The levels of metals in sediments of urban river ecosystems are crucial for aquatic environmental health and pollution assessment. Yet little is known about the interaction of nutrients with metals for environmental risks under contamination accumulation. Here, we combined hierarchical cluster, correlation, and principal component analysis with structural equation model (SEM) to investigate the pollution level, source, toxicity risk, and interaction associated with metals and nutrients in the sediments of a river network in a city area of East China. The results showed that the pollution associated with metals in sediments was rated as moderate degree of contamination load and medium-high toxicity risk in the middle and downstream of urban rivers based on contamination factor, pollution load index, and environmental toxicity quotient. The concentration of mercury (Hg) and zinc (Zn) showed a significant correlation with toxic risks, which had more contribution to toxicity than other metals in the study area. Organic nitrogen and organic pollution index showed heavily polluted sediments in south of the study area. Though correlation analysis indicated that nutrients and metals had different input zones from anthropogenic sources in the urban river network, SEM suggested that nutrient accumulation indirectly intensified toxicity risk of metals by 13.6% in sediments. Therefore, we suggested the combined consideration of metal toxicity risk with nutrient accumulation, which may provide a comprehensive understanding to identify sediment pollution.
Electrostatic precipitators (ESP) have been considered as the main particulate matter (PM) removal facility in the energy industry. This paper presents a real-time optimization method for a one-chamber industrial ESP in an ultra-low emission power plant with an intelligent optimization system (IOS). The IOS seeks to optimize the energy consumption of ESP subject to the outlet concentration requirement in real-time. A coordination control logic is designed to regulate the optimized operation set points with varying operation conditions. The operation optimized by the IOS is compared with the operations under PID (proportion-integral-derivative) and manual control. The results show that the IOS improves the emission compliance rate from 95% of manual control to 100% and the medium concentration is tuned to be 46.6% closer to the emission target. Furthermore, a good balance between emission and energy consumption is achieved, with 35.50% energy conservation for the same emission upper limit of 30 mg/m3. These results prove that the IOS significantly contributes to the efficient operation and economic PM removal by ESP for the energy industry. 相似文献
Indoor emission source models are mainly used as a component in indoor air quality (IAQ) modeling, which, in turn, is part of exposure and risk modeling. They are also widely used to interpret the experimental data obtained from environmental chambers and buildings. This paper compiles 52 indoor emission source models found in the literature. Together, they represent the achievements that IAQ modelers have made in recent years. While most models have a certain degree of usefulness, genuine predictive models are still few, and there is undoubtedly much room for improvement. This review consists of two parts. Part 1--this paper-provides an overview of the 52 models, briefly discussing their validity, usefulness, limitations, and flaws (if any). Part 2 focuses on parameter estimation, a topic that is critically important to modelers but has not been systematically discussed. 相似文献