Quantitative Transport Bias Analysis Research Articles

Overview of the Trajectory-Ensemble Potential Source Apportionment Web (TraPSA-Web) Toolkit for Atmospheric Pollutant Source Identification

Trajectory ensemble receptor models (TERMs) were widely used to determine the likely source locations and apportionment of air pollutants. This paper describes the development and applications of the Trajectory-ensemble Potential Source Apportionment Web application (TraPSA-Web), a comprehensive toolkit for likely atmospheric pollutant source location apportionments using TERMs and back trajectories generated with the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model. The TERMs integrated within the TraPSA-web include Concentration Field Analysis (CFA), Concentration Weighted Trajectory (CWT), single-site and multiple-site Potential Source Contribution Function (PSCF), and Simplified Quantitative Transport Bias Analysis (SQBA). TraPSA-Web is designed as a web application with a user-friendly modern graphical user interface (GUI), which largely enhances the accessibility to the users. TraPSA-Web will provide the air quality research community with a sophisticated toolkit for (1) easy management of the research project and datasets, (2) efficient automatization for HYSPLIT configurations, calculations, and result aggregations, (3) flexible configurations for the research scenarios and TERM parameters, and (4) interactive visualizations for the pollutant pattern analysis and TERM result mapping.

Ambient Ammonia Concentrations Across New York State

AbstractAmmonia (NH3) was monitored at four locations (two urban and two rural) across New York State from April 2016 to October 2017 using active and passive systems. The two rural sites were Pinnacle State Park (PIN) and the Village of Potsdam, and the two urban sites were the City of Rochester and Queens College in New York City. Active and passive concentrations were well correlated across all sites (r2 = 0.866), but the active systems measured 6.2% higher NH3 concentrations. The mean (±SD) NH3 concentrations measured using active systems in Queens College, City of Rochester, Village of Potsdam, and PIN were 3.22 ± 2.23, 2.84 ± 1.91, 1.29 ± 1.12, and 0.82 ± 0.64 ppb, respectively. Ambient NH3 concentrations varied with diel vehicular and seasonal agricultural activities. NH3 concentrations at the urban sites had lower seasonal variability than the rural sites. NH3 concentrations were generally related to regional and in‐state NH3 emissions although less regional influence was observed at the urban sites. Local NH3 source directions were identified using conditional bivariate probability function. The urban sites were affected by local NH3 sources such as vehicular emissions and urban population centers. Likely distant NH3 source locations affecting the four sites were identified using simplified quantitative transport bias analysis model. Rural sites were more highly affected by transported NH3. Midwestern and Atlantic were major NH3 source areas. NH3 emissions from the south of PIN were probably due to the use of diesel trucks and other diesel engines in the hydraulic fracturing industry in Pennsylvania near the New York State border.

Sources and temporal variations of constrained PMF factors obtained from multiple-year receptor modeling of ambient PM2.5 data from five speciation sites in Ontario, Canada

The Canadian National Air Pollution Surveillance (NAPS) network operates five fine particulate matter (PM2.5) speciation sites in Ontario. Data from 2005 to 2010 from these sites were subjected to constrained positive matrix factorization (PMF) to obtain factors of particulate matter pollution. Eight factors were found to be common across the sites. These constrained factors were particulate sulfate and nitrate, aged combustion aerosols, biomass/wood combustion, non-ferrous metal smelting, crustal matter, steel works, and road salt. Other factors found at these sites were largely related to local sources in their respective neighbourhoods. Diagnostic results from constraining the PMF factors could be used to select the appropriate post-PMF analyses as they reveal the factors that were expected to have regional or local sources. Interpretation of the spatial trends of factors was guided by the extent of similarity of target ratios across the five sites as determined by their coefficient of variation (C.V.). On average, particulate sulfate had PM2.5 mass contributions that ranged from 7% (Wallaceburg) to 36% (Simcoe) and nitrate species ranged from 7% (Simcoe) to 23% (Windsor). A clear low rural – high urban divide for particulate nitrate was also observed. These non-uniform impacts across the sites indicate that a single representative location is not suitable for studying PM2.5 in Ontario. Temporal variations showed greater abundance of particulate sulfate in the summer and particulate nitrate in the winter respectively. Yearly median values of the sulfate factor that is largely energy-related have been declining for most sites since peaking in 2007. A trajectory ensemble model, simplified quantitative transport bias analysis (sQTBA) was used to identify potential source regions of the constrained sulfate and nitrate factors while radial plots of the conditional probability function (CPF) were used to explore the more locally-sourced factors. The US Midwest, east coast and Canada's west were dominant regional sources.

Impacts of forest fires on ambient near–real–time PM2.5 in Ontario, Canada: Meteorological analyses and source apportionment of the July 2011–2013 episodes

The complexity of analyzing and predicting smoke plumes that originate from forest fire events and impact populated regions of southern Ontario motivates the innovative application of analytical techniques including trajectory–based receptor modeling for spatial source apportionment of the observed near–real–time particulate matter (PM) impacts. PM2.5 was selected as an indicator of a pollutant emitted by fires that could be transported over long distances (when entrained into the transport layer above the planetary boundary layer (PBL), and subject to sink and transformation processes) and be monitored using the existing air quality monitoring network. The source term modeling technique of simplified Quantitative Transport Bias Analysis (sQTBA) was applied to several summertime forest fire events to identify the locations of sources affecting air quality in Ontario during these events. Complementary techniques that helped to understand the movement of smoke plumes included satellite remote sensing of carbon monoxide and aerosols. All of these techniques, along with meteorological analysis, jointly provide a means of identifying the forest fire events that resulted in noticeably higher pollutant levels in Ontario. Specifically, three forest fire events in July of 2011, 2012 and 2013 were analyzed, and source regions of near–real–time PM2.5 concentrations were revealed to be both within Ontario and across northern Canada from Quebec to Yukon. The sQTBA was found to successfully identify the relative importance of various source regions contributing plumes from forest fires and non–wildfire related sources that caused higher pollutant levels that were measured in Ontario. The use of near–real–time PM2.5 data in this study facilitates the identification of the exact periods with high pollution impacts across multiple receptor sites, thus improving the overall quality of the analyses. This work shows how trajectory–based receptor models can be integrated with meteorological analyses for thorough source apportionment of wildfire–related pollution events.

Advanced receptor modeling of near–real–time, ambient PM2.5 and its associated components collected at an urban–industrial site in Toronto, Ontario

PM2.5 and other atmospheric pollutants were continuously monitored at high time resolution for 1 year at an urban–industrial location in Toronto, ON, Canada's largest city. The data collected for these pollutants were examined to determine seasonal trends and potential sources. Advanced receptor models including residence time weighted concentration (RTWC) and simplified quantitative transport bias analysis (sQTBA) trajectory ensemble models (TEM) and conditional probability function (CPF) were applied to these data to identify potential local and regional sources of pollution impacting this receptor site. Seasonal trends showed that concentrations of PM2.5 were more frequently high in winter than in any other season. Median concentrations of lead and arsenic were highest in fall while median levels of chromium were not significantly different over the four seasons. The black carbon–derived measurement commonly known as Delta C (i.e., BC370nm–BC880nm) had its greatest abundance in winter and lowest levels in summer. The seasonality of Delta C is indicative of the impact of residential wood combustion near the receptor site. CPF indicated that lead and iron had the most unidirectional radial plots with sectors located west–southwest of the receptor being the most likely local source regions. Winter CPF for Delta C is almost of equal strengths in all directions suggestive of near–uniform isotropic local impacts. The sQTBA model provided the most satisfactory spatial representation of impacting sources. The strongest sources of PM2.5 identified by the sQTBA model were both local and transboundary in origin. More potential source regions were found in winter and summer than in spring and fall.

Assessing the Emission Sources of Atmospheric Mercury in Wet Deposition Across Illinois, USA

From August 2007 to August 2009, we collected event-based precipitation samples for mercury (Hg) and trace element analysis at four sites in Illinois, USA. The objectives of these measurements were to quantify the levels of Hg wet deposition across the state, and to assess the contributions to Hg in precipitation from major local and regional emission sources. The measurement sites were located in Chicago, Peoria, Nilwood, and Carbondale, IL. We were not able to identify a clear spatial gradient in Hg wet deposition among the sites. At all four locations we frequently observed Hg concentrations in precipitation > 25 ng/L, while each site received > 10 μg/m2 of Hg wet deposition annually, suggesting a substantial impact from local and regional anthropogenic emission sources. We applied the multivariate statistical receptor model Positive Matrix Factorization (PMF) to the measured Hg and trace element wet deposition amounts at the four sites. The results suggested that 60-83% of total Hg deposition at each site could be attributed to coal combustion emissions. Although we identified other source signatures in the precipitation composition, including cement manufacturing, metal smelting / waste incineration, and iron-steel production, these sources contributed substantially less to the measured amounts of Hg wet deposition. We also applied the hybrid receptor model Quantitative Transport Bias Analysis (QTBA) to the Hg wet deposition data from each site to identify the major source regions associated with the measured values. Results suggested that sources in the Chicago/Gary, St. Louis, and Ohio River Valley urban/industrial areas had a substantial impact on Hg wet deposition, strongly supporting the conclusion that local and regional coal combustion was the largest source of Hg wet deposition in Illinois.

Assessing the emission sources of atmospheric mercury in wet deposition across Illinois

From August 4, 2007 to August 31, 2009, we collected event-based precipitation samples for mercury (Hg) and trace element analyses at four sites in Illinois (IL), USA. The objectives of these measurements were to quantify Hg wet deposition across the state, and to assess the contributions to Hg in precipitation from major local and regional emission sources. Monitoring sites were located, from north to south, in Chicago, Peoria, Nilwood, and Carbondale, IL. Measurements from these four sites demonstrated that a clear spatial gradient in Hg wet deposition was not evident across the state. Each site received>10μgm−2 of Hg wet deposition annually, and these observed values were comparable to annual Hg wet deposition measurements from other event-based precipitation monitoring sites in source-impacted areas of the Midwestern U.S. We applied the multivariate statistical receptor model, Positive Matrix Factorization (EPA PMF v3.0), to the measured Hg and trace element wet deposition amounts at the four sites. Results suggested that 50% to 74% of total Hg wet deposition at each site could be attributed to coal combustion emissions. The other source signatures identified in the precipitation compositions included cement manufacturing, mixed metal smelting/waste incineration, iron–steel production, and a phosphorus source. We also applied a hybrid receptor model, Quantitative Transport Bias Analysis (QTBA), to the Hg wet deposition datasets to identify the major source regions associated with the measured values. The calculated QTBA probability fields suggested that transport from urban/industrial areas, such as Chicago/Gary, St. Louis, and the Ohio River Valley, resulted in some of the highest estimated event-based Hg wet deposition amounts at the four sites (potential mass transfer of up to 0.32μgm−2). The combined application of PMF and QTBA supported the hypothesis that local and regional coal combustion was the largest source of Hg wet deposition in Illinois.

Identifying sources of fugitive emissions in industrial facilities using trajectory statistical methods

Fugitive pollutant sources from the oil and gas industry are typically quite difficult to find within industrial plants and refineries, yet they are a significant contributor of global greenhouse gas emissions. A novel approach for locating fugitive emission sources using computationally efficient trajectory statistical methods (TSM) has been investigated in detailed proof-of-concept simulations. Four TSMs were examined in a variety of source emissions scenarios developed using transient CFD simulations on the simplified geometry of an actual gas plant: potential source contribution function (PSCF), concentration weighted trajectory (CWT), residence time weighted concentration (RTWC), and quantitative transport bias analysis (QTBA). Quantitative comparisons were made using a correlation measure based on search area from the source(s). PSCF, CWT and RTWC could all distinguish areas near major sources from the surroundings. QTBA successfully located sources in only some cases, even when provided with a large data set. RTWC, given sufficient domain trajectory coverage, distinguished source areas best, but otherwise could produce false source predictions. Using RTWC in conjunction with CWT could overcome this issue as well as reduce sensitivity to noise in the data. The results demonstrate that TSMs are a promising approach for identifying fugitive emissions sources within complex facility geometries.

Sources of mercury in precipitation to Underhill, VT

Daily event precipitation samples were collected from 1995 to 2006 in Underhill, VT, USA and analyzed for mercury (Hg) and trace elements. Over the 12-year period, annual Hg deposition levels at Underhill did not decline significantly despite regulatory efforts to reduce Hg emissions in the United States. Mercury and trace element wet deposition data were examined using the multivariate receptor model EPA PMF 3.0 to identify the sources contributing to Hg deposition at the Underhill site. Results indicate that coal combustion, a mixture of incineration and non-ferrous metal smelting, and a phosphorus source contributed to the observed Hg wet deposition. The model consistently indicated that coal combustion contributed ∼60% of the total Hg measured in wet deposition and the contribution from this source did not change significantly over time. Mercury and trace element deposition were further analyzed using a hybrid-receptor model, quantitative transport bias analysis (QTBA), to identify the likely source locations contributing to Hg deposition. Results from QTBA indicate that the majority of Hg deposition at Underhill is due to transport from the Midwestern United States, where the density of coal-fired utility boilers in the U.S. is largest.

Estimation of source locations of total gaseous mercury measured in New York State using trajectory-based models

Ambient gaseous phase mercury concentrations (TGM) were measured at three locations in NY State including Potsdam, Stockton, and Sterling from May 2000 to March 2005. Using these data, three hybrid receptor models incorporating backward trajectories were used to identify source areas for TGM. The models used were potential source contribution function (PSCF), residence time weighted concentration (RTWC), and simplified quantitative transport bias analysis (SQTBA). Each model was applied using multi-site measurements to resolve the locations of important mercury sources for New York State. PSCF results showed that southeastern New York, Ohio, Indiana, Tennessee, Louisiana, and Virginia were important TGM source areas for these sites. RTWC identified Canadian sources including the metal production facilities in Ontario and Quebec, but US regional sources including the Ohio River Valley were also resolved. Sources in southeastern NY, Massachusetts, western Pennsylvania, Indiana, and northern Illinois were identified to be significant by SQTBA. The three modeling results were combined to locate the most important probable source locations, and those are Ohio, Indiana, Illinois, and Wisconsin. The Atlantic Ocean was suggested to be a possible source as well.

Spatial distribution of source locations for particulate nitrate and sulfate in the upper-midwestern United States

Two back-trajectory analysis methods designed to be used with multiple site data, simplified quantitative transport bias analysis (SQTBA) and residence time weighted concentration (RTWC), were applied to nitrate and sulfate concentration data from two rural sites (the Mammoth Cave National Park and the Great Smoky Mountain National Park) and five urban sites (Chicago, Cleveland, Detroit, Indianapolis, and St. Louis) for an intensive investigation on the spatial patterns of origins for these two species in the upper-midwestern area. The study was made by dividing the data into five categories: all sites and all seasons, rural sites in summer, rural sites in winter, urban sites in summer, and urban sites in winter. A general conclusion was that the origins of the nitrate in these seven sites were mainly in the upper-midwestern areas, while the sulfate in these seven sites were mainly from the Ohio and Tennessee River Valley areas. The upper-midwestern areas are regions of high ammonia emissions rather than high NO x emissions. In the winter, metropolitan areas showed the highest nitrate emission potential suggesting the importance of local NO x emissions. In the summer, ammonia emissions from fertilizer application in the lower midwestern area made a significant contribution to nitrate in the rural sites of this study. The impact of the wind direction prevalence on the source spatial patterns was observed by comparing the urban and rural patterns of the summer. The differences between the results of two methods are discussed and suggestions for applying these methods are also provided.

IDENTIFICATION OF POSSIBLE MERCURY SOURCES AND ESTIMATION OF MERCURY WET DEPOSITION FLUX IN LAKE ONTARIO FROM LAKE ONTARIO ATMOSPHERIC DEPOSITION STUDY (LOADS)

Total gas phase mercury (TGM) concentrations and event wet-only precipitation for Hg were collected for nine months (from April, 2002 to Dec., 2002) at Sterling, NY on the shoreline of Lake Ontario. TGM concentrations measured in this study () were in somewhat high range compared to other background sites. Using simplified quantitative transport bias analysis (SQTBA) possible sources affecting high Hg concentration in Sterling was identified, and they are coal-fired power plants located in southern NY and Pennsylvania. Wet deposition measured at Mercury Deposition Network (MDN) sites including Pt. Petre and Egbert, ON were compared with data obtained at the Sterling to estimate the total mercury wet deposition flux to Lake Ontario. The wet deposition flux was calculated to be the highest at the Sterling site ( from April, 2002 to Dec. 2002) and the lowest at the Egbert (), due to the both the difference in precipitation depth and Hg concentration in the precipitation. The deposition measured at the Sterling site is similar to Lake Michigan deposition of (converted for ninth months) measured for Lake Michigan Mass Balance Study (LMMBS).

Determination of the Source Areas Contributing to Regionally High Warm Season PM2.5 in Eastern North America

An ensemble-trajectory analysis technique known as Quantitative Transport Bias Analysis was applied to determine which geographic areas systematically contributed to above- and below-average fine particle mass (PM2.5) over eastern North America. Six-hour average measurements from 12 rural or suburban locations in eastern North America collected using a tapered element oscillating microbalance were individually associated with corresponding 3-day back-trajectories for the warm seasons (May–September) of 2000 and 2001. Much of the populated areas of northeastern North America were implicated in the build-up of PM2.5 to above-average concentrations. The finer structure of the Quantitative Transport Bias Analysis pattern indicated that transport from the Ohio River Valley, particularly the eastern portion of this area, was most often associated with the highest PM2.5 concentrations. In addition, air masses originating over a relatively large area from southeast Ohio to the western part of Virginia and the western Kentucky to central Tennessee area tended to result in relatively high PM2.5 concentrations over northeastern North America. These observation-based findings were consistent with the spatial distribution of the main sulfur dioxide emissions sources and the major oxides of nitrogen point sources.

Comparison of two trajectory based models for locating particle sources for two rural New York sites

Two back trajectory-based statistical models, simplified quantitative transport bias analysis and residence-time weighted concentrations (RTWC) have been compared for their capabilities of identifying likely locations of source emissions contributing to observed particle concentrations at Potsdam and Stockton, New York. Quantitative transport bias analysis (QTBA) attempts to take into account the distribution of concentrations around the directions of the back trajectories. In full QTBA approach, deposition processes (wet and dry) are also considered. Simplified QTBA omits the consideration of deposition. It is best used with multiple site data. Similarly the RTWC approach uses concentrations measured at different sites along with the back trajectories to distribute the concentration contributions across the spatial domain of the trajectories. In this study, these models are used in combination with the source contribution values obtained by the previous positive matrix factorization analysis of particle composition data from Potsdam and Stockton. The six common sources for the two sites, sulfate, soil, zinc smelter, nitrate, wood smoke and copper smelter were analyzed. The results of the two methods are consistent and locate large and clearly defined sources well. RTWC approach can find more minor sources but may also give unrealistic estimations of the source locations.