室内装修后苯、甲苯、二甲苯和甲醛污染调查

对青岛市装修后房屋空气进行调查,按照装修时间分装修时间1周～6个月、7个月～1年、1年以上三个组,对三组室内空气中苯、甲苯、二甲苯和甲醛进行监测,发现室内装修时间短时苯、甲苯、二甲苯的浓度较高,甲醛浓度较低;随装修时间增长,苯、甲苯、二甲苯的浓度很快降低,但甲醛的浓度呈升高趋势。     

室内空气污染调查

为了解室内空气污染状况，广州市环境监测中心站对刚装修不久的10套私人居室和5家单位办公室的室内空气进行了监测。结果表明，甲醛、苯、NH3、NOx浓度超标，最高超标倍数分别为：甲醛22.0倍，苯3.01倍，NH3 2.58倍，NOx0.30倍。指出，这些污染物主要来源于装修材料和建筑材料，会对人体健康造成危害。提出，为防止室内空气污染，应从源头抓起，装修时尽量选用低毒或无毒的材料，装修后的居室或办公室要保持通风，以降低室内污染物浓度，进驻前请有关权威部门进行监测评估。另外可在室内摆放绿色植物，以吸附一些有毒化合物。     

绍兴市新装修住房空气质量调查与分析

为了解室内装修对室内空气质量的影响,文章随机抽取浙江省绍兴市60户新装修居室进行室内空气主要污染物监测,结果表明,以甲醛和总挥发性有机物(TVOC)超标最为严重,超标率分别为32.2%和65.6%。不同功能房间中,卧室、书房甲醛和总挥发性有机物浓度明显高于客厅。另外,总挥发性有机物与装修后时间长短有很大关系,装修后3个月时,超标率为98.3%,6个月超标率为75.0%,12个月超标率降低到23.3%。     

杭州市居室空气中芳香族化合物污染现状及其来源解析

用热解吸/气质联用技术研究了杭州市居室空气中芳香族化合物的组成。结果表明,杭州市居室空气中共存在60种芳香族化合物,其中苯系化合物48种,非苯芳香族化合物12种,检出率大于50%的23种;苯、甲苯、乙苯、苯乙烯、邻二甲苯、间(对)-二甲苯等10种化合物的总含量之和大于85.39%,是室内空气中主要的芳香族污染物,除萘外,其他22种污染物的平均浓度值均随装修时间间隔延长而降低;污染物主要来源是室内装修过程中使用的或装修材料中残留的有机溶剂、机动车辆排放的尾气、居民家庭中常用的清洁用品及含萘等成分的防蛀剂。     

室内甲醛污染及对人体健康的影响

通过对三种不同类型居室内甲醛监测表明,甲醛浓度与室内装饰、吸烟和燃料的不完全燃烧有关.兰州地区夏季室内甲醛超标率高,为41.0％～51.3％.室内主要污染物除TSP以外,甲醛居第2位,且一天中浓度最高值在中午.新建居室比普通居室甲醛浓度高,在所有情况下,室内浓度高于室外.     

室内空气污染现状与特征研究

对几种典型室内空气质量进行监测，并就室内装修对空气质量的影响进行了研究，结果表明，室内空气质量状况不容乐观，PM10是不同类型室内空气的共同特征污染因子，PM10和细菌总数是公共场所的特征污染因子，室内装修是造成甲醛和苯系物等挥发性有机物污染的主要原因。     

综合评价室内空气质量初探

阐述了现行室内空气质量评价方法存在的不足,通过分析比较,确定了利用计权型多因子环境质量评价指数进行室内空气质量的综合评价方法.根据当前由于室内装修引起的室内空气污染特点,选择了甲醛、氨气、苯、甲苯、二甲苯和总挥发性有机物等6项指标作为评价因子,各评价因子的权重系数用其危害等级计算得到.     

承德市室内环境质量污染现状调查与研究

对承德市160家宾馆、饭店、歌舞厅等公共场所,80个民用建筑工程项目,80余家个人家庭装修进行室内环境检测,发现不同场所室内主要超标污染物不同。新建公共场所和个人家装室内空气主要污染物为总挥发性有机物、甲醛、苯、氨,已建成的重点公共场所空气超标污染物主要为二氧化碳、菌落总数,民用建筑工程超标污染物主要为氨。     

关注室内装修中的甲醛污染

文中主要阐述了室内装修中甲醛污染的产生、危害及其防治。     

室内装饰装修材料中苯、甲苯、二甲苯含量测定法改进

采用毛细管气相色谱法,对室内装饰装修材料中的苯、甲苯、二甲苯的测定进行了改进。称取样品后,用N,N-二甲基甲酰胺稀释定容,CBP20毛细管柱分离,可同时测定苯、甲苯、二甲苯的含量,数据准确,操作简单。     

Relationship between Pb and Cd accumulations in house crow,their habitat,and food content from Klang area,Peninsular Malaysia

Heavy metal pollution has become a global concern due to accumulation in tissue and transferable effects to humans via the food chain. This study focused on monitoring the accumulation of cadmium (Cd) and lead (Pb) in surface soil and body content: bone, heart, brain, liver, lung, muscle, kidney, feathers, feces, and gizzard contents of house crow Corvus splendens in the Klang region, Malaysia. The results revealed the occurrence of Pb and Cd in all biological samples from house crows, food contents, and surface soil samples. Heart and kidney accrued high amounts of Cd, while high amounts of Pb were found to accumulate in bones and feathers. Major discrepancies were also discovered in the concentrations of metals between juvenile and adults, as well as female and male bird samples. Concentrations of Pb and Cd in house crow internal tissues correlated significantly with that of bird feathers, but none could be established with that of surface soil. In addition, a significant correlation was observed between Pb concentration in the internal tissues to that of the feces, but the same was not the case when compared with the surface soil concentration. Metal accrual in the house crows feathers and feces may be through a long-term transmission via the food chain, which are eliminated from feathers via molting. This may suggest the utility of molted breast feathers of house crow in the bio-monitoring of Cd and Pb contamination, whereas feces of house crow appear only to be suitable for the bio-monitoring of Pb contamination.     

Northern Idaho House Dust and Soil Lead Levels Compared to the Bunker Hill Superfund Site

House dust has been identified as a major exposure medium for lead (Pb) in children. High levels of Pb in soil and house dust have been recorded at the Bunker Hill Superfund Site (BHSS) in northern Idaho, an historic mining and smelting district. Soil and dust remediation at the site was required; however, regional background soil and dust Pb levels had not been well characterized. The objective of this survey was to determine background house dust Pb levels and to compare those levels with concentrations, and dust and Pb loading rates measured at the BHSS. Soil and house dust samples were collected in five towns demographically similar to the BHSS but unaffected by the mining industry. The background concentrations and loading rates were significantly lower than those observed at the site. House age was a significant factor affecting background soil and house dust Pb concentrations and loading rates.     

Mineralogy of Atmospheric Suspended Dust in Three Indoor And One Outdoor Location in Oman

The aim of this work is to characterize the mineral phases present in the atmosphere at three locations in northern Oman. Samples of atmospheric particles were collected using a high volume sampler. Three indoor and one outdoor location were chosen in this investigation. Sampling locations included a residential house located nearby the cement plant, a residential house located nearby a refinery plant, and a residential house located at Al-Suwayq residential area. Indoor air was sampled from these three houses. Moreover, for the Al-Suwayq residential house, sampling was also taken outside the house for comparison. The dust samples were analysed for their microanalysis characterization and their mineral contents as well. The microanalysis enabled us to identify the metals present in the particles. Furthermore, the mineralogical analysis of the sample filters showed the presence of quartz as the principal phase inside the house of Al-Suwayq, whereas quartz, dolomite, and gypsum were common phases outside the house. In the residential house nearby the cement plant, it was found that calcite, quartz, dolomite and goethite were the principal phases whereas the particles collected from the house nearby the refinery composed primarily of dolomite and calcite. The airborne dust collected at the refinery and Al-Suwayq were probably sourced in the natural environment and mobilised by natural processes. However, at the cement factory the crushing and grinding of limestone during the industrial process has contributed significantly to the airborne dust load. Generally, the information obtained in this study will be invaluable as no data for the mineral content of atmospheric dust existed in the Oman.     

Occurrence of perfluorosulfonates and other perfluorochemicals in dust from selected homes in the city of Ottawa, Canada

A series of perfluorinated compounds (PFCs) including perfluorooctane sulfonate (PFOS) and perfluorooctanoic acid (PFOA) have been recently measured in a variety of environmental samples and biological matrices. In order to better understand the human exposure routes of these chemicals, levels of PFOS, PFOA, perfluorobutane sulfonate (PFBS), perfluorohexane sulfonate (PFHS) and perfluorooctane sulfonamide (PFOSA) in house dust samples were investigated. The data revealed a correlation between the concentrations of PFCs and the percentage of carpeting in the house; older houses tended to have less carpeting, hence lower levels of these perfluorinated compounds in their dust.     

PM1 and PM2.5 ionic composition and VOCs measurements in two typical apartments in Athens, Greece: investigation of smoking contribution to indoor air concentrations

During the last decades, the air quality of the city of Athens has been quite aggravated. Scientific interest has been focused on health effects caused by both outdoor and indoor air pollution. The purpose of this study was the presentation of results from air quality measurements in two similar typical Athenian apartments in the same suburban area. In addition, smoking contribution is investigated, as it is the main factor which differentiates the two apartments. The results showed that it is the outdoor environment that mainly contributes to the air quality of the non-smokers’ house. In the second apartment, PM_2.5, PM₁, and benzene concentrations were found significantly higher due to smoking activity. In contrast, no clear difference in particulate matter ionic composition between the two areas was observed, although in the smoker’s house, ion concentrations were found elevated. This observation amplifies the assumption that in the smoker’s apartment, significant outdoor sources’ contribution cannot be excluded.     

Artificial Neural Networks for Risk Decision Support in Natural Hazards: A Case Study of Assessing the Probability of House Survival from Bushfires

Risk decision-making in natural hazards encompasses a plethora of environmental, socio-economic and management-related factors, and benefits greatly from exploring possible patterns and relations among these multivariate factors. Artificial neural networks, capable of general pattern classifications, are potentially well suited for risk decision support in natural hazards. This paper reports an example that assesses the risk patterns or probabilities of house survival from bushfires using artificial neural networks, with a simulation data set based on the empirical study by Wilson and Ferguson (Predicting the probability of house survival during bushfires, Journal of Environmental Management 23 (1986) 259–270). The aim of this study was to re-model and predict the relationship between risk patterns of house survival and a series of independent variables. Various configurations for input and output variables were tested using neural networks. An approach for converting linguistic terms into crisp numbers was used to incorporate linguistic variables into the quantitative neural network analysis. After a series of tests, results show that neural networks are capable of predicting risk patterns under all tested configurations of input and output variables, with a great deal of flexibility. Risk-based mathematical functions, be they linear or non-linear, can be re-modelled using neural networks. Finally, the paper concludes that the artificial neural networks serve as a promising risk decision support tool in natural hazards.     

Artificial Neural Networks for Risk Decision Support in Natural Hazards: A Case Study of Assessing the Probability of House Survival from Bushfires

Risk decision-making in natural hazards encompasses a plethora of environmental, socio-economic and management-related factors, and benefits greatly from exploring possible patterns and relations among these multivariate factors. Artificial neural networks, capable of general pattern classifications, are potentially well suited for risk decision support in natural hazards. This paper reports an example that assesses the risk patterns or probabilities of house survival from bushfires using artificial neural networks, with a simulation data set based on the empirical study by Wilson and Ferguson (Predicting the probability of house survival during bushfires, Journal of Environmental Management 23 (1986) 259–270). The aim of this study was to re-model and predict the relationship between risk patterns of house survival and a series of independent variables. Various configurations for input and output variables were tested using neural networks. An approach for converting linguistic terms into crisp numbers was used to incorporate linguistic variables into the quantitative neural network analysis. After a series of tests, results show that neural networks are capable of predicting risk patterns under all tested configurations of input and output variables, with a great deal of flexibility. Risk-based mathematical functions, be they linear or non-linear, can be re-modelled using neural networks. Finally, the paper concludes that the artificial neural networks serve as a promising risk decision support tool in natural hazards.     

Evaluation of lot-to-lot repeatability and effect of assay media choice in the recombinant Factor C assay

Measurement of environmental endotoxin exposures is complicated by variability encountered using current biological assay methods arising in part from lot-to-lot variability of the Limulus-amebocyte lysate (LAL) reagents. Therefore, we investigated the lot-to-lot repeatability of commercially available recombinant Factor C (rFC) kits as an alternative to LAL. Specifically, we compared endotoxin estimates obtained from rFC assay of twenty indoor dust samples, using four different extraction and assay media, to endotoxin estimates previously obtained by Limulus amebocyte lysate (LAL) assay and amounts of 3-hydroxy fatty acids (3-OHFA) in lipopolysaccharide (LPS) using gas-chromatography mass spectroscopy (GC-MS). We found that lot-to-lot variability of the rFC assay kits does not significantly alter endotoxin estimates in house dust samples when performed using three of the four assay media tested and that choice of assay media significantly altered endotoxin estimates obtained by rFC assay of house dust samples. Our findings demonstrate lot-to-lot reproducibility of rFC assay of environmental samples and suggest that use of rFC assay performed with Tris buffer or water as the extraction and assay medium for measurement of endotoxin in dust samples may be a suitable choice for developing a standardized methodology.     

乌鲁木齐市室内环境空气污染成因及防治对策

为进一步掌握室内环境空气污染状况，对乌鲁木齐市毛坯房、公共场所和居民住宅的室内环境空气质量现状进行了监测统计，并调查了居民的健康状况，分析了室内空气污染的原因。监测结果表明，乌鲁木齐市新装修房屋室内环境污染较严重。对此提出了不同污染状况的防治对策。     

Development and field trial of a household surface lead loading rate sampling device in a lead-contaminated community of southern Thailand

A new dust-collecting device was developed to assess surface lead loading rates in houses in communities contaminated with lead oxide dust used for caulking in nearby boat-repair yards. The device consists of two small glass sheets with total area of 1,200 cm² placed in two plastic trays suspended from the ceiling in the house for 3 months before wiping and sending the dust specimen for determination of lead content using flame atomic absorption spectrophotometry. After a pilot trial in four households, further data were collected from 43 matched pairs of boat-caulkers’ and neighboring control households. All devices were retained in the house for 3 months without any complaint. Static measurements of lead dust levels were also assessed in all households. The values significantly discriminated high from low lead exposure households (p = 0.015) and provided good correlations with floor lead loading (Spearman rank correlation coefficient, r = 0.39 to 0.62) and dust lead content (r = 0.53 to 0.64). This sampling method is an alternative to others which consume more household space or require a longer collection period.