Abstract. Regulatory air quality models, such as the Community Multiscale Air Quality model (CMAQ), are used by federal and state agencies to guide policy decisions that determine how to best achieve adherence with National Ambient Air Quality Standards for surface ozone. We use observations of ozone and its important precursor NO2 to test the representation of the photochemistry and emission of ozone precursors within CMAQ. Observations of tropospheric column NO2 from the Ozone Monitoring Instrument (OMI), retrieved by two independent groups, show that the model overestimates urban NO2 and underestimates rural NO2 under all conditions examined for July and August 2011 in the US Northeast. The overestimate of the urban to rural ratio of tropospheric column NO2 for this baseline run of CMAQ (CB05 mechanism, mobile NOx emissions from the National Emissions Inventory; isoprene emissions from MEGAN v2.04) suggests this model may underestimate the importance of interstate transport of NOx. This CMAQ simulation leads to a considerable overestimate of the 2-month average of 8 h daily maximum surface ozone in the US Northeast, as well as an overestimate of 8 h ozone at AQS sites during days when the state of Maryland experienced NAAQS exceedances. We have implemented three changes within CMAQ motivated by OMI NO2 as well as aircraft observations obtained in July 2011 during the NASA DISCOVER-AQ campaign: (a) the modeled lifetime of organic nitrates within CB05 has been reduced by a factor of 10, (b) emissions of NOx from mobile sources has been reduced by a factor of 2, and (c) isoprene emissions have been reduced by using MEGAN v2.10 rather than v2.04. Compared to the baseline simulation, the CMAQ run using all three of these changes leads to considerably better simulation of column NO2 in both urban and rural areas, better agreement with the 2-month average of daily 8 h maximum ozone in the US Northeast, fewer number of false positives of an ozone exceedance throughout the domain, as well as an unbiased simulation of surface ozone at ground-based AQS sites in Maryland that experienced an ozone exceedance during July and August 2007. These modifications to CMAQ may provide a framework for use in studies focused on achieving future adherence to specific air quality standards for surface ozone by reducing emission of NOx from various anthropogenic sectors.
A Comprehensive Air‐Quality Model with Extensions (CAMx) version 6.10 simulation was assessed through comparison with data acquired during NASA's 2011 Deriving Information on Surface Conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER‐AQ) Maryland field campaign. Comparisons for the baseline simulation (Carbon Bond 2005 (CB05) chemistry, Environmental Protection Agency 2011 National Emissions Inventory) show a model overestimate of NOy by +86.2% and an underestimate of HCHO by −28.3%. We present a new model framework (Carbon Bond 6 Revision 2 chemistry (CB6r2), Model of Emissions of Gases and Aerosols from Nature (MEGAN) version 2.1 biogenic emissions, 50% reduction in mobile NOx, enhanced representation of isoprene nitrates) that better matches observations. The new model framework attributes 31.4% more surface ozone in Maryland to electric generating units (EGUs) and 34.6% less ozone to on‐road mobile sources. Surface ozone becomes more NOx limited throughout the eastern United States compared to the baseline simulation. The baseline model therefore likely underestimates the effectiveness of anthropogenic NOx reductions as well as the current contribution of EGUs to surface ozone.
Abstract. Regulatory air quality models, such as the Community Multiscale Air Quality model (CMAQ), are used by federal and state agencies to guide policy decisions that determine how to best achieve adherence with National Ambient Air Quality Standards for surface ozone. We use observations of ozone and its important precursor NO2 to test the representation of the photochemistry and emission of ozone precursors within CMAQ. Observations of tropospheric column NO2 from the Ozone Monitoring Instrument (OMI), retrieved by two independent groups, show that the model overestimates urban NO2 and underestimates rural NO2 under all conditions examined for July and August 2011 in the US Northeast. The overestimate of the urban to rural ratio of tropospheric column NO2 for this baseline run of CMAQ (CB05 mechanism, mobile NOx emissions from the National Emissions Inventory; isoprene emissions from MEGAN v2.04) suggests this model may under estimate the importance of interstate transport of NOx. This CMAQ simulation leads to a considerable overestimate of the 2 month average of 8 h daily maximum surface ozone in the US Northeast, as well as an overestimate of 8 h ozone at AQS sites during days when the state of Maryland experienced NAAQS exceedances. We have implemented three changes within CMAQ motivated by OMI NO2 as well as aircraft observations obtained in July 2011 during the NASA DISCOVER-AQ campaign: (a) the modeled lifetime of organic nitrates within CB05 has been reduced by a factor of 10, (b) emissions of NOx from mobile sources has been reduced by a factor of 2, and (c) isoprene emissions have been reduced by using MEGAN v2.10 rather than v2.04. Compared to the baseline simulation, the CMAQ run using all three of these changes leads to a considerably better simulation of the ratio of urban to rural column NO2, better agreement with the 2 month average of daily 8 h maximum ozone in the US Northeast, fewer number of false positives of an ozone exceedance throughout the domain, as well as an unbiased simulation of surface ozone at ground based AQS sites in Maryland that experienced an ozone exceedance during July and August 2007. These modifications to CMAQ may provide a framework for use in studies focused on achieving future adherence to specific air quality standards for surface ozone by reducing emission of NOx from various anthropogenic sectors.
Natural gas production in the United States has increased rapidly over the past decade, along with concerns about methane (CH4) fugitive emissions and its climate impacts. Quantification of CH4 emissions from oil and natural gas (O&NG) operations is important for establishing scientifically sound policies for mitigating greenhouse gases. We use the aircraft mass balance approach for three flight experiments in August and September 2015 to estimate CH4 emissions from O&NG operations over the southwestern Marcellus Shale. We estimate a mean CH4 emission rate as 21.2 kg/s with 28% coming from O&NG operations. The mean CH4 emission rate from O&NG operations was estimated to be 1.1% of total NG production. The individual best‐estimate emission rates from the three flight experiments ranged from 0.78 to 1.5%, with overall limits of 0% and 3.5%. These emission rates are at the low end of other top‐down studies, but consistent with the few observational studies in the Marcellus Shale region as well as the U.S. Environmental Protection Agency CH4 inventory. A substantial source of CH4 (~70% of observed CH4 emissions) was found to contain little ethane, possibly due to coalbed CH4 emitted either directly from coal mines or from wells drilled through coalbed layers in O&NG operations. Recent regulations requiring capture of gas from the completion‐venting step of hydraulic fracturing appear to have reduced the atmospheric release of CH4. Our study suggests that for a 20‐year time scale, energy derived from the combustion of natural gas extracted from this region likely exerts a net climate benefit compared to coal.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.