Urban ecological risk is one of the important factors that may restrict the social and economic development. Therefore, it is of great significance to carry out a comprehensive assessment of ecological risks so that an ecological risk prevention and control plan can be scientifically formulated. In this paper, a comprehensive ecological risk assessment indicator system of Xiamen was established based on local ecological properties and socioeconomic status. This indicator system covers seven indicators including air pollution, soil pollution, water pollution, fresh water consumption, change in land use, occupation of key zones with ecological functions, and road network expansion. Based on this indicator system and in conjunction with the single factor assessment of ecological risks, this study constructed a model of comprehensive ecological risk assessment and forecasted the comprehensive ecological risk of Xiamen in 2020. The results showed that the comprehensive ecological risk level of Xiamen in 2020 is medium and the main stressors are the discharge of air and water pollutants. From the perspective of risk receptors, i.e. the ecosystem services, the risk posed to the ecosystem services associated to the maintenance of air quality and water purification is the highest. Therefore, this study proposed the recommendations on ecological risk prevention and regulation in Xiamen based on the comprehensive assessment of ecological risks, in the hope to provide scientific support for local ecological protection and sustainable development. 相似文献
Urban energy consumption is one of the most important causes of air pollution. Air pollution-oriented ecological risk assessment is of great significance to the promotion of urban environmental protection. This paper focuses on ecological risk in Xiamen city caused by air pollutant discharge from urban energy consumption. The Long-range Energy Alternatives Planning model was used to establish two scenarios of energy consumption in Xiamen city, and based on different scenarios, we estimated urban energy consumption and discharge quantity of air pollutant (DQAP). A box model and an expert scoring method were used to calculate the air pollution burden (APB) of SO2, NO2, CO, PM10 and PM2.5 and to obtain the probabilities of different air pollution loads. An ecological risk assessment model was developed and utilized to predict Xiamen city’s ecological risks in 2020. The results showed that under an energy-saving scenario, the ecological risks for PM2.5, SO2 and NO2 are high, whereas the ecological risks for CO and PM10 are low. Under a baseline scenario, the ecological risks for PM2.5, SO2 and NO2 are moderate, whereas the ecological risks for CO and PM10 are low. In addition, the APB of SO2, NO2, CO, and PM2.5, but not of PM10, is predicted to rise. In the simulation, energy generation from coal is the main source of air pollution. Although the DQAP from automobiles is not high, it is predicted to rise year-on-year. In summary, the ecological risk due to pollution in Xiamen city is high, and the main pollutants are SO2, NO2 and PM2.5. 相似文献
Post-treatment impacts of a novel combined hydrogen peroxide (H2O2) oxidation and WOx/ZrO2 catalysis used for the removal of 1,4-dioxane and chlorinated volatile organic compound (CVOC) contaminants were investigated in soil and groundwater microbial community. This treatment train removed ~90% 1,4-dioxane regardless of initial concentrations of 1,4-dioxane and CVOCs. The Illumina Miseq platform and bioinformatics were used to study the changes to microbial community structure. This approach determined that dynamic shifts of microbiomes were associated with conditions specific to treatments as well as 1,4-dioxane and CVOCs mixtures. The biodiversity was observed to decrease only after oxidation under conditions that included high levels of 1,4-dioxane and CVOCs, but increased when 1,4-dioxane was present without CVOCs. WOx/ZrO2 catalysis reduced biodiversity across all conditions. Taxonomic classification demonstrated oxidative tolerance for members of the genera Massilia and Rhodococcus, while catalyst tolerance was observed for members of the genera Sphingomonas and Devosia. Linear discriminant analysis effect size was a useful statistical tool to highlight representative microbes, while the multidimensional analysis elucidated the separation of microbiomes under the low 1,4-dioxane-only condition from all other conditions containing CVOCs, as well as the differences of microbial population among original, post-oxidation, and post-catalysis states. The results of this study enhance our understanding of microbial community responses to a promising chemical treatment train, and the metagenomic analysis will help practitioners predict the microbial community status during the post-treatment period, which may have consequences for long-term management strategies that include additional biodegradation treatment or natural attenuation.