Use of Project MOHAVE perfluorocarbon tracer data to evaluate source and receptor models

Project MOHAVE was a major monitoring, modeling, and data analysis study whose objectives included the estimation of the contributions of the Mohave Power Project (MPP) and other sources to visibility impairment in the southwestern United States, in particular at Grand Canyon National Park. A major element of Project MOHAVE was the release of perfluorocarbon tracers at MPP and other locations during 50-day summer and 30-day winter intensive study periods. Tracer data (from about 30 locations) were sequestered until several source and receptor models were used to predict tracer concentrations. None of the models was successful in predicting the tracer concentrations; squared correlation coefficients between predicted and measured tracer were all less than 0.2, and most were less than 0.1.     

Relating Summer Ambient Particulate Sulfur,Sulfur Dioxide,and Light Scattering to Gaseous Tracer Emissions from the MOHAVE Power Project

ABSTRACT

Project MOHAVE was initiated in 1992 to examine the role of emissions from the 1580 MW coal-fired MOHAVE Power Project (MPP) on haze at the Grand Canyon National Park (GCNP), located about 130 km north-northeast of the power plant. Statistical relationships were analyzed between summertime ambient concentrations of a gaseous perfluorocarbon tracer released from MPP and ambient SO₂, particulate sulfur, and light scattering to evaluate whether MPP's emissions could be transported to the GCNP and then impact haze levels there. Spatial analyses indicated that particulate sulfur levels were strongly correlated across the monitoring network, regardless of whether the monitoring stations were upwind or downwind of MPP. This indicates that particulate sulfur levels in this region were influenced by distant regional emission sources. A significant particulate sulfur contribution from a point source such as MPP would result in a non-uniform pattern downwind. There was no suggestion of this in the data.

Furthermore, correlations between the MPP tracer and ambient particulate sulfur and light scattering at locations in the park were virtually zero for averaging times ranging from 24 hr to 1 hr. Hour-by-hour MPP tracer levels and light scattering were individually examined, and still no positive correlations were detected. Finally, agreement between tracer and particulate sulfur did not improve as a function of meteorological regime, implying that, even during cloudy monsoon days when more rapid conversion of SO₂ to par-ticulate sulfur would be expected, there was no evidence for downwind particulate sulfur impacts. Despite the fact that MPP was a large source of SO₂ and tracer, neither time series nor correlation analyses were able to detect any meaningful relationship between MPP's SO₂ and tracer emission “signals” to particulate sulfur or light scattering.     

Characterization of regional transport and dispersion using Project MOHAVE tracer data

Perfluorocarbon tracers were released continuously from several surface locations and one power plant stack location during the winter (30 days) and summer (50 days) intensive studies as part of Project MOHAVE. Tracers were released in winter from the Mohave Power Plant (MPP) and Dangling Rope, UT, located on the shore of Lake Powell near Page, AZ; and in summer from MPP, the Tehachapi Pass between the Mojave Desert and the Central Valley in California, and El Centro, CA, on the California-Mexico border. At the Tehachapi tracer release site six-hour pulses of a separately identifiable perfluorocarbon tracer were released every four days in order to assess the time for the tracer to clear the monitoring network. Daily 24-hr integrated samples were collected at about 30 sites in four states. Limited tracer concentration data with higher time resolution is also available. Graphical displays and analyses identify several regional transport paths, including a convergence zone in the Mojave Desert, the importance of terrain channeling, especially in winter, and a relationship between 24-hr maximum influence function and distance that may prove useful as a scoping tool and to test regional scale air quality models. In winter, Dangling Rope tracer was routinely transported through the entire length of the Grand Canyon, while in summer, MPP tracer was routinely transported over most of Lake Mead.     

Second Generation Chemical Mass Balance Source Apportionment of Sulfur Oxides and Sulfate at the Grand Canyon during the Project MOHAVE Summer Intensive

ABSTRACT

Receptor-based chemical mass balance (CMB) analysis techniques are designed to apportion species that are conserved during pollutant transport using conserved source profiles. The techniques will fail if non-conservative species (or profiles) are not properly accounted for in the CMB model. The straightforward application of the CMB model developed for Project MOHAVE using regional profiles resulted in a significant under-prediction of total sulfate oxides (SO_x, SO₂ plus fine particulate sulfate) for many samples at Meadview, AZ. In addition, for these samples the concentration of the inert tracer emitted from the MOHAVE Power Project (MPP), ocPDCH, was also under-predicted. A second-generation model has been developed which assumes that separation of particles and SO₂ can occur in the MPP plume during nighttime stable plume conditions. This second-generation CMB model accounts for all SO_x present at the various receptor sites. In addition, the concentrations of ocPDCH and the presence of other inert tracers of emission from regional sources are accurately predicted. The major source of SO_x at Meadview was the MPP, but the major source of sulfate at this site was the Las Vegas urban area. At Hopi Point in the Grand Canyon, the Baja California region (Imperial Valley and northwestern Mexico) was the major source of both SO_x and sulfate.     

Increasing the Use of Earth Science Data and Models in Air Quality Management

In 2010, the U.S. National Aeronautics and Space Administration (NASA) initiated the Air Quality Applied Science Team (AQAST) as a 5-year, $17.5-million award with 19 principal investigators. AQAST aims to increase the use of Earth science products in air quality-related research and to help meet air quality managers’ information needs. We conducted a Web-based survey and a limited number of follow-up interviews to investigate federal, state, tribal, and local air quality managers’ perspectives on usefulness of Earth science data and models, and on the impact AQAST has had. The air quality managers we surveyed identified meeting the National Ambient Air Quality Standards for ozone and particulate matter, emissions from mobile sources, and interstate air pollution transport as top challenges in need of improved information. Most survey respondents viewed inadequate coverage or frequency of satellite observations, data uncertainty, and lack of staff time or resources as barriers to increased use of satellite data by their organizations. Managers who have been involved with AQAST indicated that the program has helped build awareness of NASA Earth science products, and assisted their organizations with retrieval and interpretation of satellite data and with application of global chemistry and climate models. AQAST has also helped build a network between researchers and air quality managers with potential for further collaborations.

Implications: NASA’s Air Quality Applied Science Team (AQAST) aims to increase the use of satellite data and global chemistry and climate models for air quality management purposes, by supporting research and tool development projects of interest to both groups. Our survey and interviews of air quality managers indicate they found value in many AQAST projects and particularly appreciated the connections to the research community that the program facilitated. Managers expressed interest in receiving continued support for their organizations’ use of satellite data, including assistance in retrieving and interpreting data from future geostationary platforms meant to provide more frequent coverage for air quality and other applications.     

Relating summer ambient particulate sulfur, sulfur dioxide, and light scattering to gaseous tracer emissions from the MOHAVE Power Project

Project MOHAVE was initiated in 1992 to examine the role of emissions from the 1580 MW coal-fired MOHAVE Power Project (MPP) on haze at the Grand Canyon National Park (GCNP), located about 130 km north-north-east of the power plant. Statistical relationships were analyzed between summertime ambient concentrations of a gaseous perfluorocarbon tracer released from MPP and ambient SO2, particulate sulfur, and light scattering to evaluate whether MPP's emissions could be transported to the GCNP and then impact haze levels there. Spatial analyses indicated that particulate sulfur levels were strongly correlated across the monitoring network, regardless of whether the monitoring stations were upwind or downwind of MPP. This indicates that particulate sulfur levels in this region were influenced by distant regional emission sources. A significant particulate sulfur contribution from a point source such as MPP would result in a non-uniform pattern downwind. There was no suggestion of this in the data. Furthermore, correlations between the MPP tracer and ambient particulate sulfur and light scattering at locations in the park were virtually zero for averaging times ranging from 24 hr to 1 hr. Hour-by-hour MPP tracer levels and light scattering were individually examined, and still no positive correlations were detected. Finally, agreement between tracer and particulate sulfur did not improve as a function of meteorological regime, implying that, even during cloudy monsoon days when more rapid conversion of SO2 to particulate sulfur would be expected, there was no evidence for downwind particulate sulfur impacts. Despite the fact that MPP was a large source of SO2 and tracer, neither time series nor correlation analyses were able to detect any meaningful relationship between MPP's SO2 and tracer emission "signals" to particulate sulfur or light scattering.     

Precision and Accuracy in the Determination of Sulfur Oxides,Fluoride, and Spherical Aluminosilicate Fly Ash Particles in Project MOHAVE

The precision and accuracy of the determination of particu-late sulfate and fluoride, and gas phase SO₂ and HF are estimated from the results obtained from collocated replicate samples and from collocated comparison samples for high-and low-volume filter pack and annular diffusion denuder samplers. The results of replicate analysis of collocated samples and replicate analyses of a given sample for the determination of spherical aluminosilicate fly ash particles have also been compared. Each of these species is being used in the chemical mass balance source apportionment of sulfur oxides in the Grand Canyon region as part of Project MOHAVE, and the precision and accuracy analyses given in this paper provide input to that analysis. The precision of the various measurements reported here is ±1.8 nmol/m³ and ±2.5 nmol/m³ for the determination of SO₂ and sulfate, respectively, with an annular denuder. The precision is ±0.5 nmol/m³ and ±2.0 nmol/m³ for the determination of the same species with a high-volume or low-volume filter pack. The precision for the determination of the sum of HF(g) and fine particulate fluoride is ±0.3 nmol/m³. The precision for the determination of aluminosilicate fly ash particles is ±100 particles/m³. At high concentrations of the various species, reproducibility of the various measurements is ±10% to ±14% of the measured concentration. The concentrations of sulfate determined using filter pack samplers are frequently higher than those determined using diffusion denuder sampling systems. The magnitude of the difference (e.g., 2-10 nmol sulfate/m³) is small, but important relative to the precision of the data and the concentrations of particulate sul-fate present (typically 5-20 nmol sulfate/m³). The concentrations of SO₂(g) determined using a high-volume cascade impactor filter pack sampler are correspondingly lower than those obtained with diffusion denuder samplers. The concentrations of SO_x (SO₂(g) plus particulate sulfate) determined using the two samplers during Project MOHAVE at the Spirit Mountain, NV, and Hopi Point, AZ, sampling sites were in agreement. However, for samples collected at Painted Desert, AZ, and Meadview, AZ, the concentrations of SO_x and SO₂(g) determined with a high-volume cascade impactor filter pack sampler were frequently lower than those determined using a diffusion denuder sampling system. These two sites had very low ambient relative humidity, an average of 25%. Possible causes of observed differences in the SO₂(g) and sulfate results obtained from different types of samplers are given.     

Source Fingerprints for Receptor Modeling of Volatile Organics

The development of receptor models for the determination of the sources of an ambient air pollutant requires that the composition of the pollutant at the point of emission be known. For this study, composition information for 10 sources of volatile organic compounds (VOC) were evaluated and source fingerprints developed. The source categories include motor vehicles, gasoline vapor, petroleum refineries, architectural coatings, graphic arts, waste-water treatment, vapor degreasing, drycleaning, automobile assembly (including body painting), and polyethylene production. The fingerprints are presented for a group of 23 compounds. These compounds were selected for a variety of reasons including ease of measurement in the ambient environment, compound toxicity, reactivity, and usefulness in previous receptor modeling applications. In general, the data for sources of VOC are remarkably consistent from study to study. Because the profiles for many of the sources of VOC are controlled by physical and chemical processes (e.g. combustion) and not raw material composition, the fingerprints have general applicability.     

Receptor Oriented Methods of Air Particulate Source Apportionment

Receptor models have evolved rapidly over the past 13 years but have just recently been recognized as a distinct discipline. The general category of receptor models includes both microscopic and chemical methods of apportioning source contributions to ambient air particulates. The number and variations of these methods have grown rapidly over the past few years and include such methods as automated scanning electron microscopy, chemical mass balance and multivariate procedures. These methods as well as hybrid procedures such as target transformation factor analysis, are reviewed and their boundary conditions, strengths, and weaknesses discussed.     

Second generation chemical mass balance source apportionment of sulfur oxides and sulfate at the Grand Canyon during the Project MOHAVE summer intensive

Receptor-based chemical mass balance (CMB) analysis techniques are designed to apportion species that are conserved during pollutant transport using conserved source profiles. The techniques will fail if non-conservative species (or profiles) are not properly accounted for in the CMB model. The straightforward application of the CMB model developed for Project MOHAVE using regional profiles resulted in a significant under-prediction of total sulfate oxides (SOx, SO2 plus fine particulate sulfate) for many samples at Meadview, AZ. In addition, for these samples the concentration of the inert tracer emitted from the MOHAVE Power Project (MPP), ocPDCH, was also under-predicted. A second-generation model has been developed which assumes that separation of particles and SO2 can occur in the MPP plume during nighttime stable plume conditions. This second-generation CMB model accounts for all SOx present at the various receptor sites. In addition, the concentrations of ocPDCH and the presence of other inert tracers of emission from regional sources are accurately predicted. The major source of SOx at Meadview was the MPP, but the major source of sulfate at this site was the Las Vegas urban area. At Hopi Point in the Grand Canyon, the Baja California region (Imperial Valley and northwestern Mexico) was the major source of both SOx and sulfate.     

Conjunctive Use of Models to Design Cost-Effective Ozone Control Strategies

Abstract

The management of tropospheric ozone (O₃) is particularly difficult. The formulation of emission control strategies requires considerable information including: (1) emission inventories, (2) available control technologies, (3) meteorological data for critical design episodes, and (4) computer models that simulate atmospheric transport and chemistry. The simultaneous consideration of this information during control strategy design can be exceedingly difficult for a decision-maker. Traditional management approaches do not explicitly address cost minimization. This study presents a new approach for designing air quality management strategies; a simple air quality model is used conjunctively with a complex air quality model to obtain low-cost management strategies. A simple air quality model is used to identify potentially good solutions, and two heuristic methods are used to identify cost-effective control strategies using only a small number of simple air quality model simulations. Subsequently, the resulting strategies are verified and refined using a complex air quality model. The use of this approach may greatly reduce the number of complex air quality model runs that are required. An important component of this heuristic design framework is the use of the simple air quality model as a screening and exploratory tool. To achieve similar results with the simple and complex air quality models, it may be necessary to “tweak” or calibrate the simple model. A genetic algorithm-based optimization procedure is used to automate this tweaking process. These methods are demonstrated to be computationally practical using two realistic case studies, which are based on data from a metropolitan region in the United States.     

Dissociation of Sulfur Hexafluoride Tracer Gas in the Presence of an Indoor Combustion Source

ABSTRACT

As an odorless, nontoxic, and inert compound, sulfur hexafluoride (SF₆) is one of the most widely used tracer gases in indoor air quality studies in both controlled and uncontrolled environments. This compound may be subject to reactions with water vapor under elevated temperature to form acidic inorganic compounds such as HF and H₂SO₄. Thus, in the presence of unvented combustion sources such as kerosene heaters, natural gas heaters, gas log fireplaces, candles, and lamps, the SF₆ dissociation may interfere with measurements of the emissions from these sources. Tests were conducted in a research house with a vent-free natural gas heater to investigate these potential interferences. It was observed that the heater operation caused about a 5% reduction of SF₆ concentration, which can be an error source for the ventilation rate measurement and consequently the estimated pollutant emission rates. Further analysis indicates that this error can be much greater than the observed 5% under certain test conditions because it is a function of the ventilation flow rate. Reducing the tracer gas concentration has no effect on this error. A simple theoretical model is proposed to estimate the magnitude of this error.

The second type of interference comes from the primary and secondary products of the SF₆ dissociation, mainly H₂SO₄, SO₂, HF, and fine particulate matter (PM). In the presence of ~5 ppm SF₆, the total airborne concentrations of these species increased by a factor of 4-10. The tests were performed at relatively high SF₆ concentrations, which is necessary to determine the interferences quantitatively. The second type of interference can be significantly reduced if the SF₆ concentration is kept at a low ppb level.     

Receptor Modeling for Elemental Source Contributions to Fine Aerosols in New York State

ABSTRACT

Fine atmospheric particulate material was collected at five sites in upstate New York and analyzed for its trace element composition by instrumental neutron activation analysis. Of the 3700 daily samples collected over a 2-yr period, 1459 were analyzed for 39 elements, providing a large and detailed data set. Factor analysis (FA) was used to identify potential pollution sources or source regions and to construct inorganic source profiles for each. Following FA, the method of absolute factor scores-multiple linear regression was used to estimate the absolute elemental contribution of each of the identified sources. Factor analysis identified nine sources impacting the sampling region. Seven of these were found to be present in varying degrees among of the sampling sites. The other two sources had more localized impacts and were observed at only one of the sites each. Regional sources (such as the midwestern United States and eastern Canada) and crustal/ soil material accounted for the greatest amount of the trace elements measured in the collected material.     

Uncertainty in Nonpoint Source Pollution Models and Associated Risks

The usefulness of water quality simulation models for environmental management is explored with a focus on prediction uncertainty. The specific objective is to demonstrate how the usability of a flow and transport model (here: MACRO) can be enhanced by developing and analyzing its output probability distributions based on input variability. This infiltration-based model was designed to investigate preferential flow effects on pollutant transport. A statistical sensitivity analysis is used to identify the most uncertain input parameters based on model outputs. Probability distribution functions of input variables were determined based on field-measured data obtained under alternative tillage treatments. Uncertainty of model outputs is investigated using a Latin hypercube sampling scheme (LHS) with restricted pairing for model input sampling. Probability density functions (pdfs) are constructed for water flow rate, atrazine leaching rate, total accumulated leaching, and atrazine concentration in percolation water. Results indicate that consideration of input parameter uncertainty produces a 20% higher mean flow rate along with two to three times larger atrazine leaching rate, accumulated leachate, and concentration than that obtained using mean input parameters. Uncertainty in predicted flow rate is small but that in solute transport is an order of magnitude larger than that of corresponding input parameters. Macropore flow is observed to contribute to the variability of atrazine transport results. Overall, the analysis provides a quantification of prediction uncertainty that is found to enhance a user's ability to assess risk levels associated with model predictions.     

Uncertainty in Nonpoint Source Pollution Models and Associated Risks

The usefulness of water quality simulation models for environmental management is explored with a focus on prediction uncertainty. The specific objective is to demonstrate how the usability of a flow and transport model (here: MACRO) can be enhanced by developing and analyzing its output probability distributions based on input variability. This infiltration-based model was designed to investigate preferential flow effects on pollutant transport. A statistical sensitivity analysis is used to identify the most uncertain input parameters based on model outputs. Probability distribution functions of input variables were determined based on field-measured data obtained under alternative tillage treatments. Uncertainty of model outputs is investigated using a Latin hypercube sampling scheme (LHS) with restricted pairing for model input sampling. Probability density functions (pdfs) are constructed for water flow rate, atrazine leaching rate, total accumulated leaching, and atrazine concentration in percolation water. Results indicate that consideration of input parameter uncertainty produces a 20% higher mean flow rate along with two to three times larger atrazine leaching rate, accumulated leachate, and concentration than that obtained using mean input parameters. Uncertainty in predicted flow rate is small but that in solute transport is an order of magnitude larger than that of corresponding input parameters. Macropore flow is observed to contribute to the variability of atrazine transport results. Overall, the analysis provides a quantification of prediction uncertainty that is found to enhance a user's ability to assess risk levels associated with model predictions.     

Use of Bioassay Methods to Evaluate Mutagenicity of Ambient Air Collected Near a Municipal Waste Combustor

An ambient air sampling study was conducted around a municipal waste combustor; a primary goal was to develop procedures and methods to evaluate the emissions of organic mutagens resulting from incomplete combustion of municipal waste. The products of Incomplete combustion from incineration include complex mixtures of organics, particularly polycycllc aromatic compounds, which are present after atmospheric dilution and cooling In emissions as semi-volatile or particle bound organic compounds. Combustion emissions are generally recognized as a potential cancer risk since they contain many carcinogenic and mutagenlc polycyclic aromatic hydrocarbons. Analyzing such a complex mixture for the presence of even a few selected chemicals is difficult and provides risk information on only a fraction of the chemicals present. Bioassay methods, however, may be directly applied to evaluate the mutagenic and potential carcinogenic activity of the complex organics from combustion emissions. The Salmonella (Ames) assay was used to determine the mutagenicity associated with particles from ambient air collected near a municipal waste combustor. Dose-response data was generated, and mutagenicity concentrations were calculated to demonstrate the utility of bioassay In assessing the potential Impact of emissions from municipal waste combustion. This phase of study quantified mutagenicity concentrations In ambient air but did not detect organic mutagens that could be attributed to Incinerator emissions.     

Use of n-Fold Cross-Validation to Evaluate Three Methods to Calculate Heavy Truck Annual Average Daily Traffic and Vehicle Miles Traveled

Abstract

Reliable estimates of heavy-truck volumes in the United States are important in a number of transportation applications including pavement design and management, traffic safety, and traffic operations. Additionally, because heavy vehicles emit pollutants at much higher rates than passenger vehicles, reliable volume estimates are critical to computing accurate inventories of on-road emissions. Accurate baseline inventories are also necessary to forecast future scenarios. The research presented in this paper evaluated three different methods commonly used by transportation agencies to estimate annual average daily traffic (AADT), which is used to determine vehicle miles traveled (VMT). Traffic data from continuous count stations provided by the Iowa Department of Transportation were used to estimate AADT for single-unit and multiunit trucks for rural freeways and rural primary highways using the three methods. The first method developed general expansion factors, which apply to all vehicles. AADT, representing all vehicles, was estimated for short-term counts and was multiplied by statewide average truck volumes for the corresponding roadway type to obtain AADT for each truck category. The second method also developed general expansion factors and AADT estimates. Truck AADT for the second method was calculated by multiplying the general AADT by truck volumes from the short-term counts. The third method developed expansion factors specific to each truck group. AADT estimates for each truck group were estimated from short-term counts using corresponding expansion factors. Accuracy of the three methods was determined by comparing actual AADT from count station data to estimates from the three methods. Accuracy of the three methods was compared using n-fold cross-validation. Mean squared error of prediction was used to estimate the difference between estimated and actual AADT. Prediction error was lowest for the method that developed separate expansion factors for trucks. Implications for emissions estimation using the different methods are also discussed.     

The Use of Stable Isotopes to Differentiate Specific Source Markers for MTBE

The recent controversy over the use of MTBE within gasoline to boost oxygen content and decrease carbon monoxide emissions to the atmosphere has led to a proposed phase-out of this compound by 2002. This paper is a preliminary investigation into the use of gas chromatography isotope-ratio mass spectrometry (GCIRMS) to determine both carbon and hydrogen isotopic compositions of MTBE as a means of differentiating sources of MTBE. Three pure MTBE samples were purchased from chemical distributors. Little variation of the δ¹³C values were observed although the samples had isotopically distinct δ-D values. Four different methods of obtaining carbon isotope ratios of neat MTBE, MTBE in gasoline, and MTBE in water are described, and the precision and accuracy of each is discussed. The carbon isotopic compositions of MTBE within 10 gasoline samples from three different areas of the United States show a wide range of carbon isotope compositions. This novel method of MTBE analysis could be valuable in forensic investigations.     

The Use of Stable Isotopes to Differentiate Specific Source Markers for MTBE

The recent controversy over the use of MTBE within gasoline to boost oxygen content and decrease carbon monoxide emissions to the atmosphere has led to a proposed phase-out of this compound by 2002. This paper is a preliminary investigation into the use of gas chromatography isotope-ratio mass spectrometry (GCIRMS) to determine both carbon and hydrogen isotopic compositions of MTBE as a means of differentiating sources of MTBE. Three pure MTBE samples were purchased from chemical distributors. Little variation of the i 13 C values were observed although the samples had isotopically distinct i -D values. Four different methods of obtaining carbon isotope ratios of neat MTBE, MTBE in gasoline, and MTBE in water are described, and the precision and accuracy of each is discussed. The carbon isotopic compositions of MTBE within 10 gasoline samples from three different areas of the United States show a wide range of carbon isotope compositions. This novel method of MTBE analysis could be valuable in forensic investigations.