电除尘器气流分布的等效阻力法模拟计算

在此提出了一种电除尘器内气流分布的简易计算模拟方法 ,其核心就是把气流分布板作为均匀的透气板看待 ,使多孔板阻力与均匀透气板阻力等效 ,从而大幅度减少网格数量和计算时间。简化计算的数据与模型试验的测试数据相吻合 ,表明该简易计算模拟方法完全可以取代现行的模型试验法 ,这对计算模拟的普及、电除尘器成本的降低、设计的优化等都具有重要意义     

畜禽养殖业清洁生产的必要性及实施对策研究--以浙江省为例

集约化畜禽养殖业的发展在提高人民生活水平的同时也给环境带来了巨大的压力。清洁生产是基于污染预防的一种环境保护的战略措施,它体现了废弃物的减量化、资源化、无害化原则。实施畜禽养殖业清洁生产是保证畜禽养殖业健康可持续发展的根本途径。分析了畜禽养殖业实施清洁生产的必要性．并根据当前畜禽养殖业清洁生产进展中存在的问题,提出了相应的对策。     

猪粪经蝇蛆生态处理后粪臭素和排污量的变化

观察家蝇幼虫 (蝇蛆 )生态处理猪粪后 ,猪粪中粪臭素和排污量的变化。以养猪场的猪粪为试验材料 ,经当地蝇蛆处理的猪粪作为处理组 ,未经蝇蛆处理的猪粪为对照组 ,测定两组猪粪样本中粪臭素 ( 3 -甲基吲哚 ,简称 3 -MI)、CODCr、BOD5和 NH3-N的质量浓度。经蝇蛆处理后每 kg猪粪中的 3 -MI、CODCr、BOD5和 NH3-N分别为 2 .76× 10 - 3、5 6.3 6、14 .84和 3 .41g;对照组中上述物质分别为 3 8.5 8× 10 - 3、12 3 .0 1、60 .0 7和 3 .64 g。经蝇蛆处理后的猪粪中的 3 -MI、CODCr和 BOD5分别减少了 92 .8%、5 4.2 %和75 .3 %;而 NH3-N的含量仅减少 6.3 %。蝇蛆生态处理猪粪可有效减少粪臭素和有机污染物 ,有利于改善环境     

生物滴滤塔处理硫化氢废气

采用生物滴滤塔去除废气中的H_2S。研究了进气量及进气浓度对H_2S去除率的影响,同时对生物滴滤塔填料表面的微生物群落进行了分析。实验结果表明:当营养液喷淋量为6 L/h、进气量为0.8 m~3/h左右、进气H_2S质量浓度在0～70 mg/m~3之内随机变化时,生物滴滤塔对H_2S的去除率能稳定达到90%以上。此时生物滴滤塔的最高负荷为5 400 mg/(m~3·h)。通过高通量测序得出H_2S去除中起主导作用的细菌为硫杆菌。     

Available Water Supplies in Beijing,China, Under Single‐ and Multi‐Year Drought

Since its implementation in 2015, the Middle Route of the South‐to‐North Water Diversion Project (MR‐SNWDP) has transferred an average of 45 billion cubic meters of surface water per year from the Yangtze River in southern China to the Yellow River and Hai River Basin in northern China, but how that supply is able to cope with droughts under different scenarios has not been explored. In this study, using the water demand for 2020 as the guaranteed water target, a Water Evaluation and Planning system was used to simulate available water supplies in Beijing under different drought scenarios. In the case of a single‐year drought, without the MR‐SNWDP, Beijing’s water shortage ratio was 16.7%; with the MR‐SNWDP, this ratio reduced to 7.3%. In the case of a multi‐year drought, without the MR‐SNWDP, Beijing’s water shortage ratio was 25.3%; with the MR‐SNWDP, this ratio reduced to 7.4% and domestic water supply was improved. Our research suggests that to prepare for multi‐year drought in the Beijing area, the SNWDP supports increased supplies to the region that would mitigate drought effects. This study is, however, mostly focused on water supply provision to Beijing and does not comprehensively evaluate other potential impacts. Multiple additional avenues could be pursued that include replenishing groundwater, increasing reservoir storage, and water conservation methods. Further research is needed to explore the relative costs and benefits of these approaches.     

Sensitivity analysis of TOPSIS method in water quality assessment: I. Sensitivity to the parameter weights

Sensitivity analysis is becoming increasingly widespread in many fields of engineering and sciences and has become a necessary step to verify the feasibility and reliability of a model or a method. The sensitivity of the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method in water quality assessment mainly includes sensitivity to the parameter weights and sensitivity to the index input data. In the present study, the sensitivity of TOPSIS to the parameter weights was discussed in detail. The present study assumed the original parameter weights to be equal to each other, and then each weight was changed separately to see how the assessment results would be affected. Fourteen schemes were designed to investigate the sensitivity to the variation of each weight. The variation ranges that keep the assessment results unchangeable were also derived theoretically. The results show that the final assessment results will change when the weights increase or decrease by ±20 to ±50 %. The feedback of different samples to the variation of a given weight is different, and the feedback of a given sample to the variation of different weights is also different. The final assessment results can keep relatively stable when a given weight is disturbed as long as the initial variation ratios meet one of the eight derived requirements.     

Groundwater quality assessment based on rough sets attribute reduction and TOPSIS method in a semi-arid area, China

In order to enrich and improve the groundwater quality assessment system, a new coupled assessment model based on rough set attribute reduction and the technique for order preference by similarity to ideal solution (TOPSIS) was proposed. The proposed model was applied in the groundwater quality assessment of a semi-arid area, northwest China. The results show that most chemical indices except NH (4) (+) , F(-), and Mn meet the Standards for Drinking Water of China and the groundwater quality overall is good. All assessed water samples are found to be fit for human consumption according to the comprehensive assessment results. Rough set attribute reduction for groundwater quality assessment is practical. The assessment results after attribute reduction show a good consistency with those before attribute reduction. Rough set attribute reduction and TOPSIS evaluation coupled model is clear in ideas and simple in calculation, and evaluation results are reasonable as well. The coupled model can be applied to solve many multiple criteria decision making problems such as groundwater quality assessment.     

三种藻类引发水中17α-乙炔基雌二醇的光降解实验研究

研究了普通小球藻、铜绿微囊藻和柱孢鱼腥藻3种藻类引发水中17α-乙炔基雌二醇(EE2)的光降解.结果表明,在250 W高压汞灯(HPML,nm)的照射下,一定藻浓度下,EE2的光降解率可达19%-20%.另外,还研究光强、藻悬浮液浓度和EE2初始浓度等对EE2光降解速率的影响,发现在本实验体系中,光通量大、藻浓度高及EE2初始浓度低有利于提高EE2的光降解速率.     

基于生态系统管理的湿地概念生态模型研究

湿地是地球上的一种重要生态系统,基于生态系统管理理念,进行湿地保护与管理,既是湿地科学发展的必然结果.也是当前湿地保护与管理的客观需求.湿地生态模型是以湿地生态系统作为研究对象的模型,是对湿地生态系统组成、结构、过程和功能进行简化、类比或抽象,是用来反映湿地生态系统各种过程和关系的定性或定量化工具.湿地概念生态模型是各类湿地生态模型中最基本的类型,是对湿地生态系统组成及其相互关系的一种简约的定性表达,特别是指人类活动影响下湿地生态系统因子变化及其相互关系的概念性表达.湿地概念生态模型构建的主要目的是旨在识别人类活动对湿地生态系统的驱动与胁迫,这些驱动与胁迫产生的一系列生态效应,以及湿地生态系统对此所表现出来的特征.湿地生态系统是一个多层次、多因子组成的,结构复杂、功能多样、具有多向反馈和调节机制的复杂大系统或巨系统.影响系统状态或驱动系统变化的因子众多,既有来自系统内部的、也有来自系统外部的,它们对系统造成的影响往往具有联动关系和因果效应.湿地概念生态模型就是在生态系统管理理论指导下,将这些系统因子及其关系抽象并提取出来,以"驱动-胁迫-效应-表征"为主线,判断系统变化与演化背后存在的因果关系,构建能够反映系统变化与演化特征和规律的结构性关系网络模型.湿地概念生态模型研究的意义在于在科学与决策之间架起一座桥梁,为实施湿地生态保护与管理提供指导,同时为建立湿地数量化模型奠定基础.