12 research outputs found

    Articulating the effect of food systems innovation on the Sustainable Development Goals

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    Acknowledgments MH, DM-D, JP, JRB, AH, GDB, CMG, CLM, and KR acknowledge funding from the Commonwealth Scientific and Industrial Research Organisation. PKT, BMC, AJ, and AML acknowledge funding from the CGIAR Research Program on Climate Change, Agriculture and Food Security, which is supported by the CGIAR Trust Fund and through bilateral funding agreements. PP acknowledges funding from the German Federal Ministry of Education and Research for the BIOCLIMAPATHS project.Peer reviewedPublisher PD

    Convection forced by a descending dry layer and low-level moist convergence

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    A narrow line of convective showers was observed over southern England on 18 July 2005 during the Convective Storm Initiation Project (CSIP). The showers formed behind a cold front (CF), beneath two apparently descending dry layers (i.e. sloping so that they descended relative to the instruments observing them). The lowermost dry layer was associated with a tropopause fold from a depression, which formed 2 d earlier from a breaking Rossby wave, located northwest of the UK. The uppermost dry layer had fragmented from the original streamer due to rotation around the depression (This rotation was also responsible for the observations of apparent descent - ascent would otherwise be seen behind a CF). The lowermost dry layer descended over the UK and overran higher θw air beneath it, resulting in potential instability. Combined with a surface convergence line (which triggered the convection but had less impact on the convective available potential energy than the potential instability), convection was forced up to 5.5 km where the uppermost dry layer capped it. The period when convection was possible was very short, thus explaining the narrowness of the shower band. Convective Storm Initiation Project observations and model data are presented to illustrate the unique processes in this case. © 2009 The Authors Journal compilation © 2009 Blackwell Munksgaard

    Meteorology, Air Quality, and Health in London: The ClearfLo Project

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    Air quality and heat are strong health drivers, and their accurate assessment and forecast are important in densely populated urban areas. However, the sources and processes leading to high concentrations of main pollutants, such as ozone, nitrogen dioxide, and fine and coarse particulate matter, in complex urban areas are not fully understood, limiting our ability to forecast air quality accurately. This paper introduces the Clean Air for London (ClearfLo; www.clearflo.ac.uk) project’s interdisciplinary approach to investigate the processes leading to poor air quality and elevated temperatures. Within ClearfLo, a large multi-institutional project funded by the U.K. Natural Environment Research Council (NERC), integrated measurements of meteorology and gaseous, and particulate composition/loading within the atmosphere of London, United Kingdom, were undertaken to understand the processes underlying poor air quality. Long-term measurement infrastructure installed at multiple levels (street and elevated), and at urban background, curbside, and rural locations were complemented with high-resolution numerical atmospheric simulations. Combining these (measurement–modeling) enhances understanding of seasonal variations in meteorology and composition together with the controlling processes. Two intensive observation periods (winter 2012 and the Summer Olympics of 2012) focus upon the vertical structure and evolution of the urban boundary layer; chemical controls on nitrogen dioxide and ozone production—in particular, the role of volatile organic compounds; and processes controlling the evolution, size, distribution, and composition of particulate matter. The paper shows that mixing heights are deeper over London than in the rural surroundings and that the seasonality of the urban boundary layer evolution controls when concentrations peak. The composition also reflects the seasonality of sources such as domestic burning and biogenic emissions

    Articulating the effect of food systems innovation on the Sustainable Development Goals

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    Food system innovations will be instrumental to achieving multiple Sustainable Development Goals (SDGs). However, major innovation breakthroughs can trigger profound and disruptive changes, leading to simultaneous and interlinked reconfigurations of multiple parts of the global food system. The emergence of new technologies or social solutions, therefore, have very different impact profiles, with favourable consequences for some SDGs and unintended adverse side-effects for others. Stand-alone innovations seldom achieve positive outcomes over multiple sustainability dimensions. Instead, they should be embedded as part of systemic changes that facilitate the implementation of the SDGs. Emerging trade-offs need to be intentionally addressed to achieve true sustainability, particularly those involving social aspects like inequality in its many forms, social justice, and strong institutions, which remain challenging. Trade-offs with undesirable consequences are manageable through the development of well planned transition pathways, careful monitoring of key indicators, and through the implementation of transparent science targets at the local level

    Regional modeling of climate change impacts on smallholder agriculture and ecosystems in Central America

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    Climate change will have serious repercussions for agriculture, ecosystems, and farmer livelihoods in Central America. Smallholder farmers are particularly vulnerable due to their reliance on agriculture and ecosystem services for their livelihoods. There is an urgent need to develop national and local adaptation responses to reduce these impacts, yet evidence from historical climate change is fragmentary. Modeling efforts help bridge this gap. Here, we review the past decade of research on agricultural and ecological climate change impact models for Central America. The results of this review provide insights into the expected impacts of climate change and suggest policy actions that can help minimize these impacts. Modeling indicates future climate-driven changes, often declines, in suitability for Central American crops. Declines in suitability for coffee, a central crop in the regional economy, are noteworthy. Ecosystem models suggest that climate-driven changes are likely at low- and high-elevation montane forest transitions. Modeling of vulnerability suggests that smallholders in many parts of the region have one or more vulnerability factors that put them at risk. Initial adaptation policies can be guided by these existing modeling results. At the same time, improved modeling is being developed that will allow policy action specifically targeted to vulnerable groups, crops, and locations. We suggest that more robust modeling of ecological responses to climate change, improved representation of the region in climate models, and simulation of climate influences on crop yields and diseases (especially coffee leaf rust) are key priorities for future research.International Development Research Centre/[AC3]/IDRC/CanadaUniversidad de Costa Rica/[805-B6-143]/UCR/Costa RicaUniversidad de Costa Rica/[805-B4-227]/UCR/Costa RicaUniversidad de Costa Rica/[805-B3-600]/UCR/Costa RicaMinisterio de Ciencia, Tecnología y Telecomunicaciones/[]/MICIT/Costa RicaUCR::Vicerrectoría de Investigación::Unidades de Investigación::Ciencias Básicas::Centro de Investigaciones Geofísicas (CIGEFI

    CropPol : a dynamic, open and global database on crop pollination

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    Seventy five percent of the world's food crops benefit from insect pollination. Hence, there has been increased interest in how global change drivers impact this critical ecosystem service. Because standardized data on crop pollination are rarely available, we are limited in our capacity to understand the variation in pollination benefits to crop yield, as well as to anticipate changes in this service, develop predictions, and inform management actions. Here, we present CropPol, a dynamic, open, and global database on crop pollination. It contains measurements recorded from 202 crop studies, covering 3,394 field observations, 2,552 yield measurements (i.e., berry mass, number of fruits, and fruit density [kg/ha], among others), and 47,752 insect records from 48 commercial crops distributed around the globe. CropPol comprises 32 of the 87 leading global crops and commodities that are pollinator dependent. Malus domestica is the most represented crop (32 studies), followed by Brassica napus (22 studies), Vaccinium corymbosum (13 studies), and Citrullus lanatus (12 studies). The most abundant pollinator guilds recorded are honey bees (34.22% counts), bumblebees (19.19%), flies other than Syrphidae and Bombyliidae (13.18%), other wild bees (13.13%), beetles (10.97%), Syrphidae (4.87%), and Bombyliidae (0.05%). Locations comprise 34 countries distributed among Europe (76 studies), North America (60), Latin America and the Caribbean (29), Asia (20), Oceania (10), and Africa (7). Sampling spans three decades and is concentrated on 2001-2005 (21 studies), 2006-2010 (40), 2011-2015 (88), and 2016-2020 (50). This is the most comprehensive open global data set on measurements of crop flower visitors, crop pollinators and pollination to date, and we encourage researchers to add more datasets to this database in the future. This data set is released for non-commercial use only. Credits should be given to this paper (i.e., proper citation), and the products generated with this database should be shared under the same license terms (CC BY-NC-SA)
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