CH4 emission estimates from an active landfill site inferred from a combined approach of CFD modelling and in situ FTIR measurements

Globally, the waste sector contributes to nearly a fifth of anthropogenic methane emitted to the atmosphere and is the second largest source of methane in the UK. In recent years great improvements to reduce those emissions have been achieved by installation of methane recovery systems at landfill sites and subsequently methane emissions reported in national emission inventories have been reduced. Nevertheless, methane emissions of landfills remain uncertain and quantification of emission fluxes is essential to verify reported emission inventories and to monitor changes in emissions. Here we present a new approach for methane emission quantification from a complex source like a landfill site by applying a Computational Fluid Dynamics (CFD) model to calibrated in situ measurements of methane as part of a field campaign at a landfill site near Ipswich, UK, in August 2014. The methane distribution for different meteorological scenarios is calculated with the CFD model and compared to methane mole fractions measured by an in situ Fourier Transform Infrared (FTIR) spectrometer downwind of the prevailing wind direction. Assuming emissions only from the active site, a mean daytime flux of 0.83 mg m−2 s−1, corresponding to 53.26 kg h−1, was estimated. The addition of a secondary source area adjacent to the active site, where some methane hotspots were observed, improved the agreement between the simulated and measured methane distribution. As a result, the flux from the active site was reduced slightly to 0.71 mg m−2 s−1 (45.56 kg h−1), at the same time an additional flux of 0.32 mg m−2 s−1 (30.41 kg h−1) was found from the secondary source area. This highlights the capability of our method to distinguish between different emission areas of the landfill site, which can provide more detailed information about emission source apportionment compared to other methods deriving bulk emissions

The UV-A and visible solar irradiance spectrum: inter-comparison of absolutely calibrated, spectrally medium resolution solar irradiance spectra from balloon- and satellite-borne measurements

International audienceWithin the framework of the ENVISAT/-SCIAMACHY satellite validation, solar irradiance spectra are absolutely measured at moderate resolution in the UV/visible spectral range (in the UV from 316.7–418 nm and the visible from 400–652 nm at a full width half maximum resolution of 0.55 nm and 1.48 nm, respectively) from aboard the azimuth-controlled LPMA/DOAS balloon gondola at around 32 km balloon float altitude. After accounting for the atmospheric extinction due to Rayleigh scattering and gaseous absorption (O3, and NO2), the measured solar spectra are compared with previous observations. Our solar irradiance is +1.6% larger than the re-calibrated Kurucz et al. (1984) solar spectrum (Fontenla et al., 1999, called MODTRAN 3.5) in the visible spectral range (435–650 nm), +1.5% larger in the (370–415 nm) wavelength interval, but -4% smaller in the UV spectral range (316.7–370 nm), when the Kurucz spectrum is convolved to the spectral resolution of our instrument. The same comparison with the SOLSPEC solar spectrum (Thuillier et al., 1997, 1998a, b) confirms the somewhat larger solar irradiance (+1.7%) measured by the balloon instrument from 435–500 nm, but not from 500–650 nm, where the SOLSPEC is -1.3% lower than MODTRAN 3.5. Comparison of the SCIAMACHY solar spectrum from channels 1 to 4 (– re-calibrated by the University of Bremen –) with MODTRAN 3.5 indicates an agreement of +0.2% in the visible spectral range (435–585 nm). With this calibration, the SCIAMACHY solar spectrum is congruent with the balloon observations (-1%) in the 316.7–370 nm wavelength range, but both are up to -5%/-3% smaller than MODTRAN 3.5 and SOLSPEC, respectively. In agreement with findings of Skupin et al. (2002) our study emphasizes that the present ESA SCIAMACHY level 1 calibration is systematically +15% larger in the considered wavelength intervals when compared to all available other solar irradiance measurements

Methane emissions are predominantly responsible for record-breaking atmospheric methane growth rates in 2020 and 2021

The global atmospheric methane growth rates reported by NOAA for 2020 and 2021 are the largest since systematic measurements began in 1983. To explore the underlying reasons for these anomalous growth rates, we use newly available methane data from the Japanese Greenhouse gases Observing SATellite (GOSAT) to estimate methane surface emissions. Relative to baseline values in 2019, we find that a significant global increase in methane emissions of 27.0 ± 11.3 and 20.8 ± 11.4 Tg is needed to reproduce observed atmospheric methane in 2020 and 2021, respectively, assuming fixed climatological values for OH. We see the largest annual increases in methane emissions during 2020 over Eastern Africa (14 ± 3 Tg), tropical Asia (3 ± 4 Tg), tropical South America (5 ± 4 Tg), and temperate Eurasia (3 ± 3 Tg), and the largest reductions are observed over China (−6 ± 3 Tg) and India (−2 ± 3 Tg). We find comparable emission changes in 2021, relative to 2019, except for tropical and temperate South America where emissions increased by 9 ± 4 and 4 ± 3 Tg, respectively, and for temperate North America where emissions increased by 5 ± 2 Tg. The elevated contributions we saw in 2020 over the western half of Africa (−5 ± 3 Tg) are substantially reduced in 2021, compared to our 2019 baseline. We find statistically significant positive correlations between anomalies of tropical methane emissions and groundwater, consistent with recent studies that have highlighted a growing role for microbial sources over the tropics. Emission reductions over India and China are expected in 2020 due to the Covid-19 lockdown but continued in 2021, which we do not currently understand. To investigate the role of reduced OH concentrations during the Covid-19 lockdown in 2020 on the elevated atmospheric methane growth in 2020–2021, we extended our inversion state vector to include monthly scaling factors for OH concentrations over six latitude bands. During 2020, we find that tropospheric OH is reduced by 1.4 ± 1.7 % relative to the corresponding 2019 baseline value. The corresponding revised global growth of a posteriori methane emissions in 2020 decreased by 34 % to 17.9 ± 13.2 Tg, relative to the a posteriori value that we inferred using fixed climatological OH values, consistent with sensitivity tests using the OH climatology inversion using reduced values for OH. The counter statement is that 66 % of the global increase in atmospheric methane during 2020 was due to increased emissions, particularly from tropical regions. Regional flux differences between the joint methane–OH inversion and the OH climatology inversion in 2020 are typically much smaller than 10 %. We find that OH is reduced by a much smaller amount during 2021 than in 2020, representing about 10 % of the growth of atmospheric methane in that year. Therefore, we conclude that most of the observed increase in atmospheric methane during 2020 and 2021 is due to increased emissions, with a significant contribution from reduced levels of OH.</p

Balloon-borne stratospheric BrO measurements: comparison with Envisat/SCIAMACHY BrO limb profiles

International audienceFor the first time, results of four stratospheric BrO profiling instruments, are presented and compared with reference to the SLIMCAT 3-dimensional chemical transport model (3-D CTM). Model calculations are used to infer a BrO profile validation set, measured by 3 different balloon sensors, for the new Envisat/SCIAMACHY (ENVIronment SATellite/SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY) satellite instrument. The balloon observations include (a) balloon-borne in situ resonance fluorescence detection of BrO (Triple), (b) balloon-borne solar occultation DOAS measurements (Differential Optical Absorption Spectroscopy) of BrO in the UV, and (c) BrO profiling from the solar occultation SAOZ (Systeme d'Analyse par Observation Zenithale) balloon instrument. Since stratospheric BrO is subject to considerable diurnal variation and none of the measurements are performed close enough in time and space for a direct comparison, all balloon observations are considered with reference to outputs from the 3-D CTM. The referencing is performed by forward and backward air mass trajectory calculations to match the balloon with the satellite observations. The diurnal variation of BrO is considered by 1-D photochemical model calculation along the trajectories. The 1-D photochemical model is initialised with output data of the 3-D model with additional constraints on the vertical transport, the total amount and photochemistry of stratospheric bromine as given by the various balloon observations. Total [Bry]=(20.1±2.5) pptv obtained from DOAS BrO observations at mid-latitudes in 2003, serves as an upper limit of the comparison. Most of the balloon observations agree with the photochemical model predictions within their given error estimates. First retrieval exercises of BrO limb profiling from the SCIAMACHY satellite instrument on average agree to around 20% with the photochemically-corrected balloon observations of the remote sensing instruments (SAOZ and DOAS). An exception is the in situ Triple profile, in which the balloon and satellite data mostly does not agree within the given errors. In general, the satellite measurements show systematically higher values below 25 km than the balloon data and a change in profile shape above about 25 km

Sustainable protected areas: Synergies between biodiversity conservation and socioeconomic development

Reconciling conservation and socioeconomic development goals is key to sustainability but remains a source of fierce debate. Protected areas (PAs) are believed to play an essential role in achieving these seemingly conflicting goals. Yet, there is limited evidence as to whether PAs are actually achieving the two goals simultaneously.Here, we investigate when and to what extent synergies or trade-offs between biodiversity conservation and local socioeconomic development occur. To explore these relationships, we collected data across a wide range of socioeconomic settings through face-to-face survey with PA managers from 114 African and European PAs using structured questionnaire.We found synergies between biodiversity conservation and socioeconomic development for 62% of the PAs, albeit with significant differences between African (55%) and European PAs (75%). Moreover, the sustainability of PAs in conserving biodiversity was strongly correlated with the empowerment of the PA management and the involvement of local communities in PA planning and decision-making processes.Our results demonstrate that for PAs to promote synergies between biodiversity conservation and local socioeconomic development, and to enhance their long-term sustainability, they should invest in the empowerment of their respective management and involvement of local communities in their planning and management activities.Read the free Plain Language Summary for this article on the Journal blog

Aerosols in the central Arctic cryosphere: satellite and model integrated insights during Arctic spring and summer

The central Arctic cryosphere is influenced by the Arctic amplification (AA) and is warming faster than the lower latitudes. AA affects the formation, loss, and transport of aerosols. Efforts to assess the underlying processes determining aerosol variability are currently limited due to the lack of ground-based and space-borne aerosol observations with high spatial coverage in this region. This study addresses the observational gap by making use of total aerosol optical depth (AOD) datasets retrieved by the AEROSNOW algorithm over the vast cryospheric region of the central Arctic during Arctic spring and summer. GEOS-Chem (GC) simulations combined with AEROSNOW-retrieved data are used to investigate the processes controlling aerosol loading and distribution at different temporal and spatial scales. For the first time, an integrated study of AOD over the Arctic cryosphere during sunlight conditions was possible with the AEROSNOW retrieval and GC simulations. The results show that the spatial patterns observed by AEROSNOW differ from those simulated by GC. During spring, which is characterized by long-range transport of anthropogenic aerosols in the Arctic, GC underestimates the AOD in the vicinity of Alaska in comparison with AEROSNOW retrieval. At the same time, it overestimates the AOD along the Bering Strait, northern Europe, and the Siberian central Arctic sea-ice regions, with differences of −12.3 % and 21.7 %, respectively. By contrast, GC consistently underestimates AOD compared with AEROSNOW in summer, when transport from lower latitudes is insignificant and local natural processes are the dominant source of aerosol, especially north of 70° N. This underestimation is particularly pronounced over the central Arctic sea-ice region, where it is −10.6 %. Conversely, GC tends to overestimate AOD along the Siberian and Greenland marginal sea-ice zones by 19.5 % but underestimates AOD along the Canadian Archipelago by −9.3 %. The differences in summer AOD between AEROSNOW data products and GC-simulated AOD highlight the need to integrate improved knowledge of the summer aerosol process into existing models in order to constrain its effects on cloud condensation nuclei, on ice nucleating particles, and on the radiation budget over the central Arctic sea ice during the developing AA period.</p

Lightweight and Secure PUF Key Storage Using Limits of Machine Learning

13th International Workshop, Nara, Japan, September 28 – October 1, 2011. ProceedingsA lightweight and secure key storage scheme using silicon Physical Unclonable Functions (PUFs) is described. To derive stable PUF bits from chip manufacturing variations, a lightweight error correction code (ECC) encoder / decoder is used. With a register count of 69, this codec core does not use any traditional error correction techniques and is 75% smaller than a previous provably secure implementation, and yet achieves robust environmental performance in 65nm FPGA and 0.13μ ASIC implementations. The security of the syndrome bits uses a new security argument that relies on what cannot be learned from a machine learning perspective. The number of Leaked Bits is determined for each Syndrome Word, reducible using Syndrome Distribution Shaping. The design is secure from a min-entropy standpoint against a machine-learning-equipped adversary that, given a ceiling of leaked bits, has a classification error bounded by ε. Numerical examples are given using latest machine learning results

Greenhouse gas retrievals for the CO2M mission using the FOCAL method: first performance estimates

The Anthropogenic Carbon Dioxide Monitoring (CO2M) mission is a constellation of satellites currently planned to be launched in 2026. CO2M is planned to be a core component of a Monitoring and Verification Support (MVS) service capacity under development as part of the Copernicus Atmosphere Monitoring Service (CAMS). The CO2M radiance measurements will be used to retrieve column-averaged dry-air mole fractions of atmospheric carbon dioxide (XCO2), methane (XCH4) and total columns of nitrogen dioxide (NO2). Using appropriate inverse modelling, the atmospheric greenhouse gas (GHG) observations will be used to derive United Nations Framework Convention on Climate Change (UNFCCC) COP 21 Paris Agreement relevant information on GHG sources and sinks. This challenging application requires highly accurate XCO2 and XCH4 retrievals. Three different retrieval algorithms to derive XCO2 and XCH4 are currently under development for the operational processing system at EUMETSAT. One of these algorithms uses the heritage of the FOCAL (Fast atmOspheric traCe gAs retrievaL) method, which has already successfully been applied to measurements from other satellites. Here, we show recent results generated using the CO2M version of FOCAL, called FOCAL-CO2M. To assess the quality of the FOCAL-CO2M retrievals, a large set of representative simulated radiance spectra has been generated using the radiative transfer model SCIATRAN. These simulations consider the planned viewing geometry of the CO2 instrument and corresponding geophysical scene data (including different types of aerosols and varying surface properties), which were taken from model data for the year 2015. We consider instrument noise and systematic errors caused by the retrieval method but have not considered additional error sources due to, for example, instrumental issues, spectroscopy or meteorology. On the other hand, we have also not taken advantage in this study of CO2M's MAP (multi-angle polarimeter) instrument, which will provide additional information on aerosols and cirrus clouds. By application of the FOCAL retrieval to these simulated data, confidence is gained that the FOCAL method is able to fulfil the challenging requirements for systematic errors for the CO2M mission (spatio-temporal bias ≤ 0.5 ppm for XCO2 and ≤ 5 ppb for XCH4).</p