Consultant Guide/1987

ABSTRACT

This study considers the characteristics of ground-level ozone (O₃) in five Korean cities over a time period of 6-8 years. The focus of this study is daily maximum 1-hr and 8-hr concentrations. For all the study cities in the period examined, the mean and most of the percentiles (5, 10, 25, 50, 75, 90, and 95) for the daily maximum 1-hr and 8hr concentrations showed increasing trends, although not all trends were statistically significant. The daily maximum 1-hr and 8-hr concentrations slowly increased during late winter, and peaks were attained during the summer season (from May to September). All the selected cities exhibited a high degree of correlation between their daily maximum 8-hr and 1-hr concentrations. The daily maximum 8-hr concentrations, which were climatologi-cally equivalent to the Korean 1 hr/100 parts per billion (ppb) standard, were higher than the current 8 hr/60 ppb by a difference of 8-16 ppb. Compared with other cities in Korea, Seoul recorded a substantially higher frequency of days and hours with concentrations above 1 hr/100 ppb, and a higher frequency of days with concentrations above 8 hr/60 ppb and 8 hr/80 ppb. Seoul also recorded a substantially higher frequency of hours with concentrations above 1 hr/100 ppb than days with concentrations above 1 hr/100 ppb, implying that on some days severe exceedances persisted for more than one hour per day. During multiple-day episodes a North Pacific High dominated Korea, which is quite typical in Korea during the summer season.     

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.     

Meteorological effects on the evolution of high ozone episodes in the greater Seoul area

Three high O3 episodes--7 days in 1992 (July 3-July 9), 9 days in 1994 (July 21-July 29), and another 3 days in 1994 (August 22-August 24)--were selected on the basis of morning (7:00 a.m.-10:00 a.m.) average wind direction and speed and daily maximum O3 concentrations in the greater Seoul, Korea, of 1990-1997. To better understand their characteristics and life cycles, surface data from the Seoul Weather Station (SWS) and surface and 850-hPa wind field data covering northeast Asia around the Korean Peninsula were used for the analysis. In the July 1992 episode, westerly winds were most frequent as a result of the influence of a high-pressure system west of the Korean Peninsula behind a trough. In contrast, in the July 1994 episode, easterly winds were most frequent as a result of the effect of a typhoon moving north from the south of Japan. Despite different prevailing wind directions, the peak O3 concentrations for each episode occurred when a sea/land breeze developed in association with weak synoptic forcing. The August 1994 episode, which was selected as being representative of calm conditions, was another typical example in which a well-developed     

Forecasting peak daily ozone levels--I. A regression with time series errors model having a principal component trigger to fit 1991 ozone levels

This research was motivated by the need to warn the population of Milwaukee, WI, on high-ozone days. A statistical model for the peak daily 1-hr ozone level is proposed. A Regression with Time Series Errors (RTSE) model, which includes a principal component (PC) trigger, is the basis for forecasting the peak daily 1-hr ozone level. The RTSE model, with a PC trigger, is first employed to estimate daily peak ozone measured at the University of Wisconsin, Milwaukee-North (UWM-N), during the 1991 ozone season. The RTSE model uses peak daily temperature, morning vector average wind direction, and the PC trigger as predictor variables. The PC trigger was designed to summarize atmospheric circumstances when peak ozone was greater than 100 parts per billion (ppb). It is verified that the RTSE model, with a PC trigger, significantly improves the prediction of peak daily ozone, particularly peak ozone greater than 100 ppb. In comparison with the RTSE model without the PC trigger, the RTSE model with a PC trigger raised the R2 from 0.680 to 0.809. It is suggested that the RTSE model, with the PC trigger, is an adequate statistical model that has the potential for real-time ozone forecasting.     

Evaluation of time-resolved PM2.5 data in urban/suburban areas of New Jersey

Time-resolved data is needed for public notification of unhealthful air quality and to develop an understanding of atmospheric chemistry, including insights important to control strategies. In this research, continuous fine particulate matter (PM2.5) mass concentrations were measured with tapered element oscillating microbalances (TEOMs) across New Jersey from July 1997 to June 1998. Data features indicating the influence of local sources and long-distance transport are examined, as well as differences between 1-hr maxima and 24-hr average concentrations that might be relevant to acute health effects. Continuous mass concentrations were not significantly different from filter-collected gravimetric mass concentrations with 95% confidence intervals during any season. Annual mean PM2.5 concentrations from July 1997 to June 1998 were 17.3, 16.4, 14.1, and 15.3 micrograms/m3 at Newark, Elizabeth, New Brunswick, and Camden, NJ, respectively. Monthly averaged 24- and 1-hr daily maximum PM2.5 concentrations suggest the existence of a high PM2.5 (May-October) and a low PM2.5 (November-April) season. PM2.5 magnitudes and temporal trends were very similar across the state during high PM2.5 events. In fact, the between-site coefficients of determination (R2) for daily PM2.5 measurements were 84-98% for June and July. Additionally, during the most pronounced PM2.5 episode, PM2.5 concentrations closely tracked the daily maximum 1-hr O3 concentrations. These observations suggest the importance of transport and atmospheric chemistry (i.e., secondary formation) to PM2.5 episodes in New Jersey. The influence of local sources was observed in diurnal concentration profiles and annual average between-site differences. Urban wintertime data illustrate that high 1-hr maximum PM2.5 concentrations can occur on low 24-hr PM2.5 days.     

Modeling an air pollution episode in northwestern United States: Identifying the effect of nitrogen oxide and volatile organic compound emission changes on air pollutants formation using direct sensitivity analysis

Air quality impacts of volatile organic compound (VOC) and nitrogen oxide (NO_x) emissions from major sources over the northwestern United States are simulated. The comprehensive nested modeling system comprises three models: Community Multiscale Air Quality (CMAQ), Weather Research and Forecasting (WRF), and Sparse Matrix Operator Kernel Emissions (SMOKE). In addition, the decoupled direct method in three dimensions (DDM-3D) is used to determine the sensitivities of pollutant concentrations to changes in precursor emissions during a severe smog episode in July of 2006. The average simulated 8-hr daily maximum O₃ concentration is 48.9 ppb, with 1-hr O₃ maxima up to 106 ppb (40 km southeast of Seattle). The average simulated PM_2.5 (particulate matter with an aerodynamic diameter <2.5 μm) concentration at the measurement sites is 9.06 μg m^?3, which is in good agreement with the observed concentration (8.06 μg m^?3). In urban areas (i.e., Seattle, Vancouver, etc.), the model predicts that, on average, a reduction of NO_x emissions is simulated to lead to an increase in average 8-hr daily maximum O₃ concentrations, and will be most prominent in Seattle (where the greatest sensitivity is??0.2 ppb per % change of mobile sources). On the other hand, decreasing NO_x emissions is simulated to decrease the 8-hr maximum O₃ concentrations in remote and forested areas. Decreased NO_x emissions are simulated to slightly increase PM_2.5 in major urban areas. In urban areas, a decrease in VOC emissions will result in a decrease of 8-hr maximum O₃ concentrations. The impact of decreased VOC emissions from biogenic, mobile, nonroad, and area sources on average 8-hr daily maximum O₃ concentrations is up to 0.05 ppb decrease per % of emission change, each. Decreased emissions of VOCs decrease average PM_2.5 concentrations in the entire modeling domain. In major cities, PM_2.5 concentrations are more sensitive to emissions of VOCs from biogenic sources than other sources of VOCs. These results can be used to interpret the effectiveness of VOC or NO_x controls over pollutant concentrations, especially for localities that may exceed National Ambient Air Quality Standards (NAAQS).

Implications: The effect of NO_x and VOC controls on ozone and PM_2.5 concentrations in the northwestern United States is examined using the decoupled direct method in three dimensions (DDM-3D) in a state-of-the-art three-dimensional chemical transport model (CMAQ). NO_x controls are predicted to increase PM_2.5 and ozone in major urban areas and decrease ozone in more remote and forested areas. VOC reductions are helpful in reducing ozone and PM_2.5 concentrations in urban areas. Biogenic VOC sources have the largest impact on O₃ and PM_2.5 concentrations.     

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.     

Urban and rural ozone concentrations in Alberta,Canada

Ozone concentrations in Alberta cities typically exhibit a maximum in May (up to 35 ppb) and a minimum in November (as low as 4 ppb). This behaviour is similar to that of rural Alberta O₃ concentrations. Annual O₃ concentrations at six urban monitoring stations vary from 11 ppb to 22 ppb and are about one-half the values at rural stations. In winter, urban O₃ concentrations are always smaller than rural concentrations and the cities act as sinks for O₃. Although urban stations do not exceed Canada's maximum acceptable levels of daily (25 ppb) and annual (15 ppb) O₃ concentrations as often as rural stations, the frequency is still quite large. Canada's hourly maximum desirable level (50 ppb) is exceeded 11 times more often at the remote (rural) station than at the downtown (urban) stations.     

An enhanced ozone forecasting model using air mass trajectory analysis

An enhanced ozone forecasting model using nonlinear regression and an air mass trajectory parameter has been developed and field tested. The model performed significantly better in predicting daily maximum 1-h ozone concentrations during a five-year model calibration period (1993–1997) than did a previously reported regression model. This was particularly true on the 28 “high ozone” days ([O₃]>120 ppb) during the period, for which the mean absolute error (MAE) improved from 21.7 to 12.1 ppb. On the 77 days meteorologically conducive to high ozone, the MAE improved from 12.2 to 9.1 ppb, and for all 580 calibration days the MAE improved from 9.5 to 8.35 ppb. The model was field-tested during the 1998 ozone season, and performed about as expected. Using actual meteorological data as input for the ozone predictions, the MAE for the season was 11.0 ppb. For the daily ozone forecasts, which used meteorological forecast data as input, the MAE was 13.4 ppb. The high ozone days were all anticipated by the ozone forecasters when the model was used for next day forecasts.     

A comparison of air particulate matter and associated polycyclic aromatic hydrocarbons in some tropical and temperate urban environments

A 12 month study of urban concentrations of total suspended particulates (TSP) and 20 polycyclic aromatic hydrocarbons (PAH) was carried out in Seoul (South Korea), Hong Kong, Bangkok (Thailand), Jakarta (Indonesia) and Melbourne (Australia). Concentrations of particulate matter in the atmosphere varied widely between the cities over the course of the study, ranging from a low of 24.1 μg m⁻³ in Melbourne during the winter to a high of 376.2 μg m⁻³ in Jakarta during the dry season. Seasonal variations in both TSP and PAH were observed in the tropical cities in the study with higher concentrations during the dry season and lower concentrations during the wet season. TSP and PAH concentrations are correlated with each other in these cities, suggesting that they have related sources and sinks for these cities. In the temperate cities of Melbourne and Seoul, PAH concentrations were higher during the cold winter season and lower during the warm summer. However, TSP was quite variable over the years in these latter cities and no clear seasonal trend was observed. A number of factors have been investigated which could be contributing to seasonal variations in pollutant levels. In the temperate climates, increased emissions due to the use of fossil fuels for heating in the winter is evident. However, an interrogation of the database with respect to the other factors such as (1) increased photolytic degradation during the summer, (2) transport of pollutants from other sources, (3) removal of PAH via wet deposition and in-cloud scavenging mechanisms and (4) volatilisation of lower molecular weight species during periods of high temperature indicates the importance of multiple processes. Even though there are clearly much lower levels of both particulates and PAH in the wet season of the tropical climates, no statistically significant correlations have been observed between rainfall levels and pollutant concentrations.     

Assessment of a regulatory model's performance relative to large spatial heterogeneity in observed ozone in Houston, Texas

In Houston, some of the highest measured 8-hr ozone (O3) peaks are characterized by sudden increases in observed concentrations of at least 40 ppb in 1 hr or 60 ppb in 2 hr. Measurements show that these large hourly changes appear at only a few monitors and span a narrow geographic area, suggesting a spatially heterogeneous field of O3 concentrations. This study assessed whether a regulatory air quality model (AQM) can simulate this observed behavior. The AQM did not reproduce the magnitude or location of some of the highest observed hourly O3 changes, and it also failed to capture the limited spatial extent. On days with measured large hourly changes in O3 concentrations, the AQM predicted high O3 over large regions of Houston, resulting in overpredictions at several monitors. This analysis shows that the model can make high O3, but on these days the predicted spatial field suggests that the model had a different cause. Some observed large hourly changes in O3 concentrations have been linked to random releases of industrial volatile organic compounds (VOCs). In the AQM emission inventory, there are several emission events when an industrial point source increases VOC emissions in excess of 10,000 mol/hr. One instance increased predicted downwind O3 concentrations up to 25 ppb. These results show that the modeling system is responsive to a large VOC release, but the timing and location of the release, and meteorological conditions, are critical requirements. Attainment of the O3 standard requires the use of observational data and AQM predictions. If the large observed hourly changes are indicative of a separate cause of high O3, then the model may not include that cause, which might result in regulators enacting control strategies that could be ineffective.     

Evaluation of Time-Resolved PM2.5 Data in Urban/Suburban Areas of New Jersey

ABSTRACT

Time-resolved data is needed for public notification of unhealthful air quality and to develop an understanding of atmospheric chemistry, including insights important to control strategies. In this research, continuous fine particulate matter (PM_2.5) mass concentrations were measured with tapered element oscillating microbalances (TEOMs) across New Jersey from July 1997 to June 1998. Data features indicating the influence of local sources and long-distance transport are examined, as well as differences between 1-hr maxima and 24-hr average concentrations that might be relevant to acute health effects. Continuous mass concentrations were not significantly different from filter-collected gravimetric mass concentrations with 95% confidence intervals during any season. Annual mean PM_2.5 concentrations from July 1997 to June 1998 were 17.3, 16.4, 14.1, and 15.3 μg/m³ at Newark, Elizabeth, New Brunswick, and Camden, NJ, respectively. Monthly averaged 24- and 1-hr daily maximum PM_2.5 concentrations suggest the existence of a high PM_2.5 (May-October) and a low PM_2.5 (November-April) season.

PM_2.5 magnitudes and temporal trends were very similar across the state during high PM_2.5 events. In fact, the between-site coefficients of determination (R²) for daily PM_2.5 measurements were 84-98% for June and July. Additionally, during the most pronounced PM_2.5 episode, PM_2.5 concentrations closely tracked the daily maximum 1-hr O₃ concentrations. These observations suggest the importance of transport and atmospheric chemistry (i.e., secondary formation) to PM_2.5 episodes in New Jersey. The influence of local sources was observed in diurnal concentration profiles and annual average between-site differences. Urban wintertime data illustrate that high 1-hr maximum PM_2.5 concentrations can occur on low 24-hr PM_2.5 days.     

Source apportionment of emissions from light-duty gasoline vehicles and other sources in the United States for ozone and particulate matter

Federal Tier 3 motor vehicle emission and fuel sulfur standards have been promulgated in the United States to help attain air quality standards for ozone and PM_2.5 (particulate matter with an aerodynamic diameter <2.5 μm). The authors modeled a standard similar to Tier 3 (a hypothetical nationwide implementation of the California Low Emission Vehicle [LEV] III standards) and prior Tier 2 standards for on-road gasoline-fueled light-duty vehicles (gLDVs) to assess incremental air quality benefits in the United States (U.S.) and the relative contributions of gLDVs and other major source categories to ozone and PM_2.5 in 2030. Strengthening Tier 2 to a Tier 3-like (LEV III) standard reduces the summertime monthly mean of daily maximum 8-hr average (MDA8) ozone in the eastern U.S. by up to 1.5 ppb (or 2%) and the maximum MDA8 ozone by up to 3.4 ppb (or 3%). Reducing gasoline sulfur content from 30 to 10 ppm is responsible for up to 0.3 ppb of the improvement in the monthly mean ozone and up to 0.8 ppb of the improvement in maximum ozone. Across four major urban areas—Atlanta, Detroit, Philadelphia, and St. Louis—gLDV contributions range from 5% to 9% and 3% to 6% of the summertime mean MDA8 ozone under Tier 2 and Tier 3, respectively, and from 7% to 11% and 3% to 7% of the maximum MDA8 ozone under Tier 2 and Tier 3, respectively. Monthly mean 24-hr PM_2.5 decreases by up to 0.5 μg/m³ (or 3%) in the eastern U.S. from Tier 2 to Tier 3, with about 0.1 μg/m³ of the reduction due to the lower gasoline sulfur content. At the four urban areas under the Tier 3 program, gLDV emissions contribute 3.4–5.0% and 1.7–2.4% of the winter and summer mean 24-hr PM_2.5, respectively, and 3.8–4.6% and 1.5–2.0% of the mean 24-hr PM_2.5 on days with elevated PM_2.5 in winter and summer, respectively.

Implications: Following U.S. Tier 3 emissions and fuel sulfur standards for gasoline-fueled passenger cars and light trucks, these vehicles are expected to contribute less than 6% of the summertime mean daily maximum 8-hr ozone and less than 7% and 4% of the winter and summer mean 24-hr PM_2.5 in the eastern U.S. in 2030. On days with elevated ozone or PM_2.5 at four major urban areas, these vehicles contribute less than 7% of ozone and less than 5% of PM_2.5, with sources outside North America and U.S. area source emissions constituting some of the main contributors to ozone and PM_2.5, respectively.     

Weekday/weekend ozone differences: what can we learn from them?

A national analysis of weekday/weekend ozone (O3) differences demonstrates significant variation across the country. Weekend 1-hr or 8-hr maximum O3 varies from 15% lower than weekday levels to 30% higher. The weekend O3 increases are primarily found in and around large coastal cities in California and large cities in the Midwest and Northeast Corridor. Both the average and the 95th percentile of the daily 1-hr and 8-hr maxima exhibit the same general pattern. Many sites that have elevated O3 also have higher O3 on weekends even though traffic and O3 precursor levels are substantially reduced on weekends. Detailed studies of this phenomenon indicate that the primary cause of the higher O3 on weekends is the reduction in oxides of nitrogen (NOx) emissions on weekends in a volatile organic compound (VOC)-limited chemical regime. In contrast, the lower O3 on weekends in other locations is probably a result of NOx reductions in a NOx-limited regime. The NOx reduction explanation is supported by a wide range of ambient analyses and several photochemical modeling studies. Changes in the timing and location of emissions and meteorological factors play smaller roles in weekend O3 behavior. Weekday/weekend temperature differences do not explain the weekend effect but may modify it.     

Characterization of Ozone During Consecutive Drought and Wet Years at a Rural West Virginia Site

Ozone concentrations at a rural-remote site in a forested region of north-central West Virginia were monitored during 1988 and 1989, a drought and wet year, respectively. During 1988, the absolute maximum average concentration for a single hour was 156 ppb, while it was only 107 ppb in 1989. Overall, the frequency of high concentrations was greater during 1988; the 120 ppb National Ambient Air Quality Standard was exceeded 17 times. The 7-h period encompassing the highest growing season concentrations for this site over the 2-yr period is 1100- 1759 h EST, rather than the period 0900-1559 h originally used by the National Crop Loss Assessment Network. The 7-h growing season means (0900-1559 h) of 52.6 ppb and 47.1 ppb for 1988 and 1989, respectively, compare well to those reported for the Piedmont/Mountain/Ridge-Valley area, but are higher than those for other surrounding areas. The diurnal ozone patterns, as well as the distribution of concentration ranges and timing of seasonal maxima, suggest that long-range transport of ozone and its precursors probably is an important factor at this site, given its remote and rural character.     

Simulating urban-scale air pollutants and their predicting capabilities over the Seoul metropolitan area

Urban-scale air pollutants for sulfur dioxide, nitrogen dioxide, particulate matter with aerodynamic diameter > or = 10 microm, and ozone (O3) were simulated over the Seoul metropolitan area, Korea, during the period of July 2-11, 2002, and their predicting capabilities were discussed. The Air Pollution Model (TAPM) and the highly disaggregated anthropogenic and the biogenic gridded emissions (1 km x 1 km) recently prepared by the Korean Ministry of Environment were applied. Wind fields with observational nudging in the prognostic meteorological model TAPM are optionally adopted to comparatively examine the meteorological impact on the prediction capabilities of urban-scale air pollutants. The result shows that the simulated concentrations of secondary air pollutant largely agree with observed levels with an index of agreement (IOA) of >0.6, whereas IOAs of approximately 0.4 are found for most primary pollutants in the major cities, reflecting the quality of emission data in the urban area. The observationally nudged wind fields with higher IOAs have little effect on the prediction for both primary and secondary air pollutants, implying that the detailed wind field does not consistently improve the urban air pollution model performance if emissions are not well specified. However, the robust highest concentrations are better described toward observations by imposing observational nudging, suggesting the importance of wind fields for the predictions of extreme concentrations such as robust highest concentrations, maximum levels, and >90th percentiles of concentrations for both primary and secondary urban-scale air pollutants.     

The geographic distribution and economic value of climate change-related ozone health impacts in the United States in 2030

In this United States-focused analysis we use outputs from two general circulation models (GCMs) driven by different greenhouse gas forcing scenarios as inputs to regional climate and chemical transport models to investigate potential changes in near-term U.S. air quality due to climate change. We conduct multiyear simulations to account for interannual variability and characterize the near-term influence of a changing climate on tropospheric ozone-related health impacts near the year 2030, which is a policy-relevant time frame that is subject to fewer uncertainties than other approaches employed in the literature. We adopt a 2030 emissions inventory that accounts for fully implementing anthropogenic emissions controls required by federal, state, and/or local policies, which is projected to strongly influence future ozone levels. We quantify a comprehensive suite of ozone-related mortality and morbidity impacts including emergency department visits, hospital admissions, acute respiratory symptoms, and lost school days, and estimate the economic value of these impacts. Both GCMs project average daily maximum temperature to increase by 1–4°C and 1–5 ppb increases in daily 8-hr maximum ozone at 2030, though each climate scenario produces ozone levels that vary greatly over space and time. We estimate tens to thousands of additional ozone-related premature deaths and illnesses per year for these two scenarios and calculate an economic burden of these health outcomes of hundreds of millions to tens of billions of U.S. dollars (2010$).

Implications:?Near-term changes to the climate have the potential to greatly affect ground-level ozone. Using a 2030 emission inventory with regional climate fields downscaled from two general circulation models, we project mean temperature increases of 1 to 4°C and climate-driven mean daily 8-hr maximum ozone increases of 1–5 ppb, though each climate scenario produces ozone levels that vary significantly over space and time. These increased ozone levels are estimated to result in tens to thousands of ozone-related premature deaths and illnesses per year and an economic burden of hundreds of millions to tens of billions of U.S. dollars (2010$).     

The New England Air Quality Forecasting Pilot Program: development of an evaluation protocol and performance benchmark

The National Oceanic and Atmospheric Administration recently sponsored the New England Forecasting Pilot Program to serve as a "test bed" for chemical forecasting by providing all of the elements of a National Air Quality Forecasting System, including the development and implementation of an evaluation protocol. This Pilot Program enlisted three regional-scale air quality models, serving as prototypes, to forecast ozone (O3) concentrations across the northeastern United States during the summer of 2002. A suite of statistical metrics was identified as part of the protocol that facilitated evaluation of both discrete forecasts (observed versus modeled concentrations) and categorical forecasts (observed versus modeled exceedances/nonexceedances) for both the maximum 1-hr (125 ppb) and 8-hr (85 ppb) forecasts produced by each of the models. Implementation of the evaluation protocol took place during a 25-day period (August 5-29), utilizing hourly O3 concentration data obtained from over 450 monitors from the U.S. Environment Protection Agency's Air Quality System network.     

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.