Impact of urban tree arrangement on pedestrian exposure to the size-fractional particulate matter in a city boulevard.

Trees act as natural filters that mitigate roadside air pollution. However, the filtration impact of different tree arrangements on traffic pollutants with different particle diameters has rarely been analysed in real street canyon environments. To quantify how roadside tree arrangements impact pedestrian exposure to particle number concentrations (PNCs) of different diameters (0.25-32 µm), in situ field measurements were carried out in a boulevard-type street canyon in the city of Xi'an, China. This study analysed the experimental data of PNCs collected along segments of a pedestrian lane under four typical tree arrangements: open space without trees, a sparse-spaced tree arrangement, a medium-spaced tree arrangement, and a dense-spaced tree arrangement in a street canyon. Our results reveal that the effect of tree arrangement on PNCs depended on the particle diameter. In general, trees can significantly reduce coarse PNC (particles with diameters >2.5 µm) but not the fine PNC. Quantitative analysis showed that a medium-spaced tree arrangement, in which tree crowns are adjacent to each other but do not overlap, is the most capable of reducing PNC, followed by a sparse-spaced tree arrangement, while a the dense-spaced tree arrangement has the least impact. The attenuation effect of trees on the PNCs increased with increasing particle diameter. Moreover, the presence of trees altered the local microclimate, which also affected how exposure to PNCs changed. Our empirical findings further highlight the complexity of how trees affect particulate pollutants in street canyons and provide timely insights for enhancing tree-planning management in cities from the perspective of air quality improvement.

Beyond the Runway: Respiratory health effects of ultrafine particles from aviation in children.

Aviation has been shown to cause high particle number concentrations (PNC) in areas surrounding major airports. Particle size distribution and composition differ from motorized traffic. The objective was to study short-term effects of aviation-related UFP on respiratory health in children. In 2017-2018 a study was conducted in a school panel of 7-11 year old children (n = 161) living North and South of Schiphol Airport. Weekly supervised spirometry and exhaled nitric oxide (eNO) measurements were executed. The school panel, and an additional group of asthmatic children (n = 19), performed daily spirometry tests at home and recorded respiratory symptoms. Hourly concentrations of various size fractions of PNC and black carbon (BC) were measured at three school yards. Concentrations of aviation-related particles were estimated at the residential addresses using a dispersion model. Linear and logistic mixed models were used to investigate associations between daily air pollutant concentrations and respiratory health. PNC20, a proxy for aviation-related UFP, was virtually uncorrelated with BC and PNC50-100 (reflecting primarily motorized traffic), supporting the feasibility of separating PNC from aviation and other combustion sources. No consistent associations were found between various pollutants and supervised spirometry and eNO. Major air pollutants were significantly associated with an increase in various respiratory symptoms. Odds Ratios for previous day PNC20 per 3,598pt/cm3 were 1.13 (95%CI 1.02; 1.24) for bronchodilator use and 1.14 (95%CI 1.03; 1.26) for wheeze. Modelled aviation-related UFP at the residential addresses was also positively associated with these symptoms, corroborating the PNC20 findings. PNC20 was not associated with daily lung function, but PNC50-100 and BC were negatively associated with FEV1. PNC of different sizes indicative of aviation and other combustion sources were independently associated with an increase of respiratory symptoms and bronchodilator use in children living near a major airport. No consistent associations between aviation-related UFP with lung function was observed.

Towards a reference material for microplastics' number concentration-case study of PET in water using Raman microspectroscopy.

Increasing demand for size-resolved identification and quantification of microplastic particles in drinking water and environmental samples requires the adequate validation of methods and techniques that can be used for this purpose. In turn, the feasibility of such validation depends on the existence of suitable certified reference materials (CRM). A new candidate reference material (RM), consisting of polyethylene terephthalate (PET) particles and a water matrix, has been developed. Here, we examine its suitability with respect to a homogeneous and stable microplastic particle number concentration across its individual units. A measurement series employing tailor-made software for automated counting and analysis of particles (TUM-ParticleTyper 2) coupled with Raman microspectroscopy showed evidence of the candidate RM homogeneity with a relative standard deviation of 12% of PET particle counts involving particle sizes >30 µm. Both the total particle count and the respective sums within distinct size classes were comparable in all selected candidate RM units. We demonstrate the feasibility of production of a reference material that is sufficiently homogeneous and stable with respect to the particle number concentration.

Los Angeles Basin's air quality transformation: a long-term investigation on the impacts of PM regulations on the trends of ultrafine particles and co-pollutants.

This study investigates the long-term trends of ambient ultrafine particles (UFPs) and associated airborne pollutants in the Los Angeles Basin from 2007 to 2022, focusing on the indirect effects of regulations on UFP levels. The particle number concentration (PNC) of UFPs was compiled from previous studies in the area, and associated co-pollutant data, including nitrogen oxides (NOx), carbon monoxide (CO), elemental carbon (EC), organic carbon (OC), and ozone (O3), were obtained from the chemical speciation network (CSN) database. Over the study period, a general decrease was noted in the PNC of UFPs, NOx, EC, and OC, except for CO, the concentration trends of which did not exhibit a consistent pattern. UFPs, NOx, EC, and OC were positively correlated, while O3 had a negative correlation, especially with NOx. Our analysis discerned two distinct subperiods in pollutant trends: 2007-2015 and 2016-2022. For example, there was an overall decrease in the PNC of UFPs at an annual rate of -850.09 particles/cm3/year. This rate was more pronounced during the first sub-period (2007-2015) at -1814.9 particles/cm3/year and then slowed to -227.21 particles/cm3/year in the second sub-period (2016-2023). The first sub-period (2007-2015) significantly influenced pollutant level changes, exhibiting more pronounced and statistically significant changes than the second sub-period (2016-2022). Since 2016, almost all primary pollutants have stabilized, indicating a reduced impact of current regulations, and emphasizing the need for stricter standards. In addition, the study included an analysis of Vehicle Miles Traveled (VMT) trends from 2007 to 2022 within the Los Angeles Basin. Despite the general increase in VMT, current regulations and cleaner technologies seem to have successfully mitigated the potential increase in increase in PNC. Overall, while a decline in UFPs and co-pollutant levels was observed, the apparent stabilization of these levels underscores the need for more stringent regulatory measures and advanced emission standards.

Characteristics of airborne particles in stone quarrying areas: Human exposure assessment and mitigation.

This investigation aims to assess the levels of human exposure to airborne particulate matter (PM) in various locations of a natural stone quarry for the first time based on simultaneous measurements of both PM mass and number concentrations (PMC and PNC). A quarry located in Danang city, Vietnam, considered to be a "hotspot" of air pollution in the city, was selected for detailed investigations. Both PMC and PNC were found to be significantly higher (1.2-6.0 times) within the quarry compared to surrounding areas. Mechanical activities during mining, notably crushing, screening, hauling, and loading stones, contributed to increased emissions of PM in the coarser mode (1-10 µm) compared to the accumulation mode (0.1-1 µm) and thus increased deposition of PM1-10 in the human upper respiratory tract. In contrast, combustion activities, especially the diesel engine exhaust from various machines and vehicles used in the quarry, resulted in increased emissions of small particles in the accumulation mode that dominated the PNC and in their deposition in the lower respiratory tract. Simultaneous measurements of PNC and PMC revealed that the PM counts were strongly associated with PM deposition in the alveolar region (accounting for ≈ 76% of total PNC of particles less than 10 µm, N10), while the PM mass concentration was a better indicator of the deposition of PM in the head airway region (≈92% of total PMC of PM10). Overall, this study demonstrates the significance of measuring both PNC and PMC to assess PM exposure levels, regional respiratory doses, and potential health effects associated with human exposure to PM generated from stone quarrying activities. The novelty of this work is the integration of real-time mass and number concentrations of PM over the size range from 20 nm to 10 µm to provide insights into respiratory deposited doses of size-fractionated PM among quarry workers.

New Insights on the Formation of Nucleation Mode Particles in a Coastal City Based on a Machine Learning Approach.

Atmospheric particles have profound implications for the global climate and human health. Among them, ultrafine particles dominate in terms of the number concentration and exhibit enhanced toxic effects as a result of their large total surface area. Therefore, understanding the driving factors behind ultrafine particle behavior is crucial. Machine learning (ML) provides a promising approach for handling complex relationships. In this study, three ML models were constructed on the basis of field observations to simulate the particle number concentration of nucleation mode (PNCN). All three models exhibited robust PNCN reproduction (R2 > 0.80), with the random forest (RF) model excelling on the test data (R2 = 0.89). Multiple methods of feature importance analysis revealed that ultraviolet (UV), H2SO4, low-volatility oxygenated organic molecules (LOOMs), temperature, and O3 were the primary factors influencing PNCN. Bivariate partial dependency plots (PDPs) indicated that during nighttime and overcast conditions, the presence of H2SO4 and LOOMs may play a crucial role in influencing PNCN. Additionally, integrating additional detailed information related to emissions or meteorology would further enhance the model performance. This pilot study shows that ML can be a novel approach for simulating atmospheric pollutants and contributes to a better understanding of the formation and growth mechanisms of nucleation mode particles.

Assessment of indoor air quality in health clubs: insights into (ultra)fine and coarse particles and gaseous pollutants.

Introduction: Exercising on regular basis provides countless health benefits. To ensure the health, well-being and performance of athletes, optimal indoor air quality, regular maintenance and ventilation in sport facilities are essential. Methods: This study assessed the levels of particulate, down to the ultrafine range (PM10, PM2.5, and particle number concentration in size range of 20-1,000 nm, i.e., - PNC20-1000 nm), gaseous pollutants (total volatile organic compounds - TVOCs, CO2, and O3) and comfort parameters (temperature - T, relative humidity - RH) in different functional spaces of health clubs (n = 8), under specific occupancy and ventilation restrictions. Results and Discussion: In all HCs human occupancy resulted in elevated particles (up to 2-3 times than those previously reported), considering mass concentrations (PM10: 1.9-988.5 µg/m3 PM2.5: 1.6-479.3 µg/m3) and number (PNC 1.23 × 103 - 9.14 × 104 #/cm3). Coarse and fine PM indicated a common origin (rs = 0.888-0.909), while PNC showed low-moderate associations with particle mass (rs = 0.264-0.629). In addition, up to twice-higher PM and PNC were detected in cardiofitness & bodybuilding (C&B) areas as these spaces were the most frequented, reinforcing the impacts of occupational activities. In all HCs, TVOCs (0.01-39.67 mg/m3) highly exceeded the existent protection thresholds (1.6-8.9 times) due to the frequent use of cleaning products and disinfectants (2-28 times higher than in previous works). On contrary to PM and PNC, TVOCs were higher (1.1-4.2 times) in studios than in C&B areas, due to the limited ventilations combined with the smaller room areas/volumes. The occupancy restrictions also led to reduced CO2 (122-6,914 mg/m3) than previously observed, with the lowest values in HCs with natural airing. Finally, the specific recommendations for RH and T in sport facilities were largely unmet thus emphasizing the need of proper ventilation procedures in these spaces.

Laboratory Comparison of Low-Cost Particulate Matter Sensors to Measure Transient Events of Pollution-Part B-Particle Number Concentrations.

Low-cost Particulate Matter (PM) sensors offer an excellent opportunity to improve our knowledge about this type of pollution. Their size and cost, which support multi-node network deployment, along with their temporal resolution, enable them to report fine spatio-temporal resolution for a given area. These sensors have known issues across performance metrics. Generally, the literature focuses on the PM mass concentration reported by these sensors, but some models of sensors also report Particle Number Concentrations (PNCs) segregated into different PM size ranges. In this study, eight units each of Alphasense OPC-R1, Plantower PMS5003 and Sensirion SPS30 have been exposed, under controlled conditions, to short-lived peaks of PM generated using two different combustion sources of PM, exposing the sensors' to different particle size distributions to quantify and better understand the low-cost sensors performance across a range of relevant environmental ranges. The PNCs reported by the sensors were analysed to characterise sensor-reported particle size distribution, to determine whether sensor-reported PNCs can follow the transient variations of PM observed by the reference instruments and to determine the relative impact of different variables on the performances of the sensors. This study shows that the Alphasense OPC-R1 reported at least five size ranges independently from each other, that the Sensirion SPS30 reported two size ranges independently from each other and that all the size ranges reported by the Plantower PMS5003 were not independent of each other. It demonstrates that all sensors tested here could track the fine temporal variation of PNCs, that the Alphasense OPC-R1 could closely follow the variations of size distribution between the two sources of PM, and it shows that particle size distribution and composition are more impactful on sensor measurements than relative humidity.

Short-term exposure to ultrafine particles and mortality and hospital admissions due to respiratory and cardiovascular diseases in Copenhagen, Denmark.

Ultrafine particles (UFP; particulate matter <0.1 µm in diameter) may be more harmful to human health than larger particles, but epidemiological evidence on their health effects is still limited. In this study, we examined the association between short-term exposure to UFP and mortality and hospital admissions in Copenhagen, Denmark. Daily concentrations of UFP (measured as particle number concentration in a size range 11-700 nm) and meteorological variables were monitored at an urban background station in central Copenhagen during 2002-2018. Daily counts of deaths from all non-accidental causes, as well as deaths and hospital admissions from cardiovascular and respiratory diseases were obtained from Danish registers. Mortality and hospital admissions associated with an interquartile range (IQR) increase in UFP exposure on a concurrent day and up to six preceding days prior to the death or admission were examined in a case-crossover study design. Odds ratios (OR) with 95% confidence intervals (CI) per one IQR increase in UFP were estimated after adjusting for temperature and relative humidity. We observed 140,079 deaths in total, 236,003 respiratory and 342,074 cardiovascular hospital admissions between 2002 and 2018. Hospital admissions due to respiratory and cardiovascular diseases were significantly positively associated with one IQR increase in UFP (OR: 1.04 [95% CI: 1.01, 1.07], lag 0-4, and 1.02 [1.00, 1.04], lag 0-1, respectively). Among the specific causes, the strongest associations were found for chronic obstructive pulmonary disease (COPD) mortality and asthma hospital admissions and two-day means (lag 0-1) of UFP (OR: 1.13 [1.01, 1.26] and 1.08 [1.00, 1.16], respectively, per one IQR increase in UFP). Based on 17 years of UFP monitoring data, we present novel findings showing that short-term exposure to UFP can trigger respiratory and cardiovascular diseases mortality and morbidity in Copenhagen, Denmark. The strongest associations with UFP were observed with COPD mortality and asthma hospital admissions.

Firework smoke: Impacts on urban air quality and deposition in the human respiratory system.

Particle number concentrations and size distributions resulting from the firework displays held in Budapest, Hungary every year on St. Stephen's Day were studied over a period of seven years. In the year most impacted, the total particle number concentration reached its peak measured level of 369 × 103 cm-3 5 min after the end of the display, and returned to the pre-event state within 45 min. The fireworks increased hourly mean concentrations by a factor of 5-6, whereas the concentrations in the diameter range of 100-1000 nm, in which the magnitude of the increase was the greatest, were elevated by a factor of 20-25. An extra particle size mode at 203 nm was manifested in the size distributions as result of the fireworks. The PM10 mass concentrations at peak firework influence and as 1-h mean increased 123 and 58 times, respectively, relative to the concentration before the display. The smoke was characterised by a relatively short overall atmospheric residence time of 25 min. Spatiotemporal dispersion simulations revealed that there were substantial vertical and horizontal concentration gradients in the firework plume. The affected area made up a large part of the city. Not only the spectators of the display at the venue and nearby areas, but the population located further away downwind of the displays and more distant, large and populous urban quarters were affected by the plume and its fallout. The fireworks increased the deposition rate in the respiratory system of females by a factor of 4, as a conservative estimate. The largest surface density deposition rates were seen in the segmental and sub-segmental bronchi, which represents an excessive risk to health. Compared to adults, children were more susceptible to exposure, with the maximum surface density deposition rates in their case being three times those of adults in the trachea.

Quantification of particle number concentration in liposomal suspensions by Laser Transmission Spectroscopy (LTS).

Laser Transmission Spectroscopy (LTS) is an experimental technique able to determine the particle number concentration and the size of colloidal suspensions by a single measurement of the transmittance of a laser beam through the suspension of particles as a function of the wavelength. In this protocol, we show that LTS represents a unique and powerful tool to investigate suspensions of liposomes, where the precise quantification of the number concentration is particularly relevant for the complete definition of the colloidal properties of the suspension. We study a model formulation of Soy-PC:Chol liposomes and we validate LTS results by comparison with High-Performance Liquid Chromatography determination of lipid mass. Then LTS protocols is applied to state-of-art liposomal nanocarrier suspensions. We explain details of data analysis to obtain the particle number concentration by using the Lambert-Beer law and by calculating the extinction cross section, within the framework of Mie theory for spherical vesicles. We also determine the liposome radius and compare it with the hydrodynamic radius measured by Dynamic Light Scattering. As future perspective, we aim to extend LTS analysis to other nanostructures with different geometries and to contribute to the development of new quantitative strategies for the accurate characterization of nanocarriers and other nanoparticles.

Relationship between traffic-related air pollution and inflammation biomarkers using structural equation modeling.

BACKGROUND: Evidence suggests that exposure to traffic-related air pollution (TRAP) and social stressors can increase inflammation. Given that there are many different markers of TRAP exposure, socio-economic status (SES), and inflammation, analytical approaches can leverage multiple markers to better elucidate associations. In this study, we applied structural equation modeling (SEM) to assess the association between a TRAP construct and a SES construct with an inflammation construct. METHODS: This analysis was conducted as part of the Community Assessment of Freeway Exposure and Health (CAFEH; N = 408) study. Air pollution was characterized using a spatiotemporal model of particle number concentration (PNC) combined with individual participant time-activity adjustment (TAA). TAA-PNC and proximity to highways were considered for a construct of TRAP exposure. Participant demographics on education and income for an SES construct were assessed via questionnaires. Blood samples were analyzed for high sensitivity C-reactive protein (hsCRP), interleukin-6 (IL-6), and tumor necrosis factor-α receptor II (TNFRII), which were considered for the construct for inflammation. We conducted SEM and compared our findings with those obtained using generalized linear models (GLM). RESULTS: Using GLM, TAA-PNC was associated with multiple inflammation biomarkers. An IQR (10,000 particles/cm3) increase of TAA-PNC was associated with a 14 % increase in hsCRP in the GLM. Using SEM, the association between the TRAP construct and the inflammation construct was twice as large as the associations with any individual inflammation biomarker. SES had an inverse association with inflammation in all models. Using SEM to estimate the indirect effects of SES on inflammation through the TRAP construct strengthened confidence in the association of TRAP with inflammation. CONCLUSION: Our TRAP construct resulted in stronger associations with a combined construct for inflammation than with individual biomarkers, reinforcing the value of statistical approaches that combine multiple, related exposures or outcomes. Our findings are consistent with inflammatory risk from TRAP exposure.

Utility of outdoor central site monitoring in assessing exposure of school children to ultrafine particles.

Epidemiological studies investigating the association between daily particle exposure and health effects are frequently based on a single monitoring site located in an urban background. Using a central site in epidemiological time-series studies has been established based on the premises of low spatial variability of particles within the areas of interest and hence the adequacy of the central sites to monitor the exposure. This is true to a large extent in relation to larger particles (PM2.5, PM10) that are typically monitored and regulated. However, the distribution of ultrafine particles (UFP), which in cities predominantly originate from traffic, is heterogeneous. With increasing pressure to improve the epidemiology of UFP, an important question to ask is, whether central site monitoring is representative of community exposure to this size fraction of particulate matter; addressing this question is the aim of this paper. To achieve this aim, we measured personal exposure to UFP, expressed as particle number concentration (PNC), using Philips Aerasense Nanotracers (NT) carried by the participants of the study, and condensation particle counters (CPC) or scanning mobility particle sizers (SMPS) at central fixed-site monitoring stations. The measurements were conducted at three locations in Brisbane (Australia), Cassino (Italy) and Accra (Ghana). We then used paired t-tests to compare the average personal and average fixed-site PNC measured over the same 24-h, and hourly, periods. We found that, at all three locations, the 24-h average fixed-site PNC was no different to the personal PNC, when averaged over the study period and all the participants. However, the corresponding hourly averages were significantly different at certain times of the day. These were generally times spent commuting and during cooking and eating at home. Our analysis of the data obtained in Brisbane, showed that maximum personal exposure occurred in the home microenvironment during morning breakfast and evening dinner time. The main source of PNC for personal exposure was from the home-microenvironment. We conclude that the 24-h average PNC from the central-site can be used to estimate the 24-h average personal exposure for a community. However, the hourly average PNC from the central site cannot consistently be used to estimate hourly average personal exposure, mainly because they are affected by very different sources.

The occurrence of lower-than-expected bulk NCCN values over the marginal seas of China - Implications for competitive activation of marine aerosols.

In this study, we combined the measured bulk particle number concentration (NCN), particle number size distribution (PNSD) and bulk cloud condensation nuclei concentration (NCCN) at various supersaturation (SS) levels to investigate competitive activation of aerosols in the marine atmospheres over the marginal seas of China during two winter campaigns Campaign A (December 9-19, 2019) and Campaign B (December 28, 2019-January 16, 2020). During the two campaigns, we observed various categories of aerosols, i.e., long-range transport continental aerosols, clean marine aerosols, grown new particles ranging from nucleation mode to larger sizes, and grown pre-existing particles ranging from Aitken mode to accumulation mode size, etc. We found that the measured NCCN increased by only approximately 30 % with increases in SS levels from 0.2 % to 1.0 %, e.g., (1.8 ± 1.4) × 103 cm-3 at SS = 0.2 % and (2.4 ± 1.4) × 103 cm-3 at SS = 1.0 % during Campaign A. We further calculated the hygroscopicity parameter kappa (κ) by combining simultaneously measured PNSD and bulk NCCN to explore the causes. The calculated κ values were below 0.1 at SS = 0.4 % during the 72 % (or 88 %) period of Campaign A (or Campaign B). When κ values below 0.1 (or 0.2) were excluded, the remaining κ values were apparently reasonable, with an average of 0.22 (or 0.36) and a standard deviation of 0.10 (or 0.21) at SS = 0.4 % during Campaign A (or Campaign B). The unexpectedly lower κ values were discussed in terms of competitive activation of aerosols in marine atmospheres together with its net contribution to lowering the measured bulk NCCN below the expected value.

Short-term effects of ultrafine particles on heart rate variability: A systematic review and meta-analysis.

An increasing number of epidemiological studies have examined the association between ultrafine particles (UFP) and imbalanced autonomic control of the heart, a potential mechanism linking particulate matter air pollution to cardiovascular disease. This study systematically reviews and meta-analyzes studies on short-term effects of UFP on autonomic function, as assessed by heart rate variability (HRV). We searched PubMed and Web of Science for articles published until June 30, 2022. We extracted quantitative measures of UFP effects on HRV with a maximum lag of 15 days from single-pollutant models. We assessed the risk of bias in the included studies regarding confounding, selection bias, exposure assessment, outcome measurement, missing data, and selective reporting. Random-effects models were applied to synthesize effect estimates on HRV of various time courses. Twelve studies with altogether 1,337 subjects were included in the meta-analysis. For an increase of 10,000 particles/cm3 in UFP assessed by central outdoor measurements, our meta-analysis showed immediate decreases in the standard deviation of the normal-to-normal intervals (SDNN) by 4.0% [95% confidence interval (CI): 7.1%, -0.9%] and root mean square of successive R-R interval differences (RMSSD) by 4.7% (95% CI: 9.1%, 0.0%) within 6 h after exposure. The immediate decreases in SDNN and RMSSD associated with UFP assessed by personal measurements were smaller and borderline significant. Elevated UFP were also associated with decreases in SDNN, low-frequency power, and the ratio of low-frequency to high-frequency power when pooling estimates of lags across hours to days. We did not find associations between HRV and concurrent-day UFP exposure (daily average of at least 18 h) or exposure at lags ≥ one day. Our study indicates that short-term exposure to ambient UFP is associated with decreased HRV, predominantly as an immediate response within hours. This finding highlights that UFP may contribute to the onset of cardiovascular events through autonomic dysregulation.

Understanding Sources and Drivers of Size-Resolved Aerosol in the High Arctic Islands of Svalbard Using a Receptor Model Coupled with Machine Learning.

Atmospheric aerosols are important drivers of Arctic climate change through aerosol-cloud-climate interactions. However, large uncertainties remain on the sources and processes controlling particle numbers in both fine and coarse modes. Here, we applied a receptor model and an explainable machine learning technique to understand the sources and drivers of particle numbers from 10 nm to 20 µm in Svalbard. Nucleation, biogenic, secondary, anthropogenic, mineral dust, sea salt and blowing snow aerosols and their major environmental drivers were identified. Our results show that the monthly variations in particles are highly size/source dependent and regulated by meteorology. Secondary and nucleation aerosols are the largest contributors to potential cloud condensation nuclei (CCN, particle number with a diameter larger than 40 nm as a proxy) in the Arctic. Nonlinear responses to temperature were found for biogenic, local dust particles and potential CCN, highlighting the importance of melting sea ice and snow. These results indicate that the aerosol factors will respond to rapid Arctic warming differently and in a nonlinear fashion.

Improving the current air quality index with new particulate indicators using a robust statistical approach.

To convey the severity of ambient air pollution level to the public, air quality index (AQI) is used as a communication tool to reflect the concentrations of individual pollutants on a common scale. However, due to the enhanced air pollution control in recent years, air quality has improved, and the roles of some air pollutant species included in the existing AQI as urban air pollutants have diminished. In this study, we suggest the current AQI should be revised in a way that new air pollution indicators would be considered so that it would better represent the health effects caused by local combustion processes from traffic and residential burning. Based on the air quality data of 2017-2019 in three different sites in Helsinki metropolitan area, we assumed the statistical distributions of the current indicators (NO2 and PM2.5) and the proposed particulate indicators (BC, LDSA and PNC) were related as they have similar sources in urban regions despite the varying correlations between the current and proposed indicators (NO2: r = 0.5-0.85, PM2.5: r = 0.28-0.72). By fitting the data to an optimal distribution function, together with expert opinions, we improved the current Finnish AQI and determined the AQI breakpoints for the proposed indicators where this robust statistical approach is transferrable to other cities. The addition of the three proposed indicators to the current AQI would decrease the number of good air quality hours in all three environments (largest decrease in urban traffic site, ~22 %). The deterioration of air quality class appeared more severe during peak hours in the urban traffic site due to vehicular emission and evenings in the detached housing site where domestic wood combustion often takes place. The introduction of the AQI breakpoints of the three new indicators serve as a first step of improving the current AQI before further air quality guideline levels are updated.

Maternal exposure to traffic-related ambient particles and risk of gestational diabetes mellitus with isolated fasting hyperglycaemia: A retrospective cohort study in Beijing, China.

BACKGROUND: Ambient particles have been associated with gestational diabetes mellitus (GDM), however, no study has evaluated the effects of traffic-related ambient particles on the risks of GDM subgroups classified by oral glucose tolerance test (OGTT) values. METHODS: A retrospective analysis was conducted among 24,001 pregnant women who underwent regular prenatal care and received OGTT at Haidian Maternal and Child Health Hospital in Beijing, China, 2014-2017. A total of 3,168 (13.2%) pregnant women were diagnosed with GDM, including 1,206 with isolated fasting hyperglycaemia (GDM-IFH). At a fixed-location monitoring station, routinely monitored ambient particles included fine particulate matter (PM2.5), black carbon (BC) and particles in size ranges of 5-560 nm (PNC5-560). Contributions of PNC5-560 sources were apportioned by positive matrix factorization model. Logistic regression model was applied to estimate odds ratio (OR) of ambient particles on GDM risk. RESULTS: Among the 24,001 pregnancy women recruited in this study, 3,168 (13.2%) were diagnosed with GDM, including 1,206 with isolated fasting hyperglycaemia (GDM-IFH) and 1,295 with isolated post-load hyperglycaemia (GDM-IPH). We observed increased GDM-IFH risk with per interquartile range increase in first-trimester exposures to PM2.5 (OR = 1.94; 95% Confidence Intervals: 1.23-3.07), BC (OR = 2.14; 1.73-2.66) and PNC5-560 (OR = 2.46; 1.90-3.19). PNC5-560 originated from diesel and gasoline vehicle emissions were found in associations with increases in GDM-IFH risk, but not in GDM-IPH risk. CONCLUSION: Our findings suggest that exposure to traffic-related ambient particles may increase GDM risk by exerting adverse effects on fasting glucose levels during pregnancy, and support continuing efforts to reduce traffic emissions for protecting vulnerable population who are at greater risk of glucose metabolism disorder.

Indoor air pollution effects on pediatric asthma are submicron aerosol particle-dependent.

The school environment is crucial for the child's health and well-being. On the other hand, the data about the role of school's aerosol pollution on the etiology of chronic non-communicable diseases remain scarce. This study aims to evaluate the level of indoor aerosol pollution in primary schools and its relation to the incidence of doctor's diagnosed asthma among younger school-age children. The cross-sectional study was carried out in 11 primary schools of Vilnius during 1 year of education from autumn 2017 to spring 2018. Particle number (PNC) and mass (PMC) concentrations in the size range of 0.3-10 µm were measured using an Optical Particle Sizer (OPS, TSI model 3330). The annual incidence of doctor's diagnosed asthma in each school was calculated retrospectively from the data of medical records. The total number of 6-11 years old children who participated in the study was 3638. The incidence of asthma per school ranged from 1.8 to 6.0%. Mean indoor air pollution based on measurements in classrooms during the lessons was calculated for each school. Levels of PNC and PMC in schools ranged between 33.0 and 168.0 particles/cm3 and 1.7-6.8 µg/m3, respectively. There was a statistically significant correlation between the incidence of asthma and PNC as well as asthma and PMC in the particle size range of 0.3-1 µm (r = 0.66, p = 0.028) and (r = 0.71, p = 0.017) respectively. No significant correlation was found between asthma incidence and indoor air pollution in the particle size range of 0.3-2.5 and 0.3-10 µm.   Conclusion: We concluded that the number and mass concentrations of indoor air aerosol pollution in primary schools in the particle size range of 0.3-1 µm are primarily associated with the incidence of doctor's diagnosed asthma among younger school-age children. What is Known: • Both indoor and outdoor aerosol pollution is associated with bronchial asthma in children. What is New: • The incidence of bronchial asthma among younger school age children is related to indoor air quality in primary schools. • Aerosol pollutants in the size range of 0.3-1 µm in contrast to larger size range particles can play major role in the etiology of bronchial asthma in children.

Variations in source contributions of particle number concentration under long-term emission control in winter of urban Beijing.

Many studies revealed the rapid decline of atmospheric PM2.5 in Beijing due to the emission control measures. The variation of particle number concentration (PN) which has important influences on regional climate and human health, however, was rarely reported. This study measured the particle number size distributions (PNSD) in 3-700 nm in winter of Beijing during 2013-2019. It was found that PN decreased by 58% from 2013 to 2017, but increased by 29% from 2017 to 2019. By Positive matrix factorization (PMF) analysis, five source factors of PNSD were identified as Nucleation, Fresh traffic, Aged traffic + Diesel, Coal + biomass burning and Secondary. Overall, factors associated with primary emissions were found to decrease continuously. Coal + biomass burning dominated the reduction (65%) among the three primary sources during 2013-2017, which resulted from the great efforts on emission control of coal combustion and biomass burning. Fresh traffic and Aged traffic + Diesel decreased by 43% and 66%, respectively, from 2013 to 2019, as a result of the upgrade of the vehicle emission standards in Beijing-Tianjin-Hebei area. On the other hand, the contribution from Nucleation and Secondary decreased with the reduction of gaseous precursors in 2013-2017, but due to the increased intensity of new particle formation (NPF) and secondary oxidation, they increased by 56% and 70%, respectively, from 2017 to 2019, which led to the simultaneously increase of PN and particle volume concentration. This study indicated that NPF may play an important role in urban atmosphere under continuous air quality improvement.