Urban areas are the major sources of greenhouse gas emissions but also leaders in emission reduction efforts. Appropriate techniques to quantify emissions and any potential reductions over time are necessary to effectively inform these mitigation efforts. The aircraft mass balance experiment (MBE) is an established technique used for such a purpose. In this work, we use a series of 55 MBEs downwind of power plants to assess the technique’s bias and precision. In addition, we investigate what factors drive the absolute error, determined as the absolute difference between observed and reported emission rates, in individual experiments using multilinear regressions. Power plants are required to monitor their carbon dioxide emissions with an hourly resolution, and these publicly available reported emissions can be directly compared to the mass balance estimates as a pseudo-known release. To quantify the bias we calculated the mean error, which was 10 ± 240 Mg·h−1 (1σ), regressed mass balance emission rates against reported emission rates to yield a slope of 0.967 ± 0.062, and compared the sum across all mass balance emission rates, 31,000 ± 1,000 Mg·h−1, to the sum across all reported emissions, 30,660 ± 740 Mg·h−1. All three of these approaches suggest no systematic bias. Then to quantify the precision for individual determinations we calculated the slope of a regression between the standard deviation across repeated MBEs and the corresponding average emission rate, which is 30.7% ± 6.7%. The main drivers of the absolute error were sparse sampling of the plume, poor horizontal and vertical mixing of the plume, and smaller signal-to-noise ratios. Quantifying the capabilities of this technique provides context for previous analyses and allows stakeholders and researchers to make informed decisions when choosing quantification methods. Identifying the factors that drive the absolute error also allows us to adjust flight design to minimize it and potentially improve uncertainty estimates.

To study emissions of CO2 in the Baltimore, MD‐Washington, D.C. (Balt‐Wash) area, an aircraft campaign was conducted in February 2015, as part of the Fluxes of Atmospheric Greenhouse‐Gases in Maryland (FLAGG‐MD) project. During the campaign, elevated mole fractions of CO2 were observed downwind of the urban center and local power plants. Upwind flight data and Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model analyses help account for the impact of emissions outside the Balt‐Wash area. The accuracy, precision, and sensitivity of CO2 emissions estimates based on the mass balance approach were assessed for both power plants and cities. Our estimates of CO2 emissions from two local power plants agree well with their Continuous Emissions Monitoring Systems (CEMS) records. For the 16 power plant plumes captured by the aircraft, the mean percentage difference of CO2 emissions was −0.3%. For the Balt‐Wash area as a whole, the 1𝜎 CO2 emission rate uncertainty for any individual aircraft‐based mass balance approach experiment was ±38%. Treating the mass balance experiments, which were repeated seven times within 9 days, as individual quantifications of the Balt‐Wash CO2 emissions, the estimation uncertainty was ±16% (standard error of the mean at 95% CL). Our aircraft‐based estimate was compared to various bottom‐up fossil fuel CO2 (FFCO2) emission inventories. Based on the FLAGG‐MD aircraft observations, we estimate 1.9 ± 0.3 MtC of FFCO2 from the Balt‐Wash area during the month of February 2015. The mean estimate of FFCO2 from the four bottom‐up models was 2.2 ± 0.3 MtC.

Since greenhouse gas mitigation efforts are mostly being implemented in cities, the ability to quantify emission trends for urban environments is of paramount importance. However, previous aircraft work has indicated large daily variability in the results. Here we use measurements of CO2, CH4, and CO from aircraft over 5 days within an inverse model to estimate emissions from the DC-Baltimore region. Results show good agreement with previous estimates in the area for all three gases. However, aliasing caused by irregular spatiotemporal sampling of emissions is shown to significantly impact both the emissions estimates and their variability. Extensive sensitivity tests allow us to quantify the contributions of different sources of variability and indicate that daily variability in posterior emissions estimates is larger than the uncertainty attributed to the method itself (i.e., 17% for CO2, 24% for CH4, and 13% for CO). Analysis of hourly reported emissions from power plants and traffic counts shows that 97% of the daily variability in posterior emissions estimates is explained by accounting for the sampling in time and space of sources that have large hourly variability and, thus, caution must be taken in properly interpreting variability that is caused by irregular spatiotemporal sampling conditions.

Abstract. We use H2Ov isotopic vertical profile measurements and complementary meteorological observations to examine how boundary layer, cloud, and mixing processes influence the vertical structure of deuterium-excess (d-excess = δD – 8 × δ18O) in the boundary layer, inversion layer, and lower free troposphere. Airborne measurements of water vapor (H2Ov) stable isotopologues were conducted around two continental U.S. cities in February–March 2016. Nine research flights were designed to characterize the δD, δ18O, and d-excess vertical profiles extending from the surface to ≤ 2 km. We examine observations from three unique case study flights in detail. One case study shows H2Ov isotopologue vertical profiles that are consistent with Rayleigh isotopic distillation theory coinciding with clear skies, dry adiabatic lapse rates within the boundary layer, and relatively constant vertical profiles of wind speed and wind direction. The two remaining case studies show that H2Ov isotopic signatures above the boundary layer are sensitive to cloud processes and complex air mass mixing patterns. These two case studies indicate anomalies in the d-excess signature relative to Rayleigh theory, such as low d-excess values at the interface of the inversion layer and the free troposphere, which is possibly indicative of cloud evaporation. We discuss possible explanations for the observed d-excess anomalies, such as cloud evaporation, wind shear, and vertical mixing. In situ H2Ov stable isotope measurements, and d-excess in particular, could be useful for improving our understanding of moisture processing and transport mixing occurring between the boundary layer, inversion layer, and free troposphere.

Current research efforts on the atmospheric impacts of natural gas (NG) have focused heavily on the production, storage/transmission, and processing sectors, with less attention paid to the distribution and end use sectors. This work discusses 23 flights at 14 natural gas-fired power plants (NGPPs) using an aircraft-based mass balance technique and methane/carbon dioxide enhancement ratios (ΔCH4/ΔCO2) measured from stack plumes to quantify the unburned fuel. By comparing the ΔCH4/ΔCO2 ratio measured in stack plumes to that measured downwind, we determined that, within uncertainty of the measurement, all observed CH4 emissions were stack-based, that is, uncombusted NG from the stack rather than fugitive sources. Measured CH4 emission rates (ER) ranged from 8 (±5) to 135 (±27) kg CH4/h (±1σ), with the fractional CH4 throughput lost (loss rate) ranging from -0.039% (±0.076%) to 0.204% (±0.054%). We attribute negative values to partial combustion of ambient CH4 in the power plant. The average calculated emission factor (EF) of 5.4 (+10/-5.4) g CH4/million British thermal units (MMBTU) is within uncertainty of the Environmental Protection Agency (EPA) EFs. However, one facility measured during startup exhibited substantially larger stack emissions with an EF of 440 (+660/-440) g CH4/MMBTU and a loss rate of 2.5% (+3.8/-2.5%).

We use airborne measurements of water vapor (H2Ov) stable isotopologues and complementary meteorological observations to examine how boundary layer (BL) dynamics, cloud processing, and atmospheric mixing influence the vertical structure of δD, δ18O, and deuterium excess (d excess =δD–8×δ18O) in the BL, inversion layer (INV), and lower free troposphere (FT). Flights were conducted around two continental US cities in February–March 2016 and included vertical profiles extending from near the surface to ≤2 km. We examine observations from three unique case study flights in detail. One case study shows observations that are consistent with Rayleigh isotopic distillation theory coinciding with clear skies, dry adiabatic lapse rates within the boundary layer, and relatively constant vertical profiles of wind speed and wind direction. This suggests that the air mass retained the isotopic fingerprint of dehydration during moist adiabatic processes upwind of the study area. Also, observed d-excess values in the free troposphere were sometimes larger than Rayleigh theory predicts, which may indicate mixing of extremely dehydrated air from higher altitudes. The two remaining case studies show isotopic anomalies in the d-excess signature relative to Rayleigh theory and indicate cloud processes and complex boundary layer development. The most notable case study with stratocumulus clouds present had extremely low (negative) d-excess values at the interface of the inversion layer and the free troposphere, which is possibly indicative of cloud or rain droplet evaporation. We discuss how in situ H2Ov stable isotope measurements, and d excess in particular, could be useful for improving our understanding of water phase changes, transport, and mixing that occurs between the BL, INV, and FT.

Urban areas are responsible for a substantial fraction of anthropogenic emissions of greenhouse gases (GHGs) including methane (CH4), with the second largest anthropogenic direct radiative forcing relative to carbon dioxide (CO2). Quantification of urban CH4 emissions is important for establishing GHG mitigation policies. Comparison of observation-based and inventory-based urban CH4 emissions suggests possible improvements in estimating CH(4 )source emissions in urban environments. In this study, we quantify CH4 emissions from the Baltimore-Washington area based on the mass balance aircraft flight experiments conducted in Winters 2015 and 2016. The field measurement-based mean winter CH4 emission rates from this area were 8.66 +/- 4.17 kg/s in 2015 and 9.14 +/- 4.49 kg/s in 2016, which are 2.8 times the 2012 average U.S. GHG Inventory-based emission rate. The observed emission rate is 1.7 times that given in a population-apportioned state of Maryland inventory. Methane emission rates inferred from carbon monoxide (CO) and CO(2 )emission inventories and observed CH4/CO and CH4/CO2 enhancement ratios are similar to those from the mass balance approach. The observed ethane-to-methane ratios, with a mean value of 3.3% in Winter 2015 and 4.3% in Winter 2016, indicate that the urban natural gas system could be responsible for similar to 40-60% of total CH4 emissions from this area. Landfills also appear to be a major contributor, providing 25 +/- 15% of the total emissions for the region. Our study suggests there are grounds to reexamine the CH4 emissions estimates for the Baltimore-Washington area and to conduct flights in other seasons. Plain Language Summary In this study methane emission rates were estimated for the Baltimore-Washington region based on airborne observations. The inferred methane emission rate is greater than the national greenhouse gas inventory by a factor of 2.8. Reconciliation of the wide range of CH4 emissions estimates from landfills and the natural gas system is necessary.

Airborne mass balance experiments were conducted around the Washington, D.C.-Baltimore area using research aircraft from Purdue University and the University of Maryland to quantify emissions of nitrogen oxides (NOx = NO + NO2) and carbon monoxide (CO). The airborne mass balance experiments supported the Wintertime INvestigation of Transport, Emissions, and Reactivity (WINTER) campaign, an intensive airborne study of anthropogenic emissions along the Northeastern United States in February-March 2015, and the Fluxes of Atmospheric Greenhouse Gases in Maryland project which seeks to provide best estimates of anthropogenic emissions from the Washington, D.C.-Baltimore area. Top-down emission rates of NOx and CO estimated from the mass balance flights are compared with the Environmental Protection Agency's 2011 and 2014 National Emissions Inventory (NEI-11 and NEI-14). Inventory and observation-derived NOx emission rates are consistent within the measurement uncertainty. Observed CO emission rates are a factor of 2 lower than reported by the NEI. The NEI's accuracy has been evaluated for decades by studies of anthropogenic emissions, yet despite continuous inventory updates, observation-inventory discrepancies persist. WINTER NOx/CO2 enhancement ratios are consistent with inventories, but WINTER CO/NOx and CO/CO2 enhancement ratios are lower than those reported by other urban summertime studies, suggesting a strong influence of CO seasonal trends and/or nationwide CO reductions. There is a need for reliable observation-based criterion pollutant emission rate measurements independent of the NEI. Such determinations could be supplied by the community's reporting of sector-specific criteria pollutant/CO2 enhancement ratios and subsequent multiplication with currently available and forthcoming high-resolution CO2 inventories.

A Halo Photonics Stream Line XR Doppler lidar has been deployed for the Indianapolis Flux Experiment (INFLUX) to measure profiles of the mean horizontal wind and the mixing layer height for quantification of greenhouse gas emissions from the urban area. To measure the mixing layer height continuously and autonomously, a novel composite fuzzy logic approach has been developed that combines information from various scan types, including conical and vertical-slice scans and zenith stares, to determine a unified measurement of the mixing height and its uncertainty. The composite approach uses the strengths of each measurement strategy to overcome the limitations of others so that a complete representation of turbulent mixing is made in the lowest approximate to 2 km, depending on clouds and aerosol distribution. Additionally, submeso nonturbulent motions are identified from zenith stares and removed from the analysis, as these motions can lead to an overestimate of the mixing height. The mixing height is compared with in situ profile measurements from a research aircraft for validation. To demonstrate the utility of the measurements, statistics of the mixing height and its diurnal and annual variability for 2016 are also presented. The annual cycle is clearly captured, with the largest and smallest afternoon mixing heights observed at the summer and winter solstices, respectively. The diurnal cycle of the mixing layer is affected by the mean wind, growing slower in the morning and decaying more rapidly in the evening with lighter winds.

To effectively address climate change, aggressive mitigation policies need to be implemented to reduce greenhouse gas emissions. Anthropogenic carbon emissions are mostly generated from urban environments, where human activities are spatially concentrated. Improvements in uncertainty determinations and precision of measurement techniques are critical to permit accurate and precise tracking of emissions changes relative to the reduction targets. As part of the INFLUX project, we quantified carbon dioxide (CO2), carbon monoxide (CO) and methane (CH4) emission rates for the city of Indianapolis by averaging results from nine aircraft-based mass balance experiments performed in November-December 2014. Our goal was to assess the achievable precision of the aircraft-based mass balance method through averaging, assuming constant CO2, CH4 and CO emissions during a three-week field campaign in late fall. The averaging method leads to an emission rate of 14,600 mol/s for CO2, assumed to be largely fossil-derived for this period of the year, and 108 mol/s for CO. The relative standard error of the mean is 17% and 16%, for CO2 and CO, respectively, at the 95% confidence level (CL), i.e. a more than 2-fold improvement from the previous estimate of ~40% for single-flight measurements for Indianapolis. For CH4, the averaged emission rate is 67 mol/s, while the standard error of the mean at 95% CL is large, i.e. ±60%. Given the results for CO2 and CO for the same flight data, we conclude that this much larger scatter in the observed CH4 emission rate is most likely due to variability of CH4 emissions, suggesting that the assumption of constant daily emissions is not correct for CH4 sources. This work shows that repeated measurements using aircraft-based mass balance methods can yield sufficient precision of the mean to inform emissions reduction efforts by detecting changes over time in urban emissions.

Elevated water vapor (H 2 O v ) mole fractions were occasionally observed downwind of Indianapolis, IN, and the Washington, D.C.‐Baltimore, MD, area during airborne mass balance experiments conducted during winter months between 2012 and 2015. On days when an urban H 2 O v excess signal was observed, H 2 O v emission estimates range between 1.6 × 10 4 and 1.7 × 10 5 kg s −1 and account for up to 8.4% of the total (background + urban excess) advected flow of atmospheric boundary layer H 2 O v from the urban study sites. Estimates of H 2 O v emissions from combustion sources and electricity generation facility cooling towers are 1–2 orders of magnitude smaller than the urban H 2 O v emission rates estimated from observations. Instances of urban H 2 O v enhancement could be a result of differences in snowmelt and evaporation rates within the urban area, due in part to larger wintertime anthropogenic heat flux and land cover differences, relative to surrounding rural areas. More study is needed to understand why the urban H 2 O v excess signal is observed on some days, and not others. Radiative transfer modeling indicates that the observed urban enhancements in H 2 O v and other greenhouse gas mole fractions contribute only 0.1°C d −1 to the urban heat island at the surface. This integrated warming through the boundary layer is offset by longwave cooling by H 2 O v at the top of the boundary layer. While the radiative impacts of urban H 2 O v emissions do not meaningfully influence urban heat island intensity, urban H 2 O v emissions may have the potential to alter downwind aerosol and cloud properties.