Ecological risk assessment from the viewpoint of surface water pollution in Xiamen City, China

ABSTRACT

The ecological security of urban surface water is subject to significant risk due to rapid urbanization. Pollutant discharge and accumulation are among the most critical stressors endangering urban surface water and affecting the normal operation of urban aquatic ecosystem services. In this study, we assessed how pollutant accumulation stresses water purification systems, which perform important urban ecosystem services. First, we applied a water environmental capacity model to calculate thresholds of urban surface water environmental capacity under a given water quality target. Second, based on a stepwise regression method, an equation was used to describe the relationship between stressor factors (pollutant accumulation) and measurable socioeconomic indicators. Third, an ecological risk index was used as an assessment endpoint indicator to assess the negative ecological effect of pollutant accumulation. Finally, risk level was classified according to the risk quotient method. Taking Xiamen City as an example, we analyzed the contribution of different sources of pollutants and evaluated the urban ecological risk posed by two major contaminants present in the environment by measuring chemical oxygen demand (COD) and ammonium nitrogen (NH₄⁺-N). The results show that the ecological risk indexes of both COD and NH₄⁺-N are expected to decrease from 2020 to 2030; that of COD is expected to fall from medium to low, whereas that of NH₄⁺-N is expected to fall from high to medium. These findings demonstrate that the ecological risk posed to the surface water in Xiamen City can be reduced by controlling population growth, optimizing industrial structure, and promoting economic development.

KEYWORDS:

• Urban ecological risk
• water purification
• pollutant accumulation
• water environmental capacity
• risk quotient model
• ecological risk index

Acknowledgements

This work was supported by the National Key R&D Program of China (2017YFF0207303), the National Natural Science Foundation of China (71533003) and the National Key R&D Program of China (2016YFC0502902).

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported by the National Natural Science Foundation of China [71533003] and the National Key R&D Program of China [2016YFC0502902, 2017YFF0207303].