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.

We report the CH 4 emission flux from the city of Indianapolis, IN, the site of the Indianapolis Flux Experiment (INFLUX) project for developing, assessing, and improving top-down and bottom-up approaches for quantifying urban greenhouse gas emissions. Using an aircraft-based mass balance approach, we find that the average CH 4 emission rate from five flight experiments in 2011 is 135 ± 58 (1σ) moles s-1 (7800 ± 3300 kg hr-1). The effective per capita CH 4 emission rate for Indianapolis is 77 kg CH 4 person-1 yr-1 , a figure that is less than the national anthropogenic CH 4 emission (∼91 kg CH 4 person-1 yr-1) but considerably larger than the global figure (∼48 kg CH 4 person-1 yr-1). We consistently observed elevated CH 4 concentrations at specific coordinates along our flight transects downwind of the city. Inflight investigations as well as back trajectories using measured wind directions showed that the elevated concentrations originated from the southwest side of the city where a landfill and a natural gas transmission regulating station (TRS) are located. Street level mobile measurements downwind of the landfill and the TRS supported the results of aircraft-based data, and were used to quantify the relative contributions from the two sources. We find that the CH 4 emission from the TRS was negligible relative to the landfill, which was responsible for 33 ± 10% of the citywide emission flux. A regression of propane versus methane from aircraft flask samples suggests that the remaining citywide CH 4 emissions (∼67%) derive from the natural gas distribution system. We discuss the combination of surface mobile observations and aircraft city-wide flux measurements to determine the total flux and apportionment to important sources.

Identification and quantification of trace gas sources is a major challenge for understanding and regulating air quality and greenhouse gas emissions. Current approaches either provide continuous but localized monitoring, or quasi-instantaneous "snapshot-in-time" regional monitoring. There is a need for emissions detection that provides both continuous and regional coverage, because sources and sinks can be episodic and spatially variable. We field deploy a dual frequency comb laser spectrometer for the first time, enabling an observing system that provides continuous detection of trace gas sources over multiple-square-kilometer regions. Field tests simulating methane emissions from oil and gas production demonstrate detection and quantification of a 1.6 g min -1 source (approximate emissions from a small pneumatic valve) from a distance of 1 km, and the ability to discern two leaks among a field of many potential sources. The technology achieves the goal of detecting, quantifying, and attributing emissions sources continuously through time, over large areas, and at emissions rates ~1000x lower than current regional approaches. It therefore provides a useful tool for monitoring and mitigating undesirable sources and closes a major information gap in the atmospheric sciences.

A mathematical model for a three-tiered system consisting of solid, liquid and gas is derived for studying the combustion of RDX propellants. The resulting nonlinear two-point boundary value problem is solved by Newton's method with adaptive gridding techniques. In this study the burning rate is computed as an eigenvalue, which can remove the uncertainty associated with employing evaporation and condensation rate laws in its evaluation. Results are presented for laser-assisted and self-deflagration of RDX monopropellants and are compared with experimental results. The burning rates are computed over a wide range of ambient pressures and compare well with experimental results from one to ninety atmospheres. The burning rate is found to be proportional to the pressure raised to the 0.76 power. Sensitivity of the burning rate to initial propellant temperture is calculated and found to be extremely low, in agreement with past theoretical predictions and experimental data. Results for laser-assisted combustion' show a distinct primary and secondary flame separated by a dark zone, the length of which is dependent upon the incident laser flux intensity,

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.