This paper presents a static computable general equilibrium model of the Chinese economy with water as an explicit factor of production. This model is used to assess the broad economic impact of a policy based on water demand management, using water tax charges as a policy-setting tool. It suggests that imposing water taxes can redistribute sectoral water use and lead to shifts in production, consumption, value added, and trade patterns. Another important finding is that water taxes imposed on the agricultural sector drive most of the effects.

This paper describes a multi-region computable general equilibrium model for analyzing the effectiveness of measures and policies for mitigating North China’s water scarcity with respect to three different groups of scenarios. The findings suggest that a reduction in groundwater use would negatively affect economic growth and household incomes. A planned water-transfer project would improve economic development and reduce the over-exploitation of local water resources, while water demand management policies would improve water-use efficiency through reallocating water to those sectors having a higher marginal product value. Several important policy implications are drawn from these findings.

Rapidly predicting and revealing the spatiotemporal characteristics and driving factors of land-use changes in carbon storage within megacities under different scenarios is crucial to achieving sustainable development. In this study, Jinan City (JNC) is taken as the study area, and the Markov-FLUS-InVEST model is utilized to predict and analyze the spatiotemporal variation in carbon storage in 2030 under three scenarios, namely, the natural development scenario (S1), the ecological conservation scenario (S2), and the economic development scenario (S3). The drivers of carbon storage changes were identified using an optimal parameter-based geographic detection (OPGD) model. The findings indicate that (1) land use from 2010 to 2018 shows a trend of continuous expansion of construction land and reduction in arable land. (2) The main types of carbon pools were cropland, forest, and grassland, accounting for more than 96% of the total amount. Carbon storage showed a decreasing trend from 2010 to 2018, and the main type of carbon pool that decreased was cropland. The center of gravity of carbon storage increases and decreases was located in the southern Lixia District, and the center of gravity of increase and decrease moved to the southwest by 3057.48 m and 1478.57 m, respectively. (3) From 2018 to 2030, the reductions in carbon stocks were 3.20 × 10⁶ t (S1), 2.60 × 10⁶ t (S2), and 4.26 × 10⁶ t (S3), and the carbon release was about 9 times (S1), 4 times (S2), and 10 times (S3) that of the carbon sink. (4) The contribution of slope (A2) ∩ nighttime light index (B6) and elevation (A1) ∩ nighttime light index (B6) to the regional heterogeneity of carbon stocks was the largest among the interaction drivers. To sum up, this study deepens the simulation of spatial and temporal dynamics of carbon storage under land-use changes in megacities and the related driving mechanism, which can provide the basis for scientific decision-making for cities to conduct territorial spatial planning and ecological protection and restoration.

The United Nations and scholars called for more attention and efforts for cleaner water and water sustainability. This study established a water sustainability evaluating method framework, including indicators, goals, and methods and performs provincial and city−level assessments as case studies. The framework involves six fields, surface water quality, marine environmental quality, water−soil−agriculture, water infrastructure, water conservation, aquatic ecology, water−efficient use, and pollutant emission reduction. The methods innovatively integrate multi fields and concerns of water sustainability while providing a goal−oriented evaluation and implementing the United Nations’ call for the refinement and clarification of SDGs. China’s overall water sustainability was evaluated as 0.821 in 2021, and have performed well in surface water quality, sea quality, water conservation, and aquatic ecology fields while performing poorly in the water−soil−agriculture field. The overall strategy, policy, and action for water sustainability could be developed based on the evaluation. The water sustainability evaluation presented the regional and field/indicator differentiations. It is necessary to implement regionally classified policies and differentiated management for sustainable water development. The correlation analysis with socioeconomic factors implies the complicated and intimate interaction between socioeconomic development and water sustainability while revealing that development stages and the inherent conditions of natural ecology and water sources bring about the differentiations. A comprehensive evaluation of water sustainability may be three−dimensional, involving water quality and ecology, development related to water, and water resources and utilization.