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Abstract China's household energy demands' life-cycle water uses from 2002 to 2015 are quantified with an Input-Output analysis disaggregating rural and urban impacts. 9.73 and 1.60 km3 of water was withdrawn and consumed respectively in the life cycle of Chinese household energy demands in 2015, which was dominated by power and heat uses. An average urbanite's household energy uses, including coal, gas, petroleum products, power and heat, require about four times of life-cycle water uses than its rural counterpart. Among all upstream sectors, while agricultural sectors accounted for the largest shares for all energy uses, oil and gas extraction made significant contributions to petroleum products and gas consumption. A Structural Decomposition Analysis is conducted to disentangle the impacts of four driving factors, i.e. population, demand, economic structure and technology. Population change reduced energy consumption's life-cycle water use for rural households but increased that for urban households. Each economic sector's water intensity decreases, which represent technology advancement, played the dominant role curbing household energy consumption's life-cycle water uses. While power and heat dominates the household energy use profile, urbanization is accompanied by household consumption shifting from coal to gas and petroleum products. In order to reduce household energy consumption's impacts and reliance on water resources, it is imperative to reduce energy production's water use by adopting water-saving technologies, such as air cooling, as well as to reduce upstream sectors' water intensities, such as by promoting drip irrigation. Highlights • Household energy demands' life cycle withdrew 9.73 km3 of water in 2015. • Urban households' energy demands use 4 time water than rural ones. • Agriculture contributed the most to final energy demands' upstream water uses. • Technology has offset the most water uses for household energy demands. [ABSTRACT FROM AUTHOR]

Electricity demand in megacities may exert substantial stress on water resources, which is often expressed through the water scarcity footprint for electricity consumption (WSFE). Conversely, water scarcity may constrain electricity production, leading to increased vulnerability for megacities electricity production. The WSFE and the water related vulnerability of electricity production reflect two aspects of water-electricity conflict. This varies over time by both the amount and location of electricity production. However, no studies have conducted time-series analysis to evaluate the trends of these two indicators, both in terms of severity and spatial characteristics. Our study focused on evaluating trends in water-electricity conflict both within and beyond megacity administrative boundaries. China's four provincial-level megacities, i.e. Beijing, Tianjin, Shanghai and Chongqing, were chosen as case studies. The results show that water related vulnerability of electricity production in Tianjin, Beijing, Shanghai and Chongqing was diverse and can be classified as extreme, severe, moderate and minor, respectively. Between 2006 and 2016, the WSFE of Tianjin experienced an increasing trend, and its water related vulnerability of electricity production remained at the highest level. Beijing's WSFE has decreased, but its water related vulnerability of electricity production has increased. These differing trends highlight the need for joint reductions to both WSFE and water related vulnerability of electricity production in mitigating water-electricity conflict. [Display omitted] • Water related vulnerability of electricity production was dynamic during 2006–2016. • Water related vulnerability in four Chinese megacities was diverse. • Tianjin had the highest water related vulnerability and water scarcity footprint. • The external water scarcity footprint of Beijing was the largest, but decreasing. • Changes in water related vulnerability may differ to water scarcity footprint. [ABSTRACT FROM AUTHOR]

Eutrophication is a global challenge, which is exemplified by the tremendous efforts but little results in restoring the sixth largest and also one of the most eutrophic freshwater lakes in China, Lake Dianchi. Considering large parametric uncertainties in water quality modeling, the traditionally used deterministic water quality model is expanded to a probabilistic model to explore the Lake Dianchi's potential responses to different levels of pollutant load reductions. The results show that, given the long pollution history and severe pollution state in Lake Dianchi, a minimum pollution load reduction by half (base year 2003) is required to maintain the water quality state as it is now in 40 years. At least a 60% nutrient load reduction is required to generate any likelihood of water quality improvement, however, the system stabilizes quickly after about 10 years, which may explain why tremendous investments have generated little results. 80% of nutrient load reduction for 40 years has 95% probability of meeting the TN target but only a below 50% (45%) probability in meeting the TP target, and even less to meet water quality target for Chla. The feasibility of ever reaching the Chinese drinking water standards for total phosphorous and total nitrogen is questionable. • An uncertainty-based probabilistic model explores potential policy responses in Lake Dianchi. • 50% pollutant reduction is required to maintain the water quality state as it is now in 40 years. • At least 60% pollutant load reduction is required to achieve water quality improvement. • System stabilizes with 60% pollutant reduction in about 10 years. • 80% pollutant load reduction from land-based sources may still fail to meet target for Chla. [ABSTRACT FROM AUTHOR]

Plastic is one commonly used polymer material to support our daily lives. However, once the plastic waste enters the environment, it slowly degrades, which causes long-term and deep ecological environmental problems. As the world's largest plastic producer and consumer, China generated around 26.74 million tons of plastic waste in 2019, and has made ambitious policies to cope with the plastic waste issues. This study predicts the generation trends and management costs of plastic waste in China from 2020 to 2035 under three different scenarios (Business as usual-BAU, Current policy scenario -CPS, and Target policy scenario-TPS), in which China is divided into three regions for specific policy implications. In addition, the scenario analysis and Monte Carlo simulations are used to obtain confidence interval of assessments. The results show that the plastic waste emission will be 34.82 million tons under BAU, 13.49 million tons under CPS and 2.63 million tons under TPS in 2035, respectively, and there will be significant changes in regional contributions in plastic waste emission (e.g., Eastern region: 45.7% to 9.7%; Central region:25.2% to 30.9%; Western region: 29.1% to 59.4% from 2019 to 2035 under TPS). In addition, the environmental and economic benefits increase with the rigor of plastic waste management policy as there will generate a net income of US$3.01 billion under TPS compared to the cost of US$ 2.61 billion under BAU and US$120 million under CPS. In view of this, it is vital that China develop appropriate plastic management policies based on the status of various regions, attempt to achieve economic development while reducing plastic waste emissions, and finally achieving a "win-win" situation of economy and environment. • Scenario analysis was used to predict plastic waste emissions of China. • The net economic cost of plastic waste management in China was predicted. • Different plastic waste policy interventions derived on regional variations. • Stronger policy interventions can help reduce plastic waste emissions. • China needs extraordinary efforts to achieve the goal of reducing plastic waste. [ABSTRACT FROM AUTHOR]

Electricity transmissions have been utilized in China to balance its spatially mismatched development needs and natural resources endowments. However, it has led to spatial shifts of negative environmental impacts induced by electricity generations, including water consumption and carbon emissions. This study calculates that, from 2010 to 2016, carbon emissions and water consumption to produce the transmitted electricity have grown from 507 Mt and 2.7 km3 respectively to 642 Mt and 6.5 km3. Applying a structural decomposition model coupled with a Quasi-Input-Output model to quantify the driving factors of such increases, we find that GDP increase has played the dominant role in driving the increase of both factors. Our results also highlight the potential conflicts between carbon reduction and water conservation in developing future electricity transmission infrastructure systems. Changing the electric power sector's energy portfolio and the transmission structure by increasingly utilizing hydropower productions have both contributed to national total carbon emissions reductions, but at the expenses of increased national water consumption. As a result, on a national level, in 2016, due to the inter-provincial differences in energy portfolios and technologies, electricity transmissions have led to 155.27 Mt of net carbon reduction and 3.4 km³ of additional net water consumption compared to the counterfactual scenario where no electricity transmission were facilitated. The future expansion of electricity transmission network needs to consider such trade-offs, particularly within the contexts of global climate change mitigation and emergent challenges posed by water stresses. Image 1 • Carbon emitted and water consumed for China's power transmission have increased. • 642 Mt carbon emitted and 6.5 km³ water consumed for China's power transfers in 2016. • Changing generation and transmission structures reduce carbon but increase water. • Power transmissions led to 155.27 Mt of national net carbon reduction in 2016. • Power transmissions led to 3.4 km³ of national net water consumption increase. [ABSTRACT FROM AUTHOR]