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Abstract: Green GDP is an effective economic indicator of urban environmental management. This paper introduces a new method of accounting Green GDP, which puts the value of direct ecosystem services into GDP. Direct ecosystem services are weighted by their virtual prices and aggregated in the same way as market goods and services in GDP. They are components of nature, directly enjoyed, consumed, or used to yield human well-being. They belong to ecosystem services. In order to choose direct ecosystem services reasonably, two principles are put forward. That is, when calculating the value of ecosystem services for Green GDP, the differences between services for human beings and services for other living beings must be considered. And the green GDP of Wuyishan city of China is accounted, considering the direct ecological services value of urban ecosystem as environmental benefit. The results show that the value of direct ecosystem services in Wuyishan City in 2005 has reached 2.3 billion yuan RMB, and the green GDP is 15.3 billion yuan RMB. [ABSTRACT FROM AUTHOR]

The urbanization process has seen an accelerated increase in recent decades, leading to urban runoff pollution becoming more prominent. However, uncertainty of the pollution output and complexity of management systems have made controlling urban runoff pollution challenging. Therefore, it is necessary to propose advanced modeling methods for these challenges. This research presents an integrated urban runoff pollution management (IURPM) model for optimal configuration of low impact development (LID) practices under multiple uncertainties. The IURPM model combines the hybrid land-use prediction and improved pollution estimation models with interval parameter, stochastic parameter, and multi-objective programming. The proposed IURPM model can not only predict the output characteristics, but also provide optimal configuration schemes for the LID practices in the management of urban runoff pollution under multiple scenarios. In addition, uncertainties expressed as discrete intervals and probability density function in the management systems can be effectively addressed. A case study of the IURPM model was conducted in Dongguan City, South China. Results show that considerable amounts of urban runoff pollutants would export from Dongguan City by 2025. The export loads and pollution output flux per unit area would have significant spatial heterogeneity. The results further indicate that population size, gross domestic product, and regional area size are expected to play important roles in the pollution export, while impervious surface coverage and population density would likely have great influences on the output flux of urban runoff pollution. Based on the model findings, multiple LID practices should be adopted in Dongguan City to reduce the urban runoff pollution loads. Using the IURPM model, multiple LID implementation schemes can be obtained under different pollution reduction scenarios and significance levels, that can provide decision-making support for urban water environmental management, considering variations in the policymaker's decision-making preferences. This study demonstrates that the IURPM model can be applied to the optimal configuration of LID practices for the management of urban runoff pollution under uncertainty. • An integrated urban runoff pollution management model was proposed. • The model can predict the loads of urban runoff pollution. • The model can provide optimal configuration schemes of low impact development practices. • Interval and stochastic uncertainties in urban runoff pollution systems can be handled. [ABSTRACT FROM AUTHOR]