Water footprint of Jing-Jin-Ji urban agglomeration in China

Zhao, Dandan; Tang, Yu; Liu, Junguo; Tillotson, Martin R.

doi:10.1016/j.jclepro.2017.07.012

Cited by 97 publications

(44 citation statements)

References 29 publications

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“…The average annual water resource per capita for Beijing and Tianjin is only approximately 120 m 3 /year/capita and that for Hebei is about 160 m 3 /year/capita [24]. With increasing water demand and water pollution, the water environment is getting worse in terms of incremental groundwater depletion, river dry-ups, and degradation of wetland [34].…”

Section: Study Areamentioning

confidence: 99%

Impacts of Land-Use and Land-Cover Changes on Water Yield: A Case Study in Jing-Jin-Ji, China

Yang

Lacayo

et al. 2018

Sustainability

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Knowing the impact of land-use and land-cover (LULC) changes on the distribution of water yield (WY) is essential for water resource management. Using the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model, we investigated the spatial-temporal variations of WY from 1990 to 2015 in China's northern semi-arid region of Beijing-Tianjin-Hebei (Jing-Jin-Ji). We quantified the combined effects of LULC dynamics and climatic variation on WY. Furthermore, we identified the relative contribution of main LULC types to WY. For our study region, the built-up area increased by 35.66% (5380 km 2) during the study period. In the meantime, cropland, grassland, and wetland decreased continuously. The expansion of built-up area and decline of vegetated land led to an increase of 1047 million m 3 (5.1%) in total WY. The impacts of LULC changes on WY were mainly determined by the biophysical characteristics of LULC composition. Vegetated land has relatively lower WY coefficients due to higher rates of evapotranspiration and water infiltration. Built-up areas and bare land have higher WY coefficients as a result of their impermeable surface. The spatial-temporal analysis of WY with specification of WY coefficients by LULC types can facilitate integrated land-use planning and water resource management.

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Section: Study Areamentioning

confidence: 99%

Impacts of Land-Use and Land-Cover Changes on Water Yield: A Case Study in Jing-Jin-Ji, China

Yang

Lacayo

et al. 2018

Sustainability

Self Cite

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“…The rapid progress of urbanization and industrialization has resulted in substantial burgeons on energy production and the environment. The Beijing-Tianjin-Hebei region also experiences some of the most extreme water shortages and air and water pollution in the country [38,39]. possibilities for identifying the internal structure of urban land use and promoting efficient environmental risk management.…”

Section: Study Areamentioning

confidence: 99%

Identification of Industrial Land Parcels and Its Implications for Environmental Risk Management in the Beijing–Tianjin–Hebei Urban Agglomeration

et al. 2019

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Due to rapid, sprawling urban and industrial development, urbanization in China has led to serious environmental pollution with subsequent risks to human well-being. Landscapes comprised of intermingled residential and industrial areas are common across China, which is a large challenge for effective urban planning and environmental protection. Being able to identify industrial land across the urban landscape is critical for understanding patterns of urban design and subsequent consequences for the environment. Here, we describe a method to quickly identify industrial parcels using points of interest (POIs) and large-scale spatial data. We used the Beijing–Tianjin–Hebei urban agglomeration as a case study and identified 8325 square kilometers of industrial land, accounting for 30.7% of the total built land. Based on ground-truth randomly-sampled sites, the accuracy, precision, and recall of identified industrial areas were 87.1%, 66.4%, and 68.1%, respectively. Furthermore, we found that over 350 km2 of the industrial parcels were high human settlement risks and mainly were distributed in Tianjin and Tangshan city. Over 28.8% of the identified industrial land parcels might be at the risk of potential soil contamination. The results can be helpful in future urban planning and for identifying urban areas that are targets for implementing environmental risk management and remediation.

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“…Liu et al, 2008;Novo et al, 2009) and sub-national level (e.g. Guan and Hubacek, 2007;Ma et al, 2006;Verma et al, 2009;Dalin et al, 2014;Zhao et al, 2015;Zhuo et al, 2016a;Zhao et al, 2017). There are also several studies that analyse VW flows associated with trade in animal products (TS2) Ma et al, 2006;Dalin et al, 2014;Hanasaki et al, 2010), but the VW flows related to TS1 and TS2 are never connected.…”

Section: Introductionmentioning

confidence: 99%

Water for maize for pigs for pork: an analysis of inter-provincial trade in China

Zhuo

Liu

Yang

et al. 2020

Preprint

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a b s t r a c tTrade in commodities implies trade in virtual water (VW), which refers to the water that was used to produce the traded goods. Various studies have quantified international or inter-provincial virtual water (VW) flows related to the trade in crops and animal products. Until date, however, no effort has been undertaken to understand how the water embodied in traded feed crops (trade stage TS1) will be transferred further because of trade in animal products (trade stage TS2). This is the first study showing this mechanism, in a case study in China for maize (the major pig feed) and pork (the dominant meat), considering the period 2000e2013. We estimate the annual green and blue water footprints in maize production and then quantify the inter-provincial VW flows related to trade in maize (TS1) and trade in maize embodied in pork (TS2). Results show that in TS1, maize-related VW flowed from the water-scarce North to the water-rich South, with an increase of 40% over the study period (from 43 to 61 billion m 3 y À1 ). In TS2, about 10% of the water embodied in maize exports from North to South China returns in the form of pork, with an increase in the absolute amount of 25% (from 4.8 to 6.1 billion m 3 y À1 ). Considering blue VW flows specifically, we find that North-to-South blue VW flows decreased by 5% in TS1, while South-to-North blue VW flows increased by 23% in TS2.

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Water footprint of Jing-Jin-Ji urban agglomeration in China

Cited by 97 publications

References 29 publications

Impacts of Land-Use and Land-Cover Changes on Water Yield: A Case Study in Jing-Jin-Ji, China

Impacts of Land-Use and Land-Cover Changes on Water Yield: A Case Study in Jing-Jin-Ji, China

Identification of Industrial Land Parcels and Its Implications for Environmental Risk Management in the Beijing–Tianjin–Hebei Urban Agglomeration

Water for maize for pigs for pork: an analysis of inter-provincial trade in China

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