Dietary antioxidants, food deprivation and growth affect differently oxidative status of blood and brain in juvenile European seabass (Dicentrarchus labrax)

Compensatory growth may increase molecular oxidative damage, which may be mitigated through the intake of dietary antioxidants. However, dietary antioxidants may also reduce concentration of antioxidant enzymes, which have a key role in regulating the oxidative status. Here we investigated whether feeding on a diet rich in antioxidants (vitamin E) enables juvenile European seabass (Dicentrarchus labrax) to catch up after a period of food deprivation with negligible effects on the oxidative stress to blood and brain as compared to fish feeding on a normal diet (i.e., not enriched in antioxidants). The results show that a higher intake in antioxidants favoured compensatory growth, but this came at a cost in terms of increased oxidative damage. Increased intake of antioxidants also resulted in changes in the activity of enzymatic antioxidant defences and increased protein oxidative damage in both brain and blood. In addition, food deprivation caused increased protein oxidative damage in brain. Our findings show that the beneficial effects of dietary antioxidants on growth may be offset by hidden detrimental effects and that different early life events affect different components of oxidative status of a given tissue

Negative ozone anomalies at a high mountain site in northern Italy during 2020: a possible role of COVID-19 lockdowns?

Several studies investigated the possible impacts of the restriction measures related to the containment of the spread of the COrona VIrus Disease (COVID-19) to atmospheric ozone (O3) at global, regional, and local scales during 2020. O3 is a secondary pollutant with adverse effects on population health and ecosystems and with negative impacts on climate, acting as greenhouse gas. Most of these studies focused on spring 2020 (i.e. March–May) and on observations in the planetary boundary layer (PBL), mostly in the vicinity of urban agglomerates. Here, we analyzed the variability of O3 above the PBL of northern Italy in 2020 by using continuous observations carried out at a high mountain WMO/GAW global station in Italy (Mt. Cimone–CMN; 44°12' N, 10°42' E, 2165 m a.s.l.). Low O3 monthly anomalies were observed during spring (MAM) and summer (JJA), when periods of low O3 intertwined with periods with higher O3, within climatological ranges. A similar variability was observed for O3 precursors like NO2 and 15 anthropogenic non-methane volatile organic carbons, but the systematic O3 anomalies were not reflected in these variables. The analysis of meteorological variables and diel O3 cycles did not suggest major changes in the vertical transport related to the thermal circulation system in the mountain area. The analysis of five days back-trajectories suggested that the observed O3 anomalies cannot be explained by differences in the synoptic-scale circulation with respect to the previous years alone. On the other hand, the characterization of two transport patterns (i.e. air masses from the regional PBL or from the free troposphere) and the analysis of back-trajectories suggested an important contribution of transport from the continental PBL during the periods with the lowest O3 at CMN. When proxies of air mass transport from the regional PBL are considered, a lower NOx content was pointed out with respect to the previous years, suggesting a lower O3 production in a NOx-limited atmosphere. Our study suggested for the first time that, during MAM and JJA 2020, the reduced anthropogenic emissions related to the COVID-19 restrictions lowered the amount of this short-lived climate forcer/pollutant at remote locations above the PBL over northern Italy. This work suggests the importance of limiting anthropogenic precursor emissions for decreasing the O3 amount at remote locations and in upper atmospheric layers

The fingerprint of the summer 2018 drought in Europe on ground-based atmospheric CO2 measurements

During the summer of 2018, a widespread drought developed over Northern and Central Europe. The increase in temperature and the reduction of soil moisture have influenced carbon dioxide (CO2) exchange between the atmosphere and terrestrial ecosystems in various ways, such as a reduction of photosynthesis, changes in ecosystem respiration, or allowing more frequent fires. In this study, we characterize the resulting perturbation of the atmospheric CO2 seasonal cycles. 2018 has a good coverage of European regions affected by drought, allowing the investigation of how ecosystem flux anomalies impacted spatial CO2 gradients between stations. This density of stations is unprecedented compared to previous drought events in 2003 and 2015, particularly thanks to the deployment of the Integrated Carbon Observation System (ICOS) network of atmospheric greenhouse gas monitoring stations in recent years. Seasonal CO2 cycles from 48 European stations were available for 2017 and 2018.The UK sites were funded by the UK Department of Business, Energy and Industrial Strategy (formerly the Department of Energy and Climate Change) through contracts TRN1028/06/2015 and TRN1537/06/2018. The stations at the ClimaDat Network in Spain have received funding from the ‘la Caixa’ Foundation, under agreement 2010-002624

A top-down estimation of subnational CO2 budget using a global high-resolution inverse model with data from regional surface networks

Top-down approaches, such as atmospheric inversions, are a promising tool for evaluating emission estimates based on activity-data. In particular, there is a need to examine carbon budgets at subnational scales (e.g. state/province), since this is where the climate mitigation policies occur. In this study, the subnational scale anthropogenic CO _2 emissions are estimated using a high-resolution global CO _2 inverse model. The approach is distinctive with the use of continuous atmospheric measurements from regional/urban networks along with background monitoring data for the period 2015–2019 in global inversion. The measurements from several urban areas of the U.S., Europe and Japan, together with recent high-resolution emission inventories and data-driven flux datasets were utilized to estimate the fossil emissions across the urban areas of the world. By jointly optimizing fossil fuel and natural fluxes, the model is able to contribute additional information to the evaluation of province–scale emissions, provided that sufficient regional network observations are available. The fossil CO _2 emission estimates over the U.S. states such as Indiana, Massachusetts, Connecticut, New York, Virginia and Maryland were found to have a reasonable agreement with the Environmental Protection Agency (EPA) inventory, and the model corrects the emissions substantially towards the EPA estimates for California and Indiana. The emission estimates over the United Kingdom, France and Germany are comparable with the regional inventory TNO–CAMS. We evaluated model estimates using independent aircraft observations, while comparison with the CarbonTracker model fluxes confirms ability to represent the biospheric fluxes. This study highlights the potential of the newly developed inverse modeling system to utilize the atmospheric data collected from the regional networks and other observation platforms for further enhancing the ability to perform top-down carbon budget assessment at subnational scales and support the monitoring and mitigation of greenhouse gas emissions

High-resolution inverse modelling of European CH4emissions using the novel FLEXPART-COSMO TM5 4DVAR inverse modelling system

We present a novel high-resolution inverse modelling system ("FLEXVAR") based on FLEXPARTCOSMO back trajectories driven by COSMO meteorological fields at 7 km×7 km resolution over the European COSMO-7 domain and the four-dimensional variational (4DVAR) data assimilation technique. FLEXVAR is coupled offline with the global inverse modelling system TM5-4DVAR to provide background mole fractions ("baselines") consistent with the global observations assimilated in TM5-4DVAR. We have applied the FLEXVAR system for the inverse modelling of European CH4 emissions in 2018 using 24 stations with in situ measurements, complemented with data from five stations with discrete air sampling (and additional stations outside the European COSMO-7 domain used for the global TM5-4DVAR inversions). The sensitivity of the FLEXVAR inversions to different approaches to calculate the baselines, different parameterizations of the model representation error, different settings of the prior error covariance parameters, different prior inventories, and different observation data sets are investigated in detail. Furthermore, the FLEXVAR inversions are compared to inversions with the FLEXPART extended Kalman filter ("FLExKF") system and with TM5-4DVAR inversions at 1° × 1° resolution over Europe. The three inverse modelling systems show overall good consistency of the major spatial patterns of the derived inversion increments and in general only relatively small differences in the derived annual total emissions of larger country regions. At the same time, the FLEXVAR inversions at 7 km × 7 km resolution allow the observations to be better reproduced than the TM5-4DVAR simulations at 1° × 1°. The three inverse models derive higher annual total CH4 emissions in 2018 for Germany, France, and BENELUX compared to the sum of anthropogenic emissions reported to UNFCCC and natural emissions estimated from the Global Carbon Project CH4 inventory, but the uncertainty ranges of top-down and bottom-up total emission estimates overlap for all three country regions. In contrast, the top-down estimates for the sum of emissions from the UK and Ireland agree relatively well with the total of anthropogenic and natural bottom-up inventories

High-resolution inverse modelling of European CH<SUB>4</SUB> emissions using the novel FLEXPART-COSMO TM5 4DVAR inverse modelling system

International audienceWe present a novel high-resolution inverse modelling system ("FLEXVAR") based on FLEXPART-COSMO back trajectories driven by COSMO meteorological fields at 7 km×7 km resolution over the European COSMO-7 domain and the four-dimensional variational (4DVAR) data assimilation technique. FLEXVAR is coupled offline with the global inverse modelling system TM5-4DVAR to provide background mole fractions ("baselines") consistent with the global observations assimilated in TM5-4DVAR. We have applied the FLEXVAR system for the inverse modelling of European CH4 emissions in 2018 using 24 stations with in situ measurements, complemented with data from five stations with discrete air sampling (and additional stations outside the European COSMO-7 domain used for the global TM5-4DVAR inversions). The sensitivity of the FLEXVAR inversions to different approaches to calculate the baselines, different parameterizations of the model representation error, different settings of the prior error covariance parameters, different prior inventories, and different observation data sets are investigated in detail. Furthermore, the FLEXVAR inversions are compared to inversions with the FLEXPART extended Kalman filter ("FLExKF") system and with TM5-4DVAR inversions at 1°×1° resolution over Europe. The three inverse modelling systems show overall good consistency of the major spatial patterns of the derived inversion increments and in general only relatively small differences in the derived annual total emissions of larger country regions. At the same time, the FLEXVAR inversions at 7 km×7 km resolution allow the observations to be better reproduced than the TM5-4DVAR simulations at 1°×1°. The three inverse models derive higher annual total CH4 emissions in 2018 for Germany, France, and BENELUX compared to the sum of anthropogenic emissions reported to UNFCCC and natural emissions estimated from the Global Carbon Project CH4 inventory, but the uncertainty ranges of top-down and bottom-up total emission estimates overlap for all three country regions. In contrast, the top-down estimates for the sum of emissions from the UK and Ireland agree relatively well with the total of anthropogenic and natural bottom-up inventories

Multi-laboratory compilation of atmospheric methane data for the year 2021; obspack_ch4_1_NRT_v4.0_2022-03-03

This product is constructed using the Observation Package (ObsPack) framework [Masarie et al., 2014; www.earth-syst-sci-data.net/6/375/2014/]. The framework is designed to bring together atmospheric greenhouse gas (GHG) observations from a variety of sampling platforms, prepare them with specific applications in mind, and package and distribute them in a self-consistent and well-documented product. ObsPack products are intended to support GHG budget studies and represent a new generation of cooperative value-added GHG data products