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International audience; This study evaluates two local-scale atmospheric inversion approaches for the monitoring of methane (CH 4) emissions from industrial sites based on in situ atmospheric CH 4 mole fraction measurements from stationary or mobile sensors. We participated in a two-week campaign of CH 4 controlled-release experiments at TotalEnergies Anomaly Detection Initiatives (TADI) in Lacq, France in October 2019. We analyzed releases from various points within a 40 m × 50 m area with constant rates of 0.16 to 30 g CH 4 s −1 over 25 to 75 mins, using fixed-point and mobile measurements, and testing different inversion configurations with a Gaussian dispersion model. An inlet switching system, combining a limited number (6-7) of high-precision gas analyzers with a higher number (16) of sampling lines, ensured that a sufficient number of fixed measurement points sampled the plume downwind of the sources and the background mole fractions for any wind direction. The inversions using these fixed-point measurements provide release rate estimates with approximately 23%-30% average errors and estimates of the location of the releases with approximately 8-10 m average errors. The inversions using the mobile measurements provide estimates with approximately 20%-30% average errors for the release rates and approximately 30 m average errors for the release locations. The precision of the release rate estimates from both inversion frameworks corresponds to the best estimation This is an open access article under the terms of the Creative Commons Attribution-NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.

Open-path measurements of atmospheric composition provide spatial averages of trace gases that are less sensitive to small-scale variations and the effects of meteorology. In this study we introduce improvements to open-path near-infrared (OP-NIR) Fourier transform spectrometer measurements of CO2 and CH4. In an extended field trial, the OP-NIR achieved measurement repeatability 6 times better for CO2 (0.28 ppm) and 10 times better for CH4 (2.1 ppb) over a 1.55 km one-way path than its predecessor. The measurement repeatability was independent of path length up to 1.55 km, the longest distance tested. Comparisons to co-located in situ measurements under well-mixed conditions characterise biases of 1.41 % for CO2 and 1.61 % for CH4 relative to in situ measurements calibrated to World Meteorological Organisation – Global Atmosphere Watch (WMO-GAW) scales. The OP-NIR measurements can detect signals due to local photosynthesis and respiration, and local point sources of CH4. The OP-NIR is well-suited for deployment in urban or rural settings to quantify atmospheric composition on kilometre scales.

Deploying a dense network of sensors around emitting industrial facilities allows to detect and quantify possible CH4 leaks and monitor the emissions continuously. Designing such a monitoring network with highly precise instruments is limited by the elevated cost of instruments, requirements of power consumption and maintenance. Low cost and low power metal oxide sensor could come handy to be an alternative to deploy this kind of network at a fraction of the cost with satisfactory quality of measurements for such applications.Recent studies have tested Metal Oxide Sensors (MOx) on natural and controlled conditions to measure atmospheric methane concentrations and showed a fair agreement with high precision instruments, such as those from Cavity Ring Down Spectrometers (CRDS). Such results open perspectives regarding the potential of MOx to be employed as an alternative to measure and quantify CH4 emissions on industrial facilities. However, such sensors are known to drift with time, to be highly sensitive to water vapor mole fraction, have a poor selectivity with several known cross-sensitivities to other species and present significant sensitivity environmental factors like temperature and pressure. Different approaches for the derivation of CH4 mole fractions from the MOx signal and ancillary parameter measurements have been employed to overcome these problems, from traditional approaches like linear or multilinear regressions to machine learning (ANN, SVM or Random Forest).Most studies were focused on the derivation of ambient CH4 concentrations under different conditions, but few tests assessed the performance of these sensors to capture CH4 variations at high frequency, with peaks of elevated concentrations, which corresponds well with the signal observed from point sources in industrial sites presenting leakage and isolated methane emission. We conducted a continuous controlled experiment over four months (from November 2019 to February 2020) in which three types of MOx Sensors from Figaro® measured high frequency CH4 peaks with concentrations varying between atmospheric background levels up to 24 ppm at LSCE, Saclay, France. We develop a calibration strategy including a two-step baseline correction and compared different approaches to reconstruct CH4 spikes such as linear, multilinear and polynomial regression, and ANN and random forest algorithms. We found that baseline correction in the pre-processing stage improved the reconstruction of CH4 concentrations in the spikes. The random forest models performed better than other methods achieving a mean RMSE = 0.25 ppm when reconstructing peaks amplitude over windows of 4 days. In addition, we conducted tests to determine the minimum amount of data required to train successful models for predicting CH4 spikes, and the needed frequency of re-calibration / re-training under these controlled circumstances. We concluded that for a target RMSE Our study presents a new approach to process and reconstruct observations from low cost CH4 sensors and highlights its potential to quantify high concentration releases in industrial facilities.

The efficient and precise monitoring (detection, localization, and quantification) of fugitive methane (CH4) emissions is essential in preventing and mitigating greenhouse gas (GHG) emissions from oil and gas industrial facilities and landfills. Various strategies of mole fraction sampling within or in the vicinity of the sites and of atmospheric inversions have been developed for such a monitoring. Many studies have ensured the constant improvement of instrumentation, of measurement strategies and atmospheric inversion techniques.In this context, we participated in two controlled-release experiments at the TOTAL Anomaly Detection Initiatives (TADI) test site (Lacq, France) in October 2018 and 2019, dedicated to evaluate the ability of different local-scale atmospheric measurement and inverse modeling systems to localize and quantify point sources. We also conducted a series of 18 campaigns to regularly quantify methane emissions from the active “Butte-Bellot” landfill (about 35 km south-east of Paris) since 2018. We developed and applied different inversion approaches to process mobile or fixed-point measurements, which, in both cases, rely on a Gaussian dispersion model to simulate the atmospheric plume from the potential source location or mole fraction sensitivity at the measurement time and location to emissions at the potential source locations.The series of CH4 and carbon dioxide (CO2) controlled releases in TADI covered a wide range of release rates (~0.1 to 200 gCH4/s and 0.2 to 200 gCO2/s) and durations from 4 to 8 minutes (brief) to 25 to 75 minutes (longer). During the corresponding campaigns, we conducted both near-surface mobile and fixed-point (~2-4 m height) in situ atmospheric measurements based on Picarro CRDS, LGR (MGGA and UGGA), and LI-COR (LI-7810) instruments. Both inversions based on mobile measurements and those based on the fixed-point measurements provide estimates with a 20-30% average error for the CH4 and CO2 release rates, whatever the duration of the releases. The use of fixed-point measurements during long releases allow for a more precise localization of sources with an average location error of ~8m.The analysis of the CH4 mobile measurements at the “Butte-Bellot” landfill reveals the difficulties in exploiting measurements close to such a site with diffuse emissions whose spatial distribution is difficult to characterize, heterogeneous and highly variable in time. The series of estimates of the total CH4 emissions from the site based on remote mobile plume cross-sections, based on atmospheric inversions, are discussed.This presentation will highlight positive perspectives opened by the proposed inversion approaches and by our results and discuss options for further improvements when processing both types of measurements.

Methane (CH4) is a powerful greenhouse gas which plays a major role in climate change. The accurate monitoring of emissions from industrial facilities is needed to ensure efficient emission mitigation strategies. Local-scale atmospheric inversions are increasingly being used to provide estimates of the rates and/or locations of CH4 sources from industrial sites. They rely on local-scale atmospheric dispersion models, CH4 measurements and inversion approaches. Gaussian plume models have often been used for local-scale atmospheric dispersion modelling and inversions of emissions, because of their simplicity and good performance when used in a flat terrain and relatively constant mean wind conditions. However, even in such conditions, failure to account for wind and mole fraction variability can limit the ability to exploit the full potential of these measurements at high frequency.We study whether the accuracy of inversions can be increased by the use of more complex dispersion models. Our assessments are based on the analysis of 25 to 75-min CH4 controlled releases during a one-week campaign in October 2019 at the TOTAL’s TADI operative platform in Lacq, France (in a flat area). During this campaign, for each controlled release, we conducted near-surface in situ measurements of CH4 mole fraction from both a mobile vehicle and a circle of fixed points around the emission area. Our inversions based on a Gaussian model and either the mobile or fixed-point measurements both provided estimates of the release rates with 20-30% precision. Here we focus on comparisons between modeling and inversion results when using this Gaussian plume model, a Lagrangian model “GRAL” and a Gaussian puff model. The parameters for the three models are based on high-frequency meteorological values from a single stationary 3D sonic anemometer. GRAL should have relatively good skills under low-wind speed conditions. The Gaussian puff is a light implementation of time-dependent modeling and can be driven by high-frequency meteorological data. The performance of these dispersion models is evaluated with various metrics from the observation field that are relevant for the inversion. These analyses lead to the exploration of new types of definitions of the observational constraint for the inversions with the Gaussian puff model, when using the timeseries from fixed measurement points. The definitions explore a range of metrics in the time domain as well as in the frequency domain.Eventually, the Lagrangian model does not outperform the Gaussian plume model in these experiments, its application being notably limited by the short scales of the transport characteristics. On the other hand, the Gaussian puff model provides promising results for the inversion, in particular, in terms of comparison between the simulated and observed timeseries for fixed stations. Its performance when driven by a spatially uniform wind field is an incentive to explore the use of meteorological data from several sonic stations to parameterize its configuration. The fixed-point measurements are shown to allow for more robust inversions of the source location than the mobile measurements, with an average source localization error of the order of 10 m.

Continued developments in instrumentation and modeling have driven progress in monitoring methane (CH4) emissions at a range of spatial scales. The sites that emit CH4 such as landfills, oil and gas extraction or storage infrastructure, intensive livestock farms account for a large share of global emissions, and need to be monitored on a continuous basis to verify the effectiveness of reductions policies. Low cost sensors are valuable to monitor methane (CH4) around such facilities because they can be deployed in a large number to sample atmospheric plumes and retrieve emission rates using dispersion models. Here we present two tests of three different versions of Figaro&reg, TGS tin-oxide sensors for estimating CH4 concentrations variations, at levels similar to current atmospheric values, with a sought accuracy of 0.1 to 0.2 ppm. In the first test, we characterize the variation of the resistance of the tin-oxide semi-conducting sensors to controlled levels of CH4, H2O and CO in the laboratory, to analyze cross-sensitivities. In the second test, we reconstruct observed CH4 variations in a room, that ranged from 1.9 and 2.4 ppm during a three month experiment from observed time series of resistances and other variables. To do so, a machine learning model is trained against true CH4 recorded by a high precision instrument. The machine-learning model using 30% of the data for training reconstructs CH4 within the target accuracy of 0.1 ppm only if training variables are representative of conditions during the testing period. The model-derived sensitivities of the sensors resistance to H2O compared to CH4 are larger than those observed under controlled conditions, which deserves further characterization of all the factors influencing the resistance of the sensors.

We present a local-scale atmospheric inversion framework to estimate the location and rate of methane (CH4) and carbon dioxide (CO2) releases from point sources. It relies on mobile near-ground atmospheric CH4 and CO2 mole fraction measurements across the corresponding atmospheric plumes downwind the sources, on high-frequency meteorological measurements, and a Gaussian plume dispersion model. It exploits the spread of the positions of individual plume cross-sections and the integrals of the gas mole fractions above the background within these plume cross-sections to infer the position and rate of the releases. It has been developed and applied to provide estimates of brief controlled CH4 and CO2 point source releases during a one-week campaign in October 2018 at the TOTAL's experimental platform TADI in Lacq, France. These releases lasted typically 4 to 8 minutes and covered a wide range of rates (0.3 to 200 gCH4/s and 0.2 to 150 gCO2/s) to test the capability of atmospheric monitoring systems to react fast to emergency situations in industrial facilities. It also allowed testing their capability to provide precise emission estimates for the application of climate change mitigation strategies. However, the low and highly varying wind conditions during the releases added difficulties to the challenge of characterizing the atmospheric transport over the very short duration of the releases. We present our series of measurements of CH4 and CO2 mole fractions using instruments onboard a car that drives along the roads ~50 to 150 m downwind the 40 m × 60 m area of controlled releases for each of the releases and the results from the inversions of the release locations and rates. The comparisons of these results to the actual position and rate of the controlled release indicate a 20 %–30 % average error on the release rates and a ~30–40 m errors in the estimates of the release locations. These results are shown to be promising especially since better results could be expected for longer releases and under meteorological conditions more favorable to local scale dispersion modeling.

Wollongong, Australia is an urban site at the intersection of anthropogenic, biomass burning, biogenic and marine sources of atmospheric trace gases. The location offers a valuable opportunity to study drivers of atmospheric composition in the Southern Hemisphere. Here, a record of surface carbon monoxide (CO), methane (CH4) and carbon dioxide (CO2) was measured with an in situ Fourier transform infrared trace gas analyser between April 2011 and August 2014. Clean air was found to arrive at Wollongong in approximately 10% of air masses. Biomass burning influence was evident in the average annual cycle of clean air CO during austral spring. A significant negative short-term trend was found in clean air CO (−1.5 nmol mol−1 a−1), driven by a reduction in northern Australian biomass burning. Significant short-term positive trends in clean air CH4 (5.4 nmol mol−1 a−1) and CO2 (1.9 μmol mol−1 a−1) were consistent with the long-term global average trends. Polluted Wollongong air was investigated using wind-direction/wind-speed clustering, which revealed major influence from local urban and industrial sources from the south. High values of CH4, with anthropogenic ΔCH4/ΔCO2 enhancement ratio signatures, originated from the northwest, in the direction of local coal mining. A pollution climatology was developed for the region using back trajectory analysis and ΔO3/ΔCO enhancement ratios. Ozone production environments in austral spring and summer were associated with anticyclonic meteorology on the east coast of Australia, while ozone depletion environments in autumn and winter were associated with continental transport, or fast moving trajectories from southern latitudes. This implies the need to consider meteorological conditions when developing policies for controlling air quality.

This study presents two methods for estimating methane emissions from a waste water treatment plant (WWTP) along with results from a measurement campaign at a WWTP in Valence, France. These methods, chamber measurements and tracer release, rely on Fourier Transform Infrared (FTIR) spectroscopy and Cavity Ring Down Spectroscopy (CRDS) instruments. We show that the tracer release method is suitable to quantify facility- and some process-scale emissions, while the chamber measurements, provide insight into individual process emissions. Uncertainties for the two methods are described and discussed. Applying the methods to CH4 emissions of the WWTP, we confirm that the open basins are not a major source of CH4 on the WWTP (about 10% of the total emissions), but that the pretreatment and sludge treatment are the main emitters. Overall, the waste water treatment plant represents a small part (about 1.5%) of the methane emissions of the city of Valence and its surroundings, which is lower than the national inventories.

We thoroughly evaluate the performance of a multi-species, in situ Fourier transform infrared (FTIR) analyser with respect to high-accuracy needs for greenhouse gas monitoring networks. The in situ FTIR analyser is shown to measure CO2, CO, CH4 and N2O mole fractions continuously, all with better reproducibility than the inter-laboratory compatibility (ILC) goals, requested by the World Meteorological Organization (WMO) for the Global Atmosphere Watch (GAW) programme. Simultaneously determined δ13CO2 reaches reproducibility as good as 0.03‰. Second-order dependencies between the measured components and the thermodynamic properties of the sample, (temperature, pressure and flow rate) and the cross sensitivities among the sample constituents are investigated and quantified. We describe an improved sample delivery and control system that minimises the pressure and flow rate variations, making post-processing corrections for those quantities non-essential. Temperature disequilibrium effects resulting from the evacuation of the sample cell are quantified and improved by the usage of a faster temperature sensor. The instrument has proven to be linear for all measured components in the ambient concentration range. The temporal stability of the instrument is characterised on different time scales. Instrument drifts on a weekly time scale are only observed for CH4 (0.04 nmol mol−1 day−1) and δ13CO2 (0.02‰ day−1). Based on 10 months of continuously collected quality control measures, the long-term reproducibility of the instrument is estimated to ±0.016 μmol mol−1 CO2, ±0.03‰ δ13CO2, ±0.14 nmol mol−1 CH4, ±0.1 nmol mol−1 CO and ±0.04 nmol mol−1 N2O. We propose a calibration and quality control scheme with weekly calibrations of the instrument that is sufficient to reach WMO-GAW inter-laboratory compatibility goals.

Concern in recent decades about human impacts on Earth's climate has led to the need for improved and expanded measurement capabilities of greenhouse gases in the atmosphere. In this paper we describe in detail an in situ trace gas analyser based on Fourier Transform Infrared (FTIR) spectroscopy that is capable of simultaneous and continuous measurements of carbon dioxide (CO2), methane (CH4), carbon monoxide (CO), nitrous oxide (N2O) and 13C in CO2 in air with high precision. High accuracy is established by reference to measurements of standard reference gases. Stable water isotopes can also be measured in undried airstreams. The analyser is automated and allows unattended operation with minimal operator intervention. Precision and accuracy meet and exceed the compatibility targets set by the World Meteorological Organisation – Global Atmosphere Watch for baseline measurements in the unpolluted troposphere for all species except 13C in CO2. The analyser is mobile and well suited to fixed sites, tower measurements, mobile platforms and campaign-based measurements. The isotopic specificity of the optically-based technique and analysis allows its application in isotopic tracer experiments, for example in tracing variations of 13C in CO2 and 15N in N2O. We review a number of applications illustrating use of the analyser in clean air monitoring, micrometeorological flux and tower measurements, mobile measurements on a train, and soil flux chamber measurements.

1. A necessary component of implementing a successful marine reserve is the quantification of the biological resources that fall under its protection. Without such an initial assessment, the future effects of the reserve on the local habitat and biotic community cannot be quantified and will remain the subject of debate. 2. This study provides such a baseline assessment of fish diversity and habitat types within a recently enlarged marine reserve. Buck Island Reef National Monument, US Virgin Islands, was recently enlarged from approximately 4 km2 to over 76 km2. Areas of sand, seagrass, and hard-bottom under protection were increased from 0.29 km2, 0.47 km2, and 1.96 km2 to 2.70 km2, 2.89 km2, and 18.30 km2 respectively when the Monument was expanded. A 53 km2 area of pelagic/deep-water habitat with unknown bottom type is now also protected by the Monument. 3. Visual counts of fish within 25×4 m2 transects conducted during the day were used to assess fish community structure and habitat utilization patterns. Species richness, diversity, assemblage structure, and fish density were evaluated and compared among sand, seagrass, and hard-bottom habitats. Hard-bottom sites had over twice the mean species richness and diversity as sand and seagrass sites, and several times greater mean fish density. 4. Quantification of the fish community in pelagic and deep-water habitats within the reserve is recommended to provide a more comprehensive assessment of the offshore areas of the reserve. Fish numbers, size, and diversity outside the reserve boundaries must also be evaluated to allow quantification of the effects of the marine reserve on the adjacent fish communities. Copyright © 2004 John Wiley & Sons, Ltd.

Concern in recent decades about human impacts on Earth's climate has led to the need for improved and expanded measurement capabilities for greenhouse gases in the atmosphere. In this paper we describe in detail an in situ trace gas analyser based on Fourier Transform Infrared (FTIR) spectroscopy that is capable of simultaneous and continuous measurements of carbon dioxide (CO2), methane (CH4), carbon monoxide (CO), nitrous oxide (N2O) and 13C in CO2 in air with high precision and accuracy. Stable water isotopes can also be measured in undried airstreams. The analyser is automated and allows unattended operation with minimal operator intervention. Precision and accuracy meet and exceed the compatibility targets set by the World Meteorological Organisation – Global Atmosphere Watch Programme for baseline measurements in the unpolluted troposphere for all species except 13C in CO2. The analyser is mobile and well suited to fixed sites, tower measurements, mobile platforms and campaign-based measurements. The isotopic specificity of the optically-based technique and analysis allows application of the analyser in isotopic tracer experiments, for example 13C in CO2 and 15N in N2O. We review a number of applications illustrating use of the analyser in clean air monitoring, micrometeorological flux and tower measurements, mobile measurements on a train, and soil flux chamber measurements.

A Bayesian inversion technique to determine the location and strength of trace gas emissions from a point source in open air is presented. It was tested using atmospheric measurements of N(2)O and CO(2) released at known rates from a source located within an array of eight evenly spaced sampling points on a 20-m radius circle. The analysis requires knowledge of concentration enhancement downwind of the source and the normalized, three-dimensional distribution (shape) of concentration in the dispersion plume. The influence of varying background concentrations of ∼1% for N(2)O and ∼10% for CO(2) was removed by subtracting upwind concentrations from those downwind of the source to yield only concentration enhancements. Continuous measurements of turbulent wind and temperature statistics were used to model the dispersion plume. The analysis localized the source to within 0.8 m of the true position and the emission rates were determined to better than 3% accuracy. This technique will be useful in assurance monitoring for geological storage of CO(2) and for applications requiring knowledge of the location and rate of fugitive emissions.