Modelling spatial and inter-annual variations of nitrous oxide emissions from UK cropland and grasslands using DailyDayCent

This work contributes to the Defra funded projects AC0116: ‘Improving the nitrous oxide inventory’, and AC0114: ‘Data Synthesis, Management and Modelling’. Funding for this work was provided by the UK Department for Environment, Food and Rural Affairs (Defra) AC0116 and AC0114, the Department of Agriculture, Environment and Rural Affairs for Northern Ireland, the Scottish Government and the Welsh Government. Rothamsted Research receives strategic funding from the Biotechnology and Biological Sciences Research Council. This study also contributes to the projects: N-Circle (BB/N013484/1), U-GRASS (NE/M016900/1) and GREENHOUSE (NE/K002589/1).Peer reviewedPublisher PD

Greenhouse gas and ammonia emission mitigation priorities for UK policy targets

Acknowledgements Many thanks to the Association of Applied Biologist’s for organising and hosting the ‘Agricultural greenhouse gases and ammonia mitigation: Solutions, challenges, and opportunities’ workshop. This work was supported with funding from the Scottish Government’s Strategic Research Programme (2022-2027, C2-1 SRUC) and BBSRC (BBS/E/C/000I0320 and BBS/E/C/000I0330). We also acknowledge support from UKRI694 BBSRC (United Kingdom Research and Innovation-Biotechnology and Biological Sciences 695 Research Council; United Kingdom) via grants BBS/E/C/000I0320 and BBS/E/C/000I0330. and Rothamsted Research's Science Initiative Catalyst Award (SICA) supported by BBSRC.Peer reviewedPublisher PD

Measuring the availability of human resources for health and its relationship to universal health coverage for 204 countries and territories from 1990 to 2019: a systematic analysis for the Global Burden of Disease Study 2019

Background: Human resources for health (HRH) include a range of occupations that aim to promote or improve human health. The UN Sustainable Development Goals (SDGs) and the WHO Health Workforce 2030 strategy have drawn attention to the importance of HRH for achieving policy priorities such as universal health coverage (UHC). Although previous research has found substantial global disparities in HRH, the absence of comparable cross-national estimates of existing workforces has hindered efforts to quantify workforce requirements to meet health system goals. We aimed to use comparable and standardised data sources to estimate HRH densities globally, and to examine the relationship between a subset of HRH cadres and UHC effective coverage performance. Methods: Through the International Labour Organization and Global Health Data Exchange databases, we identified 1404 country-years of data from labour force surveys and 69 country-years of census data, with detailed microdata on health-related employment. From the WHO National Health Workforce Accounts, we identified 2950 country-years of data. We mapped data from all occupational coding systems to the International Standard Classification of Occupations 1988 (ISCO-88), allowing for standardised estimation of densities for 16 categories of health workers across the full time series. Using data from 1990 to 2019 for 196 of 204 countries and territories, covering seven Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) super-regions and 21 regions, we applied spatiotemporal Gaussian process regression (ST-GPR) to model HRH densities from 1990 to 2019 for all countries and territories. We used stochastic frontier meta-regression to model the relationship between the UHC effective coverage index and densities for the four categories of health workers enumerated in SDG indicator 3.c.1 pertaining to HRH: physicians, nurses and midwives, dentistry personnel, and pharmaceutical personnel. We identified minimum workforce density thresholds required to meet a specified target of 80 out of 100 on the UHC effective coverage index, and quantified national shortages with respect to those minimum thresholds. Findings: We estimated that, in 2019, the world had 104·0 million (95% uncertainty interval 83·5–128·0) health workers, including 12·8 million (9·7–16·6) physicians, 29·8 million (23·3–37·7) nurses and midwives, 4·6 million (3·6–6·0) dentistry personnel, and 5·2 million (4·0–6·7) pharmaceutical personnel. We calculated a global physician density of 16·7 (12·6–21·6) per 10 000 population, and a nurse and midwife density of 38·6 (30·1–48·8) per 10 000 population. We found the GBD super-regions of sub-Saharan Africa, south Asia, and north Africa and the Middle East had the lowest HRH densities. To reach 80 out of 100 on the UHC effective coverage index, we estimated that, per 10 000 population, at least 20·7 physicians, 70·6 nurses and midwives, 8·2 dentistry personnel, and 9·4 pharmaceutical personnel would be needed. In total, the 2019 national health workforces fell short of these minimum thresholds by 6·4 million physicians, 30·6 million nurses and midwives, 3·3 million dentistry personnel, and 2·9 million pharmaceutical personnel. Interpretation: Considerable expansion of the world's health workforce is needed to achieve high levels of UHC effective coverage. The largest shortages are in low-income settings, highlighting the need for increased financing and coordination to train, employ, and retain human resources in the health sector. Actual HRH shortages might be larger than estimated because minimum thresholds for each cadre of health workers are benchmarked on health systems that most efficiently translate human resources into UHC attainment

Developing greenhouse gas marginal abatement cost curves for agricultural emissions from crops and soils in the UK

Emissions of greenhouse gases from agriculture are likely to come under increasing scrutiny as governments around the world develop proposals for large cuts in greenhouse gas emissions. Yet while there is a range of technically feasible measures for reducing agricultural emissions, it is not immediately apparent which options deliver the most economically efficient reductions in greenhouse gases. This paper develops a marginal abatement cost curve (MACC) for crop and soil measures applicable in UK agriculture. A range of specific abatement measures are screened for their cost-effectiveness and mitigation potential in the field. An efficient subset is identified with reference to a cost per tonne threshold of [less-than-or-equals, slant]£100/tCO2e. Results indicate that the abatement potential by 2022 is likely to be between 1.628 and 10.164 MtCO2e y-1 depending on the policies implemented, with a central estimate of 5.196 MtCO2e y-1. This represents 11.5% of the 2005 UK agricultural GHG emissions.Marginal abatement cost curves Greenhouse gas mitigation Crops and soils

Sarıkamış İhata Manevrası ve Meydan Muharebesi (...3.Ordu)

Mathematical models, such as the DNDC (DeNitrification DeComposition) model, are powerful tools that are increasingly being used to examine the potential impacts of management and climate change in agriculture. DNDC can simulate the processes responsible for production, consumption and transport of nitrous oxide (N2O). During the last 20 years DNDC has been modified and adapted by various research groups around the world to suit specific purposes and circumstances. In this paper we review the different versions of the DNDC model including models developed for different ecosystems, e.g. Forest-DNDC, Forest-DNDC-Tropica, regionalised for different areas of the world, e.g. NZ-DNDC, UK-DNDC, modified to suit specific crops, e.g. DNDC-Rice, DNDC-CSW or modularised e.g. Mobile-DNDC, Landscape-DNDC. A �family tree� and chronological history of the DNDC model is presented, outlining the main features of each version. A literature search was conducted and a survey sent out to c. 1500 model users worldwide to obtain information on the use and development of DNDC. Survey results highlight the many strengths of DNDC including the comparative ease with which the DNDC model can be used and the attractiveness of the graphical user interface. Identified weaknesses could be rectified by providing a more comprehensive user manual, version control and increasing model transparency in collaboration with the Global Research Alliance Modelling Platform (GRAMP), which has much to offer the DNDC user community in terms of promoting the use of DNDC and addressing the deficiencies in the present arrangements for the models� stewardship