Browsing by Author "Mead, Iq"
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Item Open Access Investigating the applicability of low-cost sensors for ground-based air quality monitoring networks in developing countries: a Ghana case study.(Cranfield University, 2020-04) Gameli Hodoli, Collins; Mead, Iq; Coulon, FredericWhile several studies have reported on the utility of low-cost sensors for air quality campaigns in advanced countries including the development of data correction and quality improvement mechanisms thereby using them to complement regulatory monitors, there is, in contrast, limited information on the use of low-cost sensors for air pollution applications in Ghana and wider parts of Sub-Saharan Africa. This PhD study presented a proof of concept approach on the feasibility of factory calibrated Alphasense OPC-N2 for two main purposes. Firstly, the suitability of low-cost sensors for high-density ground-based air pollution studies and the applicability of the high-resolution data for quantification of atmospheric emissions. Pearson’s correlation analysis was applied to establish the reproducibility of the selected sensors for high-density ground-based air quality monitoring specifically for PM species due to the spatial and temporal variability and suitability of PM for developing urban air quality standards. Trend analysis, calendar plots and sectorial plots in the components of wind were experimented using the high-resolution data to quantify particulate matter (PM) and its sources. Hourly averaged data from the selected sensors have demonstrated the reproducibility of low-cost OPC-N2 for use in the selected environments for PM with correlation coefficients (Pearson’s, R) between 0.97 and 0.98 for PM₁ , PM₂.₅ and PM₁₀. For quantification of the species monitored, PM₁ 0 values were 500 µg/mᶟ; PM₂.₅ were a little below 90 µg/mᶟ and PM₁ values were a little below 60 µg/mᶟ. These levels though preliminary, agree with PM pollution reported from these types of environments. It was also found that PM pollution was locally characterised with low wind speed (≤ 2 ms⁻¹) tied to background activities and the surrounding environment which includes traffic, wind-blown dust and roadside food cooking and vending activities. The statistical difference in mean values (t-values of 17.3, 11.4 and 4.2 for PM₁ , PM₂.₅ and PM₁₀ respectively) of the reported PM species have shown that the sensors are better suited for PM₁₀ monitoring. Findings from this study provide a benchmark for future (AQ) studies in Ghana, particularly in the selected exemplar urban areas. It demonstrates the feasibility of the current generation of relatively low-cost PM sensors for a high-density ground-based air quality monitoring in environments typical of large parts of West and Sub Saharan Africa.Item Open Access Overview of Performance of Selected Low-Cost Atmospheric Sensor Nodes in Ghanaian urban areas.(Cranfield University, 2020-01-24 09:52) gameli Hodoli, Collins; Coulon, Frederic; Mead, IqThe attached dataset is specific to the overview of performance of selected low-cost atmospheric sensor nodes in Ghanaian urban areas.Item Open Access Road traffic emission dispersion modelling: an application to Hanoi and Ho Chi Minh city using ADMS.(Cranfield University, 2020-08) Ngo, Khoi Quang (Lucas); Mead, Iq; Harris, Neil R. P.Urban air quality in Vietnam has become a pressing matter that require immediate attention to ensure a sustainable development. However due to the overreliance on in-situ observations, which only measure the end result, there is limited understanding of the connection between pollution sources and concentrations. This in turn hinders the effectiveness of environmental law enforcement and management. Since road traffic is widely regarded as the main polluter, attempts have been made to adopt atmospheric dispersion models to traffic emission in Vietnam. Most however, suggest that due to input data scarcity, model applications are limited. This work therefore employed ADMS, an advanced dispersion model that is highly adaptable to produce a full mapping of road traffic derived emission for Hanoi and HCMC, i.e. Vietnam’s 2 most populated cities. Also, a modelling framework, which exploits existing, quality traffic data to generate suitable model inputs, was developed. With this framework, a detailed GIS-based road network dataset that contains road parameters, vehicle count and travel-condition-depending emission factor was produced. Carbon Monoxide was modelled as a pilot pollutant species. Resulted concentrations show an overall moderate positive correlation with observations (r = 0.4). Inadequate information on background pollution however prevents in-depth model validation to be conducted. In overall, this work demonstrates the compatibility of ADMS with the circumstance of Vietnam. Combined with an improved data processing framework, applications of dispersion model in developing countries can be greatly expanded.