Assessment of carbon Monoxide levels in a commercial district of Akure, Nigeria

The importance of having acceptable indoor environmental quality in building interiors have been well established in rating systems like BREEAM and LEED. However, in a developing nation like Nigeria, where rating systems are under consideration and adequate provision for power is a challenge, retailers in commercial buildings tend to provide power generating sets on their own, more so the influence of vehicular traffic on indoor environment is also of concern to researchers. In the development of a green building rating system for Nigeria, models need to be developed as to the patterns of carbon monoxide (CO) levels in commercial buildings in the country. The purpose of the quantitative study is to assess the level of CO in the terraces of buildings in the Obanla district of Akure in October 2015. Eighty commercial cum residential buildings was assessed in the Ijomu, Obanla commercial axis in Akure, the capital of Ondo State, using dSense Portable CO Meter - a hand held CO monitor, on a once a week measurement, for a month. The implication of increased exposure of CO levels usually from generator fumes and vehicular traffic could lead to reduction in the oxygen carrying capacity of the blood. Results show that the average one hour measurements for eighty positions were 1.225ppm for week one, 1.775ppm for week two, 1.475ppm for week three and 4ppm for week four. These average levels are lower than the WHO indoor air requirement of 30ppm for 1 hour and the USEPA (NAAQS) 35ppm outdoor air 1 hour average

Progress and challenges of demand-led co-produced sub-seasonal-to-seasonal (S2S) climate forecasts in Nigeria

This paper identifies fundamental issues which prevent the effective uptake of climate information services in Nigeria. We propose solutions which involve the extension of short-range (1 to 5 days) forecasts beyond that of medium-range (7 to 15 days) timescales through the operational use of current forecast data as well as improve collaboration and communication with forecast users. Using newly available data to provide seamless operational forecasts from short-term to sub-seasonal timescales, we examine evidence to determine if effective demand-led sub-seasonal-to-seasonal (S2S) climate forecasts can be co-produced. This evidence involves: itemization of forecast products delivered to stakeholders, with their development methodology; enumeration of inferences of forecast products and their influences on decisions taken by stakeholders; user-focused discussions of improvements on co-produced products; and the methods of evaluating the performance of the forecast products. We find that extending the production pipeline of short-range forecast timescales beyond the medium-range, such that the medium-range forecast timescales can be fed into existing tools for applying short-range forecasts, assisted in mitigating the risks of sub-seasonal climate variability on socio-economic activities in Nigeria. We also find that enhancing of collaboration and communication channels between the producers and the forecast product users helps to: enhance the development of user-tailored impact-based forecasts; increases users’ trusts in the forecasts; and, seamlessly improves forecast evaluations. In general, these measures lead to more smooth delivery and increase in uptake of climate information services in Nigeria

Correlation of Global Solar Irradiance with some Meteorological Parameters and Validation of some Existing Solar Radiation Models with Measured Data Over Selected Climatic Zones In Nigeria.

Fourteen models comprising of 12 existing and 2 parameterized models are evaluated for predicting the global solar irradiance on a horizontal surface at six different sites representative of six different climatic zones of Nigeria namely; Mangrove swamp forest (Calabar), Sahel Savannah (Nguru), Montane Vegetation (Yola), Sudan Savannah (Kano), Tropical rain forest (Ibadan) and Guinea Savannah (Minna). Results showed that the two models from this study performed well in predicting global solar irradiance over the six different zones with slight overestimation in some cases and slight underestimation in others. However, out of the two models, model 14 had a better predictive ability. For the 12 existing models, Glover and mcCulloch model was found to be most suitable for the Mangrove swamp forest, Sahel and Montane zones while Raja and Twidell , Rietveld and Annandale et al models are respectively the most suitable models in the Sudan, Tropical rainforest and Guinea zones

The African SWIFT project: growing science capability to bring about a revolution in weather prediction

Africa is poised for a revolution in the quality and relevance of weather predictions, with potential for great benefits in terms of human and economic security. This revolution will be driven by recent international progress in nowcasting, numerical weather prediction, theoretical tropical dynamics and forecast communication, but will depend on suitable scientific investment being made. The commercial sector has recognized this opportunity and new forecast products are being made available to African stakeholders. At this time, it is vital that robust scientific methods are used to develop and evaluate the new generation of forecasts. The GCRF African SWIFT project represents an international effort to advance scientific solutions across the fields of nowcasting, synoptic and short-range severe weather prediction, subseasonal-to-seasonal (S2S) prediction, user engagement and forecast evaluation. This paper describes the opportunities facing African meteorology and the ways in which SWIFT is meeting those opportunities and identifying priority next steps. Delivery and maintenance of weather forecasting systems exploiting these new solutions requires a trained body of scientists with skills in research and training; modelling and operational prediction; communications and leadership. By supporting partnerships between academia and operational agencies in four African partner countries, the SWIFT project is helping to build capacity and capability in African forecasting science. A highlight of SWIFT is the coordination of three weather-forecasting “Testbeds” – the first of their kind in Africa – which have been used to bring new evaluation tools, research insights, user perspectives and communications pathways into a semi-operational forecasting environment