Indoor Air Quality of Public Places in Mumbai, India in Terms of Volatile Organic Compounds

Indoor air quality at nine locations viz. food courts, restaurant, bar, conference room, office and theater, which can be classified as public places have been monitored for Volatile Organic Compounds (VOCs) content. Forty VOCs have been identified and one fourth of these are classified as Hazardous Air Pollutants. Levels of most VOCs are observed to be below the guideline values for public places and offices, as adopted by Hong Kong. Consumer goods are found to be predominant source of chlorinated VOCs in indoor air. Levels of benzene and carbon tetrachlorides were observed to be above the guideline values at all the locations. Effect of ozonisation on Total VOC concentrations have also been studied.     

Mathematical models for accurate prediction of atmospheric visibility with particular reference to the seasonal and environmental patterns in Hong Kong

Atmospheric visibility impairment has gained increasing concern as it is associated with the existence of a number of aerosols as well as common air pollutants and produces unfavorable conditions for observation, dispersion, and transportation. This study analyzed the atmospheric visibility data measured in urban and suburban Hong Kong (two selected stations) with respect to time-matched mass concentrations of common air pollutants including nitrogen dioxide (NO(2)), nitrogen monoxide (NO), respirable suspended particulates (PM(10)), sulfur dioxide (SO(2)), carbon monoxide (CO), and meteorological parameters including air temperature, relative humidity, and wind speed. No significant difference in atmospheric visibility was reported between the two measurement locations (p > or = 0.6, t test); and good atmospheric visibility was observed more frequently in summer and autumn than in winter and spring (p < 0.01, t test). It was also found that atmospheric visibility increased with temperature but decreased with the concentrations of SO(2), CO, PM(10), NO, and NO(2). The results showed that atmospheric visibility was season dependent and would have significant correlations with temperature, the mass concentrations of PM(10) and NO(2), and the air pollution index API (correlation coefficients mid R: R mid R: > or = 0.7, p < or = 0.0001, t test). Mathematical expressions catering to the seasonal variations of atmospheric visibility were thus proposed. By comparison, the proposed visibility prediction models were more accurate than some existing regional models. In addition to improving visibility prediction accuracy, this study would be useful for understanding the context of low atmospheric visibility, exploring possible remedial measures, and evaluating the impact of air pollution and atmospheric visibility impairment in this region.     

Indoor air quality assessment in child care and medical facilities in Korea

In order to characterize the status of indoor air pollution in some important facilities, a list of key criteria pollutants [particulate matter (PM(10)), carbon dioxide (CO(2)), carbon monoxide (CO), formaldehyde (HCHO), and bioaerosol] was measured from a total of 91 randomly selected sites in 18 different cities, Korea (February 2006 to December 2009). The target facilities include 43 child care facilities, 38 medical facilities, 6 elementary schools, and 4 postnatal care centers. The results showed that some air pollutants (e.g., CO and HCHO) did not exceed the recommended guideline [e.g., the Korean indoor air standard (KIAS) values of 10 ppm and 100 ppb, respectively]. However, concentration of PM(10), CO(2), and bioaerosol occasionally exceeded their respective guidelines (e.g., seven, three, and two cases). Discrete seasonalities were observed from indoor pollutants because of varying ventilation practice (e.g., summer time dominance of PM(10), HCHO, and bioaerosol or winter dominance of CO(2) and CO). However, as the concentrations of the indoor pollutants were scarcely above the recommended guideline level, more diversified approaches are desirable to diagnose the status of indoor pollution and to provide a realistic strategy for the improvement of IAQ.     

Qualitative Detection of Volatile Organic Compounds in Outdoor and Indoor Air

The present work attempts to identify VOC's in outdoor and indoor air in Mumbai City India. Ambient air was adsorbed on especially fabricated stainless steel cartridge packed with activated coconut charcoal at uniform flow rate. Qualitative identification of VOC's was done by thermally desorbing air from the cartridges and subsequent analysis on Varian GC-MS using NIST Library. The outdoor monitoring locations include residential area, commercial area, industrial, airport, petrol pumps, traffic junctions, arterial roads, highways, slums, parking area, service garages and municipal dump sites. The indoor locations comprised of air-conditioned and non air-conditioned offices, bedrooms, shops and instrumentation laboratory. The identified VOC's include aldehydes, ketones, polynuclear aromatic hydrocarbons, aromatic acids, oxygenated hydrocarbons, amines, esters and halogenated compounds. Thirteen VOCs in outdoor air and seven in indoor air amongst those identified, figure in the list of Hazardous Air Pollutants listed in Title III of the U.S. EPA Clean Air Act Amendments of 1990.     

Assessment of microbiological indoor air quality in an Italian office building equipped with an HVAC system

The purpose of this study was to evaluate the level and composition of bacteria and fungi in the indoor air of an Italian office building equipped with a heating, ventilation and air conditioning (HVAC) system. Airborne bacteria and fungi were collected in three open-space offices during different seasons. The microbial levels in the outdoor air, supply air diffusers, fan coil air flow and air treatment unit humidification water tank were used to evaluate the influence of the HVAC system on indoor air quality (IAQ). A medium–low level of bacterial contamination (50–500 CFU/m³) was found in indoor air. Staphylococcus and Micrococcus were the most commonly found genera, probably due to human presence. A high fungal concentration was measured due to a flood that occurred during the winter. The indoor seasonal distribution of fungal genera was related to the fungal outdoor distribution. Significant seasonal and daily variation in airborne microorganisms was found, underlining a relationship with the frequency of HVAC system switching on/off. The results of this monitoring highlight the role of the HVAC system on IAQ and could be useful to better characterise bacterial and fungal population in the indoor air of office buildings.     

Receptor modeling for analyzing PCDD/F and dioxin-like PCB sources in Hong Kong

A total of 96 ambient air samples were collected from January 2004 to December 2004 for the investigation of dioxins (polychlorinated dibenzo-para-dioxins and polychlorinated dibenzofurans [PCDD/Fs]) and dioxin-like profile for polychlorinated biphenyls (PCBs) in the atmosphere of Hong Kong. Two-day back-trajectories were obtained using the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model from National Oceanic and Atmospheric Administration (NOAA) Air Resources Laboratory. Receptor models – potential source contribution function (PSCF) and concentration-weighted trajectory (CWT) – were built based on the measured PCDD/Fs and dioxin-like PCBs total toxic equivalent (TEQ) concentrations. Both models were modified in this study so as to integrate the information obtained from three sampling sites in Hong Kong. The PSCF modeling resolved two main PCDD/F and dioxin-like PCB polluting paths from Mainland China. In line with previous studies, the northerly path around the Pearl River Delta might be one of the pollution sources of Hong Kong air. On the other hand, the receptor models also indicated another potential northeasterly source from Yangtze River Delta, which was seldom mentioned as the source region of Hong Kong air. Results from the CWT modeling suggested that the most toxic air mass affecting Hong Kong is probably attributable to the northeast path rather than the north path.     

Calibration of two passive air sampler configurations for monitoring concentrations of hexabromocyclododecanes in indoor air

While polyurethane foam (PUF) disk passive air samplers are employed increasingly to monitor persistent organic pollutants in indoor air, they essentially sample only the vapour phase. As a previous investigation of the vapour : particle phase partitioning of hexabromocyclododecanes HBCDs in (outdoor) air reported them to be present largely in the particulate phase, we monitored three offices using active air samplers. In each, approximately 65% of HBCDs were present in the vapour phase, suggesting PUF disk passive samplers are suitable for monitoring HBCDs in indoor air. Concentrations in the three offices (239-359 pg Sigma HBCD m(-3)) exceed substantially those reported in outdoor air from the United States (2.1-11 pg Sigma HBCD m(-3)), but are in line with outdoor air from Stockholm. The relative abundance of the three principal diastereomers in office air was closer to that found in technical HBCD formulations (i.e. predominantly gamma-HBCD) than in most US outdoor air samples. Time integrated air concentrations of alpha-, beta-, and gamma-HBCD were obtained for an office using a low volume sampler operated over a 50 d period alongside PUF disk samplers. This calibration exercise yielded the following passive air sampling rates for both a fully- and part-sheltered PUF disk sampler design: for alpha-, beta-, and gamma-HBCD, 0.87, 0.89, and 0.91 m3 d(-1) respectively (fully-sheltered) and 1.38, 1.54, and 1.55 m3 d(-1) respectively (part-sheltered). Deployment of the part-sheltered configuration yielded concentrations approximately 35% lower than those obtained using a high volume sampler, consistent with PUF disk samplers measuring primarily the vapour phase.     

Using improved neural network model to analyze RSP,NOx and NO2 levels in urban air in Mong Kok,Hong Kong

As the health impact of air pollutants existing in ambient addresses much attention in recent years, forecasting of airpollutant parameters becomes an important and popular topic inenvironmental science. Airborne pollution is a serious, and willbe a major problem in Hong Kong within the next few years. InHong Kong, Respirable Suspended Particulate (RSP) and NitrogenOxides NO_x and NO₂ are major air pollutants due to thedominant diesel fuel usage by public transportation and heavyvehicles. Hence, the investigation and prediction of the influence and the tendency of these pollutants are ofsignificance to public and the city image. The multi-layerperceptron (MLP) neural network is regarded as a reliable andcost-effective method to achieve such tasks. The works presentedhere involve developing an improved neural network model, whichcombines the principal component analysis (PCA) technique and theradial basis function (RBF) network, and forecasting thepollutant levels and tendencies based in the recorded data. Inthe study, the PCA is firstly used to reduce and orthogonalizethe original input variables (data), these treated variables arethen used as new input vectors in RBF neural network modelestablished for forecasting the pollutant tendencies. Comparingwith the general neural network models, the proposed modelpossesses simpler network architecture, faster training speed,and more satisfactory predicting performance. This improvedmodel is evaluated by using hourly time series of RSP, NO_x and NO₂ concentrations collected at Mong Kok Roadside Gaseous Monitory Station in Hong Kong during the year 2000. By comparing the predicted RSP, NO_x and NO₂ concentrationswith the actual data of these pollutants recorded at the monitorystation, the effectiveness of the proposed model has been proven.Therefore, in authors' opinion, the model presented in the paper is a potential tool in forecasting air quality parameters and hasadvantages over the traditional neural network methods.     

Indoor air quality during renovation actions: a case study

A temporary renovation activity releases considerably high concentrations of particulate matter, viable and non-viable, into air. These pollutants are a potential contributor to unacceptable indoor air quality (IAQ). Particulate matter and its constituents lead, sulfate, nitrate, chloride, ammonium and fungi as well as fungal spores in air were evaluated in a building during renovation action. Suspended dust was recorded at a mean value of 6.1 mg m(-3) which exceeded the Egyptian limit values for indoor air (0.15 mg m(-3)) and occupational environments (5 mg m(-3)). The highest particle frequency (23%) of aerodynamic diameter (dae) was 1.7 microm. Particulate sulfate (SO(4)(2-)), nitrate (NO(3)(-)), chloride (Cl(-)), ammonium (NH(4)(+)) and lead components of suspended dust averaged 2960, 28, 1350, 100 and 13.3 microg m(-3), respectively. Viable fungi associated with suspended dust and that in air averaged 1.11 x 10(6) colony forming unit per gram (cfu g(-1)) and 92 colony forming unit per plate per hour (cfu p(-1) h(-1)), respectively. Cladosporium(33%), Aspergillus(25.6%), Alternaria(11.2%) and Penicillium(6.6%) were the most frequent fungal genera in air, whereas Aspergillus(56.8%), Penicillium(10.3%) and Eurotium(10.3%) were the most common fungal genera associated with suspended dust. The detection of Aureobasidium, Epicoccum, Exophiala, Paecilomyces, Scopulariopsis, Ulocladium and Trichoderma is an indication of moisture-damaged building materials. Alternaria, Aureobasidium, Cladosporium, Scopulariopsis and Nigrospora have dae > 5 microm whereas Aspergillus, Penicillium and Verticillium have dae < 5 microm which are suited to penetrate deeply into lungs. Particulate matter from the working area infiltrates the occupied zones if precautionary measures are inadequate. This may cause deterioration of IAQ, discomfort and acute health problems. Renovation should be carefully designed and managed, in order to minimize degradation of the indoor and outdoor air quality.     

川东北中心城市南充大气污染态势及其主要成因

基于南充市主城区6项大气污染物浓度数据,研究了2014-2020年南充市的空气质量指数、空气质量指数等级和首要污染物的时序分布。结果表明:随着大气污染防治的开展,南充市大气污染物浓度逐渐下降,出现首要污染物的天数逐年减少,空气质量逐步提高。受污染物节律性影响,空气质量呈现明显的季节差异,冬季空气质量最差,春季次之,夏季污染相对较轻,秋季最轻。首要污染物类型的季节分布特征表现为冬季出现首要污染物天数最多,春季和夏季次之,秋季最少。春、秋、冬季以PM_2.5污染为主,夏季以O₃污染为主。从全年来看,与O₃相比,PM_2.5对空气质量的影响更为突出。在持续控制大气污染物排放总量的同时,精细化协同管控细颗粒物、氮氧化物、挥发性有机物和二氧化硫排放将有助于现阶段的大气污染防治。     

粤港珠江三角洲区域空气质量联动监测系统质控技术

空气污染日益呈现的区域性特点,使得空气质量区域联动监测成为必然趋势.以粤港珠江三角洲区域空气质量监控网络的实践为例,介绍了区域联动监测系统的组成和运行机制,并着重探讨了系统质量保证/质量控制(QA/QC)以及数据管理等核心支撑技术.     

O3自动监测的技术要点

通过多年在粤港空气监控系统中的O3自动监测实践,阐述了O3标准气浓度传递认证的范例性解决方案,并在O3气体样品输送、O3分析仪器性能维护及在线检查校准用标准气等方面提出了实用的技术方法。     

A systematic indoor air quality audit approach for public buildings

Good indoor air quality (IAQ) in buildings provides a comfortable and healthy environment for the occupants to work, learn, study, etc. Therefore, it is important to ascertain the IAQ status in the buildings. This study is aimed to establish and demonstrate the comprehensive IAQ audit approach for public buildings, based on Portugal national laws. Four public buildings in Portugal are used to demonstrate the IAQ audit application. The systematic approach involves the measurement of physical parameters (temperature, relative humidity, and concentration of the suspended particulate matter), monitoring of the concentrations of selected chemical indicators [carbon dioxide (CO₂), carbon monoxide, formaldehyde, ozone, and total volatile organic compounds], and the measurements of biological indicators (bacteria and fungi). In addition, air exchange rates are measured by the concentration decay method using metabolic CO₂ as the tracer gas. The comprehensive audits indicated some situations of common IAQ problems in buildings, namely: (1) insufficient ventilation rate, (2) too high particle concentration; and (3) poor filtration effectiveness and hygienic conditions in most of the air handling units. Accordingly, a set of recommendations for the improvement of IAQ conditions were advised to the building owner/managers.     

Forecasts using Box–Jenkins models for the ambient air quality data of Delhi City

The monthly maximum of the 24-h average time-series data of ambient air quality-sulphur dioxide (SO(2)), nitrogen dioxide (NO(2)) and suspended particulate matter (SPM) concentration monitored at the six National Ambient Air Quality Monitoring (NAAQM) stations in Delhi, was analysed using Box-Jenkins modelling approach (Box et al. 1994). Univariate linear stochastic models were developed to examine the degree of prediction possible for situations where only the past record of pollutant data are available. In all, 18 models were developed, three for each station for each of the respective pollutant. The model evaluation statistics suggest that considerably satisfactory real-time forecasts of pollution concentrations can be generated using the Box-Jenkins approach. The developed models can be used to provide short-term, real-time forecasts of extreme air pollution concentrations for the Air Quality Control Region (AQCR) of Delhi City, India.     

香港的空气污染指数预报

介绍了香港空气污染指数预报的方法和所取得的良好社会效果。通过香港空气污染指数预报的学习结合内地环境保护工作的情况，谈了几点体会。     

Cluster analysis of Delhi's ambient air quality data

The purpose of this study was to study the spatial patterns of ambient air quality in Delhi in the absence of extensive datasets needed for space-time modeling. A spatial classification was attempted on the basis of ambient air quality data of nine years (1998 is latest year for which published data were available) for three criteria pollutants--nitrogen dioxide, sulfur dioxide, and suspended particulate matter. Monitoring stations take 24-hour samples twice a week. Published monthly average concentration data were used in this study. A hierarchical agglomerative algorithm using the average linkage between groups method and the Euclidean distance metric was used. Cluster analysis indicated that till 1998, by and large, two distinct classes existed. The results of cluster analysis prompted an investigation of systematic biases in the monitored data. No statistically significant differences in the mean concentration of all pollutants were observed between stations belonging to different land-use types (residential and industrial). This fact would be useful, if and when the authorities consider modifying the network or expanding it in Delhi. The results also support the recommendation that Delhi have a uniform standard across all areas. This study has provided a methodology for Indian researchers and practitioners to do an exploratory study of spatial patterns of air pollution and data quality issues in Indian cities using the National Ambient Air Quality Monitoring System data.     

An air quality balance index estimating the total amount of air pollutants at ground level

A new index named Air Quality Balance Index (AQBI), which is able to characterise the amount of pollution level in a selected area, is proposed. This index is a function of the ratios between pollutant concentration values and their standards; it aims at identifying all situations in which there is a possible environmental risk even when several pollutants are below their limit values but air quality is reduced. AQBI is evaluated by using a high-resolution three-dimensional dispersion model: the air concentration for each substance is computed starting from detailed emissions sources: point, line and area emissions hourly modulated. This model is driven with accurate meteorological data from ground stations and remote sensing systems providing vertical profiles of temperature and wind; these data are integrated with wind and temperature profiles at higher altitudes obtained by a Local Area Model. The outputs of the dispersion model are compared with pollutant concentrations provided by measuring stations, in order to recalibrate emission data. A three-dimensional high resolution grid of AQBI data is evaluated for an industrial area close to Alessandria (Northern Italy), assessing air quality and environmental conditions. Performance of AQBI is compared with the Air Quality Index (AQI) developed by the U.S. Environmental Protection Agency. AQBI, computed taking into account all pollutants, is able to point out situations not evidenced by AQI, based on a preset limited number of substances; therefore, AQBI is a good tool for evaluating the air quality either in urban and in industrial areas. The AQBI values at ground level, in selected points, are in agreement with in situ observations.     

An Index to Measure Depreciation in Air Quality in Some Coal Mining Areas of Korba Industrial Belt of Chhattisgarh, India

The comparison with National Ambient Air Quality Standards does not always depict a true pic-ture of the Air Quality Status of a study area. As an alternative an index that measures depreciation in Air Quality on more realistic terms has been proposed and applied to the ambient air monitoring data collected from some areas of Korba Coalfields in India. Results have been discussed in detail to illustrate the applica-tion of the proposed index and utility in bringing out more realistic air quality assessment.     

Air Quality Status of Visakhapatnam (India) – Indices Basis

Industrial development in Visakhapatnam is conspicuous to urban agglomeration and the city is located in a topographical bowl formed by two-hill ranges. A major portion of the city is within the bowl area wherein most of the industrial and commercial activities are existing and lies within a distance of 10 km from the shore of the Bay of Bengal. Due to the peculiar geographic location of city, wind movement is either eastern or western and is engulfed within the hill ranges. Hence, there is a possibility of buildup of air pollution levels within the city. Due to gravity of prevailing situation, air quality status of Visakhapatnam on indices basis is analyzed using a non-linear equation for variable parameters i.e. Suspended particulate matter (SPM). Sulfur dioxide (SO2) and Oxides of nitrogen (NO(x)), which are main criteria pollutants in India. For current analysis seasonal air quality data is used, which indicates SPM values in winter at most of the sites and in summer at few sites are exceeding the prescribed standards. Calculated indices reveal that, in winter as well as in summer, most of the locations experienced poor or bad air quality, which is mainly due to higher concentration of SPM and certain extent of SO2 values. Application of Oak Ridge Air Quality Index (ORAQI) type equations (non-linear) are helpful for air quality management plan in the region on long-term basis and it has been also observed that there are certain lapses of weightage assignment for individual pollutant in application.     

Airborne particulate matter and BTEX in office environments

Total suspended particulate (TSP), PM(2.5) and BTEX were collected in nine offices in the province of Antwerp, Belgium. Both indoor and outdoor aerosol samples were analysed for their weight, elemental composition, and water-soluble fraction. Indoor TSP and PM(2.5) concentrations ranged from 7-31 microg m(-3) and 5-28 microg m(-3), with an average of 18 and 11 microg m(-3), respectively. Of all the elements analysed in indoor TSP, more than 95% was represented by Al, Si, K, Ca, Fe, Cl and S, accounting for 12% of the TSP by mass. The other elements showed significant enrichment relative to the earth's crust. The water-soluble ionic fraction accounted for almost 30% of the sampled indoor TSP by weight, and was enriched by anthropogenic activities. It was shown that the indoor PM levels varied among the offices, depending on the ventilation pattern, location, and occupation density of the office. Indoor BTEX levels ranged together from 5-47 microg m(-3) and were considerably higher than the corresponding outdoor levels. It was observed that some recently constructed and renovated buildings were clearly burdened with elevated levels for toluene, ethyl benzene, and xylenes, while outdoor air was found to be the main source for BTEX levels at the 'older' offices.