Publications

Agricultural ditches emit disproportionate amounts of nitrous oxide (N₂O), but their contributions to regional or global N₂O emissions remain unclear due to limited data. The Intergovernmental Panel on Climate Change (IPCC) recommends using emission factors (EFs) to estimate indirect N₂O emission, but the EF for ditches (EF_5g) is categorized as groundwater, which potentially introduces a significant bias. This study conducted a regional-scale campaign in the North China Plain, one of the world's most intensive agricultural regions, and calculated the EF_5g values from agricultural ditches by the concentration method (N₂O-N/NO₃^--N). The results found that the regional-scale mean EF_5g value (0.0028) was less than half of the IPCC default value (0.006), illustrating that the current IPCC methodology significantly overestimates N₂O emissions from agricultural ditches. Despite the relatively small EF_5g values, agricultural ditches exhibited a high mean N₂O concentration (3.36 μg L^-1) and a large regional emission (1.14 ± 0.86 Gg N₂O-N yr^-1), which is equal to 3.8 ± 2.9% of direct N₂O emission from the croplands in the North China Plain. Since ditches are ubiquitous in agricultural regions and are likely to expand under climate change, refining EF_5g is crucial to accurately assess their contribution to global N₂O budgets.

Abstract Global warming caused by anthropological emissions of greenhouse gas (GHG) is now an inconvenient reality. CO2, the largest contributor, was emitted at the rate of 6 Gt C y-1 by burning fossil fuels in 1990, which are projected to rise to around 10 Gt C y-1 by 2020. Using bio-fuels, such as bio-ethanol or bio-diesel in transportation, or biomass in power generation reduces CO2 emissions as the carbon is fixed by the plants from the atmosphere and saves the equivalent fossil fuel. The biospheric flux of carbon from the soil and terrestrial biota to the atmosphere is about 120 Gt C y-1 and is roughly balanced by the fixation of carbon by photosynthesis. However, anthropological land use change, through increased agriculture and forestry, resulted in atmospheric emissions of 1.1 Gt C in 1990, projected to rise to 1.5 Gt C in 2020, so the production of biofuels is not GHG emission free if land use change is involved. This paper explores the GHG emission cost of the production of bio-fuels derived from energy crops and compares them to fossil fuels used in transport and electricity generation. The bio-fuels emission cost are presented for several land use scenarios showing that highest sequestration can be achieved by using existing arable land for bio-fuel production and not land with a currently undisturbed ecosystem. Considering these drivers and the GHG emissions, we model the future potential of Europe to produce bio-fuels with four different future land use and climate change scenarios and conclude that up to 20% of Europe's current primary energy consumption could be provided by bio-fuels by the year 2080 with a corresponding reduction in carbon emissions, taking into account the GHG cost of production. Introduction The global pattern of energy use is changing with the successive industrialization of the economies of South East Asia and Brazil, and more recently with the increasing pace of the industrialization of China and India. This has driven an increase in the demand for energy, and hence for fossil fuel, at the rate of 2–3% per year 1. The rate at which conventional oil production can be increased has been reduced by the lack of refining capacity, and the fact that nearly 50% of the world's proven and probable conventional light crude oil reserves have already been consumed 2. This flat-topping in the availability of oil has been compensated for by the increased availability of natural gas and new reserves of cheap coal. Natural gas has been increasing its share of the energy supply mix as the infrastructure and technology of its transportation is put into place both by pipelines, liquefaction and conversion to methanol. In developed economies, gas has displaced both oil and coal, whilst coal use has increased in developing economies, particularly in China. At the same time the use of nuclear energy has stagnated due to public concerns about waste storage and disposal. Globally, biomass currently provides around 46 EJ of bio-energy in the form of combustible biomass and wastes, liquid bio-fuels, renewable municipal solid waste, solid biomass/charcoal, and gaseous fuels. This share is estimated to be 13.4% of global primary energy supply 3 but this is mainly from "traditional biomass" estimated to provide 32EJ in 2002 of non-commercial firewood, charcoal and dung used for cooking and heating in developing countries 4. Such low-grade biomass provides around 35% of primary energy in many developing countries, but more than 70% in Africa 5.

We summarise the work of an interdisciplinary network set up to explore the impacts of climate change in the British Uplands. In this CR Special, the contributors present the state of knowledge and this introduction synthesises this knowledge and derives implications for decision makers. The Uplands are valued semi-natural habitats, providing ecosystem services that have historically been taken for granted. For example, peat soils, which are mostly found in the Uplands, contain around 50% of the terrestrial carbon in the UK. Land management continues to be a driver of ecosystem service delivery. Degraded and managed peatlands are subject to erosion and carbon loss with negative impacts on biodiversity, carbon storage and water quality. Climate change is already being experienced in British Uplands and is likely to exacerbate these pressures. Climate envelope models suggest as much as 50% of British Uplands and peatlands will be exposed to climate stress by the end of the 21st century under low and high emissions scenarios. However, process-based models of the response of organic soils to this climate stress do not give a consistent indication of what this will mean for soil carbon: results range from a very slight increase in uptake, through a clear decline, to a net carbon loss. Preserving existing peat stocks is an important climate mitigation strategy, even if new peat stops forming. Preserving upland vegetation cover is a key win–win management strategy that will reduce erosion and loss of soil carbon, and protect a variety of services such as the continued delivery of a high quality water resource.

Abstract. Knowledge of the spatial distribution of the fluxes of greenhouse gases 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, inverse modelling estimates, and extends the previous period 1990–2017 to 2020. BU and TD products are compared with European National GHG Inventories (NGHGI) reported by Parties under the United Nations Framework Convention on Climate Change (UNFCCC) in 2021. The uncertainties of NGHGIs were evaluated using the standard deviation obtained by varying parameters of inventory calculations, reported by the EU Member States following the guidelines of the Intergovernmental Panel on Climate Change (IPCC) and harmonized by gap-filling procedures. Variation 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 (EDGAR v5v6.0, last year 2018) and 18.4 Tg CH4 yr−1 (GAINS, 2015), close to the NGHGI estimates of 17.5 ± 2.1 Tg CH4 yr−1. TD inversions 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 Tg CH4 yr−1 and 24 Tg CH4 yr−1 inferred from GOSAT and surface (SURF) network atmospheric measurements, respectively. The magnitude of natural peatland and mineral soils emissions from the JSBACH-HIMMELI model, natural rivers, lakes and reservoirs 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 (EDGAR v5v6.0 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, of great importance for CH4 and N2O, which may help identify sector contributions to divergence between prior and posterior estimates at the annual/inter-annual scale. Even if currently comparison between CH4 and N2O inversions 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 modelling and observations, as well as modelling of natural fluxes, TD inversions may arguably emerge as the most powerful tool for verifying emissions inventories for CH4, N2O and other GHGs. The referenced datasets related to figures are visualized at https://doi.org/10.5281/zenodo.6992472 (Petrescu et al., 2022).

Abstract Process and empirical‐based models that describe lignocellulosic biomass yield of the perennial energy grass M iscanthus (MiscanFor © ), short rotation coppice ( SRC ) trees and shrubs, poplar and willow (ForestGrowth‐ SRC ) and a number of short rotation forest trees ( ESC ‐ CARBINE ), were used to estimate the yield potential for current and future climates across G reat B ritain ( GB ). In current climates, modelled yields for all feedstock crops varied between 8.1 and 10.6 Mg dry weight ( DW ) ha −1 yr −1 with willow SRC and poplar SRF producing the lowest and highest yields respectively. For the medium emissions scenario ( UKCP 09) in 2050, mean yield for all feedstock crops varied between 7.6 and 12.7 Mg DW ha −1 yr −1 with willow SRC and poplar SRF once again the lowest and the highest recorded yields. There were clear geographical trends within GB . M iscanthus yield was higher than all others in the south‐west (13.1 Mg DW ha −1 yr −1 ), SRC willow and SRC poplar in the north‐west (12.1–15.8 Mg DW ha −1 yr −1 ) and in the midlands and south‐east, SRF poplar was the highest yielding (10.5–11.6 Mg DW ha −1 yr −1 ). These geographical trends changed little with climate out to 2050, with mean yield of each ‘best feedstock’ increasing from 12.7 to 14.2 Mg DW ha −1 yr −1 . Out to 2050, SRC declined slightly and M iscanthus and SRF poplar increased as the ‘best feedstock’ option. Except for a few localized examples, only SRF poplar had a higher yield than SRC or M iscanthus . These data suggest that in current and future climates, lignocellulosic biomass plantation species can be selected and optimized for best yield performance in different regions of GB . This modelling framework provides a valuable starting‐point for which to test the performance of new genetic material, as this becomes available and parameterized for the models and socio‐economic scenarios that may impact on the bioenergy industry.

Abstract Energy crops currently contribute a relatively small proportion to the total energy produced from biomass each year, but the proportion is set to grow over the next few decades. This paper reviews the current status of energy crops and their conversion technologies, assesses their potential to contribute to global energy demand and climate mitigation over the next few decades, and examines the future prospects. Previous estimates have suggested a technical potential for energy crops of∼400 EJ yr −1 by 2050. In a new analysis based on energy crop areas for each of the IPCC SRES scenarios in 2025 (as projected by the IMAGE 2.2 integrated assessment model), more conservative dry matter and energy yield estimates and an assessment of the impact on non‐CO 2 greenhouse gases were used to estimate the realistically achievable potential for energy crops by 2025 to be between 2 and 22 EJ yr −1 , which will offset∼100–2070 Mt CO 2 ‐eq. yr −1 . These results suggest that additional production of energy crops alone is not sufficient to reduce emissions to meet a 550 μmol mol −1 atmospheric CO 2 stabilization trajectory, but is sufficient to form an important component in a portfolio of climate mitigation measures, as well as to provide a significant sustainable energy resource to displace fossil fuel resources. Realizing the potential of energy crops will necessitate optimizing the dry matter and energy yield of these crops per area of land through the latest biotechnological routes, with or without the need for genetic modification. In future, the co‐benefits of bioenergy production will need to be optimized and methods will need to be developed to extract and refine high‐value products from the feedstock before it is used for energy production.