工业园区的绿色转型

开发区是我国改革开放的产物,已经走过了30多年的发展历程,作为国家战略实施载体,成为全国引进外资密集、高新技术集聚、经济增长迅猛的区域。随着经济的迅速发展和园区的快速扩张,开发区面临着土地资源既浪费严重又非常紧缺、能源供给紧张、环保压力增大、发展后劲不足等问题。金桥开发区结合自身特点,以国家生态工业示范园区建设为契机,着力改造传统制造业,大力发展生产性服务业、战略性新兴产业、高新技术产业,通过优化第二产业,发展第三产业,实现了园区产业结构的转型。同时,以生态创建为抓手,积极引导园区企业加强节能环保,使整个园区的可持续发展能力获得提升。     

纳氏试剂比色法中样品的预处理

氨是一种无色且有强烈刺激性臭味的气体,居住区大气中有害物质最高容许浓度氨的一次限值是0．2mg／m3。本文研究了环境空气监测中氨的测定方法,分析氨的预处理对监测结果的影响。     

Extraction of heavy metals from e-waste contaminated soils using EDDS

Environmental contamination due to uncontrolled e-waste recycling activities is drawing increasing attention in the world. Extraction of these metals with biodegradable chelant [S,S]-ethylenediaminedisuccinic acid (EDDS) and the factors influencing extraction efficacy were investigated in the present study. Results showed that the addition of EDDS at low pH (5.5) produced higher metal extraction than that at high pH (8.0) solution. Metal speciation analysis indicated that Cu was completely complexed with EDDS at different pH conditions with various amounts of EDDS applied. For Pb and Zn, at low EDDS dose of 0.304 mol/kg soil, they were present as Pb- and Zn-EDDS. However, at high EDDS dose of 1.26 mol/kg soil, most of Pb was bound with dissolved organic matter. Ca and Al were found to be strong competitors for trace metals to EDDS at low application dose and low pH condition.     

微电解+Fenton氧化+二级A/O组合工艺处理农药杀菌剂废水

杀菌剂生产废水含有大量三环唑、无机盐、高毒性物质和难生物降解有机物,对生化细菌有较强的抑制和毒害作用,且BOD5/COD值较小,采用传统生化处理工艺无法进行。现采用微电解、Fenton氧化和二级A/O组合工艺建成的废水处理工程,运行良好,出水各项指标达到环太湖流域排放标准DB 32/1072—2007。     

光催化膜反应器的设计及其在水处理中的应用

作为一种新型的水处理装置,光催化膜反应器具有反应迅速、降解效率高、降解彻底、无二次污染等特点,在节水减排、微污染水处理、中水回用等方面具有重要的应用价值。总结目前国内外各种不同类型的光催化膜反应器的设计、特点及在水处理中的应用情况,并对其今后的发展提出建议。     

医疗废物处置厂污水处理技术

从污水处理工艺、处理方式、水量平衡和自动控制方面论述了医疗废物处置厂污水处理系统,并申请了发明专利。根据医疗废物处置厂水质复杂、水量小、需中水回用等特点,采用物化、生化和微滤膜处理工艺,达到中水回用标准。消毒废水单独处理,循环使用。     

陆上油气田勘探开发规划环境影响评价指标体系构建研究

目前陆上油气田勘探开发规划的环境影响评价工作处于探索起步阶段,特别是国内尚未形成一套完善的环境目标和评价指标体系。本文以甘肃庆阳地区某油区"十二五"发展规划的环境影响评价为例,论述了陆上油气田勘探开发规划环境影响评价的基本原则、技术路线,重点对评价指标体系的构建进行了研究,旨在技术上推动陆上油气田勘探开发行业的规划环境影响评价工作。     

The impact of climate change on global energy use

Robust decision making, a growing approach to infrastructure planning under climate change uncertainty, aims to evaluate infrastructure performance across a wide range of possible conditions and identify the most robust strategies and designs. Robust decision making seeks to find potential weaknesses in systems in order to gird these through a combination of policy, infrastructure, and, in some cases, resilient or recovery strategies. A system can be explored by simulating many combinations of uncertain climatic and economic parameters; statistical clustering can identify parameter thresholds that lead to unacceptable performance. Often, however, uncertain variables are correlated, complicating the robustness analysis and casting doubt upon the thresholds identified. Here, we evaluate the impact of ordinary, hidden correlations in uncertainty parameters that drive simulation in robust decision making. We induced correlations between temperature and key climatic and economic parameters. We tested correlations of 0%, 30%, 60%, and 90% between temperature and the absolute value of precipitation, coefficient of variation, and downward surface solar radiation, and negative correlations between temperature and net variable benefit and the discount rate. We used a calibrated simulation model of a dam system regulating Lake Tana, Ethiopia, to compute the agricultural supply and net present value of the reservoirs. As the correlation strength increased, the results converged in a smaller region. We found that strong correlations depressed robustness scores of lower-performing alternatives and conversely increased results of the higher-performing alternatives. As the correlations increased in favorable alternatives, the failure thresholds became more extreme, speciously suggesting that only intense changes would result in poor performance. This overall analysis highlights the degree to which correlations of an interconnected climatic and economic system can impact outcomes of robust decision making and suggests methods to avoid confounding results.

     

A novel approach for VOC source apportionment combining characteristic factor and pattern recognition technology in a Chinese industrial area

Volatile organic compound (VOC) emission control and source apportionment in small-scale industrial areas have become key topics of air pollution control in China. This study proposed a novel characteristic factor and pattern recognition (CF-PR) model for VOC source apportionment based on the similarity of characteristic factors between sources and receptors. A simulation was carried out in a typical industrial area with the CF-PR model involving simulated receptor samples. Refined and accurate source profiles were constructed through in situ sampling and analysis, covering rubber, chemicals, coating, electronics, plastics, printing, incubation and medical treatment industries. Characteristic factors of n-undecane, styrene, o-xylene and propane were identified. The source apportionment simulation results indicated that the predicted contribution rate was basically consistent with the real contribution rate. Compared to traditional receptor models, this method achieves notable advantages in terms of refinement and timeliness at similar accuracy, which is more suitable for VOC source identification and apportionment in small-scale industrial areas.     

A novel approach to estimate and control denitrification performance in activated sludge systems with respirogram technology

Respirogram technology has been widely applied for aerobic process, however, the response of respirogram to anoxic denitrification is still unclear. To reveal such response may help to design a new method for the evaluation of the performance of denitrification. The size distribution of flocs measured at different denitrification moments demonstrated a clear expansion of flocs triggered by denitrification, during which higher specific endogenous and quasi-endogenous respiration rates (SOUR_e and SOUR_q) were also observed. Furthermore, SOUR_q increases exponentially with the specific denitrification rate (SDNR), suggesting that there should be a maximum SDNR in conventional activated sludge systems. Based on these findings, an index R_q/t, defined as the ratio of quasi-endogenous (OUR_q) to maximum respiration rate (OUR_t), is proposed to estimate the denitrification capacity that higher R_q/t indicates higher denitrification potential, which can be readily obtained without complex measurement or analysis, and it offers a novel and promising respirogram-based approach for denitrification estimation and control by taking measures to extend anoxic time to maintain its value at a high level within a certain range.