Midwave infrared interband-cascade light-emitting devices (ICLEDs) have the potential to improve the selectivity, stability, and sensitivity of low-cost gas sensors. We demonstrate a broadband direct absorption CH 4 sensor with an ICLED coupled to a plastic hollow-core fiber (1 m length, 1500 µm inner diameter). The sensor achieves a 1σ noise equivalent absorption of approximately 0.2 ppmv CH 4 at 1 Hz, while operating at a low drive power of 0.5 mW. A low-cost sub-ppmv CH 4 sensor would make monitoring emissions more affordable and more accessible for many relevant industries, such as the petroleum, agriculture, and waste industries.

Abstract Natural gas vehicles (NGVs) have been promoted in China to mitigate air pollution, yet our measurements and analyses show that NGV growth in China may have significant negative impacts on climate change. We conducted real-world vehicle emission measurements in China and found high methane emissions from heavy-duty NGVs (90% higher than current emission limits). These emissions have been ignored in previous emission estimates, leading to biased results. Applying our observations to life-cycle analyses, we found that switching to NGVs from conventional vehicles in China has led to a net increase in greenhouse gas (GHG) emissions since 2000. With scenario analyses, we also show that the next decade will be critical for China to reverse the trend with the upcoming China VI standard for heavy-duty vehicles. Implementing and enforcing the China VI standard is challenging, and the method demonstrated here can provide critical information regarding the fleet-level CH 4 emissions from NGVs.

Abstract. Mobile laboratory measurements provide information on the distribution of CH4 emissions from point sources such as oil and gas wells, but uncertainties are poorly constrained or justified. Sources of uncertainty and bias in ground-based Gaussian-derived emissions estimates from a mobile platform were analyzed in a combined field and modeling study. In a field campaign where 1009 natural gas sites in Pennsylvania were sampled, a hierarchical measurement strategy was implemented with increasing complexity. Of these sites,  ∼ 93 % were sampled with an average of 2 transects in  < 5 min (standard sampling),  ∼ 5 % were sampled with an average of 10 transects in  < 15 min (replicate sampling) and  ∼ 2 % were sampled with an average of 20 transects in 15–60 min. For sites sampled with 20 transects, a tower was simultaneously deployed to measure high-frequency meteorological data (intensive sampling). Five of the intensive sampling sites were modeled using large eddy simulation (LES) to reproduce CH4 concentrations in a turbulent environment. The LES output and LES-derived emission estimates were used to compare with the results of a standard Gaussian approach. The LES and Gaussian-derived emission rates agreed within a factor of 2 in all except one case; the average difference was 25 %. A controlled release was also used to investigate sources of bias in either technique. The Gaussian method agreed with the release rate more closely than the LES, underlining the importance of inputs as sources of uncertainty for the LES. The LES was also used as a virtual experiment to determine an optimum number of repeat transects and spacing needed to produce representative statistics. Approximately 10 repeat transects spaced at least 1 min apart are required to produce statistics similar to the observed variability over the entire LES simulation period of 30 min. Sources of uncertainty from source location, wind speed, background concentration and atmospheric stability were also analyzed. The largest contribution to the total uncertainty was from atmospheric variability; this is caused by insufficient averaging of turbulent variables in the atmosphere (also known as random errors). Atmospheric variability was quantified by repeat measurements at individual sites under relatively constant conditions. Accurate quantification of atmospheric variability provides a reasonable estimate of the lower bound for emission uncertainty. The uncertainty bounds calculated for this work for sites with  > 50 ppb enhancements were 0.05–6.5q (where q is the emission rate) for single-transect sites and 0.5–2.7q for sites with 10+ transects. More transects allow a mean emission rate to be calculated with better precision. It is recommended that future mobile monitoring schemes quantify atmospheric variability, and attempt to minimize it, under representative conditions to accurately estimate emission uncertainty. These recommendations are general to mobile-laboratory-derived emissions from other sources that can be treated as point sources.

We describe a set of methods for locating and quantifying natural gas leaks using a small unmanned aerial system equipped with a path-integrated methane sensor. The algorithms are developed as part of a system to enable the continuous monitoring of methane, supported by a series of over 200 methane release trials covering 51 release location and flow rate combinations. The system was found throughout the trials to reliably distinguish between cases with and without a methane release down to 2 standard cubic feet per hour (0.011 g/s). Among several methods evaluated for horizontal localization, the location corresponding to the maximum path-integrated methane reading performed best with a mean absolute error of 1.2 m if the results from several flights are spatially averaged. Additionally, a method of rotating the data around the estimated leak location according to the wind is developed, with the leak magnitude calculated from the average crosswind integrated flux in the region near the source location. The system is initially applied at the well pad scale (100–1000 m2 area). Validation of these methods is presented including tests with unknown leak locations. Sources of error, including GPS uncertainty, meteorological variables, data averaging, and flight pattern coverage, are discussed. The techniques described here are important for surveys of small facilities where the scales for dispersion-based approaches are not readily applicable.

Abstract. Satellite remote sensing of the Earth s atmospheric composition usually samples irregularly in space and time, and many applications require spatially and temporally averaging the satellite observations (level 2) to a regular grid (level 3). When averaging level 2 data over a long period to a target level 3 grid that is significantly finer than the sizes of level 2 pixels, this process is referred to as “oversampling”. An agile, physics-based oversampling approach is developed to represent each satellite observation as a sensitivity distribution on the ground, instead of a point or a polygon as assumed in previous methods. This sensitivity distribution can be determined by the spatial response function of each satellite sensor. A generalized 2-D super Gaussian function is proposed to characterize the spatial response functions of both imaging grating spectrometers (e.g., OMI, OMPS, and TROPOMI) and scanning Fourier transform spectrometers (e.g., GOSAT, IASI, and CrIS). Synthetic OMI and IASI observations were generated to compare the errors due to simplifying satellite fields of view (FOVs) as polygons (tessellation error) and the errors due to discretizing the smooth spatial response function on a finite grid (discretization error). The balance between these two error sources depends on the target grid size, the ground size of the FOV, and the smoothness of spatial response functions. Explicit consideration of the spatial response function is favorable for fine-grid oversampling and smoother spatial response. For OMI, it is beneficial to oversample using the spatial response functions for grids finer than ∼16 km. The generalized 2-D super Gaussian function also enables smoothing of the level 3 results by decreasing the shape-determining exponents, which is useful for a high noise level or sparse satellite datasets. This physical oversampling approach is especially advantageous during smaller temporal windows and shows substantially improved visualization of trace gas distribution and local gradients when applied to OMI NO2 products and IASI NH3 products. There is no appreciable difference in the computational time when using the physical oversampling versus other oversampling methods.

Natural gas is an abundant resource across the United States, of which methane (CH4) is the main component. About 2% of extracted CH4 is lost through leaks. The Remote Methane Leak Detector (RMLD)-Unmanned Aerial Vehicle (UAV) system was developed to investigate natural gas fugitive leaks in this study. The system is composed of three major technologies: miniaturized RMLD (mini-RMLD) based on Backscatter Tunable Diode Laser Absorption Spectroscopy (TDLAS), an autonomous quadrotor UAV and simplified quantification and localization algorithms. With a miniaturized, downward-facing RMLD on a small UAV, the system measures the column-integrated CH4 mixing ratio and can semi-autonomously monitor CH4 leakage from sites associated with natural gas production, providing an advanced capability in detecting leaks at hard-to-access sites compared to traditional manual methods. Automated leak characterization algorithms combined with a wireless data link implement real-time leak quantification and reporting. This study placed particular emphasis on the RMLD-UAV system description and the quantification algorithm development based on a mass balance approach. Early data were gathered to test the prototype system and to evaluate the algorithm performance. The quantification algorithm derived in this study tended to underestimate the gas leak rates and yielded unreliable estimations in detecting leaks under 7 × 10 − 6 m3/s (\textasciitilde1 Standard Cubic Feet per Hour (SCFH)). Zero-leak cases can be ascertained via a skewness indicator, which is unique and promising. The influence of the systematic error was investigated by introducing simulated noises, of which Global Positioning System (GPS) noise presented the greatest impact on leak rate errors. The correlation between estimated leak rates and wind conditions were investigated, and steady winds with higher wind speeds were preferred to get better leak rate estimations, which was accurate to approximately 50% during several field trials. High precision coordinate information from the GPS, accurate wind measurements and preferred wind conditions, appropriate flight strategy and the relative steady survey height of the system are the crucial factors to optimize the leak rate estimations.

Significance Our measurements show that tropospheric halogen chemistry has a larger capacity to destroy O 3 and oxidize atmospheric mercury than previously recognized. Halogen chemistry is currently missing in most global and climate models, and is effective at removing O 3 at altitudes where intercontinental O 3 transport occurs. It further helps explain the low O 3 levels in preindustrial times. Public health concerns arise from bioaccumulation of the neurotoxin mercury in fish. Our results emphasize that bromine chemistry in the free troposphere oxidizes mercury at a faster rate, and makes water-soluble mercury available for scavenging by thunderstorms. Naturally occurring bromine in air aloft illustrates global interconnectedness between energy choices affecting mercury emissions in developing nations and mercury deposition in, e.g., Nevada, or the southeastern United States. , Halogens in the troposphere are increasingly recognized as playing an important role for atmospheric chemistry, and possibly climate. Bromine and iodine react catalytically to destroy ozone (O 3 ), oxidize mercury, and modify oxidative capacity that is relevant for the lifetime of greenhouse gases. Most of the tropospheric O 3 and methane (CH 4 ) loss occurs at tropical latitudes. Here we report simultaneous measurements of vertical profiles of bromine oxide (BrO) and iodine oxide (IO) in the tropical and subtropical free troposphere (10°N to 40°S), and show that these halogens are responsible for 34% of the column-integrated loss of tropospheric O 3 . The observed BrO concentrations increase strongly with altitude (∼3.4 pptv at 13.5 km), and are 2–4 times higher than predicted in the tropical free troposphere. BrO resembles model predictions more closely in stratospheric air. The largest model low bias is observed in the lower tropical transition layer (TTL) over the tropical eastern Pacific Ocean, and may reflect a missing inorganic bromine source supplying an additional 2.5–6.4 pptv total inorganic bromine (Br y ), or model overestimated Br y wet scavenging. Our results highlight the importance of heterogeneous chemistry on ice clouds, and imply an additional Br y source from the debromination of sea salt residue in the lower TTL. The observed levels of bromine oxidize mercury up to 3.5 times faster than models predict, possibly increasing mercury deposition to the ocean. The halogen-catalyzed loss of tropospheric O 3 needs to be considered when estimating past and future ozone radiative effects.

Abstract. Cirrus clouds have large yet uncertain impacts on Earth s climate. Ice supersaturation (ISS) – where the relative humidity with respect to ice (RHi) is greater than 100% – is the prerequisite condition of ice nucleation. Here we use 1 Hz (\textasciitilde230 m) in situ, aircraft-based observations from 87° N to 67° S to analyze the spatial characteristics of ice-supersaturated regions (ISSRs). The median length of 1-D horizontal ISSR segments is found to be very small (\textasciitilde1 km), which is 2 orders of magnitude smaller than previously reported. To understand the conditions of these small-scale ISSRs, we compare individual ISSRs with their horizontally adjacent subsaturated surroundings and show that 99% and 73% of the ISSRs are moister and colder, respectively. When quantifying the contributions of water vapor (H2O) and temperature (T) individually, the magnitudes of the differences between the maximum RHi values inside ISSRs (RHimax) and the RHi in subsaturated surroundings are largely derived from the H2O spatial variabilities (by 88%) than from those of T (by 9%). These features hold for both ISSRs with and without ice crystals present. Similar analyses for all RHi horizontal variabilities (including ISS and non-ISS) show strong contributions from H2O variabilities at various T, H2O, pressure (P) and various horizontal scales (\textasciitilde1–100 km). Our results provide a new observational constraint on ISSRs on the microscale (\textasciitilde100 m) and point to the importance of understanding how these fine-scale features originate and impact cirrus cloud formation and the RHi field in the upper troposphere (UT).

Abstract. We demonstrate a compact, open-path, quantum cascade-laser-based atmospheric ammonia sensor operating at 9.06 μm for high-sensitivity, high temporal resolution, ground-based measurements. Atmospheric ammonia (NH3) is a gas-phase precursor to fine particulate matter, with implications for air quality and climate change. Currently, NH3 sensing challenges have led to a lack of widespread in situ measurements. Our open-path sensor configuration minimizes sampling artifacts associated with NH3 surface adsorption onto inlet tubing and reduced pressure sampling cells, as well as condensed-phase partitioning ambiguities. Multi-harmonic wavelength modulation spectroscopy allows for selective and sensitive detection of atmospheric pressure-broadened absorption features. An in-line ethylene reference cell provides real-time calibration (±20% accuracy) and normalization for instrument drift under rapidly changing field conditions. The sensor has a sensitivity and noise-equivalent limit (1σ) of 0.15 ppbv NH3 at 10 Hz, a mass of \textasciitilde 5 kg and consumes \textasciitilde 50 W of electrical power. The total uncertainty in NH3 measurements is 0.20 ppbv NH3 ± 10%, based on a spectroscopic calibration method. Field performance of this open-path NH3 sensor is demonstrated, with 10 Hz time resolution and a large dynamic response for in situ NH3 measurements. This sensor provides the capabilities for improved in situ gas-phase NH3 sensing relevant for emission source characterization and flux measurements.

Dusty Origins The formation of cirrus clouds begins with the production of ice nuclei, on which water vapor then condenses. Cziczo et al. (p. 1320 , published online 9 May) determined the kinds of particles on which cirrus ice crystals form by sublimating samples collected by research aircraft and analyzing the chemical and physical properties of the residual seeds. Most of the seed particles were either mineral dust or metallic. , Mineral dust and metallic particles initiate most ice nucleus condensation during cirrus cloud formation. , Formation of cirrus clouds depends on the availability of ice nuclei to begin condensation of atmospheric water vapor. Although it is known that only a small fraction of atmospheric aerosols are efficient ice nuclei, the critical ingredients that make those aerosols so effective have not been established. We have determined in situ the composition of the residual particles within cirrus crystals after the ice was sublimated. Our results demonstrate that mineral dust and metallic particles are the dominant source of residual particles, whereas sulfate and organic particles are underrepresented, and elemental carbon and biological materials are essentially absent. Further, composition analysis combined with relative humidity measurements suggests that heterogeneous freezing was the dominant formation mechanism of these clouds.

The HIAPER Pole-to-Pole Observations (HIPPO) programme has completed three of five planned aircraft transects spanning the Pacific from 85° N to 67° S, with vertical profiles every approximately 2.2° of latitude. Measurements include greenhouse gases, long-lived tracers, reactive species, O 2 /N 2 ratio, black carbon (BC), aerosols and CO 2 isotopes. Our goals are to address the problem of determining surface emissions, transport strength and patterns, and removal rates of atmospheric trace gases and aerosols at global scales and to provide strong tests of satellite data and global models. HIPPO data show dense pollution and BC at high altitudes over the Arctic, imprints of large N 2 O sources from tropical lands and convective storms, sources of pollution and biogenic CH 4 in the Arctic, and summertime uptake of CO 2 and sources for O 2 at high southern latitudes. Global chemical signatures of atmospheric transport are imaged, showing remarkably sharp horizontal gradients at air mass boundaries, weak vertical gradients and inverted profiles (maxima aloft) in both hemispheres. These features challenge satellite algorithms, global models and inversion analyses to derive surface fluxes. HIPPO data can play a crucial role in identifying and resolving questions of global sources, sinks and transport of atmospheric gases and aerosols.

Abstract. The Total Carbon Column Observing Network (TCCON) produces precise measurements of the column average dry-air mole fractions of CO2, CO, CH4, N2O and H2O at a variety of sites worldwide. These observations rely on spectroscopic parameters that are not known with sufficient accuracy to compute total columns that can be used in combination with in situ measurements. The TCCON must therefore be calibrated to World Meteorological Organization (WMO) in situ trace gas measurement scales. We present a calibration of TCCON data using WMO-scale instrumentation aboard aircraft that measured profiles over four TCCON stations during 2008 and 2009. These calibrations are compared with similar observations made in 2004 and 2006. The results indicate that a single, global calibration factor for each gas accurately captures the TCCON total column data within error.