Evaluation of a Probabilistic Exposure Model Applied

The probabilistic National Ambient Air Quality Standards (NAAQS) Exposure Model applied to carbon monoxide (pNEM/CO) was developed by the U.S. Environmental Protection Agency (EPA) to estimate frequency distributions of population exposure to carbon monoxide (CO) and the resulting carboxyhemoglobin (COHb) levels. To evaluate pNEM/CO, the model was set up to simulate CO exposure data collected during a Denver Personal Exposure Monitoring Study (PEM) conducted during the winter of 1982-1983.

This paper compares computer-simulated exposure distributions obtained by pNEM/CO with the observed cumulative

relative frequency distributions of population exposure to CO from 779 people in the Denver PEM study. The subjects were disaggregated into two categories depending upon whether they lived in a home with a gas stove or an electric stove. The observed and predicted population exposure frequency distributions were compared in terms of 1-hr daily maximum exposure (1DME) and 8-hr daily maximum moving average exposure (8DME) for people living in homes with gas stove or an electric stove. For 1DME, the computer-simulated results from pNEM/CO agreed most closely within the range of 6-13 ppm, but overestimated occurrences at low exposure (<6 ppm) and underestimated occurrences at high exposure (>13 ppm). For 8DME, the predicted exposures agreed best with observed exposures in the range of CO concentration between 5.5 and 7 ppm, and over-predicted occurrences below 5.5 ppm and under-predicted occurrences above 7 ppm.     

Evaluation of a Probabilistic Exposure Model Applied to Carbon Monoxide (pNEM/CO) Using Denver Personal Exposure Monitoring Data

The probabilistic National Ambient Air Quality Standards (NAAQS) Exposure Model applied to carbon monoxide (pNEM/CO) was developed by the U.S. Environmental Protection Agency (EPA) to estimate frequency distributions of population exposure to carbon monoxide (CO) and the resulting carboxyhemoglobin (COHb) levels. To evaluate pNEM/CO, the model was set up to simulate CO exposure data collected during a Denver Personal Exposure Monitoring Study (PEM) conducted during the winter of 1982-1983. This paper compares computer-simulated exposure distributions obtained by pNEM/CO with the observed cumulative relative frequency distributions of population exposure to CO from 779 people in the Denver PEM study.

The subjects were disaggregated into two categories depending upon whether they lived in a home with a gas stove or an electric stove. The observed and predicted population exposure frequency distributions were compared in terms of 1-hr daily maximum exposure (1DME) and 8-hr daily maximum moving average exposure (8DME) for people living in homes with gas stove or an electric stove. For 1DME, the

computer-simulated results from pNEM/CO agreed most closely within the range of 6-13 ppm, but overestimated occurrences at low exposure (<6 ppm) and underestimated occurrences at high exposure (>13 ppm). For 8DME, the predicted exposures agreed best with observed exposures in the range of CO concentration between 5.5 and 7 ppm, and over-predicted occurrences below 5.5 ppm and under-predicted occurrences above 7 ppm.     

The prediction of maximum air pollution concentrations for tsp and co using Larsen's model and the ATDL model

A modeling methodology is introduced to predict maximum TSP concentrations. The methodology consists of using the ATDL model of Gifford and Hanna (1971) and the Larsen model (1971) to predict the distribution of air pollution concentrations from wind speed data for the upper percentiles. The data set used is total suspended particulate (TSP) data. Since the highest TSP concentrations occur at extremely low wind speeds where the use of the ATDL model is questionable, the methodology adopted here is to use the ATDL model together with wind speed data to reproduce TSP concentrations only for the range of wind speeds where the model is applicable. Assuming these TSP concentrations are lognormally distributed, Larsen's model is then used to predict the maximum TSP concentration. These results agree with the work by Daly and Steele (1976) for CO. This methodology works quite well, for time averages of 8 h or more but in its present form is questionable for shorter time averages.     

Personal carbon monoxide exposures of preschool children in Helsinki, Finland—comparison to ambient air concentrations

The associations of personal carbon monoxide (CO) exposures with ambient air CO concentrations measured at fixed monitoring sites, were studied among 194 children aged 3–6 yr in four downtown and four suburban day-care centers in Helsinki, Finland. Each child carried a personal CO exposure monitor between 1 and 4 times for a time period of between 20 and 24 h. CO concentrations at two fixed monitoring sites were measured simultaneously. The CO concentrations measured at the fixed monitoring sites were usually lower (mean maximum 8-h concentration: 0.9 and 2.6 mg m⁻³) than the personal CO exposure concentrations (mean maximum 8-h concentration: 3.3 mg m⁻³). The fixed site CO concentrations were poor predictors of the personal CO exposure concentrations. However, the correlations between the personal CO exposure and the fixed monitoring site CO concentrations increased (−0.03–−0.12 to 0.13–0.16) with increasing averaging times from 1 to 8 h. Also, the fixed monitoring site CO concentrations explained the mean daily or weekly personal CO exposures of a group of simultaneously measured children better than individual exposure CO concentrations. This study suggests that the short-term CO personal exposure of children cannot be meaningfully assessed using fixed monitoring sites.     

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.     

Carbon monoxide concentration forecasting in Santiago, Chile

In the city of Santiago, Chile, air quality is defined in terms of particulate matter with an aerodynamic diameter < or = 10 microm (PM10) concentrations. An air quality forecasting model based on past concentrations of PM10 and meteorological conditions currently is used by the metropolitan agency for the environment, which allows restrictions to emissions to be imposed in advance. This model, however, fails to forecast between 40 and 50% of the days considered to be harmful for the inhabitants every year. Given that a high correlation between particulate matter and carbon monoxide (CO) concentrations is observed at monitoring stations in the city, a model for CO concentration forecasting would be a useful tool to complement information about expected air quality in the city. Here, the results of a neural network-based model aimed to forecast maximum values of the 8-hr moving average of CO concentrations for the next day are presented. Forecasts from the neural network model are compared with those produced with linear regressions. The neural network model seems to leave more room to adjust free parameters with 1-yr data to predict the following year's values. We have worked with 3 yr of data measured at the monitoring station located in the zone with the worst air quality in the city of Santiago, Chile.     

Alteration in Carboxyhemoglobin Concentrations During Exposure to 9 ppm Carbon Monoxide for 8 Hours at Sea Level and 2134 m Altitude in a Hypobaric Chamber

Seventeen non-smoking young men served as subjects to determine the alteration in carboxyhemoglobin (COHb) concentrations during exposure to 0 or 9 ppm carbon monoxide for 8 hours (CO) at sea level or an altitude of 2134 meters (7000 feet) in a hypobaric chamber. Nine subjects rested during the exposure and 8 exercised for 10 minutes of each exposure hour at a mean ventilation of 25 L (BTPS). All subjects performed a maximal aerobic capacity test at the completion of their respective exposures. Carboxyhemoglobin concentrations fell in all subjects during their exposures to 0 ppm CO at sea level or 2134 m. During the 8-h exposures to 9 ppm CO, COHb rose linearly from approximately 0.2 percent to 0.7 percent. No significant differences in uptake were found whether the subjects were resting or intermittently exercising during their 8-h exposures. COHb levels attained were similar at both sea level and 2134 m. Maximal aerobic capacity was reduced approximately 7-10 percent consequent to altitude exposure during 0 ppm CO exposures. These values were not altered following exposure for 8 h to 9 ppm CO in either the resting or exercising subjects.     

Estimates of community exposure and health risk to sulfur dioxide from power plant emissions using short-term mobile and stationary ambient air monitoring

To estimate plausible health effects associated with peak sulfur dioxide (SO₂) levels from three coal-fired power plants in the Baltimore, Maryland, area, air monitoring was conducted between June and September 2013. Historically, the summer months are periods when emissions are highest. Monitoring included a 5-day mobile and a subsequent 61-day stationary monitoring study. In the stationary monitoring study, equipment was set up at four sites where models predicted and mobile monitoring data measured the highest average concentrations of SO₂. Continuous monitors recorded ambient concentrations each minute. The 1-min data were used to calculate 5-min and 1-hr moving averages for comparison with concentrations from clinical studies that elicited lung function decrement and respiratory symptoms among asthmatics. Maximum daily 5-min moving average concentrations from the mobile monitoring study ranged from 70 to 84 ppb (183–220 µg/m³), and maximum daily 1-hr moving average concentrations from the mobile monitoring study ranged from 15 to 24 ppb (39–63 µg/m³). Maximum 5-min moving average concentrations from stationary monitoring ranged from 39 to 229 ppb (102–600 µg/m³), and maximum daily 1-hr average concentrations ranged from 15 to 134 ppb (40–351 µg/m³). Estimated exposure concentrations measured in the vicinity of monitors were below the lowest levels that have demonstrated respiratory symptoms in human clinical studies for healthy exercising asthmatics. Based on 5-min and 1-hr monitoring, the exposure levels of SO₂ in the vicinity of the C.P. Crane, Brandon Shores, and H.A. Wagner power plants were not likely to elicit respiratory symptoms in healthy asthmatics.

Implications: Mobile and stationary air monitoring for SO₂ were conducted to quantify short-term exposure risk, to the surrounding community, from peak emissions of three coal-fired power plants in the Baltimore area. Concentrations were typically low, with only a few 5-min averages higher than levels indicated during clinical trials to induce changes in lung capacity for healthy asthmatics engaged in exercise outdoors.     

Analysis of air pollution in two major Korean cities: trends, seasonal variations, daily 1-hour maximum versus other hour-based concentrations, and standard exceedances

This study considers the characteristics of carbon monoxide (CO), nitrogen dioxide (NO(2)), ozone (O(3)) and sulfur dioxide (SO(2)) in two major South Korean cities, including the capital city of Seoul, over a time period of 7-8 years. Changes in the annual mean and percentiles of the daily 1-h maximum and other hour-based concentrations varied according to the compound and city type. Seasonal variations varied according to the compound, yet not with the city type. Both Seoul and Taegu exhibited lower O(3) concentrations in July compared to other summer months. There was a high degree of correlation between the daily 1- and 8-h maximum or daily mean concentrations of all compounds in both cities, with an R(2) of 0.66-0.90 at p<0.0001. It was indicated that for CO and O(3), the 8-h standard was more stringent than the 1-h standard, while for NO(2) and SO(2), the 1-h standard was more stringent than the 24-h standard. The correlation coefficients between the daily 1-h maximum and daily mean concentrations decreased as the maximum concentration values of NO(2), O(3 ), and SO(2) increased in the two cities. For all the target compounds, Seoul recorded a substantially higher frequency of days with concentrations above the relevant 1-, 8-, and 24-h standards compared to Taegu.     

Persistence Factors for Mobile Source (Roadway) Carbon Monoxide Modeling

A critical step in the modeling of the carbon monoxide (CO) impacts of mobile sources is predicting an 8-hour CO concentration given a modeled "worst-case" 1-hour concentration. Often, this is done by a multiplicative persistence factor. A meteorological persistence factor (MPF) accounts for the variability over 8 hours of wind speed, wind direction, stability class, and temperature. A vehicular persistence factor (VPF) reflects the lower traffic volumes during the off-peak hours.

Hourly meteorological data for ten years for four cities in Florida were obtained from the National Climatic Data Center. The CALINE3 model was used to obtain hourly CO concentrations, which were combined to derive MPFs for each city. Similarly, VPFs were derived from hourly vehicle counts from one busy roadway in each city. The mean VPF multiplied by the second highest MPF was defined as the worst-case total persistence factor (TPF). These worst-case TPFs increased significantly as more hours of nighttime were included in the 8- hour averaging time, but were fairly consistent from city to city. In general, the results suggest worst-case TPFs in the range of 0.4 to 0.5, lower than has been recommended by EPA in the past.     

The Exposure to Carbon Monoxide of Occupants of Vehicles Moving in Heavy Traffic

Carbon monoxide and hydrocarbons were sampled at operator’s nose height inside vehicles moving in moderate to heavy traffic in six cities. The samples were integrated over 20-30 minutes by collection in Mylar bags. Carbon monoxide and hydrocarbons were analyzed by infrared and flame ionization, respectively, with instruments at the Continuous Air Monitoring Program (CAMP) station in each city. Detector tubes for carbon monoxide were also used to determine 5-min concentrations at suspected high points in the field. Estimates of traffic density were made. Three types of traffic arteries were considered: (7) heavily traveled, wide expressways, (2) main city streets with moderately rapid vehicular traffic, and (3) center city streets with slow-moving traffic. Integrated half-hour CO concentrations obtained within the vehicles while in traffic were generally considerably higher than the concurrent concentrations measured at the CAMP sites. In-traffic CO values in all cities sampled exceeded 30 ppm in at least 10% of the integrated samples. The range of city averages was 21–39 ppm carbon monoxide and the range of individual integrated samples was 7–77 ppm of carbon monoxide.     

Spatial heterogeneity of PM10 and O3 in São Paulo, Brazil, and implications for human health studies

Developing exposure estimates is a challenging aspect of investigating the health effects of air pollution. Pollutant levels recorded at centrally located ambient air quality monitors in a community are commonly used as proxies for population exposures. However, if ample intraurban spatial variation in pollutants exists, city-wide averages of concentrations may introduce exposure misclassification. We assessed spatial heterogeneity of particulate matter with an aerodynamic diameter < or = 10 microm (PM10) and ozone (O3) and evaluated implications for epidemiological studies in S?o Paulo, Brazil, using daily (24-hr) and daytime (12-hr) averages and 1-hr daily maximums of pollutant levels recorded at the regulatory monitoring network. Monitor locations were also analyzed with respect to a socioeconomic status index developed by the municipal government. Hourly PM10 and O3 data for the Sāo Paulo Municipality and Metropolitan Region (1999-2006) were used to evaluate heterogeneity by comparing distance between monitors with pollutants' correlations and coefficients of divergence (CODs). Both pollutants showed high correlations across monitoring sites (median = 0.8 for daily averages). CODs across sites averaged 0.20. Distance was a good predictor of CODs for PM10 (p < 0.01) but not O3, whereas distance was a good predictor of correlations for O3 (p < 0.01) but not PM10. High COD values and low temporal correlation indicate a spatially heterogeneous distribution of PM10. Ozone levels were highly correlated (r > or = 0.75), but high CODs suggest that averaging over O3 levels may obscure important spatial variations. Of municipal districts in the highest of five socioeconomic groups, 40% have > or = 1 monitor, whereas districts in the lowest two groups, representing half the population, have no monitors. Results suggest that there is a potential for exposure misclassification based on the available monitoring network and that spatial heterogeneity depends on pollutant metric (e.g., daily average vs. daily 1-hr maximum). A denser monitoring network or alternative exposure methods may be needed for epidemiological research. Findings demonstrate the importance of considering spatial heterogeneity and differential exposure misclassification by subpopulation.     

Relating meteorological variables and trends in motor vehicle emissions to monthly urban carbon monoxide concentrations

A model which quantifies the relationship between the monthly time series for CO emissions, the monthly time series in ambient CO concentration, and meteorologically driven dispersion was developed. Fifteen cities representing a wide range of geographical and climatic conditions were selected. An eight-year time series (1984–1991 inclusive) of monthly averaged data were examined in each city. A new method of handling missing ambient concentration values which is designed to calculate city-wide average concentrations that follow the trend seen at individual monitor sites is presented. This method is general and can be used in other applications involving missing data. The model uses emissions estimates along with two meteorological variables (wind speed and mixing height) to estimate monthly averages of ambient air pollution concentrations. The model is shown to have a wide range of applicability; it works equally well for a wide range of cities that have very different temporal CO distributions. The model is suited for assessing long-term trends in ambient air pollutants and can also be used for estimating seasonal variations in concentration, estimation of trends in emissions, and for filling in gaps in the ambient concentration record.     

Air Pollution Control and Waste Management in a New World

Abstract

A research site for atmospheric chemistry and air pollution measurements was established at Pinnacle State Park in Addison, NY, in 1995. This paper presents an overview of the site characteristics and measurement program, as well as monthly average concentrations for many of the trace gas and aerosol pollutants over the full measurement period. Monthly averaged ozone concentrations range from values as low as 15 parts per billion (ppb) during cold-season months, to values approaching 50 ppb during some spring and summer months. Sulfur dioxide (SO₂), oxides of nitrogen (NO_x), and reactive odd nitrogen (NO_y) all show distinct seasonal variation, with summertime monthly averages as low as 1–3 ppb, and wintertime monthly averages from 6–12 ppb. The variation in carbon monoxide (CO) is much smaller, with minimums of approximately 150 ppb and maximums only rarely exceeding 250 ppb. Data for three hydrocarbon species propane, benzene, and isoprene—are presented. Propane and benzene show higher monthly averaged concentrations in the winter and lower values in the summer, with values ranging over a factor of 4–5. Isoprene, on the other hand has much higher values during the summer season, sometimes a factor of 10 or more greater than concentrations measured in the winter. Monthly averaged plots for fine particulate matter (PM_2.5) beginning in 1999 show a robust summer maximum and winter minimum, and roughly a factor of two difference between the two. An empirical measure of ozone production using the correlation of hour-averaged ozone and NO_y data illustrates relatively robust ozone production during some, but not all, summertime months over the time period. Also, an analysis of the frequency distribution of the hours of maximum ozone concentration shows a strong mid-afternoon peak, as expected, but also a prominent secondary maximum centered around midnight. The secondary peak is interpreted as ozone transported from ozone-producing areas to the west, including Buffalo, Cleveland, Pittsburgh, and the Ohio Valley. Finally, SO₂ concentrations as a function of wind direction clearly indicate maximum impacts when the winds are out of the south (Pittsburgh and Philadelphia), with a secondary peak when the winds are from the north-northeast, consistent with the locations of major SO₂ emission sources in the region.     

Establishing Relevant Ozone Standards to Protect Vegetation and Human Health: Exposure/Dose-Response Considerations

For assessing the efficacy of a specific form of the National Ambient Air Quality Standard for 0₃, those exposure patterns that result in vegetation and human health effects must be identified. For vegetation, it has been found that the higher hourly average concentrations should be weighted more than the lower concentrations. Controlled human exposure work supports the suggestion that concentration may be more important than exposure duration and ventilation rates. It has been indicated in the literature that the current form of the federal 0₃ standard may not be appropriate for protecting vegetation and human health from 0₃ exposures. The proposed use of the cumulative index alone as a form of the standard may not provide sufficient protection to vegetation. An extended-period average index, such as a daily maximum 8-hour average concentration, may not be appropriate to protect human health because of the reduced ability to observe differences among hourly 0₃ concentrations exhibited within exposure regimes. For both vegetation and human health effects research, additional experimentation is required to identify differences in responses that occur when ambient-type exposure regimes are applied. Any standard promulgated to protect vegetation and human health from 0₃ exposures should consider combining cumulative exposure indices with other parameters so that those unique exposures that have the potential for eliciting an adverse effect can be adequately described.     

Evaluation of CO exposure in active smokers while smoking using breath analysis technique

The current study evaluated the personal CO exposure of active smokers while smoking under controlled conditions, decay rate of CO in the body following active smoking, and CO accumulation in the body from repeated active smoking using a novel device for the direct measurement of alveolar breath CO. Prior to this evaluation, the proposed alveolar CO measurement device was successfully evaluated as regards the effect of humidity, CO recovery, carryover effect, and in comparison with the bag sampling method. The breath concentrations prior to and after a single cigarette were measured using a repeated measure design. Under the controlled conditions employed in the present study, active smoking was found to cause a significant body burden of CO. The post-exposure breath CO level was 1.6-2.0 times higher than the background breath level, depending on the subject and cigarette brand. In addition, the pre- and post-exposure breath concentrations were both significantly different among the subjects, yet the ratios of post-exposure to pre-exposure breath concentrations did not differ significantly between the different cigarette brands. The time-series alveolar breath concentrations measured following active smoking showed that the post-exposure alveolar CO concentrations decreased slowly even in the early phase of the decay curves, indicating a mono-compartment uptake and elimination model for the human body. The half-lives estimated in the present study (301, 315, and 385 min) were longer than or comparable to those in previous studies. The breath measurements prior to and after repeated active smoking exhibited a significant increasing trend for both the pre- and post-exposure concentrations. The changes in the pre- and post-exposure breath CO concentrations with repeated smoking ranged from 7% to 23% and from 10% to 15%, respectively, with half-hour intervals between cigarettes, and from 4% to 11% and from 6% to 8%, respectively, with hour intervals between cigarettes. Accordingly, most of the current results indicated that CO was accumulated in the human body with repeated active smoking.     

Carbon Monoxide and Lead-An Environmental Appraisal

Because of the common source, lead and CO values in the atmosphere tend to behave in a similar manner. Thus, diurnal variations in these two pollutants show a pattern related to motor vehicle traffic flow. Also, the exposure to both vary by orders of magnitude with the highest being on the road (in the car) thus setting up special dosage situations. Community sources seem to affect background level at least based on fall-off with distance. There may be a relatively wider exposure of the general population to lead and CO. While the lead levels may not be increasing in the downtown portion of the central city proper, typical central city levels of several years ago may be more diffuse and spread out, thus occurring over increasingly large portions of the community. Similarly, there may be a wider exposure of the population to CO as the levels become more nearly uniformly high over a larger area. In addition, there may be problems of a shorter term exposure to high levels of CO in commuter traffic. This may be of consequence to selected types of drivers or passengers. Finally, it should also be noted that during air pollution episodes, CO levels appear to rise with no data currently available on changes in concomitant ambient lead levels.     

Ozone distribution and phytotoxic potential in mixed conifer forests of the San Bernardino Mountains, southern California

In the San Bernardino Mountains of southern California, ozone (O(3)) concentrations have been elevated since the 1950s with peaks reaching 600ppb and summer seasonal averages >100ppb in the 1970s. During that period increased mortality of ponderosa and Jeffrey pines occurred. Between the late 1970s and late1990s, O(3) concentrations decreased with peaks approximately 180ppb and approximately 60ppb seasonal averages. However, since the late 1990s concentrations have not changed. Monitoring during summers of 2002-2006 showed that O(3) concentrations (2-week averages) for individual years were much higher in western sites (58-69ppb) than eastern sites (44-50ppb). Potential O(3) phytotoxicity measured as various exposure indices was very high, reaching SUM00 - 173.5ppmh, SUM60 - 112.7ppmh, W126 - 98.3ppmh, and AOT40 - 75ppmh, representing the highest values reported for mountain areas in North America and Europe.     

Differential response of CO2 uptake parameters of soil- and sand-grown phaseolus vulgaris (L.) plants to absorbed ozone flux

Shoots of a soil- or sand-grown dwarf bean variety were exposed to O(3) concentrations in the range of 500 to 900 ppb for up to 5 h. The measured exchange rates of water vapor and CO(2) during exposures were used to calculate stomatal and mesophyll conductances averaged across all leaves. Changes in conductances were related to exposure duration and absorbed O(3) totals (AOT). Both conductances were more sensitive to AOT in sand-grown plants, which also had more visible injury under comparable AOT values. Measurements of the relationship between CO(2) exchange and internal CO(2) concentration of single leaflets of treated plants also showed greater sensitivity of CO(2)-saturated photosynthesis in sand-grown plants. Diffusional processes were not likely to have been the cause of dissimilar responses because the O(3) absorption rate was lower in sand-grown plants. A difference in the scaveninng capacities in cells is suggested to be the cause of the differences in sensitivity to acute O(3) exposure.     

Measurement of personal and integrated exposure to particulate matter and co-pollutant gases

Personal exposure measurement can serve as an effective tool to understand the effect of exposure to air pollutants. Alternatively, exposure assessment using pollutant concentrations in different microenvironments and accurate time–activity information for the subjects can provide good information regarding human integrated exposure. A panel of 18 healthy students of Indian Institute of Technology (IIT) Kanpur in the age group of 18 to 30 years participated in the personal exposure measurements for particulate matter, CO, NO₂ and VOC during post-monsoon and pre-monsoon seasons. Overall, 432 h person exposure data was collected in this study. The major sources of particulate and gaseous co-pollutants were identified. These directly obtained personal exposure values were then compared to the indirectly estimated integrated exposure values. Personal and integrated exposures gave statistically similar results. Through this study, we have shown that integrated exposure values could closely estimate the personal exposure values for particulate matter that can significantly reduce time and cost involved in personal exposure studies. The lung parameters for all the subjects measured during the pre-monsoon and post-monsoon seasons showed statistically significant reduction during pre-monsoon. This was attributed to the high levels of coarse particles during pre-monsoon.