Browsing by Author "Gameli Hodoli, Collins"

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    Applicability of factory calibrated optical particle counters for high-density air quality monitoring networks in Ghana
    (Elsevier, 2020-06-16) Gameli Hodoli, Collins; Coulon, Frederic; Mead, Mohammed Iqbal
    In this study, we demonstrate the feasibility of using miniaturised optical particle counters (OPCs) for understanding AQ in Sub-Saharan Africa. Specifically, the potential use of OPCs for high-density ground-based air pollution networks and the use of derived data for quantification of atmospheric emissions were investigated. Correlation and trend analysis for particulate matters (PM), including PM10, PM2.5 and PM1 were undertaken on hourly basis alongside modelled meteorological parameters. Hourly averaged PM values were 500 μg/m3, 90 μg/m3 and 60 μg/m3 for PM10, PM2.5 and PM1, respectively and Pearson's correlation coefficient ranged between 0.97 and 0.98. These levels are in the agreement with range of PM emission reported for these types of environmental settings. PM was locally associated with low wind speeds (<= 2 ms−1) and was closely linked to anthropogenic activities. This study provides a benchmark for future AQ and demonstrates the feasibility of the current generation of OPCs for AQ monitoring in environments typical of large parts of West and Sub Saharan Africa.
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    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, Frederic
    While 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.
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    Source identification with high-temporal resolution data from low-cost sensors using bivariate polar plots in urban areas of Ghana
    (Elsevier, 2022-11-28) Gameli Hodoli, Collins; Coulon, Frederic; Mead, Mohammed Iqbal
    The emergence of low-cost sensors for atmospheric observations presents a new opportunity for identifying atmospheric emission sources based on high-resolution data reporting. Low-cost sensors have been widely assessed for use in source monitoring and identification of hotspots of key atmospheric species in advanced countries (e.g., for CO, NOx, CO2, SO2, O3, VOCs and PM (PM10, PM2.5 including emerging PM1). In contrast, research in recent years has focused on their utility for real-time monitoring, understanding precision and associated calibration requirements in technologically lagging environments. This leads to limited evidence on the utility of high-resolution data from low-cost sensor networks for air pollution source identification in Ghana and more widely across the African continent. In this paper, we demonstrate the potential of low-cost sensors for emission source apportionment in urban areas of Ghana when used with analytical tools such as sectoral and cluster analysis. With a 14-week dataset from a low-cost sensor deployment study at Cape Coast in the Central Region of Ghana, we aimed to identify sources of particulate matter (PM2.5 and PM10). PM pollution was local (associated with increased PM at wind speeds of ≤2 ms−1). High levels of PM during this study were associated with transport from the NNE. For coarse PM, hourly levels as high as 125 μg/m3 were observed at higher wind speeds (7-8 ms−1) indicating the importance of meteorology in the transport of PM. This study suggests that low-cost sensors could be deployed to (1) augment any existing sparsely distributed air quality monitoring and (2) undertake air quality monitoring for source apportionment studies in areas with no existing air quality observational capability (with appropriate calibration and operation in both cases). The urban landscape monitored in this study is typical of both Ghana and wider areas across Sub-Saharan Africa demonstrating the reproducibility of this study.