Number Concentration Research Articles

Relationship between Exhaled Aerosol and Carbon Dioxide Emission Across Respiratory Activities.

Respiratory particles produced during vocalized and nonvocalized activities such as breathing, speaking, and singing serve as a major route for respiratory pathogen transmission. This work reports concomitant measurements of exhaled carbon dioxide volume (VCO2) and minute ventilation (VE), along with exhaled respiratory particles during breathing, exercising, speaking, and singing. Exhaled CO2 and VE measured across healthy adult participants follow a similar trend to particle number concentration during the nonvocalized exercise activities (breathing at rest, vigorous exercise, and very vigorous exercise). Exhaled CO2 is strongly correlated with mean particle number (r = 0.81) and mass (r = 0.84) emission rates for the nonvocalized exercise activities. However, exhaled CO2 is poorly correlated with mean particle number (r = 0.34) and mass (r = 0.12) emission rates during activities requiring vocalization. These results demonstrate that in most real-world environments vocalization loudness is the main factor controlling respiratory particle emission and exhaled CO2 is a poor surrogate measure for estimating particle emission during vocalization. Although measurements of indoor CO2 concentrations provide valuable information about room ventilation, such measurements are poor indicators of respiratory particle concentrations and may significantly underestimate respiratory particle concentrations and disease transmission risk.

Aerosol mixing state, new particle formation, and cloud droplet number concentration in an urban environment

Anthropogenically derived aerosols have been hypothesized to influence convective precipitation by increasing the available pool of cloud condensation nuclei. Here, we present a synthesis of aerosol size distribution and subsaturated hygroscopicity measurements between 15 and 250 nm diameter particles during the TRacking Aerosol Convection interactions ExpeRiment (TRACER). We found that the aerosol is externally mixed and can be described by a quasi-two-component description comprising a more and less hygroscopic mode. The mean hygroscopicity parameters for these modes across all sizes were 0.03 ± 0.04 and 0.22 ± 0.08 with no significant dependence on particle size. The number fraction of the more hygroscopic mode is 40 % for particles between 15 and 40 nm and gradually increases to ~70 % for particles >100 nm. Winds from the southerly direction feature particles with larger hygroscopicity parameters and have a larger fraction of particles in the more hygroscopic mode. The hygroscopicity parameter exhibits diurnal cycles that are consistent with condensation of a species with a hygroscopicity parameter ~0.1 which corresponds to values expected for secondary organic aerosol. We also identified nine small particle events that were attributed to particle formation by nucleation. The data are consistent with new particle formation having occurred aloft, followed by downward mixing with daytime turbulence. The species that are responsible for modal growth had hygroscopicity parameters varying between 0.05 and 0.34. These values systematically depended on the wind sector, suggesting that the chemical composition of the precursors differed. Hourly cloud condensation nuclei (CCN) and cloud droplet number concentration (CDNC) values derived from the aerosol size distribution, subsaturated hygroscopicity measurements, and adiabatic parcel model simulations showed a dynamic range of a factor of 2–3 in CDNC depending on the wind sector, with lower values associated with southerly onshore flow.

Study of oblique granular impingement flow through CFD-DEM simulations and energy consumption statistics

This paper investigates an experimental granular impingement flow system through simulations and energy consumption statistics. With the increase of solid concentration, flow patterns undergo cross flow (dense edge and dilute center), dispersed flow, and mixed-jet flow (dilute edge and dense center) in turn. The influence of gas phase on the flow pattern was investigated. According to the analysis of force and time-averaged velocity, it is revealed that gas-solid interaction will cause energy dissipation of granular flow, which cannot be ignored in specific cases. Then, a flow map is proposed according to both the Archimedes number and solid concentration. In addition, the flow pattern transition and local structure variations can be reflected by energy consumption statistics. Based on the simulations and methods developed in this work, it is promising to deepen the understanding and study of granular impingement flow from the viewpoints of energy consumption and new-type flow map.

Influence of soot aerosol properties on the counting efficiency of instruments used for the periodic technical inspection of diesel vehicles

Abstract. In this work, we investigated the influence of different types of soot aerosol on the counting efficiency (CE) of instruments employed for the periodic technical inspection (PTI) of diesel vehicles. Such instruments report particle number (PN) concentration. Combustion aerosols were generated by a prototype bigCAST, a miniCAST 5201 BC, a miniCAST 6204 C, and a miniature inverted soot generator (MISG). For comparison purposes, diesel soot was generated by a Euro 5b diesel test vehicle with by-passed diesel particulate filter (DPF). The size-dependent counting efficiency profile of six PN–PTI instruments was determined with each one of the aforementioned test aerosols. The results showed that the type of soot aerosol affected the response of the PN–PTI sensors in an individualised manner. Consequently, it was difficult to identify trends and draw conclusive results about which laboratory-generated soot is the best proxy for diesel soot. Deviations in the counting efficiency remained typically within 0.25 units when using laboratory-generated soot compared to Euro 5b diesel soot of similar mobility diameter (∼ 50–60 nm). Soot with a mobility diameter of ∼ 100 nm generated by the MISG, the lowest size we could achieve, resulted in most cases in similar counting efficiencies as those generated by the different CAST generators at the same particle size, showing that MISG may be a satisfactory – and affordable – option for PN–PTI verification; however, further optimisation will be needed for low-cost soot generators to comply with European PN–PTI verification requirements.

Airborne particulate matter and diesel engine exhaust on infrastructure construction sites in the Copenhagen metropolitan area.

Diesel engine exhaust (DEE) is carcinogenic and potentially hazardous for those working in close proximity to diesel-powered machines. This study characterizes workplace exposure to DEE and its associated particulate matter (PM) during outdoor construction activities. We sampled at 4 construction sites in the Copenhagen metropolitan area. We used portable constant-flow pumps and quartz-fiber filters to quantify personal exposure to elemental carbon (EC), and used real-time instruments to collect activity-based information about particle number and size distribution, as well as black carbon (BC) concentration. Full-shift measurements of EC concentration ranged from < 0.3 to 6.4 µg/m3. Geometric mean (GM) EC exposure was highest for ground workers (3.4 µg/m3 EC; geometric standard deviation, GSD = 1.3), followed by drilling rig operators (2.6 µg/m3 EC; GSD = 1.4). Exposure for non-drilling-rig machine operators (1.2 µg/m3 EC; GSD = 2.9) did not differ significantly from background (0.9 µg/m3 EC; GSD = 1.7). The maximum 15-min moving average concentration of BC was 17 µg/m3, and the highest recorded peak concentration was 44 µg/m3. In numbers, the particle size distributions were dominated by ultrafine particles ascribed to DEE and occasional welding activities at the sites. The average total particle number concentrations (PNCs) measured in near-field and far-field positions across all worksites were 10,600 (GSD = 3.0) and 6,000 (GSD = 2.8)/cm3, respectively. Sites with active drilling rigs saw significantly higher average total PNCs at their near-field stations (13,600, 32,000, and 9,700/cm3; GSD = 2.4, 3.4, and 2.4) than sites without (4,700/cm3; GSD = 1.6). Overall, the DEE exposures at these outdoor construction sites were below current occupational exposure limits for EC (10 µg/m3 in Denmark; 50 µg/m3 in the European Union), but extended durations of exposure to the observed DEE levels may still be a health risk.

In-situ aircraft observations of aerosol and cloud microphysical characteristics of mixed-phase clouds over the North China Plain

Aerosol-cloud interactions play a vital role in climate change. This study leverages observations from the King-350 aircraft over the North China Plain on November 29, 2019, to examine aerosol and cloud microphysical characteristics of mixed-phase clouds. Through detailed vertical and spectral distributions, we investigate aerosol, cloud droplet, and ice crystal distributions in seeded clouds (SC) and natural precipitating clouds (NPC) within the same cloud system. From the vertical profile, SC and NPC have similar vertical distributions of aerosol and cloud droplets, with over 95 % of aerosols concentrated below 1600 m near the ground. Cloud droplets are more evenly distributed within the two clouds, cloud droplet number concentrations (Nc) in SC were three orders of magnitude higher than in NPC. Ice water content (IWC) and ice crystal number concentration (Ni) show distinct layer preferences—accumulating predominantly in SC's top layer and NPC's middle layer. From spectral distribution, a smaller proportion of cloud droplets (40–50 μm in diameter, the same hereafter) in SC compared to NPC. Rimed ice crystals and globular graupel (1325–1550 μm in diameter) were in SC, while plate and irregular ice crystals (300–450 μm) were in NPC with an order of magnitude higher than in SC. These microphysical differences highlight the complexity of cloud seeding efficacy, which varies based on cloud conditions and microphysical properties. In the first seeding, Ni increased by 1–2 orders of magnitude (125–300 μm) in the high Nc (Nc > 1.11 × 105 L−1) region. Seeding in low Nc (Nc < 1.11 × 105 L−1) regions was hard to be effective, especially in low Nc and low liquid water content (LWC) (LWC < 0.122 g/m3) regions. In the second seeding, ice crystals (125–250 μm) produced by the first seeding enhance the seeding efficiency. The responded regions were more sensitive to subsequent seeding, resulting in stronger reactions or longer duration.

Assessing the abundance, sources, and potential ecological risk assessment of microplastics using their particle and mass units in Uiam Lake, South Korea

Microplastics (MPs) enter lakes through various pathways, including effluents from wastewater treatment plants (WWTPs), surface runoff, and improperly disposed of plastic waste. In this study, the extent of MPs pollution in Uiam Lake in fall of 2022 and spring of 2023 was assessed by determining both the number (n/m3) and mass concentrations (μg/m3) of MPs. Moreover, the correlation between water quality parameters and MP properties was analyzed, and an ecological risk assessment was conducted. MPs abundance was higher in spring than in fall, probably due to the lifting of coronavirus disease-19 restrictions, melting of ice, higher rainfall, and faster wind speed. Fragment was the dominant shape of the MPs collected, while polyvinyl chloride (PVC) and polyester/polyethylene terephthalate were the frequently detected polymer types of MPs in fall and spring, respectively. There was a moderate positive correlation between the number concentration of MPs and the total nitrogen, total phosphorus (T-P), and total organic carbon levels; in contrast, there was no significant relationship between the mass concentration of MPs and all water quality parameters. However, the abundance (μg/m3) of PVC and polymethyl methacrylate MPs were positively correlated with T-P and electrical conductivity. The pollution load index, polymer hazard index, and potential ecological risk index (PERI) were generally higher when the mass unit of MPs was used due to the presence of large-sized MPs composed of highly hazardous polymers (e.g., polyurethane, PVC, and alkyd). For instance, the PERI value of the WWTP effluent was at the very high level (>1200) in both seasons, regardless of the abundance unit of MPs. Therefore, WWTP effluents may have increased the ecological toxicity of MPs pollution in Uiam Lake.

Using Machine Learning to Predict Cloud Turbulent Entrainment‐Mixing Processes

AbstractDifferent turbulent entrainment‐mixing mechanisms between clouds and environment are essential to cloud‐related processes; however, accurate representation of entrainment‐mixing in weather/climate models still poses a challenge. This study exploits the use of machine learning (ML) to address this challenge. Four ML (Light Gradient Boosting Machine [LGB], eXtreme Gradient Boosting, Random Forest, and Support Vector Regression) are examined and compared. It is found that LGB performs best, and thus is selected to understand the impact of entrainment‐mixing on microphysics using simulation data from Explicit Mixing Parcel Model. Compared with traditional parameterizations, the trained LGB provides more accurate microphysical properties (number concentration and cloud droplet spectral dispersion). The partial dependences of predicted microphysics on features exhibit a strong alignment with physical mechanisms and expectations, as determined by the interpreting method, thus overcoming the limitations of the “black box” scheme. The underlying mechanisms are that the smaller number concentration and larger spectral dispersion correspond to more inhomogeneous entrainment‐mixing. Specifically, number concentration after entrainment‐mixing is positively correlated with adiabatic number concentration and liquid water content affected by entrainment‐mixing, and inversely correlated with adiabatic volume mean radius. Spectral dispersion after entrainment‐mixing is negatively correlated with liquid water content affected by entrainment‐mixing, turbulent dissipation rate and relative humidity of entrained air. Sensitivity analysis further suggests that number concentration is mainly determined by cloud microphysical properties whereas spectral dispersion is influenced by both cloud microphysical properties and environmental variables. The results indicate that the LGB scheme has the potential to enhance the representation of entrainment‐mixing in weather/climate models.

Effect of Vocalization on Human Aerosol Dynamics: Whispering Produces More Aerosols than Speaking

ObjectivesSound pressure and exhaled flow have been identified as important factors associated with higher particle emissions. The aim of this study was to assess how different vocalizations affect the particle generation independently from other factors. DesignExperimental study MethodsThirty-three experienced singers repeated two different sentences in normal loudness and whispering. The first sentence consisted mainly of consonants like /k/ and /t/ as well as open vowels, while the second sentence also included the /s/ sound and contained primarily closed vowels. The particle emission was measured using condensation particle counter (CPC, 3775 TSI Inc.) and aerodynamic particle sizer (APS, 3321 TSI Inc.). The CPC measured particle number concentration for particles larger than 4 nm and mainly reflects the number of particles smaller than 0.5 µm since these particles dominate total number concentration. The APS measured particle size distribution and number concentration in the size range of 0.5 – 10 µm and data were divided into > 1 µm and < 1 µm particle size ranges. Generalized linear mixed effects models were constructed to assess the factors affecting particle generation. ResultsWhispering produced more particles than speaking and sentence 1 produced more particles than sentence 2 while speaking. Sound pressure level had effect on particle production independently from vocalization. The effect of exhaled airflow was not statistically significant. ConclusionsBased on our results the type of vocalization has a significant effect on particle production independently from other factors such as sound pressure level.

Predicting within-city spatiotemporal variations in daily median outdoor ultrafine particle number concentrations and size in Montreal and Toronto, Canada.

Epidemiological evidence suggests that long-term exposure to outdoor ultrafine particles (UFPs, <0.1 μm) may have important human health impacts. However, less is known about the acute health impacts of these pollutants as few models are available to estimate daily within-city spatiotemporal variations in outdoor UFPs. Several machine learning approaches (i.e., generalized additive models, random forest models, and extreme gradient boosting) were used to predict daily spatiotemporal variations in outdoor UFPs (number concentration and size) across Montreal and Toronto, Canada using a large database of mobile monitoring measurements. Separate models were developed for each city and all models were evaluated using a 10-fold cross-validation procedure. In total, our models were based on measurements from 12,705 road segments in Montreal and 10,929 road segments in Toronto. Daily median outdoor UFP number concentrations varied substantially across both cities with 1st-99th percentiles ranging from 1389 to 181,672 in Montreal and 2472 to 118,544 in Toronto. Outdoor UFP size tended to be smaller in Montreal (mean [SD]: 34 nm [15]) than in Toronto (mean [SD]: 44 nm [25]). Extreme gradient boosting models performed best and explained the majority of spatiotemporal variations in outdoor UFP number concentrations (Montreal, R 2: 0.727; Toronto, R 2: 0.723) and UFP size (Montreal, R 2: 0.823; Toronto, R 2: 0.898) with slopes close to one and intercepts close to zero for relationships between measured and predicted values. These new models will be applied in future epidemiological studies examining the acute health impacts of outdoor UFPs in Canada's two largest cities.

IMO2020 Regulations Accelerate Global Warming by up to 3 Years in UKESM1

AbstractThe International Maritime Organization (IMO) introduced new regulations on the sulfur content of shipping emissions in 2020 (IMO2020). Estimates of the climatic impact of this global reduction in anthropogenic sulfate aerosols vary widely. Here, we contribute to narrowing this uncertainty with two sets of climate model simulations using UKESM1. Using fixed sea‐surface temperature atmosphere‐only simulations, we estimate an IMO2020 global effective radiative forcing of 0.139 ± 0.019 Wm−2 and show that most of this forcing is due to aerosol‐induced changes to cloud properties. Using coupled ocean‐atmosphere simulations, we note significant changes in cloud top droplet number concentration and size across regions with high shipping traffic density, and—in the North Atlantic and North Pacific—these microphysical changes translate to a decrease in cloud albedo. We show that IMO2020 increases global annual surface temperature on average by 0.046 ± 0.010°C across 2020–2029; approximately 2–3 years of global warming. Furthermore, our model simulations show that IMO2020 helps to explain the exceptional warming in 2023, but other factors are needed to fully account for it. The year 2023 also had an exceptionally large decrease in reflected shortwave radiation at the top‐of‐atmosphere. Our results show that IMO2020 made that more likely, yet the observations are within the variability of simulations without the reduction in shipping emissions. To better understand the climatic impacts of IMO2020, a model intercomparison project would be valuable whilst the community waits for a more complete observational record.

Particle dispersion in atmospheric modelling: A comprehensive review

Atmospheric dispersion modeling, traditionally inclined towards gaseous dispersion, has undergone significant evolution in capturing the intricacies of particle dispersion in urban and open environments. This comprehensive review explores the nuances of particle-gas interactions, highlighting discrepancies in correlations between their concentrations, influenced by factors such as turbulence and multiple emission sources. The research accentuates the intriguing dynamics between PM2.5 and PM10 concentrations, suggesting the viability of models based on passive scalars for such particles in open environments. However, a marked challenge emerges in modeling particle number concentration, necessitating the integration of aerosol dynamics modules. Emphasizing the diversity of model types, this paper elucidates the specific requirements across varying spatial scales, identifying gaps in understanding particle dispersion and aerosol dynamics. The review critically assesses the performance of notable models, highlighting the paramount importance of quality data sources and underscoring the need for more dedicated focus on particle dynamics beyond mass predictions. Through a synthesis of existing literature and model evaluations, this review seeks to guide future research endeavors, fostering advancements in atmospheric dispersion modeling.

Impact of sea ice on the physicochemical characteristics of marine aerosols in the Arctic Ocean

Marine aerosols (MA) can be influenced by sea ice concentration, potentially playing a pivotal role in the formation of cloud condensation nuclei and exerting an impact on regional climate. In this study, a high-resolution aerosol observation system was employed to measure the concentration and size of aerosols in the floating ice region and seawater region of the Arctic Ocean during the 8th and 9th Chinese Arctic Expedition Research Cruise. The identification of aerosol sources was conducted using a modified positive definite matrix factorization method and a backward air mass trajectory model. Two types of MA including the sea-salt aerosol (SSA) and the marine biogenic aerosol (BA) were identified and their concentrations were calculated. Then the physical-chemical characteristics of MA in the floating ice region and seawater region were compared under normalized conditions (−2.5 °C < T < −0.1 °C; 5.80 m/s < WS < 10.95 m/s) to discern the impact of sea ice. A unimodal distribution was observed for MA number concentration with a dominant peak ranging from 0.5 μm to 1.0 μm in size range. The findings revealed that the presence of sea ice cover led to a significant reduction of 52.2 % in the number concentration of SSA, while exerting minimal influence on its composition. BA number concentration in the floating ice region was 33.3 % higher than that in the seawater region. Strong winds (wind speed >6.5 m/s) transported organic matter and nutrients entrapped in sea ice into the atmosphere, leading to an increase in BA concentration. However, the presence of sea ice cover hampered the exchange of biogenic gases between the ocean and air, resulting in a reduction of secondary BA formation. Our study elucidates the correlation between MA release and sea ice coverage in the Arctic Ocean, thereby establishing a theoretical foundation for climate prediction models.

Multi-process atmospheric particle number size distribution over the Bohai Sea: Insights from cruise and onboard unmanned aerial vehicle observations

A better understanding of the particle number size distribution aids to better assess the direct and indirect effects of particles on air quality and climate. In this study, particle number concentrations (PNCs) and size distribution along with chemical components, gaseous pollutants, and meteorological parameters were measured during a cruise campaign over the Bohai Sea. Four distinct periods were identified, showing significant impacts from continental outflows and ocean emissions on the particle number size distributions. Under the strong terrestrial pollution transport period, an obvious increase of PNCs below 1 μm was observed. The significant correlation between black carbon (BC) and PNCs in the size range of 0.35–1.0 μm suggested aging of aerosols during the long-range transport. An invaded dust pollution significantly reduced PNCs below 0.5 μm, while tripled the number concentration of particles larger than 0.5 μm. The ocean moisture facilitated the mixing between dust and secondary aerosols. An intense sea fog event observed during the cruise slightly increased PNCs smaller than 1 μm while decreasing larger ones. The correlations between PNCs below 0.5 μm and BC as well as SO2 demonstrated the impact of shipping activities on the formation of fresh particles. Aerosol vertical profiles in the marine boundary layer were measured by an unmanned aerial vehicle platform. The vertical patterns of particle number size distribution were largely governed by the origins of transported air masses and profiles of wind fields. Observations showed that the particle distribution in the lower marine boundary layer was typically inhomogeneous and rapidly evolving with time, highlighting the importance of strengthening the vertical observations of atmospheric parameters over the ocean.

Long term measurements of aerosol mass concentration with optical particle counters: Discrepancies with plausible reasons

Gravimetry-based direct measurements of mass concentration require offline analysis which is not suited for field campaigns. Hence such campaigns rely on the estimation of mass concentration by indirect methods mostly calibrated in controlled laboratory conditions. Optical particle counter (OPC) employs algorithms converting the measured number concentration to mass concentration using appropriate conversion factors. The accuracy of such conversion has not been validated for widely varying atmospheric conditions. This study compares the mass concentration estimated by OPC with those directly obtained from gravimetry-based instruments for outdoor samples collected in Bathinda City, Punjab, India from January 2022 to November 2023. The difference in the gravimetrically measured and OPC predicted values quantified in terms of ratios (gravimetric to optically estimated mass concentration), came out to be 1.42 ± 0.77, 0.99 ± 0.51, and 1.17 ± 0.58 for PM10, PM2.5 and PM1, respectively. This difference when estimated with the back-up filter of OPC itself (C Factor), was 1.37 ± 0.66. More than half of the samples showed ratios outside the 0.8–1.2 range thus indicating under or over-estimation in the OPC predicted values. The probable role of variation in density, shape, and refractive index of atmospheric aerosol particles towards the observed inaccuracy of estimated mass concentration has been highlighted. In the absence of clear guidelines and protocols, the study suggests ways to improve the accuracy via periodic measurement of the C Factor and/or incorporating calibration factors in such measurements.

Impact of vehicles at the roadside of expressway in urban area: Simultaneous measurement of particle size distribution and positive matrix factorization

This study conducted real-time monitoring of size-resolved particle concentrations ranging from 9 nm to 10 μm simultaneously at four sites on the park ground and the roof of a five-story apartment buildings in the upwind and downwind areas of the Olympic Expressway next to apartment complex areas of Seoul, Korea. Using a positive matrix factorization model for source apportionment, eight factors were resolved at each monitoring site: four exhaust emissions of vehicles, one non-exhaust emission of vehicle, two regional sources, and one unknown source. After categorizing monitoring data into three cases by wind conditions, impact and contribution of each vehicle-related source on the local road to the roadside pollution was quantified and characterized by subtracting the urban background concentrations. Throughout the measurement period, the contribution of vehicle-related sources to the particle number concentration at each monitoring site ranged from 61 % to 69 %, while that to the particle mass concentration ranged from 39 % to 87 %. During periods of steady traffic flow and wind blowing from the road to three downwind sites at speeds exceeding >0.5 m/s during working hours, the particle number concentrations at the downwind sites were 2.2–2.5 times higher than the average levels. Among vehicle-related sources, gasoline vehicles with multiple injections or high-emitting diesel vehicles showed the highest contribution to particle number concentrations at all sites. As wind speed increased, the number concentrations of particles from vehicle exhaust and non-exhaust emissions decreased and increased, respectively, probably due to enhanced dilution and transport, respectively. In addition, particle number concentrations showed a parabolic curve-like trend with traffic volumes increasing to approximately 10,000 vehicles/h, and then decreasing for both vehicle exhaust and non-exhaust emissions. These results can be utilized in numerical modeling studies and in establishing traffic-related environmental policies to reduce seasonal and temporal particle exposure near the roadsides.

Investigation of emission characteristics of a marine cargo ship in real-world conditions

Pollution caused by ship emissions will considerably impact coastal areas. A test system that matched the actual conditions of a ship was designed based on a portable emission measurement system (PEMS), and the emission characteristic of gaseous and particle emissions and the particle size distribution of the ship's main engine were investigated under real-world operating conditions. The results showed that the emission concentrations of the main pollutants fluctuated greatly under the departure, anchoring, and docking conditions, and the peaks of CO, CO2, and NOx emissions appeared under these transient conditions. The emission concentrations of CO2, hydrocarbons, particle number (PN), and particulate mass increased with the increase in speed. The PN-based particle size distribution of the engine presented a unimodal distribution under daily operating conditions. The maximum emission factor of NOx based on the engine power was 29.53 g/kWh at the engine speed of 66 r/min. The results of the study may contribute to supplementing the emission factors of this type of ship, and provide data support for monitoring and assessment of the marine environment.

Characterizing sector-oriented roadside exposure to ultrafine particles (PM0.1) via machine learning models: Implications of covariates influences on sectors variability

Ultrafine particles (UFPs; PM0.1) possess intensified health risk due to their smaller size and unique spatial variability. One of major emission sources for UFPs is vehicle exhaust, which varies based on the traffic composition in each type of roadside sector. The current challenge of epidemiological UFPs study is limited characterization ability due to expensive instruments. This study assessed the UFPs particle number concentrations (UFPs PNC) exposure dose for typical healthy adults and children at three different roadside sectors, including industrial roadside (IN), residential roadside (RS), and urban background (UB). Furthermore, this study also developed and utilized machine learning (ML) algorithms that could accurately characterize the UFPs exposure dose and explain the covariates effects on the model outputs, representing the intra-urban variability of UFPs between sectors. It was found that the average inhaled UFPs dose for healthy adults and children during off-peak season (warm period) were 1.71 ± 0.19 × 1010; 1.28 ± 0.22 × 1010; 1.09 ± 0.18 × 1010 #/hour and 1.33 ± 0.15 × 1010; 0.99 ± 0.17 × 1010; 0.86 ± 0.14 × 1010 #/hour at IN, RS, UB. Inhaled UFPs were mainly deposited in tracheobronchial (TB) respiratory fraction for adults (67.7%) and in alveoli (ALV) fraction for children (67.5%). Among three ML algorithms implemented in this study, XGBoost possessed the highest UFPs PNC exposure dose estimation performances with R2 = 0.965; 0.959; 0.929 & RMSE = 0.79 × 108; 0.54 × 108; 0.15 × 105 #/hour at IN, RS, and UB which then followed by multiple linear regression (MLR), and random forest (RF). Furthermore, SHAP analysis from the XGBoost model has successfully pointed out the spatial variability of each roadside sector by quantifying the approximated contributions of covariates to the model's output. Findings in this study highlighted the potential use of ML models as an alternative for preliminary particle exposure source apportionment.

First insights into the new particle formation and growth at a north-eastern Romanian urban site, Iasi. Potential health risks from ultrafine particles

New particle formation (NPF) process brings significant contribution to the global atmospheric particle number concentrations. Evidence on the formation and growth of NPF is reported for the first time at a Romanian urban site, i.e., Iasi, north-eastern Romania. Size-dependent aerosol number concentrations were obtained during two short-term campaigns undertaken in 2017 by using a scanning mobility particle sizer. The existence of two categories of events can be highlighted by investigating the net maximum increase in the nucleation mode particle number concentration and the maximum size of the geometric median diameter of new particles. The variability of meteorological parameters showed that the solar radiation peak was usually associated with NPF events, while relative humidity was anti-correlated with those events. Calculated nucleation rate values for events in May, median of 4.5 cm−3 s−1, was lower than the corresponding median values of 8.6 cm−3 s−1 for December. The particle growth rates showed a similar trend with a median of 4.0 nm h−1 and 7.7 nm h−1, in May and December, respectively. The obtained results suggest that regional emission sources might bring some contributions on the particle nucleation and growth processes, particularly over the cold season. Regarding the deposition of particles in the respiratory system, it appears that ultrafine particles are among the most significant contributors to the alveolar deposits. Moreover, evidences were obtained that the impact on the particle deposition at the alveolar region is not mandatory in direct relation to the intensity of the NPF event, the pollution burden of the particles most probably playing an important role.

Multi-laser nanoparticle tracking analysis (NTA): A unique method to visualize dynamic (shear) and dynamic (Brownian motion) light scattering and quantify nonliving natural organic matter (NNOM) in environmental water

Application of simultaneous multi-laser nanoparticle tracking analysis (NTA) to environmental water samples to investigate nonliving natural organic matter (NNOM) is introduced as an innovative method for observing particles directly in their native media. Multi-laser NTA results of particle visualization, particle number concentration, and particle size distribution elucidated particle dynamics in low and high total dissolved solids (TDS) aqueous environmental samples. A pond water sample and concentrate from a reverse osmosis (RO) treatment process (Stage 1) had 1.3 × 108 and 5.62 × 1019 particles/mL, respectively, (at time = 0) after filtration at 0.45 μm. Beyond the traditional applications for this instrument, this research presents novel evidence-based investigations that probe the existence of supramolecular structures in environmental waters during turbulence or quiescence. The pond water sample exhibited time-dependent aggregation as the volume distribution shifted to greater diameter during quiescence, compared to turbulence. Disaggregation (increased numbers of particles over time) was noted in the >250 nm to <600 nm region, and aggregation of >450 nm particles was also noted in the quiescent RO concentrate sample, indicative of depletion of small particles to form larger ones. Multi-laser NTA and dynamic light scattering (DLS) capabilities were compared and contrasted. DLS and NTA are different (complementary) particle sizing techniques. DLS yielded more information about the physical hydrogel in the NNOM hierarchy whereas multi-laser NTA better characterized meta-chemical and chemical hydrogel characteristics. Operationalization of innovation—moving from fundamental investigations to application—is supported by implementing novel analytical instrumentation as we address issues involving climate change, drought, and the scarcity of potable water. Multi-laser NTA can be used as a tool to study and optimize complex water and wastewater treatment processes. Questions about water treatment efficiencies, membrane fouling, assistance of pollutant transport, and carbon capture cycles affected by NNOM will benefit from insights from multi-laser NTA.