Metal Aerosols Research Articles

Comprehensive Analysis of Heavy Metal Aerosol Emissions and Health Risk from the Electrical Discharge Machining Process: A Control and Mitigation Approach for Green Manufacturing

Comprehensive Analysis of Heavy Metal Aerosol Emissions and Health Risk from the Electrical Discharge Machining Process: A Control and Mitigation Approach for Green Manufacturing

Breakdown dynamics and instability of underwater metallic aerosol bubble atomized by electrical explosion

This study delves into the electrophysical processes and intricate fluid dynamics of an electrical-explosion-induced bubble in water. A fine copper wire is heated up and exploded to dense metallic aerosol (vapor–drop mixture) via a μs-timescale 10 kA current pulse, crossing a wide range of the density–temperature parametric space. High-speed photography along with discharge diagnostics reveals two modes for plasma development (restrike) inside explosion products: gas discharge and volume ionization. Experimental results indicate the metal–insulator transition of metal can easily throttle down circuit current at a moderate degree of vaporization, resulting in a free-expanding metallic aerosol in the presence of a quasi-direct current axial electric field of kV/cm level. After dozens of μs, an anode-directed, “ionization wave” is observed inside the aerosol bubble, propagating with a speed of 3–10 km/s. Remarkably, adjustments in the electric field permit the observation of cathode-directed discharge development. Increasing the charging voltage or wire diameter promotes the overheating degree, accompanied by partial ionized striation of electro-thermal instability. With sufficient high overheating of the wire (ξ > 1), the gas discharge disappears and restrike is dominated by volume ionization.

Metal Concentrations in E-Cigarette Aerosol Samples: A Comparison by Device Type and Flavor.

The rapid evolution of electronic cigarette (e-cigarette) products warrants surveillance of the differences in exposure across device types-modifiable devices (MODs), cartridge ("pod")-containing devices (PODs), disposable PODs (d-PODs)-and flavors of the products available on the market. This study aimed to measure and compare metal aerosol concentrations by device type and common flavors. We collected aerosol from 104 MODs, 67 PODs (four brands: JUUL, Bo, Suorin, PHIX), and 23 d-PODs (three brands: ZPOD, Bidi, Stig) via droplet deposition in a series of conical pipette tips. Metals and metalloids [aluminum (Al), arsenic (As), cobalt (Co), chromium (Cr), copper (Cu), iron (Fe), manganese (Mn), nickel (Ni), lead (Pb), antimony (Sb), tin (Sn), and zinc (Zn)] were measured using inductively coupled plasma mass spectrometry (ICP-MS), results were log-transformed for statistical analysis, and concentrations are reported in aerosol units (). Of the 12 elements analyzed, concentrations were statistically significantly higher in MOD devices, except for Co and Ni, which were higher in PODs and d-PODs. Of the POD brands analyzed, PHIX had the highest median concentrations among four metals (Al, Ni, Pb, and Sn) compared to the rest of the POD brands. According to POD flavor, seven metals were three to seven orders of magnitude higher in tobacco-flavored aerosol compared to those in mint and mango flavors. Among the d-POD brands, concentrations of four metals (Al, Cu, Ni, and Pb) were higher in the ZPOD brand than in Bidi Stick and Stig devices. According to d-POD flavor, only Cr concentrations were found to be statistically significantly higher in mint than tobacco-flavored d-PODs. We observed wide variability in aerosol metal concentrations within and between the different e-cigarette device types, brands, and flavors. Overall, MOD devices generated aerosols with higher metal concentrations than PODs and d-PODs, and tobacco-flavored aerosols contained the highest metal concentrations. Continued research is needed to evaluate additional factors (i.e., nicotine type) that contribute to metal exposure from new and emerging e-cigarette devices in order to inform policy. https://doi.org/10.1289/EHP11921.

Effect of morphological properties on the particle size distribution measurements and modelling of porous and nonspherical aerosol behaviour

Estimating the time evolution of the suspended aerosol concentration in nuclear reactor containment is critical in assessing the environmental source term during severe accident conditions. Morphological properties of porous and non-spherical aerosol particles are necessary to convert the measured equivalent size distributions to actual size distributions and modelling the aerosol processes. Towards this, the dynamics of liquid PAO (Poly Alpha Olefin) and metal aerosol (non-radioactive fission product equivalent SrO2; and structural steel) are studied individually in a 1 m3 closed chamber. The effect of initial particle size distributions (PSDs) based on different equivalent diameters and the morphological properties on realistic modeling of experimental results is analysed. Electrical Low-Pressure Impactor (ELPI) and Scanning Mobility Particle Sizer (SMPS) are used to measure concentration decay and size growth. The aerosol dynamics model is validated with PAO aerosol data and applied to metal aerosol. Modelled dynamics using both the aerodynamic and effective density (ρe) corrected mobility equivalent PSDs of ELPI (APSD and MEPSD) agree with the measured values within 10% deviation for PAO aerosol, which are spherical with ρe (0.82 g cm−3) slightly differed from 1 g cm−3. Modelled dynamics using APSD significantly deviate around 77.5–137% for the porous and non-spherical/fractal metal aerosols, irrespective of the morphological properties explicitly used to model the aerosol processes with marginal effect. As ρe of SrO2 and steel aerosols (3.16 and 3.34 g cm−3) are >1 g cm−3, aerodynamic distribution underestimates the coagulation phenomenon, the primary aerosol dynamics process to a larger extent. The mobility equivalent size distributions of ELPI model the aerosol dynamics within 6–23% deviation, as supported by SMPS measurements. This study can be extended to ascertain the input parameters required for improved estimations of sodium combustion aerosol dynamics, which has added complexity of hygroscopic growth and time-varying chemical speciation.

Data to Action: Community-Based Participatory Research to Address Concerns about Metal Air Pollution in Overburdened Neighborhoods near Metal Recycling Facilities in Houston.

Exposures to environmental contaminants can be influenced by social determinants of health. As a result, persons living in socially disadvantaged communities may experience disproportionate health risks from environmental exposures. Mixed methods research can be used to understand community-level and individual-level exposures to chemical and nonchemical stressors contributing to environmental health disparities. Furthermore, community-based participatory research (CBPR) approaches can lead to more effective interventions. We applied mixed methods to identify environmental health perceptions and needs among metal recyclers and residents living in disadvantaged neighborhoods near metal recycling facilities in Houston, Texas, in a CBPR study, Metal Air Pollution Partnership Solutions (MAPPS). Informed by what we learned and our previous findings from cancer and noncancer risk assessments of metal air pollution in these neighborhoods, we developed an action plan to lower metal aerosol emissions from metal recycling facilities and enhance community capacity to address environmental health risks. Key informant interviews, focus groups, and community surveys were used to identify environmental health concerns of residents. A diverse group from academia, an environmental justice advocacy group, the community, the metal recycling industry, and the local health department collaborated and translated these findings, along with results from our prior risk assessments, to inform a multifaceted public health action plan. An evidence-based approach was used to develop and implement neighborhood-specific action plans. Plans included a voluntary framework of technical and administrative controls to reduce metal emissions in the metal recycling facilities, direct lines of communication among residents, metal recyclers, and local health department officials, and environmental health leadership training. Using a CBPR approach, health risk assessment findings based on outdoor air monitoring campaigns and community survey results informed a multipronged environmental health action plan to mitigate health risks associated with metal air pollution. https://doi.org/10.1289/EHP11405.

Direct evidence of pyrogenic aerosol iron by intrusions of continental polluted air into the Eastern China Seas

Atmospheric iron (Fe) is an important micronutrient controlling marine primary productivity, which affects marine ecosystems and biogeochemistry. However, few studies have reported the abundance of aerosol Fe and its associated mixing state and solubility in marine environments. Here, aerosol samples were collected over the Bohai Sea and the Yellow Sea near East China during a research cruise. The results show that anthropogenic Fe-containing particles accounted for 9.3% of the total observed marine particles with diameters from 0.1 to 7 μm. Almost all of the Fe-containing particles (94%) were internal mixtures of FeOx particles (i.e., Fe-rich/fly ash) and secondary aerosols (e.g., nitrate, sulfate, and organics). During their aging process, the FeOx particles grew approximately tenfold in size from 100 nm to 1 μm by acquiring a thick secondary aerosol coating after one to two days of transport. The elemental mapping on a per-particle basis showed that the secondary aerosol coating likely homogeneously contained little Fe, suggesting that the acidic coating solubilized Fe via an acid dissolution process in the marine air. Therefore, acid dissolution of metal aerosols in anthropogenic smog should be considered in studies on the biogeochemical cycle between coastal marine air and ocean productivity.

96 Optimization of the Preparation of Cascade Impactors Collection Media for Airborne Metallic Ultrafine Particles Sampling

Abstract For some years, the characterization of workers' exposure to airborne metallic ultrafine particles (UFP) has been an increasing issue. Many industrial processes may generate UFP, which are characterized by constituent particle diameter less than 100 nm, and refer to nanosized particles not intentionally produced (welding, thermal spraying, 3D-printing ...). Thus, determining the size distribution of such an aerosol together with its chemical composition provide a real contribution to the understanding of UFP exposures and associated health effects. In the framework of proposing characterization methods adapted to occupational situations, the optimization of metallic aerosol sampling using cascade impactors is studied in order to improve the reproducibility of these samplings. Cascade impactors represent a valuable help since both the size distribution of an aerosol and its chemical characterization can be obtained from the samples collected. A welding fume bench was used to generate a highly reproducible test aerosol of metallic UFP (mass median aerodynamic diameter MMAD = 430 nm, ρeff = 0.55 g.cm-3). Four different cascade impactors were involved (DLPI+, MARPLE, SIOUTAS and Minimoudi 135-8). Our investigations allowed the lubrificating procedure of the collection supports (membranes, filters) to be optimized by determining the nature and the quantity of grease, which is of significative influence in the collection efficiency. Furthermore, under optimized conditions, the Minimoudi 135-8 (intended for personal sampling) leads to results very close to those stemming from the reference low pressure cascade impactor, DLPI+, thanks to its high resolution in terms of number of stages (8) and lowest cutoff diameter (180 nm).

Machine learning approach to packaging compatibility testing in the new product development process

The paper compares the effectiveness of selected machine learning methods as modelling tools supporting the selection of a packaging type in new product development process. The main goal of the developed model is to reduce the risk of failure in compatibility tests which are preformed to ensure safety, durability, and efficacy of the finished product for the entire period of its shelf life and consumer use. This kind of testing is mandatory inter alia for all aerosol packaging as any mechanical alterations of the packaging can cause the pressurized product to unseal and stop working properly. Moreover, aerosol products are classified as dangerous goods and any leaking of the product or propellent can be a serious hazard to the storage place, environment, and final consumer. Thus, basic compatibility observations of metal aerosol packaging (i.e. general corrosion, pitting corrosion, coating blistering or detinning) and different compatibility factors (e.g. formula ingredients, water contamination, pH, package material and coatings) were discussed. Artificial intelligence methods applied in the design process can reduce the lengthy testing time as well as developing costs and help benefit from the knowledge and experience of technologists stored in historical data in databases.

Creation of Gases with Interplanetary Oxygen Concentration at Atmospheric Pressure by Nanoparticle Aerosol Scavengers: Implications for Metal Processing from nm to mm Range

A gas purification setup (GPS) is presented that is capable of producing ultrapure inert gases, such as nitrogen, at ambient pressure with residual oxygen concentrations of 10–13 ppm and below. The GPS relies on the interaction of metallic aerosol nanoparticles that capture residual oxygen, resulting in metal oxide particle formation. The finally reached residual oxygen level can be illustrated by the 6.8 billion years needed for the creation of one monolayer of oxygen on a substrate. Consequently, the processing of oxygen-affine materials of any size may be shifted from vacuum processes toward machining steps at atmospheric pressure, maintaining an oxygen-free environment in the future. As an outlook, the presented work includes measurements of the electron work function of nanoparticles under purified (10–13 ppm-level) and unpurified process gas (100 ppm-level), pointing at the strong influence of residual oxygen on nanostructured materials with reference to copper nanoparticles. Future syntheses and applications of nanoscaled structures will be inspired by the opportunity to work with true inert gases at ambient pressure, which has been inaccessible so far.

Development of a thermal spray coating aerosol generator and inhalation exposure system

Thermal spray coating involves spraying a product (oftentimes metal) that is melted by extremely high temperatures and then applied under pressure onto a surface. Large amounts of a complex metal aerosol (e.g., Fe, Cr, Ni, Zn) are formed during the process, presenting a potentially serious risk to the operator. Information about the health effects associated with exposure to these aerosols is lacking. Even less is known about the chemical and physical properties of these aerosols. The goal was to develop and test an automated thermal spray coating aerosol generator and inhalation exposure system that would simulate workplace exposures. An electric arc wire-thermal spray coating aerosol generator and exposure system was designed and separated into two areas: (1) an enclosed room where the spray coating occurs; (2) an exposure chamber with different measurement devices and controllers. The physicochemical properties of aerosols generated during electric arc wire-thermal spray coating using five different consumable wires were examined. The metal composition of each was determined by inductively coupled plasma-atomic emission spectroscopy (ICP-AES), including two stainless-steel wires [PMET720 (82 % Fe, 13 % Cr); PMET731(66 % Fe, 26 % Cr)], two Ni-based wires [PMET876 (55 % Ni, 17 % Cr); PMET885 (97 % Ni)], and one Zn-based wire [PMET540 (99 % Zn)]. The particles generated regardless of composition were poorly soluble, complex metal oxides and mostly arranged as chain-like agglomerates and similar in size distribution as determined by micro-orifice uniform deposit impactor (MOUDI) and electrical low-pressure impactor (ELPI). To allow for continuous, sequential spray coating during a 4-hr exposure period, a motor rotated the metal pipe to be coated in a circular and up-and-down direction. In a pilot animal study, male Sprague-Dawley rats were exposed to aerosols (25 mg/m3 × 4 h/d × 9 d) generated from electric arc wire- thermal spray coating using the stainless-steel PMET720 consumable wire. The targeted exposure chamber concentration was achieved and maintained during a 4-hr period. At 1 d after exposure, lung injury and inflammation were significantly elevated in the group exposed to the thermal spray coating aerosol compared to the air control group. The system was designed and constructed for future animal exposure studies to generate continuous metal spray coating aerosols at a targeted concentration for extended periods of time without interruption.

Improving quantitative analysis of spark-induced breakdown spectroscopy: Multivariate calibration of metal particles using machine learning

We have recently developed a low-cost spark-induced breakdown spectroscopy (SIBS) instrument for in-situ analysis of toxic metal aerosol particles that we call TARTA (toxic-metal aerosol real time analyzer). In this work, we applied machine learning methods to improve the quantitative analysis of elemental mass concentrations measured by this instrument. Specifically, we applied least absolute shrinkage and selection operator (LASSO), partial least squares (PLS) regression, principal component regression (PCR), and support vector regression (SVR) to develop multivariate calibration models for 13 metals (e.g., Cr, Cu, Mn, Fe, Zn, Co, Al, K, Be, Hg, Cd, Pb, and Ni), some of which are included on the US EPA hazardous air pollutants (HAPS) list. The calibration performance, adjusted coefficient of determination (R2) and normalized root mean square error (RMSE), and limit of detection (LOD) of the proposed models were compared to those of univariate calibration models for each analyte. Our results suggest that machine learning models tend to have better prediction accuracy and lower LODs than conventional univariate calibration, of which the LASSO approach performs the best with R2 > 0.8 and LODs of 40–170 ng m−3 at a sampling time of 30 min and a flow rate of 15 l min−1. We then assessed the applicability of the LASSO model for quantifying elemental concentrations in mixtures of these metals, serving as independent validation datasets. Ultimately, the LASSO model developed in this work is a very promising machine learning approach for quantifying mass concentration of metals in aerosol particles using TARTA.

Electrical explosion across gas–liquid interface: Aerosol breakdown, shock waves, and cavity dynamics

The electrical explosion of a conductor driven by a pulsed current can be used to simulate the effects of explosions in the laboratory, including the resulting shock waves and bubble dynamics. A fine metallic wire can also be used to initiate pulsed discharge in different media. This study shows images of an exploding wire across an air–water interface for the first time in the literature. The transient process was analyzed using high-speed backlit photography as well as waveforms of the spectrum and discharge. Streamer-like discharge developed from a triple-junction point within the current pause to induce a restrike in metallic aerosol, verifying that gas discharge was prevalent in the system. An upward dense plasma jet accompanied by a crown-like water spike was then observed and led to violent plasma–water interactions (mushroom cloud-like cluster) that were examined through a hydrodynamic simulation. The Stark broadening of the Hα line at 656.28 nm suggested that the electron density of the reaction zone could be 1018 cm−3 or higher. The resolved spatial–temporal images revealed that the plasma evolution process (in μs) was much faster than hydrodynamic processes, including damage to the interface and perturbations of the bubbles (in ms). Water, thus, remained in a “rigid” state during the pulsed discharge, and the explosion of the wire in it was not an adiabatic process at a timescale of 102 μs. Recombination and heat loss through the electrode governed the evolution of the post-discharge plasma, and the microscopic images revealed nano-lamellate nucleation on the surface of the electrode.

Discharge characteristics and spatial-temporal evolution of Cu-Ni alloy wire explosion

Electrical explosion of wires (EEW) driven by pulse current can produce plasmas with high energy density, and is accompanied by electromagnetic pulses, strong shock waves, etc., therefore it is widely adopted in Z-pinch, electrothermal chemical weapons, oil and gas exploitation and other fields. Compared to pure metal, alloy has characteristics of the high resistivity, adjustable composition, and complex phase transitions. It has great potential in regulating parameters of EEW. This paper presents an experimental study on exploding Cu, Ni, and Cu-Ni alloy (constantan) wires in atmospheric air under a microsecond time-scale pulsed current. Through the diagnoses of electrical parameters and self-emission images, the discharge characteristics and spatial-temporal evolution of explosion products were obtained. Features of the alloy wire explosion in phase transition and plasma were acquired as well. Experiments revealed that in the early stage of EEW, the high resistivity of the alloy could improve the energy deposition efficiency, namely 52% for Cu, 74% for Ni, and 78% for Cu-Ni, while after the explosion, performance of the alloy wire was closer to that of the Ni wire. The initial expansion rate of the plasma channel reached 5 mm/μs level but then decayed. The expansion process of alloy wire endured longer, and the average resistivity went up slowly after the breakdown. Also, a correlation was found between plasma radiation and metal aerosol in spatial scale. Especially, the alloy aerosol has crossed striation features (10−1 mm), but it is more uniform than Cu aerosol generally.

Evaluation of metal aerosols in four communities adjacent to metal recyclers in Houston, Texas, USA

ABSTRACT The metal recycling industry provides jobs, generates revenue in local communities and conserves energy and resources. Nonetheless, possible negative impacts of metal recyclers (MRs) include the potential for emissions of metal aerosols and other dusts, noise, traffic and fire during operations. In Houston, Texas, there were more than 180 resident complaints about air quality related to MRs from 2006 to 2011 that were reported to the city’s 311 call system. As a part of a community-based participatory research study, Metal Air Pollution Partnership Solutions (MAPPS), we evaluated the impact of metal emissions from MRs on air quality over two years in four environmental justice communities. We simultaneously collected samples of inhalable particles (aerodynamic particle size less than 10 µm, PM10) using a sampling strategy to capture emissions from the MRs while they were in operation at four locations within each community: an upwind location, the fence line of MR and two downwind locations and analyzed the samples for 10 metals. The highest values of iron (Fe), manganese (Mn), nickel (Ni), lead (Pb), arsenic (As) and chromium (Cr) were detected at the fence lines of MRs. The normalized ratios of these metals at near and far neighborhood locations were 0.01 to 0.64 and 0.01 to 0.34, respectively, as compared with the metals at the fence line. The concentrations of metals rapidly decreased by 57–70% within 100 meters and reached similar levels at upwind (background) locations at approximately 600 meters. After adjusting the measured data for wind direction, rain and operating hours, we calculated non-carcinogenic hazard index values and carcinogenic risks for adult residents from breathing metals emitted from the facilities. Estimated inhalation cancer risks ranged from 0.12 case to 24 cases in 1 million people and the hazard index values ranged from 0.04 to 11. Implications: In Houston, Texas, residents complained about air quality related to metal recyclers from 2006 to 2011. Using a community-based participatory research method, metal emissions were characterized at four environmental justice communities. The results indicate that metal concentrations were the highest at the fence line and decreased by 57–70% within 100 meters and reached similar levels of background at 600 meters. After adjusting the measured data for meteorological parameters and operating hours, estimated inhalation cancer risks ranged from 0.12 cases to 24 cases in 1 million people and hazard index values ranged from 0.04 to 11.

Metal air pollution partnership solutions: building an academic-government-community-industry collaboration to improve air quality and health in environmental justice communities in Houston

BackgroundFrom 2006 to 2011, the City of Houston received nearly 200 community complaints about air pollution coming from some metal recycling facilities. The investigation by the Houston Health Department (HHD) found that while operating within legal limits, emissions from facilities that use torch cutting, a technique generating metal aerosols, may increase health risks for neighboring residents. Choosing to use collaborative problem solving over legislative rulemaking, HHD reached out to The University of Texas Health Science Center at Houston (UTHealth) to further evaluate and develop plans to mitigate, if necessary, health risks associated with metal emissions from these facilities.MethodsUtilizing a community-based participatory research approach, we constituted a research team from academia, HHD and an air quality advocacy group and a Community Advisory Board (CAB) to draw diverse stakeholders (i.e., frustrated and concerned residents and wary facility managers acting within their legal rights) into an equitable, trusting and respectful space to work together. Next, we investigated metal air pollution and inhalation health risks of adults living near metal recyclers and ascertained community views about environmental health using key informant interviews, focus groups and surveys. Finally, working collaboratively with the CAB, we developed neighborhood-specific public health action plans to address research findings.ResultsAfter overcoming challenges, the CAB evolved into an effective partnership with greater trust, goodwill, representation and power among members. Working together to translate and share health risk assessment results increased accessibility of the information. These results, coupled to community survey findings, set the groundwork for developing and implementing a stakeholder-informed action plan, which included a voluntary framework to reduce metal emissions in the scrap yard, improved lines of communication and environmental health leadership training. Tangible outcomes of enhanced capacity of our community and governmental partners included trained residents to conduct door-to-door surveys, adaptation of our field training protocol and survey by our community partner and development of a successful HHD program to engage residents to improve environmental health in their neighborhood.ConclusionsAcademic-government-community-industry partnerships can reduce environmental health disparities in underserved neighborhoods near industrial facilities.

Prevalence and predictors of iron-deficiency anemia: Women's health perspective at reproductive age in the suburb of dried Urmia Lake, Northwest of Iran.

BACKGROUND:Dried Urmia Lake in the northwest of Iran is a major regional source of sodium and toxic metal aerosols which may cause numerous health problems. The aim of this study was to evaluate iron-deficiency anemia (IDA) and some related risk factors among women of reproductive age in the suburb of dried Urmia Lake to provide the information about the problem to the health-care providers.METHODS:This cross-sectional study was conducted on 278 healthy nonpregnant, nonlactating women aged 18–45 years, living in the rural area of the Salmas city, closest to the Urmia Lake between February and June 2017. The study participants were selected using a stratified random sampling method with proportional allocation from seven villages. A general questionnaire was completed for each participant to collect sociodemographic information and a 3-day dietary recall questionnaire to obtain daily dietary intakes. IDA was defined as a hemoglobin (Hb) level of <12 g/dl and ferritin concentration of <15 μg/l. Spearman's correlation coefficient and Fisher's exact test were applied to determine sociodemographic factors associated with the serum Hb and ferritin levels.RESULTS:The prevalence of overall anemia (Hb <12 g/dl) was 7.9%. IDA was determined in 4.3% and iron deficiency (ID) in 19.1% (serum ferritin <15 μg/l) of the participants. There was a significant positive correlation between serum Hb concentrations and the mean daily intakes of protein and iron (P < 0.001). Similarly, a significant positive correlation was observed between serum ferritin levels and body mass index (P < 0.001). Significant inverse associations were found between Hb concentrations and the number of pregnancies and children (P < 0.001), as well as the number of family members (P < 0.05).CONCLUSIONS:Results indicated a mild prevalence of IDA and a relatively high rate of ID among studied participants. Educational programs are needed to improve nutritional habits as well as the use of contraceptives to promote women's health.

Classification of iron oxide aerosols by a single particle soot photometer using supervised machine learning

Abstract. Single particle soot photometers (SP2) use laser-induced incandescence to detect aerosols on a single particle basis. SP2s that have been modified to provide greater spectral contrast between their narrow and broad-band incandescent detectors have previously been used to characterize both refractory black carbon (rBC) and light-absorbing metallic aerosols, including iron oxides (FeOx). However, single particles cannot be unambiguously identified from their incandescent peak height (a function of particle mass) and color ratio (a measure of blackbody temperature) alone. Machine learning offers a promising approach for improving the classification of these aerosols. Here we explore the advantages and limitations of classifying single particle signals obtained with a modified SP2 using a supervised machine learning algorithm. Laboratory samples of different aerosols that incandesce in the SP2 (fullerene soot, mineral dust, volcanic ash, coal fly ash, Fe2O3, and Fe3O4) were used to train a random forest algorithm. The trained algorithm was then applied to test data sets of laboratory samples and atmospheric aerosols. This method provides a systematic approach for classifying incandescent aerosols by providing a score, or conditional probability, that a particle is likely to belong to a particular aerosol class (rBC, FeOx, etc.) given its observed single particle features. We consider two alternative approaches for identifying aerosols in mixed populations based on their single particle SP2 response: one with specific class labels for each species sampled, and one with three broader classes (rBC, anthropogenic FeOx, and dust-like) for particles with similar SP2 responses. Predictions of the most likely particle class (the one with the highest mean probability) based on applying the trained random forest algorithm to the single particle features for test data sets comprising examples of each class are compared with the true class for those particles to estimate generalization performance. While the specific class approach performed well for rBC and Fe3O4 (≥99 % of these aerosols are correctly identified), its classification of other aerosol types is significantly worse (only 47 %–66 % of other particles are correctly identified). Using the broader class approach, we find a classification accuracy of 99 % for FeOx samples measured in the laboratory. The method allows for classification of FeOx as anthropogenic or dust-like for aerosols with effective spherical diameters from 170 to &gt;1200 nm. The misidentification of both dust-like aerosols and rBC as anthropogenic FeOx is small, with &lt;3 % of the dust-like aerosols and &lt;0.1 % of rBC misidentified as FeOx for the broader class case. When applying this method to atmospheric observations taken in Boulder, CO, a clear mode consistent with FeOx was observed, distinct from dust-like aerosols.

Entrained Metal Aerosol Emissions from Air-Fired Biomass and Coal Combustion for Carbon Capture Applications.

Biomass energy with CO2 capture could achieve net negative emissions, vital for meeting carbon budgets and emission targets. However, biomass often has significant quantities of light metals/inorganics that cause issues for boiler operation and downstream processes; including deposition, corrosion, and solvent degradation. This study investigated the pilot-scale combustion of a typical biomass used for power generation (white wood) and assessed the variations in metal aerosol release compared to bituminous coal. Using inductively coupled plasma optical emission spectrometry, it was found that K aerosol levels were significantly greater for biomass than coal, on average 6.5 times, with peaks up to 10 times higher; deposition could thus be more problematic, although Na emissions were only 20% of those for coal. Transition metals were notably less prevalent in the biomass flue gas; with Fe and V release in particular much lower (3–4% of those for coal). Solvent degradation may therefore be less severe for biomass-generated flue gases. Furthermore, aerosol emissions of toxic/heavy metals (As/Cd/Hg) were absent from biomass combustion, with As/Cd also not detected in the coal flue gas. Negligible Cr aerosol concentrations were found for both. Overall, except for K, metal aerosol release from biomass combustion was considerably reduced compared to coal.

Sources Analysis of Heavy Metal Aerosol Particles in North Suburb of Nanjing

Heavy metal aerosol particles were first measured with Single Particle Aerosol Mass Spectrometry (SPAMS) in north suburb of Nanjing from January to December, 2013. Using the ART-2a neural network algorithm, we studied the chemical characteristics of aerosol particles and found that the main sources of heavy metal aerosols in Nanjing were industrial emissions, biomass burning, traffic emissions, fuel combustion and dust, accounting for 35.7%, 34.45%, 13.6%, 11.03% and 4.07% respectively. Pb, Cd and Cr-containing aerosols mainly came from industrial emissions. Cu, Co and Hg-containing aerosols mainly came from biomass burning. V, Zn and Ba-containing aerosols mainly came from traffic emissions. As and Ni-containing aerosols mainly came from fuel combustion.

Quantification of Airborne Biological Contaminants Associated with Land-Applied Biosolids

Greater than 50% of all class B biosolids produced in the US are reused by application to agricultural land. The goal of this research was to pair a comprehensive literature review with a field aerosol sampling campaign to characterize aerosols emitted during the land application process and provide a simplified framework for evaluating exposure to on-site workers and off-site residents. Three aerosolization scenarios for dewatered biosolids were considered and include spreading biosolids onto land by side slinging, disk incorporating into soils, and aerosolization of land applied biosolids due to high wind events. Particulate mater, metal aerosols, and biological aerosols of biosolids origin were in the respirable size range and were markedly greater downwind of land application than in upwind ambient control sites. Low level aerosolization of field applied biosolids were detected during high wind events, and biosolids derived aerosols were detected at 170 meters downwind of disk incorporation. The ability to reconstruct source aerosol concentration from PM10 measurements and the linear correlations made between bulk biosolids concentrations and source emission rates serve as a framework for determining relevant aerosol concentrations without the requirement of biological or chemical aerosol sampling. Application of this framework eliminates the inherent limitations and costs associated with monitoring low aerosol concentration of toxic compounds and pathogens. This title belongs to WERF Research Report Series ISBN: 9781843397700 (eBook)