Crude oil spillage is a major challenge in Nigeria. It affects the environment, health, life, and livelihood of residents of the Niger Delta region, where oil is explored, processed, and transported via a network of p...Crude oil spillage is a major challenge in Nigeria. It affects the environment, health, life, and livelihood of residents of the Niger Delta region, where oil is explored, processed, and transported via a network of pipelines. Oil spillage is primarily caused by vandalization/sabotage and operational issues such as corrosion, equipment failure, operation, and maintenance errors. Thus, prompt response is required to mitigate the impact of oil spills. In this study, we deployed low-cost Arduino systems, including sensors (vibration and flow), modules (GPS and Wifi) and an IoT platform (ThingSpeak) to detect spillage caused by vandalism and operational inefficiencies proactively. The results demonstrate that low-cost sensors can detect changes in the flow volume between the inflow and outflow attributable to spillage, and vibration shocks caused by vandalism can be detected and linked to the cause of the spillage and communicated in real time to inform response action. Moreover, we proposed a framework for field validation utilizing KoboToolBox (a crowdsourcing/citizen science platform). The prototype system designed and programmed showed promising results, as it could detect spillage for vandalism and operational scenarios in real-time, quantify the volume of spillage, and identify the location and time of spillage occurrence;indicators relevant for response planning to minimize the impact of oil spillage. A video demonstration of the prototype system developed is accessible via: https://youtu.be/wKa9MZvYf1w. .展开更多
Extreme flood events are becoming more frequent and intense in recent times, owing to climate change and other anthropogenic factors. Nigeria, the case-study for this research experiences recurrent flooding, with the ...Extreme flood events are becoming more frequent and intense in recent times, owing to climate change and other anthropogenic factors. Nigeria, the case-study for this research experiences recurrent flooding, with the most disastrous being the 2012 flood event that resulted in unprecedented damage to infrastructure, displacement of people, socio-economic disruption, and loss of lives. To mitigate and minimize the impact of such floods now and in the future, effective planning is required, underpinned by analytics based on reliable data and information. Such data are seldom available in many developing regions, owing to financial, technical, and organizational drawbacks that result in short-length and inadequate historical data that are prone to uncertainties if directly applied for flood frequency estimation. This study applies regional Flood Frequency Analysis (FFA) to curtail deficiencies in historical data, by agglomerating data from various sites with similar hydro-geomorphological characteristics and is governed by a similar probability distribution, differing only by an “index-flood”;as well as accounting for climate variability effect. Data from 17 gauging stations within the Ogun-Osun River Basin in Western Nigeria were analysed, resulting in the delineation of 3 sub-regions, of which 2 were homogeneous and 1 heterogeneous. The Generalized Logistic distribution was fitted to the annual maximum flood series for the 2 homogeneous regions to estimate flood magnitudes and the probability of occurrence while accounting for climate variability. The influence of climate variability on flood estimates in the region was linked to the Madden-Julian Oscillation (MJO) climate indices and resulted in increased flood magnitude for regional and direct flood frequency estimates varying from 0% - 35% and demonstrate that multi-decadal changes in atmospheric conditions influence both small and large floods. The results reveal the value of considering climate variability for flood frequency analysis, especially when non-stationarity is established by homogeneity analysis.展开更多
With the increasing trend of development and industrialization in Malaysia, air pollution has become an inevitable part of the process, resulting from increased vehicular activities and industrial processes. Toll oper...With the increasing trend of development and industrialization in Malaysia, air pollution has become an inevitable part of the process, resulting from increased vehicular activities and industrial processes. Toll operators are potentially exposed to high levels of air pollutants from working in proximity to traffic pollution sources, thereby increasing their risk of health defects associated with air pollution exposure. This study assessed the levels of Nitrogen dioxide (NO2) toll operators are exposed to, considering the influences traffic density and meteorological factors. This is intended to serve as an indicator of the cumulative pollution emanating from the combustion process of vehicles at toll plazas. Using Passive diffusion samplers saturated with Triethanolamine (TEA), the weekly indoor and outdoor NO2 concentrations at tollbooth were measured at Sungai Besi (SB), Kajang (KJ) and Putra-Makhota (PM) toll Plazas, to capture the varying traffic densities of 138,000, 65,000 and 24,100 vehicles/day respectively. The results showed that NO2 concentrations increase with traffic densities, and indoor NO2 concentrations correlated highly with outdoor NO2 concentrations (R2: SB = 0.767, KJ = 0.689 and PM = 0.877). The indoor/outdoor NO2 ratio varied from 0.7 to 1.2 for all toll booths, suggesting pollution control in-efficiency, caused by technical and behavioural factors. Also, meteorological factors had no significant effect on nitrogen dioxide concentrations, contrary to previous studies, which is likely due to the far distance between tool plazas and meteorological stations. Furthermore, the NO2 concentrations reported in this study were higher in comparison to weekly standards adopted in Germany (0.032 ppm) and previous literature. Therefore, toll operators are potentially exposed to high levels of pollution, and we advise that toll operators to wear pollution protection gears to reduce the risk of exposure, and the ventilation systems and mitigation measure (air curtain) reviewed to assess its efficiency.展开更多
文摘Crude oil spillage is a major challenge in Nigeria. It affects the environment, health, life, and livelihood of residents of the Niger Delta region, where oil is explored, processed, and transported via a network of pipelines. Oil spillage is primarily caused by vandalization/sabotage and operational issues such as corrosion, equipment failure, operation, and maintenance errors. Thus, prompt response is required to mitigate the impact of oil spills. In this study, we deployed low-cost Arduino systems, including sensors (vibration and flow), modules (GPS and Wifi) and an IoT platform (ThingSpeak) to detect spillage caused by vandalism and operational inefficiencies proactively. The results demonstrate that low-cost sensors can detect changes in the flow volume between the inflow and outflow attributable to spillage, and vibration shocks caused by vandalism can be detected and linked to the cause of the spillage and communicated in real time to inform response action. Moreover, we proposed a framework for field validation utilizing KoboToolBox (a crowdsourcing/citizen science platform). The prototype system designed and programmed showed promising results, as it could detect spillage for vandalism and operational scenarios in real-time, quantify the volume of spillage, and identify the location and time of spillage occurrence;indicators relevant for response planning to minimize the impact of oil spillage. A video demonstration of the prototype system developed is accessible via: https://youtu.be/wKa9MZvYf1w. .
文摘Extreme flood events are becoming more frequent and intense in recent times, owing to climate change and other anthropogenic factors. Nigeria, the case-study for this research experiences recurrent flooding, with the most disastrous being the 2012 flood event that resulted in unprecedented damage to infrastructure, displacement of people, socio-economic disruption, and loss of lives. To mitigate and minimize the impact of such floods now and in the future, effective planning is required, underpinned by analytics based on reliable data and information. Such data are seldom available in many developing regions, owing to financial, technical, and organizational drawbacks that result in short-length and inadequate historical data that are prone to uncertainties if directly applied for flood frequency estimation. This study applies regional Flood Frequency Analysis (FFA) to curtail deficiencies in historical data, by agglomerating data from various sites with similar hydro-geomorphological characteristics and is governed by a similar probability distribution, differing only by an “index-flood”;as well as accounting for climate variability effect. Data from 17 gauging stations within the Ogun-Osun River Basin in Western Nigeria were analysed, resulting in the delineation of 3 sub-regions, of which 2 were homogeneous and 1 heterogeneous. The Generalized Logistic distribution was fitted to the annual maximum flood series for the 2 homogeneous regions to estimate flood magnitudes and the probability of occurrence while accounting for climate variability. The influence of climate variability on flood estimates in the region was linked to the Madden-Julian Oscillation (MJO) climate indices and resulted in increased flood magnitude for regional and direct flood frequency estimates varying from 0% - 35% and demonstrate that multi-decadal changes in atmospheric conditions influence both small and large floods. The results reveal the value of considering climate variability for flood frequency analysis, especially when non-stationarity is established by homogeneity analysis.
文摘With the increasing trend of development and industrialization in Malaysia, air pollution has become an inevitable part of the process, resulting from increased vehicular activities and industrial processes. Toll operators are potentially exposed to high levels of air pollutants from working in proximity to traffic pollution sources, thereby increasing their risk of health defects associated with air pollution exposure. This study assessed the levels of Nitrogen dioxide (NO2) toll operators are exposed to, considering the influences traffic density and meteorological factors. This is intended to serve as an indicator of the cumulative pollution emanating from the combustion process of vehicles at toll plazas. Using Passive diffusion samplers saturated with Triethanolamine (TEA), the weekly indoor and outdoor NO2 concentrations at tollbooth were measured at Sungai Besi (SB), Kajang (KJ) and Putra-Makhota (PM) toll Plazas, to capture the varying traffic densities of 138,000, 65,000 and 24,100 vehicles/day respectively. The results showed that NO2 concentrations increase with traffic densities, and indoor NO2 concentrations correlated highly with outdoor NO2 concentrations (R2: SB = 0.767, KJ = 0.689 and PM = 0.877). The indoor/outdoor NO2 ratio varied from 0.7 to 1.2 for all toll booths, suggesting pollution control in-efficiency, caused by technical and behavioural factors. Also, meteorological factors had no significant effect on nitrogen dioxide concentrations, contrary to previous studies, which is likely due to the far distance between tool plazas and meteorological stations. Furthermore, the NO2 concentrations reported in this study were higher in comparison to weekly standards adopted in Germany (0.032 ppm) and previous literature. Therefore, toll operators are potentially exposed to high levels of pollution, and we advise that toll operators to wear pollution protection gears to reduce the risk of exposure, and the ventilation systems and mitigation measure (air curtain) reviewed to assess its efficiency.
