Contact
Jeffrey Wilson, School of Environment, Enterprise and Development
Introduction
Freshwater scarcity has become a major threat to sustainable development due to increasing demand caused by population growth, higher living standards, changing consumption patterns and the expansion of agriculture. In China, water resources are unevenly distributed both spatially and temporally, causing serious scarcity issues in some regions. In addition, urbanization and industrialization have caused serious water pollution issues. To date, water management studies and policy actions have focused more on the long-term supply of freshwater as opposed to addressing the impacts of water quality degradation.
The grey water footprint (GWF) is an indicator of the volume of water required to assimilate a pollutant load that reaches a water body and provides a tool to assess the sustainable, efficient and equitable use of water resources. This study applied the GWF to eight economic regions in China, while expanding its scope to include impacts associated with animal husbandry. In addition, the study included an assessment of background driving forces of respective GWFs and identified policy implications.
Methodology
Figure 1 shows the geographical, water resources and economic background information for the study area. In each economic region, the total GWF was computed by summing the respective footprints of primary, secondary and tertiary industries. Primary industry included GWFs estimated from farming and animal husbandry activities, with water quality impacts from farming mainly caused by fertilizer use and impacts from animal husbandry caused by animal wastes. The GWF from secondary industry was mainly caused by wastewater discharges, while the GWF from tertiary industry was caused by wastewater pollution from the service sector and domestic sources. The logarithmic mean division index method was used to explore the background mechanisms driving the GWFs calculated for different economic zones.
Data for the study was obtained from government sources, including the China Statistical Yearbook and China Environmental Statistics Yearbook. Study limitations include a reliance on nitrogen and chemical oxygen demand as appropriate indicators of water quality, ignoring other activity-related pollutants such as heavy metals. In addition, values for some parameters in the calculation do not account for regional differences due to the lack of specific georeferenced data.
Figure 1: Water resources and economic information for the study regions.
Outcomes
Figure 2 illustrates the calculated average GWF by economic zone in China from 2003 to 2015. Results show that, because of animal husbandry, primary industry contributed the most to the regional GWFs, particularly for the Northwest economic region. More specifically, the GWF of the less developed Northwest region was larger than of the more developed regions along the Southeast Coast due to more intensive farming and animal husbandry. The highest GWFs, however, were found in the Southwest region, followed closely by regions located in the middle of the Yangtze River and Yellow River, indicating that these regions should be the focus of GWF control. The results also indicated that the agricultural sector contributed the most to regional GWFs. Furthermore, the contribution from animal husbandry was shown to be much greater than crop farming (Figure 3). The tertiary sector was responsible for the second greatest contribution to the GWF, while the industrial sector contributed the least.
An analysis of driving forces behind the GWFs showed that the effects of economic scale and industrial structure played the most important role in explaining the GWFs for half of the regions (the East Coast, middle Yellow River, Northwest, and Southwest economic regions). The effects of economic scale and pollution intensity were key driving forces behind the GWF in the Northeast region. For the North Coast and middle Yangtze River regions, economic scale, industrial structure and pollution intensity were driving forces, while for the South Coast region, population, economic scale and industrial structure were important drivers.
Figure 2: Average grey water footprint by region over the time period 2003 to 2015.
Figure 3: Grey water footprint of primary industry by region (average over 2003 to 2015).
Conclusions
The GWF is an indicator of the amount of freshwater pollution associated with economic activities, making it a powerful information and decision-making tool for policy makers and those responsible for managing freshwater systems. This study assessed the GWF of eight economic regions in China and found that the primary sector (agriculture) dominated the estimated footprints, primarily because of the influence of animal husbandry activities. The analysis of underlying driving forces showed that the GWFs were mainly impacted regionally by the scale of the economic activities, the economic structure, pollution intensity and population density.
The results of this study aim to support water managers and policy makers in China to focus their efforts on effective measures that control or mitigate the impacts of activities that cause significant GWF impacts in the analyzed regions. This includes, for example, best management practices for fertilizer use or livestock runoff control, or upgrading wastewater treatment technologies. In addition, economic planners might use the GWF to assess industrial structures and economic scales for specific regions against alternative scenarios that might lessen the GWF by moving to more water efficient and less pollution intensive activities.
Cui, S., Dong, H. & Wilson, J. (2020). Grey water footprint evaluation and driving force analysis of eight economic regions in China. Environmental Science and Pollution Research, 27, 20380-20391. doi:10.1007/s11356-020-08450-8
For more information about WaterResearch, contact Allie Dusome.
