Evaluation of industrial water use efficiency considering pollutant discharge in China.

Problems in estimating self-supplied industrial water use by indirect methods, the California example

Improving water utilization efficiency can effectively alleviate the contradiction between water shortage and water demand in the process of rapid urbanization. The middle and lower reaches of the Yellow River Basin, China, are characterized by water shortage. In order to improve water use efficiency, taking the 43 prefecture-level units in this region as the study area, industrial and agricultural water use efficiency is calculated based on the undesired SBM-DEA model. Then, the Tobit model is used to explore their influencing factors. The results show that the regional average agricultural water use efficiency is greater than the industrial water use efficiency. The temporal trend indicates that the agricultural water use efficiency shows a fluctuating upward trend, while industrial water use efficiency has a fluctuating downward trend. The gravity center of industrial water use efficiency moves from northwest to southeast in a “Z” shape, while the gravity center of agricultural water use efficiency moves westward as a whole. From the perspective of spatial patterns, the standard deviation ellipse of industrial water use efficiency shows that the industrial water use efficiency is higher in the east–west direction, while the agricultural water use efficiency is higher in the northwest–southeast direction. The improvement of urbanization level is conducive to the improvement of industrial water use efficiency; however, the development of urbanization has a significant inhibitory effect on improving agricultural water use efficiency.

Regional differences in the industrial water use efficiency of China: The spatial spillover effect and relevant factors

Low industrial water use efficiency has become a resource bottleneck to industrial development in China. The SBM-undesirable and meta-frontier models were used in combination with empirical data in 30 provinces in mainland China (Tibet excluded due to data missing from 1999 to 2013), to compare industrial water use efficiency in mainland China under meta-frontier and group-frontier, and explore the influencing factors. The empirical results of the study reveal that: (a) there is a large difference in the industrial water use efficiency between meta-frontier and group-frontier in mainland China, due to the heterogeneity in the levels of industrial water use technology; (b) given the low recycle rate of polluted industrial water, there is room for improvement in the industrial water use efficiency in the 30 provinces in mainland China. Further, the study finds that the current price of industrial water is distorted to some extent, failing to coordinate with the use of water resources. Policy implications indicate that industrial water use efficiency is not only related to technological heterogeneity in different regions, but also the control and treatment of industrial water pollution. Therefore, the current price of industrial water should be gradually raised. A scalar water pricing system as residential water could also be applied to industrial water.

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.

Carbon mitigation strategies have been developed without sufficient consideration of their impacts on the water system. Here, our study evaluates whether carbon mitigation strategies would decrease or increase local industrial water use and water-related pollutants discharge by using a computable general equilibrium (CGE) model coupled with a water withdrawals and pollutants discharge module in Shenzhen, the fourth largest city in China. To fulfill China's Nationally Determined Contributions (NDC) targets, Shenzhen's GDP and welfare losses are projected to be 1.6% and 5.6% in 2030, respectively. The carbon abatement cost will increase from 56 USD/t CO2 in 2020 to 274 USD/t CO2 in 2030. The results reveal that carbon mitigation accelerates local industrial structure upgrading by restricting carbon-, energy-, and water-intensive industries, e.g., natural gas mining, nonmetal, agriculture, food production, and textile sectors. Accordingly, carbon mitigation improves energy use efficiency and decreases 55% of primary energy use in 2030. Meanwhile, it reduces 4% of total industrial water use and 2.2-2.4% of two major pollutants discharge, i.e., CODCr and NH3-N. Carbon mitigation can also decrease petroleum (2.2%) and V-ArOH (0.8%) discharge but has negative impacts on most heavy metal(loid)s pollutants discharge (increased by -0.01% to 4.6%). These negative impacts are evaluated to be negligible on the environment. This study highlights the importance of considering the energy-water nexus for better-coordinated energy and water resources management at local and national levels.

Drivers of industrial water use during 2003–2012 in Tianjin, China: A structural decomposition analysis

S team systems are a ubiquitous element in nearly every type of manufacturing plant. In the United States, steam systems are the single largest consumer of energy in the industrial sector, where they account for 37% of annual onsite energy use. Steam use is particularly prominent in the chemicals, paper, petroleum refining, and food and beverage industries, where it is used in a wide range of processes, including reforming, distillation, concentration, cooking, and drying. Together, these four industries comprise nearly 90% of U.S. industrial steam demand, with chemicals manufacturing (30%) and paper manufacturing (30%) holding the largest shares. At the national level, industrial steam systems account for around 6% of U.S. total primary energy use, or 5,900 trillion British thermal units (TBtu). As such, much attention has been paid to steam system energy efficiency improvements as part of corporate, utility, and government energy and air pollution initiatives. Key incentives include local utility rebates, tax incentives, and lowor no-cost steam system energy efficiency audits. Steam system energy efficiency not only makes sense from an environmental perspective, but also from an economic perspective. As of 2006, U.S. manufacturers spent $21 billion on externally purchased boiler fuels. The actual price tag of industrial steam is likely much higher; nearly one-half of U.S. boiler fuels are self-generated within plants in the form of waste gas, black liquor, wood wastes, and other byproducts. These byproduct fuels are not free, as they are generated from purchased materials and typically require further processing for efficient combustion. Reducing demand for boiler fuels can, therefore, help reduce operating costs and improve profit margins. While clearly justified, the historical focus on reducing energy use has overlooked an increasingly compelling benefit of steam system efficiency: namely, reduced water use. Compared to the many public and private incentives for industrial energy efficiency, there are surprisingly few external incentives for industrial water efficiency. One key barrier to such incentives is the lack of credible data on industrial water use, which, unlike data on energy use, are not compiled at the manufacturing industry or process level in regular national surveys. This dearth of data contributes to a general lack of awareness of the sources and scale of industrial water use within the engineering and policy communities, which limits broader attention to water efficiency beyond the plant floor. Another barrier to steam system water efficiency is that the cost of boiler water—and the associated chemicals required for its treatment—typically only represents a small fraction of boiler operating costs, which are dominated by the costs of fuel. However, as we discuss in this Perspective, U.S. industrial steam systems consume copious amount of water. It follows that steam systems are worth a closer look as a manufacturing water efficiency target. Several current trends suggest that water efficiency will play an increasingly prominent role in the financial and sustainability plans of U.S. manufacturers. Recent water stress due to droughts and rising water infrastructure costs have led to increased public water rates around the country. These conditions may worsen with a changing climate. An increasing number of manufacturers are reporting water use as an important environmental indicator in annual corporate sustainability reports, which raises both public awareness of and accountability for water efficiency. Many manufacturers are also being asked by their corporate customers for environmental “footprint” data as part of large-scale sustainable Correspondence concerning this article should be addressed to E. Masanet at eric.masanet@northwestern.edu; M.E. Walker at mwalker9@hawk.iit.edu.

Decomposition methods for analyzing changes of industrial water use

Population growth and economic development are the two major driving forces of water demand. In developing countries, the rapid population growth together with an eagerness to develop the national economy, typically through industrialization, has generated a strong demand for additional water. This situation has been the basis underlying many projections of a substantial expansion of industrial water use. While the increase in industrial water use is a trend evident in many countries, it is also observed that industrial water use in some developed countries has experienced an increase, level-off and then decrease with the economic development and income rises. This inverted U-shaped trend resembles the well-known Environmental Kuznets Curve (EKC). Prior to this study, however, there has been no systematic investigation into changes in industrial water use associated with the process of industrialization. This paper investigates the existence of the Kuznets curve in industrial water use. It focuses on the following questions: does an inverted U-shaped relationship generally exist between industrial water use and the level of income? If so, where is the turning point of industrial water use? And, what are the preconditions for the decline? Based on the results from the analysis of the OECD countries, preliminary discussion is made for developing countries on the scale of potential increment in industrial water use before reaching the turning point. A standard EKC model is expressed as a quadratic function of the level of income (Eq. 1). We apply this model to statistically verify the Kuznets curve relationship between industrial water use and income observed in the OECD countries. tttot eYaYaaIW +++=

Decomposition of industrial water use from 2003 to 2012 in Tianjin, China

Achieving carbon neutrality enables China to attain its industrial water-use target

京津冀城市群用水效率及其与城市化水平的关系

根据2003年至2014年景德镇市农业、工业、生活、生态环境等行业的用水量资料，分析景德镇市近12年来行业用水的变化发展，结合SPSS统计软件对引起行业用水变化的主要驱动力因子进行分析和说明。结果表明：景德镇市的水资源利用以农业用水为主，占用水总量的50.6%，工业用水占用水总量的34.5%，比重相对较大，生活用水和生态环境用水所占用水总量的比重较小，分别为13.9%和1.0%；景德镇市用水总量基本稳定，无整体上升或下降趋势，农业用水量及其所占用水总量的比重呈现整体上升的趋势，工业用水量及其所占用水总量的比重呈现出先上升而后下降的趋势，生活用水量及其所占用水总量的比重近10年来呈现逐年攀升的趋势，生态环境用水量及其所占用水总量的比重呈现略微上升的态势；因子分析的结果显示人口因素、经济发展因素和农田灌溉因素是景德镇市行业用水演变的主要驱动力。 According to the agricultural, industrial, life, public and ecological environment water use data of Jing-dezhen city from 2003 to 2014, the paper analyzes the change of water use in various industries in Jing-dezhen city during the last 12 years, and analyzes and explains the main driving factors of the develop-ment of water use in various industries by using SPSS statistical software. The results show that the water resources utilization in Jingdezhen city is mainly agricultural water use, which accounts for 50.6% of the total amount; the proportion of industrial water use is relatively larger, which accounts for 34.5% of the total amount; the proportion of water used for life, public and ecological environment is small, which accounts for 13.9% and 1.0% of the total amount. The total amount of water use in Jingdezhen is basically stable, and there is no overall rise or fall, agricultural water use, water use of the ecological environment are showing an overall upward trend and the proportion of total water use in agriculture and ecological environment is also increasing; industrial water use and its proportion of the total water use showed a trend of first increasing and then decreasing trend; water use for life and public and their proportion of the total water use in the past 10 years has been rising year by year. Factor analysis results show that the main driving force of the development of water use in various industries in Jingdezhen city is the population, economic development and farmland irrigation.

Water is a strategicand basic resource for industrial development.The efficient use of water resources is of great significance for the sustainable development of the economy and society. Dynamic SBM model could overcome the shortcomings of static models and reflect inter-temporal efficiency levels. The kernel density curve is used to fit the distribution pattern of industrial water use efficiency and describe its dynamic evolution. Empirical results show that from 2013 to 2017, under the meta-frontier, the industrial water use efficiency values of Beijing, Tianjin, Shandong, Inner Mongolia, and Shaanxi are all 1, and industrial water use efficiency is high, while the industrial water use efficiency values of Sichuan, Guizhou, Anhui, and other provinces are below 0.3, reflecting the low industrial water use efficiency. From 2013 to 2015, China's industrial water use efficiency generally shows a downward trend but begins to rise in the next 2 years. The kernel density curve generally exhibits a bimodal distribution trend and evolves from a "spike shape" to a "broad peak shape".