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Abstract
A detailed sensitivity analysis was conducted to help to quantify the impacts of various emission control options in terms of potential visibility improvements at class I national parks and wilderness areas in the southeastern United States. Particulate matter (PM) levels were estimated using the Community Multiscale Air Quality (CMAQ) model, and light extinctions were calculated using the modeled PM concentrations. First, likely changes in visibility at class I areas were estimated for 2018. Then, using emission projections for 2018 as a starting point, the sensitivity of light extinction was evaluated by reducing emissions from various source categories by 30%. Source categories to be analyzed were determined using a tiered approach: any category that showed significant impact in one tier was broken into subcategories for further analysis in the next tier. In the first tier, sulfur dioxide (SO2), nitrogen oxides, ammonia, volatile organic compound, and primary carbon emissions were reduced uniformly over the entire domain. During summer, when most class I areas experience their worst visibility, reduction of SO2 emissions was the most effective control strategy. In the second tier, SO2 sources were separated as ground level and elevated. The elevated sources in 10 southeastern states were differentiated from those in the rest of the domain and broken into three subcategories: coal-fired power plant (CPP), other power plant, and other than power plant [i.e., non–electric generating unit (non EGU)]. The SO2 emissions from the CPP subcategory had the largest impact on visibility at class I areas, followed by the non-EGU subcategory. In the third tier, emissions from these two subcategories were further broken down by state. Most class I areas were affected by the emissions from several states, indicating the regional nature of the haze problem. Here, the visibility responses to all of the aforementioned emission reductions are quantified and deviations from general trends are identified.
Abstract
A detailed sensitivity analysis was conducted to help to quantify the impacts of various emission control options in terms of potential visibility improvements at class I national parks and wilderness areas in the southeastern United States. Particulate matter (PM) levels were estimated using the Community Multiscale Air Quality (CMAQ) model, and light extinctions were calculated using the modeled PM concentrations. First, likely changes in visibility at class I areas were estimated for 2018. Then, using emission projections for 2018 as a starting point, the sensitivity of light extinction was evaluated by reducing emissions from various source categories by 30%. Source categories to be analyzed were determined using a tiered approach: any category that showed significant impact in one tier was broken into subcategories for further analysis in the next tier. In the first tier, sulfur dioxide (SO2), nitrogen oxides, ammonia, volatile organic compound, and primary carbon emissions were reduced uniformly over the entire domain. During summer, when most class I areas experience their worst visibility, reduction of SO2 emissions was the most effective control strategy. In the second tier, SO2 sources were separated as ground level and elevated. The elevated sources in 10 southeastern states were differentiated from those in the rest of the domain and broken into three subcategories: coal-fired power plant (CPP), other power plant, and other than power plant [i.e., non–electric generating unit (non EGU)]. The SO2 emissions from the CPP subcategory had the largest impact on visibility at class I areas, followed by the non-EGU subcategory. In the third tier, emissions from these two subcategories were further broken down by state. Most class I areas were affected by the emissions from several states, indicating the regional nature of the haze problem. Here, the visibility responses to all of the aforementioned emission reductions are quantified and deviations from general trends are identified.
Abstract
Into the Community Multiscale Air Quality modeling system (CMAQ) that is widely used for simulating the transport and fate of air pollutants, a new module was inserted that accounts for the partitioning of semivolatile organic compounds—in particular, polycyclic organic hydrocarbons (PAHs)—between the gaseous and the particulate phases. This PAH version of CMAQ can at this time be applied to substances that are predominantly associated with particles and can be assumed to be inert, as is the case for benzo(a)pyrene [B(a)P]. The model was set up for Europe on a grid with 54-km cell width with a nest of 18-km gridcell width located around the North Sea to simulate ambient air concentrations and depositions of B(a)P in January, April, July, and October 2000. To evaluate the quality of the simulation results, daily and monthly mean concentrations were compared with measurements from six monitoring stations. The typical ratio of modeled to measured values is circa 4 (median), which—with respect to both measurement and simulation uncertainties and problems involved when comparing measurements with simulations—proved that the PAH version of CMAQ is suitable to simulate the fate and transport of B(a)P over Europe and can serve as a starting point for models for other PAHs that additionally consider degradation.
Abstract
Into the Community Multiscale Air Quality modeling system (CMAQ) that is widely used for simulating the transport and fate of air pollutants, a new module was inserted that accounts for the partitioning of semivolatile organic compounds—in particular, polycyclic organic hydrocarbons (PAHs)—between the gaseous and the particulate phases. This PAH version of CMAQ can at this time be applied to substances that are predominantly associated with particles and can be assumed to be inert, as is the case for benzo(a)pyrene [B(a)P]. The model was set up for Europe on a grid with 54-km cell width with a nest of 18-km gridcell width located around the North Sea to simulate ambient air concentrations and depositions of B(a)P in January, April, July, and October 2000. To evaluate the quality of the simulation results, daily and monthly mean concentrations were compared with measurements from six monitoring stations. The typical ratio of modeled to measured values is circa 4 (median), which—with respect to both measurement and simulation uncertainties and problems involved when comparing measurements with simulations—proved that the PAH version of CMAQ is suitable to simulate the fate and transport of B(a)P over Europe and can serve as a starting point for models for other PAHs that additionally consider degradation.
Abstract
This paper presents a review of recent natural surface mercury exchange research in the context of a new modeling framework. The literature indicates that the mercury biogeochemical flux is more dynamic than the current models predict, with interacting multimedia storage and processes. Although several natural mercury emissions models have been created and incorporated into air quality models (AQMs), none are coupled with air quality models on a mass balance basis, and all lack the capacity to explain processes that involve the transport of mercury across atmosphere–surface media concentration gradients. Existing natural mercury emission models treat the surface as both an infinite source and infinite sink for emissions and deposition, respectively, and estimate emissions through the following three pathways: soil, vegetation, and surface waters. The use of these three transport pathways, but with compartmentalized surface storage in a surface–vegetation–atmosphere transport (SVAT) resistance model, is suggested. Surface water fluxes will be modeled using a two-film diffusion model coupled to a surface water photochemical model. This updated framework will allow both the parameterization of the transport of mercury across atmosphere–surface media concentration gradients and the accumulation/depletion of mercury in the surface media. However, several key parameters need further experimental verification before the proposed modeling framework can be implemented in an AQM. These include soil organic mercury interactions, bioavailability, cuticular transport of mercury, atmospheric surface compensation points for different vegetation species, and enhanced soil diffusion resulting from pressure perturbations.
Abstract
This paper presents a review of recent natural surface mercury exchange research in the context of a new modeling framework. The literature indicates that the mercury biogeochemical flux is more dynamic than the current models predict, with interacting multimedia storage and processes. Although several natural mercury emissions models have been created and incorporated into air quality models (AQMs), none are coupled with air quality models on a mass balance basis, and all lack the capacity to explain processes that involve the transport of mercury across atmosphere–surface media concentration gradients. Existing natural mercury emission models treat the surface as both an infinite source and infinite sink for emissions and deposition, respectively, and estimate emissions through the following three pathways: soil, vegetation, and surface waters. The use of these three transport pathways, but with compartmentalized surface storage in a surface–vegetation–atmosphere transport (SVAT) resistance model, is suggested. Surface water fluxes will be modeled using a two-film diffusion model coupled to a surface water photochemical model. This updated framework will allow both the parameterization of the transport of mercury across atmosphere–surface media concentration gradients and the accumulation/depletion of mercury in the surface media. However, several key parameters need further experimental verification before the proposed modeling framework can be implemented in an AQM. These include soil organic mercury interactions, bioavailability, cuticular transport of mercury, atmospheric surface compensation points for different vegetation species, and enhanced soil diffusion resulting from pressure perturbations.
Abstract
The uncertainties in simulations of annually averaged concentrations of two air toxics (benzene and 1,3-butadiene) are estimated for two widely used U.S. air quality models, the Industrial Source Complex Short-Term, version 3, (ISCST3) model and the American Meteorological Society–Environmental Protection Agency Model (AERMOD). The effects of uncertainties in emissions input, meteorological input, and dispersion model parameters are investigated using Monte Carlo probabilistic uncertainty methods, which involve simultaneous random and independent perturbations of all inputs. The focus is on a 15 km × 15 km domain in the Houston, Texas, ship channel area. Concentrations are calculated at hypothetical receptors located at the centroids of population census tracts. The model outputs that are analyzed are the maximum annually averaged maximum concentration at any single census tract or monitor as well as the annually averaged concentration averaged over the census tracts. The input emissions uncertainties are estimated to be about a factor of 3 (i.e., covering the 95% range) for each of several major categories. The uncertainties in meteorological inputs (such as wind speed) and dispersion model parameters (such as the vertical dispersion coefficient σz ) also are estimated. The results show that the 95% range in predicted annually averaged concentrations is about a factor of 2–3 for the air toxics, with little variation by model. The input variables whose variations have the strongest effect on the predicted concentrations are on-road mobile sources and some industrial sources (dependent on chemical), as well as wind speed, surface roughness, and σz . In most scenarios, the uncertainties of the emissions input group contribute more to the total uncertainty than do the uncertainties of the meteorological/dispersion input group.
Abstract
The uncertainties in simulations of annually averaged concentrations of two air toxics (benzene and 1,3-butadiene) are estimated for two widely used U.S. air quality models, the Industrial Source Complex Short-Term, version 3, (ISCST3) model and the American Meteorological Society–Environmental Protection Agency Model (AERMOD). The effects of uncertainties in emissions input, meteorological input, and dispersion model parameters are investigated using Monte Carlo probabilistic uncertainty methods, which involve simultaneous random and independent perturbations of all inputs. The focus is on a 15 km × 15 km domain in the Houston, Texas, ship channel area. Concentrations are calculated at hypothetical receptors located at the centroids of population census tracts. The model outputs that are analyzed are the maximum annually averaged maximum concentration at any single census tract or monitor as well as the annually averaged concentration averaged over the census tracts. The input emissions uncertainties are estimated to be about a factor of 3 (i.e., covering the 95% range) for each of several major categories. The uncertainties in meteorological inputs (such as wind speed) and dispersion model parameters (such as the vertical dispersion coefficient σz ) also are estimated. The results show that the 95% range in predicted annually averaged concentrations is about a factor of 2–3 for the air toxics, with little variation by model. The input variables whose variations have the strongest effect on the predicted concentrations are on-road mobile sources and some industrial sources (dependent on chemical), as well as wind speed, surface roughness, and σz . In most scenarios, the uncertainties of the emissions input group contribute more to the total uncertainty than do the uncertainties of the meteorological/dispersion input group.
Abstract
A prototype online photolysis module has been developed for the Community Multiscale Air Quality (CMAQ) modeling system. The module calculates actinic fluxes and photolysis rates (j values) at every vertical level in each of seven wavelength intervals from 291 to 850 nm, as well as the total surface irradiance and aerosol optical depth within each interval. The module incorporates updated opacity at each time step, based on changes in local ozone, nitrogen dioxide, and particle concentrations. The module is computationally efficient and requires less than 5% more central processing unit time than using the existing CMAQ “lookup” table method for calculating j values. The main focus of the work presented here is to describe the new online module as well as to highlight the differences between the effective cross sections from the lookup-table method currently being used and the updated effective cross sections from the new online approach. Comparisons of the vertical profiles for the photolysis rates for nitrogen dioxide (NO2) and ozone (O3) from the new online module with those using the effective cross sections from a standard CMAQ simulation show increases in the rates of both NO2 and O3 photolysis.
Abstract
A prototype online photolysis module has been developed for the Community Multiscale Air Quality (CMAQ) modeling system. The module calculates actinic fluxes and photolysis rates (j values) at every vertical level in each of seven wavelength intervals from 291 to 850 nm, as well as the total surface irradiance and aerosol optical depth within each interval. The module incorporates updated opacity at each time step, based on changes in local ozone, nitrogen dioxide, and particle concentrations. The module is computationally efficient and requires less than 5% more central processing unit time than using the existing CMAQ “lookup” table method for calculating j values. The main focus of the work presented here is to describe the new online module as well as to highlight the differences between the effective cross sections from the lookup-table method currently being used and the updated effective cross sections from the new online approach. Comparisons of the vertical profiles for the photolysis rates for nitrogen dioxide (NO2) and ozone (O3) from the new online module with those using the effective cross sections from a standard CMAQ simulation show increases in the rates of both NO2 and O3 photolysis.
Abstract
During the past 20 years, organized experimental campaigns as well as continuous development and implementation of air-pollution modeling have led to significant gains in the understanding of the paths and scales of pollutant transport and transformation in the greater Mediterranean region (GMR). The work presented in this paper has two major objectives: 1) to summarize the existing knowledge on the transport paths of particulate matter (PM) in the GMR and 2) to illustrate some new findings related to the transport and transformation properties of PM in the GMR. Findings from previous studies indicate that anthropogenically produced air pollutants from European sources can be transported over long distances, reaching Africa, the Atlantic Ocean, and North America. The PM of natural origin, like Saharan dust, can be transported toward the Atlantic Ocean and North America mostly during the warm period of the year. Recent model simulations and studies in the area indicate that specific long-range transport patterns of aerosols, such as the transport from Asia and the Indian Ocean, central Africa, or America, have negligible or at best limited contribution to air-quality degradation in the GMR when compared with the other sources. Also, new findings from this work suggest that the imposed European Union limits on PM cannot be applicable for southern Europe unless the origin (natural or anthropogenic) of the PM is taken into account. The impacts of high PM levels in the GMR are not limited only to air quality, but also include serious implications for the water budget and the regional climate. These are issues that require extensive investigation because the processes involved are complex, and further model development is needed to include the relevant physicochemical processes properly.
Abstract
During the past 20 years, organized experimental campaigns as well as continuous development and implementation of air-pollution modeling have led to significant gains in the understanding of the paths and scales of pollutant transport and transformation in the greater Mediterranean region (GMR). The work presented in this paper has two major objectives: 1) to summarize the existing knowledge on the transport paths of particulate matter (PM) in the GMR and 2) to illustrate some new findings related to the transport and transformation properties of PM in the GMR. Findings from previous studies indicate that anthropogenically produced air pollutants from European sources can be transported over long distances, reaching Africa, the Atlantic Ocean, and North America. The PM of natural origin, like Saharan dust, can be transported toward the Atlantic Ocean and North America mostly during the warm period of the year. Recent model simulations and studies in the area indicate that specific long-range transport patterns of aerosols, such as the transport from Asia and the Indian Ocean, central Africa, or America, have negligible or at best limited contribution to air-quality degradation in the GMR when compared with the other sources. Also, new findings from this work suggest that the imposed European Union limits on PM cannot be applicable for southern Europe unless the origin (natural or anthropogenic) of the PM is taken into account. The impacts of high PM levels in the GMR are not limited only to air quality, but also include serious implications for the water budget and the regional climate. These are issues that require extensive investigation because the processes involved are complex, and further model development is needed to include the relevant physicochemical processes properly.
Abstract
This study investigates the potential utility of the application of a photochemical modeling system in providing simultaneous forecasts of ozone (O3) and fine particulate matter (PM2.5) over New York State. To this end, daily simulations from the Community Multiscale Air Quality (CMAQ) model for three extended time periods during 2004 and 2005 have been performed, and predictions were compared with observations of ozone and total and speciated PM2.5. Model performance for 8-h daily maximum O3 was found to be similar to other forecasting systems and to be better than that for the 24-h-averaged total PM2.5. Both pollutants exhibited no seasonal differences in model performance. CMAQ simulations successfully captured the urban–rural and seasonal differences evident in observed total and speciated PM2.5 concentrations. However, total PM2.5 mass was strongly overestimated in the New York City metropolitan area, and further analysis of speciated observations and model predictions showed that most of this overprediction stems from organic aerosols and crustal material. An analysis of hourly speciated data measured in Bronx County, New York, suggests that a combination of uncertainties in vertical mixing, magnitude, and temporal allocation of emissions and deposition processes are all possible contributors to this overprediction in the complex urban area. Categorical evaluation of CMAQ simulations in terms of exceeding two different threshold levels of the air quality index (AQI) again indicates better performance for ozone than PM2.5 and better performance for lower exceedance thresholds. In most regions of New York State, the routine air quality forecasts based on observed concentrations and expert judgment show slightly better agreement with the observed distributions of AQI categories than do CMAQ simulations. However, CMAQ shows skill similar to these routine forecasts in terms of capturing the AQI tendency, that is, in predicting changes in air quality conditions. Overall, the results presented in this study reveal that additional research and development is needed to improve CMAQ simulations of PM2.5 concentrations over New York State, especially for the New York City metropolitan area. On the other hand, because CMAQ simulations capture urban–rural concentration gradients and day-to-day fluctuations in observed air quality despite systematic overpredictions in some areas, it would be useful to develop tools that combine CMAQ’s predictive capability in terms of spatial concentration gradients and AQI tendencies with real-time observations of ambient pollutant levels to generate forecasts with higher temporal and spatial resolutions (e.g., county level) than those of techniques based exclusively on monitoring data.
Abstract
This study investigates the potential utility of the application of a photochemical modeling system in providing simultaneous forecasts of ozone (O3) and fine particulate matter (PM2.5) over New York State. To this end, daily simulations from the Community Multiscale Air Quality (CMAQ) model for three extended time periods during 2004 and 2005 have been performed, and predictions were compared with observations of ozone and total and speciated PM2.5. Model performance for 8-h daily maximum O3 was found to be similar to other forecasting systems and to be better than that for the 24-h-averaged total PM2.5. Both pollutants exhibited no seasonal differences in model performance. CMAQ simulations successfully captured the urban–rural and seasonal differences evident in observed total and speciated PM2.5 concentrations. However, total PM2.5 mass was strongly overestimated in the New York City metropolitan area, and further analysis of speciated observations and model predictions showed that most of this overprediction stems from organic aerosols and crustal material. An analysis of hourly speciated data measured in Bronx County, New York, suggests that a combination of uncertainties in vertical mixing, magnitude, and temporal allocation of emissions and deposition processes are all possible contributors to this overprediction in the complex urban area. Categorical evaluation of CMAQ simulations in terms of exceeding two different threshold levels of the air quality index (AQI) again indicates better performance for ozone than PM2.5 and better performance for lower exceedance thresholds. In most regions of New York State, the routine air quality forecasts based on observed concentrations and expert judgment show slightly better agreement with the observed distributions of AQI categories than do CMAQ simulations. However, CMAQ shows skill similar to these routine forecasts in terms of capturing the AQI tendency, that is, in predicting changes in air quality conditions. Overall, the results presented in this study reveal that additional research and development is needed to improve CMAQ simulations of PM2.5 concentrations over New York State, especially for the New York City metropolitan area. On the other hand, because CMAQ simulations capture urban–rural concentration gradients and day-to-day fluctuations in observed air quality despite systematic overpredictions in some areas, it would be useful to develop tools that combine CMAQ’s predictive capability in terms of spatial concentration gradients and AQI tendencies with real-time observations of ambient pollutant levels to generate forecasts with higher temporal and spatial resolutions (e.g., county level) than those of techniques based exclusively on monitoring data.
Abstract
This paper presents model estimates of the effect of chlorine emissions on atmospheric ozone concentrations in the eastern United States. The model included anthropogenic molecular chlorine emissions, anthropogenic hypochlorous acid emissions from cooling towers and swimming pools, and chlorine released from sea-salt aerosols. The release of chlorine emissions from sea-salt aerosols was modeled using heterogeneous reactions involving chloride ions in aerosols and three gas-phase species. The gas-phase chlorine chemistry was combined with the Carbon Bond Mechanism and incorporated into the Community Multiscale Air Quality modeling system. Air quality model simulations were performed for July 2001 and the results obtained with and without chlorine emissions were analyzed. When chlorine emissions were included in the model, ozone concentrations increased in the Houston, Texas, and New York–New Jersey areas. The daily maximum 1-h ozone concentrations increased by up to 12 parts per billion by volume (ppbv) in the Houston area and 6 ppbv in the New York–New Jersey area. The daily maximum 8-h ozone concentrations increased by up to 8 ppbv in the Houston area and 4 ppbv in the New York–New Jersey area. The monthly average daily maximum 1-h ozone concentration increased by up to 3 ppbv in the Houston area, but the increases in the monthly average daily maximum 1-h ozone concentration in the New York–New Jersey area were small. Chlorine emissions and chemistry enhanced the volatile organic compound oxidation rates and, thereby, increased the ozone production rate.
Abstract
This paper presents model estimates of the effect of chlorine emissions on atmospheric ozone concentrations in the eastern United States. The model included anthropogenic molecular chlorine emissions, anthropogenic hypochlorous acid emissions from cooling towers and swimming pools, and chlorine released from sea-salt aerosols. The release of chlorine emissions from sea-salt aerosols was modeled using heterogeneous reactions involving chloride ions in aerosols and three gas-phase species. The gas-phase chlorine chemistry was combined with the Carbon Bond Mechanism and incorporated into the Community Multiscale Air Quality modeling system. Air quality model simulations were performed for July 2001 and the results obtained with and without chlorine emissions were analyzed. When chlorine emissions were included in the model, ozone concentrations increased in the Houston, Texas, and New York–New Jersey areas. The daily maximum 1-h ozone concentrations increased by up to 12 parts per billion by volume (ppbv) in the Houston area and 6 ppbv in the New York–New Jersey area. The daily maximum 8-h ozone concentrations increased by up to 8 ppbv in the Houston area and 4 ppbv in the New York–New Jersey area. The monthly average daily maximum 1-h ozone concentration increased by up to 3 ppbv in the Houston area, but the increases in the monthly average daily maximum 1-h ozone concentration in the New York–New Jersey area were small. Chlorine emissions and chemistry enhanced the volatile organic compound oxidation rates and, thereby, increased the ozone production rate.
Abstract
Ozone is produced by chemical interactions involving nitrogen oxides (NO x ) and volatile organic compounds in the presence of sunlight. At high concentrations, ground-level ozone has been shown to be harmful to human health and to the environment. It has been recognized that ozone is a regional-scale problem and that regionwide control strategies would be needed to improve ozone air quality in the eastern United States. To mitigate interstate transport of ozone and its precursors, the U.S. Environmental Protection Agency issued a regional rule in 1998 known as the “NO x State Implementation Plan (SIP) Call,” requiring 21 states in the eastern United States to reduce their summertime NO x emissions by 30 May 2004. In this paper, the effectiveness of the new emission control measures mandated by the NO x SIP Call is assessed by quantifying the changes that occurred in the daily maximum 8-h ozone concentrations measured at nearly 50 locations, most of which are rural (33 sites of the Clean Air Status and Trend Network and 16 sites of the Air Quality System), over the eastern United States. Given the strong dependence of ozone formation and accumulation on meteorological conditions, the incidence of the latter is first mitigated, and meteorologically adjusted ozone concentrations are extracted using a multiple regression technique. By examining the differences between the cumulative distribution functions of the meteorologically adjusted ozone concentrations, it is shown that ozone concentrations in the eastern United States are now on average 13% less than those prior to the NO x SIP Call. Using back-trajectory analyses, it is also shown that emission controls on the electricity-generating units located in the Ohio River Valley have contributed toward the improvement of ozone air quality in downwind regions, especially east and northeast of the Ohio River Valley.
Abstract
Ozone is produced by chemical interactions involving nitrogen oxides (NO x ) and volatile organic compounds in the presence of sunlight. At high concentrations, ground-level ozone has been shown to be harmful to human health and to the environment. It has been recognized that ozone is a regional-scale problem and that regionwide control strategies would be needed to improve ozone air quality in the eastern United States. To mitigate interstate transport of ozone and its precursors, the U.S. Environmental Protection Agency issued a regional rule in 1998 known as the “NO x State Implementation Plan (SIP) Call,” requiring 21 states in the eastern United States to reduce their summertime NO x emissions by 30 May 2004. In this paper, the effectiveness of the new emission control measures mandated by the NO x SIP Call is assessed by quantifying the changes that occurred in the daily maximum 8-h ozone concentrations measured at nearly 50 locations, most of which are rural (33 sites of the Clean Air Status and Trend Network and 16 sites of the Air Quality System), over the eastern United States. Given the strong dependence of ozone formation and accumulation on meteorological conditions, the incidence of the latter is first mitigated, and meteorologically adjusted ozone concentrations are extracted using a multiple regression technique. By examining the differences between the cumulative distribution functions of the meteorologically adjusted ozone concentrations, it is shown that ozone concentrations in the eastern United States are now on average 13% less than those prior to the NO x SIP Call. Using back-trajectory analyses, it is also shown that emission controls on the electricity-generating units located in the Ohio River Valley have contributed toward the improvement of ozone air quality in downwind regions, especially east and northeast of the Ohio River Valley.
Abstract
The observed scatter of observations about air quality model predictions stems from a combination of naturally occurring stochastic variations that are impossible for any model to simulate explicitly and variations arising from limitations in knowledge and from imperfect input data. In this paper, historical tracer experiments of atmospheric dispersion were analyzed to develop algorithms to characterize the observed stochastic variability in the ground-level crosswind concentration profile. The algorithms were incorporated into a Lagrangian puff model (“INPUFF”) so that the consequences of variability in the dispersion could be simulated using Monte Carlo methods. The variability in the plume trajectory was investigated in a preliminary sense by tracking the divergence in trajectories from releases adjacent to the actual release location. The variability in the near-centerline concentration values not described by the Gaussian crosswind profile was determined to be on the order of a factor of 2. The variability in the trajectory was determined as likely to be larger than the plume width, even with local wind observations for use in characterizing the transport. Two examples are provided to illustrate how estimates of variability 1) can provide useful information to inform decisions for emergency response and 2) can provide a basis for sound statistical designs for model performance assessments.
Abstract
The observed scatter of observations about air quality model predictions stems from a combination of naturally occurring stochastic variations that are impossible for any model to simulate explicitly and variations arising from limitations in knowledge and from imperfect input data. In this paper, historical tracer experiments of atmospheric dispersion were analyzed to develop algorithms to characterize the observed stochastic variability in the ground-level crosswind concentration profile. The algorithms were incorporated into a Lagrangian puff model (“INPUFF”) so that the consequences of variability in the dispersion could be simulated using Monte Carlo methods. The variability in the plume trajectory was investigated in a preliminary sense by tracking the divergence in trajectories from releases adjacent to the actual release location. The variability in the near-centerline concentration values not described by the Gaussian crosswind profile was determined to be on the order of a factor of 2. The variability in the trajectory was determined as likely to be larger than the plume width, even with local wind observations for use in characterizing the transport. Two examples are provided to illustrate how estimates of variability 1) can provide useful information to inform decisions for emergency response and 2) can provide a basis for sound statistical designs for model performance assessments.
