Evaluation of air quality zone classification methods based on ambient air concentration exposure

Air quality zones are used by regulatory authorities to implement ambient air standards in order to protect human health. Air quality measurements at discrete air monitoring stations are critical tools to determine whether an air quality zone complies with local air quality standards or is noncompliant. This study presents a novel approach for evaluation of air quality zone classification methods by breaking the concentration distribution of a pollutant measured at an air monitoring station into compliance and exceedance probability density functions (PDFs) and then using Monte Carlo analysis with the Central Limit Theorem to estimate long-term exposure. The purpose of this paper is to compare the risk associated with selecting one ambient air classification approach over another by testing the possible exposure an individual living within a zone may face. The chronic daily intake (CDI) is utilized to compare different pollutant exposures over the classification duration of 3 years between two classification methods. Historical data collected from air monitoring stations in Kuwait are used to build representative models of 1-hr NO₂ and 8-hr O₃ within a zone that meets the compliance requirements of each method. The first method, the “3 Strike” method, is a conservative approach based on a winner-take-all approach common with most compliance classification methods, while the second, the 99% Rule method, allows for more robust analyses and incorporates long-term trends. A Monte Carlo analysis is used to model the CDI for each pollutant and each method with the zone at a single station and with multiple stations. The model assumes that the zone is already in compliance with air quality standards over the 3 years under the different classification methodologies. The model shows that while the CDI of the two methods differs by 2.7% over the exposure period for the single station case, the large number of samples taken over the duration period impacts the sensitivity of the statistical tests, causing the null hypothesis to fail. Local air quality managers can use either methodology to classify the compliance of an air zone, but must accept that the 99% Rule method may cause exposures that are statistically more significant than the 3 Strike method.

Implications: A novel method using the Central Limit Theorem and Monte Carlo analysis is used to directly compare different air standard compliance classification methods by estimating the chronic daily intake of pollutants. This method allows air quality managers to rapidly see how individual classification methods may impact individual population groups, as well as to evaluate different pollutants based on dosage and exposure when complete health impacts are not known.     

Total human exposure: basic concepts, EPA field studies, and future research needs

Historically, environmental regulatory programs designed to protect public health have monitored pollutants only in geophysical carrier media (for example, outdoor air, streams, soil). Field studies have identified a gap between the levels observed in geophysical carrier media and the concentrations with which people actually come into contact: their daily exposures. A new approach--Total Human Exposure (THE)--has evolved to fill this gap and provide the critical data needed for accurately assessing public health risk. The THE approach considers a three-dimensional "bubble" around each person and measures the concentrations of all pollutants contacting that bubble, either through the air, food, water, or skin. Two basic THE approaches have emerged: (1) the direct approach using probability samples of populations and measuring pollutant concentrations in the food eaten, air breathed, water drunk, and skin contacted; and (2) the indirect approach using human activity pattern-exposure models to predict population exposure distributions. Using the direct approach, EPA has conducted over 20 field studies for pollutants representing four groups--volatile organic compounds, carbon monoxide, pesticides, and particles--in 15 cities in 12 states. The indirect modeling approach has been applied to several of these pollutants. Additional research is needed in a great variety of areas. Even from the few projects completed thus far, the THE approach has yielded a rich new data base for risk assessments and has provided many surprises about the relative contribution of various pollutant sources to public health risk.     

Total Human Exposure: Basic Concepts,EPA Field Studies,and Future Research Needs

Historically, environmental regulatory programs designed to protect public health have monitored pollutants only in geophysical carrier media (for example, outdoor air, streams, soil). Field studies have identified a gap between the levels observed in geophysical carrier media and the concentrations with which people actually come into contact: their daily exposures. A new approach—Total Human Exposure (THE)—has evolved to fill this gap and provide the critical data needed for accurately assessing public health risk. The THE approach considers a three-dimensional "bubble" around each person and measures the concentrations of all pollutants contacting that bubble, either through the air, food, water, or skin. Two basic THE approaches have emerged: (1) the direct approach using probability samples of populations and measuring pollutant concentrations in the food eaten, air breathed, water drunk, and skin contacted; and (2) the indirect approach using human activity pattern-exposure models to predict population exposure distributions. Using the direct approach, EPA has conducted over 20 field studies for pollutants representing four groups—volatile organic compounds, carbon monoxide, pesticides, and particles—in 15 cities in 12 states. The indirect modeling approach has been applied to several of these pollutants. Additional research is needed in a great variety of areas. Even from the few projects completed thus far, the THE approach has yielded a rich new data base for risk assessments and has provided many surprises about the relative contribution of various pollutant sources to public health risk.     

Spatial variation of airborne pollutant concentrations in Brisbane,Australia and its potential impact on population exposure assessment

Spread of air pollution sources and non-uniform mixing conditions in urban or regional air sheds often result in spatial variation of pollutant concentrations over different parts of the air sheds. A comprehensive understanding of this variation of concentrations is imperative for informed planning, monitoring and assessment in a range of critical areas including assessment of monitoring network efficiency or assessment of population exposure variation as a function of the location in the city. The aims of this work were to study the citywide variability of pollutants as measured by “urban background” type monitoring stations and to interpret the results in relation to the applicability of the data to population exposure assessments and the network efficiency. A comparison between ambient concentrations of NO_x, ozone and PM₁₀ was made for three stations in the Brisbane air shed network. The best correlated between the three stations were ozone concentrations followed by NO_x concentration, with the worst correlations observed for PM₁₀. With a few exceptions correlations of all pollutants between the stations were statistically significant. Marginally better were the correlations for the lower concentrations of pollutants that represent urban background, over the correlations for higher concentrations, representing peak values. Implications of these findings on application of the monitoring data to air-quality management, as well as the need for further investigations has been discussed.     

Origin of polluted air masses in the Alps. An overview and first results for MONARPOP

The contribution of ZAMG to MONAROP consists of special weather forecasts to control the SOCs sampling procedure and of the analysis of the specific transport processes for SOCs, which is still in progress.In this paper, air pollutant transport into the Alps is demonstrated by examples of inorganic pollutants: Measurements of NO_x and ozone provide evidence for air pollutant transport by local wind systems (valley and slope winds), especially at low elevated sites of the Alps. In addition, trajectory analyses for the high elevation sites demonstrate the importance of large scale synoptic air pollutant transport. The effects of these transport processes with different spatial and temporal scales are governed by the physical and chemical properties of the particular pollutant.First results for the high alpine MONARPOP stations show that air masses from east Europe influence mostly Sonnblick (Austria), whereas the influence of the Po basin is strongest at Weissfluhjoch (Switzerland).     

Statistical and diagnostic evaluation of the ADMS-Urban model compared with an urban air quality monitoring network

The present study examines the behaviour of the ADMS-Urban air quality forecasting model in predicting dispersion of traffic-related pollutants in urban areas. The study has been carried out in Ravenna (NE Italy), a medium-sized town where pollution produced by vehicle traffic accounts for most of the emissions. ADMS-Urban performances have been assessed through statistical analysis, by comparing carbon monoxide concentrations (vehicle traffic tracing pollutant) estimated by the model with concentrations measured by stations of the air quality monitoring network. Although the correspondence of values estimated by ADMS-Urban with measured values turns out to be satisfactory, the study shows that the model tends to produce an underestimated value compared with the actual situation, and identifies a corrective method that makes it possible to improve the relevant performances. Furthermore, the diagnostic analysis highlights that the model performances depend upon some meteorological parameters.     

The exceedance patterns of air quality criteria: a case study of ozone and nitrogen dioxide in Seoul, Korea between 1990 and 2000

In this study, the environmental behavior of two major airborne pollutants, ozone and nitrogen dioxide, was investigated with respect to their exceedance patterns of air quality criteria. For this purpose, we used data sets collected from a total of 31 air quality monitoring stations dispersed across the Seoul metropolitan city between 1990 and 2000. In the case of NO(2), the frequency of hourly exceedance data sets exhibited little changes in the early 90s. However, it increased dramatically after 1995, probably in compliance with a rapid increase in the total number of automobiles. Likewise, the daily exceedance of O(3) in the early 90s was not significant, approaching 100 cases (except in 1994). However, its total quantity began to surpass 300 cases since around 1996. Comparison of those exceedance data was also made among spatially divided data groups. In the case of NO(2), the occurrence of exceedance data was dominated by the western part of the city in both magnitude and frequency. On the other hand, that for O(3) was characterized by notably strong occurrences in the eastern counterpart. The overall results of our analysis of the NO(2) and O(3) exceedance data sets indicate an inextricable linkage between the two pollutants in association with geographical and meteorological factors.     

Spatiotemporal Features of Severe Air Pollution in Northern Taiwan (8 pp)

Background, Aims and Scope This research attempted to identify the dominant factors simultaneously affecting the airborne concentrations of five air pollutants with principal component analysis and to determine the meteorologically related parameters that cause severe air-pollution events. According to the definition of subPSI and PSI values through the U.S. EPA, the historical raw data of five criteria air pollutants, SO2, CO, O3, PM10 and NO2, were calculated as daily subPSI values. In addition to the airborne concentrations, this study simultaneous collected the surface meteorological parameters of the Taipei meteorological station, established by the Central Weather Bureau. Methods Principal component analysis was conducted to screen severe air pollution scenarios for five air pollutants: SO2, CO, O3, PM10 and NO2. The concentrations of various air pollutants measured at 17 air-quality stations in northern Taiwan from 1995 to 2001 were transformed into daily subPSI values. The correlation analysis of the five air pollutants and four meteorological parameters (wind speed, temperature, mixing height and ventilation rate) were included in this research. After screening severe air pollution scenarios, this study recognized the synoptic patterns easily causing the severe air-pollution events. Results and Discussion Analytical results showed that the eigenvalues of the first two principal components for SO2, CO, O3, PM10 and NO2 were greater than 1. The first component of five air pollutants explained 64, 64, 67, 76 and 63% of subPSI variance for SO2, CO, O3, PM10 and NO2, respectively. Only the correlation coefficient of NO2 and CO had statistically significant positive values (0.82); other pollutant pairs presented medium (0.4 to 0.7) or low (0 to 0.4) positive values. The correlation coefficients for air pollutants and three meteorological parameters (wind speed, mixing height and ventilation index) were medium or low negative values. In northern Taiwan, spring was most likely induced high concentrations and the component scores of the first component for SO2, CO, PM10 and NO2; summer was the worst season that caused high O3 episodes. Consequently, the analytical results of factor loadings for the first principal component and emission inventory of various sources revealed that mobile sources were dominant factors affecting ambient air quality in northern Taiwan. Conclusion According to the results of principal component analysis for the five air pollutants, the first two of 17 components were cited as major factors and explained 71% of subPSI variance. Based on the inventory of NOx emissions and the isopleth diagram of factor loading for the first component, mobile sources in the southwest Taipei City accounted for the highest factor loading values and emission inventory values. Synoptic analysis and principal component analysis demonstrated that three types of weather patterns (high-pressure recirculation, prefrontal warm sector and the southwesterly wind system) easily caused the severe air-pollution scenarios. In summary, if severe air-pollution days occurred, the average meteorological parameters experienced adverse conditions for diffusing air pollutants; that is, the average values of wind speed, mixing height and ventilation index were lower than 2.1 ms-1, 360 m and 800 m2s-1, respectively. If one of the three synoptic patterns were to occur in combination with adverse meteorological conditions, severe air-pollution events would be developed. Recommendation and Outlook By utilizing synoptic patterns, this work found three weather systems easily caused severe air-pollution events over northern Taiwan. Analytical results showed, respectively, the wind speed and mixing height were less than 2.1 m/s and 360 m during severe air-pollution events.     

Relationship between antecedent dry period and highway pollutant: conceptual models of buildup and removal processes

This paper investigated the highway stormwater quality at two Texas cities-Austin and College Station. Two highways with high average daily traffic were monitored using passive stormwater samplers for collecting first-flush runoff during a 16-month period. Detailed traffic and weather data were collected at College Station sites, but only weather data were obtained at Austin sites. A stepwise regression analysis on College Station data identifies the antecedent dry period (ADP) as the most significant predictor of pollutant concentration. Specifically, the College Station data show an unexpected result that pollutant event mean concentrations significantly decrease with increasing ADP for all analyzed pollutants. However, the runoff concentrations observed in Austin were not significantly correlated with ADP. The result from College Station data provides a different insight to the pollutant buildup and removal process on highways. Conceptual highway pollutant buildup and removal models are proposed for generating further discussion and research interest.     

Daily mortality in the Philadelphia metropolitan area and size-classified particulate matter

Time-series of daily mortality data from May 1992 to September 1995 for various portions of the seven-county Philadelphia, PA, metropolitan area were analyzed in relation to weather and a variety of ambient air quality parameters. The air quality data included measurements of size-classified PM, SO4(2-), and H+ that had been collected by the Harvard School of Public Health, as well as routine air pollution monitoring data. Because the various pollutants of interest were measured at different locations within the metropolitan area, it was necessary to test for spatial sensitivity by comparing results for different combinations of locations. Estimates are presented for single pollutants and for multiple-pollutant models, including gaseous pollutants and mutually exclusive components of PM (PM2.5 and coarse particles, SO4(2-) and non-SO4(2-) portions of total suspended particulate [TSP] and PM10), measured on the day of death and the previous day. We concluded that associations between air quality and mortality were not limited to data collected in the same part of the metropolitan area; that is, mortality for one part may be associated with air quality data from another, not necessarily neighboring, part. Significant associations were found for a wide variety of gaseous and particulate pollutants, especially for peak O3. Using joint regressions on peak O3 with various other pollutants, we found that the combined responses were insensitive to the specific other pollutant selected. We saw no systematic differences according to particle size or chemistry. In general, the associations between daily mortality and air pollution depended on the pollutant or the PM metric, the type of collection filter used, and the location of sampling. Although peak O3 seemed to exhibit the most consistent mortality responses, this finding should be confirmed by analyzing separate seasons and other time periods.     

A real-time monitoring and assessment method for calculation of total amounts of indoor air pollutants emitted in subway stations

Subway systems are considered as main public transportation facility in developed countries. Time spent by people in indoors, such as underground spaces, subway stations, and indoor buildings, has gradually increased in the recent past. Especially, operators or old persons who stay in indoor environments more than 15 hr per day usually influenced a greater extent by indoor air pollutants. Hence, regulations on indoor air pollutants are needed to ensure good health of people. Therefore, in this study, a new cumulative calculation method for the estimation of total amounts of indoor air pollutants emitted inside the subway station is proposed by taking cumulative amounts of indoor air pollutants based on integration concept. Minimum concentration of individual air pollutants which naturally exist in indoor space is referred as base concentration of air pollutants and can be found from the data collected. After subtracting the value of base concentration from data point of each data set of indoor air pollutant, the primary quantity of emitted air pollutant is calculated. After integration is carried out with these values, adding the base concentration to the integration quantity gives the total amount of indoor air pollutant emitted. Moreover the values of new index for cumulative indoor air quality obtained for 1 day are calculated using the values of cumulative air quality index (CAI). Cumulative comprehensive indoor air quality index (CCIAI) is also proposed to compare the values of cumulative concentrations of indoor air pollutants. From the results, it is clear that the cumulative assessment approach of indoor air quality (IAQ) is useful for monitoring the values of total amounts of indoor air pollutants emitted, in case of exposure to indoor air pollutants for a long time. Also, the values of CCIAI are influenced more by the values of concentration of NO2, which is released due to the use of air conditioners and combustion of the fuel. The results obtained in this study confirm that the proposed method can be applied to monitor total amounts of indoor air pollutants emitted, inside apartments and hospitals as well. Implications: Nowadays, subway systems are considered as main public transportation facility in developed countries. Time spent by people in indoors, such as underground spaces, subway stations, and indoor buildings, has gradually increased in the recent past. Especially, operators or old persons who stay in the indoor environments more than 15 hr per day usually influenced a greater extent by indoor air pollutants. Hence, regulations on indoor air pollutants are needed to ensure good health of people. Therefore, this paper presents a new methodology for monitoring and assessing total amounts of indoor air pollutants emitted inside underground spaces and subway stations. A new methodology for the calculation of cumulative amounts of indoor air pollutants based on integration concept is proposed. The results suggest that the cumulative assessment approach of IAQ is useful for monitoring the values of total amounts of indoor air pollutants, if indoor air pollutants accumulated for a long time, especially NO2 pollutants. The results obtained here confirm that the proposed method can be applied to monitor total amounts of indoor air pollutants emitted, inside apartments and hospitals as well.     

Effects of the density of meteorological observations on the diagnostic wind fields and the performance of photochemical modeling in the greater Seoul area

The high ozone episode in the greater Seoul area (GSA) for the period of 27 July–1 August 1997 was modeled by the California Institute of Technology (CIT) three-dimensional photochemical model. During the period, ozone concentrations around 140 ppb were observed for 2 days. Two sets of diagnostic wind fields were constructed by using observations from the weather stations operated by the Korea Meteorological Administration. One set of wind fields utilized only observations from the surface weather stations (SWS) and the other set also utilized observations from the automatic weather stations (AWS) that were more densely distributed than the SWS. The results showed that utilizing observations from the AWS could represent fine variations in the wind field such as those caused by topography. A better wind field gave a more reasonable spatial distribution of ozone concentrations. The model performance of ozone prediction was also improved to some extent, but only marginally acceptable owing to large day-to-day variations. Overshoots of primary pollutants particularly for NO₂ were observed as pollutants were accumulated where low wind speeds were maintained. More precise information on diurnal and daily variations in emissions was warranted in order to better model the photochemical phenomena over the GSA.     

New indicator approaches for effective urban air quality management

Measurements of urban air quality at monitoring stations in developed countries have frequently involved the criteria gaseous pollutants, particulates, hazardous air pollutants, perceived air quality and relevant meteorological conditions. Large numbers of indicators have therefore been established to quantify emissions, concentrations and environmental and human health impacts of each of these groups of substances. To simplify the data for management, several indicators have been grouped together to form urban air quality indices but the weightings of individual variables is contentious. In industrialising and developing countries, data may be limited and traditional air pollutant indicators cannot often be constructed. The emphasis therefore has to be placed on the development of policy-relevant indicators, such as Response Indicators that reflect different policy principles for regulating air pollutant emissions. Indices that quantify the air quality management capabilities and capacities at the city level provide further useful decision-relevant tools. Four sets of indices, namely, 1. air quality measurement capacity, 2. data assessment and availability, 3. emissions estimates, and 4. management enabling capabilities, and a composite index to evaluate air quality management capability, were constructed and applied to 80 cities. The indices revealed that management capability varied widely between the cities. In some of the cities, existing national knowledge on urban air quality could have been more effectively used for management. It was concluded that for effective urban air quality management, a greater emphasis should be given, not just to monitoring and data capture programmes, but to the development of indicators and indices that empower decision-makers to initiate management response strategies. Over-reliance on restricted, predetermined sets of traditional air quality indicators should be avoided.     

A real-time monitoring and assessment method for calculation of total amounts of indoor air pollutants emitted in subway stations

Subway systems are considered as main public transportation facility in developed countries. Time spent by people in indoors, such as underground spaces, subway stations, and indoor buildings, has gradually increased in the recent past. Especially, operators or old persons who stay in indoor environments more than 15 hr per day usually influenced a greater extent by indoor air pollutants. Hence, regulations on indoor air pollutants are needed to ensure good health of people. Therefore, in this study, a new cumulative calculation method for the estimation of total amounts of indoor air pollutants emitted inside the subway station is proposed by taking cumulative amounts of indoor air pollutants based on integration concept. Minimum concentration of individual air pollutants which naturally exist in indoor space is referred as base concentration of air pollutants and can be found from the data collected. After subtracting the value of base concentration from data point of each data set of indoor air pollutant, the primary quantity of emitted air pollutant is calculated. After integration is carried out with these values, adding the base concentration to the integration quantity gives the total amount of indoor air pollutant emitted. Moreover, the values of new index for cumulative indoor air quality obtained for 1 day are calculated using the values of cumulative air quality index (CAI). Cumulative comprehensive indoor air quality index (CCIAI) is also proposed to compare the values of cumulative concentrations of indoor air pollutants. From the results, it is clear that the cumulative assessment approach of indoor air quality (IAQ) is useful for monitoring the values of total amounts of indoor air pollutants emitted, in case of exposure to indoor air pollutants for a long time. Also, the values of CCIAI are influenced more by the values of concentration of NO₂, which is released due to the use of air conditioners and combustion of the fuel. The results obtained in this study confirm that the proposed method can be applied to monitor total amounts of indoor air pollutants emitted, inside apartments and hospitals as well.

Implications: Nowadays, subway systems are considered as main public transportation facility in developed countries. Time spent by people in indoors, such as underground spaces, subway stations, and indoor buildings, has gradually increased in the recent past. Especially, operators or old persons who stay in the indoor environments more than 15 hr per day usually influenced a greater extent by indoor air pollutants. Hence, regulations on indoor air pollutants are needed to ensure good health of people. Therefore, this paper presents a new methodology for monitoring and assessing total amounts of indoor air pollutants emitted inside underground spaces and subway stations. A new methodology for the calculation of cumulative amounts of indoor air pollutants based on integration concept is proposed. The results suggest that the cumulative assessment approach of IAQ is useful for monitoring the values of total amounts of indoor air pollutants, if indoor air pollutants accumulated for a long time, especially NO₂ pollutants. The results obtained here confirm that the proposed method can be applied to monitor total amounts of indoor air pollutants emitted, inside apartments and hospitals as well.     

Neural network forecasting of air pollutants hourly concentrations using optimised temporal averages of meteorological variables and pollutant concentrations

The new method for the forecasting hourly concentrations of air pollutants is presented in the paper. The method was developed for a site in urban residential area in city of Zagreb, Croatia, for four air pollutants (NO₂, O₃, CO and PM₁₀). Meteorological variables and concentrations of the respective pollutant were taken as predictors. A novel approach, based on families of univariate regression models, was employed in selecting the averaging intervals for input variables. For each variable and each averaging period between 1 and 97 h, a separate model was built. By inspecting values of the coefficient of correlation between measured and modelled concentrations, optimal averaging periods for each variable were selected. A new dataset for building the forecasting model was then calculated as temporal moving averages (running means) of former variables. A multi-layer perceptron type of neural networks is used as the forecasting model. Index of agreement, calculated for the entire dataset including the data for model building, ranged from 0.91 to 0.97 for the respective pollutants. As suggested by the analysis of the relative importance of the input variables, different agreements for different pollutants are likely due to different sources and production mechanisms of investigated pollutants. A comparison of the new method with more traditional method, which takes hourly averages of the forecast hour as input variables, showed similar or better performance. The model was developed for the purpose of public-health-oriented air quality forecasting, aiming to use a numerical weather forecast model for the prediction of the part of input data yet unknown at the forecasting time. It is to expect that longer term averages used as inputs in the proposed method will contribute to smaller input errors and the greater accuracy of the model.     

Air pollution characteristics associated with mesoscale atmospheric patterns in northwest continental Europe

An impact related daily air quality index (DAQx), calculated for 15 air quality monitoring stations (traffic, background, and industry) in Belgium, France, Germany and Luxembourg, was compared to mesoscale atmospheric patterns between 2001 and 2007. Meteorological conditions were described by the Hess and Brezowsky synoptic weather classification system and gridded data of the EU FP6 ENSEMBLES project of total precipitation and mean surface temperature. DAQx values indicate sufficient to poor air quality in the urban area of Brussels and at urban traffic stations, as well as satisfactory air quality at the background stations. The air quality index refers to more than 90% to the presence of high PM₁₀, O₃ and NO₂ concentrations. SO₂ and CO play only a minor role. The investigation of weather regimes indicates that zonal and mixed cyclonic circulation regimes are associated with better air quality than meridional and anticyclonic weather regimes. In general, weather regimes with high daily precipitation lead to better air quality than dryer air masses because of lower contribution of PM₁₀ to the air quality index. A trend analysis of weather regimes from 1978 to 2007 shows significant (α = 0.05) positive trends for weather classes associated with lower PM₁₀ concentrations. The results of a case study at a German station examining the relationship between PM₁₀ concentrations and local meteorological quantities (wind speed and precipitation) confirm the results of the regional analysis.     

A multi-approach monitoring of particulate matter, metals and PAHs in an urban street canyon

For the first time until now, the results from a prediction model (Atmospheric Dispersion Modelling System (ADMS)-Road) of pollutant dispersion in a street canyon were compared to the results obtained from biomonitors. In particular, the instrumental monitoring of particulate matter (PM10) and the biomonitoring of 14 polycyclic aromatic hydrocarbons (PAHs) and 11 metals by Quercus ilex leaves and Hypnum cupressiforme moss bags, acting as long- and short-term accumulators, respectively, were carried out. For both PAHs and metals, similar bioaccumulation trends were observed, with higher concentrations in biomonitors exposed at the leeward canyon side, affected by primary air vortex. The major pollutant accumulation at the leeward side was also predicted by the ADMS-Road model, on the basis of the prevailing wind direction that determines different exposure of the street canyon sides to pollutants emitted by vehicular traffic. A clear vertical (3, 6 and 9 m) distribution gradient of pollutants was not observed, so that both the model and biomonitoring results suggested that local air turbulences in the street canyon could contribute to uniform pollutant distribution at different heights.     

An Epidemiological Appraisal of the Effects of Ambient Air on Health: Particulates and Oxides of Sulfur

This review has attempted to evaluate the present state of our knowledge of the effects on health in man of environmental exposure to oxides of sulfur, sulfates, and particulate matter. There has been a great deal of activity in this field over the last 15 years, and therefore any collation of this material will represent the selected biases of the reviewer. The conclusions reached can be summarized as follows: (1) These pollutants, as they have been measured in epidemiological investigations, can only be considered as indirect indices of general air pollution and in many cases cannot be separated from each other. Therefore, we cannot incriminate a specific source of any one pollutant as the producer of the most harmful substance to reach the ambient air. Conversely, we cannot excuse any specific source of one pollutant because that specific pollutant has not been found to cause disease at a given concentration. The measurements in ambient air are the net results from all sources of pollution in combination with factors influenced by weather and meteorological considerations. (2) Direct effects from acute, high ambient air pollution disasters have been adequately demonstrated. Significant excess mortality has occurred in association with particular air pollution episodes. All of these episodes have occurred during cold weather, and the effects of temperature must also be considered along with elevated levels of smoke and sulfur oxides. (3) Specific working groups exposed to unusually high levels of these pollutants do not demonstrate dramatic effects. This is presumably related to the fact that susceptible people are self-selected out of these environments. (4) Associations between the prevalence of chronic respiratory disease in the general population and specific levels of these air pollutants have been demonstrated. The major thrusts of epidemiological investigations have been to study the effects of chronic exposure to ambient levels of smoke and sulfur dioxide. The studies to date have collected and analyzed point-prevalence data and information obtained from retrospective investigations. Although epidemiological investigations cannot prove a cause-and-effect relationship, the consistency of the results is such that one must conclude that a causal association is likely. In this reviewer’s opinion we have reached the stage at which we no longer need to demonstrate the effect of past exposure to these pollutants. What is needed now is to demonstrate the effects of current and continued exposure. This will require a better understanding of the natural history and pathophysiology of the diseases thought to be associated with chronic exposure to smoke and sulfur dioxide. Because of the nature of chronic respiratory disease, groups of subjects for whom exposure is known, must be followed over extended periods of time. The logical extension of these observations will be the follow-up of large populations for whom exposure has been reduced. Only by studies of this kind may we be able to prove the cause-and-effect relationship which most likely exists.     

Evaluation of gas well setback policy in the Marcellus Shale region of Pennsylvania in relation to emissions of fine particulate matter

Shale gas has become an important strategic energy source with considerable potential economic benefits and the potential to reduce greenhouse gas emissions in so far as it displaces coal use. However, there still exist environmental health risks caused by emissions from exploration and production activities. In the United States, states and localities have set different minimum setback policies to reduce the health risks corresponding to the emissions from these locations, but it is unclear whether these policies are sufficient. This study uses a Gaussian plume model to evaluate the probability of exposure exceedance from EPA concentration limits for PM2.5 at various locations around a generic wellsite in the Marcellus shale region. A set of meteorological data monitored at ten different stations across Marcellus shale gas region in Pennsylvania during 2015 serves as an input to this model. Results indicate that even though the current setback distance policy in Pennsylvania (500 ft. or 152.4 m) might be effective in some cases, exposure limit exceedance occurs frequently at this distance with higher than average emission rates and/or greater number of wells per wellpad. Setback distances should be 736 m to ensure compliance with the daily average concentration of PM2.5, and a function of the number of wells to comply with the annual average PM2.5 exposure standard.

Implications: The Marcellus Shale gas is known as a significant source of criteria pollutants and studies show that the current setback distance in Pennsylvania is not adequate to protect the residents from exceeding the established limits. Even an effective setback distance to meet the annual exposure limit may not be adequate to meet the daily limit. The probability of exceeding the annual limit increases with number of wells per site. We use a probabilistic dispersion model to introduce a technical basis to select appropriate setback distances.     

Daily Mortality in the Philadelphia Metropolitan Area and Size-Classified Particulate Matter

ABSTRACT

Time-series of daily mortality data from May 1992 to September 1995 for various portions of the seven-county Philadelphia, PA, metropolitan area were analyzed in relation to weather and a variety of ambient air quality parameters. The air quality data included measurements of size-classified PM, SO₄ ^2-, and H+ that had been collected by the Harvard School of Public Health, as well as routine air pollution monitoring data. Because the various pollutants of interest were measured at different locations within the metropolitan area, it was necessary to test for spatial sensitivity by comparing results for different combinations of locations. Estimates are presented for single pollutants and for multiple-pollutant models, including gaseous pollutants and mutually exclusive components of PM (PM_2.5 and coarse particles, SO₄ ^2- and non-SO₄ ^2- portions of total suspended particulate [TSP] and PM₁₀), measured on the day of death and the previous day.

We concluded that associations between air quality and mortality were not limited to data collected in the same part of the metropolitan area; that is, mortality for one part may be associated with air quality data from another, not necessarily neighboring, part. Significant associations were found for a wide variety of gaseous and particulate pollutants, especially for peak O₃. Using joint regressions on peak O₃ with various other pollutants, we found that the combined responses were insensitive to the specific other pollutant selected. We saw no systematic differences according to particle size or chemistry. In general, the associations between daily mortality and air pollution depended on the pollutant or the PM metric, the type of collection filter used, and the location of sampling. Although peak O₃ seemed to exhibit the most consistent mortality responses, this finding should be confirmed by analyzing separate seasons and other time periods.