Your search found 3 records
1 Lv, C.; Jue, Y.; Guo, X.; Ling, M.; Yan, D. 2022. Research on quantification method of water pollution ecological environment losses. AQUA - Water Infrastructure, Ecosystems and Society, 71(6):709-721. [doi: https://doi.org/10.2166/aqua.2022.002]
Water pollution ; Ecological factors ; Environmental factors ; Ecosystem services ; Energy ; Water resources ; Groundwater pollution ; Water quality ; Soil pollution ; Biodiversity ; Models / China / Henan / Kaifeng
(Location: IWMI HQ Call no: e-copy only Record No: H051264)
https://iwaponline.com/aqua/article-pdf/71/6/709/1065275/jws0710709.pdf
https://vlibrary.iwmi.org/pdf/H051264.pdf
https://vlibrary.iwmi.org/pdf/H051264.pdf
(0.75 MB) (764 KB)
Economic and social development have worsened the situation of water pollution and even the ecological environment. It is helpful to quantify the water pollution ecological environment losses for decision-makers to formulate reasonable pollution control plans. However, the current quantitative analyses led by economic methods are not comprehensive and systematic. Therefore, based on the emergy theory and method system of eco-economics, this study analyzed the internal energy flow process of the water-polluted ecosystem, discussed the composition of water-polluted ecological environment loss, and proposed a quantitative model of water-polluted ecological environment loss based on the emergy analysis method. It can reasonably quantify the ecological environment loss caused by water pollution and provide a reference for optimizing regional industrial layout, scientifically formulating pollution control planning, and promoting the sustainable development of the ecosystem. Taking Kaifeng City in Henan Province as an example, the rationality of the model is verified. The results show that the annual average total energy value of water pollution ecological environment loss in Kaifeng City is 3.83 × 1020sej, equivalent to 145 million yuan (0.76) of Kaifeng's gross domestic product (GDP) in 2018.
2 Yan, H.; Yang, H.; Guo, X.; Zhao, S.; Jiang, Q. 2022. Payments for ecosystem services as an essential approach to improving ecosystem services: a review. Ecological Economics, 201:107591. (Online first) [doi: https://doi.org/10.1016/j.ecolecon.2022.107591]
Payments for ecosystem services ; Land rent ; Land use ; Land rights ; Estimation ; Economic aspects ; Stakeholders
(Location: IWMI HQ Call no: e-copy only Record No: H051350)
(0.69 MB)
There remain considerable controversies over payments for ecosystem services (PES) as an essential approach to improving ecosystem services. This study reviewed various definitions of PES and explored its economic nature; then explored previous methods for estimating the PES standard and finally proposed possible agendas for future PES research. Results suggested the PES and traditional land rent both originate from the monopoly of the providers on use rights of land vital to provision of certain ecosystem services, therefore PES should be redefined as a special kind of land rent for sharing land use rights of the providers to guarantee sustainable provision of certain ecosystem services. Besides, there has been no universal methods for estimating the rational PES standard due to insufficient understanding of the economic cause and nature of the PES. Re-imagining and re-designing PES as a system of land rights is advantageous to clearing up misunderstanding and disputes over the economic cause and nature of PES and overcoming limitations of existing methods for estimating the PES standard. Additionally, it is necessary to further improve the PES schemes based on cost-efficiency and explore the methods for estimating the PES standard based on the land rent theory and interdisciplinary knowledge.
3 Bai, P; Guo, X.. 2023. Development of a 60-year high-resolution water body evaporation dataset in China. Agricultural and Forest Meteorology, 334:109428. [doi: https://doi.org/10.1016/j.agrformet.2023.109428]
Evapotranspiration ; Datasets ; Lakes ; Models ; Hydrological cycle ; Uncertainty ; Water balance ; Precipitation ; Water reservoirs ; Water temperature / China / Songhuajiang and Liaohe River Basin / Haihe River Basin / Yellow River Basin / Huaihe River Basin / Yangtze River Basin / Southeast River Basin / Pearl River Basin / Southwest River Basin / Northwest River Basin
(Location: IWMI HQ Call no: e-copy only Record No: H051845)
(10.90 MB)
Evaporation from water bodies (Ew) is a critical component of the global water cycle. However, existing evaporation products that include Ew often suffer from drawbacks such as coarse resolution, short time span, and high uncertainty. This study developed a 60-year (1960–2019) high-resolution (0.05º×0.05º) evaporation dataset for small shallow water bodies in China based on the Penman model. Two key factors affecting the accuracy of the Penman model were considered: the uncertainty of the empirical wind function and changes in heat storage in the water body. Specifically, we used large-size (20 or 100 m2) pan evaporation (Epan) observations from 21 sites as a benchmark to correct the wind function of the Penman model. A data-driven model was then developed to map the spatial distribution of the wind function coefficients across China. The corrected wind function significantly improved the accuracy of Epan estimates compared to the original wind function, with the Kling-Gupta efficiency (KGE) increased by 0.05~0.10. To model the effect of heat storage changes on evaporation, an equilibrium temperature method was used. We also introduced an area-dependent scaling factor into the wind function to account for the effect of water body's size on Ew estimation. The reliability of the Ew algorithm was tested on two lakes using eddy-covariance flux observations, and simulations showed good agreement with observations. The Epan (20 m2 pan) dataset and its two components calculated from the radiative and aerodynamic terms of the Penman model can be accessed at https://osf.io/qd28m/. Users can utilize the two Epan components and the area-dependent scaling factor to estimate evaporation for water bodies of varying sizes. However, caution is needed when applying this dataset to deep water bodies, as it is designed for shallow water bodies.
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