Quantifying methane emissions from United States landfills.

Methane emissions from solid waste may represent a substantial fraction of the global anthropogenic budget, but few comprehensive studies exist to assess inventory assumptions. We quantified emissions at hundreds of large landfills across 18 states in the United States between 2016 and 2022 using airborne imaging spectrometers. Spanning 20% of open United States landfills, this represents the most systematic measurement-based study of methane point sources of the waste sector. We detected significant point source emissions at a majority (52%) of these sites, many with emissions persisting over multiple revisits (weeks to years). We compared these against independent contemporaneous in situ airborne observations at 15 landfills and established good agreement. Our findings indicate a need for long-term, synoptic-scale monitoring of landfill emissions in the context of climate change mitigation policy.

Attribution of individual methane and carbon dioxide emission sources using EMIT observations from space.

Carbon dioxide and methane emissions are the two primary anthropogenic climate-forcing agents and an important source of uncertainty in the global carbon budget. Uncertainties are further magnified when emissions occur at fine spatial scales (<1 km), making attribution challenging. We present the first observations from NASA's Earth Surface Mineral Dust Source Investigation (EMIT) imaging spectrometer showing quantification and attribution of fine-scale methane (0.3 to 73 tonnes CH4 hour-1) and carbon dioxide sources (1571 to 3511 tonnes CO2 hour-1) spanning the oil and gas, waste, and energy sectors. For selected countries observed during the first 30 days of EMIT operations, methane emissions varied at a regional scale, with the largest total emissions observed for Turkmenistan (731 ± 148 tonnes CH4 hour-1). These results highlight the contributions of current and planned point source imagers in closing global carbon budgets.

Strong methane point sources contribute a disproportionate fraction of total emissions across multiple basins in the United States.

Understanding, prioritizing, and mitigating methane (CH4) emissions requires quantifying CH4 budgets from facility scales to regional scales with the ability to differentiate between source sectors. We deployed a tiered observing system for multiple basins in the United States (San Joaquin Valley, Uinta, Denver-Julesburg, Permian, Marcellus). We quantify strong point source emissions (>10 kg CH4 h-1) using airborne imaging spectrometers, attribute them to sectors, and assess their intermittency with multiple revisits. We compare these point source emissions to total basin CH4 fluxes derived from inversion of Sentinel-5p satellite CH4 observations. Across basins, point sources make up on average 40% of the regional flux. We sampled some basins several times across multiple months and years and find a distinct bimodal structure to emission timescales: the total point source budget is split nearly in half by short-lasting and long-lasting emission events. With the increasing airborne and satellite observing capabilities planned for the near future, tiered observing systems will more fully quantify and attribute CH4 emissions from facility to regional scales, which is needed to effectively and efficiently reduce methane emissions.

California's methane super-emitters.

Methane is a powerful greenhouse gas and is targeted for emissions mitigation by the US state of California and other jurisdictions worldwide1,2. Unique opportunities for mitigation are presented by point-source emitters-surface features or infrastructure components that are typically less than 10 metres in diameter and emit plumes of highly concentrated methane3. However, data on point-source emissions are sparse and typically lack sufficient spatial and temporal resolution to guide their mitigation and to accurately assess their magnitude4. Here we survey more than 272,000 infrastructure elements in California using an airborne imaging spectrometer that can rapidly map methane plumes5-7. We conduct five campaigns over several months from 2016 to 2018, spanning the oil and gas, manure-management and waste-management sectors, resulting in the detection, geolocation and quantification of emissions from 564 strong methane point sources. Our remote sensing approach enables the rapid and repeated assessment of large areas at high spatial resolution for a poorly characterized population of methane emitters that often appear intermittently and stochastically. We estimate net methane point-source emissions in California to be 0.618 teragrams per year (95 per cent confidence interval 0.523-0.725), equivalent to 34-46 per cent of the state's methane inventory8 for 2016. Methane 'super-emitter' activity occurs in every sector surveyed, with 10 per cent of point sources contributing roughly 60 per cent of point-source emissions-consistent with a study of the US Four Corners region that had a different sectoral mix9. The largest methane emitters in California are a subset of landfills, which exhibit persistent anomalous activity. Methane point-source emissions in California are dominated by landfills (41 per cent), followed by dairies (26 per cent) and the oil and gas sector (26 per cent). Our data have enabled the identification of the 0.2 per cent of California's infrastructure that is responsible for these emissions. Sharing these data with collaborating infrastructure operators has led to the mitigation of anomalous methane-emission activity10.

A large airborne survey of Earth's visible-infrared spectral dimensionality.

The intrinsic spectral dimensionality indicates the observable degrees of freedom in Earth's solar-reflected light field, quantifying the diversity of spectral content accessible by visible and infrared remote sensing. The solar-reflected regime spans the 0.38 - 2.5 µm interval, and is captured by a wide range of current and planned instruments on both airborne and orbital platforms. To date there has been no systematic study of its spectral dimensionality as a function of space, time, and land cover. Here we report a multi-site, multi-year statistical survey by NASA's "Classic" Airborne Visible Near InfraRed Spectrometer (AVIRIS-C). AVIRIS-C measured large regions of California, USA, spanning wide latitudinal and elevation gradients containing all canonical MODIS land cover types. The spectral uniformity of the AVIRIS-C design enabled consistent in-scene assessment of measurement noise across acquisitions. The estimated dimensionality as a function of cover type ranged from the low 20s to the high 40s, and was approximately 50 for the combined dataset. This result indicates the high diversity of physical processes distinguishable by imaging spectrometers like AVIRIS-C for one region of the Earth.

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

Methane (CH4) 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 CH4 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 [Formula: see text] 2 kg/h to 5 kg/h through [Formula: see text] 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.

Atmospheric correction with the Bayesian empirical line.

Atmospheric correction of visible/infrared spectra traditionally involves either (1) physics-based methods using Radiative Transfer Models (RTMs), or (2) empirical methods using in situ measurements. Here a more general probabilistic formulation unifies the approaches and enables combined solutions. The technique is simple to implement and provides stable results from one or more reference spectra. This makes empirical corrections practical for large or remote environments where it is difficult to acquire coincident field data. First, we use a physics-based solution to define a prior distribution over reflectances and their correction coefficients. We then incorporate reference measurements via Bayesian inference, leading to a Maximum A Posteriori estimate which is generally more accurate than pure physics-based methods yet more stable than pure empirical methods. Gaussian assumptions enable a closed form solution based on Tikhonov regularization. We demonstrate performance in atmospheric simulations and historical data from the "Classic" Airborne Visible Infrared Imaging Spectrometer (AVIRIS-C) acquired during the HyspIRI mission preparatory campaign.

Portable Remote Imaging Spectrometer coastal ocean sensor: design, characteristics, and first flight results.

The design, characteristics, and first test flight results are described of the Portable Remote Imaging Spectrometer, an airborne sensor specifically designed to address the challenges of coastal ocean remote sensing. The sensor incorporates several technologies that are demonstrated for the first time, to the best of our knowledge, in a working system in order to achieve a high performance level in terms of uniformity, signal-to-noise ratio, low polarization sensitivity, low stray light, and high spatial resolution. The instrument covers the 350-1050 nm spectral range with a 2.83 nm sampling per pixel, and a 0.88 mrad instantaneous field of view, with 608 cross-track pixels in a pushbroom configuration. Two additional infrared channels (1240 and 1610 nm) are measured by a spot radiometer housed in the same head. The spectrometer design is based on an optically fast (F/1.8) Dyson design form coupled to a wide angle two-mirror telescope in a configuration that minimizes polarization sensitivity without the use of a depolarizer. A grating with minimum polarization sensitivity and broadband efficiency was fabricated as well as a slit assembly with black (etched) silicon surface to minimize backscatter. First flight results over calibration sites as well as Monterey Bay in California have demonstrated good agreement between in situ and remotely sensed data, confirming the potential value of the sensor to the coastal ocean science community.

Ultra-high optical absorption efficiency from the ultraviolet to the infrared using multi-walled carbon nanotube ensembles.

The optical absorption efficiencies of vertically aligned multi-walled (MW)-carbon nanotube (CNT) ensembles are characterized in the 350-7000 nm wavelength range where CNT site densities > 1 × 10(11) /cm(2) are achieved directly on metallic substrates. The site density directly impacts the optical absorption characteristics, and while high-density arrays of CNTs on electrically insulating and non-metallic substrates have been commonly reported, achieving high site-densities on metals has been challenging and remains an area of active research. These absorber ensembles are ultra-thin (<10 µm) and yet they still exhibit a reflectance as low as ∼0.02%, which is 100 times lower than the reference; these characteristics make them potentially attractive for high-sensitivity and high-speed thermal detectors. In addition, the use of a plasma-enhanced chemical vapor deposition process for the synthesis of the absorbers increases the portfolio of materials that can be integrated with such absorbers due to the potential for reduced synthesis temperatures. The remarkable ruggedness of the absorbers is also demonstrated as they are exposed to high temperatures in an oxidizing ambient environment, making them well-suited for extreme thermal environments encountered in the field, potentially for solar cell applications. Finally, a phenomenological model enables the determinatiom of the extinction coefficients in these nanostructures and the results compare well with experiment.

Reflectance microspectroscopy of natural rock samples in the visible and near infrared.

We have collected reflectance spectra of various unprocessed rock samples in the 450-1,650 nm wavelength range with a spatial resolution of 60 and 120 microm (diameter) and using three illumination modes. Spectra taken in diffuse reflectance (dark field) mode are comparable to those obtained from macroscopic measurements and can provide the basis for mineral detection at that spatial scale. The spectral discrimination of the dark field mode is demonstrated to be consistent with the spatial resolution of the microscope for the samples examined. These results support the conclusion that reflectance microspectroscopy in the visible and near-infrared regions can be a valuable tool for understanding mineral formation at the spatial scale of tens of micrometers.

Optical design of a coastal ocean imaging spectrometer.

We present an optical design for an airborne imaging spectrometer that addresses the unique constraints imposed by imaging the coastal ocean region. A fast (F/1.8) wide field system (36 degrees) with minimum polarization dependence and high response uniformity is required, that covers the spectral range 350-1050 nm with 3 nm sampling. We show how these requirements can be achieved with a two-mirror telescope and a compact Dyson spectrometer utilizing a polarization-insensitive diffraction grating.

Invasive plants transform the three-dimensional structure of rain forests.

Biological invasions contribute to global environmental change, but the dynamics and consequences of most invasions are difficult to assess at regional scales. We deployed an airborne remote sensing system that mapped the location and impacts of five highly invasive plant species across 221,875 ha of Hawaiian ecosystems, identifying four distinct ways that these species transform the three-dimensional (3D) structure of native rain forests. In lowland to montane forests, three invasive tree species replace native midcanopy and understory plants, whereas one understory invader excludes native species at the ground level. A fifth invasive nitrogen-fixing tree, in combination with a midcanopy alien tree, replaces native plants at all canopy levels in lowland forests. We conclude that this diverse array of alien plant species, each representing a different growth form or functional type, is changing the fundamental 3D structure of native Hawaiian rain forests. Our work also demonstrates how an airborne mapping strategy can identify and track the spread of certain invasive plant species, determine ecological consequences of their proliferation, and provide detailed geographic information to conservation and management efforts.