Multi-dimensional diagnosis model for the sustainable development of regions facing water scarcity problem: A case study for Guangdong, China

Water Footprint Analysis Under Dual Pressures of Carbon Mitigation and Trade Barrier: A CGE‐Based Study for Yangtze River Economic Belt

“…In detail, based on the national water quality standard (GB 8978–1996), is the following pollutants are investigated: chemical oxygen demand (COD), ammonia nitrogen (NH 3 ‐N), phosphorus (P), petroleum pollutants (PP), volatile phenol (V‐ArOH), cyanide, mercury (Hg), cadmium (Cd), chromium (Cr), lead (Pb), and arsenic (As). The detailed blue/gray water can be calculated as follows: $$$b{w}_{i}=f{w}_{i}-w{d}_{i}$$$ $$$g{w}_{i}=\mathrm{max}\left(\frac{{l}_{p,i}}{{C}_{max}-{C}_{nat}}\right)$$$ where $$b{w}_{i}$$ (tonne) and $$g{w}_{i}$$ (tonne) are blue and gray WFs of sector $$i$$, respectively; $${l}_{p,i}$$ (tonne/year) is the total amount of pollutant $$p$$ discharged by sector $$i$$; $${C}_{max}$$ (tonne/10 3 m 3 ) is the concentrations of pollutant $$p$$ based on the Grade III Wastewater Discharge Standard (i.e., GB 8978–1,996); $${C}_{nat}$$ (tonne/10 3 m 3 ) is the natural concentration of pollutant $$p$$ in the receiving water (Aldaya, 2012; He et al., 2020).…”

“…where (Aldaya, 2012;He et al, 2020). Second, the WF of consumption (or consumption-based WF) and virtual water (the amount of water embedded in commodities) (Allan, 1998) are analyzed through the development of a modified MRIO table.…”

Assessing the “negative effect” and “positive effect” of COVID-19 in China

“…Recent researchers modified traditional HEM by using vertical Integrated Processes and established GHEM, which is widely used in the analysis of water resource utilization ( Deng et al, 2018 ; He et al, 2020 ), energy consumption ( Dietzenbacher et al, 2019 ) and pollution emission ( Sajid et al, 2019 ; Zhang, L. et al, 2020) of various industries in the economic system. However, GHEM does not solve the problem of improper use of analytical assumptions in the process of assumption elimination, which leads to various deviations in the industrial linkage measurement results and economic interpretation.…”

The Spatial-Temporal Matching Characteristics of Water Resources and Socio-Economic Development Factors: A Case Study of Guangdong Province

“…The spatial distribution of matching characteristics, pressure, and inequality between water elements and socio-economic parameters can provide valuable advice on the allocation and management of water resources, which would then promote the water-related SDGs (SDGs 1, 2, 3, 6, and 8), sustainable cities and communities SDGs (SDGs 11), and SDGs related to ecosystems, biodiversity, and mitigating the impacts of climate change (SDG 13, SDG 14, and SDG 15). Apart from the mismatch of water and socio-economic parameters, Guangdong has been suffering from severe water scarcity and pollution [25,26]. In general, the water resources security situation is relatively severe in the relatively developed core area of the Pearl River Delta, as well as the eastern and western coastal areas of Guangdong.…”