Effects of Smoke Emissions from a Charcoal Kiln on the Functioning of Forest Soil Systems: A Microcosm Study

Long-term charcoal production in small private charcoal kilns (CK) in Eastern Bieszczady Mts. (SE Poland) can cause local smoke contamination of the ambient forest environment. Responses of model soil systems, contaminated or not contaminated by CK smoke, to contrasting combinations of hydrothermic regimes were compared in laboratory microcosms (respiration of soil community, decomposition rate of soil organic matter and cotton stripes, herb seeds germination were studied). The majority of the obtained data show a markedly higher level of soil biological activity in the CK versus the control series. In some cases CK and control soil systems show different patterns of reactions to the tested combinations of microclimate regime. These phenomena should at least partly be attributed to the effects of CK pollution.     

Characterisation of Particulate Matter Sampled during a Study of Children's Personal Exposure to Airborne Particulate Matter in a UK Urban Environment

The personal exposure of children aged 9 – 11 years to particulate matter (PM₁₀ and PM_2.5) was carried out between January and September 1997 in the London Borough of Barnet. Personal sampling along with home, garden and classroom microenvironmental monitoring was completed for all ten children. Each child was monitored for five days during winter, spring and summer. All children completed daily time activity diaries to provide information on any potential activities that could influence their exposure to particulate matter. Each evening a household activity questionnaire was also completed by the parents. Personal Environmental Monitors were used to sample personal exposure to PM₁₀ and PM_2.5. Harvard Impactors were used for the microenvironmental sampling of both size fractions. The children's mean personal exposure concentrations for PM₁₀ during winter, spring and summer were 72, 54 and 35 µg/m³ respectively and for PM_2.5 22, 17 and 18 µg/m³ respectively. In order to determine the potential sources of particulate matter, analysis of the Teflon filters has been undertaken. The physical characteristics of the particles have been identified using Scanning Electron Microscopy. The relationships between personal exposure concentrations and the different microenvironments will be discussed.     

Climate change, urban air problems and transport policy in the European Union

This paper surveys some recent studies on conventional air pollution and climate change in the transport sector in Europe. Fuel efficiency standards, car emission standards and transport pricing instruments are analysed from an economic perspective taking into account environmental and economic efficiency objectives. This revised version was published online in July 2006 with corrections to the Cover Date.     

学龄儿童肺功能水平影响因素的研究

用逐步回归分析方法对与室内、外空气污染和机体状况等有关的因素对广州市学龄儿童肺功能 (FVC、FEV1 、PEFR和 FEF2 5～ 75 )水平的影响进行研究。结果提示 ,影响肺功能水平的主要因素是内因 ,身高的影响最明显 ,呼吸系统疾病或症状发生与肺功能水平下降有关 ;室外空气污染使肺功能水平下降 ,SO2 、NOx 和 PM2 .5 的影响明显 ,PM2 .5 的影响明显大于 PM1 0 和 TSP;居室或厨房通风不良、家庭烹饪用不洁燃料对儿童肺功能的生长不利 ;被动吸烟对女性儿童肺功能有不利影响。对各种影响因素 ,PEFR和 FEF2 5～ 75 比 FVC和 FEV1 更为敏感     

兰州市空气污染对儿童肺功能影响的前瞻性研究

从不同的角度阐述了室内外空气污染对儿童肺功能 ,特别是小气道功能的影响及其影响程度的前瞻性研究结果。并通过多因素、多指标的综合分析 ,揭示了一些影响儿童肺功能的主要因素。指出了从保护人体健康的角度来说 ,好的环境空气质量和良好的室内空气质量同样重要     

乌鲁木齐市电磁辐射污染的调查及分析

报道了乌鲁木剂市电磁辐射污染的调查结果,阐明了乌鲁木齐市电磁污染的现状和分析状况,并依据调查结果对各类污染源的电磁泄漏进行了分析讨论。     

伊犁河伊宁市段水质污染特征分析

在对伊犁河伊宁市段历年水质状况进行综合评价的基础上,探讨了城市河段水质的变化规律、污染特征和成因。     

克拉玛依市区大气尘污染研究

对克拉玛依市区大气尘污染的特征及变化规律进行了全面的分析和研究。结果表明,市区的尘污染有加重的趋势,降尘属中度污染,道路尘污 染也较严重。提出了一些具体的防治对策。     

Magnetic mapping of fly-ash pollution and heavy metals from soil samples around a point source in a dry tropical environment

The Singrauli region in the southeastern part of Uttar Pradesh, India is one of the most polluted industrial sites of Asia. It encompasses 11 open cast coalmines and six thermal power stations that generate about 7,500 MW (about 10% of India’s installed generation capacity) electricity. Thermal power plants represent the main source of pollution in this region, emitting six million tonnes of fly-ash per annum. Fly-ash is deposited on soils over a large area surrounding thermal power plants. Fly-ashes have high surface concentrations of several toxic elements (heavy metals) and high atmospheric mobility. Fly ash is produced through high-temperature combustion of fossil fuel rich in ferromagnetic minerals. These contaminants can be identified using rock-magnetic methods. Magnetic susceptibility is directly linked to the concentration of ferromagnetic minerals, primarily high values of magnetite. In this study, magnetic susceptibility of top soil samples collected from surrounding areas of a bituminous-coal-fired power plant were measured to identify areas of high emission levels and to chart the spatial distribution of airborne solid particles. Sites close to the power plant have shown higher values of susceptibility that decreases with increasing distance from the source. A significant correlation between magnetic susceptibility and heavy metal content in soils is found. A comparison of the spatial distribution of magnetic susceptibility with heavy-metal concentrations in soil samples suggests that magnetic measurements can be used as a rapid and inexpensive method for proxy mapping of air borne pollution due to industrial activity.     

Artificial neural network based carbon monoxide persistence models for episodic urban air quality management

This paper describes the development of artificial neural network (ANN) based carbon monoxide (CO) persistence (ANNCOP) models to forecast 8-h average CO concentration using 1-h maximum predicted CO data for the critical (winter) period (November–March). The models have been developed for three 8-h groupings of 10 p.m. to 6 a.m., 6 a.m. to 2 p.m. and 2–10 p.m., at two air quality control regions (AQCRs) in Delhi city, representing an urban intersection and an arterial road consisting heterogeneous traffic flows. The result indicates that time grouping of 2–10 pm is dominantly affected by inversion conditions and peak traffic flow. The ANNCOP model corresponding to this grouping predicts the 8-h average CO concentrations within the accuracy range of 68–71%. The CO persistence values derived from ANNCOP model are comparable with the persistence values as suggested by the Environmental Protection Agency (EPA), USA. This work demonstrates that ANN based model is capable of describing winter period CO persistence phenomena.