Real-time measurements of mineral dust concentration in coarse particulate matter (PM10-2.5) by employing a novel optical-based technique in Los Angeles

Size-segregated source identification of water-soluble and water-insoluble metals and trace elements of coarse and fine PM in central Los Angeles

In this study, the water-solubility and sources of metals and trace elements in both fine and coarse particulate matter (PM) were investigated in Central Los Angeles. Sampling was performed in the winter, spring, and summer of 2022 at the Particle Instrumentation Unit (PIU) of the University of Southern California located in the proximity of I-110 freeway. Both fine and coarse PM samples were collected using Personal Cascade Impactors (PCIS) and chemically analyzed to determine their water-soluble and water-insoluble metal content. Principal Component Analysis (PCA) and Multiple Linear Regression (MLR) were used to determine the sources of soluble and insoluble metals and obtain their contributions to total metal concentration. Our results indicate that the water-solubility of most of the metals is higher in the fine size fraction compared to the coarse fraction. Seasonal variations in the water solubility of selected metals for both coarse and fine fractions were observed, with higher water-soluble metal concentrations in summer for several species (e.g., Fe , S, Pb, Cu, La, Ni, and Al ), possibly due to higher photochemical processing, while in winter, almost all species exhibited higher insoluble fraction concentrations. The PCA and MLR analyses results showed that tire and brake wear was the most significant contributor to the total metals for both fine soluble and insoluble portions, accounting for 35% and 75% of the total metals, respectively. Combustion sources also contributed substantially to water-soluble metals for fine and coarse size ranges, representing 40% and 32% of the total metal mass, respectively. In addition, mineral dust and soil and re-suspended dust were identified as the highest contributors to coarse metals. The MLR analysis also revealed that secondary aerosols contributed 11% to the fine water-soluble metals. Our results suggest that non-tailpipe emissions significantly contribute to both coarse and fine PM metals in the Central Los Angeles region.

Design, optimization, and evaluation of a wet electrostatic precipitator (ESP) for aerosol collection

In this study, we developed, optimized, and evaluated in lab and field experiments a wet electrostatic precipitator (ESP) for the collection of ambient PM2.5 (particulate matter with aerodynamic diameter < 2.5 μm) into ultrapure water by applying an electrostatic charge to the particles. We operated the wet ESP at different flow rates and voltages to identify the optimal operating conditions. According to our experimental measurements, a flow rate of 125 lpm and an applied positive voltage of 11 kV resulted in a lower ozone generation of 133 ppb and a particle collection efficiency exceeding 80-90% in all size ranges. For the field tests, the wet ESP was compared with the versatile aerosol concentration enrichment system (VACES) connected to a BioSampler, a PTFE filter sampler, and an OC/EC analyzer (Sunset Laboratory Inc., USA) as a reference. The chemical analysis results indicated the wet ESP concentrations of metal and trace elements were in very good agreement with those measured by the VACES/BioSampler and PTFE filter sampler. Moreover, our results showed comparable total organic carbon (TOC) concentrations measured by the wet ESP, BioSampler, and OC/EC analyzer, while somewhat lower TOC concentrations were measured by the PTFE filter sampler, possibly due to the limitations of extracting water-insoluble organic carbon (WIOC) from a dry substrate in the latter sampler. The comparable TOC content in the wet ESP and BioSampler samples differs from previous findings that showed higher TOC content in BioSampler samples compared to those collected by dry ESP. The results of the Dithiothreitol (DTT) assay showed comparable DTT activity in the VACES/BioSampler and wet ESP PM samples while slightly lower in the PTFE filter samples. Overall, our results suggest that the wet ESP could be a promising alternative to other conventional sampling methods.

Wintertime aerosol properties of urban desert region of western India: Implications in regional climate assessment

This study assessed the inter-relation between physiochemical and optical characteristics of aerosols measured at a desert-urban region affected by anthropogenic sources and desert dust during October 2020 to January 2021. Based on horizontal visibility and measured PM_2.5 concentration, clear (37 %), light (33 %) and high (31 %) pollution periods were identified. Elemental and organic carbon (50 ± 15 μgm^-3_; 31 %) and secondary inorganics (53 ± 21 μgm^-3; 33 %) dominated the PM_2.5 mass (160 ± 4 μgm^-3) during high pollution period with low dust (14 ± 7 μgm^-3; 8 %) content. Interestingly, the clear pollution period was also influenced by carbonaceous fraction (19 ± 8 μgm^-3; 32 %) and secondary inorganics (19 ± 5 μgm^-3; 32 %), but the PM_2.5 concentrations (59 ± 9 μgm^-3) were ∼ one-third as compared to high pollution period. High scattering coefficients were observed which were comparable to highly polluted Indian city like Delhi. An exponential increase in non-absorbing material was observed and showed clear influence on light absorption capacity of EC and dust due to coating/mixing. High absorption Ångström exponent (AAE) >0.6 was observed for the ratio of non-absorbing to light absorbing components (LAC) in the range of 1-2.5 and EC/PM_2.5 fraction of 7-14 %. While further increase in non-absorbing to absorbing components ratio > 4 and low amount of EC (<4 %) tend to decrease AAE below 0.4. Higher mass absorption cross-section (>30 m²g^-1 of EC) was observed when 4-10 % EC fraction of PM_2.5 associated with 1.5-3.5 times non-absorbing components to total absorbing components. Likewise, absorption enhanced by three to five folds compared to uncoated EC for low EC fraction (3-6 %) in PM_2.5, but high non-absorbing to absorbing component ratio (>2.5). Interestingly, absorption was minimally amplified for nominal coating fraction associated with significant core materials or vice-versa. These findings have implications not only in regional climate assessment but also for other regions with comparable geography and source-mixes.

Investigation of organic carbon profiles and sources of coarse PM in Los Angeles

Source apportionment analyses are essential tools to determine sources of ambient coarse particles (2.5 <d_p < 10 μm) and to disentangle their association and contribution from other pollutants, particularly PM_2.5 (<2.5 μm). A semi-continuous sampling campaign was conducted using two virtual impactors/concentrators to enhance coarse particulate matter concentrations coupled with an online thermal-optical EC/OC monitor to quantify coarse PM-bound organic carbon volatility fractions (OC₁-OC₄) in central Los Angeles during the winter, spring, and summer of 2021. The total OC and its volatility fraction concentrations, meteorological parameters (i.e., wind speeds and relative humidity), vehicle miles traveled (VMT), and gaseous source tracers (i.e., O₃ and NO₂) were used as inputs to positive matrix factorization (PMF) model. A 3-factor solution identified vehicular emissions (accounting for 46% in the cold phase and 26% in the warm phase of total coarse OC concentrations), secondary organic carbon (27% and 37%), and re-suspended dust (27% and 37%) as the primary organic carbon sources of coarse PM. The re-suspended dust factor showed a higher contribution of more volatile organic carbons (i.e., OC₁ up to 77%) due to their re-distribution on dust particles, whereas the SOA factor was the dominant contributor to less volatile organic aerosols (i.e., OC₄ up to 54%), which are the product of reactions at high relative humidity (RH). Our findings revealed that the total OC concentrations in the coarse size range were comparable with those of previous studies in the area, underscoring the challenges in curtailing coarse PM-bound OC sources and the necessity of developing effective emission control regulations on coarse PM. The results from the current study provide insights into the seasonal and temporal variation of total OC and its volatility fractions in Los Angeles.

Estimation of dust concentration by a novel machine vision system

The dust phenomenon is one of the main environmental problems that it reversely affects human health and economical and social activities. In the present research, a novel algorithm has been developed based on image processing to estimate dust concentration. An experimental setup was implemented to create airborne dust with different concentration values from 0 to 2750 µg.m⁻³. The images of the different dust concentration values were acquired and analyzed by image processing technique. Different color and texture features were extracted from various color spaces. The extracted features were used to develop single and multivariable models by regression method. Totally 285 single variable models were obtained and compared to select efficient features among them. The best single variable model had a predictive accuracy of 91%. The features were used for multivariable modeling and the best model was selected with a predictive accuracy of 100% and a mean squared error of 1.44 × 10⁻²³. The results showed the high ability of the developed machine vision system for estimating dust concentration with high speed and accuracy.