MOPGA/Make Air Quality Great Again: Filling in the air quality data gap in Africa using lower-cost RAMP monitors

• DOI: 10.5194/egusphere-egu2020-10942
• Publication Date: 2020-03-09T21:42:26Z
• Authors: Ramachandran Subr...; Matthias Beekmann; Carl Malings; Anais Feron; Paola Formenti; Michael Giordano; Beatrice Marticorena; Corinne Galy-Lacaux; Catherine Liousse; Joseph Adesina; Stuart Piketh; Kofi Amegah; Julien Bahino; Véronique Yoboué; Laouali Dungall; Rebecca M Garland; Jimmy Gasore; Vincent Madadi; Jean-Louis Rajot
• Keywords: 13. Climate action; 11. Sustainability; 6. Clean water; 3. Good health

<p>Ambient air pollution is a leading cause of premature mortality across the world, with an estimated 258,000 deaths in Africa (UNICEF/GBD 2017). These impacts have large uncertainties as many major cities do not any ground-based quality monitoring. The lack data due part to high cost traditional monitoring equipment and trained personnel. As “Make Air Quality Great Again” project under Our Planet framework (MOPGA), we propose filling this gap low-cost sensors carefully calibrated against reference monitors.</p><p>Fifteen real-time affordable multi-pollutant (RAMP) monitors been deployed Abidjan, Côte d'Ivoire; Accra, Ghana; Kigali, Rwanda; Nairobi, Kenya; Niamey, Niger; Zamdela, South (near Johannesburg). RAMPs use Plantower optical nephelometers measure fine particulate matter mass (PM<sub>2.5</sub>) four Alphasense electrochemical detect pollutant gases including nitrogen dioxide (NO<sub>2</sub>) ozone (O<sub>3</sub>).</p><p>Using calibration developed Créteil, France, deployments thus far reveal morning evening spikes combustion-related pollution. median hourly NO<sub>2</sub> Accra Nairobi for September-October 2019 was about 11 ppb; similar value observed November-December Zamdela. However, previous long-term deployment Rwanda showed that, robust quality, must be collocated develop localized models. Hence, acquired regulatory-grade PM<sub>2.5</sub>, NO<sub>2</sub>, O<sub>3</sub> Abidjan Accra. We also existing Lamto (a rural site d'Ivoire). In talk, will present results on spatio-temporal variability collocation-based sensor calibrations these different cities, source identification, challenges plans future expansion.</p>