factors, the former tended to increase with time and accounted for roughly 30% of the total variability explained by the model in 2015. Overall, this study provides an improved technical framework for undertaking a comprehensive analysis of the spatiotemporal pattern of NPP and its influencing factors at multiple-spatial scales.

Ecosystem vulnerability in the Yellow River Basin (YRB) is a prominent concern. Exploration vegetative net primary productivity (NPP) serve as an important aspect of assessing and protecting ecosystem health. We used a range of spatial analysis techniques, residual trend analysis, and the cutting-edge computing-intensive variable importance decomposition method to explore spatiotemporal changes and influencing factors for vegetative NPP in the YRB from 2000–2015. The results found that NPP showed a fluctuating growth trend over time, ranging from 165.9–227.7 gC∙m-2∙a-1, as well as a clear negative south-north spatial gradient. Significant spatial agglomeration pattern was observed, with Low-Low and High-High clusters being the dominated area classifications at both scales of grid cells, counties and cities in the study area. Foremost, we found that NPP was statistically significantly affected by both natural factors, including climate and topography, and human activities, whilst precipitation accounts for the most important factor, explaining roughly 42% of the variability in NPP on average. Although the impact of human activities on NPP was relatively low, human activities tended to promote NPP on average, mainly due to the implementation of the ecological restoration project in the region, such as the Forest Protection and Grain for Green Project. Overall, this study provides an improved technical framework for a comprehensive analysis of spatiotemporal pattern of vegetative NPP and its influencing factors at multiple-spatial scales.