Anthropogenic methane plume detection from point sources in the Paris megacity area and characterization of their δ¹³C signature

International audienceMitigating anthropogenic methane emissions is one of the available tools for reaching the near term objectives of the Paris Agreement. Characterizing the isotopic signature of the methane plumes emitted by these sources is needed to improve the quantification of methane sources at the regional scale. Urbanized and industrialized regions such as the Paris megacity are key places to better characterize anthropogenic methane sources. In this study, we present the results of the first mobile surveys in the Paris region, assessing methane point sources from 10 landfills (which in the regional inventory are the main emission sector of methane in the region), 5 gas storage sites (supplying Paris) and 1 waste water treatment (WWT) facility (Europe’s largest, second worldwide). Local atmospheric methane concentration (or mixing ratio) enhancements in the source plumes were quantified and their d13C in CH4 (further noted d13CH4) signature characterized. Among the 10 landfills sampled, at 6 of them we detected atmospheric methane local enhancements ranging from 0.8 to 8.5 parts per million (ppm) with d13CH4 signatures between -63.7 ± 0.3 permils (‰) to - 58.2 ± 0.3 ‰. Among the 5 gas storage sites surveyed, we could observe that 3 of them were leaking methane with local methane concentration enhancements ranging from 0.8 to 8.1 ppm and d13CH4 signatures spanning from -43.4 ± 0.5 ‰ to -33.8 ± 0.4 ‰. Dutch gas with a d13CH4 signature of -33.8 ± 0.4 ‰ (typical of thermogenic gas) was also likely identified. The WWT site emitted local methane enhancements up to 4.0 ppm. For this site, two d13CH4 signatures were determined as -51.9 ± 0.2 ‰ and -55.3 ± 0.1 ‰, typical of a biogenic origin. About forty methane plumes were also detected in the Paris city, leading to local concentration enhancements whose origin was in two cases interpreted as natural gas leaks thanks to their isotopic composition. However, such enhancements were much less common than in cities of North America. More isotopic surveys are needed to discriminate whether such urban methane enhancements are outcoming from gas line leaks and sewer network emanations. Furthermore, our results lead us to the conclusion that the regional emissions inventory could underestimate methane emissions from the WWT sector. Further campaigns are needed to assess the variability and seasonality of the sources and of their isotopic signature, and to estimate their emissions using methods independent of the inventory

Remote sensing of aerosols by using polarized, directional and spectral measurements within the A-Train: the PARASOL mission

Instruments dedicated to aerosol monitoring are recently available and the POLDER (POLarization and Directionality of the Earth's Reflectances) instrument on board the PARASOL (Polarization & Anisotropy of Reflectances for Atmospheric Sciences coupled with Observations from a Lidar) mission is one of them. By measuring the spectral, angular and polarization properties of the radiance at the top of the atmosphere, in coordination with the other A-Train instruments, PARASOL provides the aerosol optical depths (AOD) as well as several optical and microphysical aerosol properties. The instrument, the inversion schemes and the list of aerosol parameters are described. Examples of retrieved aerosol parameters are provided as well as innovative approaches and further inversion techniques

Faint young Sun paradox remains

The Sun was fainter when the Earth was young, but the climate was generally at least as warm as today; this is known as the `faint young Sun paradox'. Rosing et al. [1] claim that the paradox can be resolved by making the early Earth's clouds and surface less reflective. We show that, even with the strongest plausible assumptions, reducing cloud and surface albedos falls short by a factor of two of resolving the paradox. A temperate Archean climate cannot be reconciled with the low level of CO2 suggested by Rosing et al. [1]; a stronger greenhouse effect is needed.Comment: 3 pages, no figures. In press in Nature. v2 corrects typo in author list in original submissio

A synthesis of carbon dioxide emissions from fossil-fuel combustion

This synthesis discusses the emissions of carbon dioxide from fossil-fuel combustion and cement production. While much is known about these emissions, there is still much that is unknown about the details surrounding these emissions. This synthesis explores our knowledge of these emissions in terms of why there is concern about them; how they are calculated; the major global efforts on inventorying them; their global, regional, and national totals at different spatial and temporal scales; how they are distributed on global grids (i.e., maps); how they are transported in models; and the uncertainties associated with these different aspects of the emissions. The magnitude of emissions from the combustion of fossil fuels has been almost continuously increasing with time since fossil fuels were first used by humans. Despite events in some nations specifically designed to reduce emissions, or which have had emissions reduction as a byproduct of other events, global total emissions continue their general increase with time. Global total fossil-fuel carbon dioxide emissions are known to within 10 % uncertainty (95 % confidence interval). Uncertainty on individual national total fossil-fuel carbon dioxide emissions range from a few percent to more than 50 %. This manuscript concludes that carbon dioxide emissions from fossil-fuel combustion continue to increase with time and that while much is known about the overall characteristics of these emissions, much is still to be learned about the detailed characteristics of these emissions

Ice crystal shapes in cirrus clouds derived from POLDER-1/ADEOS-1.

International audienceThis paper discusses the retrieval of ice crystal shapes of cirrus clouds on a global scale using observations collected with POLDER-1 (POLarization and Directionality of the Earth Reflectance) onboard the ADEOS-1 platform. The retrieval is based on polarized bidirectional observations made by POLDER. First, normalized polarized radiances are simulated for cirrus clouds composed of ice crystals that differ in shape and are randomly oriented in space. Different values of cloud optical depths, viewing geometries and solar zenith angles are used in the simulations. This sensitivity study shows that the normalized polarized radiance is highly sensitive to the shape of the scatterers for specific viewing geometries, and that it saturates after a few scattering events, which makes it rapidly independent of the optical depth of the cirrus clouds. Next, normalized polarized radiance observations obtained by POLDER have been selected, based on suitable viewing geometries and on the occurrence of thick cirrus clouds composed of particles randomly oriented in space. For various ice crystal shapes these observations are compared with calculated values pertaining to the same geometry, in order to determine the shape that best reproduces the measurements. The method is tested fully for the POLDER data collected on January 12, 1997. Thereafter, it is applied to six periods of 6 days of observations obtained in January, February, March, April, May, and June 1997. This study shows that the particle shape is highly variable with location and season, and that polycrystals and hexagonal columns are dominant at low latitudes, whereas hexagonal plates occur more frequently at high latitudes

Declining uncertainty in transient climate response as CO2 forcing dominates future climate change

Carbon dioxide has exerted the largest portion of radiative forcing and surface temperature change over the industrial era, but other anthropogenic influences have also contributed. However, large uncertainties in total forcing make it difficult to derive climate sensitivity from historical observations. Anthropogenic forcing has increased between the Fourth and Fifth Assessment Reports of the Intergovernmental Panel of Climate Change (IPCC; refs,), although its relative uncertainty has decreased. Here we show, based on data from the two reports, that this evolution towards lower uncertainty can be expected to continue into the future. Because it is easier to reduce air pollution than carbon dioxide emissions and because of the long lifetime of carbon dioxide, the less uncertain carbon dioxide forcing is expected to become increasingly dominant. Using a statistical model, we estimate that the relative uncertainty in anthropogenic forcing of more than 40% quoted in the latest IPCC report for 2011 will be almost halved by 2030, even without better scientific understanding. Absolute forcing uncertainty will also decline for the first time, provided projected decreases in aerosols occur. Other factors being equal, this stronger constraint on forcing will bring a significant reduction in the uncertainty of observation-based estimates of the transient climate response, with a 50% reduction in its uncertainty range expected by 2030

Near-real-time monitoring of global CO₂ emissions reveals the effects of the COVID-19 pandemic

The COVID-19 pandemic is impacting human activities, and in turn energy use and carbon dioxide (CO2) emissions. Here we present daily estimates of country-level CO2 emissions for different sectors based on near-real-time activity data. The key result is an abrupt 8.8% decrease in global CO2 emissions (−1551 Mt CO2) in the first half of 2020 compared to the same period in 2019. The magnitude of this decrease is larger than during previous economic downturns or World War II. The timing of emissions decreases corresponds to lockdown measures in each country. By July 1st, the pandemic’s effects on global emissions diminished as lockdown restrictions relaxed and some economic activities restarted, especially in China and several European countries, but substantial differences persist between countries, with continuing emission declines in the U.S. where coronavirus cases are still increasing substantially

Can we use atmospheric CO₂ measurements to verify emission trends reported by cities? Lessons from a 6-year atmospheric inversion over Paris

Existing CO2 emissions reported by city inventories usually lag in real-time by a year or more and are prone to large uncertainties. This study responds to the growing need for timely and precise estimation of urban CO2 emissions to support present and future mitigation measures and policies. We focus on the Paris metropolitan area, the largest urban region in the European Union and the city with the densest atmospheric CO2 observation network in Europe. We performed long-term atmospheric inversions to quantify the citywide CO2 emissions, i.e., fossil fuel as well as biogenic sources and sinks, over 6 years (2016–2021) using a Bayesian inverse modeling system. Our inversion framework benefits from a novel near-real-time hourly fossil fuel CO2 emission inventory (Origins.earth) at 1 km spatial resolution. In addition to the mid-afternoon observations, we attempt to assimilate morning CO2 concentrations based on the ability of the Weather Research and Forecasting model with Chemistry (WRF-Chem) transport model to simulate atmospheric boundary layer dynamics constrained by observed layer heights. Our results show a long-term decreasing trend of around 2 % ± 0.6 % per year in annual CO2 emissions over the Paris region. The impact of the COVID-19 pandemic led to a 13 % ± 1 % reduction in annual fossil fuel CO2 emissions in 2020 with respect to 2019. Subsequently, annual emissions increased by 5.2 % ± 14.2 % from 32.6 ± 2.2 Mt CO2 in 2020 to 34.3 ± 2.3 Mt CO2 in 2021. Based on a combination of up-to-date inventories, high-resolution atmospheric modeling and high-precision observations, our current capacity can deliver near-real-time CO2 emission estimates at the city scale in less than a month, and the results agree within 10 % with independent estimates from multiple city-scale inventories.</p

A review of applying second-generation wavelets for noise removal from remote sensing data.

The processing of remotely sensed data includes compression, noise reduction, classification, feature extraction, change detection and any improvement associated with the problems at hand. In the literature, wavelet methods have been widely used for analysing remote sensing images and signals. The second-generation of wavelets, which is designed based on a method called the lifting scheme, is almost a new version of wavelets, and its application in the remote sensing field is fresh. Although first-generation wavelets have been proven to offer effective techniques for processing remotely sensed data, second-generation wavelets are more efficient in some respects, as will be discussed later. The aim of this review paper is to examine all existing studies in the literature related to applying second-generation wavelets for denoising remote sensing data. However, to make a better understanding of the application of wavelet-based denoising methods for remote sensing data, some studies that apply first-generation wavelets are also presented. In the part of hyperspectral data, there is a focus on noise removal from vegetation spectrum