On the errors associated with the use of hourly data in wind-driven rain calculations on building facades

Wind-driven rain (WDR) is the one of the main moisture sources for building facades. It is an important factor in the dry and wet deposition of pollutants, facade surface soiling and facade erosion. WDR calculations require data records of wind speed, wind direction and horizontal rainfall intensity as input. Most meteorological datasets contain at best arithmetically averaged hourly wind and rain data. Their use is common practice in WDR calculations. As an example, existing WDR standards request at best hourly data. This paper however demonstrates that the use of such data can yield (very) large errors in the calculated WDR amounts and intensities. The reason is that arithmetic averaging on an hourly basis generally causes an important loss of information about the co-occurrence of wind and rain. An improved data averaging technique for wind and rain data is proposed that respects this co-occurrence by applying appropriate weighting factors in the averaging procedure. The performance of this technique is evaluated by WDR calculations on buildings in three cities with different climates. While arithmetically averaged hourly data yield large underestimation errors (Eindhoven, The Netherlands: 11%, Bloomington, USA: 45%, Grahamstown, South Africa: 31%), the improved averaging technique provides very good results (errors: 0%, 4%, 3%, respectively). In conclusion, WDR calculations should not be performed with arithmetically averaged hourly data. Instead, either high-resolution data (e.g. 10-min data) or hourly data that have been obtained with the proposed weighted averaging technique should be used.     

Temporal analysis of airborne particulate matter reveals a dose-rate effect on mortality in El Paso: indications of differential toxicity for different particle mixtures

One of two topics explored is the limitations of the daily average in summarizing pollutant hourly profiles. The daily average of hourly measurements of air pollutant constituents provides continuity with previous studies using monitoring technology that only provided the daily average. However, other summary statistics are needed that make better use of all available information in 24-hr profiles. The daily average reflects the total daily dose, obscuring hourly resolution of the dose rate. Air pollutant exposures with comparable total daily doses may have very different effects when occurring at high levels over a few hours as opposed to low levels over a longer time. Alternative data-based choices for summary statistics are provided using principal component analysis to capture the exposure dose rate, while preserving ease of interpretation. This is demonstrated using the earliest hourly particle concentration data available for El Paso from archived records of particulate matter (PM)10. In this way, a significant association between evening PM10 exposures and nonaccidental daily mortality is found in El Paso from 1992 to 1995, otherwise missed using the daily average. Secondly, the nature and, hence, effects of particles in the ambient aerosol during El Paso sandstorms is believed different from that of particles present during still-air conditions resulting from atmospheric temperature inversions. To investigate this, wind speed (ws) is used as a surrogate variable to label PM10 exposures as Low-ws (primarily fine particles), High-ws (primarily coarse particles), or Mid-ws (a mixture of fine and coarse particles). A High-ws evening is significantly associated with a 10% lower risk of mortality on the succeeding third day, as compared with comparable exposures at Low- or Mid-ws. Although this analysis cannot be used to form firm conclusions because it uses a very small data set, it demonstrates the limitations of the daily average and suggests differential toxicity for different particle compositions.     

Ambient Oxidant Exposure andHealth Costs in the United States—1973

The body of information presented in this paper is directed to policy makers and administrators involved in the evaluation and assessment of damages caused by oxidant air pollution on human health and welfare and of possible benefits of control.

To provide a comparison of some of the benefits that can be obtained by reducing photochemical oxidant levels, estimated health costs were derived from data relating adverse health effects to hourly oxidant concentrations. Hourly oxidant or ozone concentrations were measured at approximately 400 monitoring stations scattered throughout the U.S. Most of these sites were located in major urban areas or in other areas where high oxidant concentrations prevailed. Estimates of populations at risk and per capita health costs were generated for those areas where oxidant data was available.

During the period 1971-1973, nearly two-thirds of the U.S. population resided in areas where the hourly primary standard for oxidants of 160 µg/m³ was exceeded. The total annual health cost attributable to oxidants was estimated to range from $120 to over $240 million in the U.S.     

Temporal Analysis of Airborne Particulate Matter Reveals a Dose-Rate Effect on Mortality in El Paso: Indications of Differential Toxicity for Different Particle Mixtures

Abstract

One of two topics explored is the limitations of the daily average in summarizing pollutant hourly profiles. The daily average of hourly measurements of air pollutant constituents provides continuity with previous studies using monitoring technology that only provided the daily average. However, other summary statistics are needed that make better use of all available information in 24-hr profiles. The daily average reflects the total daily dose, obscuring hourly resolution of the dose rate. Air pollutant exposures with comparable total daily doses may have very different effects when occurring at high levels over a few hours as opposed to low levels over a longer time. Alternative data-based choices for summary statistics are provided using principal component analysis to capture the exposure dose rate, while preserving ease of interpretation. This is demonstrated using the earliest hourly particle concentration data available for El Paso from archived records of particulate matter (PM)₁₀. In this way, a significant association between evening PM₁₀ exposures and nonaccidental daily mortality is found in El Paso from 1992 to 1995, otherwise missed using the daily average. Secondly, the nature and, hence, effects of particles in the ambient aerosol during El Paso sandstorms is believed different from that of particles present during stillair conditions resulting from atmospheric temperature inversions. To investigate this, wind speed (ws) is used as a surrogate variable to label PM₁₀ exposures as Low-ws (primarily fine particles), High-ws (primarily coarse particles), or Mid-ws (a mixture of fine and coarse particles). A High-ws evening is significantly associated with a 10% lower risk of mortality on the succeeding third day, as compared with comparable exposures at Low- or Mid-ws. Although this analysis cannot be used to form firm conclusions because it uses a very small data set, it demonstrates the limitations of the daily average and suggests differential toxicity for different particle compositions.     

The development of sulfur dioxide and ozone exposure profiles that mimic ambient conditions in the rural southeastern united states

A design for constructing experimental mixed-pollutant exposure profiles that reflect regional O₃ and SO₂ ambient air quality is described. The profiles were developed using hour-by-hour O₃ and SO₂ concentration data from monitoring sites in the southeastern United States where slash pine is indigenous. Only sites designated rural or remote, with co-monitored O₃ and SO₂, and at least 75% of the hourly values reported for the period April– October, were used. Each site was characterized by concentration, frequency of occurrence and duration of concentration values, length of time between episodes, and frequency of cooccurrence. A base profile, a 30-day hour-by-hour concentration regime, was constructed using averaged air quality characteristics from the selected sites. Using the base profile, additional regimes were constructed by increasing the concentration of all hourly values above a designated minimum, or by increasing the frequency of occurrence of selected hourly concentrations.     

Sensitivity of nitrogen dioxide concentrations to oxides of nitrogen controls in the United Kingdom

There is a possibility of further controls on emissions to the atmosphere of nitrogen oxides to meet air quality objectives in the UK. Data in the National Air Quality Archive were used to calculate the likely sensitivity of hourly concentrations of nitrogen dioxide in ambient urban air to changes in the total oxides of nitrogen. Since the role of atmospheric chemical reactions is to make the response non-linearly dependent on the emissions control, we seek to establish the magnitude and sign of the effects that this non-linearity might cause. We develop a quantitative approach to analysing the non-linearity in the data. Polynomial curve fits have been developed for the empirical ratio NO₂ : NO_x (the ‘yield’). They describe nitrogen dioxide concentrations using total oxides of nitrogen. The new functions have the important feature of increased yield in winter episodes. Simpler functions tend to omit this feature of the yields at the highest hourly concentrations. Based on this study, the hourly nitrogen dioxide objective in the UK may require emissions control of no more than ≈50% on total oxides of nitrogen at the most polluted sites: other sites require less or even no control.     

Using prognostic model-generated meteorological output in the AERMOD dispersion model: an illustrative application in Philadelphia, PA

In this study, we introduce the prospect of using prognostic model-generated meteorological output as input to steady-state dispersion models by identifying possible advantages and disadvantages and by presenting a comparative analysis. Because output from prognostic meteorological models is now routinely available and is used for Eulerian and Lagrangian air quality modeling applications, we explore the possibility of using such data in lieu of traditional National Weather Service (NWS) data for dispersion models. We apply these data in an urban application where comparisons can be made between the two meteorological input data types. Using the U.S. Environment Protection Agency's American Meteorological Society/U.S. Environmental Protection Agency Regulatory Model (AERMOD) air quality dispersion model, hourly and annual average concentrations of benzene are estimated for the Philadelphia, PA, area using both hourly MM5 model-generated meteorological output and meteorological data taken from the NWS site at the Philadelphia International Airport. Our intent is to stimulate a discussion of the relevant issues and inspire future work that examines many of the questions raised in this paper.     

Searching for evidence of acid-catalyzed enhancement of secondary organic aerosol formation using ambient aerosol data

Laboratory experiments suggest that strong acids promote formation of enhanced levels of secondary organic aerosol (SOA), and organic aerosols may contribute to the health impacts of fine PM. We report results from examining hourly speciated fine particle data for evidence of ambient aerosol acidity-catalyzed SOA formation, as indicated by larger increases in the concentrations of organic aerosol mass occurring on days and in locations where more acidic aerosol (lower NH₄⁺/SO₄⁼ molar ratios) exists. Data sets from the southeastern U.S. were examined for which hourly acidity of PM_2.5 aerosols could be estimated, and for which hourly organic carbon (OC) content had been measured simultaneously. Within-day organic aerosol changes during selected periods were statistically related to concurrent aerosol acidity levels estimated from nitrate-corrected ammonium-to-sulfate ratios. Data from the Look Rock, TN, TVA/IMPROVE site for mid-July to mid-August 2004 showed average compositions frequently as acidic as NH₄HSO₄, however, no apparent increases in OC levels with increasing aerosol acidity were observed, even when [OC] changes were compared with time-delayed aerosol acidity estimates. SEARCH network data (2003–2004) for rural Centreville, AL (CTR) and Yorkville, GA (YRK) sites were also examined. Warm-season acidity levels were higher at CTR than at YRK, and daytime levels exceeded those at night at both sites. At the YRK site no consistent positive correlations were found between changes in OC or TC levels and aerosol acidity, even with time lags up to 6 h. Aerosol acidity at this site, however, is relatively low due to nearby agricultural sources of NH₃. In contrast, during selected periods from April to October 2004, at CTR, 6-h lagged OC changes were weakly correlated with daytime, nitrate-corrected NH₄⁺/SO₄⁼ molar ratios, but distinguishing this apparent relationship from meteorological effects on measured OC levels is challenging.     

A Test Reference Year (TRY) approach to gas dispersion in the atmosphere

For environmental analysis such as the dispersion of pollutants in the atmosphere, it is essential to have meteorological data that are relevant for a long period. In this paper, we explore the possibility of using an environmental Test Reference Year (TRY), i.e., a set of real, contemporaneous and hourly meteorological variables, 'extracted' from a hourly series of at least 10 years, for modelling pollutant dispersion in the atmosphere. The classical approach, based on a statistical data set, implies the loss of important information such as the real correlation between the different meteorological variables, and this implies crude approximation in the simulation results. We compare the simulation results with the long hourly 10 years data set (which can be considered a 'brute force' approach, since it requires a huge amount of data and time processing, but it is here considered the most severe benchmark) and with the statistical data set commonly used. It is shown that the results obtained using the TRY have a good agreement with the ones obtained with the simulation of the 10 years and they are also much better than those obtained using the statistical data set.     

The utility of Pinus sylvestris L. in dendrochemical investigations: pollution impact of lead mining and smelting in Darley Dale, Derbyshire, UK

This research investigates atmospheric pollution from an isolated and increasingly productive lead-smelting site by examining the dendrochemistry of Pinus sylvestris growing in the local environment and at control sites. Tree increment cores and soil in the rooting environment were analysed for lead content. Inter-site comparisons of lead-in-soil suggest that contamination of the soil may be a less important pathway for lead inclusion within wood than pathways via bark or needles. Levels of lead-in-wood (up to 38mgkg(-1)) are at the upper end of those previously reported. There is evidence of radial translocation of lead towards the heartwood and variability in intra-site dendrochemical records. Mean site lead-in-wood records can however be related to a well-documented pollution chronology and also suggest the importance of local topography in the dispersal and deposition of particulate lead. This study demonstrates that P. sylvestris can be used to estimate the scale and timing of past pollution episodes in similar environmental contexts to those investigated at Darley Dale, where precisely dated pollution chronologies are lacking.     

A comparison of hourly with annual air pollutant emissions: Implications for estimating acute exposure and public health risk

Health risks from air pollutants are evaluated by comparing chronic (i.e., an average over 1 yr or greater) or acute (typically 1-hr) exposure estimates with chemical- and duration-specific reference values or standards. When estimating long-term pollutant concentrations via exposure modeling, facility-level annual average emission rates are readily available as model inputs for most air pollutants. In contrast, there are far fewer facility-level hour-by-hour emission rates available for many of these same pollutants. In this report, we first analyze hour-by-hour emission rates for total reduced sulfur (TRS) compounds from eight kraft pulp mill operations. This data set is used to demonstrate discrepancies between estimating exposure based on a single TRS emission rate that has been calculated as the mean of all operating hours of the year, as opposed to reported hourly emission rates. A similar analysis is then performed using reported hourly emission rates for sulfur dioxide (SO₂) and oxides of nitrogen (NO_x) from three power generating units from a U.S. power plant. Results demonstrate greater variability at kraft pulp mill operations, with ratios of reported hourly to average hourly TRS emissions ranging from less than 1 to greater than 160 during routine facility operations. Thus, if fluctuations in hourly emission rates are not accounted for, over- or underestimates of hourly exposure, and thus acute health risk, may occur. In addition to this analysis, we also demonstrate an additional challenge when assessing health risk based on hourly exposures: the lack of human health reference values based on 1-hr exposures.

Implications: Largely due to the lack of reported hourly emission rate data for many air pollutants, an hourly average emission rate (calculated from an annual emission rate) is often used when modeling the potential for acute health risk. We calculated ratios between reported hourly and hourly average emission rates from pulp and paper mills and a U.S. power plant to demonstrate that if not considered, hourly fluctuations in emissions could result in an over- or underestimation of exposure and risk. We also demonstrate the lack of 1-hr human health reference values meant to be protective of the general population, including children.     

Characterizing changes in surface ozone levels in metropolitan and rural areas in the United States for 1980–2008 and 1994–2008

In this analysis, we characterize urban and rural ozone (O₃) trends across the US for the periods 1980–2008 (29 years) and 1994–2008 (15 years) using three exposure metrics, which summarize daily O₃ concentrations to reflect different ways O₃ may affect human health and vegetation. We observe that a statistically significant trend at a specific monitoring site, using one exposure metric, does not necessarily result in a similar trend using the other two metrics. The two most common trends among the monitoring sites are either a continuation of negative trending over the 29-year period or a shift from negative to no trend status, indicating a leveling off of the trending. Very few sites exhibit statistically significant increases in the exposure indices. In characterizing the statistically significant changes in the distribution of hourly average O₃, we observe subtle statistically significant changes in the lower part of the distribution (i.e., below 50 ppb) that are not necessarily captured by the trending patterns associated with the three exposure metrics. Using multisite data from 12 metropolitan cities, we find that as the frequency of higher hourly average concentrations is reduced, the lower hourly average concentrations also move upward toward the mid-level values. The change in the number of the hourly average concentrations in the lower range is consistent with decreased NO scavenging. We recommend assessing possible subtle shifts in O₃ concentrations by characterizing changes in the distribution of hourly average concentrations by month. Identifying statistically significant monthly changes in the mid- and low-level hourly average concentrations may provide important information for assessing changes in physical processes associated with global climate change, long-range transport, and the efficacy of models used for emission and risk reductions. Our results indicate that it is important to investigate the change in the trending pattern with time (e.g., moving 15-year trending) in order to assess how year-to-year variability may influence the trend calculation.     

Changes in seasonal and diurnal cycles of ozone and temperature in the eastern U.S.

The pollutant tropospheric ozone causes human health problems, and environmental degradation and acts as a potent greenhouse gas. Using long-term hourly observations at five US air quality monitoring surface stations we studied the seasonal and diel cycles of ozone concentrations and surface air temperature to examine the temporal evolution over the past two decades. Such an approach allows visualizing the impact of natural and anthropogenic processes on ozone; nocturnal inversion development, photochemistry, and stratospheric intrusion. Analysis of the result provides an option for determining the duration for a regulatory ozone season. The application of the method provides independent confirmation of observed changes and trends in the ozone and temperature data records as reported elsewhere. The results provide further evidence supporting the assertion that ozone reductions can be attributed to emission reductions as opposed to weather variation. Despite a (～0.5 °C decade^?1) daytime warming trend, ozone decreased by up to 6 ppb decade^?1 during times of maximum temperature in the most polluted locations. Ozone also decreased across the emission reduction threshold of 2002 by 6–10 ppb indicating that emission reductions have been effective where and when it is most needed. Longer time series, and coupling with other data sources, may allow for the direct investigation of climate change influence on regional ozone air pollution formation and destruction over annual and daily time scales.     

Correlating emissions with time and temperature to predict worst-case emissions from open liquid area sources

The two primary factors influencing ambient air pollutant concentrations are emission rate and dispersion rate. Gaussian dispersion modeling studies for odors, and often other air pollutants, vary dispersion rates using hourly meteorological data. However, emission rates are typically held constant, based on one measured value. Using constant emission rates can be especially inaccurate for open liquid area sources, like wastewater treatment plant units, which have greater emissions during warmer weather, when volatilization and biological activity increase. If emission rates for a wastewater odor study are measured on a cooler day and input directly into a dispersion model as constant values, odor impact will likely be underestimated. Unfortunately, because of project schedules, not all emissions sampling from open liquid area sources can be conducted under worst-case summertime conditions. To address this problem, this paper presents a method of varying emission rates based on temperature and time of the day to predict worst-case emissions. Emissions are varied as a linear function of temperature, according to Henry's law, and a tenth order polynomial function of time. Equation coefficients are developed for a specific area source using concentration and temperature measurements, captured over a multiday period using a data-logging monitor. As a test case, time/temperature concentration correlation coefficients were estimated from field measurements of hydrogen sulfide (H2S) at the Rowlett Creek Wastewater Treatment Plant in Garland, TX. The correlations were then used to scale a flux chamber emission rate measurement according to hourly readings of time and temperature, to create an hourly emission rate file for input to the dispersion model ISCST3. ISCST3 was then used to predict hourly atmospheric concentrations of H2S. With emission rates varying hourly, ISCST3 predicted 384 acres of odor impact, compared with 103 acres for constant emissions. Because field sampling had been conducted on relatively cool days (85-90 degrees F), the constant emission rate underestimated odor impact significantly (by 73%).     

The Characterization of Ozone and Sulfur Dioxide Air Quality Data for Assessing Possible Vegetation Effects

Since the 1960s, much effort has been devoted to collecting and formatting air quality data. This paper discusses 1) the availability of air quality data for assessing potential biological impacts associated with ozone and sulfur dioxide ambient exposures, 2) examples of how air quality data can be characterized for assessing vegetation effects, and 3) the limitations associated with some exposure parameters used for developing relevant vegetation doseresponse yield reduction models. Data are presented showing that some ozone monitoring sites not continuously affected by local urban sources experience consecutive hourly ozone exposures ≥0.10 ppm in the late evening and early morning hours. These sites experience their maximum ozone concentrations either in the spring or summer months. Sites influenced by local rural sources experience their maximum ozone concentrations during the summer months. It is suggested that further research be performed to identify whether the sensitivity of a target organism at the time of exposure, as well as the pollutant concentration and chemical form that enters into the target organism, is as important in defining effects as air pollutant exposure alone.     

An Urban Diffusion Simulation Model For Carbon Monoxide

A relatively simple Gaussian-type diffusion simulation model for calculating urban carbon monoxide (CO) concentrations as a function of local meteorology and the distribution of traffic is described. The model can be used in two ways: (1) in the synoptic mode, in which hourly concentrations at one or many receptor points are calculated from historical or forecast traffic and meteorological data; and (2) in the climatological mode, in which concentration frequency distributions are calculated on the basis of long-term sequences of input data. For model evaluation purposes, an extensive field study involving meteorological and air-quality measurements was conducted during November-December 1970 in San Jose, Calif., which has an automated network to provide traffic data throughout the central business district. Model refinements made on the basis of the data from this experimental program include the addition of a street-canyon submodel to compensate for the important aerodynamic effects of buildings on CO concentrations at streetside receptors. The magnitude of these effects was underscored by the concentrations measured on opposite sides of the street in San Jose, which frequently differed by a factor of two or more. Evaluation of the revised model has shown that calculated and observed concentration frequency distributions for street-canyon sites are in good agreement. Hour-average predictions are well correlated with observations (correlation coefficient of about 0.6 to 0.7), and about 80 percent of the calculated values are within 3 ppm of the observed hour-average concentrations, which ranged as high as 16 ppm.     

Computer Analysis of the California Cycle

The current trend toward greater instrumentation in analysis of automobile exhaust gases is sure to increase in future years. This will come about as a result of increased activity to find a solution to air pollution problems resulting from automobile exhaust gases. Owing to the complex driving cycle needed to evaluate vehicle emission, considerable time has been required to analyze and interpret the records from any run. To alleviate this analytic problem, an automatic data logger was obtained that records on magnetic tape the signal from a number of analytical instruments each second (in binary coded decimal form). These records are then analyzed on a computer to give integrated and averaged results over the specified driving cycle. There is no longer any need for manual evaluation of the data. In addition to the standard analyses already mentioned, the use of the data logger permits a much more complete analysis of what is happening in a vehicle. For example, the analytical instruments used include an oxygen analyzer in addition to carbon dioxide, carbon monoxide, and hydrocarbons. With these measurements the air-fuel ratio of any or all driving conditions can be calculated.     

Comparative statistical study of hourly precipitation determined by radar-based Stage IV and ground-based methods in the North Central United States

Detailed hourly precipitation data are required for long-range modeling of dispersion and wet deposition of particulate matter and water-soluble pollutants using the CALPUFF model. In sparsely populated areas such as the north central United States, ground-based precipitation measurement stations may be too widely spaced to offer a complete and accurate spatial representation of hourly precipitation within a modeling domain. The availability of remotely sensed precipitation data by satellite and the National Weather Service array of next-generation radars (NEXRAD) deployed nationally provide an opportunity to improve on the paucity of data for these areas. Before adopting a new method of precipitation estimation in a modeling protocol, it should be compared with the ground-based precipitation measurements, which are currently relied upon for modeling purposes. This paper presents a statistical comparison between hourly precipitation measurements for the years 2006 through 2008 at 25 ground-based stations in the north central United States and radar-based precipitation measurements available from the National Center for Environmental Predictions (NCEP) as Stage IV data at the nearest grid cell to each selected precipitation station. It was found that the statistical agreement between the two methods depends strongly on whether the ground-based hourly precipitation is measured to within 0.1 in/hr or to within 0.01 in/hr. The results of the statistical comparison indicate that it would be more accurate to use gridded Stage IV precipitation data in a gridded dispersion model for a long-range simulation, than to rely on precipitation data interpolated between widely scattered rain gauges.

Implications:

The current reliance on ground-based rain gauges for precipitation events and hourly data for modeling of dispersion and wet deposition of particulate matter and water-soluble pollutants results in potentially large discontinuity in data coverage and the need to extrapolate data between monitoring stations. The use of radar-based precipitation data, which is available for the entire continental United States and nearby areas, would resolve these data gaps and provide a complete and accurate spatial representation of hourly precipitation within a large modeling domain.     

Diurnal and seasonal patterns in light scattering,extinction, and relative humidity

Since 1988, several federal and state governmental agencies in the US have coordinated efforts to operate the interagency monitoring of protected visual environments (IMPROVE) network at sites in remote areas. Most IMPROVE sites are equipped with either a transmissometer to measure light extinction (B_ext) or a nephelometer to measure particle scattering (B_sp). Optical, temperature, and relative humidity (RH) measurements are made hourly at these sites. The diurnal and seasonal patterns in these data are examined and discussed here. At many IMPROVE sites the diurnal patterns in RH and therefore B_ext or B_sp are as expected based on average temperature. On average, RH is higher at night and during the winter than during warmer times of the day and year. Also as expected, based on RH alone, at many sites hourly mean B_ext or B_sp values are either in phase with RH or weakly dependent on time of day. Usually, the diurnal differences are not as large as the seasonal differences. Another group of IMPROVE sites have mean RH patterns similar to those described above but have a different diurnal pattern in measured scattering or extinction. At these sites, the highest mean B_sp or B_ext occurs during mid-day rather than at night. At several of these sites, especially those on ridge tops, it is hypothesized that this is because the diurnal shifts in mixing height only allow the surface layer of the atmosphere to reach the monitor during mid-day. Several other sites have unique diurnal or seasonal patterns in average B_sp or B_ext that can usually be linked to emissions in nearby source regions or local meteorology and terrain.     

Estimating the Effect of Being Indoors on Total Personal Exposure to Outdoor Air Pollution

A personal air quality model (PAQM) has been developed to estimate the effect of being indoors on total personal exposure to outdoor-generated air pollution. Designed to improve air toxics risk assessment, PAQM accounts for individual hourly activity patterns, indoor-outdoor differences, physical exercise level, and geographic location for up to 56 different population groups. Unique hourly activity profiles are specified for each population group; group members are assigned each hour to one of up to 10 different indoor and outdoor microenvironments. To illustrate PAQM use, we apply it to two example cases: a long-term example representative of situations where pollutant health impact is related to integrated exposure (as in the case of potentially carcinogenic air toxics) and a short-term example representative of situations where health impact is related to acute exposure to peak concentrations (as with ozone).

Case study results illustrate that personal exposure, and thus health risk, attributable to outdoor-generated air pollution is sensitive to indoor-outdoor differences and population mobility. Where health impact is related to long-term integrated exposure (e.g., air toxics), exposure and subsequent risk are likely to be lower than that estimated by previous modeling techniques which do not account for such effects.