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Biochar influences soil biophysicochemical processes and nutrient availability, yet the effects of different biochar and soil water dynamics on carbon (C) and nitrogen (N) retention in the soil-plant systems remain unknown. Maize plants were grown in split-root pots filled with clay loam soil amended with wheat straw pellet biochar (WSP) and softwood pellet biochar (SWP) at 2% (w/w) and were either irrigated daily to 90% of water-holding capacity (FI) or irrigated with 70% volume of water used for FI to the whole root-zone (DI) or alternately to half root-zone (PRD) from the fourth leaf to grain-filling stage. Compared to the unamended controls, biochar amendment enhanced plant biomass and water-use efficiency, particularly when combined with PRD. Although the WSP amendment tended to decrease soil net N mineralization rate, it significantly increased C and N retention in the soil-plant systems. Compared to DI, PRD significantly increased soil respiration rate while lowering soil total organic C content. Moreover, PRD increased soil inorganic N content, which might be related to increased mineralization of soil organic C (SOC) and soil organic N (SON). Such effects might implicate that PRD outperformed DI in enhancing the mineralization of soil organic matter. Although PRD alone might not be a sustainable irrigation method because of greater C and N losses, biochar addition could alleviate these undesirable effects via depressing SOC and SON mineralization. Biochar amendment, especially WSP combined with PRD, could be a promising practice to increase maize growth and water-use efficiency while sustaining C and N retention in the soil-plant systems.Highlightscenter dot Effects of biochar addition and irrigation regimes on C and N retention in the soil-plant systems of maize were investigated.center dot Biochar increased plant N retention and maize growth. Partial root-zone drying (PRD) irrigation increased soil respiration rate and soil organic C and N mineralization.center dot Biochar addition combined with PRD improved maize growth, water-use efficiency, and sustained C and N retention in the soil-plant systems.

Despite its well-established negative impacts on society and biodiversity, eutrophication continues to be one of the most pervasive anthropogenic influence along the freshwater to marine continuum. The interaction between eutrophication and climate change, particularly climate warming, was explicitly focused upon a decade ago in the paper by Moss et al. (2011), which called for an integrated response to both problems, given their apparent synergy. In this review, we summarise advances in the theoretical framework and empirical research on this issue and analyse the current understanding of the major drivers and mechanisms by which climate change can enhance eutophication, and vice versa, with a particular focus on shallow lakes. Climate change can affect nutrient loading, through changes at the catchment and landscape levels by affecting hydrological patterns and fire frequency, and through temperature effects on nutrient cycling. Biotic communities and their interactions can also be directly and indirectly affected by climate change, leading to an overall weakening of resilience to eutrophication impacts. Increasing empirical evidence now indicates several mechanisms by which eutrophying aquatic systems can increasingly act as important sources of greenhouse gases to the atmosphere, particularly methane. We also highlight potential feedbacks between eutrophication, cyanobacterial blooms, and climate change. Facing both challenges at the same time is more pressing than ever. Meaningful and strong measures at the landscape and water body levels are therefore required if we are to ensure ecosystem resilience and safe water supply, conserving biodiversity, and decreasing the carbon footprint of freshwaters. European Union’s Horizon 2020- grant agreement No 869296 The PONDERFUL Project

Tropical montane forests store high amounts of soil organic carbon (SOC). However, global warming may affect these stocks via enhanced soil respiration. Improved insight into the temperature response of SOC respiration can be obtained from in and ex situ warming studies. In situ warming via the translocation of intact soil mesocosms was carried out along an elevation gradient ranging between ca. 1250 m in the Kibale Forest to ca. 3000 m in the Rwenzori Mountains in Uganda. Samples from the same transect were also warmed ex situ. Ex situ results revealed that, following the elevation gradient, which represents a natural climate gradient, specific heterotrophic CO2 respiration decreased linearly by 1.01 ± 0.12 µgCh-1g-1 of SOC per 100 m of elevation increase. The coefficient of temperature sensitivity increased from 1.50 ± 0.13 in the lowest- to 2.68 ± 0.25 in the highest-elevation cluster, showing a linear increase of 0.09 ± 0.03 per 100 m of elevation increase. Additionally, respired CO2 was more depleted in 13C in the warmer lower elevations as compared to colder higher elevations, with a linear decrease of 0.23 ‰ ± 0.04 ‰ per 100 m of elevation increase. Furthermore, the microbial community structure indicated a weak trend along the elevation gradient, with higher elevations more dominated by fungi relative to bacteria. The results indicate an increased recalcitrance and decreased mineralisation of SOC, with elevation likely driven by decreasing soil temperature and pH. Subsequently, after 2 years of in situ warming (0.9 to 2.8 ∘C), specific heterotrophic SOC respiration tended to be lower for warmed soil compared to control soil. Furthermore, in warmed soils, δ13C values and SOC content tended to increase and decrease, respectively. Collectively, this points towards the increased mineralisation and depletion of readily available C during 2 years of warming. In conclusion, our results suggest that climate warming may trigger enhanced losses of SOC from tropical montane forests due to a combination of a higher temperature sensitivity of mineralisation and higher SOC content at higher elevations.

Knowledge of the spatial distribution of the fluxes of greenhouse gases (GHGs) and their temporal variability as well as flux attribution to natural and anthropogenic processes is essential to monitoring the progress in mitigating anthropogenic emissions under the Paris Agreement and to inform its global stocktake. This study provides a consolidated synthesis of CH4 and N2O emissions using bottom-up (BU) and top-down (TD) approaches for the European Union and UK (EU27 + UK) and updates earlier syntheses (Petrescu et al., 2020, 2021). The work integrates updated emission inventory data, process-based model results, data-driven sector model results and inverse modeling estimates, and it extends the previous period of 1990–2017 to 2019. BU and TD products are compared with European national greenhouse gas inventories (NGHGIs) reported by parties under the United Nations Framework Convention on Climate Change (UNFCCC) in 2021. Uncertainties in NGHGIs, as reported to the UNFCCC by the EU and its member states, are also included in the synthesis. Variations in estimates produced with other methods, such as atmospheric inversion models (TD) or spatially disaggregated inventory datasets (BU), arise from diverse sources including within-model uncertainty related to parameterization as well as structural differences between models. By comparing NGHGIs with other approaches, the activities included are a key source of bias between estimates, e.g., anthropogenic and natural fluxes, which in atmospheric inversions are sensitive to the prior geospatial distribution of emissions. For CH4 emissions, over the updated 2015–2019 period, which covers a sufficiently robust number of overlapping estimates, and most importantly the NGHGIs, the anthropogenic BU approaches are directly comparable, accounting for mean emissions of 20.5 Tg CH4 yr−1 (EDGARv6.0, last year 2018) and 18.4 Tg CH4 yr−1 (GAINS, last year 2015), close to the NGHGI estimates of 17.5±2.1 Tg CH4 yr−1. TD inversion estimates give higher emission estimates, as they also detect natural emissions. Over the same period, high-resolution regional TD inversions report a mean emission of 34 Tg CH4 yr−1. Coarser-resolution global-scale TD inversions result in emission estimates of 23 and 24 Tg CH4 yr−1 inferred from GOSAT and surface (SURF) network atmospheric measurements, respectively. The magnitude of natural peatland and mineral soil emissions from the JSBACH–HIMMELI model, natural rivers, lake and reservoir emissions, geological sources, and biomass burning together could account for the gap between NGHGI and inversions and account for 8 Tg CH4 yr−1. For N2O emissions, over the 2015–2019 period, both BU products (EDGARv6.0 and GAINS) report a mean value of anthropogenic emissions of 0.9 Tg N2O yr−1, close to the NGHGI data (0.8±55 % Tg N2O yr−1). Over the same period, the mean of TD global and regional inversions was 1.4 Tg N2O yr−1 (excluding TOMCAT, which reported no data). The TD and BU comparison method defined in this study can be operationalized for future annual updates for the calculation of CH4 and N2O budgets at the national and EU27 + UK scales. Future comparability will be enhanced with further steps involving analysis at finer temporal resolutions and estimation of emissions over intra-annual timescales, which is of great importance for CH4 and N2O, and may help identify sector contributions to divergence between prior and posterior estimates at the annual and/or inter-annual scale. Even if currently comparison between CH4 and N2O inversion estimates and NGHGIs is highly uncertain because of the large spread in the inversion results, TD inversions inferred from atmospheric observations represent the most independent data against which inventory totals can be compared. With anticipated improvements in atmospheric modeling and observations, as well as modeling of natural fluxes, TD inversions may arguably emerge as the most powerful tool for verifying emission inventories for CH4, N2O and other GHGs. The referenced datasets related to figures are visualized at https://doi.org/10.5281/zenodo.7553800 (Petrescu et al., 2023).

Purpose: Alpine wetland ecosystems can contribute large amounts of methane (CH 4) to the atmosphere; however, their emissions vary with environmental conditions. Microbial activity is known to drive CH 4 emissions, but how environmental conditions determine microbial activity is still uncertain. Here, we seek to quantify the variability of the CH 4 flux, to detect the effects of CH 4-related microbes on CH 4 emissions, and to study the dependency of these effects on environmental conditions. Materials and methods: We measured the CH 4 flux, environmental conditions, and CH 4-related microbial communities (mcrA and pmoA gene abundances for methanogens and methanotrophs, respectively) under three hydrological conditions (submerged, soil–water interface, and emerged) from seven sampling sites in the Zoige alpine wetland, China. Results and discussion: The CH 4 flux varied greatly from 0 to 41 mg m −2 h −1 in the Zoige alpine wetland. The methanogenic and methanotrophic abundances both showed positive correlations with CH 4 flux, while CH 4 flux increased linearly with the increase of soil water content (SWC) when SWC was above 60%. CH 4 flux and methanogenic and methanotrophic abundances maintained the high levels when soil C:N ratio was in the range of 11–24 and decreased exponentially with the increase of soil DOC:TN ratio in Zoige alpine wetland, which might result from its influence on nutrient supply for microbial decomposition process. Conclusion: The results provided new insight into the effects of CH 4-related microbes on CH 4 emission and its response to different environmental conditions and helped us to comprehend the risks of high CH 4 emissions from alpine wetlands under climatic change and anthropogenic disturbance.

The environmental impacts of food are currently at unsustainable levels. Consumers undoubtedly play a central role in reducing the impacts of the food system to more sustainable levels via dietary changes and food waste reduction. Mathematical optimisation is one approach to identifying less environmentally impactful dietary patterns. A limited number of studies, however, have assessed whether impact reductions offered by optimised diets are enough to remain within planetary boundaries (i.e. attain ‘absolute’ environmental sustainability). Using UK food consumption as a case study, here we employ linear programming to identify nutritionally adequate diets that meet sociocultural acceptability criteria whilst minimising (a) environmental impact transgressions of their allocated share of the safe operating space (SoSOS) for nine planetary boundaries (PBs), (b) cost, or (c) deviation from the current diet. We show that the current diet is unsustainable as it transgresses six or seven PBs, depending on the SoSOS allocation principle. Optimising for minimum SoSOS transgressions yields diets offering significant impact reductions (66 - 95% reduction across all PBs) compared to the current average dietary pattern, but whether they completely mitigate SoSOS transgressions depends on the sharing principle adopted to assign the SoSOS to national food consumption. Additionally, by comparing least-cost and least-transgression solutions, we find a trade-off between cost and environmental sustainability indicating that more sustainable dietary patterns are not currently incentivised by the relative prices of food items in the UK. Our work demonstrates the value in embedding ‘absolute’ sustainability in diet optimisation so that solutions inherently provide a more clear-cut understanding of their broad implications on the environment., Sustainable Production and Consumption, 28, ISSN:2352-5509

Partially replacing ordinary Portland cement (OPC) with low-carbon supplementary cementitious materials (SCMs) in blended cement concrete (BCC) is perceived as the most promising route for sustainable concrete production. Despite having a lower environmental impact, BCC could exhibit performance inferior to OPC in design-governing functional properties. Hence, concrete manufacturers and scientists have been seeking methods to predict the performance of BCC mixes in order to reduce the cost and time of experimentally testing all alternatives. Machine learning algorithms have been proven in other fields for treating large amounts of data drawing meaningful relationships between data accurately. However, the existing prediction models in the literature come short in covering a wide range of SCMs and/or functional properties. Considering this, in this study, a non-linear multi-layered machine learning regression model was created to predict the performance of a BCC mix for slump, strength, and resistance to carbonation and chloride ingress based on any of five prominent SCMs: fly ash, ground granulated blast furnace slag, silica fume, lime powder and calcined clay. A database from>150 peer-reviewed sources containing>1650 data points was created to train and test the model. The statistical performance was found to be comparable to that of existing models (R = 0.94–0.97). For the first time, the model, Pre-bcc, was also made available online for users to conduct their own prediction studies.

Riparian forests are known as hot spots of nitrogen cycling in landscapes. Climate warming speeds up the cycle. Here we present results from a multi-annual high temporal-frequency study of soil, stem, and ecosystem (eddy covariance) fluxes of N2O from a typical riparian forest in Europe. Hot moments (extreme events of N2O emission) lasted a quarter of the study period but contributed more than half of soil fluxes. We demonstrate that high soil emissions of N2O do not escape the ecosystem but are processed in the canopy. Rapid water content change across intermediate soil moisture was a major determinant of elevated soil emissions in spring. The freeze-thaw period is another hot moment. However, according to the eddy covariance measurements, the riparian forest is a modest source of N2O. We propose photochemical reactions and dissolution in canopy-space water as reduction mechanisms.

Objective:To identify food purchase patterns and to assess their carbon footprint and expenditure.Design:Cross-sectional.Setting:Purchase patterns were identified by factor analysis from the annual purchases of 3435 product groups. The associations between purchase patterns and the total purchases’ carbon footprints (based on life-cycle assessment) and expenditure were analysed using linear regression and adjusted for nutritional energy content of the purchases.Participants:Loyalty card holders (n 22 860) of the largest food retailer in Finland.Results:Eight patterns explained 55 % of the variation in food purchases. The Animal-based pattern made the greatest contribution to the annual carbon footprint, followed by the Easy-cooking, and Ready-to-eat patterns. High-energy, Traditional and Plant-based patterns made the smallest contribution to the carbon footprint of the purchases. Animal-based, Ready-to-eat, Plant-based and High-energy patterns made the greatest contribution, whereas the Traditional and Easy-cooking patterns made the smallest contribution to food expenditure. Carbon footprint per euros spent increased with stronger adherence to the Traditional, Animal-based and Easy-cooking patterns.Conclusions:The Animal-based, Ready-to-eat and High-energy patterns were associated with relatively high expenditure on food, suggesting no economic barrier to a potential shift towards a plant-based diet for consumers adherent to those patterns. Strong adherence to the Traditional pattern resulted in a low energy-adjusted carbon footprint but high carbon footprint per euro. This suggests a preference for cheap nutritional energy rather than environment-conscious purchase behaviour. Whether a shift towards a plant-based pattern would be affordable for those with more traditional and cheaper purchase patterns requires more research.

The aim of this research was to determine the amount of energy input and output used for grapefruit production in the province of Hatay, one of the most important citrus production centers in Turkey, and to conduct energy efficiency and environmental price analyses accordingly. This study was performed for the 2020 production season in Arsuz, Erzin, Dortyol, and Samandag towns in Hatay province. The data were collected from 42 different grapefruit growers by using a face-to-face questionnaire method. The agricultural input values, input energies, output values, and output energies used in grapefruit production were computed to determine the energy efficiency. Also, environmental prices were calculated depending on greenhouse gas (GHG) emission of agricultural inputs. According to the results of the research, the energy input was found to be 60,944.87 MJ ha(-1), and the output was 107,982.64 MJ ha(-1) in grapefruit production. The environmental price was 464 euro ha(-1), and the total GHG emission was calculated as 8140.35 kgCO(2-eq) ha(-1). Electricity consumption accounted for 42.06% of the total GHG emissions in grapefruit production. This was followed by the use of nitrogen fertilizer, at 16.94%. The GHG ratio was found to be 0.13 kgCO(2-eq) kg(-1). Energy use efficiency, specific energy, energy efficiency, and net energy value were determined as 1.77, 0.96 MJ kg(-1), 1.04 kg MJ(-1), and 47,037.77 MJ ha(-1), respectively. The renewable energy usage rate was 14.14% of the total energy input. Energy efficiency should be increased in grapefruit production, and more renewable energy should be used for sustainable agriculture and a clean environment.

Dwellings are material intensive products. To date, material use in dwellings has been investigated mainly using economic (exogenous) or dwelling (endogenous) drivers, with few studies comprehensively combining both. For the first time, we identify a comprehensive set of such drivers of demand for building materials and analyze them using the logarithmic mean divisia index (LMDI) method. We combine the LMDI method, the concept of dynamic material flow analysis, and physical and monetary flows to decompose the demand for building materials into the following six effects: material intensity, floor area shape, dwelling type, dwelling intensity, economic output, and population. We analyze these six effects on demand for concrete in new dwellings in the U.K. from 1951 to 2014, classified into six dwelling types and four subregions. Of these six effects, the material intensity effect is the most important, overall contributing to increasing concrete demand by +79 Mt from 1950 to 2014, while the dwelling intensity effect plays an opposite role, overall reducing concrete demand from 1950 to 2014 by -56 Mt. The economic output effect is also significant (+38 Mt from 1950 to 2014). A comparative analysis of the six effects in the four U.K. nations reveals that most of the effects arise from England, while the other nations have minor effects due to their smaller populations. Our results show that changes to the demand for concrete in the U.K. fluctuate and have mainly remained between ±30 Mt year-2 from 1950 to 2014, and thus the inflows of concrete into the in-use stock of dwellings have experienced neither entirely increasing or decreasing trends during this period. This study contributes to understanding changes in resource demand due to social, economic, and technological factors and thus improves the capability to reliably and quantitatively model the use of materials in the built environment.

It is a challenging task for determining the emissions and energy-saving options for counties and countries. In order to overcome this issue, two new concepts are introduced in this study. These are residential base electricity consumption and residential base natural gas consumption. A new model that estimates the total energy consumption of urban residential buildings from the available electricity consumption data is developed. The model employs heating degree days (HDD) and cooling degree days (CDD) parameters to predict the energy consumption for heating and cooling purposes. A month with zero or almost zero values of both HDD and CDD is considered as \"base month.\" These months when there is neither heating nor cooling, plays a key role in this study. The proposed model is applied to a county with a population of over 62,000 located in Southern Turkey, and the total electricity consumption is calculated with 1.24% accuracy. The validity and accuracy of the model are tested by theoretical electricity calculations, coal, and wood consumption. Accordingly, while annual electrical heating is equal to 2618 kWh/year for an average house of 96 m(2), for the coal and wood burning households, the annual energy consumption values are 2190 and 2616 kWh/year, respectively.

Inland waters (rivers, lakes and ponds) are important conduits for the emission of terrestrial carbon in Arctic permafrost landscapes. These emissions are driven by turnover of contemporary terrestrial carbon and additional pre-aged (Holocene and late-Pleistocene) carbon released from thawing permafrost soils, but the magnitude of these source contributions to total inland water carbon fluxes remains unknown. Here we present unique simultaneous radiocarbon age measurements of inland water CO2, CH4 and dissolved and particulate organic carbon in northeast Siberia during summer. We show that >80% of total inland water carbon was contemporary in age, but pre-aged carbon contributed >50% at sites strongly affected by permafrost thaw. CO2 and CH4 were younger than dissolved and particulate organic carbon, suggesting emissions were primarily fuelled by contemporary carbon decomposition. Our findings reveal that inland water carbon emissions from permafrost landscapes may be more sensitive to changes in contemporary carbon turnover than the release of pre-aged carbon from thawing permafrost.

Atmospheric inversions have been used for the past two decades to derive large-scale constraints on the sources and sinks of CO2 into the atmosphere. The development of dense in situ surface observation networks, such as ICOS in Europe, enables in theory inversions at a resolution close to the country scale in Europe. This has led to the development of many regional inversion systems capable of assimilating these high-resolution data, in Europe and elsewhere. The EUROCOM (European atmospheric transport inversion comparison) project is a collaboration between seven European research institutes, which aims at producing a collective assessment of the net carbon flux between the terrestrial ecosystems and the atmosphere in Europe for the period 2006–2015. It aims in particular at investigating the capacity of the inversions to deliver consistent flux estimates from the country scale up to the continental scale. The project participants were provided with a common database of in situ-observed CO2 concentrations (including the observation sites that are now part of the ICOS network) and were tasked with providing their best estimate of the net terrestrial carbon flux for that period, and for a large domain covering the entire European Union. The inversion systems differ by the transport model, the inversion approach, and the choice of observation and prior constraints, enabling us to widely explore the space of uncertainties. This paper describes the intercomparison protocol and the participating systems, and it presents the first results from a reference set of inversions, at the continental scale and in four large regions. At the continental scale, the regional inversions support the assumption that European ecosystems are a relatively small sink (-0.21±0.2 Pg C yr−1). We find that the convergence of the regional inversions at this scale is not better than that obtained in state-of-the-art global inversions. However, more robust results are obtained for sub-regions within Europe, and in these areas with dense observational coverage, the objective of delivering robust country-scale flux estimates appears achievable in the near future.

Atmospheric inversions have been used for the past two decades to derive large-scale constraints on the sources and sinks of CO2 into the atmosphere. The development of dense in situ surface observation networks, such as ICOS in Europe, enables in theory inversions at a resolution close to the country scale in Europe. This has led to the development of many regional inversion systems capable of assimilating these high-resolution data, in Europe and elsewhere. The EUROCOM (European atmospheric transport inversion comparison) project is a collaboration between seven European research institutes, which aims at producing a collective assessment of the net carbon flux between the terrestrial ecosystems and the atmosphere in Europe for the period 2006-2015. It aims in particular at investigating the capacity of the inversions to deliver consistent flux estimates from the country scale up to the continental scale.The project participants were provided with a common database of in situ-observed CO2 concentrations (including the observation sites that are now part of the ICOS network) and were tasked with providing their best estimate of the net terrestrial carbon flux for that period, and for a large domain covering the entire European Union. The inversion systems differ by the transport model, the inversion approach, and the choice of observation and prior constraints, enabling us to widely explore the space of uncertainties.This paper describes the intercomparison protocol and the participating systems, and it presents the first results from a reference set of inversions, at the continental scale and in four large regions. At the continental scale, the regional inversions support the assumption that European ecosystems are a relatively small sink (-0.21 +/- 0.2 Pg C yr(-1)). We find that the convergence of the regional inversions at this scale is not better than that obtained in state-of-the-art global inversions. However, more robust results are obtained for subregions within Europe, and in these areas with dense observational coverage, the objective of delivering robust country-scale flux estimates appears achievable in the near future.

We present a modelling framework for fossil fuel CO2 emissions in an urban environment, which allows constraints from emission inventories to be combined with atmospheric observations of CO2 and its co-emitted species CO, NOx , and SO2. Rather than a static assignment of average emission rates to each unit area of the urban domain, the fossil fuel emissions we use are dynamic: they vary in time and space in relation to data that describe or approximate the activity within a sector, such as traffic density, power demand, 2m temperature (as proxy for heating demand), and sunlight and wind speed (as proxies for renewable energy supply). Through inverse modelling, we optimize the relationships between these activity data and the resulting emissions of all species within the dynamic fossil fuel emission model, based on atmospheric mole fraction observations. The advantage of this novel approach is that the optimized parameters (emission factors and emission ratios, N D 44) in this dynamic emission model (a) vary much less over space and time, (b) allow for a physical interpretation of mean and uncertainty, and (c) have better defined uncertainties and covariance structure. This makes them more suited to extrapolate, optimize, and interpret than the gridded emissions themselves. The merits of this approach are investigated using a pseudo-observation-based ensemble Kalman filter inversion set-up for the Dutch Rijnmond area at 1km-1km resolution. We find that the fossil fuel emission model approximates the gridded emissions well (annual mean differences < 2 %, hourly temporal r2 D 0:21-0.95), while reported errors in the underlying parameters allow a full covariance structure to be created readily. Propagating this error structure into atmospheric mole fractions shows a strong dominance of a few large sectors and a few dominant uncertainties, most notably the emission ratios of the various gases considered. If the prior emission ratios are either sufficiently well-known or well constrained from a dense observation network, we find that including observations of co-emitted species improves our ability to estimate emissions per sector relative to using CO2 mole fractions only. Nevertheless, the total CO2 emissions can be well constrained with CO2 as the only tracer in the inversion. Because some sectors are sampled only sparsely over a day, we find that propagating solutions from day-to-day leads to largest uncertainty reduction and smallest CO2 residuals over the 14 consecutive days considered. Although we can technically estimate the temporal distribution of some emission categories like shipping separate from their total magnitude, the controlling parameters are difficult to distinguish. Overall, we conclude that our new system looks promising for application in verification studies, provided that reliable urban atmospheric transport fields and reasonable a priori emission ratios for CO2 and its co-emitted species can be produced.

Estimates of regional and global freshwater N2O emissions have remained inaccurate due to scarce data and complexity of the multiple processes driving N2O fluxes the focus predominantly being on summer time measurements from emission hot spots, agricultural streams. Here, we present four‐season data of N2O concentrations in the water columns of randomly selected boreal lakes covering a large variation in latitude, lake type, area, depth, water chemistry, and land use cover. Nitrate was the key driver for N2O dynamics, explaining as much as 78% of the variation of the seasonal mean N2O concentrations across all lakes. Nitrate concentrations varied among seasons being highest in winter and lowest in summer. Of the surface water samples, 71% were oversaturated with N2O relative to the atmosphere. Largest oversaturation was measured in winter and lowest in summer stressing the importance to include full year N2O measurements in annual emission estimates. Including winter data resulted in fourfold annual N2O emission estimates compared to summer only measurements. Nutrient‐rich calcareous and large humic lakes had the highest annual N2O emissions. Our emission estimates for Finnish and boreal lakes are 0.6 and 29 Gg N2O‐N/year, respectively. The global warming potential of N2O from lakes cannot be neglected in the boreal landscape, being 35% of that of diffusive CH4 emission in Finnish lakes., Up‐scaling of freshwater N2O emissions at regional to global scales has remained challenging due to sparse data based on summer measurements. We collected seasonal data on N2O concentrations from 112 randomly selected boreal lakes in Finland and determined a representative set of possible drivers. Our data underline the key role of nitrate in regulating seasonal and spatial N2O concentrations. Nitrate explained 78% of the variation in N2O across all lakes. The Global Warming Potential of N2O in our data was 35% of that of diffusive CH4 emission underlining the importance to include N2O in landscape GHG evasion estimates.

Boreal peatiands are major sources of nitrogen (N), phosphorus (P) and dissolved organic carbon (DOC) to downstream aquatic ecosystems, and forest harvesting generally further increases the loading of DOC and nutrients. Continuous cover forestry (CCF) is proposed to be an environmentally more sustainable management option for peatland forests than conventional even-aged clear-cutting. However, the impacts of CCF on water quality, the biodegradability of DOC and consequent CO2 emissions from inland waters are poorly known. We studied the concentrations of N, P and DOC, the quality of DOC, and the mineralization of DOC to CO2 in ground water and ditch water in clear-cut, partially harvested, i.e. CCF, and uncut drained forests in Finland. Groundwater total N, NH4-N and PO4-P concentrations were significantly lower in CCF and uncut forest than in the clear-cut forest. Groundwater DOC concentrations were often highest in the clear-cut forest, where the water table was doser to the soil surface. Ditch water DOC and N concentrations were lowest next to the clear-cut area. DOC aromaticity in ground water was higher in the uncut forest than in the clear-cut and CCF, whereas ditch water aromaticity did not differ between the treatments. The biodegradation of DOC was studied by incubating water (at 15 degrees C for 24 h) 1, 3, 7 and 21 days after sampling. The results indicated that the majority of the CO2 production took place during the first three days, and CO2 fluxes were considerably higher from the ditch water than from the groundwater. The CO2 emissions were lower in summer than in the other seasons. Ditch water and groundwater CO2 production were generally significantly higher in the clear-cut than in the uncut forest. The results suggest that CCF can decrease the nutrient concentrations as well as CO2 emissions from inland waters compared to conventional clear-cutting. (C) 2021 The Authors. Published by Elsevier B.V.

Sustainability of livestock production is a highly contested issue in agricultural sustainability discourse. This study aimed to assess the environmental impact of farms using semi-natural grasslands in Finland, or so-called High Nature Value (HNV) farms. We estimated the environmental impact of 11 such farms, including greenhouse gas emissions (GHG), nitrogen (N) balance, land occupation, and carbon storage. We also accounted for unique biodiversity, defined in this study as communities that are dependent on semi-natural grasslands. We compared these to the alternative states of the farms, specifically a hypothetical farm with the same production output but without access to semi natural grasslands. GHG emissions at the farm level (tCO(2eq)/ha) in HNV farms were 64% lower than on the alternative farms; GHG emissions at the product level (tCO(2eq)/t LW) and N balance (N kg/ha) were 31% and 235% lower, respectively. The carbon stocks were 163% higher at farm level. Biodiversity values, indicated by the share of semi-natural grassland in management, ranged from 23% to 83% on HNV farms. Six out of eleven farms would need to increase their arable land occupation by an average of 39% of arable land to fulfil their needs for animal feed if they did not utilize semi-natural grassland. This study contributes to growing evidence that HNV farming systems can support sustainable production by minimising arable land occupation, reducing nutrient loses, and increasing carbon storage while maintaining unique biodiversity.

Aims: This study aimed to compare the environmental impacts and diet qualities of popular diet models with the recommendations of the Turkish national dietary guidelines. Methods: Seven-day isocaloric (8368 kJ) diet models were created taking into account the Mediterranean, Atkins (20/40/100), Ornish, Zone diets, and Turkey Dietary Guidelines-2015 recommendations with different food and nutrient contents. Water footprints were evaluated using the global water footprint standards. Greenhouse gas emissions were evaluated using carbon footprint factors compiled as a result of meta-analyses of life cycle analysis studies in the literature. In addition, the quality of diets was evaluated with the Diet Quality Index-International. Results: Atkins20 diet model had the most harmful environmental impact (greenhouse gas emissions 8.74 kg CO2-eq/per/day and total water footprint 7731 L/per/day), whereas Ornish and Mediterranean diet models (greenhouse gas emissions 2.2/3.07 kg CO2-eq/per/day and total water footprints 3184/ 3675 L/per/day, respectively) had less harmful environmental impact. The highest Diet Quality Index-International score was in the Ornish diet model while the lowest Diet Quality Index-International was in the Atkins20 diet model. Conclusion: Ornish and Mediterranean diet models had less harmful environmental impacts, which contributed to sustainable nutrition. The importance of diet quality and environmental impacts should be kept in mind when evaluating diet models to ensure sustainable nutrition.

The main objective of this study was to determined environmental prices and energy efficiency for mandarin (Citrus reticulata) production in Hatay province of Turkey. This study was performed for 2019 production season in Arsuz, Erzin, Dortyol and Samandag towns in Hatay province of Turkey. The data provided from study were collected from 78 different mandarin productioner by using a face to face questionnaire method. Environmental prices were calculated depent with greenhouse gas (GHG) emission of agricultural inputs. Also, the agricultural input values, input energies and output values, output energies used in mandarin production were calculated to detetthine the energy efficiency. According to the study findings, the environmental prices in mandarin production was calculated as 430.11 ha(-1). Total GHG emission was calculated as 7545.87 kgCO(2-q) ha(-1) for mandarin production with the greatest portions for electricity usage (39.42%). The electricity usage followed up nitrogen fertilizer (17.67%), water consumption of irrigation (14.49%), human labour (6.88%), diesel fuel consumption (4.96%), phosphate fertilizer usage (4.77%), machine usage (2.66%), fatutyard manure usage (2.64%), potassium fertilizer usage (2.07%), herbicides usage (1.71%), fungicides usage (1.60%) and insecticides usage (1.14%), respectively. Additionally, GHG ratio value was calculated as 0.23 kgCO(2-eq) kg(-1). Energy efficiency, specific energy, energy productivity and net energy calculations were calculated respectively as 0.98, 1.73 MJ kg(-1), 0.58 kg MJ(-1) and -1134.65 MJ ha(-1).

Climate change and the destruction of ecosystems by human activities are among the greatest challenges of the 21st century and require urgent action. Health care activities significantly contribute to the emission of greenhouse gases and waste production, with gastrointestinal (GI) endoscopy being one of the largest contributors. This Position Statement aims to raise awareness of the ecological footprint of GI endoscopy and provides guidance to reduce its environmental impact. The European Society of Gastrointestinal Endoscopy (ESGE) and the European Society of Gastroenterology and Endoscopy Nurses and Associates (ESGENA) outline suggestions and recommendations for health care providers, patients, governments, and industry. Main statements 1 GI endoscopy is a resource-intensive activity with a significant yet poorly assessed environmental impact. 2 ESGE-ESGENA recommend adopting immediate actions to reduce the environmental impact of GI endoscopy. 3 ESGE-ESGENA recommend adherence to guidelines and implementation of audit strategies on the appropriateness of GI endoscopy to avoid the environmental impact of unnecessary procedures. 4 ESGE-ESGENA recommend the embedding of reduce, reuse, and recycle programs in the GI endoscopy unit. 5 ESGE-ESGENA suggest that there is an urgent need to reassess and reduce the environmental and economic impact of single-use GI endoscopic devices. 6 ESGE-ESGENA suggest against routine use of single-use GI endoscopes. However, their use could be considered in highly selected patients on a case-by-case basis. 7 ESGE-ESGENA recommend inclusion of sustainability in the training curricula of GI endoscopy and as a quality domain. 8 ESGE-ESGENA recommend conducting high quality research to quantify and minimize the environmental impact of GI endoscopy. 9 ESGE-ESGENA recommend that GI endoscopy companies assess, disclose, and audit the environmental impact of their value chain. 10 ESGE-ESGENA recommend that GI endoscopy should become a net-zero greenhouse gas emissions practice by 2050.

International audience; The two most urgent and interlinked environmental challenges humanity faces are climate change and biodiversity loss. We are entering a pivotal decade for both the international biodiversity and climate change agendas with the sharpening of ambitious strategies and targets by the Convention on Biological Diversity and the United Nations Framework Convention on Climate Change. Within their respective Conventions, the biodiversity and climate interlinked challenges have largely been addressed separately. There is evidence that conservation actions that halt, slow or reverse biodiversity loss can simultaneously slow anthropogenic mediated climate change significantly. This review highlights conservation actions which have the largest potential for mitigation of climate change. We note that conservation actions have mainly synergistic benefits and few antagonistic trade-offs with climate change mitigation. Specifically, we identify direct co-benefits in 14 out of the 21 action targets of the draft post-2020 global biodiversity framework of the Convention on Biological Diversity, notwithstanding the many indirect links that can also support both biodiversity conservation and climate change mitigation. These relationships are context and scale-dependent; therefore, we showcase examples of local biodiversity conservation actions that can be incentivized, guided and prioritized by global objectives and targets. The close interlinkages between biodiversity, climate change mitigation, other nature's contributions to people and good quality of life are seldom as integrated as they should be in management and policy. This review aims to re-emphasize the vital relationships between biodiversity conservation actions and climate change mitigation in a timely manner, in support to major Conferences of Parties that are about to negotiate strategic frameworks and international goals for the decades to come.