Publications

Complete mutation hotspot list included in Custom Ampliseq gene panel for melanoma, including common driver mutations in BRAF, NRAS, KRAS, MEK, GNAQ, and GNA11. (DOCX 125 kb)

Food production is a major driver of environmental change, and unhealthy diets are the leading cause of global disease burden. In high-income countries (HICs), modelling studies suggest that adoption of healthy diets could improve population health and reduce environmental footprints associated with food production. We assessed whether such benefits from dietary change could occur in India, where under-nutrition and overweight and obesity are simultaneously prevalent. We calculated the potential changes in greenhouse gas (GHG) emissions, blue and green water footprints (WFs), and land use (LU), that would result from shifting current national food consumption patterns in India to healthy diets (meeting dietary guidelines) and to "affluent diets" (those consumed by the wealthiest quartile of households, which may represent future purchasing power and nutritional trajectories). Dietary data were derived from the 2011-12 nationally-representative household expenditure survey, and we assessed dietary scenarios nationally and across six Indian sub-regions, by rural or urban location, and for those consuming above or below recommended dietary energy intakes. We modelled the changes in consumption of 34 food groups necessary to meet Indian dietary guidelines, as well as an affluent diet representative of those in the highest wealth quartile. These changes were combined with food-specific data on GHG emissions, calculated using the Cool Farm Tool, and WF and LU adapted from the Water Footprint Network and Food and Agriculture Organization, respectively. Shifting to healthy guidelines nationally required a minor increase in dietary energy (3%), with larger increases in fruit (18%) and vegetable (72%) intake, though baseline proportion of dietary energy from fat and protein was adequate and did not change significantly. Meeting healthy guidelines slightly increased environmental footprints by about 3-5% across GHG emissions, blue and green WFs, and LU. However, these national averages masked substantial variation within sub-populations. For example, shifting to healthy diets among those with dietary energy intake below recommended guidelines would result in increases of 28% in GHG emissions, 18 and 34% in blue and green WFs, respectively, and 41% in LU. Decreased environmental impacts were seen among those who currently consume above recommended dietary energy (-6 to -16% across footprints). Adoption of affluent diets by the whole population would result in increases of 19-36% across the environmental indicators. Specific food groups contributing to these shifts varied by scenario. Environmental impacts also varied markedly between six major Indian sub-regions. In India, where undernutrition is prevalent, widespread adoption of healthy diets may lead to small increases in the environmental footprints of the food system relative to the status quo, although much larger increases would occur if there was widespread adoption of diets currently consumed by the wealthiest quartile of the population. To achieve lower diet-related disease burdens and reduced environmental footprints of the food system, greater efficiency of food production and reductions in food waste are likely to be required alongside promotion of healthy diets.

Nitrogen (N) surplus is a useful indicator for improving agricultural N management and controlling N pollution. Few studies have developed benchmark values for cropping systems in China, a country with the largest N fertilizer use in the world. We established N surplus benchmarks for 13 main cropping systems, at optimal N management, using results from >4500 on-farm field experiments and a soil surface balance approach. These cropping systems accounted for about 50% of total N fertilizer consumption in Chinese agriculture in 2009. The results showed that N surplus benchmarks for single cropping systems ranged from 40 to 100 kg N ha^-1 yr^-1 (average 73 kg N ha^-1 yr^-1), and for double cropping systems from 110 to 190 kg N ha^-1 yr^-1 (average 160 kg N ha^-1 yr^-1), roughly twice that of single cropping systems. These N surplus benchmarks may be further refined, following further decreases in N deposition rates and reactive N losses as a result of strict implementation of "4R-nutrient stewardship" and improvements in fertilization techniques and agronomic managements. Our N surplus benchmarks could serve as realistic targets to improve the N management of current conventional practices, and thereby could lay the foundations for a more sustainable N management in China.

Producing sufficient, healthy food for a growing world population amid a changing climate is a major challenge for the twenty-first century. Agricultural trade could help alleviate this challenge by using comparative productivity advantages between countries. However, agricultural trade has implications for national food security and could displace environmental impacts from developed to developing countries. This study illustrates the global effects resulting from the agricultural trade of a single country, by analysing the global cropland and greenhouse gas impacts of the UK's food and feed supply. The global cropland footprint associated with the UK food and feed supply increased by 2022 kha (+23%) from 1986 to 2009. Greenhouse gas emissions (GHGE) associated with fertilizer and manure application, and rice cultivation remained relatively constant at 7.9 Mt CO 2 e between 1987 and 2008. Including GHGE from land-use change, however, leads to an increase from 19.1 in 1987 to 21.9 Mt CO 2 e in 2008. The UK is currently importing over 50% of its food and feed, whereas 70% and 64% of the associated cropland and GHGE impacts, respectively, are located abroad. These results imply that the UK is increasingly reliant on external resources and that the environmental impact of its food supply is increasingly displaced overseas.

Abstract. Reliable quantification of the sources and sinks of greenhouse gases, together with trends and uncertainties, is essential to monitoring the progress in mitigating anthropogenic emissions under the Paris Agreement. This study provides a consolidated synthesis of CH4 and N2O emissions with consistently derived state-of-the-art bottom-up (BU) and top-down (TD) data sources for the European Union and UK (EU27+UK). We integrate recent emission inventory data, ecosystem process-based model results, and inverse modelling estimates over the period 1990–2018. BU and TD products are compared with European National GHG Inventories (NGHGI) reported to the UN climate convention secretariat UNFCCC in 2019. For uncertainties, we used for NGHGI the standard deviation obtained by varying parameters of inventory calculations, reported by the Member States following the IPCC guidelines recommendations. For atmospheric inversion models (TD) or other inventory datasets (BU), we defined uncertainties from the spread between different model estimates or model specific uncertainties when reported. In comparing NGHGI with other approaches, a key source of bias is the activities included, e.g. anthropogenic versus anthropogenic plus natural fluxes. In inversions, the separation between anthropogenic and natural emissions is sensitive to the geospatial prior distribution of emissions. Over the 2011–2015 period, which is the common denominator of data availability between all sources, the anthropogenic BU approaches are directly comparable, reporting mean emissions of 20.8 Tg CH4 yr−1 (EDGAR v5.0) and 19.0 Tg CH4 yr−1 (GAINS), consistent with the NGHGI estimates of 18.9 ± 1.7 Tg CH4 yr−1. TD total inversions estimates give higher emission estimates, as they also include natural emissions. Over the same period regional TD inversions with higher resolution atmospheric transport models give a mean emission of 28.8 Tg CH4 yr−1. Coarser resolution global TD inversions are consistent with regional TD inversions, for global inversions with GOSAT satellite data (23.3 Tg CH4yr−1) and surface network (24.4 Tg CH4 yr−1). The magnitude of natural peatland emissions from the JSBACH-HIMMELI model, natural rivers and lakes emissions and geological sources together account for the gap between NGHGI and inversions and account for 5.2 Tg CH4 yr−1. For N2O emissions, over the 2011–2015 period, both BU approaches (EDGAR v5.0 and GAINS) give a mean value of anthropogenic emissions of 0.8 and 0.9 Tg N2O yr−1 respectively, agreeing with the NGHGI data (0.9 ± 0.6 Tg N2O yr−1). Over the same period, the average of the three total TD global and regional inversions was 1.3 ± 0.4 and 1.3 ± 0.1 Tg N2O yr−1 respectively, compared to 0.9 Tg N2O yr−1 from the BU data. The TU and BU comparison method defined in this study can be operationalized for future yearly updates for the calculation of CH4 and N2O budgets both at EU+UK scale and at national scale. The referenced datasets related to figures are visualized at https://doi.org/10.5281/zenodo.4288969 (Petrescu et al., 2020).