High spatial resolution imaging of methane and other trace gases with the airborne Hyperspectral Thermal Emission Spectrometer (HyTES)

Currently large uncertainties exist associated with the attribution and quantification of fugitive emissions of criteria pollutants and greenhouse gases such as methane across large regions and key economic sectors. In this study, data from the airborne Hyperspectral Thermal Emission Spectrometer (HyTES) have been used to develop robust and reliable techniques for the detection and wide-area mapping of emission plumes of methane and other atmospheric trace gas species over challenging and diverse environmental conditions with high spatial resolution that permits direct attribution to sources. HyTES is a pushbroom imaging spectrometer with high spectral resolution (256 bands from 7.5 to 12 µm), wide swath (1–2 km), and high spatial resolution (∼ 2 m at 1 km altitude) that incorporates new thermal infrared (TIR) remote sensing technologies. In this study we introduce a hybrid clutter matched filter (CMF) and plume dilation algorithm applied to HyTES observations to efficiently detect and characterize the spatial structures of individual plumes of CH_4, H_2S, NH_3, NO_2, and SO_2 emitters. The sensitivity and field of regard of HyTES allows rapid and frequent airborne surveys of large areas including facilities not readily accessible from the surface. The HyTES CMF algorithm produces plume intensity images of methane and other gases from strong emission sources. The combination of high spatial resolution and multi-species imaging capability provides source attribution in complex environments. The CMF-based detection of strong emission sources over large areas is a fast and powerful tool needed to focus on more computationally intensive retrieval algorithms to quantify emissions with error estimates, and is useful for expediting mitigation efforts and addressing critical science questions

Silica in a Mars analog environment: Ka'u Desert, Kilauea Volcano, Hawaii

Airborne Visible/Near-Infrared Imaging Spectrometer (AVIRIS) data acquired over the Ka'u Desert are atmospherically corrected to ground reflectance and used to identify the mineralogic components of relatively young basaltic materials, including 250–700 and 200–400 year old lava flows, 1971 and 1974 flows, ash deposits, and solfatara incrustations. To provide context, a geologic surface units map is constructed, verified with field observations, and supported by laboratory analyses. AVIRIS spectral end-members are identified in the visible (0.4 to 1.2 μm) and short wave infrared (2.0 to 2.5 μm) wavelength ranges. Nearly all the spectral variability is controlled by the presence of ferrous and ferric iron in such minerals as pyroxene, olivine, hematite, goethite, and poorly crystalline iron oxides or glass. A broad, nearly ubiquitous absorption feature centered at 2.25 μm is attributed to opaline (amorphous, hydrated) silica and is found to correlate spatially with mapped geologic surface units. Laboratory analyses show the silica to be consistently present as a deposited phase, including incrustations downwind from solfatara vents, cementing agent for ash duricrusts, and thin coatings on the youngest lava flow surfaces. A second, Ti-rich upper coating on young flows also influences spectral behavior. This study demonstrates that secondary silica is mobile in the Ka'u Desert on a variety of time scales and spatial domains. The investigation from remote, field, and laboratory perspectives also mimics exploration of Mars using orbital and landed missions, with important implications for spectral characterization of coated basalts and formation of opaline silica in arid, acidic alteration environments

Airborne methane remote measurements reveal heavy-tail flux distribution in Four Corners region

Methane (CH_4) impacts climate as the second strongest anthropogenic greenhouse gas and air quality by influencing tropospheric ozone levels. Space-based observations have identified the Four Corners region in the Southwest United States as an area of large CH_4 enhancements. We conducted an airborne campaign in Four Corners during April 2015 with the next-generation Airborne Visible/Infrared Imaging Spectrometer (near-infrared) and Hyperspectral Thermal Emission Spectrometer (thermal infrared) imaging spectrometers to better understand the source of methane by measuring methane plumes at 1- to 3-m spatial resolution. Our analysis detected more than 250 individual methane plumes from fossil fuel harvesting, processing, and distributing infrastructures, spanning an emission range from the detection limit ∼2 kg/h to 5 kg/h through ∼5,000 kg/h. Observed sources include gas processing facilities, storage tanks, pipeline leaks, and well pads, as well as a coal mine venting shaft. Overall, plume enhancements and inferred fluxes follow a lognormal distribution, with the top 10% emitters contributing 49 to 66% to the inferred total point source flux of 0.23 Tg/y to 0.39 Tg/y. With the observed confirmation of a lognormal emission distribution, this airborne observing strategy and its ability to locate previously unknown point sources in real time provides an efficient and effective method to identify and mitigate major emissions contributors over a wide geographic area. With improved instrumentation, this capability scales to spaceborne applications [Thompson DR, et al. (2016) Geophys Res Lett 43(12):6571–6578]. Further illustration of this potential is demonstrated with two detected, confirmed, and repaired pipeline leaks during the campaign

Surface temperatures in New York City: Geospatial data enables the accurate prediction of radiative heat transfer

Three decades into the research seeking to derive the urban energy budget, the dynamics of the thermal exchange between the densely built infrastructure and the environment are still not well understood. We present a novel hybrid experimental-numerical approach for the analysis of the radiative heat transfer in New York City. The aim of this work is to contribute to the calculation of the urban energy budget, in particular the stored energy. Improved understanding of urban thermodynamics incorporating the interaction of the various bodies will have implications on energy conservation at the building scale, as well as human health and comfort at the urban scale. The platform presented is based on longwave hyperspectral imaging of nearly 100 blocks of Manhattan, and a geospatial radiosity model that describes the collective radiative heat exchange between multiple buildings. The close comparison of temperature values derived from measurements and the computed surface temperatures (including streets and roads) implies that this geospatial, thermodynamic numerical model applied to urban structures, is promising for accurate and high resolution analysis of urban surface temperatures.Comment: 11 pages, 5 figure

A Systems level characterization and tradespace evaluation of a simulated airborne fourier transform infrared spectrometer for gas detection

The remote sensing gas detection problem is one with no straightforward solution. While success has been achieved in detecting and identifying gases released from industrial stacks and other large plumes, the fugituve gas detection problem is far more complex. Fugitive gas represents a far smaller target and may be generated by leaking pipes, vents, or small scale chemical production. The nature of fugitive gas emission is such that one has no foreknowledge of the location, quantity, or transient rate of the targeted effluent which requires one to cover a broad area with high sensitivity. In such a scenario, a mobile airborne platform would be a likely candidate. Further, the spectrometer used for gas detection should be capable of rapid scan rates to prevent spatial and spectral smearing, while maintaining high resolution to aid in species identification. Often, insufficient signal to noise (SNR) prevents spectrometers from delivering useful results under such conditions. While common dispersive element spectrometers (DES) suffer from decreasing SNR with increasing spectral dispersion, Fourier Transform Spectrometers (FTS) generally do not and would seemingly be an ideal choice for such an application. FTS are ubiquitous in chemical laboratories and in use as ground based spectrometers, but have not become as pervasive in mobile applications. While FTS spectrometers would otherwise be ideal for high resolution rapid scanning in search of gaseous effluents, when conducted via a mobile platform the process of optical interferogram formation to form spectra is corrupted when the input signal is temporally unstable. This work seeks to explore the tradespace of an airborne Michelson based FTS in terms of modeling and characterizing the performance degradation over a variety of environmental and optical parameters. The major variables modeled and examined include: maximum optical path distance (resolution), scan rate, platform velocity, altitude, atmospheric and background emissivity variability, gas target parameters such as temperature, concentration-pathlength, confuser gas presence, and optical effects including apodization effects, single and double-sided interferograms, internal mirror positional accuracy errors, and primary mirror jitter effects. It is through an understanding of how each of the aforementioned variables impacts the gas detection performance that one can constrain design parameters in developing and engineering an FTS suitable to the airborne environment. The instrument model was compared to output from ground-based FTS instruments as well as airborne data taken from the Airborne Hyperspectral Imager (AHI) and found to be in good agreement. Monte Carlo studies were used to map the impact of the performance variables and unique detection algorithms, based on common detection scores, were used to quantify performance degradation. Scene-based scenarios were employed to evaluate performance of a scanning FTS under variable and complex conditions. It was found that despite critical sampling errors and rapidly varying radiance signals, while losing the ability to reproduce a radiometrically accurate spectrum, an FTS offered the unique ability to reproduce spectral evidence of a gas in scenarios where a dispersive element spectrometer (DES) might not

An Examination of Enhanced Atmospheric Methane Detection Methods for Predicting Performance of a Novel Multiband Uncooled Radiometer Imager

To evaluate the potential for a new uncooled infrared radiometer imager to detect enhanced atmospheric levels of methane, three different analysis methods were examined. A single-pixel brightness temperature to noise-equivalent delta temperature (NEdT) comparison study performed using data simulated from MODTRAN6 revealed that a single thermal band centered on the 7.68 µm methane feature leads to a detectable brightness temperature difference exceeding the sensor noise level for a plume of about 17 ppm at ambient atmospheric temperature compared to an ambient plume with no enhanced methane present. Application of a normalized differential methane index method, a novel approach for methane detection, demonstrated how a simple two-band method can be utilized to detect a plume of methane that is 10 ppm above ambient atmospheric concentration and −10 K from ambient atmospheric temperature with an 80 % hit rate and 17 % false alarm rate. This method was capable of detecting methane with similar levels of success as the third method, a proven multichannel method, matched filter. The matched-filter approach was performed with six spectral channels. Results from these examinations suggest that given a high enough concentration and temperature contrast, a multispectral system with a single band allocated to a methane absorption feature can detect enhanced levels of methane