Many climate models treat the light-absorbing SOA component called “brown carbon” (BrC) as non-light absorbing because its formation and transformations are poorly understood. We therefore investigated the influence of reactive nitrogen (NOx, NH3)-, acidity (H2SO4)-, and water-mediated chemistry on SOA formed by the photo-oxidation of toluene, the subsequent formation and transformation of BrC, and its optical properties. We discovered that nitrogen-poor (NP) SOA is formed when the molar ratio of NOx to reacted toluene (henceforth, [NOx/ΔHC]) is 0.15 or less, whereas nitrogen-rich (NR) SOA is formed when [NOx/ΔHC] > 0.15. NR and NP SOA have markedly different characteristics. The light absorption coefficient (Babs) and mass absorption cross-section (MAC) of the SOA increased with [NOx/ΔHC] under both the NP and NR regimes. For NP SOA, the MAC increased with [NOx/ΔHC] independently of the relative humidity (RH). However, the MAC of NR SOA was RH-dependent. Under both NP and NR regimes, acidity promoted SOA browning while NH3 increased Babs and MAC at 80% RH. The highest MAC was observed at the lowest RH (20%) for acidic NR SOA, and it was postulated that the MAC of SOA depends mainly on the pH and the [H+]free/[SOA mass] ratio of the aqueous SOA phase.

The observed high BC and BrC levels were linked to local biomass burning, where BrC was mostly primary in nature and co-emitted with BC. BrC transformation during the daytime was potentially associated with photochemical processes.

Abstract. We report on the long-term performance of a popular low-cost PM2.5 sensor, the PurpleAir PA-II, at multiple sites in India, with the aim of identifying robust calibration protocols. We established 3 distinct sites in India (North India: Delhi, Hamirpur; South India: Bangalore), where we collocated PA-II with reference beta-attenuation monitors to characterize sensor performance and to model calibration relationships between PA-IIs and reference monitors for hourly data. Our sites remained in operation across all major seasons of India. Without calibration, the PA-IIs had high precision (Normalized Root Mean Square Error [NRMSE] among replicate sensors ≤ 15 %) and tracked the overall seasonal and diurnal signals from the reference instruments well (Pearson’s r ≥ 0.9) but were inaccurate (NRMSE ≥ 40 %). We used a comprehensive feature selection process to create optimized site-specific calibrations. Relative to the uncalibrated data, parsimonious least-squares long-term calibration models improved PA-II performance at all sites (cross-validated NRMSE: 20–30 %, R2: 0.82–0.95), particularly by reducing seasonal and diurnal biases. Because aerosol properties and meteorology vary regionally, the form of these long-term models differed by site. Likewise, using a moving-window calibration, we find a calibration scheme using seasonally specific information somewhat improves performance relative to a static long-term calibration model. In contrast, we demonstrate that a successful short-term calibration exercise for one season may not transfer reliably to other seasons. Overall, we demonstrate how the PA-II, when paired with a careful calibration scheme, can provide actionable information on PM2.5 in India with only modest irreducible uncertainty.

In this study, we developed a framework for interpreting the in situ morphological properties of black carbon (BC, also referred to as “soot” due to combustion relevance) mixed with primary organic aerosol. Integration of the experiment considering primary organic aerosol (POA) evaporation from the soot particles was examined using a Differential mass–mobility analyzer (DMA) and showed the untold story of the mixing of BC and POA. We also hypothesize that morphological transformation of soots and determined such as (i) the evaporation of externally and internally mixed POA led to a decline in the particle number and size of monodisperse aerosol; (ii) presence of externally mixed BC was interpreted from the occurrence of two peaks of soot upon heating; (iii) heat-induced collapse of the BC core possibly resulted from the evaporation of material from the voids and effect of heat; (iv) volume equivalent to changes in the mobility diameter represented evaporation of POA from the surface and collapse upon heating. POA constituted a high fraction (20–40% by mass) of aerosol mass from these flames and was predominantly (i.e., 92–97% by mass) internally mixed with BC. POA was found to be highly light absorptive, i.e., an Ångström absorption exponent (AAE) value of (in general) >1.5 was estimated for BC + POA at 405/781 nm wavelengths. Interestingly, a much more highly absorptive POA [mass absorption cross-section (MAC)-5 m2 g−1] at 405 nm was discovered under a specific flame setting, which was comparable to MACs of BC particles (8–9 m2 g−1).

Table S1. Most relevant parameters selected through sequential feature selection (SFS) for each PM2.5 channel (CF1, ATM, ALT) from Delhi collocation. Parameters: relative humidity (RH), temperature (T), and dew point (D). As expected, the PM2.5 was selected as the most relevant, followed by RH features.