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Low-cost gas and particulate matter sensor packages offer a compact, lightweight, and easily transportable solution to address global gaps in air quality (AQ) observations. However, regions that would benefit most from widespread deployment of low-cost AQ monitors often lack the reference-grade equipment required to reliably calibrate and validate them. In this study, we explore approaches to calibrating and validating three integrated sensor packages before a 1-year deployment to rural Malawi using colocation data collected at a regulatory site in North Carolina, USA. We compare the performance of five computational modeling approaches to calibrate the electrochemical gas sensors: k -nearest neighbors (k NN) hybrid, random forest (RF) hybrid, high-dimensional model representation (HDMR), multilinear regression (MLR), and quadratic regression (QR). For the CO, O x , NO, and NO 2 sensors, we found that k NN hybrid models returned the highest coefficients of determination and lowest error metrics when validated. Hybrid models were also the most transferable approach when applied to deployment data collected in Malawi. We compared k NN hybrid calibrated CO observations from two regions in Malawi to remote sensing data and found qualitative agreement in spatial and annual trends. However, ARISense monthly mean surface observations were 2 to 4 times higher than the remote sensing data, partly due to proximity to residential biomass combustion activity not resolved by satellite imaging. We also compared the performance of the integrated Alphasense OPC-N2 optical particle counter to a filter-corrected nephelometer using colocation data collected at one of our deployment sites in Malawi. We found the performance of the OPC-N2 varied widely with environmental conditions, with the worst performance associated with high relative humidity (RH >70 %) conditions and influence from emissions from nearby residential biomass combustion. We did not find obvious evidence of systematic sensor performance decay after the 1-year deployment to Malawi. Data recovery (30 %–80 %) varied by sensor and season and was limited by insufficient power and access to resources at the remote deployment sites. Future low-cost sensor deployments to rural, low-income settings would benefit from adaptable power systems, standardized sensor calibration methodologies, and increased regional regulatory-grade monitoring infrastructure. [ABSTRACT FROM AUTHOR]

Biofuel combustion is an important source of particulate light absorbing organic carbon (OC), also known as brown carbon (BrC). We applied spectrophotometry to characterize methanol-extracted BrC from emission tests of 'real-world' biofuel combustion in India and Malawi, including wood stoves ('traditional', 'improved' and 'chimney') and artisanal charcoal kilns. Average mass absorption coefficient (MACbulk,λ) of extracted BrC was highest for 'traditional', followed by 'improved', 'chimney', and 'charcoal', at near-ultraviolet to blue wavelengths, with this order reversed for BrC absorption Angstrom exponent (AAE). MACbulk,λ in UV wavelengths was positively correlated with the elemental carbon to organic aerosol ratio (EC/OA), though the correlation was weaker than that observed in laboratory cookstove samples. BrC imaginary refractive indices (k) were anti-correlated with wavelength dependence (w), thus less wavelength dependent BrC had higher light absorptivity. MACbulk,λ correlated with the fraction of OC evolving at higher temperature steps in thermo-optical analysis, consistent with a link between BrC absorptivity and OC volatility, and suggesting that BrC absorption may be parameterized using existing OC data. Modeling analyses showed that BrC makes a strong contribution to overall absorption (average of 48% to 80% at 365 nm), and a strong negative correlation between EC/OA and the relative contribution of BrC to total aerosol (BrC + BC) light absorption; the latter trend is dominated by the quantity versus optical properties of BrC. The estimated direct radiative effect of BrC is approximately equal to that of BC for biofuel combustion emissions in India, highlighting the importance of BrC in the climate energy budget. Copyright © 2022 American Association for Aerosol Research [ABSTRACT FROM AUTHOR]