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- Hammar, Linus, 1979, et al.
(författare)
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Simplified site-screening method for micro tidal current turbines applied in Mozambique
- 2012
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Ingår i: Renewable Energy. - : Elsevier BV. - 0960-1481 .- 1879-0682. ; 2012:44, s. 414-422
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Tidskriftsartikel (refereegranskat)abstract
- A variety of tidal current turbines (TCT) are emerging, the majority focussing on large-scale extraction ofrenewable energy at global tidal hot-spots. Concurrently, some turbines are small and may be suitable also for micro-scale applications (micro-TCT) in remote areas, such as decentralized electrification in countries where fuel-independent energy systems with high power predictability are particularly important. In shallow waters the force of tidal currents varies considerably over short distances and very site-specific measurements are important for assessment of localization, but are also expensive. For micro-TCT to be of interest site-screening and evaluation must be inexpensive, and low-cost methods are thus required. This study proposes a simplified tidal model that is calibrated to site-specific conditions by short-term observations using lightweight equipment. By measurements comprising down to 8% of themonthly tidal period the potential power output can be estimated, with uncertainty intervals up to +-20%, for currents applicable for micro-TCT. This site-screening method was tested at five sites in Mozambique where near-shore tidal currents were measured with lightweight current meters. At three of the sites, currents were estimated to exceed 1 m s-1 and power output was calculated based on technical assumptions for a micro-TCT device. Results are discussed from the perspective of micro-TCT development and decentralized remote area electrification.
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| 2. |
- Armando, Chaibo Jose, et al.
(författare)
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Climate variability, socio-economic conditions and vulnerability to malaria infections in Mozambique 2016–2018 : a spatial temporal analysis
- 2023
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Ingår i: Frontiers In Public Health. - : Frontiers Media S.A.. - 2296-2565. ; 11
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Tidskriftsartikel (refereegranskat)abstract
- Background: Temperature, precipitation, relative humidity (RH), and Normalized Different Vegetation Index (NDVI), influence malaria transmission dynamics. However, an understanding of interactions between socioeconomic indicators, environmental factors and malaria incidence can help design interventions to alleviate the high burden of malaria infections on vulnerable populations. Our study thus aimed to investigate the socioeconomic and climatological factors influencing spatial and temporal variability of malaria infections in Mozambique.Methods: We used monthly malaria cases from 2016 to 2018 at the district level. We developed an hierarchical spatial–temporal model in a Bayesian framework. Monthly malaria cases were assumed to follow a negative binomial distribution. We used integrated nested Laplace approximation (INLA) in R for Bayesian inference and distributed lag nonlinear modeling (DLNM) framework to explore exposure-response relationships between climate variables and risk of malaria infection in Mozambique, while adjusting for socioeconomic factors.Results: A total of 19,948,295 malaria cases were reported between 2016 and 2018 in Mozambique. Malaria risk increased with higher monthly mean temperatures between 20 and 29°C, at mean temperature of 25°C, the risk of malaria was 3.45 times higher (RR 3.45 [95%CI: 2.37–5.03]). Malaria risk was greatest for NDVI above 0.22. The risk of malaria was 1.34 times higher (1.34 [1.01–1.79]) at monthly RH of 55%. Malaria risk reduced by 26.1%, for total monthly precipitation of 480 mm (0.739 [95%CI: 0.61–0.90]) at lag 2 months, while for lower total monthly precipitation of 10 mm, the risk of malaria was 1.87 times higher (1.87 [1.30–2.69]). After adjusting for climate variables, having lower level of education significantly increased malaria risk (1.034 [1.014–1.054]) and having electricity (0.979 [0.967–0.992]) and sharing toilet facilities (0.957 [0.924–0.991]) significantly reduced malaria risk.Conclusion: Our current study identified lag patterns and association between climate variables and malaria incidence in Mozambique. Extremes in climate variables were associated with an increased risk of malaria transmission, peaks in transmission were varied. Our findings provide insights for designing early warning, prevention, and control strategies to minimize seasonal malaria surges and associated infections in Mozambique a region where Malaria causes substantial burden from illness and deaths.
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