Quantifying functional group compositions of household fuel-burning emissions.

Globally, billions of people burn fuels indoors for cooking and heating, which contributes to millions of chronic illnesses and premature deaths annually. Additionally, residential burning contributes significantly to black carbon emissions, which have the highest global warming impacts after carbon dioxide and methane. In this study, we use Fourier transform infrared spectroscopy (FTIR) to analyze fine-particulate emissions collected on Teflon membrane filters from 15 cookstove types and 5 fuel types. Emissions from three fuel types (charcoal, kerosene, and red oak wood) were found to have enough FTIR spectral response for functional group (FG) analysis. We present distinct spectral profiles for particulate emissions of these three fuel types. We highlight the influential FGs constituting organic carbon (OC) using a multivariate statistical method and show that OC estimates by collocated FTIR and thermal-optical transmittance (TOT) are highly correlated, with a coefficient determination of 82.5 %. As FTIR analysis is fast and non-destructive and provides complementary FG information, the analysis method demonstrated herein can substantially reduce the need for thermal-optical measurements for source emissions.

Elemental Characterization of Ambient Particulate Matter for a Globally Distributed Monitoring Network: Methodology and Implications.

Global ground-level measurements of elements in ambient particulate matter (PM) can provide valuable information to understand the distribution of dust and trace elements, assess health impacts, and investigate emission sources. We use X-ray fluorescence spectroscopy to characterize the elemental composition of PM samples collected from 27 globally distributed sites in the Surface PARTiculate mAtter Network (SPARTAN) over 2019-2023. Consistent protocols are applied to collect all samples and analyze them at one central laboratory, which facilitates comparison across different sites. Multiple quality assurance measures are performed, including applying reference materials that resemble typical PM samples, acceptance testing, and routine quality control. Method detection limits and uncertainties are estimated. Concentrations of dust and trace element oxides (TEO) are determined from the elemental dataset. In addition to sites in arid regions, a moderately high mean dust concentration (6 µg/m3) in PM2.5 is also found in Dhaka (Bangladesh) along with a high average TEO level (6 µg/m3). High carcinogenic risk (>1 cancer case per 100000 adults) from airborne arsenic is observed in Dhaka (Bangladesh), Kanpur (India), and Hanoi (Vietnam). Industries of informal lead-acid battery and e-waste recycling as well as coal-fired brick kilns likely contribute to the elevated trace element concentrations found in Dhaka.

Oxidized and Unsaturated: Key Organic Aerosol Traits Associated with Cellular Reactive Oxygen Species Production in the Southeastern United States.

Exposure to ambient fine particulate matter (PM2.5) is associated with millions of premature deaths annually. Oxidative stress through overproduction of reactive oxygen species (ROS) is a possible mechanism for PM2.5-induced health effects. Organic aerosol (OA) is a dominant component of PM2.5 worldwide, yet its role in PM2.5 toxicity is poorly understood due to its chemical complexity. Here, through integrated cellular ROS measurements and detailed multi-instrument chemical characterization of PM in urban southeastern United States, we show that oxygenated OA (OOA), especially more-oxidized OOA, is the main OA type associated with cellular ROS production. We further reveal that highly unsaturated species containing carbon-oxygen double bonds and aromatic rings in OOA are major contributors to cellular ROS production. These results highlight the key chemical features of ambient OA driving its toxicity. As more-oxidized OOA is ubiquitous and abundant in the atmosphere, this emphasizes the need to understand its sources and chemical processing when formulating effective strategies to mitigate PM2.5 health impacts.

Beyond the Ångström Exponent: Probing Additional Information in Spectral Curvature and Variability of In Situ Aerosol Hyperspectral (0.3-0.7 µm) Optical Properties.

Ångström exponents (α) allow reconstruction of aerosol optical spectra over a broad range of wavelengths from measurements at two or more wavelengths. Hyperspectral measurements of atmospheric aerosols provide opportunities to probe measured spectra for information inaccessible from only a few wavelengths. Four sets of hyperspectral in situ aerosol optical coefficients (aerosol-phase total extinction, σ ext, and absorption, σ abs; liquid-phase soluble absorption from methanol, σ MeOH-abs, and water, σ DI-abs, extracts) were measured from biomass burning aerosols (BBAs). Hyperspectral single scattering albedo (ω), calculated from σ ext and σ abs, provide spectral resolution over a wide spectral range rare for this optical parameter. Observed spectral shifts between σ abs and σ MeOH-abs/σ DI-abs argue in favor of measuring σ abs rather than reconstructing it from liquid extracts. Logarithmically transformed spectra exhibited curvature better fit by second-order polynomials than linear α. Mapping second order fit coefficients (a 1, a 2) revealed samples from a given fire tended to cluster together, that is, aerosol spectra from a given fire were similar to each other and somewhat distinct from others. Separation in (a 1, a 2) space for spectra with the same α suggest additional information in second-order parameterization absent from the linear fit. Spectral features found in the fit residuals indicate more information in the measured spectra than captured by the fits. Above-detection σ MeOH-abs at 0.7 µm suggests assuming all absorption at long visible wavelengths is BC to partition absorption between BC and brown carbon (BrC) overestimates BC and underestimates BrC across the spectral range. Hyperspectral measurements may eventually discriminate BBA among fires in different ecosystems under variable conditions.

Analysis of black carbon on filters by image-based reflectance.

Black carbon (BC) is an important contributor to global particulate matter emissions. BC is associated with adverse health effects, and an important short-lived climate pollutant. Here, we describe a low cost method of analysis that utilizes images of PTFE filters taken with a digital camera to estimate BC content on filters. This method is compared with two existing optical methods for analyzing BC (Smokestain Reflectance and Hybrid Integrating Plate and Sphere System) as well as the standard chemical analysis method for determining elemental carbon (Thermal-Optical Reflectance). In comparisons of aerosol generated under controlled conditions (using an inverted diffusion flame burner to cover a range of mass loading and reflectance levels) (N=12) and in field samples collected from residential solid fuel combustion in China and India (N=50), the image-based method was found to correlate well (normalized RMSE <10% for all comparisons) with existing methods. A correlational analysis of field samples between the optical methods and Fourier-transform infrared spectroscopy indicated that the same functional groups were predominantly responsible for light attenuation in each optical method. This method offers reduced equipment cost, rapid analysis time, and is available at no cost, which may facilitate more measurement of BC where PM2.5 mass concentrations are already measured, especially in low income countries or other sampling efforts with limited resources.

Long-Term Strategy for Assessing Carbonaceous Particulate Matter Concentrations from Multiple Fourier Transform Infrared (FT-IR) Instruments: Influence of Spectral Dissimilarities on Multivariate Calibration Performance.

Matching the spectral response between multiple spectrometers is a mandatory procedure when developing robust calibrations whose prediction is independent of instrument-related signal variations. A viable alternative to complex calibration transfer methods consists of matching the instrument spectral response by controlling a set of key instrumental and environmental parameters. This paper discusses the applicability of such an approach to three Fourier transform infrared (FT-IR) spectrometers used for the routine assessment of carbonaceous particulate matter concentrations in the Interagency Monitoring of PROtected Visual Environments (IMPROVE) speciation network. The effectiveness of the proposed matching procedure is evaluated by comparing the spectral response for each individual instrument in order to characterize the extent, and nature, of the remaining inter-instrument spectral dissimilarities. Instrument-related contributions to the signal were determined to be small compared with the spectral variability induced by the filter type used for sample collection. The impact of spectral differences on prediction was addressed through the comparison of model performance derived from multiple calibration scenarios. A hybrid model yielding accurate and homogeneous prediction regardless of the instrument was proposed for organic carbon (OC) and elemental carbon (EC), two major constituents of atmospheric particulate matter. Coefficients of determination of 0.98 (OC) and 0.90 (EC) with median biases not exceeding 0.20 µg (OC) and 0.07 µg (EC) are reported. The long-term stability, assessed from weekly measurements of reference samples, shows a deviation in predicted concentrations of less than ±5% over a 2.5-year period for most of the data collected. Extending OC and EC hybrid models to the prediction of ambient samples collected during the two subsequent years provides satisfactory performance. The proposed instrument matching procedure coupled with the relative simplicity of the hybrid model is an alternative to computationally advanced calibration transfer methodologies for the characterization of carbonaceous particulate matter using multiple FT-IR instruments.

The impact of the 2016 Fort McMurray Horse River Wildfire on ambient air pollution levels in the Athabasca Oil Sands Region, Alberta, Canada.

An unprecedented wildfire impacted the northern Alberta city of Fort McMurray in May 2016 causing a mandatory city wide evacuation and the loss of 2,400 homes and commercial structures. A two-hectare wildfire was discovered on May 1, grew to ~157,000ha by May 5, and continued to burn an estimated ~590,000ha by June 13. A comprehensive air monitoring network operated by the Wood Buffalo Environmental Association (WBEA) in and around Fort McMurray provided essential health-related real-time air quality data to firefighters during the emergency, and provided a rare opportunity to elucidate the impact of gaseous and particulate matter emissions on near-field communities and regional air pollution concentrations. The WBEA network recorded 188 fire-related exceedances of 1-hr and 24-hr Alberta Ambient Air Quality Objectives. Two air monitoring sites within Fort McMurray recorded mean/maximum 1-hr PM2.5 concentrations of 291/5229µgm-3 (AMS-6) and 293/3259µgm-3 (AMS-7) during fire impact periods. High correlations (r2=0.83-0.97) between biomass combustion related gases (carbon monoxide (CO), non-methane hydrocarbons (NMHC), total hydrocarbons (THC), total reduced sulfur (TRS), ammonia) and PM2.5 were observed at the sites. Filter-based 24-hr integrated PM2.5 samples collected every 6 days showed maximum concentrations of 267µgm-3 (AMS-6) and 394µgm-3 (AMS-7). Normalized excess emission ratios relative to CO were 149.87±3.37µgm-3ppm-1 (PM2.5), 0.274±0.002ppmppm-1 (THC), 0.169±0.001ppmppm-1 (NMHC), 0.104±0.001ppmppm-1 (CH4), 0.694±0.007ppbppm-1 (TRS), 0.519±0.040ppbppm-1 (SO2), 0.412±0.045ppbppm-1 (NO), 1.968±0.053ppbppm-1 (NO2), and 2.337±0.077ppbppm-1 (NOX). A subset of PM2.5 filter samples was analyzed for trace elements, major ions, organic carbon, elemental carbon, and carbohydrates. Sample mass reconstruction and fire specific emission profiles are presented and discussed. Potential fire-related photometric ozone instrument positive interferences were observed and were positively correlated with NO and NMHC.

Particulate matter sample deposit geometry and effective filter face velocities.

Aerosol filter face velocities can be underestimated when the sample deposit area does not cover the entire face of the filter. In many aerosol samplers, Teflon filters are backed with a metal support screen. In these samplers, air flows through the filter only in the small area upstream of each hole in the screen, resulting in a sample deposit that is an array of tiny dots that mimics the array of holes. Thus, the filter deposit area is smaller than the total filter area and the effective face velocity is greater than that calculated from the sample deposit envelope. The Interagency Monitoring of Protected Visual Environments (IMPROVE) network has used filter holders with two different screen hole arrays. The U.S. Environmental Protection Agency's Chemical Speciation Network (CSN) and the Federal Reference Method samplers also use a metal support screen, but with much smaller screen holes than IMPROVE. These networks also use larger filters and lower flow rates than those used in IMPROVE. Filter face velocities for all of these networks that are calculated using the actual deposit array area range from 1.6 to 3.5 times larger than those calculated incorrectly using the entire sample deposit envelope.

Generation of hydroxyl radicals from ambient fine particles in a surrogate lung fluid solution.

While it has been hypothesized that the adverse health effects associated with ambient particulate matter (PM) are due to production of hydroxyl radical (*OH), few studies have quantified *OH production from PM. Here we report the amounts of *OH produced from ambient fine particles (PM2.5) collected in northern California and extracted in a cell-free surrogate lung fluid (SLF). On average, the extracted particles produced 470 nmol *OH mg(-1)-PM2.5 during our 15-month collection period. There was a clear seasonal pattern in the efficiency with which particles generated *OH, with highest production during spring and summer and lowest during winter. In addition, nighttime PM was typically more efficient than daytime PM at generating *OH. Transition metals played the dominant role in *OH production: on average (+/-sigma), the addition of desferoxamine (a chelator that prevents metals from forming *OH) to the SLF removed (90 +/- 5) % of *OH generation. Furthermore, based on the concentrations of Fe in the PM2.5 SLF extracts, and the measured yield of *OH as a function of Fe concentration, dissolved iron can account for the majority of *OH produced in most of our PM2.5 extracts.