Suchergebnisse

Plantains (Musa spp., plantain subgroup in the AAB genome group), an important staple food and income crop for millions of people in Africa and Latin America, grow best at lower elevations (<1,200 m a.s.l.) characterized by high temperatures and humid conditions. In Africa, this includes the Congo basin that has a high diversity of plantains. Plantains are high in pro-vitamin A carotenoid content, and identifying cultivars suitable for mid- to high altitude sites could potentially increase their contribution to reducing the problem of vitamin A deficiency. This study evaluated 52 plantain cultivars sourced from eastern DR Congo (representing the majority of plantain diversity in Eastern DR Congo and less than 50% of the known diversity across the whole of DR Congo) for their interaction and adaptability to different altitudes/temperatures, with the aim of identifying cultivars suited to high/cooler altitudes. The performance of plantains declined with increasing altitude. Highest yields (18–50 tonnes ha-1 yr-1) occurred at 1,066 m compared with 11–35 at the mid-altitude (1,815 m), and only 0.6–3.5 tonnes ha-1 yr-1 at the high altitude (2,172 m) site. Most (65%) of the 52 plantain cultivars performed well at the mid-altitude site. Thus, and in agreement with previous reports on 5 plantains, a broad range of plantains sourced from Eastern DR Congo could be promoted at mid-altitude areas that have traditionally been known to be conducive for only the East African highland bananas (Musa AAA-EAH genome group). Studies to evaluate, at mid- to high elevation, a larger portion of the plantain diversity of the whole of DR Congo and even West Africa are warranted. ; Directorate-General for Development Cooperation and Humanitarian Aid, Belgium ; Peer Review

Solid waste management (SWM) decision makers are under increasing pressure to implement strategies that are both cost effective and environmentally sound. Consequently, SWM has developed into a highly complex systemic planning problem and analytical tools are needed to assist in the development of more sustainable SWM strategies. Here, we present the Solid Waste Infrastructure Modelling System (SWIMS) software, which is the first non-linear dynamic, LCA-based optimisation tool for SWM that optimises for both economic and environmental performance. The environmental and economic costs of treating generated wastes at available treatment facilities are calculated through a series of life cycle process models, based on non-linear expressions defined for each waste material and each treatment process type. Possible treatment paths for waste streams are identified using a depth first search algorithm and a sequential evolutionary genetic algorithm is used to prioritise the order of these paths, in lieu of user defined optimisation criteria and constraints. SWIMS calculates waste arisings into the future and determines if it is possible to treat generated waste, while considering present and future constraints (e.g. capacity). If additional capacity is required, SWIMS will identify the optimum infrastructure solution to meet this capacity demand. A demonstrative case study of MSW management in GB from 2010 to 2050 is presented. Results suggest that sufficient capacity is available in existing and planned infrastructure to cope with future demand for SWM and meet national regulatory and legislative requirements with relatively little capital investment beyond 2020. SWIMS can be used to provide valuable information for SWM decision makers, particularly when used to analyse the effects of possible future national or regional policies.

Accurate monitoring of global scale changes in the terrestrial biosphere has become acutely important as the scope of human impacts on biological systems and atmospheric chemistry grows. For example, the Kyoto Protocol of 1997 signals some of the dramatic socioeconomic and political decisions that may lie ahead concerning CO2 emissions and global carbon cycle impacts. These decisions will rely heavily on accurate measures of global biospheric changes Schimel 1998 and IGBP TCWG 1998. An array of national and international programs have inaugurated global satellite observations, critical field measurements of carbon and water fluxes, and global model development for the purposes of beginning to monitor the biosphere. The detection by these programs of interannual variability of ecosystem fluxes and of longer term trends will permit early indication of fundamental biospheric changes which might otherwise go undetected until major biome conversion begins. This article describes a blueprint for more comprehensive coordination of the various flux measurement and modeling activities into a global terrestrial monitoring network that will have direct relevance to the political decision making of global change.

Attenuated backscatter measurements from a Vaisala CL31 ceilometer and a modified form of the well-known slope method are used to derive the ceilometer extinction profiles during rain events, restricted to rainfall rates (RRs) below approximately 10 mm/h. RR estimates from collocated S-band radar and portable disdrometer are used to derive the RR-to-extinction correlation models for the ceilometer-radar and ceilometer-disdrometer combinations. Data were collected during an intensive observation period of the Verification of the Origins of Rotation in Tornadoes Experiment Southeast (VORTEX-SE) conducted in northern Alabama. These models are used to estimate the RR from the ceilometer observations in similar situations that do not have collocated radar or the disdrometer. Such correlation models are, however, limited by the different temporal and spatial resolutions of the measured variables, measurement capabilities of the instruments, and the inherent assumption of a homogeneous atmosphere. An empirical method based on extinction and RR uncertainty scoring and covariance fitting are proposed to solve, in part, these limitations. ; This work was supported by the National Oceanic and Atmospheric Administration (NOAA) under Grant NA1501R4590232 and Grant NA16OAR4590209 and by the Department of Earth, Atmospheric, and Planetary Sciences, Purdue University. CommSensLab-Universitat Politècnica de Catalunya (UPC) (which is a María de Maeztu Excellence Unit funded by the Agencia Estatal de Investigación, Spain; MDM-2016-0600) collaborated via Spanish Government - European Regional Development Funds under PGC2018-094132-B-I00 and TEC2015- 63832-P projects, and via European Union (funds) (EU) Funds under Grant H2020 ACTRIS-2 (GA-654109) and Grant ACTRIS-PPP (GA-739530). The work of Rubén Barragán was supported by the Spanish Ministry of Science, Innovation and Universities under Grant BES-2013-066340. ; Peer Reviewed ; Postprint (published version)