A climate-dependent global model of ammonia emissions from chicken farming

Ammonia (NH3) has significant impacts on the environment, which can influence climate and air quality and cause acidification and eutrophication in terrestrial and aquatic ecosystems. Agricultural activities are the main sources of NH3 emissions globally. Emissions of NH3 from chicken farming are highly dependent on climate, affecting their environmental footprint and impact. In order to investigate the effects of meteorological factors and to quantify how climate change affects these emissions, a process-based model, AMmonia–CLIMate–Poultry (AMCLIM–Poultry), has been developed to simulate and predict temporal variations in NH3 emissions from poultry excretion, here focusing on chicken farms and manure spreading. The model simulates the decomposition of uric acid to form total ammoniacal nitrogen, which then partitions into gaseous NH3 that is released to the atmosphere at an hourly to daily resolution. Ammonia emissions are simulated by calculating nitrogen and moisture budgets within poultry excretion, including a dependence on environmental variables. By applying the model with global data for livestock, agricultural practice and meteorology, we calculate NH3 emissions from chicken farming on a global scale (0.5∘ resolution). Based on 2010 data, the AMCLIM–Poultry model estimates NH3 emissions from global chicken farming of 5.5 ± 1.2 Tg N yr−1, about 13 % of the agriculture-derived NH3 emissions. Taking account of partial control of the ambient environment for housed chicken (layers and broilers), the fraction of excreted nitrogen emitted as NH3 is found to be up to 3 times larger in humid tropical locations than in cold or dry locations. For spreading of manure to land, rain becomes a critical driver affecting emissions in addition to temperature, with the emission fraction being up to 5 times larger in the semi-dry tropics than in cold, wet climates. The results highlight the importance of incorporating climate effects into global NH3 emissions inventories for agricultural sources. The model shows increased emissions under warm and wet conditions, indicating that climate change will tend to increase NH3 emissions over the coming century

Environmental footprint family to address local to planetary sustainability and deliver on the SDGs

The number of publications on environmental footprint indicators has been growing rapidly, but with limited efforts to integrate different footprints into a coherent framework. Such integration is important for comprehensive understanding of environmental issues, policy formulation and assessment of trade-offs between different environmental concerns. Here, we systematize published footprint studies and define a family of footprints that can be used for the assessment of environmental sustainability. We identify overlaps between different footprints and analyse how they relate to the nine planetary boundaries and visualize the crucial information they provide for local and planetary sustainability. In addition, we assess how the footprint family delivers on measuring progress towards Sustainable Development Goals (SDGs), considering its ability to quantify environmental pressures along the supply chain and relating them to the water-energy-food-ecosystem (WEFE) nexus and ecosystem services. We argue that the footprint family is a flexible framework where particular members can be included or excluded according to the context or area of concern. Our paper is based upon a recent workshop bringing together global leading experts on existing environmental footprint indicators

First insights into the phylogenetic diversity of Mycobacterium tuberculosis in Nepal

BACKGROUND: Tuberculosis (TB) is a major public health problem in Nepal. Strain variation in Mycobacterium tuberculosis may influence the outcome of TB infection and disease. To date, the phylogenetic diversity of M. tuberculosis in Nepal is unknown. METHODS AND FINDINGS: We analyzed 261 M. tuberculosis isolates recovered from pulmonary TB patients recruited between August 2009 and August 2010 in Nepal. M. tuberculosis lineages were determined by single nucleotide polymorphisms (SNP) typing and spoligotyping. Drug resistance was determined by sequencing the hot spot regions of the relevant target genes. Overall, 164 (62.8%) TB patients were new, and 97 (37.2%) were previously treated. Any drug resistance was detected in 50 (19.2%) isolates, and 16 (6.1%) were multidrug-resistant. The most frequent M. tuberculosis lineage was Lineage 3 (CAS/Delhi) with 106 isolates (40.6%), followed by Lineage 2 (East-Asian lineage, includes Beijing genotype) with 84 isolates (32.2%), Lineage 4 (Euro-American lineage) with 41 (15.7%) isolates, and Lineage 1 (Indo-Oceanic lineage) with 30 isolates (11.5%). Based on spoligotyping, we found 45 different spoligotyping patterns that were previously described. The Beijing (83 isolates, 31.8%) and CAS spoligotype (52, 19.9%) were the dominant spoligotypes. A total of 36 (13.8%) isolates could not be assigned to any known spoligotyping pattern. Lineage 2 was associated with female sex (adjusted odds ratio [aOR] 2.58, 95% confidence interval [95% CI] 1.42-4.67, p = 0.002), and any drug resistance (aOR 2.79; 95% CI 1.43-5.45; p = 0.002). We found no evidence for an association of Lineage 2 with age or BCG vaccination status. CONCLUSIONS: We found a large genetic diversity of M. tuberculosis in Nepal with representation of all four major lineages. Lineages 3 and 2 were dominating. Lineage 2 was associated with clinical characteristics. This study fills an important gap on the map of the M. tuberculosis genetic diversity in the Asian reg

Implementation strategies for knowledge products in primary healthcare: A systematic review of systematic reviews

BACKGROUND: The underuse or overuse of knowledge products leads to waste in healthcare, and primary care is no exception. OBJECTIVE: We aimed to characterize which knowledge products are frequently implemented, the implementation strategies used in primary care, and the implementation outcomes that are measured. METHODS: We performed a systematic review of systematic reviews (SR) using the Cochrane systematic approach to include eligible SR. The inclusion criteria were: any primary care contexts; healthcare professionals and patients; any EPOC implementation strategies of specified knowledge products; any comparator; and any implementation outcomes based on the Proctor framework. We searched the Medline, EMBASE, CINAHL, Ovid PsycINFO, Web of Science, and Cochrane Library databases from their inception to October 2019, without any restriction. We searched the references of the included SR. Pairs of reviewers independently performed selection, data extraction and methodological quality assessment with AMSTAR 2. Data extraction was informed by EPOC taxonomy for implementation strategies and the Proctor framework for implementation outcomes. We performed a descriptive analysis and summarized the results using a narrative synthesis. RESULTS: Of the 11,101 records identified, 81 SR were included. Forty-seven SR involved healthcare professionals alone. Fifteen SR were of high or moderate methodological quality. Most of them addressed one type of knowledge product (56/81), common clinical practice guidelines (26/56) or management, and behavioural or pharmacological health interventions (24/56). Mixed strategies were used for implementation (67/81), predominantly educational-based (meetings in 60/81, materials distribution in 59/81, and academic detailing in 45/81), reminder (53/81) and audit and feedback (40/81) strategies. Education meetings (P=.13) and academic detailing (P=.11) seem to be more used when the population is composed of Healthcare professionals alone. The improvement of the adoption of knowledge products was the most commonly measured outcome (72/81). The evidence level was reported in 10/81 SR on 62 outcomes (including 48 improvement of adoption), of which 16 outcomes were of moderate or high level. CONCLUSIONS: Clinical practice guidelines and management, behavioural or pharmacological health interventions are the most commonly implemented knowledge products through the mixed use of educational, reminders and audit and feedback strategies. There is need for a strong methodology for the SR of RCTs to explore their effectiveness and the whole cascade of implementation outcomes. CLINICALTRIAL: Not applicable

Nitrogen Challenges and Opportunities for Agricultural and Environmental Science in India

In the last six decades, the consumption of reactive nitrogen (Nr) in the form of fertilizer in India has been growing rapidly, whilst the nitrogen use efficiency (NUE) of cropping systems has been decreasing. These trends have led to increasing environmental losses of Nr, threatening the quality of air, soils, and fresh waters, and thereby endangering climate-stability, ecosystems, and human-health. Since it has been suggested that the fertilizer consumption of India may double by 2050, there is an urgent need for scientific research to support better nitrogen management in Indian agriculture. In order to share knowledge and to develop a joint vision, experts from the UK and India came together for a conference and workshop on “Challenges and Opportunities for Agricultural Nitrogen Science in India.” The meeting concluded with three core messages: (1) Soil stewardship is essential and legumes need to be planted in rotation with cereals to increase nitrogen fixation in areas of limited Nr availability. Synthetic symbioses and plastidic nitrogen fixation are possibly disruptive technologies, but their potential and implications must be considered. (2) Genetic diversity of crops and new technologies need to be shared and exploited to reduce N losses and support productive, sustainable agriculture livelihoods. Móring et al. Nitrogen Challenges and Opportunities (3) The use of leaf color sensing shows great potential to reduce nitrogen fertilizer use (by 10–15%). This, together with the usage of urease inhibitors in neem-coated urea, and better management of manure, urine, and crop residues, could result in a 20–25% improvement in NUE of India by 2030

Selective improvement of global datasets for the computation of locally relevant environmental indicators : A method based on global sensitivity analysis

Several global datasets are available for environmental modelling, but information provided is hardly used for decision-making at a country-level. Here we propose a method, which relies on global sensitivity analysis, to improve local relevance of environmental indicators from global datasets. This method is tested on nitrogen use framework for two contrasted case studies: mixed dairy supply chains in Rwanda and the Netherlands. To achieve this, we evaluate how indicators computed from a global dataset diverge from same indicators computed from survey data. Second, we identify important input parameters that explain the variance of indicators. Subsequently, we fix non-important ones to their average values and substitute important ones with field data. Finally, we evaluate the effect of this substitution. This method improved relevance of nitrogen use indicators; therefore, it can be applied to any environmental modelling using global datasets to improve their relevance by prioritizing important parameters for additional data collection.</p