ALBERT

Description: Particles in smoke emitted from biomass combustion have a large impact on global climate and urban air quality. There is limited understanding of how particle optical properties – especially the contributions of black carbon (BC) and brown carbon (BrC) – evolve with photochemical aging of smoke. We analyze the evolution of the optical properties and chemical composition of particles produced from combustion of a wide variety of biomass fuels, largely from the western United States. The smoke is photochemically aged in a reaction chamber over atmospheric-equivalent timescales ranging from 0.25 to 8 d. Various aerosol optical properties (e.g., the single-scatter albedo, the wavelength dependence of absorption, and the BC mass absorption coefficient, MACBC) evolved with photochemical aging, with the specific evolution dependent on the initial particle properties and conditions. The impact of coatings on BC absorption (the so-called lensing effect) was small, even after photochemical aging. The initial evolution of the BrC absorptivity (MACBrC) varied between individual burns but decreased consistently at longer aging times; the wavelength dependence of the BrC absorption generally increased with aging. The observed changes to BrC properties result from a combination of secondary organic aerosol (SOA) production and heterogeneous oxidation of primary and secondary OA mass, with SOA production being the major driver of the changes. The SOA properties varied with time, reflecting both formation from precursors having a range of lifetimes with respect to OH and the evolving photochemical environment within the chamber. Although the absorptivity of BrC generally decreases with aging, the dilution-corrected absorption may actually increase from the production of SOA. These experimental results provide context for the interpretation of ambient observations of the evolution of particle optical properties in biomass-combustion-derived smoke plumes.

Description: Relationships between various optical, physical, and chemical properties of biomass-combustion-derived particles are characterized for particles produced in the laboratory from a wide range of fuels and burn conditions. The modified combustion efficiency (MCE), commonly used to parameterize biomass particle emissions and properties, is shown to generally have weak predictive capabilities, especially for more efficient combustion conditions. There is, however, a strong relationship between many intensive optical properties (e.g., single-scatter albedo, Ångström absorption exponent, mass absorption efficiency) and the organic aerosol-to-black carbon ([OA] ∕ [BC]) mass ratio over a wider range than previously considered (0.3 to 105). The properties of brown carbon (BrC, i.e., light-absorbing organic carbon) also vary with [OA] ∕ [BC]. Coating-induced enhancements (i.e., “lensing” effects) contribute only a minor amount to BC absorption for all of the burns despite some burns producing particles having large ensemble-average coating-to-core mass ratios. The BC–OA mixing state varies strongly with [OA] ∕ [BC]; the fraction of OA that is internally mixed with BC decreases with [OA] ∕ [BC] while the relative amount of OA coated on BC increases. In contrast, there is little relationship between many OA bulk chemical properties and [OA] ∕ [BC], with the O : C and H : C atomic ratios and the relative abundance of a key marker ion (m/z=60, linked to levoglucosan) all showing no dependence on [OA] ∕ [BC]. In contrast, both the organic nitrate fraction of OA and the OA volatility do depend on the [OA] ∕ [BC]. Neither the total particle nor BC-specific size distributions exhibit any clear dependence on the burn conditions or [OA] ∕ [BC], although there is perhaps a dependence on fuel type. Overall, our results expand on existing knowledge to contribute new understanding of the properties of particles emitted from biomass combustion.

Description: Low-cost sensors for measuring particulate matter (PM) offer the ability to understand human exposure to air pollution at spatiotemporal scales that have previously been impractical. However, such low-cost PM sensors tend to be poorly characterized, and their measurements of mass concentration can be subject to considerable error. Recent studies have investigated how individual factors can contribute to this error, but these studies are largely based on empirical comparisons and generally do not examine the role of multiple factors simultaneously. Here, we present a new physics-based framework and open-source software package (opcsim) for evaluating the ability of low-cost optical particle sensors (optical particle counters and nephelometers) to accurately characterize the size distribution and/or mass loading of aerosol particles. This framework, which uses Mie theory to calculate the response of a given sensor to a given particle population, is used to estimate the fractional error in mass loading for different sensor types given variations in relative humidity, aerosol optical properties, and the underlying particle size distribution. Results indicate that such error, which can be substantial, is dependent on the sensor technology (nephelometer vs. optical particle counter), the specific parameters of the individual sensor, and differences between the aerosol used to calibrate the sensor and the aerosol being measured. We conclude with a summary of likely sources of error for different sensor types, environmental conditions, and particle classes and offer general recommendations for the choice of calibrant under different measurement scenarios.

Description: Atmospheric particulate matter smaller than 2.5 µm in diameter (PM2.5) has a negative impact on public health, the environment, and Earth's climate. Consequently, a need exists for accurate, distributed measurements of surface-level PM2.5 concentrations at a global scale. Existing PM2.5 measurement infrastructure provides broad PM2.5 sampling coverage but does not adequately characterize community-level air pollution at high temporal resolution. This motivates the development of low-cost sensors which can be more practically deployed in spatial and temporal configurations currently lacking proper characterization. Wendt et al. (2019) described the development and validation of a first-generation device for low-cost measurement of AOD and PM2.5: the Aerosol Mass and Optical Depth (AMODv1) sampler. Ford et al. (2019) describe a citizen-science field deployment of the AMODv1 device. In this paper, we present an updated version of the AMOD, known as AMODv2, featuring design improvements and extended validation to address the limitations of the AMODv1 work. The AMODv2 measures AOD and PM2.5 at 20 min time intervals. The sampler includes a motorized Sun tracking system alongside a set of four optically filtered photodiodes for semicontinuous, multiwavelength (current version at 440, 500, 675, and 870 nm) AOD sampling. Also included are a Plantower PMS5003 sensor for time-resolved optical PM2.5 measurements and a pump/cyclone system for time-integrated gravimetric filter measurements of particle mass and composition. AMODv2 samples are configured using a smartphone application, and sample data are made available via data streaming to a companion website (https://csu-ceams.com/, last access: 16 July 2021). We present the results of a 9 d AOD validation campaign where AMODv2 units were co-located with an AERONET (Aerosol Robotics Network) instrument as the reference method at AOD levels ranging from 0.02 ± 0.01 to 1.59 ± 0.01. We observed close agreement between AMODv2s and the reference instrument with mean absolute errors of 0.04, 0.06, 0.03, and 0.03 AOD units at 440, 500, 675, and 870 nm, respectively. We derived empirical relationships relating the reference AOD level to AMODv2 instrument error and found that the mean absolute error in the AMODv2 deviated by less than 0.01 AOD units between clear days and elevated-AOD days and across all wavelengths. We identified bias from individual units, particularly due to calibration drift, as the primary source of error between AMODv2s and reference units. In a test of 15-month calibration stability performed on 16 AMOD units, we observed median changes to calibration constant values of −7.14 %, −9.64 %, −0.75 %, and −2.80 % at 440, 500, 675, and 870 nm, respectively. We propose annual recalibration to mitigate potential errors from calibration drift. We conducted a trial deployment to assess the reliability and mechanical robustness of AMODv2 units. We found that 75 % of attempted samples were successfully completed in rooftop laboratory testing. We identify several failure modes in the laboratory testing and describe design changes that we have since implemented to reduce failures. We demonstrate that the AMODv2 is an accurate, stable, and low-cost platform for air pollution measurement. We describe how the AMODv2 can be implemented in spatial citizen-science networks where reference-grade sensors are economically impractical and low-cost sensors lack accuracy and stability.