Low-Cost Sensor Performance Intercomparison, Correction Factor Development, and 2+ Years of Ambient PM2.5 Monitoring in Accra, Ghana.

Particulate matter air pollution is a leading cause of global mortality, particularly in Asia and Africa. Addressing the high and wide-ranging air pollution levels requires ambient monitoring, but many low- and middle-income countries (LMICs) remain scarcely monitored. To address these data gaps, recent studies have utilized low-cost sensors. These sensors have varied performance, and little literature exists about sensor intercomparison in Africa. By colocating 2 QuantAQ Modulair-PM, 2 PurpleAir PA-II SD, and 16 Clarity Node-S Generation II monitors with a reference-grade Teledyne monitor in Accra, Ghana, we present the first intercomparisons of different brands of low-cost sensors in Africa, demonstrating that each type of low-cost sensor PM2.5 is strongly correlated with reference PM2.5, but biased high for ambient mixture of sources found in Accra. When compared to a reference monitor, the QuantAQ Modulair-PM has the lowest mean absolute error at 3.04 µg/m3, followed by PurpleAir PA-II (4.54 µg/m3) and Clarity Node-S (13.68 µg/m3). We also compare the usage of 4 statistical or machine learning models (Multiple Linear Regression, Random Forest, Gaussian Mixture Regression, and XGBoost) to correct low-cost sensors data, and find that XGBoost performs the best in testing (R2: 0.97, 0.94, 0.96; mean absolute error: 0.56, 0.80, and 0.68 µg/m3 for PurpleAir PA-II, Clarity Node-S, and Modulair-PM, respectively), but tree-based models do not perform well when correcting data outside the range of the colocation training. Therefore, we used Gaussian Mixture Regression to correct data from the network of 17 Clarity Node-S monitors deployed around Accra, Ghana, from 2018 to 2021. We find that the network daily average PM2.5 concentration in Accra is 23.4 µg/m3, which is 1.6 times the World Health Organization Daily PM2.5 guideline of 15 µg/m3. While this level is lower than those seen in some larger African cities (such as Kinshasa, Democratic Republic of the Congo), mitigation strategies should be developed soon to prevent further impairment to air quality as Accra, and Ghana as a whole, rapidly grow.

Surveillance of WHO Priority Gram-Negative Pathogenic Bacteria in Effluents from Two Seafood Processing Facilities in Tema, Ghana, 2021 and 2022: A Descriptive Study.

Antimicrobial resistant (AMR) bacteria in effluents from seafood processing facilities can contribute to the spread of AMR in the natural environment. In this study conducted in Tema, Ghana, a total of 38 effluent samples from two seafood processing facilities were collected during 2021 and 2022, as part of a pilot surveillance project to ascertain the bacterial load, bacterial species and their resistance to 15 antibiotics belonging to the WHO AWaRe group of antibiotics. The bacterial load in the effluent samples ranged from 13-1800 most probable number (MPN)/100 mL. We identified the following bacterial species: E. coli in 31 (82%) samples, K. pneumoniae in 15 (39%) samples, Proteus spp. in 6 (16%) samples, P. aeruginosa in 2 (5%) samples and A. baumannii in 2 (5%) samples. The highest levels of antibiotic resistance (100%) were recorded for ampicillin and cefuroxime among Enterobacteriaceae. The WHO priority pathogens-E. coli (resistant to cefotaxime, ceftazidime and carbapenem) and K.pneumoniae (resistant to ceftriaxone)-were found in 5 (13%) effluent samples. These findings highlight the need for enhanced surveillance to identify the source of AMR and multi-drug resistant bacteria and an adoption of best practices to eliminate these bacteria in the ecosystem of the seafood processing facilities.

Bacteria and Their Antibiotic Resistance Profiles in Ambient Air in Accra, Ghana, February 2020: A Cross-Sectional Study.

Inappropriate use of antibiotics has led to the presence of antibiotic-resistant bacteria in ambient air. There is no published information about the presence and resistance profiles of bacteria in ambient air in Ghana. We evaluated the presence and antibiotic resistance profiles of selected bacterial, environmental and meteorological characteristics and airborne bacterial counts in 12 active air quality monitoring sites (seven roadside, two industrial and three residential) in Accra in February 2020. Roadside sites had the highest median temperature, relative humidity, wind speed and PM10 concentrations, and median airborne bacterial counts in roadside sites (115,000 CFU/m3) were higher compared with industrial (35,150 CFU/m3) and residential sites (1210 CFU/m3). Bacillus species were isolated in all samples and none were antibiotic resistant. There were, however, Pseudomonas aeruginosa, Escherichia coli, Pseudomonas species, non-hemolytic Streptococci, Coliforms and Staphylococci species, of which six (50%) showed mono-resistance or multidrug resistance to four antibiotics (penicillin, ampicillin, ciprofloxacin and ceftriaxone). There was a positive correlation between PM10 concentrations and airborne bacterial counts (rs = 0.72), but no correlations were found between PM10 concentrations and the pathogenic bacteria nor their antibiotic resistance. We call for the expansion of surveillance of ambient air to other cities of Ghana to obtain nationally representative information.