水体中四环素类抗生素的去除技术研究进展

四环素类抗生素因其可以防治人类和动物由病菌引起的疾病,同时又能用作生长促进剂以加快动物生长,目前在国内外被大量使用。抗生素的使用甚至滥用对自然环境造成不容忽视的污染,并进一步对人类身体健康产生潜在危害。从常规处理、膜处理、化学氧化和吸附等角度讨论了国内外对四环素类抗生素去除技术的研究进展,为环境水体中四环素类抗生素污染的有效去除提供了方向。     

Water quality prediction of copper-molybdenum mining-beneficiation wastewater based on the PSO-SVR model

● Data acquisition and pre-processing for wastewater treatment were summarized. ● A PSO-SVR model for predicting COD_eff in wastewater was proposed. ● The COD_eff prediction performances of the three models in the paper were compared. ● The COD_eff prediction effects of different models in other studies were discussed. The mining-beneficiation wastewater treatment is highly complex and nonlinear. Various factors like influent quality, flow rate, pH and chemical dose, tend to restrict the effluent effectiveness of mining-beneficiation wastewater treatment. Chemical oxygen demand (COD) is a crucial indicator to measure the quality of mining-beneficiation wastewater. Predicting COD concentration accurately of mining-beneficiation wastewater after treatment is essential for achieving stable and compliant discharge. This reduces environmental risk and significantly improves the discharge quality of wastewater. This paper presents a novel AI algorithm PSO-SVR, to predict water quality. Hyperparameter optimization of our proposed model PSO-SVR, uses particle swarm optimization to improve support vector regression for COD prediction. The generalization capacity tested on out-of-distribution (OOD) data for our PSO-SVR model is strong, with the following performance metrics of root means square error (RMSE) is 1.51, mean absolute error (MAE) is 1.26, and the coefficient of determination (R²) is 0.85. We compare the performance of PSO-SVR model with back propagation neural network (BPNN) and radial basis function neural network (RBFNN) and shows it edges over in terms of the performance metrics of RMSE, MAE and R², and is the best model for COD prediction of mining-beneficiation wastewater. This is because of the less overfitting tendency of PSO-SVR compared with neural network architectures. Our proposed PSO-SVR model is optimum for the prediction of COD in copper-molybdenum mining-beneficiation wastewater treatment. In addition, PSO-SVR can be used to predict COD on a wide variety of wastewater through the process of transfer learning.     

化学生物絮凝工艺中生物去除效果研究

通过工艺的对比试验,指出化学生物絮凝工艺去除效果要优于化学絮凝工艺,当投加相同量的絮凝剂和混凝剂时,前者比后者的去除效率提高了20％以上。同时通过测定耗氧速率证实化学生物絮凝系统内存在明显的生物作用。     

Modeling using dynamic variables – An approach for the design of loss prevention programs

Records from The National Safety Council [National Safety Council, 2007. Safety Intervention Evaluation: A Systematic Approach. <http://www.acgih.org/events/ControlBand/Thomas_SafetyIntervention.pdf> (accessed 10.01.07)] have shown that in 2004 alone, on-the-job injuries to workers constituted 35% of total recorded injuries in the United States. This generated an associated cost of about $142.2 billion. Unfortunately, the safety intervention programs enforced at work places to mitigate such losses are driven mainly by intuition and experience of involved safety personnel. This paper details implementing a computer program to furnish safety personnel with an empirical basis for designing loss prevention programs based on historical safety data. The computer tool is driven by a dynamic mathematical model which adapts itself to variations in data patterns and explains the correlation between historical incident rates and corresponding resources committed to interventions. This study empowers the industry with a tool that is capable of forming the core of optimizing valuable human resource allocation in safety program designs.     

土壤侵蚀经济损失分析及价值估算—以贵州省猫跳河流域为例

以贵州省猫跳河流域为例,运用环境经济学理论和方法,分析土壤侵蚀的经济损失内在机制,估算土壤侵蚀的经济损失,揭示土壤侵蚀经济损失分布的空间格局,为该区域水土流失防治提供科学依据。结果表明,研究区平均每年土壤侵蚀经济损失为36 602.44×104元,其中土壤养分损失占总损失的89.46%,土地废弃损失占总损失的4.64%,土壤水分损失占总损失的1.05%,泥沙损失占总损失的4.85%。旱地土壤侵蚀经济损失最大,占土壤侵蚀经济损失的61.94%。从各县来看,清镇市土壤侵蚀经济损失最大,占总经济损失的32.87%。研究区平均单位面积经济损失为1 174.86元/hm2,北部地区和西南部地区土壤侵蚀单位面积经济损失价值较大。推进水土流失治理,实行生态补偿制度势在必行。     

重庆市酸沉降污染经济损失估算

重庆市酸沉降降污染严重,为确定其造成的经济损失,经经济社会发展决策提供依据和拟订,选择满意的防治姑人群健康和农林污染危害调查,材料挂片耐蚀试验,模拟酸沉降实验等基础上,用人力资本法,市场价值法和投入产出损益比较法进行估算。     

化学实验室火灾、爆炸原因分析及防火防爆措施

从化学实验室内使用的化学物品的易燃易爆性能,存在的各种火源入手,分析了化学实验室发生火灾爆炸事故的原因和爆炸事故的特点,在此基础上提出了防火防爆的具体措施。     

无汞盐化学需氧量测定方法研究

本法基于可定量测定K_2Cr_2O_7和Cl~-的反应产物C~2这一原理,在用吸收装置吸收Cl_2后,用碘量法测定余氯。试验结果表明,本法有较高的准确度和精密度。     

汽车尾气中NO_X再燃烧过程的动力学

为了阐明汽车尾气中 NOX再燃烧的动力学进程 ,以甲醛和 NO2 作为探针分子 ,通过 FT-IR跟踪研究了反应体系中所产生的 HCO自由基与 NO2 反应的动力学。结果表明 ,反应的主要产物中包括 CO、CO2 、NO、HONO和 H2 O等分子 ,经长时间的反应 ,当体系中的 NO2 基本耗尽时 ,才有少量的 N2 O生成。这些产物分子分别是在几个不同途径的连串反应中形成的。从体系中 CO和 CO2 的生成量 ,测定了主反应的歧化反应速率比 ,并对相应的动力学机理进行了讨论。     

Linking climate policy across economic sectors: A case for green growth in Nepal

While the energy sector is the largest global contributor to greenhouse gas (GHG) emissions, the agriculture, forestry, and other land use (AFOLU) sector account for up to 80% of GHG emissions in the least developed countries (LDCs). Despite this, the nationally determined contributions (NDCs) of LDCs, including Nepal, focus primarily on climate mitigation in the energy sector. This paper introduces green growth—a way to foster economic growth while ensuring access to resources and environmental services—as an approach to improving climate policy coherence across sectors. Using Nepal as a case country, this study models the anticipated changes in resource use and GHG emissions between 2015 and 2030, that would result from implementing climate mitigation actions in Nepal's NDC. The model uses four different scenarios. They link NDC and policies across economic sectors and offer policy insights regarding (1) energy losses that could cost up to 10% of gross domestic product (GDP) by 2030, (2) protection of forest resources by reducing the use of biomass fuels from 465 million gigajoules (GJ) in 2015 to 195 million GJ in 2030, and (3) a significant reduction in GHG emissions by 2030 relative to the business-as-usual (BAU) case by greater use of electricity from hydropower rather than biomass. These policy insights are significant for Nepal and other LDCs as they seek an energy transition towards using more renewable energy and electricity.