Emission Data Product Research Articles

Exploring differences in FFCO2 emissions in the United States: comparison of the Vulcan data product and the EPA national GHG inventory

Quantitative assessment of greenhouse gas emissions is an essential step to plan, track, and verify emission reductions. Multiple approaches have been taken to quantify U.S. CO2 emissions from fossil fuel combustion (FFCO2), the primary driver of global climate change. A 2020 study analyzing atmospheric 14CO2 observations (a key check on bottom-up estimates) and multiple inventories found significant differences in the U.S. total FFCO2 emissions. The specific reasons for the differences were left for future work. Here, we take up this task and explore the differences between two widely used U.S. FFCO2 inventories, the Vulcan FFCO2 emissions data product and the Environmental Protection Agency (EPA) GHG inventory, developed using mostly independent data sources. Where possible, we isolate definitions and data sources to quantify/understand discrepancies. We find that the initial 2011 emissions difference (104 MtC yr−1; RD = 10.7%) can be reduced by aligning the two estimates to account for differing definitions of emission categories or system boundaries. Out of the remaining 90.6 MtC yr−1 gap (RD = 6.2%), we find that differences can be largely explained by data completeness, emission factors, and fuel heating values. The remaining difference, 45.4 MtC yr−1 (3.2%), is difficult to isolate due to limited EPA documentation and disaggregation of emissions by sector/fuel categories. Furthermore, the final net difference obscures countervailing gross differences (∼40 MtC yr−1) within individual sectors. Nevertheless, this comparison suggests the potential for a national estimation approach that can simultaneously satisfy reporting at the national/global scale and the local scale, maintaining internal consistency throughout and offering detailed decision support to a much wider array of stakeholders.

Mahuika‐Auckland: A spatially and temporally resolved fossil fuel CO2 emissions data product for Auckland, New Zealand

AbstractAccurate, high‐resolution and sector‐specific greenhouse gas emissions information is increasingly needed for the development of local, targeted mitigation policies. We describe a detailed, spatially and temporally resolved CO2 emissions data product, Mahuika‐Auckland, for Auckland, New Zealand, based on Auckland's regional greenhouse gas and air emissions inventories. Emissions are provided at 500 m spatial resolution and at a 1‐hr time step, a level of detail not previously available for any New Zealand city. We divide fossil fuel emissions into six sectors that comprise the majority of Auckland Region's CO2 emissions profile: on‐road transport, industrial non‐point buildings and point sources, commercial non‐point buildings, residential non‐point buildings, air transport and sea transport. We also include separate layers representing biogenic CO2 emissions (primarily waste and wood burning), as these are significant sources in Auckland. We distribute emissions spatially and temporally based on activity data, energy and fuel consumption patterns, and population statistics. The code to generate Mahuika‐Auckland has been designed to be flexible so that updated information and/or data from more recent years can easily be incorporated. This data product improves upon New Zealand's current inventories that are only resolved at the regional and annual scale, providing a new level of detail that can be used as a prior estimate for atmospheric inversions, to inform emissions reduction policies and to guide the development of zero carbon pathways.

Under-reporting of greenhouse gas emissions in U.S. cities

Cities dominate greenhouse gas emissions. Many have generated self-reported emission inventories, but their value to emissions mitigation depends on their accuracy, which remains untested. Here, we compare self-reported inventories from 48 US cities to independent estimates from the Vulcan carbon dioxide emissions data product, which is consistent with atmospheric measurements. We found that cities under-report their own greenhouse gas emissions, on average, by 18.3% (range: −145.5% to +63.5%) – a difference which if extrapolated to all U.S. cities, exceeds California’s total emissions by 23.5%. Differences arise because city inventories omit particular fuels and source types and estimate transportation emissions differently. These results raise concerns about self-reported inventories in planning or assessing emissions, and warrant consideration of the new urban greenhouse gas information system recently developed by the scientific community.

Informing urban climate planning with high resolution data: the Hestia fossil fuel CO2 emissions for Baltimore, Maryland

BackgroundCities contribute more than 70% of global anthropogenic carbon dioxide (CO2) emissions and are leading the effort to reduce greenhouse gas (GHG) emissions through sustainable planning and development. However, urban greenhouse gas mitigation often relies on self-reported emissions estimates that may be incomplete and unverifiable via atmospheric monitoring of GHGs. We present the Hestia Scope 1 fossil fuel CO2 (FFCO2) emissions for the city of Baltimore, Maryland—a gridded annual and hourly emissions data product for 2010 through 2015 (Hestia-Baltimore v1.6). We also compare the Hestia-Baltimore emissions to overlapping Scope 1 FFCO2 emissions in Baltimore’s self-reported inventory for 2014.ResultsThe Hestia-Baltimore emissions in 2014 totaled 1487.3 kt C (95% confidence interval of 1158.9–1944.9 kt C), with the largest emissions coming from onroad (34.2% of total city emissions), commercial (19.9%), residential (19.0%), and industrial (11.8%) sectors. Scope 1 electricity production and marine shipping were each generally less than 10% of the city’s total emissions. Baltimore’s self-reported Scope 1 FFCO2 emissions included onroad, natural gas consumption in buildings, and some electricity generating facilities within city limits. The self-reported Scope 1 FFCO2 total of 1182.6 kt C was similar to the sum of matching emission sectors and fuels in Hestia-Baltimore v1.6. However, 20.5% of Hestia-Baltimore’s emissions were in sectors and fuels that were not included in the self-reported inventory. Petroleum use in buildings were omitted and all Scope 1 emissions from industrial point sources, marine shipping, nonroad vehicles, rail, and aircraft were categorically excluded.ConclusionsThe omission of petroleum combustion in buildings and categorical exclusions of several sectors resulted in an underestimate of total Scope 1 FFCO2 emissions in Baltimore’s self-reported inventory. Accurate Scope 1 FFCO2 emissions, along with Scope 2 and 3 emissions, are needed to inform effective urban policymaking for system-wide GHG mitigation. We emphasize the need for comprehensive Scope 1 emissions estimates for emissions verification and measuring progress towards Scope 1 GHG mitigation goals using atmospheric monitoring.

The Vulcan Version 3.0 High-Resolution Fossil Fuel CO2 Emissions for the United States.

Estimates of high‐resolution greenhouse gas (GHG) emissions have become a critical component of climate change research and an aid to decision makers considering GHG mitigation opportunities. The “Vulcan Project” is an effort to estimate bottom‐up carbon dioxide emissions from fossil fuel combustion and cement production (FFCO2) for the U.S. landscape at space and time scales that satisfy both scientific and policy needs. Here, we report on the Vulcan version 3.0 which quantifies emissions at a resolution of 1 km2/hr for the 2010–2015 time period. We estimate 2011 FFCO2 emissions of 1,589.9 TgC with a 95% confidence interval of 1,367/1,853 TgC (−14.0%/+16.6%), implying a one‐sigma uncertainty of ~ ±8%. Per capita emissions are larger in states dominated by electricity production and industrial activity and smaller where onroad and building emissions dominate. The U.S. FFCO2 emissions center of mass (CoM) is located in the state of Missouri with mean seasonality that moves on a near‐elliptical NE/SW path. Comparison to ODIAC, a global gridded FFCO2 emissions estimate, shows large total emissions differences (100.4 TgC for year 2011), a spatial correlation of 0.68 (R2), and a mean absolute relative difference at the 1 km2 scale of 104.3%. The Vulcan data product offers a high‐resolution estimate of FFCO2 emissions in every U.S. city, obviating costly development of self‐reported urban inventories. The Vulcan v3.0 annual gridded emissions data product can be downloaded from the Oak Ridge National Laboratory Distributed Active Archive Center (Gurney, Liang, et al., 2019, https://doi.org/10.3334/ORNLDAAC/1741).

Estimating US fossil fuel CO2 emissions from measurements of 14C in atmospheric CO2.

We report national scale estimates of CO2 emissions from fossil-fuel combustion and cement production in the United States based directly on atmospheric observations, using a dual-tracer inverse modeling framework and CO2 and [Formula: see text] measurements obtained primarily from the North American portion of the National Oceanic and Atmospheric Administration's Global Greenhouse Gas Reference Network. The derived US national total for 2010 is 1,653 ± 30 TgC yr-1 with an uncertainty ([Formula: see text]) that takes into account random errors associated with atmospheric transport, atmospheric measurements, and specified prior CO2 and 14C fluxes. The atmosphere-derived estimate is significantly larger ([Formula: see text]) than US national emissions for 2010 from three global inventories widely used for CO2 accounting, even after adjustments for emissions that might be sensed by the atmospheric network, but which are not included in inventory totals. It is also larger ([Formula: see text]) than a similarly adjusted total from the US Environmental Protection Agency (EPA), but overlaps EPA's reported upper 95% confidence limit. In contrast, the atmosphere-derived estimate is within [Formula: see text] of the adjusted 2010 annual total and nine of 12 adjusted monthly totals aggregated from the latest version of the high-resolution, US-specific "Vulcan" emission data product. Derived emissions appear to be robust to a range of assumed prior emissions and other parameters of the inversion framework. While we cannot rule out a possible bias from assumed prior Net Ecosystem Exchange over North America, we show that this can be overcome with additional [Formula: see text] measurements. These results indicate the strong potential for quantification of US emissions and their multiyear trends from atmospheric observations.

Comparing a global high-resolution downscaled fossil fuel CO2 emission dataset to local inventory-based estimates over 14 global cities

BackgroundCompilation of emission inventories (EIs) for cities is a whole new challenge to assess the subnational climate mitigation effort under the Paris Climate Agreement. Some cities have started compiling EIs, often following a global community protocol. However, EIs are often difficult to systematically examine because of the ways they were compiled (data collection and emission calculation) and reported (sector definition and direct vs consumption). In addition, such EI estimates are not readily applicable to objective evaluation using modeling and observations due to the lack of spatial emission extents. City emission estimates used in the science community are often based on downscaled gridded EIs, while the accuracy of the downscaled emissions at city level is not fully assessed.ResultsThis study attempts to assess the utility of the downscaled emissions at city level. We collected EIs from 14 major global cities and compare them to the estimates from a global high-resolution fossil fuel CO2 emission data product (ODIAC) commonly used in the science research community. We made necessary adjustments to the estimates to make our comparison as reasonable as possible. We found that the two methods produce very close area-wide emission estimates for Shanghai and Delhi (< 10% difference), and reach good consistency in half of the cities examined (< 30% difference). The ODIAC dataset exhibits a much higher emission compared to inventory estimates in Cape Town (+ 148%), Sao Paulo (+ 43%) and Beijing (+ 40%), possibly related to poor correlation between nightlight intensity with human activity, such as the high-emission and low-lighting industrial parks in developing countries. On the other hand, ODIAC shows lower estimates in Manhattan (− 62%), New York City (− 45%), Washington D.C. (− 42%) and Toronto (− 33%), all located in North America, which may be attributable to an underestimation of residential emissions from heating in ODIAC’s nightlight-based approach, and an overestimation of emission from ground transportation in registered vehicles statistics of inventory estimates.ConclusionsThe relatively good agreement suggests that the ODIAC data product could potentially be used as a first source for prior estimate of city-level CO2 emission, which is valuable for atmosphere CO2 inversion modeling and comparing with satellite CO2 observations. Our compilation of in-boundary emission estimates for 14 cities contributes towards establishing an accurate inventory in-boundary global city carbon emission dataset, necessary for accountable local climate mitigation policies in the future.

The Hestia fossil fuel CO&amp;lt;sub&amp;gt;2&amp;lt;/sub&amp;gt; emissions data product for the Los Angeles megacity (Hestia-LA)

Abstract. High-resolution bottom-up estimation provides a detailed guide for city greenhouse gas mitigation options, offering details that can increase the economic efficiency of emissions reduction options and synergize with other urban policy priorities at the human scale. As a critical constraint to urban atmospheric CO2 inversion studies, bottom-up spatiotemporally explicit emissions data products are also necessary to construct comprehensive urban CO2 emission information systems useful for trend detection and emissions verification. The “Hestia Project” is an effort to provide bottom-up granular fossil fuel (FFCO2) emissions for the urban domain with building/street and hourly space–time resolution. Here, we report on the latest urban area for which a Hestia estimate has been completed – the Los Angeles megacity, encompassing five counties: Los Angeles County, Orange County, Riverside County, San Bernardino County and Ventura County. We provide a complete description of the methods used to build the Hestia FFCO2 emissions data product for the years 2010–2015. We find that the LA Basin emits 48.06 (±5.3) MtC yr−1, dominated by the on-road sector. Because of the uneven spatial distribution of emissions, 10 % of the largest-emitting grid cells account for 93.6 %, 73.4 %, 66.2 %, and 45.3 % of the industrial, commercial, on-road, and residential sector emissions, respectively. Hestia FFCO2 emissions are 10.7 % larger than the inventory estimate generated by the local metropolitan planning agency, a difference that is driven by the industrial and electricity production sectors. The detail of the Hestia-LA FFCO2 emissions data product offers the potential for highly targeted, efficient urban greenhouse gas emissions mitigation policy. The Hestia-LA v2.5 emissions data product can be downloaded from the National Institute of Standards and Technology repository (https://doi.org/10.18434/T4/1502503, Gurney et al., 2019).

A global map of emission clumps for future monitoring of fossil fuel CO&amp;lt;sub&amp;gt;2&amp;lt;/sub&amp;gt; emissions from space

Abstract. A large fraction of fossil fuel CO2 emissions emanate from “hotspots”, such as cities (where direct CO2 emissions related to fossil fuel combustion in transport, residential, commercial sectors, etc., excluding emissions from electricity-producing power plants, occur), isolated power plants, and manufacturing facilities, which cover a small fraction of the land surface. The coverage of all high-emitting cities and point sources across the globe by bottom-up inventories is far from complete, and for most of those covered, the uncertainties in CO2 emission estimates in bottom-up inventories are too large to allow continuous and rigorous assessment of emission changes (Gurney et al., 2019). Space-borne imagery of atmospheric CO2 has the potential to provide independent estimates of CO2 emissions from hotspots. But first, what a hotspot is needs to be defined for the purpose of satellite observations. The proposed space-borne imagers with global coverage planned for the coming decade have a pixel size on the order of a few square kilometers and a XCO2 accuracy and precision of &lt;1 ppm for individual measurements of vertically integrated columns of dry-air mole fractions of CO2 (XCO2). This resolution and precision is insufficient to provide a cartography of emissions for each individual pixel. Rather, the integrated emission of diffuse emitting areas and intense point sources is sought. In this study, we characterize area and point fossil fuel CO2 emitting sources which generate coherent XCO2 plumes that may be observed from space. We characterize these emitting sources around the globe and they are referred to as “emission clumps” hereafter. An algorithm is proposed to identify emission clumps worldwide, based on the ODIAC global high-resolution 1 km fossil fuel emission data product. The clump algorithm selects the major urban areas from a GIS (geographic information system) file and two emission thresholds. The selected urban areas and a high emission threshold are used to identify clump cores such as inner city areas or large power plants. A low threshold and a random walker (RW) scheme are then used to aggregate all grid cells contiguous to cores in order to define a single clump. With our definition of the thresholds, which are appropriate for a space imagery with 0.5 ppm precision for a single XCO2 measurement, a total of 11 314 individual clumps, with 5088 area clumps, and 6226 point-source clumps (power plants) are identified. These clumps contribute 72 % of the global fossil fuel CO2 emissions according to the ODIAC inventory. The emission clumps is a new tool for comparing fossil fuel CO2 emissions from different inventories and objectively identifying emitting areas that have a potential to be detected by future global satellite imagery of XCO2. The emission clump data product is distributed from https://doi.org/10.6084/m9.figshare.7217726.v1.

Comparison of Global Downscaled Versus Bottom‐Up Fossil Fuel CO2 Emissions at the Urban Scale in Four U.S. Urban Areas

AbstractSpatiotemporally resolved urban fossil fuel CO2 (FFCO2) emissions are critical to urban carbon cycle research and urban climate policy. Two general scientific approaches have been taken to estimate spatiotemporally explicit urban FFCO2 fluxes, referred to here as “downscaling” and “bottom‐up.” Bottom‐up approaches can specifically characterize the CO2‐emitting infrastructure in cities but are labor‐intensive to build and currently available in few U.S. cities. Downscaling approaches, often available globally, require proxy information to allocate or distribute emissions resulting in additional uncertainty. We present a comparison of a downscaled FFCO2 emission data product (Open‐source Data Inventory for Anthropogenic CO2 (ODIAC)) to a bottom‐up estimate (Hestia) in four U.S. urban areas in an effort to better isolate and understand differences between the approaches. We find whole‐city differences ranging from −1.5% (Los Angeles Basin) to +20.8% (Salt Lake City). At the 1 km × 1 km spatial scale, comparisons reveal a low‐emission limit in ODIAC driven by saturation of the nighttime light spatial proxy. At this resolution, the median difference between the two approaches ranged from 47 to 84% depending upon city with correlations ranging from 0.34 to 0.68. The largest discrepancies were found for large point sources and the on‐road sector, suggesting that downscaled FFCO2 data products could be improved by incorporating independent large point‐source estimates and estimating on‐road sources with a relevant spatial surrogate. Progressively coarsening the spatial resolution improves agreement but greater than approximately 25 km2, there were diminishing returns to agreement suggesting a practical resolution when using downscaled approaches.

Bayesian inverse estimation of urban CO2 emissions: Results from a synthetic data simulation over Salt Lake City, UT

Top-down, data-driven models possess ample power to improve the accuracy of bottom-up carbon dioxide (CO2) emission inventories, and more work is needed to explore the merger of top-down and bottom-up estimates to better inform the metrics used to monitor global CO2 fluxes. Here we present a Bayesian inverse modeling framework over Salt Lake City, Utah, which utilizes available CO2 emission inventories to establish a synthetic data simulation aimed at exploring model uncertainties. Prescribing a high-resolution, urban-scale data product (Hestia) as the “true” emissions in the model, we combine prior emissions with an atmospheric transport model to derive modeled afternoon CO2 enhancements at six monitoring sites within the Salt Lake Valley during the month of September 2015. A global high-resolution gridded emissions data product (ODIAC) is used as the prior, and objective uncertainty structures are defined for both the a priori estimates and the transport model-data relationship which consider non-negligible spatial and temporal covariances. Optimized (posterior) emissions over the Salt Lake Valley agree closely with the assumed “true” emissions during afternoon times, while results including unconstrained times (e.g. night-time) lack such agreement. Both spatial and temporal correlations of prior errors were found to be necessary for obtaining a robust posterior estimate. Model sensitivity analyses are performed, which examine correlation length and time scales, model-data mismatch error, and measurement site network variability. Through these analyses, one measurement site is identified as being particularly prone to introducing bias into posterior emissions due to influences from a nearby point source. Increasing model-data mismatch error at this site is shown to reduce bias in the posterior without significantly compromising agreement with monthly averaged true emissions.

The Open-source Data Inventory for Anthropogenic Carbon dioxide (CO2), version 2016 (ODIAC2016): A global, monthly fossil-fuel CO2 gridded emission data product for tracer transport simulations and surface flux inversions.

The Open-source Data Inventory for Anthropogenic CO2 (ODIAC) is a global high-spatial resolution gridded emission data product that distributes carbon dioxide (CO2) emissions from fossil fuel combustion. The emission spatial distributions are estimated at a 1×1 km spatial resolution over land using power plant profiles (emission intensity and geographical location) and satellite-observed nighttime lights. This paper describes the year 2016 version of the ODIAC emission data product (ODIAC2016) and presents analyses that help guiding data users, especially for atmospheric CO2 tracer transport simulations and flux inversion analysis. Since the original publication in 2011, we have made modifications to our emission modeling framework in order to deliver a comprehensive global gridded emission data product. Major changes from the 2011 publication are 1) the use of emissions estimates made by the Carbon Dioxide Information Analysis Center (CDIAC) at the Oak Ridge National Laboratory (ORNL) by fuel type (solid, liquid, gas, cement manufacturing, gas flaring and international aviation and marine bunkers), 2) the use of multiple spatial emission proxies by fuel type such as nightlight data specific to gas flaring and ship/aircraft fleet tracks and 3) the inclusion of emission temporal variations. Using global fuel consumption data, we extrapolated the CDIAC emissions estimates for the recent years and produced the ODIAC2016 emission data product that covers 2000-2015. Our emission data can be viewed as an extended version of CDIAC gridded emission data product, which should allow data users to impose global fossil fuel emissions in more comprehensive manner than original CDIAC product. Our new emission modeling framework allows us to produce future versions of ODIAC emission data product with a timely update. Such capability has become more significant given the CDIAC/ORNL's shutdown. ODIAC data product could play an important role to support carbon cycle science, especially modeling studies with space-based CO2 data collected near real time by ongoing carbon observing missions such as Japanese Greenhouse Observing SATellite (GOSAT), NASA's Orbiting Carbon Observatory 2 (OCO-2) and upcoming future missions. The ODIAC emission data product including the latest version of the ODIAC emission data (ODIAC2017, 2000-2016), is distributed from http://db.cger.nies.go.jp/dataset/ODIAC/ with a DOI.

Vapor hydrogen and oxygen isotopes reflect water of combustion in the urban atmosphere.

Anthropogenic modification of the water cycle involves a diversity of processes, many of which have been studied intensively using models and observations. Effective tools for measuring the contribution and fate of combustion-derived water vapor in the atmosphere are lacking, however, and this flux has received relatively little attention. We provide theoretical estimates and a first set of measurements demonstrating that water of combustion is characterized by a distinctive combination of H and O isotope ratios. We show that during periods of relatively low humidity and/or atmospheric stagnation, this isotopic signature can be used to quantify the concentration of water of combustion in the atmospheric boundary layer over Salt Lake City. Combustion-derived vapor concentrations vary between periods of atmospheric stratification and mixing, both on multiday and diurnal timescales, and respond over periods of hours to variations in surface emissions. Our estimates suggest that up to 13% of the boundary layer vapor during the period of study was derived from combustion sources, and both the temporal pattern and magnitude of this contribution were closely reproduced by an independent atmospheric model forced with a fossil fuel emissions data product. Our findings suggest potential for water vapor isotope ratio measurements to be used in conjunction with other tracers to refine the apportionment of urban emissions, and imply that water vapor emissions associated with combustion may be a significant component of the water budget of the urban boundary layer, with potential implications for urban climate, ecohydrology, and photochemistry.

A multiyear, global gridded fossil fuel CO2 emission data product: Evaluation and analysis of results

AbstractHigh‐resolution, global quantification of fossil fuel CO2 emissions is emerging as a critical need in carbon cycle science and climate policy. We build upon a previously developed fossil fuel data assimilation system (FFDAS) for estimating global high‐resolution fossil fuel CO2 emissions. We have improved the underlying observationally based data sources, expanded the approach through treatment of separate emitting sectors including a new pointwise database of global power plants, and extended the results to cover a 1997 to 2010 time series at a spatial resolution of 0.1°. Long‐term trend analysis of the resulting global emissions shows subnational spatial structure in large active economies such as the United States, China, and India. These three countries, in particular, show different long‐term trends and exploration of the trends in nighttime lights, and population reveal a decoupling of population and emissions at the subnational level. Analysis of shorter‐term variations reveals the impact of the 2008–2009 global financial crisis with widespread negative emission anomalies across the U.S. and Europe. We have used a center of mass (CM) calculation as a compact metric to express the time evolution of spatial patterns in fossil fuel CO2 emissions. The global emission CM has moved toward the east and somewhat south between 1997 and 2010, driven by the increase in emissions in China and South Asia over this time period. Analysis at the level of individual countries reveals per capita CO2 emission migration in both Russia and India. The per capita emission CM holds potential as a way to succinctly analyze subnational shifts in carbon intensity over time. Uncertainties are generally lower than the previous version of FFDAS due mainly to an improved nightlight data set.

Constraints on emissions of carbon monoxide, methane, and a suite of hydrocarbons in the Colorado Front Range using observations of &amp;lt;sup&amp;gt;14&amp;lt;/sup&amp;gt;CO&amp;lt;sub&amp;gt;2&amp;lt;/sub&amp;gt;

Abstract. Atmospheric radiocarbon (14C) represents an important observational constraint on emissions of fossil-fuel derived carbon into the atmosphere due to the absence of 14C in fossil fuel reservoirs. The high sensitivity and precision that accelerator mass spectrometry (AMS) affords in atmospheric 14C analysis has greatly increased the potential for using such measurements to evaluate bottom-up emissions inventories of fossil fuel CO2 (CO2ff), as well as those for other co-emitted species. Here we use observations of 14CO2 and a series of primary hydrocarbons and combustion tracers from discrete air samples collected between June 2009 and September 2010 at the National Oceanic and Atmospheric Administration Boulder Atmospheric Observatory (BAO; Lat: 40.050° N, Lon: 105.004° W) to derive emission ratios of each species with respect to CO2ff. The BAO tower is situated at the boundary of the Denver metropolitan area to the south and a large industrial and agricultural region to the north and east, making it an ideal location to study the contrasting mix of emissions from the activities in each region. The species considered in this analysis are carbon monoxide (CO), methane (CH4), acetylene (C2H2), benzene (C6H6), and C3–C5 alkanes. We estimate emissions for a subset of these species by using the Vulcan high resolution CO2ff emission data product as a reference. We find that CO is overestimated in the 2008 National Emissions Inventory (NEI08) by a factor of ~2. A close evaluation of the inventory suggests that the ratio of CO emitted per unit fuel burned from on-road gasoline vehicles is likely over-estimated by a factor of 2.5. Using a wind-directional analysis of the data, we find enhanced concentrations of CH4, relative to CO2ff, in air influenced by emissions to the north and east of the BAO tower when compared to air influenced by emissions in the Denver metro region to the south. Along with enhanced CH4, the strongest enhancements of the C3–C5 alkanes are also found in the north and east wind sector, suggesting that both the alkane and CH4 enhancements are sourced from oil and gas fields located to the northeast, though it was not possible to rule out the contribution of non oil and gas CH4 sources.