The spatial distribution of ammonia, methane and nitrous oxide emissions from agriculture in the UK 2016

Annual Report to Defra (Project SCF0107), modelling and mapping UK ammonia and greenhouse gas emissions from agriculture. • Agricultural emissions of ammonia, methane and nitrous oxide for 2016 were spatially distributed across the UK, and maps produced. • Emission estimates produced for the 2016 inventory are based on a new emissions model developed by ADAS, Rothamsted Research and Cranfield University. The new emissions model replaces the previous NARSES and GHGI spreadsheets used to estimate emissions in the 2015 inventory and has been written in C#. • In parallel with the development of the new emission inventory model under Defra project SCF0102, the AENEID model, used to produce high-resolution maps of UK agricultural emissions, has also been updated. The new model version builds on techniques previously implemented in the AENEID model (e.g. Dragosits et al. 1998, Hellsten et al. 2008) and has been developed in the R statistical environment. It produces non-disclosive agricultural emission maps at a grid resolution of 1 km, compared with a 5 km grid resolution previously. The model incorporates detailed agricultural census data, landcover data (Rowland et al., 2017), agricultural practice information (e.g. fertiliser application rates, stocking densities) and emission source strength data from the UK emissions inventories for agriculture 2016 (Wakeling et al. 2018 and Brown et al. 2018). • All emission maps correspond to the totals reported by Rothamsted Research North Wyke (RResNW) for 2016

The spatial distribution of ammonia, methane and nitrous oxide emissions from agriculture in the UK 2018

Annual Report to Defra (Project SCF0107). • Agricultural emissions of ammonia, methane and nitrous oxide for 2018 were spatially distributed across the UK, and maps produced. • Holding-level agricultural statistics on livestock numbers and crop areas for 2018 were not available in sufficient time for a full inventory model run. Therefore emission estimates produced for the 2018 inventory were derived by scaling the 2017 emissions based on the changes to 2018 in DA-level livestock numbers and crop areas. • Non-disclosive agricultural emission maps were produced at a grid resolution of 1 km by 1 km, using detailed agricultural census data, land cover data (Rowland et al., 2017), agricultural practice information (e.g. fertiliser application rates, stocking densities) and emission source strength data from the UK emissions inventories for agriculture 2017 (Misselbrook and Gilhespy 2020 and Brown et al. 2020). • All emission maps correspond to the totals reported by Rothamsted Research North Wyke (RResNW) for 2018

UK emissions of the greenhouse gas nitrous oxide

Signatories of the Kyoto Protocol are obliged to submit annual accounts of their anthropogenic greenhouse gas emissions, which include nitrous oxide (N2O). Emissions from the sectors industry (3.8 Gg), energy (14.4 Gg), agriculture (86.8 Gg), wastewater (4.4 Gg), land use, land-use change and forestry (2.1 Gg) can be calculated by multiplying activity data (i.e. amount of fertilizer applied, animal numbers) with simple emission factors (Tier 1 approach), which are generally applied across wide geographical regions. The agricultural sector is the largest anthropogenic source of N2O in many countries and responsible for 75 per cent of UK N2O emissions. Microbial N2O production in nitrogen-fertilized soils (27.6 Gg), nitrogen-enriched waters (24.2 Gg) and manure storage systems (6.4 Gg) dominate agricultural emission budgets. For the agricultural sector, the Tier 1 emission factor approach is too simplistic to reflect local variations in climate, ecosystems and management, and is unable to take into account some of the mitigation strategies applied. This paper reviews deviations of observed emissions from those calculated using the simple emission factor approach for all anthropogenic sectors, briefly discusses the need to adopt specific emission factors that reflect regional variability in climate, soil type and management, and explains how bottom-up emission inventories can be verified by top-down modelling

The influence of residential and workday population mobility on exposure to air pollution in the UK

Traditional approaches of quantifying population-level exposure to air pollution assume that concentrations of air pollutants at the residential address of the study population are representative for overall exposure. This introduces potential bias in the quantification of human health effects. Our study combines new UK Census data comprising information on workday population densities, with high spatio-temporal resolution air pollution concentration fields from the WRF-EMEP4UK atmospheric chemistry transport model, to derive more realistic estimates of population exposure to NO2, PM2.5 and O3. We explicitly allocated workday exposures for weekdays between 8:00 am and 6:00 pm. Our analyses covered all of the UK at 1 km spatial resolution. Taking workday location into account had the most pronounced impact on potential exposure to NO2, with an estimated 0.3 μg m−3 (equivalent to 2%) increase in population-weighted annual exposure to NO2 across the whole UK population. Population-weighted exposure to PM2.5 and O3 increased and decreased by 0.3%, respectively, reflecting the different atmospheric processes contributing to the spatio-temporal distributions of these pollutants. We also illustrate how our modelling approach can be utilised to quantify individual-level exposure variations due to modelled time-activity patterns for a number of virtual individuals living and working in different locations in three example cities. Changes in annual-mean estimates of NO2 exposure for these individuals were considerably higher than for the total UK population average when including their workday location. Conducting model-based evaluations as described here may contribute to improving representativeness in studies that use small, portable, automatic sensors to estimate personal exposure to air pollution

UK informative inventory report (1990 to 2013)

This is the 10th Informative Inventory Report (IIR) from the UK National Atmospheric Emissions Inventory (NAEI) Programme. The report is compiled to accompany the UK’s 2015 data submission under the United Nations Economic Commission for Europe (UNECE) Convention on Long-Range Transboundary Air Pollution (CLRTAP) and contains detailed information on annual emission estimates of air quality pollutants by source in the UK from 1990 onwards

Long-term increases in soil carbon due to ecosystem fertilization by atmospheric nitrogen deposition demonstrated by regional-scale modelling and observations

Fertilization of nitrogen (N)-limited ecosystems by anthropogenic atmospheric nitrogen deposition (Ndep) may promote CO2 removal from the atmosphere, thereby buffering human effects on global radiative forcing. We used the biogeochemical ecosystem model N14CP, which considers interactions among C (carbon), N and P (phosphorus), driven by a new reconstruction of historical Ndep, to assess the responses of soil organic carbon (SOC) stocks in British semi-natural landscapes to anthropogenic change. We calculate that increased net primary production due to Ndep has enhanced detrital inputs of C to soils, causing an average increase of 1.2 kgCm−2 (c. 10%) in soil SOC over the period 1750–2010. The simulation results are consistent with observed changes in topsoil SOC concentration in the late 20th Century, derived from sample-resample measurements at nearly 2000 field sites. More than half (57%) of the additional topsoil SOC is predicted to have a short turnover time (c. 20 years), and will therefore be sensitive to future changes in Ndep. The results are the first to validate model predictions of Ndep effects against observations of SOC at a regional field scale. They demonstrate the importance of long-term macronutrient interactions and the transitory nature of soil responses in the terrestrial C cycle

A Spatial Analysis of Atmospheric Ammonia and Ammonium in the U.K.

As measures are implemented internationally to reduce SO2 and NOx emissions, attention is falling on the contribution of NH3 emissions to acidification, nitrogen eutrophication, and aerosol formation. In the U.K., a monitoring network has been established to measure the spatial distribution and long-term trends in atmospheric gaseous NH3 and aerosol NH4+. At the same time, an atmospheric chemistry and transport model, FRAME, has been developed with a focus on reduced nitrogen (NHx). The monitoring data are important to evaluate the model, while the model is essential for a more detailed spatial assessment. The national network is established with over 80 sampling locations. Measurements of NH3 and NH4+ (at up to 50 sites) have been made using a new low-cost denuder-filterpack system. Additionally, improved passive sampling methods for NH3 have been applied to explore local variability. The measurements confirm the high spatial variability of NH3 (annual means 0.06 to 11 mg NH3 m�3), consistent with its nature as a primary pollutant emitted from ground-level sources, while NH4+, being a slowly formed secondary product, shows much less spatial variability (0.14 to 2.4 mg NH4+ m�3). These features are reproduced in the FRAME model, which provides estimates at a 5-km level. Analysis of the underlying NH3 emission inventory shows that sheep emissions may have been underestimated and nonagricultural sources overestimated relative to emissions from cattle. The combination of model and measurements is applied to estimate spatial patterns of dry deposition to different vegetation types. The combined approach provides the basis to assess NHx responses across the U.K. to international emission controls

Vegetation analysis and bioindicator checks at Ballynahone Bog SAC.

Ballynahone Bog is designated as a Special Area of Conservation (SAC) and Area of Special Scientific Interest (ASSI). It is one of the largest intact active raised bogs in Northern Ireland with hummock and hollow pool complexes. The peatland flora includes bog-rosemary Andromeda polifolia, and the bog-mosses Sphagnum fuscum, S. imbricatum and S. pulchrum

The impact of oxygen on the transcriptome of recombinant S. cerevisiae and P. pastoris - a comparative analysis

Background: Saccharomyces cerevisiae and Pichia pastoris are two of the most relevant microbial eukaryotic platforms for the production of recombinant proteins. Their known genome sequences enabled several transcriptomic profiling studies under many different environmental conditions, thus mimicking not only perturbations and adaptations which occur in their natural surroundings, but also in industrial processes. Notably, the majority of such transcriptome analyses were performed using non-engineered strains. In this comparative study, the gene expression profiles of S. cerevisiae and P. pastoris, a Crabtree positive and Crabtree negative yeast, respectively, were analyzed for three different oxygenation conditions (normoxic, oxygen-limited and hypoxic) under recombinant protein producing conditions in chemostat cultivations. Results: The major differences in the transcriptomes of S. cerevisiae and P. pastoris were observed between hypoxic and normoxic conditions, where the availability of oxygen strongly affected ergosterol biosynthesis, central carbon metabolism and stress responses, particularly the unfolded protein response. Steady state conditions under low oxygen set-points seemed to perturb the transcriptome of S. cerevisiae to a much lesser extent than the one of P. pastoris, reflecting the major tolerance of the baker's yeast towards oxygen limitation, and a higher fermentative capacity. Further important differences were related to Fab production, which was not significantly affected by oxygen availability in S. cerevisiae, while a clear productivity increase had been previously reported for hypoxically grown P. pastoris. Conclusions: The effect of three different levels of oxygen availability on the physiology of P. pastoris and S. cerevisiae revealed a very distinct remodelling of the transcriptional program, leading to novel insights into the different adaptive responses of Crabtree negative and positive yeasts to oxygen availability. Moreover, the application of such comparative genomic studies to recombinant hosts grown in different environments might lead to the identification of key factors for efficient protein production