Air pollution exposure monitoring and estimation. Part IV. Urban exposure in children

In the winter of 1994, 2300 school-age children in Oslo participated in a panel study of the role of traffic pollution on the exacerbation of diseases of the respiratory system and other symptoms of reduced health and well being in children. The children filled out a diary daily with information for five time points over six weeks. In order to quantify exposure-effect relationships for the symptoms, individual exposure to NO2 and particulate matter (PM2.5) was estimated, using the DINEX method a combination of information from the diary as to the children's whereabouts during the five time points each day, coupled with continuous dispersion modelling. An individual exposure estimate for each time point for each child was defined. Individual exposure estimated using dispersion modelling can be used to examine patterns of exposure such as isolating geographic areas with higher concentrations or describing concentrations of pollution by time of day. The diary allowed the time-use of the children to be described.     

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.     

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.     

Air pollution exposure monitoring and estimation. Part II. Model evaluation and population exposure

The air pollution dispersion model EPISODE has been developed at the Norwegian Institute for Air Research (NILU) over the past several years in order to meet the needs of modern air quality management work in urban areas. The model has recently been used as a basis for exposure calculations of NOx and NO2 in order to assess the effects of different traffic diversion measures on health and well being for the residents in the V?lerenga-Ekeberg-Gamlebyen area in Oslo. Here we describe some results from the most recent evaluations of the model for NOx and NO2 at station Nordahl Brunsgate in Oslo for the period 1 October 1996-19 November 1996. In addition examples of population exposure calculations for Oslo performed during the winter period of 1995-96, are also presented.     

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 estimation. Part III. Development of new types of air quality indicators

The temporal pattern of exposure to a specific compound may affect health in several ways. Exposure to pollution can have short-term effects or long-term effects. For some compounds there is a threshold under which there is no presumed measurable effect, whereas for other compounds, there is no presumed threshold. For short-term effects, the exposure to a high concentration of a compound one day may either increase or decrease the response if values of the same compound become high again the next day. Adaptation to effects of short-term exposure to ozone, for example, is reported. Similarly, health response to sudden high peaks of concentration may also possibly differ in effect from those to peaks attained more gradually. For long-term effects of some compounds, the cumulative exposure may be more decisive in influencing health. This paper proposes and describes in detail several air quality indicators that reflect the time variability and the episodic nature of air pollution exposure, as an attempt to represent the temporal aspects of pollution exposure that may have important effects on health. Mean concentrations, 98th percentile and maximum values are the traditional indicators for estimating exposure. The temporal variability of particulate matter (PM10) and NO2, however, is here described by means of: (1) the rate of change of pollution as the difference between two consecutive hourly or daily values, and of (2) episodes, described in terms of number, duration and inter-episode period, maximum concentration in the episode, and integrated episode exposure.     

Simulation and Evaluation of Control Strategies for Ozone Reduction in a Complex Terrain in Southwestern Spain

During the central months of the year, southwestern Spain is under strong insolation and weak synoptic forcing, promoting the development of sea breezes and mountain-induced winds and creating recirculations of pollutants. The complex topography of the Southwestern Iberia Peninsula induces the formation of vertical layers, into which the pollutants are injected and subjected to long-distance transport and compensatory subsidence. The characteristics of these highly complex flows have important effects on the pollutant dispersion. Air pollution studies in very complex terrains require high-resolution modelling for resolving the flow dynamics. This paper shows the results obtained from using the MM5-CAMx multiscale-nested air quality model to relate the sensitivity regimes for ozone, nitrogen oxides and volatile organic compounds in an area of high geographical complexity. The article assesses the impact on the hourly and eight-hourly maximum daily ozone concentrations of four reduction strategies during two ozone pollution episodes. This analysis of the ozone response has led to a preliminary evaluation of the effectiveness of the most common control strategies: traffic, industry, mixed traffic and industry, and closure of some of the largest industries (oil and petrochemical refineries). Photochemical indicators show that ozone chemistry in southwestern Spain is strongly sensitive to NO _x . However, volatile organic compound-sensitive points are found in areas with anthropogenic influence (highways, cities and industrial parks). Our results indicate that reductions in road traffic lead to ozone reductions over large areas, whereas reductions in industrial emissions, despite sometimes showing greater decreases in the maximum hourly and eight-hourly ground-level ozone levels, lead to ozone reductions in a local area only. In the control study case, with the oil refinery and the petrochemical plants closed, decreases in ozone hourly concentrations are up to 40% higher than in the other emission control scenarios studied. This analysis provides an assessment of the effectiveness of different policies for controlling precursor emissions by comparing the modelled results for different scenarios.     

On the evaluation of box model results: the case of BOXURB model

In the present paper, the BOXURB model results, as they occurred in the Greater Area of Athens after model application on an hourly basis for the 10-year period 1995-2004, are evaluated both in time and space in the light of observed pollutant concentrations time series from 17 monitoring stations. The evaluation is performed at a total, monthly, daily and hourly scale. The analysis also includes evaluation of the model performance with regard to the meteorological parameters. Finally, the model is evaluated as an air quality forecasting and urban planning tool. Given the simplicity of the model and the complexity of the area topography, the model results are found to be in good agreement with the measured pollutant concentrations, especially in the heavy traffic stations. Therefore, the model can be used for regulatory purposes by authorities for time-efficient, simple and reliable estimation of air pollution levels within city boundaries.     

Why Should We Calculate Complex Indices of Ozone Exposure? Results from Mediterranean Background Sites

While moving towards a flux-based approach, exposure-based ozone metrics are still a practical measure for summarising ambient air quality. Ozone hourly concentrations for the period 2000–2004 from sites in the Mediterranean Italy (≤600 m a.s.l.) were examined to define the O₃ summary statistic in the area, and to determine how O₃ exposure indices correlate to each other. Thirty-four of the most common O₃ exposure metrics were calculated. The results show that background O₃ pollution in Italy exceeds the European and North American standards. The exceedances of the target value, information and alert thresholds set by the 2002/3/CE Directive should encourage Italy to take the appropriate measures to reduce the risk. All the O₃ exposure indices, except the maximum permissible ozone concentration (MPOC) for forests, point to the potential for negative effects on vegetation and human health across Italy. As indices evaluated significantly correlated with each other, we suggest use of the most biologically meaningful metric when summarizing air quality information.     

Health impact assessment of air pollution using a dynamic exposure profile: Implications for exposure and health impact estimates

In both ambient air pollution epidemiology and health impact assessment an accurate assessment of the population exposure is crucial. Although considerable advances have been made in assessing human exposure outdoors, the assessments often do not consider the impact of individual travel behavior on such exposures.Population-based exposures to NO₂ and O₃ using only home addresses were compared with models that integrate all time-activity patterns—including time in commute—for Flanders and Brussels. The exposure estimates were used to estimate the air pollution impact on years of life lost due to respiratory mortality.Health impact of NO₂ using an exposure that integrates time-activity information was on average 1.2% higher than when assuming that people are always at their home address. For ozone the overall estimated health impact was 0.8% lower. Local differences could be much larger, with estimates that differ up to 12% from the exposure using residential addresses only. Depending on age and gender, deviations from the population average were seen.Our results showed modest differences on a regional level. At the local level, however, time-activity patterns indicated larger differences in exposure and health impact estimates, mainly for people living in more rural areas. These results suggest that for local analyses the dynamic approach can contribute to an improved assessment of the health impact of various types of pollution and to the understanding of exposure differences between population groups.     

Indoor and outdoor air concentrations of BTEX and NO2: correlation of repeated measurements

Studies on health effects of air pollutants ideally define exposure through the collection of air samples in the participants' homes. Concentrations derived from these samples are then considered as an estimate for the average concentration of air pollutants in the homes. Conclusions drawn from such studies therefore depend very much on the validity of the measured air pollution concentrations. In this paper we analysed repeated BTEX and NO(2) measurements with a time period of several months lying between the two conducted home visits. We investigated the variability of their concentrations over time by determining correlation coefficients and calculating within- and between-home variances. Our population consisted of 631 homes of participants from two cohort studies within the framework of the German study on Indoor Factors and Genetics in Asthma. Air pollutants were measured using passive samplers both indoors and outdoors. The measured BTEX concentrations were poorly correlated, with Pearson's correlation coefficient r ranging from -0.19 to 0.27. Additionally, a considerable seasonal effect could be observed. A higher correlation was found for the NO(2) concentrations with r ranging between 0.24 and 0.55. For the BTEX, the between-home variance was bigger than the within-home variance, for NO(2) both variances were of about the same order. Our results indicate that in a setting of moderate climate like in Germany, the variability of BTEX and NO(2) concentrations over time is high and a single measurement is a poor surrogate for the long-term concentrations of these air pollutants.     

Trends analysis of ambient 8 hour ozone and precursor monitoring data in the south central U.S

For the south central U.S., lower tropospheric ozone pollution has been a persistent and challenging problem. This paper provides long-term trends analyses of the ozone and precursor monitoring data collected over the past 20 years in four south central U.S. cities. The results of these analyses should be useful to air quality scientists, managers, planners, and modelers in assessing the effectiveness of ozone pollution control strategies being implemented or being planned for the future. Results of the data analyses show that all areas have monitored significant decreases in ozone and precursor concentrations over the past 20 years, especially in El Paso, Texas. Continuing challenges include the reduction of the percentage of time that monitors record 8 hour ozone concentrations over the U.S. 8 hour ozone standard, and the future control of highly reactive volatile organic compounds.     

Indoor air pollution levels in public buildings in Thailand and exposure assessment

Levels of pollutants including PM2.5 and PM2.5 composition (black carbon and water soluble ions), SO(2), NO(2), CO, CO(2), and BTEX (benzene, toluene, ethylbenzene, xylene) were monitored for indoor and outdoor air at a university campus and a shopping center, both located in the Northern suburb of Bangkok. Sampling was done during December 2005-February 2006 on both weekdays and weekends. At the university, indoor monitoring was done in two different air conditioned classrooms which shows the I/O ratios for all pollutants to be below 0.5-0.8 during the weekends. However, on weekdays the ratios for CO(2) and most detected BTEX were above 1.0. The concept of classroom occupancy was defined using a function of the student number in a lecture hour and the number of lecture hours per day. Classroom 2, which had a higher occupancy than classroom 1, was characterized by higher concentrations of most pollutants. PM2.5 was an exception and was higher in classroom 1 (37 microg/m(3), weekdays) as compared to classroom 2 (26 microg/m(3), weekdays) which was likely linked to the dust resuspension from the carpeted floor in the former. Monitoring was also done in the shopping mall at three different sites. Indoor pollutants levels and the I/O ratios at the shopping mall were higher than at the university. Levels of all pollutants measured at the car park, except for toluene and CO(2), were the highest. I/O ratios of the pollutants at the mall were above 1.0, which indicates the relatively higher influence of the indoor sources. However, the black carbon content in PM2.5 outdoor is higher than indoor, which suggest the important contribution from outdoor combustion sources such as the traffic. Major sources of outdoor air pollution in the areas were briefly discussed. Exposure modeling was applied using the time activity and measured pollutant concentrations to assess the exposure of different groups of people in the study areas. High exposure to PM2.5, especially for the people working in the mall, should be of health effect concern.     

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.     

A model for the maximum credible hourly impact on any ground receptor from point sources with momentumdominated plume rise

A pollutant dispersion model is developed, allowing rapid evaluation of the maximum credible one-hour-average concentration on any given ground-level receptor, along with the corresponding critical meteorological conditions (wind speed and stability class) for stacks with momentum-dominated plume rise in urban or rural areas under buoyancy or no buoyancy induced dispersion. Site-specific meteorological data are not required, as the computed concentrations are maximized against all credible combinations of wind speed, stability class, and mixing height.The analysis is based on the dispersion relations of Pasquill-Gifford and Briggs for rural and urban settings respectively, the buoyancy induced dispersion correlation of Pasquill, the wind profile exponent values suggested by Irwin, the momentum plume rise relations of Briggs, as well as the Benkley and Schulman's model for the minimum mixing heights.The model is particularly suited for air pollution management studies, as it allows fast screening of the maximum impact on any selected receptor and evaluation of the ways to have this impact reduced. Also, for regulatory purposes, as it allows accurate setting of minimum stack height requirements as function of the exit gas volume and velocity, the pollutant emission rates and their hourly concentration standards, as well as the source location relative to sensitive receptors.     

Multipoint source method in air pollution modelling of cold start emission

The paper presents a new method of air pollution modelling on a micro scale. For estimation of concentration of car exhaust pollutants, each car is treated as an instantaneous moving emission source. This approach enables us to model time and spatial changes of emission, especially during cold and cool start of an engine. These stages of engine work are a source of significant pollution concentration in urban areas. In this work, two models are proposed: one for the estimation of emission after cold start of the engine and another for the prediction of pollutant concentration. The first model (defined for individual exhaust gas pollutants) enables us to calculate the emission as a function of time after the cold or cool start, ambient temperature and average speed of motion. This model uses the HBEFA database. The second mathematical model is developed in order to calculate the pollutant dispersion and concentrations. The finite volume method is applied to discretise the set of partial differential equations describing wind flow and pollutant dispersion in the domain considered. Models presented in this paper can be called short-term models on a small spatial scale. The results of numerical simulation of pollutant emission and dispersion are also presented.     

2018年11—12月北京市重污染天气过程数值预报能力评估

2018年11—12月北京市发生了4次以PM_2.5为首要污染物的重污染天气过程,为了分析数值模型对4次重污染过程的预报能力,将CMAQ模式提前1~7 d对北京市PM_2.5的小时预报结果与观测结果对比,分别从离散统计和分类统计2个方面评估CMAQ模式对4次重污染天气过程的预报效果,并简要分析了偏差产生的气象方面原因。结果表明：CMAQ模式提前1~6 d对重污染天气过程的预报显示出良好的性能,为日常业务预报提供了可借鉴的参考信息,可较好地预报出PM_2.5小时浓度变化趋势和浓度水平,离散统计结果显示提前1~4 d的预报结果好于提前5~7 d,相关系数r基本大于0.8,但有一定程度的低估趋势;分类统计结果显示不同预报时效预报准确率大于70%,探测准确率高于55%,部分时段可以达到80%~90%,对人工预报起到了良好的参考作用;输入的气象场的变化及其偏差对于重污染的起始时间、持续时间及清除时间有一定的影响,对相对湿度预报偏小和风速预报偏大是造成CMAQ模式低估的一个重要原因。     

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.     

Estimating the background air concentration excluding the contribution of an individual source

This paper presents two simple methods for the estimation of the instantaneous background air pollution level in a study area around an emitting point source. The methods allow estimation of concentrations non-inclusive of the contribution of the local emitting source. Hourly records of several monitoring stations located around the point source and results of the diagnostic Lagrangian particle dispersion model LADISMO are used in the calculations. A hypothetical case study is used to demonstrate the application of the two methods. This revised version was published online in July 2006 with corrections to the Cover Date.