Conventional methods for water and wastewater treatment are energy-intensive, notably at the stage of coagulation–flocculation, calling for new strategies to predict pollutant reduction because the amount of energy consumed is related to how much of the pollutant is treated. Here we developed a model, named Bio-logic, inspired by ecosystems, where pollutants represent organisms, coagulants are food, and the wider environmental conditions are the living environment. Artificial intelligence was used to learn the biological behavior, which enabled an accurate prediction of the amount of pollutant reduction. Results show that pseudo-biological objects that have a strong affinity for biological food, such as turbidity, total phosphorus, ammonia nitrogen and the potassium permanganate index, induced a strong correlation, between measured pollutant consumption capacity and predicted values. For instance, R2 correlation coefficients are 0.97 for turbidity and 0.92 for the potassium permanganate index in the laboratory; and 0.99 for turbidity, 0.90 for total phosphorus, 0.75 for ammonia nitrogen and 0.63 for the potassium permanganate index in water treatment plants. Overall, our findings demonstrate that artificial intelligence can use the water Bio-logic model to predict the pollutant consumption capacity.
We utilized a multi-biomarker approach (Integrated Biomarker Response version 2, IBRv2) to investigate the scope and dispersion of groundwater contamination surrounding a rare earth mine tailings impoundment. Parameters of SD rat included in our IBRv2 analyses were glutathione levels, superoxide dismutase, catalase, and glutathione peroxidase activities, total anti-oxidative capacity, chromosome aberration, and micronucleus formation. The concentration of 20 pollutants including Cl?, SO42?, Na+, K+, Mg2+, Ca2+, TH, CODMn, As, Se, TDS, Be, Mn, Co, Ni, Cu, Zn, Mo, Cd, and Pb in the groundwater were also analyzed. The results of this study indicated that groundwater polluted by tailings impoundment leakage exhibited significant ecotoxicological effects. The selected biomarkers responded sensitively to groundwater pollution. Analyses showed a significant relationship between IBRv2 values and the Nemerow composite index. IBRv2 could serve as a sensitive ecotoxicological diagnosis method for assessing groundwater contamination in the vicinity of rare earth mine tailings. According to the trend of IBRv2 value and Nemerow composite index, the maximum diffusion distance of groundwater pollutants from rare earth mine tailings was approximately 5.7 km.
DB 52/12—1999《贵州省环境污染物排放标准》自第一次修订至今已有13年,随着我省经济社会的发展,现行标准执行过程中暴露出一些不足之处,导致标准执行困难。针对现行标准中存在的问题,在对有关法律法规、本省主要工业结构、特征污染物和国外相关排放标准进行研究分析的基础上,以水污染物为例,对标准制定中有关排放等级、时段划分、污染物控制限值等内容进行了思考。 相似文献
Environmental conditions act above and below ground, and regulate carbon fluxes and evapotranspiration. The productivity of boreal forest ecosystems is strongly governed by low temperature and moisture conditions, but the understanding of various feedbacks between vegetation and environmental conditions is still unclear. In order to quantify the seasonal responses of vegetation to environmental factors, the seasonality of carbon and heat fluxes and the corresponding responses for temperature and moisture in air and soil were simulated by merging a process-based model (CoupModel) with detailed measurements representing various components of a forest ecosystem in Hyytiälä, southern Finland. The uncertainties in parameters, model assumptions, and measurements were identified by generalized likelihood uncertainty estimation (GLUE). Seasonal and diurnal courses of sensible and latent heat fluxes and net ecosystem exchange (NEE) of CO2 were successfully simulated for two contrasting years. Moreover, systematic increases in efficiency of photosynthesis, water uptake, and decomposition occurred from spring to summer, demonstrating the strong coupling between processes. Evapotranspiration and NEE flux both showed a strong response to soil temperature conditions via different direct and indirect ecosystem mechanisms. The rate of photosynthesis was strongly correlated with the corresponding water uptake response and the light use efficiency. With the present data and model assumptions, it was not possible to precisely distinguish the various regulating ecosystem mechanisms. Our approach proved robust for modeling the seasonal course of carbon fluxes and evapotranspiration by combining different independent measurements. It will be highly interesting to continue using long-term series data and to make additional tests of optional stomatal conductance models in order to improve our understanding of the boreal forest ecosystem in response to climate variability and environmental conditions. 相似文献
