Air pollution exposure monitoring and estimation. Part V. Traffic exposure in adults

In Oslo, traffic has been one of the dominating sources of air pollution in the last decade. In one part of the city where most traffic collects, two tunnels were built. A series of before and after studies was carried out in connection with the tunnels in use. Dispersion models were used as a basis for estimating exposure to nitrogen dioxide and particulate matter in two fractions. Exposure estimates were based on the results of the dispersion model providing estimates of outdoor pollutant concentrations on an hourly basis. The estimates represent concentrations in receptor points and in a square kilometre grid. The estimates were used to assess development of air pollution load in the area, compliance with air quality guidelines, and to provide a basis for quantifying exposure-effect relationships in epidemiological studies. After both tunnels were taken in use, the pollution levels in the study area were lower than when the traffic was on the surface (a drop from 50 to 40 micrograms m-3). Compliance with air quality guidelines and other prescribed values has improved, even if high exposures still exist. The most important residential areas are now much less exposed, while areas around tunnel openings can be in periods exposed to high pollutant concentrations. The daily pattern of exposure shows smaller differences between peak and minimum concentrations than prior to the traffic changes. Exposures at home (in the investigation area) were reduced most, while exposures in other locations than at home showed only a small decrease. Highest hourly exposures are encountered in traffic.     

A comparative study of respirable particulate microenvironmental concentrations and personal exposures

Personal monitoring (PM) for respirable suspended particulate matter (RSP) of thirty subjects was performed as part of an air pollution health effects study conducted in Houston, Texas. Parallel RSP measurements were performed in the study subjects' homes and two fixed site monitoring stations. The participants' daytime activities were independently recorded by study techicians. These data were used to characterize RSP concentrations in each microenvironment visited by the participants. Four estimates of daytime exposure to RSP were calculated based on two different microenvironmental models, and home and fixed site mean daytime RSP concentrations. These estimates were compared to mean daytime personal exposure from PM. Hourly estimates of exposure were calculated from a microenvironmental model and mean hourly home RSP concentrations and compared to hourly PM data. The results of the study indicate that, as in the case of NO₂, it is important to characterize indoor microenvironmental RSP concentrations according to location, sources, and concurrent activities, both qualitatively and quantitatively. Stratification of concentrations according to sources present and self-reported activity can lead to misclassification of exposures. For RSP and, probably, other pollutants with indoor sources and with short exposure integration times, adequate measures of exposure can only be obtained with very detailed and complex microenvironmental models or comprehensive personal monitoring.     

Air pollution exposure monitoring and estimating. Part I. Integrated air quality monitoring system

This paper presents an integrated exposure monitoring system, based on an expansion of existing air quality monitoring systems using dispersion modelling. The system allows: (1) identifying geographical areas whose inhabitants are most exposed to ambient pollution; (2) identifying how many people in an area are exposed to concentrations of pollution exceeding air quality guidelines; (3) describing the exposure of population subgroups (e.g. children); (4) planning pollution abatement measures and quantifying their effects; (5) establishing risk assessment and management programs, and (6) investigating the short- and long-term effects of both pollutants and pollution sources on public health. The effect of pollution is rarely very large and in order to discover it, exposure estimation must provide data that reflects both spatial and temporal variations. Estimates of pollution exposure are obtained using an integrated approach that combines results of measurements from monitoring programs with dispersion calculations. These values can serve as estimates for individual short-term or long-term exposure. The grouped data allows the expression of ambient pollution concentrations as the spatial distribution of estimates such as the mean or 98th percentile of such compounds as SO2, O3, NO2, PM10 and PM2.5. This integrated approach has been combined into a single software package, AirQUIS.     

Estimated distributions of personal exposure to respirable particles

A method of estimating distributions of exposure to respirable particles is presented. Using pollutant monitoring data from outdoors and indoors, time-activity data and a time-weighted exposure model, means and variances for exposure distributions are generated. Variances are estimated using Gauss' law of error propagation. The model is calibrated using data from a personal monitoring study. Estimated distributions of exposure to respirable particles for children in six cities living in homes with and without smokers are presented. The implications of these estimates for air pollution epidemiology and needs for further research are discussed.     

Do the pollution related to high-traffic roads in urbanised areas pose a significant threat to the local population?

Many large neighbourhoods are located near heavy-traffic roads; therefore, it is necessary to control the levels of air pollution near road exposure. The primary air pollutants emitted by motor vehicles are CO, NO₂ and PM. Various investigations identify key health outcomes to be consistently associated with NO₂ and CO. The objective of this study was the measurement-based assessment for determining whether by high-traffic roads, such as motorways and express ways, and the concentrations of CO and NO₂ are within normal limits and do not pose threat to the local population. Average daily values (arithmetic values calculated for 1-h values within 24 h or less, depending on result availability) were measured for concentrations of NO₂ and CO by automatic stations belonging to the Voivodship Environmental Protection Inspectorate in Katowice, in areas with similar dominant source of pollutant emission. The measurements were made in three sites: near the motorway and expressway, where the average daily traffic intensity is 100983 and 35414 of vehicles relatively. No evidence was found of exceeding average daily values equal to the maximum allowable NO₂ concentration due to the protection of human health in the measurement area of the stations. No daily average values exceeding the admissible CO concentration (8-h moving average) were noted in the examined period. The results clearly show lack of hazards for general population health in terms of increased concentrations of CO and NO₂ compounds that are closely related to high intensity car traffic found on selected motorways and speedways located near the city centres.     

Spatial variability of air pollutants in the city of Taranto, Italy and its potential impact on exposure assessment

Epidemiological studies typically use monitored air pollution data from a single station or as averaged data from several stations to estimate population exposure. In industrialized urban areas, this approach may present critical issues due to the spatial complexities of air pollutants which are emitted by different sources. This study focused on the city of Taranto, which is one of the most highly industrialized cities in southern Italy. Epidemiological studies have revealed several critical situations in this area, in terms of mortality excess and short-term health effects of air pollution. The aims of this paper are to study the variability of air pollutants in the city of Taranto and to interpret the results in relation to the applicability of the data in assessing population exposure. Meteorological and pollution data (SO2, NO2, PM10), measured simultaneously and continuously during the period 2006–2010 in five air quality stations, were analyzed. Relative and absolute spatial concentration variations were investigated by means of statistical indexes. Results show significant differences among stations. The highest correlation between stations was observed for PM10 concentrations, while critical values were found for NO2. The worst values were observed for the SO2 series. The high values of 90th percentile of differences between pairs of monitoring sites for the three pollutants index suggest that mean concentrations differ by large amounts from site to site. The overall analysis supports the hypothesis that various parts of the city are differently affected by the different emission sources, depending on meteorological conditions. In particular, analysis revealed that the influence of the industrial site may be primarily identified with the series of SO2 data which exhibit higher mean concentration values and positive correlations with wind intensity when the monitoring station is downwind from the industrial site. Results suggest evaluating the population exposure to air pollutants in industrialized cities by taking into account the possible zones of influence of different emission sources. More research is needed to identify an indicator, which ought to be a synthesis of several pollutants, and take into account the meteorological variables.     

Assessment of air pollution from small scale industry

Air pollution due to small scale industries have been found tocause serious occupational health hazards and adverse effects on vegetation and heritage. The study for air pollution impactassessment for brick kiln industries was undertaken. The stackmonitoring exercise was carried out to estimate the pollution level of SPM, SO₂, and NO_x. The ambient air quality was also measured in the vicinity of brick kilns to assess the impact of stack emission on ground level concentration. Characterisation of SPM for toxic metals were studied. Modelling exercise was carried to predict the impact of emission of brick kiln on surrounding environment. To minimise the emission level and ground level concentration, airpollution mitigation measures are suggested.     

Integrated Ambient and Microenvironment Model for Estimation of PM10 Exposures of Children in Annual and Episode Settings

Particulate matter air pollution is estimated to cause in the order of 350,000 excess deaths in the European Union calling for policy development and evaluation tools. In the current work, a model for PM₁₀ exposures of children is developed using microenvironment time activities and infiltration of ambient pollution indoors, both evaluated against observations earlier and integrated with city-wide air quality models in the current work. The model is demonstrated using data from two cities in Italy. High-end short-term exposures are characterized by an episode-day situation in Turin, and annual mean exposures in downtown Bologna. The air quality model was unable to capture the highest levels during the episode, and therefore, the exposure model was adjusted using observed–modeled ratio from a monitoring station. Air quality model performance for the annual levels was significantly better. Annual exposure variability within the target population was 1.5-fold in the downtown area Bologna and tenfold during the episode day in Turin.     

Public-Health Impact of Outdoor Air Pollution in Russia

Based on the well-known approaches to risk assessment, estimates of the number of attributable deaths caused by atmospheric air pollution in the towns of Russia have been obtained. The data of daily monitoring of air pollution in 1993 and 1998 carried out by Rosgidromet (Weather Service of Russia) were used for assessment. The epidemiology-based exposure–response function for a 10 g/m³ increase in particulate matter PM₁₀ was used to assess the attributable number of cases of deaths in Russia. The EPA approach was applied to derive the risk of carcinogenesis caused by outdoor carcinogens controlled by Rosgidromet. In the present paper, it has been shown that up to 219–233 thousands of premature deaths or 15–17% out of the total annual mortality might be caused by air pollution in Russia. The data are given on a possible contribution of various carcinogens controlled by Rosgidromet at the stations of constant observation to the total mortality caused by atmospheric pollution. On the whole, the number of people that fell ill with cancer as a result of exposure to all the carcinogens present in the atmosphere can be assessed within the range of 2000–4000 humans. This assessment estimates the public-health impacts of air pollution. At the present time, we have no information concerning the degree of universality of the exposure–response function for PM₁₀ and its sensitivity to a change in social-demographic indicators. Nevertheless, the assessments, given in the present work, make it possible to obtain important information concerning the possible scale of health-outcome due to atmospheric pollution for the population of Russia.     

Air quality monitoring in NIS (SERBIA) and health impact assessment

The aim of this study is to indicate the significance of air quality monitoring and to determine the air quality fields for the assessment of air pollution health effects, with special attention to risk population. Radial basis function network was used for air quality index mapping. Between 1991 and 2005, on the territory of Nis, several epidemiological studies were performed on risk groups (pre-school children, school children, pregnant women and persons older than 65). The total number of subjects was 5837. The exposed group comprised individuals living in the areas with unhealthy AQI, while the control group comprised individuals living in city areas with good or moderate AQI. It was determined that even relatively low levels of air pollution had impact on respiratory system and the occurrence of anaemia, allergy and skin symptoms.     

Preparation and Validation of Gridded Emission Inventory of Criteria Air Pollutants and Identification of Emission Hotspots for Megacity Delhi

Delhi is one of the many megacities struggling with punishing levels of pollution from industrial, residential, and transportation sources. Over the years, pollution abatement in Delhi has become an important constituent of state policies. In the past one decade a lot of policies and regulations have been implemented which have had a noticeable effect on pollution levels. In this context, air quality models provide a powerful tool to study the impact of development plans on the expected air pollution levels and thus aid the regulating and planning authorities in decision-making process. In air quality modeling, emissions in the modeling domain at regular interval are one of the most important inputs. From the annual emission data of over a decade (1990–2000), emission inventory is prepared for the megacity Delhi. Four criteria pollutants namely, CO, SO₂, PM, and NO _x are considered and a gridded emission inventory over Delhi has been prepared taking into account land use pattern, population density, traffic density, industrial areas, etc. A top down approach is used for this purpose. Emission isopleths are drawn and annual emission patterns are discussed mainly for the years 1990, 1996 and 2000. Primary and secondary areas of emission hotspots are identified and emission variations discussed during the study period. Validation of estimated values is desired from the available data. There is a direct relationship of pollution levels and emission strength in a given area. Hence, an attempt has been made to validate the emission inventory for all criteria pollutants by analyzing emissions in various sampling zones with the ambient pollution levels. For validation purpose, the geographical region encompassing the study area (Delhi) has been divided into seven emission zones as per the air quality monitoring stations using Voronoi polygon concept. Dispersion modeling is also used for continuous elevated sources to have the contributing emissions at the ground level to facilitate validation. A good correlation between emission estimates and concentration has been found. Correlation coefficient of 0.82, 0.77, 0.58 and 0.68 for CO, SO₂, PM and NO _x respectively shows a reasonably satisfactory performance of the present estimates.     

Application of a risk assessment based approach to designing ambient air quality monitoring networks for evaluating non-cancer health impacts

An ambient air quality monitoring network has been establishedusing risk assessment techniques to evaluate adverse health effects from exposures to airborne contaminants. The risk assessment method was compared to traditional methods of establishing air quality monitoring networks: identifying maximumconcentration impacts or maximum total population. Results suggest that the health risk method best predicted the locationof adverse, non-carcinogenic respiratory illnesses during the evaluation period. Spearman Rank Correlation Coefficient, r _s, values obtained using the risk assessment method werestatistically greater than the values obtained using theconcentration and population methods. The concentration methodwas the least accurate predictor of adverse effects.     

Estimating residential air pollution exposure among citizens in Oslo 1974-1998 using a geographical information system

Annual concentration fields of SO2 and NOx for the period 1974-1998 are calculated for a 22 x 18 km2-grid in Oslo. In a study of lung cancer and air pollution in Oslo, 16209 men living in Oslo have been followed from 1972/73 to 1998. This paper presents a method for estimating their annual residential air pollution exposure for SO2 and NOx. In the exposure assessment the National Population Register provided information on home addresses. Each participant was given an annual average air pollutant concentration outdoors of the address he lived the largest part of that year. Persons living close to streets with high traffic were given an additional concentration, and persons who moved outside Oslo were given a region value for each year. Due to regulations of the sulfur content in fuel oil and a general change of local heating systems to electricity or distant heating, the SO2-concentrations in Central Oslo were reduced during the period from about 60 microg m(-3) in 1974-75 to about 4 microg m(-3) in 1997-98. Due to the increasing traffic the NOx-concentrations have increased slowly, from about 40 microg m(-3) in 1974-84 to about 60 microg m(-3) in 1989. After the introduction of catalyst cars the concentrations were reduced to about 45 microg m(-3) in 1997-98.     

Change of air quality and its impact on atmospheric visibility in central-western Pearl River Delta

Ambient air quality data, including atmospheric visibility, of Foshan city, a highly polluted city in the Pearl River Delta (PRD), and data obtained by the On-line Air Pollutant Exhaust Monitoring Network (OAPEMN), recently established by the National Emission Monitoring and Control Network for major industrial enterprises, were analyzed and are reported here for the first time, revealing the change in air pollution patterns and its impact on visibility degradation in the last decade. Reduced visibility of less than 8 km (after elimination of rainy and foggy periods) was found 22% of the time from 1998 to 2008, accompanied by elevated levels of pollutants, especially SO₂ and PM₁₀, in comparison with that of other developed cities. However, PM₁₀ showed a steady decreasing trend (0.004 mg m^???3 year^???1) during 2001?C2008, in contrast to the noticeable increase in ambient NO₂ concentrations from ~0.020 mg m^???3 before 2005 to above 0.050 mg m^???3 afterward. Multiple regression analysis revealed that the percentage of reduced visibility strongly correlated with PM₁₀ concentration, suggesting that visibility degradation was directly proportional to the loading of particles. Moreover, the fairly significant correlation between reduced visibility and NO₂ concentration also implied that the impact of primary emissions of NO₂ and enhanced secondary pollutants, formed via photochemical processes in the atmosphere, could not be ignored. The decreased PM₁₀ levels were obviously the predominant factor for the improvement in visibility (5.0% per 0.01 mg m^???3) and were likely due to the implementation of stricter air pollution control measures for industrial exhaust, which also resulted in reduced SO₂ pollution levels in the recent 2 years. In particular, the OAPEMN records showed an overall enhanced SO₂ removal by 64% in major industrial sectors. The continuous increase in road traffic and lack of efficient NO _x control strategies in the PRD region, however, caused an increase in ambient NO₂ concentrations.     

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.     

Assessment of Urban Air Quality in South Estonia by Simple Measures

In countries having limited resources, it is difficult to assess urban air quality on contemporaneously, due to the absence of on-line information about air pollution levels and emission rates. An alternative approach is recommended for smaller cities with lower demands of resources. The applied scheme consists of a database of air pollution sources (NO _x and CO from industry, traffic, and domestic heating), the simple Gaussian-plume model AEROPOL and a series of measurements by passive monitors. This method was used in Tartu, a small city situated in the valley of the river Emajõgi, within a landscape with noteworthy topographical variations. Simulations of annual average and maximal concentrations were performed, and a fair agreement obtained with NO₂ monitoring results from passive Palmes monitors. Inventories of pollution sources in 1998 revealed that official statistics of stationary sources covered 64% of SO₂,36% of CO, 37% of NO _x and 32% of total particulate matter emissions. Recommendations for measures for reducing air pollution levels and for further investigations towards improving air quality assessment and management, are given.     

Transformation of nitrogen dioxide into ozone and prediction of ozone concentrations using multiple linear regression techniques

Analysis and forecasting of air quality parameters are important topics of atmospheric and environmental research today due to the health impact caused by air pollution. This study examines transformation of nitrogen dioxide (NO₂) into ozone (O₃) at urban environment using time series plot. Data on the concentration of environmental pollutants and meteorological variables were employed to predict the concentration of O₃ in the atmosphere. Possibility of employing multiple linear regression models as a tool for prediction of O₃ concentration was tested. Results indicated that the presence of NO₂ and sunshine influence the concentration of O₃ in Malaysia. The influence of the previous hour ozone on the next hour concentrations was also demonstrated.     

Exposure estimates in assessing helath effects of air pollution

Air pollution has been associated with adverse health effects. Difficulties in interpreting studies of health effects of exposure to air pollution arise in estimating exposure. Until recently, studies of effects of air pollution have relied on pollution exposure measurements obtained from fixed location air pollution stations monitoring outside air (to evaluate compliance with air quality standards, rather than to examine population exposure). However, recent evidence suggests that there are substantial differences between air pollution levels measured at such sites and levels to which people are actually exposed, i.e. personal exposure. The present study examines effects of ambient urban air pollution on persons suffering from asthma, healthy non-asthmatic subjects and school children (in 2 Canadian cities, Toronto and Hamilton). Air pollution exposure is being assessed by data obtained from: (1) conventional abatement oriented fixed location air pollution monitoring stations, (2) an extensive population oriented network, (3) inside and (4) outside structures (homes and schools) as well as (5) personal air pollution samplers. The data indicate variability in these different estimates of exposure which have implications on health effects assessment.     

广州主要工业源排放的气态污染物扩散模拟研究

以广州省控工业污染源排放的气态污染物(SO₂、NO_x为主要研究对象,通过中尺度气象模式MM5与空气质量模式CALPUFF耦合,模拟11月典型气象条件下, SO₂和NO_x的扩散传输过程,研究其时空分布特征,并分析省控工业污染源排放对特定区域(主要针对2010年亚运场馆)空气质量的影响。结果表明,主要受典型风速的影响,SO₂和NO_x浓度具有明显的时空分布不均匀性。浓度高峰值主要出现在晚间至凌晨时段,而浓度低峰值主要出现在白天至中午时段。受污染源分布、排放高度和风向的影响,荔湾区和越秀区污染物浓度较高,且在广州西南部形成较明显的污染带;且这些省控污染源对南沙体育馆空气质量有较大影响。 研究结果对广州空气污染来源分析具有一定参考意义。