Modeling to Evaluate Contribution of Oil and Gas Emissions to Air Pollution

Oil and gas production in the Western United States has increased considerably over the past 10 years. While many of the still limited oil and gas impact assessments have focused on potential human health impacts, the typically remote locations of production in the Intermountain West suggests that the impacts of oil and gas production on national parks and wilderness areas (Class I and II areas) could also be important. To evaluate this, we utilize the Comprehensive Air quality Model with Extensions (CAMx) with a year-long modeling episode representing the best available representation of 2011 meteorology and emissions for the Western United States. The model inputs for the 2011 episodes were generated as part of the Three State Air Quality Study (3SAQS). The study includes a detailed assessment of oil and gas (O&G) emissions in Western States. The year-long modeling episode was run both with and without emissions from O&G production. The difference between these two runs provides an estimate of the contribution of the O&G production to air quality. These data were used to assess the contribution of O&G to the 8 hour average ozone concentrations, daily and annual fine particulate concentrations, annual nitrogen deposition totals and visibility in the modeling domain. We present the results for the Class I and II areas in the Western United States. Modeling results suggest that emissions from O&G activity are having a negative impact on air quality and ecosystem health in our National Parks and Class I areas.

Implications: In this research, we use a modeling framework developed for oil and gas evaluation in the western United States to determine the modeled impacts of emissions associated with oil and gas production on air pollution metrics. We show that oil and gas production may have a significant negative impact on air quality and ecosystem health in some national parks and other Class I areas in the western United States. Our findings are of particular interest to federal land managers as well as regulators in states heavy in oil and gas production as they consider control strategies to reduce the impact of development.     

Updated methods for assessing the impacts of nearby gas drilling and production on neighborhood air quality and human health

An explosive growth in natural gas production within the last decade has fueled concern over the public health impacts of air pollutant emissions from oil and gas sites in the Barnett and Eagle Ford shale regions of Texas. Commonly acknowledged sources of uncertainty are the lack of sustained monitoring of ambient concentrations of pollutants associated with gas mining, poor quantification of their emissions, and inability to correlate health symptoms with specific emission events. These uncertainties are best addressed not by conventional monitoring and modeling technology, but by increasingly available advanced techniques for real-time mobile monitoring, microscale modeling and source attribution, and real-time broadcasting of air quality and human health data over the World Wide Web. The combination of contemporary scientific and social media approaches can be used to develop a strategy to detect and quantify emission events from oil and gas facilities, alert nearby residents of these events, and collect associated human health data, all in real time or near-real time. The various technical elements of this strategy are demonstrated based on the results of past, current, and planned future monitoring studies in the Barnett and Eagle Ford shale regions.

Implications: Resources should not be invested in expanding the conventional air quality monitoring network in the vicinity of oil and gas exploration and production sites. Rather, more contemporary monitoring and data analysis techniques should take the place of older methods to better protect the health of nearby residents and maintain the integrity of the surrounding environment.     

Investigating the real-world emission characteristics of light-duty gasoline vehicles and their relationship to local socioeconomic conditions in three communities in Los Angeles,California

This paper discusses results from a vehicular emissions research study of over 350 vehicles conducted in three communities in Los Angeles, CA, in 2010 using vehicle chase measurements. The study explores the real-world emission behavior of light-duty gasoline vehicles, characterizes real-world super-emitters in the different regions, and investigates the relationship of on-road vehicle emissions with the socioeconomic status (SES) of the region. The study found that in comparison to a 2007 earlier study in a neighboring community, vehicle emissions for all measured pollutants had experienced a significant reduction over the years, with oxides of nitrogen (NO_X) and black carbon (BC) emissions showing the largest reductions. Mean emission factors of the sampled vehicles in low-SES communities were roughly 2–3 times higher for NO_X, BC, carbon monoxide, and ultrafine particles, and 4–11 times greater for fine particulate matter (PM_2.5) than for vehicles in the high-SES neighborhood. Further analysis indicated that the emission factors of vehicles within a technology group were also higher in low-SES communities compared to similar vehicles in the high-SES community, suggesting that vehicle age alone did not explain the higher vehicular emission in low-SES communities.

Evaluation of the emission factor distribution found that emissions from 12% of the sampled vehicles were greater than five times the mean from all of the sampled fleet, and these vehicles were consequently categorized as “real-world super-emitters.” Low-SES communities had approximately twice as many super-emitters for most of the pollutants as compared to the high-SES community. Vehicle emissions calculated using model-year-specific average fuel consumption assumptions suggested that approximately 5% of the sampled vehicles accounted for nearly half of the total CO, PM_2.5, and UFP emissions, and 15% of the vehicles were responsible for more than half of the total NO_X and BC emissions from the vehicles sampled during the study.

Implications: This study evaluated the real-world emission behavior and super-emitter distribution of light-duty gasoline vehicles in California, and investigated the relationship of on-road vehicle emissions with local socioeconomic conditions. The study observed a significant reduction in vehicle emissions for all measured pollutants when compared to an earlier study in Wilmington, CA, and found a higher prevalence of high-emitting vehicles in low-socioeconomic-status communities. As overall fleet emissions decrease from stringent vehicle emission regulations, a small fraction of the fleet may contribute to a disproportionate share of the overall on-road vehicle emissions. Therefore, this work will have important implications for improving air quality and public health, especially in low-SES communities.     

Power models and average ship parameter effects on marine emissions inventories

Maritime greenhouse gas emissions are projected to increase significantly by 2050, highlighting the need for reliable inventories as a first step in analyzing ship emission control policies. The impact of ship power models on marine emissions inventories has garnered little attention, with most inventories employing simple, load-factor-based models to estimate ship power consumption. The availability of more expansive ship activity data provides the opportunity to investigate the inventory impacts of adopting complex power models. Furthermore, ship parameter fields can be sparsely populated in ship registries, making gap-filling techniques and averaging processes necessary. Therefore, it is important to understand of the impact of averaged ship parameters on ship power and emission estimations. This paper examines power estimation differences between results from two complex, resistance-based and two simple, load-factor-based power models on a baseline inventory with unique ship parameters. These models are additionally analyzed according to their sensitivities toward average ship parameters. Automated Identification System (AIS) data from a fleet of commercial marine vessels operating over a 6-month period off the coast of the southwestern United States form the basis of the analysis. To assess the inventory impacts of using averaged ship parameters, fleet-level carbon dioxide (CO₂) emissions are calculated using ship parameter data averaged across ship types and their subtype size classes. Each of the four ship power models are used to generate four CO₂ emissions inventories, and results are compared with baseline estimates for the same sample fleet where no averaged values were used. The results suggest that a change in power model has a relatively high impact on emission estimates. They also indicate relatively little sensitivity, by all power models, to the use of ship characteristics averaged by ship and subtype.

Implications: Commercial marine vessel emissions inventories were calculated using four different models for ship engine power. The calculations used 6 months of Automated Identification System (AIS) data from a sample of 248 vessels as input data. The results show that more detailed, resistance-based models tend to estimate a lower propulsive power, and thus lower emissions, for ships than traditional load-factor-based models. Additionally, it was observed that emission calculations using averaged values for physical ship parameters had a minimal impact on the resulting emissions inventories.     

Spatiotemporal analysis of traffic emissions in over 5000 municipal districts in Brazil

Exposure to traffic emission is harmful to human health. Emission inventories are essential to public health policies aiming at protecting human health, especially in areas with incomplete or nonexistent air pollution monitoring networks. In Brazil, for example, only 1.7% of municipal districts have a monitoring network, and only a few studies have reported data on vehicle emission inventories. No studies have presented emission inventories by municipality. In this study, we predicted vehicular emissions for 5570 municipal districts in Brazil during the period 2001–2012. We used a top-down method to estimate emissions. Carbon dioxide (CO₂) is the pollutant with the highest emissions, with approximately 190 million tons per year during the period 2001–2012). For the other traffic-related pollutants, we predicted annual emissions of 1.5 million tons for carbon monoxide (CO), 1.2 million tons of nitrogen oxides (NO_x), 209,000 tons of nonmethane hydrocarbons (NMHC), 58,000 tons of particulate matter (PM), and 42,000 tons for methane (CH₄). From 2001 to 2012, CO, NMHC, and PM emissions decreased by 41, 33, and 47%, respectively, whereas those CH₄, NO_x, and CO₂ increased by 2, 4, and 84%, respectively. We estimated uncertainties in our study and found that NO_x was the pollutant with the lowest percentage difference, 8%, and NMHC with the highest one, 30%. For CO, CH₄, CO₂, and PM, the values were 22, 14, 21, and 20%, respectively. Finally, we found that during 2001 and 2012 emissions increased in the Northwest and Northeast. In contrast, pollutant emissions, except for CO₂, decreased in the Southeast, South, and part of Midwest. Our predictions can be critical to efforts developing cost-effective public policies tailored to individual municipal districts in Brazil.

Implications: Emission inventories may be an alternative approach to provide data for air quality forecasting in areas where air quality data are not available. This approach can be an effective tool in developing spatially resolved emission inventories.     

Spatial surrogate for domestic combustion’s air emissions: A case study from Silesian Metropolis,Poland

The aim of this study is improving currently applied methodology for spatial disaggregation, as well as mapping air emission inventories by taking into account the auxiliary spatial data on population density. District heating infrastructure occurring in more populated areas changes distinctly the spatial distribution of estimated air emission; however, it does not change the initial estimate. That means the total, disaggregated value is constant. Considered sources of domestic combustion are located in the central part of the Silesian Metropolis, in the southern part of Poland. A large part of this area is strongly urbanized and supplied with heat (hot water) from the district heating system. Data on population density help to determine the area within which the dwellers use heat energy and hot water supplied by the heating infrastructure, apart from heating with small domestic boilers and stoves. This causes the domestic combustion’s emission impact within the distinguished area to be significantly lower in comparison to the official guidelines on air emission inventories. The important differences in spatial air emissions distributions calculated using a top-down approach are found for strongly urbanized areas supplied partly with heat and hot water from the district heating network. This fact should be taken into account when preparing detailed, high-resolution emission inventories for air regional and local quality modeling.

Implications: The spatial issues connected with elaboration of the high-resolution emission inventories are presented for the example of the populated area of the Silesian Metropolis (Poland). Spatial distribution of the population density is used to determine the area supplied with heat and hot water from the district heating system. It changes distinctly the spatial distribution of the air emission from small residential combustion sources.     

Freight shipment modal split and its environmental impacts: An exploratory study

Freight transportation activities are responsible for a large share of air pollution and greenhouse gas emissions in the United States. Various freight transportation modes have significantly different impacts on air quality and environmental sustainability, and this highlights the need for a better understanding of interregional freight shipment mode choices. This paper develops a binomial logit market share model to predict interregional freight modal share between truck and rail as a function of freight and shipment characteristics. This model can be used to estimate the impacts of various factors, such as oil price, on shippers’ mode choice decisions. A set of multiyear freight and geographical information databases was integrated to construct regression models for typical freight commodities. The atmospheric impact levels incurred by different freight modal choice decisions are analyzed to provide insights on the relationship among freight modal split, oil price change, and air quality.

Implications:

Freight transportation has become a major source of energy consumption and air pollution, and emissions rates vary significantly across different modes. Understanding freight shipment mode choice under various economic and engineering factors will help assess the environmental impacts of freight shipment systems at the national level. This paper develops a binomial logit model for two dominating modes (truck and rail) and shows how this model is incorporated into an environmental impact analysis. The framework will be useful to policy makers to assess the impacts of freight movements on air quality and public health and to mitigate those adverse impacts.     

Trends in onroad transportation energy and emissions

Globally, 1.3 billion on-road vehicles consume 79 quadrillion BTU of energy, mostly gasoline and diesel fuels, emit 5.7 gigatonnes of CO₂, and emit other pollutants to which approximately 200,000 annual premature deaths are attributed. Improved vehicle energy efficiency and emission controls have helped offset growth in vehicle activity. New technologies are diffusing into the vehicle fleet in response to fuel efficiency and emission standards. Empirical assessment of vehicle emissions is challenging because of myriad fuels and technologies, intervehicle variability, multiple emission processes, variability in operating conditions, and varying capabilities of measurement methods. Fuel economy and emissions regulations have been effective in reducing total emissions of key pollutants. Real-world fuel use and emissions are consistent with official values in the United States but not in Europe or countries that adopt European standards. Portable emission measurements systems, which uncovered a recent emissions cheating scandal, have a key role in regulatory programs to ensure conformity between “real driving emissions” and emission standards. The global vehicle fleet will experience tremendous growth, especially in Asia. Although existing data and modeling tools are useful, they are often based on convenience samples, small sample sizes, large variability, and unquantified uncertainty. Vehicles emit precursors to several important secondary pollutants, including ozone and secondary organic aerosols, which requires a multipollutant emissions and air quality management strategy. Gasoline and diesel are likely to persist as key energy sources to mid-century. Adoption of electric vehicles is not a panacea with regard to greenhouse gas emissions unless coupled with policies to change the power generation mix. Depending on how they are actually implemented and used, autonomous vehicles could lead to very large reductions or increases in energy consumption. Numerous other trends are addressed with regard to technology, emissions controls, vehicle operations, emission measurements, impacts on exposure, and impacts on public health.

Implications: Without specific policies to the contrary, fossil fuels are likely to continue to be the major source of on-road vehicle energy consumption. Fuel economy and emission standards are generally effective in achieving reductions per unit of vehicle activity. However, the number of vehicles and miles traveled will increase. Total energy use and emissions depend on factors such as fuels, technologies, land use, demographics, economics, road design, vehicle operation, societal values, and others that affect demand for transportation, mode choice, energy use, and emissions. Thus, there are many opportunities to influence future trends in vehicle energy use and emissions.     

Autonomous mobile platform for monitoring air emissions from industrial and municipal wastewater ponds

Significant amounts of volatile organic compounds and greenhouse gases are generated from wastewater lagoons and tailings ponds in Alberta, Canada. Accurate measurements of these air pollutants and greenhouse gases are needed to support management and regulatory decisions. A mobile platform was developed to measure air emissions from tailings pond in the oil sands region of Alberta. The mobile platform was tested in 2015 in a municipal wastewater treatment lagoon. With a flux chamber and a CO₂/CH₄ sensor on board, the mobile platform was able to measure CO₂ and CH₄ emissions over two days at two different locations in the pond. Flux emission rates of CO₂ and CH₄ that were measured over the study period suggest the presence of aerobic and anaerobic zones in the wastewater treatment lagoon. The study demonstrated the capabilities of the mobile platform in measuring fugitive air emissions and identified the potential for the applications in air and water quality monitoring programs.

Implications: The Mobile Platform demonstrated in this study has the ability to measure greenhouse gas (GHG) emissions from fugitive sources such as municipal wastewater lagoons. This technology can be used to measure emission fluxes from tailings ponds with better detection of spatial and temporal variations of fugitive emissions. Additional air and water sampling equipment could be added to the mobile platform for a broad range of air and water quality studies in the oil sands region of Alberta.     

An exploratory study of air emissions associated with shale gas development and production in the Barnett Shale

Information regarding air emissions from shale gas extraction and production is critically important given production is occurring in highly urbanized areas across the United States. Objectives of this exploratory study were to collect ambient air samples in residential areas within 61 m (200 feet) of shale gas extraction/production and determine whether a “fingerprint” of chemicals can be associated with shale gas activity. Statistical analyses correlating fingerprint chemicals with methane, equipment, and processes of extraction/production were performed. Ambient air sampling in residential areas of shale gas extraction and production was conducted at six counties in the Dallas/Fort Worth (DFW) Metroplex from 2008 to 2010. The 39 locations tested were identified by clients that requested monitoring. Seven sites were sampled on 2 days (typically months later in another season), and two sites were sampled on 3 days, resulting in 50 sets of monitoring data. Twenty-four-hour passive samples were collected using summa canisters. Gas chromatography/mass spectrometer analysis was used to identify organic compounds present. Methane was present in concentrations above laboratory detection limits in 49 out of 50 sampling data sets. Most of the areas investigated had atmospheric methane concentrations considerably higher than reported urban background concentrations (1.8–2.0 ppm_v). Other chemical constituents were found to be correlated with presence of methane. A principal components analysis (PCA) identified multivariate patterns of concentrations that potentially constitute signatures of emissions from different phases of operation at natural gas sites. The first factor identified through the PCA proved most informative. Extreme negative values were strongly and statistically associated with the presence of compressors at sample sites. The seven chemicals strongly associated with this factor (o-xylene, ethylbenzene, 1,2,4-trimethylbenzene, m- and p-xylene, 1,3,5-trimethylbenzene, toluene, and benzene) thus constitute a potential fingerprint of emissions associated with compression.

Implications: Information regarding air emissions from shale gas development and production is critically important given production is now occurring in highly urbanized areas across the United States. Methane, the primary shale gas constituent, contributes substantially to climate change; other natural gas constituents are known to have adverse health effects. This study goes beyond previous Barnett Shale field studies by encompassing a wider variety of production equipment (wells, tanks, compressors, and separators) and a wider geographical region. The principal components analysis, unique to this study, provides valuable information regarding the ability to anticipate associated shale gas chemical constituents.     

Future-year ozone prediction for the United States using updated models and inputs

The relationship between emission reductions and changes in ozone can be studied using photochemical grid models. These models are updated with new information as it becomes available. The primary objective of this study was to update the previous Collet et al. studies by using the most up-to-date (at the time the study was done) modeling emission tools, inventories, and meteorology available to conduct ozone source attribution and sensitivity studies. Results show future-year, 2030, design values for 8-hr ozone concentrations were lower than base-year values, 2011. The ozone source attribution results for selected cities showed that boundary conditions were the dominant contributors to ozone concentrations at the western U.S. locations, and were important for many of the eastern U.S. locations. Point sources were generally more important in the eastern United States than in the western United States. The contributions of on-road mobile emissions were less than 5 ppb at a majority of the cities selected for analysis. The higher-order decoupled direct method (HDDM) results showed that in most of the locations selected for analysis, NOx emission reductions were more effective than VOC emission reductions in reducing ozone levels. The source attribution results from this study provide useful information on the important source categories and provide some initial guidance on future emission reduction strategies.

Implications: The relationship between emission reductions and changes in ozone can be studied using photochemical grid models, which are updated with new available information. This study was to update the previous Collet et al. studies by using the most current, at the time the study was done, models and inventory to conduct ozone source attribution and sensitivity studies. The source attribution results from this study provide useful information on the important source categories and provide some initial guidance on future emission reduction strategies.     

Air pollutant emissions from the development,production, and processing of Marcellus Shale natural gas

The Marcellus Shale is one of the largest natural gas reserves in the United States; it has recently been the focus of intense drilling and leasing activity. This paper describes an air emissions inventory for the development, production, and processing of natural gas in the Marcellus Shale region for 2009 and 2020. It includes estimates of the emissions of oxides of nitrogen (NO_x), volatile organic compounds (VOCs), and primary fine particulate matter (≤2.5 µm aerodynamic diameter; PM_2.5) from major activities such as drilling, hydraulic fracturing, compressor stations, and completion venting. The inventory is constructed using a process-level approach; a Monte Carlo analysis is used to explicitly account for the uncertainty. Emissions were estimated for 2009 and projected to 2020, accounting for the effects of existing and potential additional regulations. In 2020, Marcellus activities are predicted to contribute 6–18% (95% confidence interval) of the NO_x emissions in the Marcellus region, with an average contribution of 12% (129 tons/day). In 2020, the predicted contribution of Marcellus activities to the regional anthropogenic VOC emissions ranged between 7% and 28% (95% confidence interval), with an average contribution of 12% (100 tons/day). These estimates account for the implementation of recently promulgated regulations such as the Tier 4 off-road diesel engine regulation and the U.S. Environmental Protection Agency's (EPA) Oil and Gas Rule. These regulations significantly reduce the Marcellus VOC and NO_x emissions, but there are significant opportunities for further reduction in these emissions using existing technologies.

Implications: The Marcellus Shale is one of the largest natural gas reserves in United States. The development and production of this gas may emit substantial amounts of oxides of nitrogen and volatile organic compounds. These emissions may have special significance because Marcellus development is occurring close to areas that have been designated nonattainment for the ozone standard. Control technologies exist to substantially reduce these impacts. PM_2.5 emissions are predicted to be negligible in a regional context, but elemental carbon emissions from diesel powered equipment may be important.     

Emissions of organic compounds from produced water ponds II: Evaluation of flux chamber measurements with inverse-modeling techniques

In this study, the authors apply two different dispersion models to evaluate flux chamber measurements of emissions of 58 organic compounds, including C2–C11 hydrocarbons and methanol, ethanol, and isopropanol from oil- and gas-produced water ponds in the Uintah Basin. Field measurement campaigns using the flux chamber technique were performed at a limited number of produced water ponds in the basin throughout 2013–2016. Inverse-modeling results showed significantly higher emissions than were measured by the flux chamber. Discrepancies between the two methods vary across hydrocarbon compounds and are largest in alcohols due to their physical chemistries. This finding, in combination with findings in a related study using the WATER9 wastewater emission model, suggests that the flux chamber technique may underestimate organic compound emissions, especially alcohols, due to its limited coverage of the pond area and alteration of environmental conditions, especially wind speed. Comparisons of inverse-model estimations with flux chamber measurements varied significantly with the complexity of pond facilities and geometries. Both model results and flux chamber measurements suggest significant contributions from produced water ponds to total organic compound emission from oil and gas productions in the basin.

Implications: This research is a component of an extensive study that showed significant amount of hydrocarbon emissions from produced water ponds in the Uintah Basin, Utah. Such findings have important meanings to air quality management agencies in developing control strategies for air pollution in oil and gas fields, especially for the Uintah Basin in which ozone pollutions frequently occurred in winter seasons.     

A survey of valleys and basins of the western United States for the capacity to produce winter ozone

High winter ozone in the Uintah Basin, Utah, and the Upper Green River Basin, Wyoming, occurs because of the confluence of three separate factors: (1) extensive oil or natural gas production, (2) topography conducive to strong multiple-day thermal inversions, and (3) snow cover. We surveyed 13 basins and valleys in the western United States for the existence and magnitude of these factors. Seven of the basins, because winter ozone measurements were available, were assigned to four different behavioral classes. Based on similarities among the basins, the remaining six were also given a tentative assignment. Two classes (1 and 2) correspond to basins with high ozone because all three factors just listed are present at sufficient magnitude. Class 3 corresponds to rural basins with ozone at background levels, and occurs because at least one of the three factors is weak or absent. Class 4 corresponds to ozone below background levels, and occurs, for example, in urban basins where emissions scavenge ozone. All three factors are present in the Wind River Basin, Wyoming, but compared to the Uintah or the Upper Green Basins, it has only moderate oil and gas production and is assigned to class 3. We predict that the Wind River Basin, as well as other class 3 basins that have inversions and snow cover, would transition from background (class 3) to high ozone behavior (class 1 or 2) if oil or gas production were to intensify, or to class 4 (low winter ozone) if they were to become urban.

Implications: High ozone concentrations in winter only occur in basins or valleys that have an active oil and natural gas production industry, multiple-day thermal inversions, and snow cover, and have only been documented in two basins worldwide. We have examined a number of other candidate basins in the western United States and conclude that these factors are either absent or too weak to produce high winter ozone. This study illustrates how strong each factor needs to be before winter ozone can be expected, and can be used by planners and regulators to foresee the development of winter ozone problems.     

Modeling emissions for three-dimensional atmospheric chemistry transport models

Poor air quality is still a threat for human health in many parts of the world. In order to assess measures for emission reductions and improved air quality, three-dimensional atmospheric chemistry transport modeling systems are used in numerous research institutions and public authorities. These models need accurate emission data in appropriate spatial and temporal resolution as input. This paper reviews the most widely used emission inventories on global and regional scales and looks into the methods used to make the inventory data model ready. Shortcomings of using standard temporal profiles for each emission sector are discussed, and new methods to improve the spatiotemporal distribution of the emissions are presented. These methods are often neither top-down nor bottom-up approaches but can be seen as hybrid methods that use detailed information about the emission process to derive spatially varying temporal emission profiles. These profiles are subsequently used to distribute bulk emissions such as national totals on appropriate grids. The wide area of natural emissions is also summarized, and the calculation methods are described. Almost all types of natural emissions depend on meteorological information, which is why they are highly variable in time and space and frequently calculated within the chemistry transport models themselves. The paper closes with an outlook for new ways to improve model ready emission data, for example, by using external databases about road traffic flow or satellite data to determine actual land use or leaf area. In a world where emission patterns change rapidly, it seems appropriate to use new types of statistical and observational data to create detailed emission data sets and keep emission inventories up-to-date.

Implications: Emission data are probably the most important input for chemistry transport model (CTM) systems. They need to be provided in high spatial and temporal resolution and on a grid that is in agreement with the CTM grid. Simple methods to distribute the emissions in time and space need to be replaced by sophisticated emission models in order to improve the CTM results. New methods, e.g., for ammonia emissions, provide grid cell–dependent temporal profiles. In the future, large data fields from traffic observations or satellite observations could be used for more detailed emission data.     

Evaluation of gas well setback policy in the Marcellus Shale region of Pennsylvania in relation to emissions of fine particulate matter

Shale gas has become an important strategic energy source with considerable potential economic benefits and the potential to reduce greenhouse gas emissions in so far as it displaces coal use. However, there still exist environmental health risks caused by emissions from exploration and production activities. In the United States, states and localities have set different minimum setback policies to reduce the health risks corresponding to the emissions from these locations, but it is unclear whether these policies are sufficient. This study uses a Gaussian plume model to evaluate the probability of exposure exceedance from EPA concentration limits for PM2.5 at various locations around a generic wellsite in the Marcellus shale region. A set of meteorological data monitored at ten different stations across Marcellus shale gas region in Pennsylvania during 2015 serves as an input to this model. Results indicate that even though the current setback distance policy in Pennsylvania (500 ft. or 152.4 m) might be effective in some cases, exposure limit exceedance occurs frequently at this distance with higher than average emission rates and/or greater number of wells per wellpad. Setback distances should be 736 m to ensure compliance with the daily average concentration of PM2.5, and a function of the number of wells to comply with the annual average PM2.5 exposure standard.

Implications: The Marcellus Shale gas is known as a significant source of criteria pollutants and studies show that the current setback distance in Pennsylvania is not adequate to protect the residents from exceeding the established limits. Even an effective setback distance to meet the annual exposure limit may not be adequate to meet the daily limit. The probability of exceeding the annual limit increases with number of wells per site. We use a probabilistic dispersion model to introduce a technical basis to select appropriate setback distances.     

Total life cycle emissions of post-Panamax containerships powered by conventional fuel or natural gas

This study proposes an easy-to-apply method, the Total Life Cycle Emission Model (TLCEM), to calculate the total emissions from shipping and help ship management groups assess the impact on emissions caused by their capital investment or operation decisions. Using TLCEM, we present the total emissions of air pollutants and greenhouse gases (GHGs) during the 25-yr life cycle of 10 post-Panamax containerships under slow steaming conditions. The life cycle consists of steel production, shipbuilding, crude oil extraction and transportation, fuel refining, bunkering, and ship operation. We calculate total emissions from containerships and compare the effect of emission reduction by using various fuels. The results can be used to differentiate the emissions from various processes and to assess the effectiveness of various reduction approaches. Critical pollutants and GHGs emitted from each process are calculated. If the containerships use heavy fuel oil (HFO), emissions of CO₂ total 2.79 million tonnes (Mt), accounting for 95.37% of total emissions, followed by NO_x and SO_x emissions,which account for 2.25% and 1.30%, respectively.The most significant emissions are from the operation of the ship and originate from the main engine (ME).When fuel is switched to 100% natural gas (NG), SO_x, PM₁₀, and CO₂ emissions show remarkable reductions of 98.60%, 99.06%, and 21.70%, respectively. Determining the emission factor of each process is critical for estimating the total emissions. The estimated emission factors were compared with the values adopted by the International Maritime Organization (IMO).The proposed TLCEM may contribute to more accurate estimates of total life cycle emissions from global shipping.

Implications: We propose a total life cycle emissions model for 10 post-Panamax container ships. Using heavy fuel oil, emissions of CO₂ total 2.79 Mt, accounting for approximately 95% of emissions, followed by NO_x and SO_x emissions. Using 100% natural gas, SO_x, PM₁₀, and CO₂ emissions reduce by 98.6%, 99.1%, and 21.7%, respectively. NO_x emissions increase by 1.14% when running a dual fuel engine at low load in natural gas mode.     

The air quality forecast rote: Recent changes and future challenges

Air quality forecasting is a recent development, with most programs initiated only in the last 20 years. During the last decade, forecast preparation procedure—the forecast rote—has changed dramatically. This paper summarizes the unique challenges posed by air quality forecasting, details the current forecast rote, and analyzes prospects for future improvements. Because air quality forecasts must diagnose and predict several pollutants and their precursors in addition to standard meteorological variables, it is, compared with weather forecasts, a higher-uncertainty forecast. Forecasters seek to contain the uncertainty by “anchoring” the forecast, using an a priori field, and then “adjusting” the forecast using additional information. The air quality a priori, or first guess, field is a blend of past, current, and near-term future observations of the pollutants of interest, on both local and regional scales, and is typically coupled with predicted air parcel trajectories. Until recently, statistical methods, based on long-term training data sets, were used to adjust the first guess. However, reductions in precursor emissions in the United States, beginning in the late 1990s and continuing to the present, eroded the stationarity assumption for the training data sets and degraded forecast skill. Beginning in the mid-2000s, output from modified numerical air quality prediction (NAQP) models, originally developed to test pollution control strategies, became available in near real time for forecast support. The current adjustment process begins with the analyses and postprocessing of individual NAQP models and their ad hoc ensembles, often in concert with new statistical techniques. The final adjustment step uses forecaster expertise to assess the impact of mesoscale features not resolved by the NAQP models. It is expected that advances in model resolution, chemical data assimilation, and the formulation of emissions fields will improve mesoscale predictions by NAQP models and drive future changes in the forecast rote.

Implications: Routine air quality forecasts are now issued for nearly all the major U.S. metropolitan areas. Methods of forecast preparation—the forecast rote—have changed significantly in the last decade. Numerical air quality models have matured and are now an indispensable part of the forecasting process. All forecasting methods, particularly statistically based models, must be continually calibrated to account for ongoing local- and regional-scale emission reductions.     

Investigation of the influence of transport from oil and natural gas regions on elevated ozone levels in the northern Colorado front range

The Northern Colorado Front Range (NCFR) has been in exceedance of the ozone National Ambient Air Quality Standard (NAAQS) since 2004, which has led to much debate over the sources of ozone precursors to the region, as this area is home to both the Denver, CO, metropolitan area and the Denver–Julesburg Basin, which has experienced rapid growth of oil and natural gas (O&NG) operations and associated emissions. Several recent studies have reported elevated levels of atmospheric volatile organic compounds (VOCs) as a result of O&NG emissions and the potential for significant ozone production from these emissions, despite implementation of stricter O&NG VOC emissions regulations in 2008. Approximately 88% of 1-hr elevated ozone events (>75 ppbv) occur during June–August, indicating that elevated ozone levels are driven by regional photochemistry. Analyses of surface ozone and wind observations from two sites, namely, South Boulder and the Boulder Atmospheric Observatory, both near Boulder, CO, show a preponderance of elevated ozone events associated with east-to-west airflow from regions with O&NG operations in the N-ESE, and a relatively minor contribution of transport from the Denver Metropolitan area to the SE-S. Transport from upwind areas associated with abundant O&NG operations accounts for on the order of 65% (mean for both sites) of 1-hr averaged elevated ozone levels, while the Denver urban corridor accounts for 9%. These correlations contribute to mounting evidence that air transport from areas with O&NG operation has a significant impact on ozone and air quality in the NCFR.

Implications: This article builds on several previous pieces of research that implied significant contributions from oil and natural gas emissions on ozone production in the Northern Colorado Front Range. By correlating increased ozone events with transport analyses we show that there is a high abundance of transport events with elevated ozone originating from the Denver–Julesburg oil and natural gas basin. These findings will help air quality regulators to better assess contributing sources to ozone production and in directing policies to curb ozone pollution in this region.     

Characterization of methane emissions from five cold heavy oil production with sands (CHOPS) facilities

Cold heavy oil production with sands (CHOPS) is a common oil extraction method in the Canadian provinces of Alberta and Saskatchewan that can result in significant methane emissions due to annular venting. Little is known about the magnitude of these emissions, nor their contributions to the regional methane budget. Here the authors present the results of field measurements of methane emissions from CHOPS wells and compare them with self-reported venting rates. The tracer ratio method was used not only to analyze total site emissions but at one site it was also used to locate primary emission sources and quantify their contributions to the facility-wide emission rate, revealing the annular vent to be a dominant source. Emissions measured from five different CHOPS sites in Alberta showed large discrepancies between the measured and reported rates, with emissions being mainly underreported. These methane emission rates are placed in the context of current reporting procedures and the role that gas-oil ratio (GOR) measurements play in vented volume estimates. In addition to methane, emissions of higher hydrocarbons were also measured; a chemical “fingerprint” associated with CHOPS wells in this region reveals very low emission ratios of ethane, propane, and aromatics versus methane. The results of this study may inform future studies of CHOPS sites and aid in developing policy to mitigate regional methane emissions.

Implications: Methane measurements from cold heavy oil production with sand (CHOPS) sites identify annular venting to be a potentially major source of emissions at these facilities. The measured emission rates are generally larger than reported by operators, with uncertainty in the gas-oil ratio (GOR) possibly playing a large role in this discrepancy. These results have potential policy implications for reducing methane emissions in Alberta in order to achieve the Canadian government’s goal of reducing methane emissions by 40–45% below 2012 levels within 8 yr.