Low-Cost PM2.5 Sensor Performance Characteristics against Meteorological Influence in Sub-Saharan Africa: Evidence from the Air Sensor Evaluation and Training Facility for the West Africa Project

被引:0
作者
Nimo, James [1 ,2 ,3 ]
Borketey, Mathias A. [2 ]
Appoh, Emmanuel K. -E. [2 ]
Morrison, Abena Kyerewaa [2 ]
Ibrahim-Anyass, Yussif [2 ]
Owusu Tawiah, Audrey [2 ]
Arku, Raphael E. [4 ]
Amoah, Selina [5 ]
Tetteh, Esi Nerquaye [5 ]
Brown, Tim [6 ]
Presto, Albert A. [7 ]
Subramanian, R. [8 ]
Westervelt, Daniel M. [9 ,10 ]
Giordano, Michael R. [2 ,6 ,11 ]
Hughes, Allison Felix [2 ,3 ]
机构
[1] SUNY Albany, Dept Environm & Sustainable Engn, Albany, NY 12203 USA
[2] Univ Ghana, Dept Phys, Air Sensor Evaluat & Training Facil West Africa, LG 25, Accra, Ghana
[3] Univ Ghana, Dept Biomed Engn, POB LG 25, Accra, Ghana
[4] Univ Massachusetts, Dept Environm Hlth Sci, Amherst, MA 01003 USA
[5] Ghana Minist Hlth Author, GA-1071998 Accra, Ghana
[6] Kigali Collaborat Res Ctr, BP6150, Kigali, Rwanda
[7] Carnegie Mellon Univ, Dept Mech Engn, Pittsburgh, PA 15213 USA
[8] Ctr Study Sci Technol & Policy CSTEP, Bengaluru 560094, India
[9] Columbia Univ, Lamont Doherty Earth Observ, Palisades, NY 10964 USA
[10] Univ Mohammed VI Polytech, Benguerir 43150, Morocco
[11] Minist Hlth, BP6150, Kigali, Rwanda
关键词
air quality; Afri-SET; low-cost sensors; Open Air; Air Visual Outdoor; ModulAir-PM; Air Quality Egg; Airly PM; AirBeam3; Sensor.Africa; Praxis Urban; sub-Saharan Africa; OPTICAL-PARTICLE COUNTER; CLIMATE-CHANGE; POLLUTION; AMBIENT; CALIBRATION; IMPACTS; OPC-N3; HEALTH; OZONE;
D O I
10.1021/acs.est.4c09752
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Fine particulate matter (PM2.5) pollution represents a major environmental health risk in Africa. The use of low-cost sensors (LCS) for air quality monitoring for policy and civic engagement in sub-Saharan Africa (SSA) has become paramount, as access to traditional reference-grade instruments is still sparse. Yet, studies pertaining to sensor performance under SSA's meteorological conditions and diverse emission sources are limited. Hence, we tested eight low-cost PM2.5 sensors on the market from different manufacturers containing Plantower PMS, Alphasense OPC-N3, and AVO-Sensor sensors by collocating them with the federal equivalent method Teledyne T640 to ascertain data accuracy, reliability, and responsiveness during wet and dry periods. After 6 months of collocation, PM2.5 concentrations from the LCS showed low intrasensor variability in both the wet and dry periods, but high intersensor variability with the Teledyne T640. A strong relationship existed between the LCS and Teledyne T640, with average coefficient of determination (R 2) values of 0.7 (range: 05-0.9) and 0.8 (0.64-0.97) in the wet and dry periods, respectively. Larger errors were also associated with LCS data during the dry than the wet period, with the average mean absolute error and root mean squared error, respectively, 4.5 and 5.3 times higher in the dry period. Uncertainties with large errors were also observed with high PM2.5 measured in the wet period, levels that were more common during the dry period typically characterized by long-range transport of PM2.5 pollution. The results show that season significantly affects LCS performance and data quality and that care must be taken during deployment and data usage in SSA, with regular maintenance, particularly in the dry season. Strong collaborative efforts between governmental agencies, industries, and civil society are needed to come up with an effective framework for their application.
引用
收藏
页码:6623 / 6635
页数:13
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