Development of monitoring technology for airborne particulate matter

Particulate matter suspended in the air has adverse effects onhuman health. Its level of concentration is an important parameter in evaluating the degree of hazard it poses to the atmosphere. Conventional methods used in measuring particulatematter are often filter-based, which indicates some disadvantagesbecause such a base requires labor and time. In this study, to achieve real-time measurements, a new electrical method was developed for measuring PM10 and PM2.5 concentrations. The basicprinciple is to electrically charge particles passing through thePM inlet using a corona charger and measure the currents createdby charged particles to obtain the number concentration of particulate matter. A new type inlet based on the particle cupimpactor configuration was designed and its performance was evaluated. A unipolar diffusion charger was developed and thecharger's efficiency was determined experimentally in terms ofPn, which represents the penetration through the charger,P, times the average charge number acquired by a particle,n, for different particle sizes. The correlation was constructed between the PM10 (or the PM2.5) mass concentrationsand the electrical currents due to particles, which were chargedby the diffusion charger.     

Recycling of petroleum-contaminated sand

The environmental impact of using petroleum-contaminated sand (PCS) as a substitute in asphalt paving mixtures was examined. An appreciable component of PCS is oily sludge, which is found as the dregs in oil storage tanks and is also produced as a result of oil spills on clean sand. The current method for the disposal of oily sludge is land farming. However, this method has not been successful as an oil content of < 1% w/w is required, and difficulty was encountered in reaching this target. The reuse of the sludge in asphalt paving mixtures was therefore considered as an alternative. Standard tests and environmental studies were conducted to establish the integrity of the materials containing the recycled sludge. These included physical and chemical characterization of the sludge itself, and an assessment of the mechanical properties of materials containing 0%, 5%, 22% and 50% oily sludge. The blended mixtures were subjected to special tests, such as Marshall testing and the determination of stability and flow properties. The experimental results indicated that mixtures containing up to 22% oily sludge could meet the necessary criteria for a specific asphalt concrete wearing course or bituminous base course. To maximize the assay from the recycled material, the environmental assessment was restricted to the 50% oily sludge mixture. Leachates associated with this particular mixture were assayed for total organic residue and certain hazardous metal contaminants. The results revealed that the organics were negligible, and the concentrations of the metals were not significant. Thus, no adverse environmental impact should be anticipated from the use of the recycled product. Our research showed that the disposal of oily sludge in asphalt paving mixtures could possibly yield considerable savings per tonne of asphalt concrete, and concurrently minimize any direct impact on the environment.     

江苏省环境监测系统进行监测分析质量大检查

由江苏省环保局、省监测站具体领导、并由省和各市监测站质量管理人员组成的“江苏省环境监测质量管理组”,于今年9月1日至13日分南北两片对全省十一个省辖市监测站实验室的监测分析质量进行了全面检查。     

湖北省召开大气环境监测网站工作会议

会议对全省网络建设基本情况、网站设置内容落实情况、监测质量保证及网站建设中存在的问题等作了全面总结,讨论和修订了《湖北省大气环境例行监测技术规定》.省中心站还表扬了多年来不间断监测、上报数据齐全、报表清晰和规矩的网站,同时对今后网站工作提出了要求.     

Analysis of pollutant levels in central Hong Kong applying neural network method with particle swarm optimization

Air pollution has emerged as an imminent issue in modernsociety. Prediction of pollutant levels is an importantresearch topic in atmospheric environment today. For fulfillingsuch prediction, the use of neural network (NN), and inparticular the multi-layer perceptrons, has presented to be acost-effective technique superior to traditional statisticalmethods. But their training, usually with back-propagation (BP)algorithm or other gradient algorithms, is often with certaindrawbacks, such as: 1) very slow convergence, and 2) easilygetting stuck in a local minimum. In this paper, a newlydeveloped method, particle swarm optimization (PSO) model, isadopted to train perceptrons, to predict pollutant levels, andas a result, a PSO-based neural network approach is presented. The approach is demonstrated to be feasible and effective bypredicting some real air-quality problems.     

绘制氯气校准曲线的方法

甲基橙分光光度法测定氯气[1 ] 的机理是利用氯气氧化溴化钾 ,生成的溴能破坏甲基橙分子结构 ,使在酸性溶液中的甲基橙红色褪去 ,氯气含量越高 ,减色越明显。在用分光光度法测定时 ,吸光值是递减的 ,不同于一般的显色反应。因此 ,在绘制校准曲线时 ,标准系列的吸光值 ,不是通常的Ａ-Ａ0 ,而应采用Ａ0 -Ａ ,由此进行回归方程计算。同理 ,在样品测定时 ,也应以吸收液的吸光值Ａ吸-Ａ所得到的样品吸光值查出相应的含量。绘制氯气校准曲线的方法@丁建刚$泰兴市环境监测站!江苏泰兴225400 @殷红兰$泰兴市环境监测站!江苏泰兴225400 @屈红梅…     

Speciation of arsenic using solid phase extraction cartridges

Various solid phase extraction (SPE) cartridges were investigated for speciation of arsenite [As(III)], arsenate [As(v)], monomethylarsonic acid (MMA) and dimethylarsinic acid (DMA). Cartridges containing different types of sorbent materials were tested for arsenic retention and elution characteristics. Alumina cartridges were found to completely retain all the four target arsenic species, and are suitable for removal and preconcentration purposes. For speciation analysis, different arsenic species were separated on the basis of their selective retention on and elution from specific cartridges. DMA was retained on a resin-based strong cation exchange cartridge and eluted with 1.0 M HCl. MMA and As(v) were both retained on a silica-based strong anion exchange cartridge and sequentially eluted with 60 mM acetic acid (for MMA) and 1.0 M HCl [for As(v)]. As(III) was not retained on either cartridge and remained in solution. Arsenic species in solution and those eluted from the cartridges were subsequently quantified by using flow injection with hydride generation atomic fluorescence spectrometry (FI-HGAFS) and hydride generation atomic absorption spectrometry (FI-HGAAS). A detection limit of 0.05 microg L(-1) arsenic in water sample was achieved using HGAFS. An application of the method was demonstrated at a drinking water treatment facility. As(III) and As(v) species were determined in water at various stages of treatment. The method is suitable for routine determination of trace levels of arsenic in drinking water to comply with more stringent environmental regulations.     

水中Mg~(2+)的测试管快速测定

研制了一种测定水中Mg2 + 的测试管 ,测定范围为 0 .5mg/L～ 2 .0mg/L。该测试管适用于现场应急监测 ,具有快速、简便、抗干扰能力强和价格低廉等特点     

Development of a diffusive sampling method for determination of methyl isocyanate in air

A diffusive sampling method for determination of methyl isocyanate in air has been developed. A glass fibre filter impregnated with 1-(2-methoxyphenyl)piperazine in a commercially available diffusive sampling device was used to collect methyl isocyanate and the derivative formed was analysed with LC-MS/MS. The sampling rate was determined to be 15.6 ml min(-1), with a relative standard deviation of 7.3%. The sampler was validated for sampling periods from 15 min to 8 h, for relative humidities from 20% to 80% and for concentrations from I to 46 microg m(-3). A field validation was also made and the diffusive sampling results showed no difference compared to a pumped reference method. The impregnated filters have to be stored apart from the diffusive sampler housing and loaded into the sampler prior to each sampling.     

Multi-objective, decision-based assessment of a water quality monitoring network in a river system

Water quality monitoring network design has historically tended to use experience, intuition and subjective judgement in locating monitoring stations. Better design procedures to optimize monitoring systems need to simultaneously identify significant planning objectives and consider a number of social, economic and environmental constraints. The consideration of multiple objectives may require further decision analysis to determine the preference weights associated with the objectives to aid in the decision-making process. This may require the application of an optimization study to extract such information from decision makers or experts and to evaluate the overall effectiveness of locating strategies. This paper assesses the optimal expansion and relocation strategies of a water quality monitoring network using a two-stage analysis. The first stage focuses on the information retrieval of preference weights with respect to the designated planning objectives. With the aid of a pre-emptive goal programming model, data analysis is applied to obtain the essential information from the questionnaire outputs. The second stage then utilizes a weighted multi-objective optimization approach to search for the optimal locating strategies of the monitoring stations in the river basin. Practical implementation is illustrated by a case study in the Kao-Ping River Basin, south Taiwan.