Development of a Speciated,Hourly, and Gridded Air Pollutants Emission Modeling System—A Case Study on the Precursors of Photochemical Smog in the Seoul Metropolitan Area,Korea

ABSTRACT

A speciated, hourly, and gridded air pollutants emission modeling system (SHEMS) was developed and applied in predicting hourly nitrogen dioxide (NO₂) and ozone (O₃) levels in the Seoul Metropolitan Area (SMA). The primary goal of the SHEMS was to produce a systemized emission inventory for air pollutants including ozone precursors for modeling air quality in urban areas.

The SHEMS is principally composed of three parts: (1) a pre-processor to process emission factors, activity levels, and spatial and temporal information using a geographical information system; (2) an emission model for each source type; and (3) a post-processor to produce report and input data for air quality models through database modeling. The source categories in SHEMS are point, area, mobile, natural, and other sources such as fugitive emissions. The emission database produced by SHEMS contains 22 inventoried compounds: sulfur dioxide, NO₂, carbon monoxide, and 19 speciated volatile organic compounds. To validate SHEMS, the emission data were tested with the Urban Airshed Model to predict NO₂ and O₃ concentrations in the SMA during selected episode days in 1994. The results turned out to be reliable in describing temporal variation and spatial distribution of those pollutants.     

Correlating Emissions with Time and Temperature to Predict Worst-Case Emissions from Open Liquid Area Sources

Abstract

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 °F), the constant emission rate underestimated odor impact significantly (by 73%).     

Sensitivity of Source Apportionment of Urban Particulate Matter to Uncertainty in Motor Vehicle Emissions Profiles

Abstract

A sensitivity analysis was conducted to characterize sources of uncertainty in results of a molecular marker source apportionment model of ambient particulate matter using mobile source emissions profiles obtained as part of the Gasoline/Diesel PM Split Study. A chemical mass balance (CMB) model was used to determine source contributions to samples of fine particulate matter (PM_2.5) collected over 3 weeks at two sites in the Los Angeles area in July 2001. The ambient samples were composited for organic compound analysis by the day of the week to investigate weekly trends in source contributions. The sensitivity analysis specifically examined the impact of the uncertainty in mobile source emissions profiles on the CMB model results. The key parameter impacting model sensitivity was the source profile for gasoline smoker vehicles. High-emitting gasoline smoker vehicles with visible plumes were seen to be a significant source of PM in the area, but use of different measured profiles for smoker vehicles in the model gave very different results for apportionment of gasoline, diesel, and smoker vehicle tailpipe emissions. In addition, the contributions of gasoline and diesel emissions to total ambient PM varied as a function of the site and the day of the week.     

Development of a speciated, hourly, and gridded air pollutants emission modeling system--a case study on the precursors of photochemical smog in the Seoul metropolitan area, Korea

A speciated, hourly, and gridded air pollutants emission modeling system (SHEMS) was developed and applied in predicting hourly nitrogen dioxide (NO2) and ozone (O3) levels in the Seoul Metropolitan Area (SMA). The primary goal of the SHEMS was to produce a systemized emission inventory for air pollutants including ozone precursors for modeling air quality in urban areas. The SHEMS is principally composed of three parts: (1) a pre-processor to process emission factors, activity levels, and spatial and temporal information using a geographical information system; (2) an emission model for each source type; and (3) a post-processor to produce report and input data for air quality models through database modeling. The source categories in SHEMS are point, area, mobile, natural, and other sources such as fugitive emissions. The emission database produced by SHEMS contains 22 inventoried compounds: sulfur dioxide, NO2, carbon monoxide, and 19 speciated volatile organic compounds. To validate SHEMS, the emission data were tested with the Urban Airshed Model to predict NO2 and O3 concentrations in the SMA during selected episode days in 1994. The results turned out to be reliable in describing temporal variation and spatial distribution of those pollutants.     

Comparison and Evaluation of Chemically Speciated Mobile Source PM2.5 Particulate Matter Profiles

ABSTRACT

Mobile sources are significant contributors to ambient PM_{2 5}, accounting for 50% or more of the total observed levels in some locations. One of the important methods for resolving the mobile source contribution is through chemical mass balance (CMB) receptor modeling. CMB requires chemically speciated source profiles with known uncertainty to ensure accurate source contribution estimates. Mobile source PM profiles are available from various sources and are generally in the form of weight fraction by chemical species. The weight fraction format is commonly used, since it is required for input into the CMB receptor model. This paper examines the similarities and differences in mobile source PM_2.5 profiles that contain data for elements, ions, elemental carbon (EC) and organic carbon (OC), and in some cases speciated organics (e.g., polycyclic aromatic hydrocarbons [PAHs]), drawn from four different sources.

Notable characteristics of the mass fraction data include variability (relative contributions of elements and ions) among supposedly similar sources and a wide range of average EC:OC ratios (0.60 ± 0.53 to 1.42 ± 2.99) for light-duty gasoline vehicles (LDGVs), indicating significant EC emissions from LDGVs in some cases. For diesel vehicles, average EC:OC ratios range from 1.09 ± 2.66 to 3.54 ± 3.07. That different populations of the same class of emitters can show considerable variability suggests caution should be exercised when selecting and using profiles in source apportionment studies.     

An Environmental Decision-Making Tool for Evaluating Ground-Level Ozone-Related Health Effects

Abstract

A computer model called the Ozone Risk Assessment Model (ORAM) was developed to evaluate the health effects caused by ground-level ozone (O₃) exposure. ORAM was coupled with the U.S. Environmental Protection Agency’s (EPA) Third-Generation Community Multiscale Air Quality model (Models-3/CMAQ), the state-of-the-art air quality model that predicts O₃ concentration and allows the examination of various scenarios in which emission rates of O₃ precursors (basically, oxides of nitrogen [NO_x] and volatile organic compounds) are varied. The principal analyses in ORAM are exposure model performance evaluation, health-effects calculations (expected number of respiratory hospital admissions), economic valuation, and sensitivity and uncertainty analysis through a Monte Carlo simulation. As a demonstration of the system, ORAM was applied to the eastern Tennessee region, and the entire O₃ season was simulated for a base case (typical emissions) and three different emission scenarios. The results indicated that a synergism occurs when reductions in NO_x emissions from mobile and point sources were applied simultaneously. A 12.9% reduction in asthma hospital admissions is expected when both mobile and point source NO_x emissions are reduced (50 and 70%, respectively) versus a 5.8% reduction caused by mobile source and a 3.5% reduction caused by point sources when these emission sources are reduced individually.     

Which meteorological conditions produce worst-case odors from area sources?

Two competing meteorological factors influence atmospheric concentrations of pollutants from open liquid area sources such as wastewater treatment plant units: temperature and stability. High temperatures in summer produce greater emissions from liquid area sources because of increased compound volatility; however, these emissions tend to disperse more readily because of frequent occurrence of unstable conditions. An opposite scenario occurs in winter, with lesser emissions due to lower temperatures, but also frequently less dispersion, due to stable atmospheric conditions. The primary objective of this modeling study was thus to determine whether higher atmospheric concentrations from open liquid area sources occur more frequently in summer, when emissions are greater but so is dispersion, or in winter, when emissions are lesser but so is dispersion. The study utilized a rectangular clarifier emitting hydrogen sulfide as a sample open liquid area source. Dispersion modeling runs were conducted using ISCST3 and AERMOD, encompassing 5 yr of hourly meteorological data divided by season. Emission rates were varied hourly on the basis of a curve-fit developed from previously collected field data. Model output for each season was used to determine (1) maximum 2-min average concentrations, (2) the number of odor events (2-min average concentrations greater than odor detection thresholds), and (3) areas of impact. On the basis of these 3 types of output, it was found that the worst-case odors were associated with summer, considering impacts of meteorology upon both emissions and dispersion. Not accounting for the impact of meteorology on emissions (using a constant worst-case emission rate) caused concentrations to be overpredicted compared with a variable emission rate case. The highest concentrations occurred during stability classes D, E, and F, as anticipated. A comparison of ISCST3 and AERMOD found that for the area source modeled, ISCST3 predicted higher concentrations and more odor events for all seasons.     

An Efficient Gaussian-Plume Multiple-Source Air Quality Algorithm

The information presented in this paper is directed to air pollution scientists with an interest in applying air quality simulation models. RAM is the three letter designation for this efficient Gaussian-plume multiple-source air quality algorithm. RAM is a method of estimating short-term dispersion using the Gaussian steady-state model. This algorithm can be used for estimating air quality concentrations of relatively stable pollutants for averaging times from an hour to a day in urban areas from point and area sources. The algorithm is applicable for locations with level or gently rolling terrain where a single wind vector for each hour is a good approximation to the flow over the source area considered. Calculations are performed for each hour. Hourly meteorological data required are wind direction, wind speed, stability class, and mixing height. Emission information required of point sources consists of source coordinates, emission rate, physical height, stack gas volume flow and stack gas temperature. Emission information required of area sources consists of south-west corner coordinates, source area, total area emission rate and effective area source height. Computation time is kept to a minimum by the manner in which concentrations from area sources are estimated using a narrow plume hypothesis and using the area source squares as given rather than breaking down all sources to an area of uniform elements. Options are available to the user to allow use of three different types of receptor locations: 1 ) those whose coordinates are input by the user, 2) those whose coordinates are determined by thé model and are downwind óf significant point and area sources where maxima are likely to occur, and 3) those whose coordinates are determined by the model to give good area coverage of a specific portion of the region. Computation time is also decreased by keeping the number of receptors to a minimum.     

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%).     

Preparation of mercury emissions inventory for eastern North America

Point and area inventories of anthropogenic mercury emissions documented by US and Canadian environmental agencies have been aggregated into a single archive for analysis and air pollution modeling work. For 5341 point sources and 1634 aggregated area sources, mercury emissions are apportioned among elemental gaseous [Hg(0)], reactive gaseous[Hg(II)], and particulate [Hg(p)] emissions using speciation factors derived from available monitoring measurements. According to this inventory, 4.82 x 10(5) mol of mercury were emitted in calendar year 1996 in the latitude range 24-51 degrees north, and longitude range 64-91 degrees west, which covers most of North America east of the Mississippi River. Using speciation factors consistent with past emission source studies, we find the relative emission proportions among Hg(0):Hg(II):Hg(p) species are 47:35:18. Maps of the various mercury species' emissions patterns are presented. Gridded emission patterns show local mercury emission extremes associated with individual cement production and municipal incineration facilities, and in contrast to past inventories, population centers do not stand out. Considerable uncertainties are still present in estimating emissions from large point sources, as are methods of apportioning emissions among various mercury species.     

Resolving the interactions between population density and air pollution emissions controls in the San Joaquin Valley,USA

The effectiveness of emissions control programs designed to reduce concentrations of airborne particulate matter with an aerodynamic diameter <2.5 μm (PM_2.5) in California's San Joaquin Valley was studied in the year 2030 under three growth scenarios: low, medium, and high population density. Base-case inventories for each choice of population density were created using a coupled emissions modeling system that simultaneously considered interactions between land use and transportation, area source, and point source emissions. The ambient PM_2.5 response to each combination of population density and emissions control was evaluated using a regional chemical transport model over a 3-week winter stagnation episode. Comparisons between scenarios were based on regional average and population-weighted PM_2.5 concentrations. In the absence of any emissions control program, population-weighted concentrations of PM_2.5 in the future San Joaquin Valley are lowest under growth scenarios that emphasize low population density. A complete ban on wood burning and a 90% reduction in emissions from food cooking operations and diesel engines must occur before medium- to high-density growth scenarios result in lower population-weighted concentrations of PM_2.5. These trends partly reflect the fact that existing downtown urban cores that naturally act as anchor points for new high-density growth in the San Joaquin Valley are located close to major transportation corridors for goods movement. Adding growth buffers around transportation corridors had little impact in the current analysis, since the 8-km resolution of the chemical transport model already provided an artificial buffer around major emissions sources.

Assuming that future emissions controls will greatly reduce or eliminate emissions from residential wood burning, food cooking, and diesel engines, the 2030 growth scenario using “as-planned” (medium) population density achieves the lowest population-weighted average PM_2.5 concentration in the future San Joaquin Valley during a severe winter stagnation event.

Implications: The San Joaquin Valley is one of the most heavily polluted air basins in the United States that are projected to experience strong population growth in the coming decades. The best plan to improve air quality in the region combines medium- or high-density population growth with rigorous emissions controls. In the absences of controls, high-density growth leads to increased population exposure to PM_2.5 compared with low-density growth scenarios (urban sprawl).     

Inhalation Transfer Factors for Air Pollution Health Risk Assessment

ABSTRACT

To facilitate routine health risk assessments, we develop the concept of an inhalation transfer factor (ITF). The ITF is defined as the pollutant mass inhaled by an exposed individual per unit pollutant mass emitted from an air pollution source. A cumulative population inhalation transfer factor (PITF) is also defined to describe the total fraction of an emitted pollutant inhaled by all members of the exposed population. In this paper, ITFs and PITFs are calculated for outdoor releases from area, point, and line sources, indoor releases in single zone and multizone indoor environments, and releases within motor vehicles. Typical PITFs for an urban area from emissions outdoors are ~10^-6–10^-3. PITFs associated with emissions in buildings or in moving vehicles are typically much higher, ~10^-3–10^-1.     

PM10 Dispersion Modeling for Treasure Valley,Idaho

ABSTRACT

The recorded exceedances of the 24-hr PM₁₀ National Ambient Air Quality Standard (NAAQS) in Treasure Valley, Idaho, have been associated with prolonged stagnation periods during the winter. A comprehensive modeling study of PM₁₀ impact in Treasure Valley was performed to support the State Implementation Plan (SIP). The study included base-year and short-term episodic conditions. The ISCST3 (Industrial Source Complex Short Term 3) model, using the base-year meteorology and gridded emissions of mobile sources, point sources, and wood burning as input, generally agreed well with measurements in both temporal patterns and annual averages. The WYNDvalley model was evaluated using monitoring data and was used to simulate the PM₁₀ impact for episodic exceedances during stagnant winter conditions. An emission inventory was prepared for a base year (1995) and then extrapolated to the years 2000, 2005, 2010, and 2015 in order to determine air quality planning requirements. According to the simulations using base-year emissions and meteorology, exceedances are not expected. However, exceedances at some stations could be expected using projected emissions and episodic meteorology. Results from emission control strategies we developed indicate that mobile-source emissions have the most significant impact; reduction of 25% would be needed to eliminate the simulated exceedances in all projected years.     

Air Quality Modeling of Interpollutant Trading for Ozone Precursors in an Urban Area

Abstract

Emission trading is a market‐based approach designed to improve the efficiency and economic viability of emission control programs; emission trading has typically been confined to trades among single pollutants. Interpollutant trading (IPT), as described in this work, allows for trades among emissions of different compounds that affect the same air quality end point, in this work, ambient ozone (O₃) concentrations. Because emissions of different compounds impact air quality end points differently, weighting factors or trading ratios (tons of emissions of nitrogen oxides (NO_x) equivalent to a ton of emissions of volatile organic compounds [VOCs]) must be developed to allow for IPT. In this work, IPT indices based on reductions in O₃ concentrations and based on reductions in population exposures to O₃ were developed and evaluated using a three‐dimensional gridded photochemical model for Austin, TX, a city currently on the cusp of nonattainment with the National Ambient Air Quality Standards for O₃ concentrations averaged over 8 hr. Emissions of VOC and NO_x from area and mobile sources in Austin are larger than emissions from point sources. The analysis indicated that mobile and area sources exhibited similar impacts. Trading ratios based on maximum O₃ concentration or population exposure were similar. In contrast, the trading ratios did exhibit significant (more than a factor of two) day‐to‐day variability. Analysis of the air quality modeling indicated that the daily variability in trading ratios could be attributed to daily variations in both emissions and meteorology.     

Surface Air Pollutant Concentration Frequency Distributions: Implications for Urban Modeling

With the development of ambient air quality standards (AAQS), the need arises to describe the characteristics of regional surface air-pollutant concentration frequency distributions. In the evaluation of land use plans, numerous agencies will be concerned with evaluating the effectiveness of emission zoning and/or control actions. On a regional basis, one means of performing this assessment lies in determining the changes in the pollutant frequency distributions resulting from control actions.

This study presents new data concerning the surface air-pollutant concentration frequency distributions observed for area sources and continuous point sources, and compares these distributions with those of the pertinent meteorological variables describing the transport and diffusion of the pollutant. The observed surface air pollutant frequency distributions are compared to those corresponding to simple modeling concepts from either an urban area source or a continuous point source. For an urban source and a relatively inert pollutant like CO, we found that the observed frequency distribution for CO surface air concentration parallels the approximately log-normal frequency distribution of the reciprocal of the wind speed. We show that the constant relating these two well-correlated frequency distributions can be determined either experimentally or with a numerical simulation model of air pollution. The usefulness of numerical models in air pollution is discussed.     

Dispersion of Traffic and Space Heating Emissions In Urban Settings

A long-term dispersion model is presented for traffic and space heating emissions in urban areas, allowing fast assessment of the spatial-averaged and center-maximum pollutant concentrations.

The assumption of study areas with circular shape and normal emissions density profiles is made for the purpose of streamlining model inputs with the inventory data normally available. In addition, the rather typical assumptions of Gaussian dispersion, narrow plume, flat or gently rolling terrain, homogeneous wind field and nonreactive pollutants are made. Values of σz from Briggs correlation are used with an initial value of 30 to account for building effects.

Meterological data inputs are reduced to six parameters, inventory data inputs to two, while computations are simplified to a degree that use of a digital computer is not required.

The model is well suited to yield separate assessments for individual types of sources and control measures, as well as to reveal sensitivities from parameters such as city size, or emission density levels and distribution patterns. Its predictions are virtually identical to those of the CDM-2 UNAPMAR model for study areas with circular shape and normal emissions density profiles, and as results do not appear overly sensitive to shape and distribution patterns, the model is believed to be valid for most urban areas.     

Use of abatement cost curves in developing environmental bubble policy for managing SPM in Jamshedpur region

This paper evaluates environmental bubble policy using abatement cost curves drawn for different abatement measures in Jamshedpur region. Surveys were conducted to estimate industrial emissions of suspended particulate matter (SPM) from different emitting sources in the region, and the characteristics of the existing and alternative abatement devices for each emitting source. The abatement cost functions were developed and used to rank the abatement devices. An environmental bubble with its limit equal to the existing SPM emissions from all selected companies was developed. The abatement costs for the bubble were estimated from abatement cost curves with alternative and best available technologies. The estimated abatement costs were found to be less than those of the existing measures. It was also found that M/s TISCO alone can account for SPM emissions reductions in the selected group with less cost.     

An environmental decision-making tool for evaluating ground-level ozone-related health effects

A computer model called the Ozone Risk Assessment Model (ORAM) was developed to evaluate the health effects caused by ground-level ozone (O3) exposure. ORAM was coupled with the U.S. Environmental Protection Agency's (EPA) Third-Generation Community Multiscale Air Quality model (Models-3/CMAQ), the state-of-the-art air quality model that predicts O3 concentration and allows the examination of various scenarios in which emission rates of O3 precursors (basically, oxides of nitrogen [NOx] and volatile organic compounds) are varied. The principal analyses in ORAM are exposure model performance evaluation, health-effects calculations (expected number of respiratory hospital admissions), economic valuation, and sensitivity and uncertainty analysis through a Monte Carlo simulation. As a demonstration of the system, ORAM was applied to the eastern Tennessee region, and the entire O3 season was simulated for a base case (typical emissions) and three different emission scenarios. The results indicated that a synergism occurs when reductions in NOx emissions from mobile and point sources were applied simultaneously. A 12.9% reduction in asthma hospital admissions is expected when both mobile and point source NOx emissions are reduced (50 and 70%, respectively) versus a 5.8% reduction caused by mobile source and a 3.5% reduction caused by point sources when these emission sources are reduced individually.     

Sensitivity of source apportionment of urban particulate matter to uncertainty in motor vehicle emissions profiles

A sensitivity analysis was conducted to characterize sources of uncertainty in results of a molecular marker source apportionment model of ambient particulate matter using mobile source emissions profiles obtained as part of the Gasoline/Diesel PM Split Study. A chemical mass balance (CMB) model was used to determine source contributions to samples of fine particulate matter (PM2.5) collected over 3 weeks at two sites in the Los Angeles area in July 2001. The ambient samples were composited for organic compound analysis by the day of the week to investigate weekly trends in source contributions. The sensitivity analysis specifically examined the impact of the uncertainty in mobile source emissions profiles on the CMB model results. The key parameter impacting model sensitivity was the source profile for gasoline smoker vehicles. High-emitting gasoline smoker vehicles with visible plumes were seen to be a significant source of PM in the area, but use of different measured profiles for smoker vehicles in the model gave very different results for apportionment of gasoline, diesel, and smoker vehicle tailpipe emissions. In addition, the contributions of gasoline and diesel emissions to total ambient PM varied as a function of the site and the day of the week.