Characterization of Fe-Containing and Pb-Containing Nanoparticles Resulting from Corrosion of Plumbing Materials in Tap Water Using a Hyphenated ATM-DMA-spICP-MS System.

Single-particle inductively coupled plasma mass spectrometry (spICP-MS) has been used to characterize metallic nanoparticles (NPs) assuming that all NPs are spherical and composed of pure element. However, environmental NPs generally do not meet these criteria, suggesting that spICP-MS may underestimate their true sizes. This study employed a system hyphenating the atomizer (ATM), differential mobility analyzer (DMA), and spICP-MS to characterize metallic NPs in tap water. Its performance was validated by using reference Au nanoparticles (AuNPs) and Ag-shelled AuNPs. The hyphenated system can determine the actual size and metal composition of both NPs with additional heating after ATM, while stand-alone spICP-MS misidentified the Ag-shelled AuNPs as smaller individual AgNPs and AuNPs. Dissolved metal ions could introduce artifact NPs after heating but could be eliminated by centrifugation. The hyphenated system was applied to characterize Fe-containing and Pb-containing NPs resulting from the corrosion of plumbing materials in tap water. The mode sizes of Fe-containing and Pb-containing NPs were determined to be 110 and 100 nm and the particle number concentrations were determined to be 4.99 × 107 and 1.40 × 106 #/mL, respectively. Cautions should be paid to potential changes in particle size induced by heating for metallic NPs with a low melting point or a high organic content.

A mobile platform for characterizing on-road tailpipe emissions and toxicity of ultrafine particles under real driving Conditions.

Acute exposure to fresh traffic-related air pollutants (TRAPs) can be high for road users, including motorbike drivers, cyclists, and pedestrians. However, evaluating the toxicity of fresh traffic emissions from on-road vehicles is challenging since pollution properties can change dynamically within a short distance and time. This study demonstrated a mobile platform equipped with an On-Board Diagnostic II (OBDII) system, a tailor-made portable emission measurement system, and an electrostatic air-liquid interface exposure system with human monocytic THP-1 cells to characterize on-road tailpipe emissions under real driving conditions. High number concentrations up to 106-107 # cm-3 of ultrafine particles (UFPs) were observed for a gasoline engine at the cold-start stage and a diesel engine during particulate filter regeneration. In particular, a substantial fraction of freshly emitted UFPs within the size less than 23 nm were observed and should be cautioned. The potential toxicity of fresh TRAPs was quantified by cell viability, cytotoxicity, oxidative stress, and inflammatory biomarkers. Results show that the decreased cell viability, increased lactate dehydrogenase (LDH) activity, and high oxidative stress induced by the fresh TRAPs were potentially contributed by gaseous pollutants as well as particles, especially driving with the high idling frequency. Moreover, the dominant contributor to the toxicity is different for gasoline's and diesel's TRAPs. Characterizing on-road air pollutant toxicity as well as physicochemical properties using an innovative mobile platform can fill this knowledge gap.

Characterizing emission factors and oxidative potential of motorcycle emissions in a real-world tunnel environment.

Transportation emissions significantly affect human health, air quality, and climate in urban areas. This study conducted experiments in an urban tunnel in Taipei, Taiwan, to characterize vehicle emissions under real driving conditions, providing emission factors of PM2.5, eBC, CO, and CO2. By applying multiple linear regression, it derives individual emission factors for heavy-duty vehicles (HDVs), light-duty vehicles (LDVs), and motorcycles (MCs). Additionally, the oxidative potential using dithiothreitol assay (OPDTT) was established to understand PM2.5 toxicity. Results showed HDVs dominated PM2.5 and eBC concentrations, while LDVs and MCs influenced CO and CO2 levels. The CO emission factor for transportation inside the tunnel was found to be higher than those in previous studies, likely owing to the increased fraction of MCs, which generally emit higher CO levels. Among the three vehicle types, HDVs exhibited the highest PM2.5 and eBC emission factors, while CO and CO2 levels were relatively higher for LDVs and MCs. The OPDTTm demonstrated that fresh traffic emissions were less toxic than aged aerosols, but higher OPDTTv indicated the impact on human health cannot be ignored. This study updates emission factors for various vehicle types, aiding in accurate assessment of transportation emissions' effects on air quality and human health, and providing a guideline for formulating mitigation strategies.

Assessing traffic-related air pollution-induced fiber-specific white matter degradation associated with motor performance declines in aged rats.

Fine particulate matter (PM2.5) is thought to exacerbate Parkinson's disease (PD) in the elderly, and early detection of PD progression may prevent further irreversible damage. Therefore, we used diffusion tensor imaging (DTI) for probing microstructural changes after late-life chronic traffic-related PM2.5 exposure. Herein, 1.5-year-old Fischer 344 rats were exposed to clean air (control), high-efficiency particulate air (HEPA)-filtered ambient air (HEPA group), and ambient traffic-related PM2.5 (PM2.5 group, 9.933 ± 1.021 µg/m3) for 3 months. Rotarod test, DTI tractographic analysis, and immunohistochemistry were performed in the end of study period. Aged rats exposed to PM2.5 exhibited motor impairment with decreased fractional anisotropy and tyrosine hydroxylase expression in olfactory and nigrostriatal circuits, indicating disrupted white matter integrity and dopaminergic (DA) neuronal loss. Additionally, increased radial diffusivity and lower expression of myelin basic protein in PM2.5 group suggested ageing progression of demyelination exacerbated by PM2.5 exposure. Significant production of tumor necrosis factor-α was also observed after PM2.5 exposure, revealing potential inflammation of injury to multiple fiber tracts of DA pathways. Microstructural changes demonstrated potential links between PM2.5-induced inflammatory white matter demyelination and behavioral performance, with indication of pre-manifestation of DTI-based biomarkers for early detection of PD progression in the elderly.

Deployment of a mobile platform to characterize spatial and temporal variation of on-road fine particles in an urban area.

Traffic-related air pollutants (TRAPs) pose a serious health hazard for residents and commuters in urban areas. In this study, a real-time mobile monitoring system was deployed in Taipei, a typical East Asian city with an overlap of high population density, traffic, and special structures (e.g., viaducts), to capture the on-road TRAPs at different times of the day. In general, black carbon, ultrafine particles (UFPs), CO concentrations, and lung deposition surface area (LDSA) were positively correlated with traffic flow, and for PM2.5, a more independent fluctuating concentration was observed. During rush-hour periods, the mean concentrations of UFPs, PM2.5, and LDSA were 6.12 × 104 ± 3.83 × 104 cm-3, 23 ± 8 µg/m3, and 2.29 × 102 ± 1.20 × 102 µm2/cm3, respectively. Additionally, the UFP number concentration and LDSA were two times higher along the high-traffic commuting route than along the lower traffic route. Pollutants tended to accumulate at sites near viaducts and high buildings and were significantly influenced by vehicle composition. In this study, the ratio of LDSA to total particle surface area concentration was used as an indicator of the degree of particle irregularity, which was directly related to aging during transport.

Effects of antibiotics and metals on lung and intestinal microbiome dysbiosis after sub-chronic lower-level exposure of air pollution in ageing rats.

We investigated the effects of antibiotics, drugs, and metals on lung and intestinal microbiomes after sub-chronic exposure of low-level air pollution in ageing rats. Male 1.5-year-old Fischer 344 ageing rats were exposed to low-level traffic-related air pollution via whole-body exposure system for 3 months with/without high-efficiency particulate air (HEPA) filtration (gaseous vs. particulate matter with aerodynamic diameter of ≤2.5 µm (PM2.5) pollution). Lung functions, antibiotics, drugs, and metals in lungs were examined and linked to lung and fecal microbiome analyses by high-throughput sequencing analysis of 16 s ribosomal (r)DNA. Rats were exposed to 8.7 µg/m3 PM2.5, 10.1 ppb NO2, 1.6 ppb SO2, and 23.9 ppb O3 in average during the study period. Air pollution exposure decreased forced vital capacity (FVC), peak expiratory flow (PEF), forced expiratory volume in 20 ms (FEV20), and FEF at 25∼75% of FVC (FEF25-75). Air pollution exposure increased antibiotics and drugs (benzotriazole, methamphetamine, methyl-1 H-benzotriazole, ketamine, ampicillin, ciprofloxacin, pentoxifylline, erythromycin, clarithromycin, ceftriaxone, penicillin G, and penicillin V) and altered metals (V, Cr, Cu, Zn, and Ba) levels in lungs. Fusobacteria and Verrucomicrobia at phylum level were increased in lung microbiome by air pollution, whereas increased alpha diversity, Bacteroidetes and Proteobacteria and decreased Firmicutes at phylum level were occurred in intestinal microbiome. Lung function decline was correlated with increasing antibiotics, drugs, and metals in lungs as well as lung and intestinal microbiome dysbiosis. The antibiotics, drugs, and Cr, Co, Ca, and Cu levels in lung were correlated with lung and intestinal microbiome dysbiosis. The lung microbiome was correlated with intestinal microbiome at several phylum and family levels after air pollution exposure. Our results revealed that antibiotics, drugs, and metals in the lung caused lung and intestinal microbiome dysbiosis in ageing rats exposed to air pollution, which may lead to lung function decline.

Indoor, outdoor, and personal exposure to PM2.5 and their bioreactivity among healthy residents of Hong Kong.

Direct evidence about associations between fine particles (PM2.5) components and the corresponding PM2.5 bioreactivity at the individual level is limited. We conducted a panel study with repeated personal measurements involving 56 healthy residents in Hong Kong. Fractional exhaled nitric oxide (FeNO) levels were measured from these subjects. Out of 56 subjects, 27 (48.2%) participated in concurrent outdoor, indoor, and personal PM2.5 monitoring. Organic carbon (OC), elemental carbon (EC), particle bound-polycyclic aromatic hydrocarbons (PAHs), and phthalates were analyzed. Alteration in cell viability, lactic dehydrogenase (LDH), interleukin-6 (IL-6), and 8-isoprostane by 50 µg/mL PM2.5 extracts was determined in A549 cells in vitro. Moderate heterogeneities were shown in PM2.5 exposures and the corresponding PM2.5 bioreactivity across different sample types. Associations between the analyzed components and PM2.5 bioreactivity were assessed using the multiple regression models. Toxicological results revealed that indoor and personal exposure to OC as well as PAH compounds and their derivatives (e.g., Alkyl-PAHs, Oxy-PAHs) induced cell viability reduction and increase in levels of LDH, IL-6, and 8-isoprostane. Overall, OC in personal exposure played a dominant role in PM2.5-induced bioreactivity. Subsequently, we examined the associations of FeNO with IL-6 and 8-isoprostane levels using mixed-effects models. The results showed that per interquartile change in IL-6 and 8-isoprostane were associated with a 6.4% (p < 0.01) and 11.1% (p < 0.01) increase in FeNO levels, respectively. Our study explored the toxicological properties of chemical components in PM2.5 exposure, which suggested that residential indoors and personal OC and PAHs should be of great concern for human health. These findings indicated that further studies in inflammation and oxidative stress-related illnesses due to particle exposure would benefit from the assessment of in vitro PM2.5 bioreactivity.

Chronic pulmonary exposure to traffic-related fine particulate matter causes brain impairment in adult rats.

BACKGROUND: Effects of air pollution on neurotoxicity and behavioral alterations have been reported. The objective of this study was to investigate the pathophysiology caused by particulate matter (PM) in the brain. We examined the effects of traffic-related particulate matter with an aerodynamic diameter of < 1 µm (PM1), high-efficiency particulate air (HEPA)-filtered air, and clean air on the brain structure, behavioral changes, brainwaves, and bioreactivity of the brain (cortex, cerebellum, and hippocampus), olfactory bulb, and serum after 3 and 6 months of whole-body exposure in 6-month-old Sprague Dawley rats. RESULTS: The rats were exposed to 16.3 ± 8.2 (4.7~ 68.8) µg/m3 of PM1 during the study period. An MRI analysis showed that whole-brain and hippocampal volumes increased with 3 and 6 months of PM1 exposure. A short-term memory deficiency occurred with 3 months of exposure to PM1 as determined by a novel object recognition (NOR) task, but there were no significant changes in motor functions. There were no changes in frequency bands or multiscale entropy of brainwaves. Exposure to 3 months of PM1 increased 8-isoporstance in the cortex, cerebellum, and hippocampus as well as hippocampal inflammation (interleukin (IL)-6), but not in the olfactory bulb. Systemic CCL11 (at 3 and 6 months) and IL-4 (at 6 months) increased after PM1 exposure. Light chain 3 (LC3) expression increased in the hippocampus after 6 months of exposure. Spongiosis and neuronal shrinkage were observed in the cortex, cerebellum, and hippocampus (neuronal shrinkage) after exposure to air pollution. Additionally, microabscesses were observed in the cortex after 6 months of PM1 exposure. CONCLUSIONS: Our study first observed cerebral edema and brain impairment in adult rats after chronic exposure to traffic-related air pollution.

Investigation into the pulmonary inflammopathology of exposure to nickel oxide nanoparticles in mice.

We investigated the effects of nickel oxide nanoparticles (NiONPs) on the pulmonary inflammopathology. NiONPs were intratracheally installed into mice, and lung injury and inflammation were evaluated between 1 and 28 days. NiONPs caused significant increases in LDH, total protein, and IL-6 and a decrease in IL-10 in the BALF and increases in 8-OHdG and caspase-3 in lung tissues at 24 h. Airway inflammation was present in a dose-dependent manner from the upper to lower airways at 24 h of exposure as analyzed by SPECT. Lung parenchyma inflammation and small airway inflammation were observed by CT after NiONP exposure. 8-OHdG in lung tissues had increased with formation of fibrosis at 28 days. Focal adhesion was the most important pathways identified at 24 h as determined by protemics, whereas glutathione metabolism was the most important identified at 28 days. Our results demonstrated the pulmonary inflammopathology caused by NiONPs based on image-to-biochemical approaches.

Quantifying Surface Area of Nanosheet Graphene Oxide Colloid Using a Gas-Phase Electrostatic Approach.

We demonstrate a new, facile gas-phase electrostatic approach to successfully quantify equivalent surface area of graphene oxide (GO) colloid on a number basis. Mobility diameter (dp,m)-based distribution and the corresponding equivalent surface area (SA) of GO colloids (i.e., with different lateral aspect ratios) were able to be identified by electrospray-differential mobility analysis (ES-DMA) coupled to a condensation particle counter (CPC) and an aerosol surface area analyzer (ASAA). A correlation of SA ∝ dp,m2.0 was established using the ES-DMA-CPC/ASAA, which is consistent with the observation by the 2-dimensional image analysis of size-selected GOs. An ultrafast surface area measurement of GO colloid was achieved via a direct coupling of ES with a combination of ASAA and CPC (i.e., measurement time was 2 min per sample; without size classification). The measured equivalent surface area of GO was ∼202 ± 7 m2 g-1, which is comparable to Brunauer-Emmett-Teller (BET) surface area, ∼240 ± 59 m2 g-1. The gas-phase electrostatic approach proposed in this study has the superior advantages of being fast, requiring no elaborate drying process, and requiring only a very small amount of sample (i.e., <0.01 mg). To the best of our knowledge, this is the first study of using an aerosol-based electrostatic coupling technique to obtain the equivalent surface area of graphene oxide on a number basis with a high precision of measurement.

Pulmonary pathobiology induced by zinc oxide nanoparticles in mice: A 24-hour and 28-day follow-up study.

Inhaled zinc oxide nanoparticles (ZnONPs) have high deposition rates in the alveolar region of the lungs; however, the adverse health effects of ZnONPs on the respiratory system are unclear. Herein, pathobiological responses of the respiratory system of mice that received intratracheal administration of ZnONPs were investigated by a combination of molecular and imaging (SPECT and CT) approaches. Also, normal BEAS-2B and adenocarcinoma A549 cells were used to confirm the results in mice. First, female BALB/c mice were administrated a series of doses of 20-nm ZnONPs and were compared to the phosphate-buffered saline control for 24-h and 28-day follow-up observations. Field emission-scanning electron microscopy and an energy-dispersive X-ray microanalysis were first used to characterize ZnONPs. After 24h, instilled ZnONPs had caused significant increases in lactic dehydrogenase (LDH) in bronchoalveolar lavage fluid (BALF) and 8-hydroxy-2'-deoxyguanosine (8-OHdG), caspase-3, and the p63 tumor marker in lung tissues (p<0.05). Airway inflammation was present in a dose-dependent manner from the upper to the lower airway as analyzed by SPECT. After 28days, p63 had significantly increased due to ZnONP exposure in lung tissues (p<0.05). Pulmonary inflammatory infiltration mainly occurred in the left and right subsegments of the secondary bronchial bifurcation as observed by CT. A significant increase in p63 and decrease in TTF1 levels were observed in BEAS-2B cells by ZnONP (p<0.05), but not in A549 cells. Our results demonstrated that regional lung inflammation occurred with ZnONP exposure. We also showed that p63 was consistently overexpressed due to ZnONP exposure in vivo and in vitro. This work provides unique findings on the p63 response and the pathobiology in response to ZnONPs, which could be important to the study of pulmonary toxicity and repair.

Quantitative characterization of colloidal assembly of graphene oxide-silver nanoparticle hybrids using aerosol differential mobility-coupled mass analyses.

In this work, we develop an aerosol-based, time-resolved ion mobility-coupled mass characterization method to investigate colloidal assembly of graphene oxide (GO)-silver nanoparticle (AgNP) hybrid nanostructure on a quantitative basis. Transmission electron microscopy (TEM) and zeta potential (ZP) analysis were used to provide visual information and elemental-based particle size distributions, respectively. Results clearly show a successful controlled assembly of GO-AgNP by electrostatic-directed heterogeneous aggregation between GO and bovine serum albumin (BSA)-functionalized AgNP under an acidic environment. Additionally, physical size, mass, and conformation (i.e., number of AgNP per nanohybrid) of GO-AgNP were shown to be proportional to the number concentration ratio of AgNP to GO (R) and the selected electrical mobility diameter. An analysis of colloidal stability of GO-AgNP indicates that the stability increased with its absolute ZP, which was dependent on R and environmental pH. The work presented here provides a proof of concept for systematically synthesizing hybrid colloidal nanomaterials through the tuning of surface chemistry in aqueous phase with the ability in quantitative characterization. Graphical Abstract Colloidal assembly of graphene oxide-silver nanoparticle hybrids characterized by aerosol differential mobility-coupled mass analyses.

Surface PEGylation of Silver Nanoparticles: Kinetics of Simultaneous Surface Dissolution and Molecular Desorption.

A quantitative study of the stability of silver nanoparticles (AgNPs) conjugated with thiolated polyethylene glycol (SH-PEG) was conducted using gas-phase ion-mobility and mass analyses. The extents of aggregation and surface dissolution of AgNPs, as well as the amount of SH-PEG adsorption and desorption, were able to be characterized simultaneously for the kinetic study. The results show that the SH-PEG with a molecular mass of 6 kg/mol (SH-PEG6K) was able to adsorb to the surface of AgNP to form PEG6K-HS-AgNP conjugates, with the maximum surface adsorbate density of ∼0.10 nm(-2). The equilibrium binding constant for SH-PEG6K on AgNPs was calculated as ∼(4.4 ± 0.9) × 10(5) L/mol, suggesting a strong affinity due to thiol bonding to the AgNP surface. The formation of SH-PEG6K corona prevented PEG6K-HS-AgNP conjugates from aggregation under the acidic environment (pH 1.5), but dissolution of core AgNPs occurred following a first-order reaction. The rate constant of Ag dissolution from PEG6K-HS-AgNP was independent of the starting surface packing density of SH-PEG6K on AgNP (σ0), indicating that the interactions of H(+) with core AgNP were not interfered by the presence of SH-PEG6K corona. The surface packing density of SH-PEG6K decreased simultaneously following a first-order reaction, and the desorption rate constant of SH-PEG6K from the conjugates was proportional to σ0. Our work presents the first quantitative study to illustrate the complex mechanism that involves simultaneous aggregation and dissolution of core AgNPs in combination with adsorption and desorption of SH-PEG. This work also provides a prototype method of coupled experimental scheme to quantify the change of particle mass versus the corresponding surface density of functional molecular species on nanoparticles.

Chemical characteristics and formation mechanism of secondary inorganic aerosols: The decisive role of aerosol acidity and meteorological conditions.

In recent years, there has been a growing concern about air pollution and its impact on the air quality and human health, especially for fine particulate matter (PM2.5) and its associated secondary aerosols in urban areas. This study conducted a year-long field campaign to collect PM2.5 samples day and night in an urban area of central Taiwan. Higher PM2.5 mass concentrations were observed in winter (27.7 ± 9.7 µg/m3), followed by autumn (22.5 ± 8.3 µg/m3), spring (19.2 ± 6.4 µg/m3), and summer (11.0 ± 3.1 µg/m3). The dominant formation mechanism of secondary inorganic aerosols was heterogeneous reactions of NO3- at night and homogeneous reactions of SO42- during the day. Additionally, significant correlations were observed between aerosol liquid water content (ALWC) and NO3- during nighttime, indicating the importance of aqueous-phase NO3- formation. The role of aerosol acidity was explored and a unique alkaline condition was found in spring and summer, which showed lower PM2.5 concentrations than the neutralized condition. Under the neutralized condition, higher PM2.5 concentrations were commonly found when combining the ammonium-rich regime with molar ratios of [NO3-]/[SO42-] exceeding 1.6, suggesting the importance of reducing both NH3 and NOx. Furthermore, the results showed that reducing NH3 should be prioritized under high temperature conditions, while reducing NOx became important under low temperature conditions. Clustering of backward trajectories showed that long-range transport could enhance the formation of secondary aerosols, but local emissions emerged as the main factor driving high PM2.5 concentrations. This study provides insights for policymakers to improve air quality, suggesting that different mitigation strategies should be formulated based on meteorological variables and that using clean energy for vehicles and electricity generation is important to alleviate air pollution.

A traffic-induced shift of ultrafine particle sources under COVID-19 soft lockdown in a subtropical urban area.

During the unprecedented COVID-19 city lockdown, a unique opportunity arose to dissect the intricate dynamics of urban air quality, focusing on ultrafine particles (UFPs) and volatile organic compounds (VOCs). This study delves into the nuanced interplay between traffic patterns and UFP emissions in a subtropical urban setting during the spring-summer transition of 2021. Leveraging meticulous roadside measurements near a traffic nexus, our investigation unravels the intricate relationship between particle number size distribution (PNSD), VOCs mixing ratios, and detailed vehicle activity metrics. The soft lockdown era, marked by a 20-27% dip in overall traffic yet a surprising surge in early morning motorcycle activity, presented a natural experiment. We observed a consequential shift in the urban aerosol regime: the decrease in primary emissions from traffic substantially amplified the role of aged particles and secondary aerosols. This shift was particularly pronounced under stagnant atmospheric conditions, where reduced dilution exacerbated the influence of alternative emission sources, notably solvent evaporation, and was further accentuated with the resumption of normal traffic flows. A distinct seasonal trend emerged as warmer months approached, with aromatic VOCs such as toluene, ethylbenzene, and xylene not only increasing but also significantly contributing to more frequent particle growth events. These findings spotlight the criticality of targeted strategies at traffic hotspots, especially during periods susceptible to weak atmospheric dilution, to curb UFP and precursor emissions effectively. As we stand at the cusp of widespread vehicle electrification, this study underscores the imperative of a holistic approach to urban air quality management, embracing the complexities of primary emission reductions and the resultant shifts in atmospheric chemistry.

A comprehensive examination of temporal-seasonal variations of PM1.0 and PM2.5 in taiwan before and during the COVID-19 lockdown.

COVID-19 has been a significant global concern due to its contagious nature. In May 2021, Taiwan experienced a severe outbreak, leading the government to enforce strict Pandemic Alert Level 3 restrictions in order to curtail its spread. Although previous studies in Taiwan have examined the effects of these measures on air quality, further research is required to compare different time periods and assess the health implications of reducing particulate matter during the Level 3 lockdown. Herein, we analyzed the mass concentrations, chemical compositions, seasonal variations, sources, and potential health risks of PM1.0 and PM2.5 in Central Taiwan before and during the Level 3 lockdown. As a result, coal-fired boilers (47%) and traffic emissions (53%) were identified as the predominant sources of polycyclic aromatic hydrocarbons (PAHs) in PM1.0, while in PM2.5, the dominant sources of PAHs were coal-fired boilers (28%), traffic emissions (50%), and iron and steel sinter plants (22.1%). Before the pandemic, a greater value of 20.9 ± 6.92 µg/m3 was observed for PM2.5, which decreased to 15.3 ± 2.51 µg/m3 during the pandemic due to a reduction in industrial and anthropogenic emissions. Additionally, prior to the pandemic, PM1.0 had a contribution rate of 79% to PM2.5, which changed to 89% during the pandemic. Similarly, BaPeq values in PM2.5 exhibited a comparable trend, with PM1.0 contributing 86% and 65% respectively. In both periods, the OC/EC ratios for PM1.0 and PM2.5 were above 2, due to secondary organic compounds. The incremental lifetime cancer risk (ILCR) of PAHs in PM2.5 decreased by 4.03 × 10-5 during the pandemic, with PM1.0 contributing 73% due to reduced anthropogenic activities.

A hybrid model for estimating the number concentration of ultrafine particles based on machine learning algorithms in central Taiwan.

Modeling is a cost-effective measure to estimate ultrafine particle (UFP) levels. Previous UFP estimates generally relied on land-use regression with insufficient temporal resolution. We carried out in-situ measurements for UFP in central Taiwan and developed a model incorporating satellite-based measurements, meteorological variables, and land-use data to estimate daily UFP levels at a 1-km resolution. Two sampling campaigns were conducted for measuring hourly UFP concentrations at six sites between 2008-2010 and 2017-2021, respectively, using scanning mobility particle sizers. Three machine learning algorithms, namely random forest, eXtreme gradient boosting (XGBoost), and deep neural network, were used to develop UFP estimation models. The performances were evaluated with a 10-fold cross-validation, temporal, and spatial validation. A total of 1,022 effective sampling days were conducted. The XGBoost model had the best performance with a training coefficient of determination (R2) of 0.99 [normalized root mean square error (nRMSE): 6.52%] and a cross-validation R2 of 0.78 (nRMSE: 31.0%). The ten most important variables were surface pressure, distance to the nearest road, temperature, calendar year, day of the year, NO2, meridional wind, the total length of roads, PM2.5, and zonal wind. The UFP levels were elevated along the main roads across different seasons, suggesting that traffic emission is an important contributor to UFP. This hybrid model outperformed prior land use regression models and thus can provide more accurate estimates of UFP for epidemiological studies.

Sources, transport, and visibility impact of ambient submicrometer particle number size distributions in an urban area of central Taiwan.

This study applied positive matrix factorization (PMF) to identify the sources of size-resolved submicrometer (10-1000 nm) particles and quantify their contributions to impaired visibility based on the particle number size distributions (PNSDs), aerosol light extinction (bp), air pollutants (PM10, PM2.5, SO2, O3, and NO), and meteorological parameters (temperature, relative humidity, wind speed, wind direction, and ultraviolet index) measured hourly over an urban basin in central Taiwan between 2017 and 2021. The transport of source-specific PNSDs was evaluated with wind and back trajectory analyses. The PMF revealed six sources to the total particle number (TPN), surface (TPS), volume (TPV), and bp. Factor 1 (F1), the key contributor to TPN (35.0 %), represented nucleation (<25 nm) particles associated with fresh traffic emission and secondary new particle formation, which were transported from the west-southwest by stronger winds (>2.2 m s-1). F2 represented the large Aitken (50-100 nm) particles transported regionally via northerly winds, whereas F3 represented large accumulation (300-1000 nm) particles, which showed elevated concentrations under stagnant conditions (<1.1 m s-1). F4 represented small Aitken (25-50 nm) particles arising from the growth and transport of the nucleation particles (F1) via west-southwesterly winds. F5 represented large Aitken particles originating from combustion-related SO2 sources and carried by west-northwesterly winds. F6 represented small accumulation (100-300 nm) particles emitted both by local sources and by the remote SO2 sources found for F5. Overall, large accumulation particles (F3) played the greatest role in determining the TPV (66.4 %) and TPS (34.8 %), and their contribution to bp increased markedly from 17.3 % to 40.7 % as visibility decreased, indicating that TPV and TPS are better metrics than TPN for estimating bp. Furthermore, slow-moving air masses-and therefore stagnant conditions-facilitate the build-up of accumulation mode particles (F3 + F6), resulting in the poorest visibility.

Source-oriented risk and lung-deposited surface area (LDSA) of ultrafine particles in a Southeast Asia urban area.

Submicron and ultrafine particle (UFP) exposure may be epidemiologically and toxicologically linked to pulmonary, neurodegenerative, and cardiovascular diseases. This study explores UFP and fine particle sources using a positive matrix factorization (PMF) model based on PM2.5 chemical compositions and particle number size distributions (PNSDs). The particle chemical composition and size distribution contributions are simultaneously identified to evaluate lung deposition and excess cancer risks. High correlations between the PNSD and chemical composition apportionment results were observed. Fresh and aged traffic particles dominated the number concentrations, while heterogeneous, photochemical reactions and/or regional transport may have resulted in secondary aerosol formation. Fresh and aged road traffic particle sources mostly contributed to the lung deposition dosage in the pulmonary region (~53 %), followed by the tracheobronchial (~30.4 %) and head regions (~16.6 %). However, lung-deposited surface area (LDSA) concentrations were dominated by aged road traffic (~39.2 %) and secondary aerosol (~33.2 %) sources. The excess cancer risks caused by Cr6+, Ni, and As were also mainly contributed to by aged road traffic (~31.7 %) and secondary aerosols (~67 %). The source apportionments based on the physical and chemical properties of aerosol particles are complementary, offering a health impact benchmark of UFPs in a Southeast Asia urban city.

Embedded information of aerosol type, hygroscopicity and scattering enhancement factor revealed by the relationship between PM2.5 and aerosol optical depth.

Satellite aerosol optical depth (AOD) provides an alternative way to depict the spatial distribution of near-surface PM2.5. In this study, a mathematical formulation of how PM2.5 is related to AOD is presented. When simplified to a linear equation, a functional dependence of the slope on the aerosol type, scattering enhancement factor f(RH), and boundary layer height is revealed, while the influence of the vertical aerosol profile is embedded in the intercept. Specifically, we focus on the effects of aerosol properties and employ a new aerosol index (Normalized Gradient Aerosol Index, NGAI) for classifying aerosol subtypes. The combination of AOD difference at shorter wavelengths over longer-wavelength AOD from AERONET data could distinguish and subclassify aerosol types previously indistinguishable by AE (i.e., urban-industrial pollution, U/I, and biomass burning, BB). AOD-PM2.5 regressions are performed on these aerosol subtypes at various relative humidity (RH) levels. The results suggest that BB aerosols are nearly hydrophobic until the RH exceeds 80 %, while the AOD-PM2.5 regressions for U/I depend on RH levels. Moreover, the scattering enhancement factor f(RH) can be calculated by taking the ratio of intercepts between dry and humidity conditions, which is proposed and tested for the first time in this study. Our results show an f(RH ≥ 80 %) of ∼2.6 for U/I-dominated aerosols, whereas the value is not over 1.5 for BB aerosols. The f(RH) can be further used to derive the optical hygroscopicity parameter (κsca), demonstrating that the NGAI can be used to exploit differences in aerosol hygroscopicity and improve the AOD-PM2.5 relationship.