Wintertime CO2, CH4, and CO Emissions Estimation for the Washington, DC-Baltimore Metropolitan Area Using an Inverse Modeling Technique.

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.

Observations of Methane Emissions from Natural Gas-Fired Power Plants.

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%).

Direct and Indirect Measurements and Modeling of Methane Emissions in Indianapolis, Indiana.

This paper describes process-based estimation of CH4 emissions from sources in Indianapolis, IN and compares these with atmospheric inferences of whole city emissions. Emissions from the natural gas distribution system were estimated from measurements at metering and regulating stations and from pipeline leaks. Tracer methods and inverse plume modeling were used to estimate emissions from the major landfill and wastewater treatment plant. These direct source measurements informed the compilation of a methane emission inventory for the city equal to 29 Gg/yr (5% to 95% confidence limits, 15 to 54 Gg/yr). Emission estimates for the whole city based on an aircraft mass balance method and from inverse modeling of CH4 tower observations were 41 ± 12 Gg/yr and 81 ± 11 Gg/yr, respectively. Footprint modeling using 11 days of ethane/methane tower data indicated that landfills, wastewater treatment, wetlands, and other biological sources contribute 48% while natural gas usage and other fossil fuel sources contribute 52% of the city total. With the biogenic CH4 emissions omitted, the top-down estimates are 3.5-6.9 times the nonbiogenic city inventory. Mobile mapping of CH4 concentrations showed low level enhancement of CH4 throughout the city reflecting diffuse natural gas leakage and downstream usage as possible sources for the missing residual in the inventory.

Urban Emissions of Water Vapor in Winter.

Elevated water vapor (H2Ov) mole fractions were occassionally 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 H2Ov excess signal was observed, H2Ov emissions estimates range between 1.6 × 104 and 1.7 × 105 kg s-1, and account for up to 8.4% of the total (background + urban excess) advected flow of atmospheric boundary layer H2Ov from the urban study sites. Estimates of H2Ov emissions from combustion sources and electricity generation facility cooling towers are 1-2 orders of magnitude smaller than the urban H2Ov emission rates estimated from observations. Instances of urban H2Ov 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 H2Ov excess signal is observed on some days, and not others. Radiative transfer modeling indicates that the observed urban enhancements in H2Ov and other greenhouse gas mole fractions contribute only 0.1°C day-1 to the urban heat island at the surface. This integrated warming through the boundary layer is offset by longwave cooling by H2Ov at the top of the boundary layer. While the radiative impacts of urban H2Ov emissions do not meaningfully influence urban heat island intensity, urban H2Ov emissions may have the potential to alter downwind aerosol and cloud properties.