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The present work aimed to assess the ambient levels of air pollution with particulate matter for both mass concentrations and number of particles for various fractions in Ploiesti city during the lockdown period determined by the COVID-19 pandemic (March–June 2020). The PM10 continuously monitored data was retrieved from four air quality automatic stations that are connected to the Romanian National Network for Monitoring Air Quality and located in the city. Because no other information was available for other more dangerous fractions, we used monitoring campaigns employing the Lighthouse 3016 IAQ particle counter near the locations of monitoring stations assessing size-segregated mass fraction concentrations (PM0.5, PM1, PM2.5, PM5, PM10, and TPM) and particle number concentration (differential Δ) range between 0.3 and 10 microns during the specified timeline between 8.00 and 11.00 a.m., which were considered the morning rush hours interval. Interpolation maps estimating the spatial distribution of the mass concentrations of various PM fractions and particle number concentration were drawn using the IDW algorithm in ArcGIS 10.8.2. Regarding the particle count of 0.5 microns during the lockdown, the smallest number was recorded when the restriction of citizens’ movement was declared (24 March 2020), which was 5.8-times lower (17,301.3 particles/cm3) compared to a common day outside the lockdown period (100,047.3 particles/cm3). Similar results were observed for other particle sizes. Regarding the spatial distribution of the mass concentrations, the smaller fractions were higher in the middle of the city and west (PM0.5, PM1, and PM2.5) while the PM10 was more concentrated in the west. These are strongly related to traffic patterns. The analysis is useful to establish the impact of PM and the assessment of urban exposure and better air quality planning. Long-term exposure to PM in conjunction with other dangerous air pollutants in urban aerosols of Ploiesti can lead to potential adverse effects on the population, especially for residents located in the most impacted areas.

Cyclopentanone from lignocelluloses is a promising renewable biofuel and can be used as diesel alternative fuel. Cyclopentanone has excellent fuel properties and high intramolecular oxygen content, which has the potential in promoting combustion and reducing emissions. In this study, the effects of blending cyclopentanone with diesel on the combustion and emission of common rail diesel engine were investigated. The novelty of this study is to figure out which blending ratio is the most promising for diesel engine. Cyclopentanone is blended with diesel with 10% and 20% ratio by vol., noted as C10 and C20, respectively. Double injection strategy (pre-injection and main-injection) was adopted in this study. Compared with pure diesel, blending cyclopentanone can prolong the ignition delay, increase the peak heat release rate and increase the peak in-cylinder temperature. The emission tests indicate that blending cyclopentanone can effectively reduce the particle number concentrations (PNC) and particle volume concentrations (PVC) compared to diesel. Further, the number geometric mean diameters (NGMD) of cyclopentanone diesel blend fuels are lower than those of diesel and the reduction increases with cyclopentanone blending ratio. However, a little increase in NOx emission is observed. With the increase of EGR ratio, the NOx emissions of all test fuels decrease obviously, the PNCs and PVCs of diesel and C10 increase. PNCs and PVCs of C20 almost remain unchanged when the EGR ratio is no higher than 8%. Consequently, with 8% EGR ratio, C20 has the best effect in reducing both particle and NOx emissions and it has great potential for application on diesel vehicles.

Background Exposure to fine and ultrafine particles from transport processes is a main consequence of emissions from engines, especially those with self-ignition. The particles released in these processes are a source of occupational and environmental particles exposure. The aim of this study was to assess the fine and nano-sized particles emission degree during work connected with transport and vehicle servicing. Material and Methods The tests were carried out at 3 workplaces of vehicles service and maintenance (a car repair workshop, a truck service hall, and a bus depot) during 1 work day in each of them. Measurements were performed using the following devices: DISCmini meters, GRIMM 1.109 optical counter and the DustTrak monitor. The number, surface area and mass concentration, and the number size distribution were analyzed. Results The mean number concentration (DISCmini) increased during the analyzed processes, ranging from 4×104 p/cm 3 to 8×104 p/cm 3 , and the highest concentration was found in the car repair workshop. The particles mean diameters during the processes ranged 31–47 nm, depending on the process. An increase in the surface area concentration value was observed in correlation with the particles number, and its highest concentration (198 m 2 /cm 3 ) was found during work in the car repair workshop. The number size distribution analysis (GRIMM 1.109) showed the maximum value of the number concentration for particles sized 60 nm. The mean mass concentrations increased during the tested processes by approx. 40–70%, as compared to the background. Conclusions According to the measurement results, all the workplaces under study constituted a source of an increase in all analyzed parameters characterizing emissions of nano-sized particles. Such working environment conditions can be harmful to the exposed workers; therefore, at such workplaces solutions for minimizing workers’ exposure, such as fume hoods or respiratory protection, should be used. Med Pr. 2021;72(5):489–500

A series of student-led research activities were performed using a cargo bicycle equipped with air chemistry instrumentation to study the dynamics of aerosol particles in urban air before, during, and after the COVID-19 lockdown periods. The studies examined a high-traffic route and a low-traffic route around the city center of Münster, Germany. A complex picture emerged for how the particle number concentrations (PN) and particle mass concentrations (PM, specifically PM10) were affected by the day of the week, the route selected, the meteorological conditions, and the traffic intensity. Traffic had the most impact on PN through the multitude of exhaust plumes from motorized vehicles. The impact of traffic on PM10 was rather low, which is also mirrored in the general pattern of the low response of PM10 to the pandemic lockdown in Germany. Instead, PM10 responded more to the day of the week. Presumably, PM10 responds either to a specific traffic component, such as commercial low-duty vehicles, or to other business, such as construction activity. Meteorological conditions exert their impact mostly through the relative humidity, which affects particle growth. As such, future research could examine PN and PM10 responses over all seasons of the year. In any case, this student-led study in which high-resolution data were acquired deepened our understanding and broadened our view on particle dynamics in urban air. Well-trained university graduates will contribute to meeting further challenges in studying and combatting air pollution.

Airports contribute substantially to ultrafine particle (UFP

Particle matter is one of the criteria air pollutants which have the most considerable effect on human health in cities. Its legislation and regulation are mostly based on mass. We showed here that the total number of particles and the particle number concentrations in different size fractions seem to be efficient quantities for air quality monitoring in urbanized areas. Particle number concentration (N) measurements were realized in Budapest, Hungary, for nine full measurements years between 2008 and 2021. The datasets were complemented by meteorological data and concentrations of criteria air pollutants. The annual medians of N were approximately 9 × 103 cm−3. Their time trends and diurnal variations were similar to other large continental European cities. The main sources of N are vehicle road traffic and atmospheric new aerosol particle formation (NPF) and consecutive growth events. The latter process is usually regional, so it appears to be better assessible for contribution quantification than mass concentration. It is demonstrated that the relative occurrence frequency of NPF was considerable, and its annual mean was around 20%. NPF events increased the contribution of ultrafine (UF < 100 nm) particles with respect to the regional particle numbers by 12% and 37% in the city center and in the near-city background, respectively. The pre-existing UF concentrations were doubled on the NPF event days.

In this study, isopropanol and n-pentanol are blended in diesel with 20% ratio by volume, named D80IP20 and D80NP20. Their combustion and emission performances were compared with diesel on a four cylinder common rail diesel engine under pilot plus main injection strategy. The pilot injection duration decreases and the main injection duration increases with engine loads. For test fuels, the starts of pilot and main injection and the durations of pilot injection are remained unchanged in each engine operation. D80IP20 has the longest ignition delay due to the lowest cetane number and the shortest combustion duration due to the highest fuel oxygen. However, the peak combustion temperature of D80IP20 is lower than that of D80NP20 under double injection strategy. Compared to diesel, both D80IP20 and D80NP20 obviously reduce the particle number concentrations (PNCs) and the particle volume concentrations (PVCs), while increase the NOx emissions. D80IP20 has the lowest PNCs and PVCs and its number geometric mean diameter (NGMD) and volume geometric mean diameter (VGMD) are the lowest among the three fuels. D80IP20 has higher NOx emission than diesel, but lower than D80NP20 due to lower PCT. Further, D80IP20 with 10% EGR can achieve the simultaneous reduction for NOx emission and PNCs at low and high loads compared to diesel without EGR. Results indicate that blending isopropanol in diesel has better effects in combustion improvement and emission control and is more suitable than n-pentanol under pilot plus main injection strategy.

During April and May 2019 Salzburg Airport was closed for five weeks for runway renovation. As a result, landings and take-offs (LTOs) were impossible during this period. This offered a rare opportunity to carry out a field study to investigate the concentration of ultrafine particles prior to, during and after completion of the renovation work. During the construction phase, the sharp particle concentration peaks resulting from LTOs during normal operation were no longer encountered at the measurement site, 140 m from the runway. Towards the end of the airport closure, construction activity was all but completed and LTO activity was strictly limited to test purposes, which resulted in average ultrafine-particle concentrations of approximately 3,000 to 4,000 cm-3 (06-23 h average value). The reconstruction work itself and the high numbers of construction vehicles caused an increase in ultrafine-particle concentrations of an additional 1,000 to 2,000 cm-3 (06-23 h average value). In comparison, in the three weeks before and the three weeks after the closure, when airport operations were running as normal, concentrations increased by 3,000 to 4,000 cm-3 (06-23 h average value).

10 pages, 3 figures, 1 table, supporting information https://doi.org/10.1021/acs.est.1c07796, 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, This research was supported by the Natural Environment Research Council (grant no. NE/S00579X/1) and endorsed by the Surface Ocean-Lower Atmosphere Study (SOLAS), With the institutional support of the ‘Severo Ochoa Centre of Excellence’ accreditation (CEX2019-000928-S)

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.

Cooking food in water or soup, such as hot pot, is a widely used cooking method in China. This type of cooking requires no oil and cooks at a lower temperature, but that does not mean it produces fewer pollutants or is less harmful. There are few research studies on the emission characteristics and mechanisms of particulate matter emissions when eating hot pot (the boiling process), which leads to the unreasonable design of ventilation systems for this kind of catering. In this paper, the effects of boiling different ingredients (including noodles, potatoes, fish, tofu, meatballs, and pork) on particle number concentration emissions were studied. The particle number concentration and particle size distribution of PM with diameters of 0.3 μm and less, 0.3–0.5 μm and 0.5–1.0 μm (PM0.3, PM0.3–0.5 and PM0.5–1.0, respectively) were measured in an experimental chamber. The food type and shape showed very little change in the PM emission characteristics of boiling. When the boiling state was reached, the number concentration, particle size distribution, and arithmetic mean diameter of particles all fluctuated within 60 s. The emission characteristics of particles produced by boiling water and heating oil were compared. Heating oil produced more small particles, and boiling water released more large particles. Transient and steady methods were used to calculate the emission rate of particles, and the steady-state calculation has a high estimation of the emission rate.

A correlation between the mass concentration of particulate matter (PM) and the occurrence of health-related problems or diseases has been confirmed by several studies. However, little is known about indoor PM concentrations, their associated risks or their impact on health. In this work, the PM1, PM2.5 and PM10 produced by different indoor aerosol sources (candles, cooking, electronic cigarettes, tobacco cigarettes, mosquito coils and incense) are studied. The purpose is to quantify the emission characteristics of different indoor particle sources. The mass concentration, the numerical concentration, and the size distribution of PM from various sources were determined in an examination room 65 m3 in volume. Sub-micrometer particles and approximations of PM1, PM2.5 and PM10 concentrations were measured simultaneously using a diffusion aerosol spectrometer (DAS). The ultrafine particle concentration for the studied indoor aerosol sources was approximately 7 × 104 particles/cm3 (incense, mosquito coils and electronic cigarettes), 1.2 × 105 particles/cm3 for candles and cooking and 2.7 × 105 particles/cm3 for tobacco cigarettes. The results indicate that electronic cigarettes can raise indoor PM2.5 levels more than 100 times. PM1 concentrations can be nearly 55 and 30 times higher than the background level during electronic cigarette usage and tobacco cigarette burning, respectively. It is necessary to study the evaluation of indoor PM, assess the toxic potential of internal molecules and develop and test strategies to ensure the improvement of indoor air quality.

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.

Subway particulate toxicity results from in vitro and in vivo studies diverge and call for applied human research on outcomes from chronic exposures and potential exposure biomarkers. We aimed to (1) quantify airborne particulate matter (PM) concentrations (mass and number) and metal concentrations in exhaled breath condensate (EBC), urine, and PM; (2) investigate their associations (EBC vs. PM vs. urine); and (3) assess the relevance of EBC in biomonitoring. Nine subway workers in three jobs: station agents, locomotive operators and security guards were monitored during their 6-h shifts over two consecutive weeks. Six-hour weighed average mass concentrations expressed as PM10, PM2.5 and their metal concentrations were determined. Urine and EBC samples were collected pre- and post-shift. Ultrafine particle (UFP) number concentrations were quantified in PM and EBC samples. Metal concentrations in urine and EBC were standardized by creatinine and EBC volume, respectively, and log-transformed. Associations were investigated using Pearson correlation and linear mixed regression models, with participant's ID as random effect. PM concentrations were below occupational exposure limits (OEL) and varied significantly between jobs. Locomotive operators had the highest exposure (189 and 137 μg/m 3 for PM10 and PM2.5, respectively), while station agents had the highest UFP exposure (1.97 × 10 4 particles/cm 3 ). Five metals (Al, Fe, Zn, Cu, and Mn) in PM2.5 and three (Al, Fe, and Zn) in PM10 were above the limit of quantification (LOQ). Fe, Cu, Al and Zn were the most abundant by mass fraction in PM. In EBC, the metal concentrations in decreasing order were: Zn > Cu > Ni > Ba > Mn. Security guards had the highest EBC metal concentrations, and in particular Zn and Cu. Urinary metal concentrations in decreasing order were: Si > Zn > Mo > Ti > Cu > Ba ≈ Ni > Co. All urinary metal concentrations from the subway workers were similar to concentrations found in the general population. A statistically significant relationship was found for ultrafine particle number concentrations in PM and in EBC. Zn and Cu concentrations in post-shift EBC were associated with Zn and Cu concentrations in PM10 and with post-shift urinary Zn and Cu concentrations. Therefore, EBC appears a relevant matrix for assessing exposure to UFP in human biomonitoring when inhalation is a primary route of exposure. We found different temporal variation patterns between particle and metal exposures in three matrices (PM, urine, EBC) quantified daily over two full weeks in subway workers. These patterns might be related to metal oxidation, particulates' solubility and size as well as their lung absorption capabilities, which need to be further explored in toxicological research. Further research should also focus on understanding possible influences of low chronic exposures to subway particulates on health in larger cohorts.

Factor analysis models use the covariance of measured variables to identify and apportion sources. These models, particularly positive matrix factorization (PMF), have been extensively used for analyzing particle number concentrations (PNCs) datasets. However, the variation of observed PNCs and particle size distribution are driven by both the source emission rates and atmospheric dispersion as well as chemical and physical transformation processes. This variation in the observation data caused by meteorologically induced dilution reduces the ability to obtain accurate source apportionment results. To reduce the influence of dilution on quantitative source estimates, a methodology for improving the accuracy of source apportionment results by incorporating a measure of dispersion, the ventilation coefficient, into the PMF analysis (called dispersion normalized PMF, DN-PMF) was applied to a PNC dataset measured from a field campaign that includes the Spring Festival event and the start of the COVID-19 lockdown in Tianjin, China. The data also included gaseous pollutants and hourly PM2.5 compositional data. Eight factors were resolved and interpreted as municipal incinerator, traffic nucleation, secondary inorganic aerosol (SIA), traffic emissions, photonucleation, coal combustion, residential heating and festival emissions. The DN-PMF enhanced the diel patterns of photonucleation and the two traffic factors by enlarging the differences between daytime peak values and nighttime concentrations. The municipal incinerator plant, traffic emissions, and coal combustion have cleaner and more clearly defined directionalities after dispersion normalization. Thus, dispersion normalized PMF is capable of enhancing the source emission patterns. After the COVID-19 lockdown began, PNC of traffic nucleation and traffic emissions decreased by 41% and 44%, respectively, while photonucleation produced more particles likely due to the reduction in the condensation sink. The significant changes in source emissions indicate a substantially reduced traffic volume after the implement of lockdown measures., Graphical abstract Unlabelled Image, Highlights • A dispersion normalized PMF was applied to PNCs dataset. • DN-PMF enhanced the diel emission pattern and directionality of sources. • Traffic emissions decreased by more than 40% after the COVID-19 outbreak.

A correlation between the mass concentration of particulate matter (PM) and the occurrence of health-related problems or diseases has been confirmed by several studies. However, little is known about indoor PM concentrations, their associated risks or their impact on health. In this work, the PM1, PM2.5 and PM10 produced by different indoor aerosol sources (candles, cooking, electronic cigarettes, tobacco cigarettes, mosquito coils and incense) are studied. The purpose is to quantify the emission characteristics of different indoor particle sources. The mass concentration, the numerical concentration, and the size distribution of PM from various sources were determined in an examination room 65 m3 in volume. Sub-micrometer particles and approximations of PM1, PM2.5 and PM10 concentrations were measured simultaneously using a diffusion aerosol spectrometer (DAS). The ultrafine particle concentration for the studied indoor aerosol sources was approximately 7 × 104 particles/cm3 (incense, mosquito coils and electronic cigarettes), 1.2 × 105 particles/cm3 for candles and cooking and 2.7 × 105 particles/cm3 for tobacco cigarettes. The results indicate that electronic cigarettes can raise indoor PM2.5 levels more than 100 times. PM1 concentrations can be nearly 55 and 30 times higher than the background level during electronic cigarette usage and tobacco cigarette burning, respectively. It is necessary to study the evaluation of indoor PM, assess the toxic potential of internal molecules and develop and test strategies to ensure the improvement of indoor air quality. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.

MHSc (Occupational Hygiene), North-West University, Potchefstroom Campus Background: AM (Additive Manufacturing) is a process that produces three-dimensional (3D) parts via the layering of materials. To date, there has been little research on the health risks associated with the use of this technology to produce sand moulds for metal casting. Apart from the processing steps involving the AM machine, binder jetting (BJ) of sand moulds includes an additional step which involves the coating of virgin (new) silica sand with sulphonic acid prior to the AM processes. As yet, there is also no information available on the risks concerning the coating process. Both coating and AM processes involve the handling of silica sand, which may result in personal exposure to respirable crystalline silica and particulate matter. Also, furan resin binders used during processing may cause emission of volatile organic compounds (VOCs). Objectives: This study was aimed at determining emissions of and personal respiratory exposure to hazardous chemical substances (respirable crystalline silica, VOCs and respirable particulate matter) during various phases of AM with silica sand as well as during the coating of silica sand prior to AM. Methodology: Analysis of bulk silica sand was performed through the characterisation of particle size and shape using Malvern Morphologi particle analyser and scanning electron microscopy (SEM) while the X-ray diffraction (XRD) process was utilised to determine elemental composition. The Aerosol Particle Counter (APC) and Condensation Particle Counter (CPC) were used to quantify emissions of 0.3 - 10 μm (APC) and 0.01 - ~ 1.0 μm (CPC) sized particles during the coating process as well as pre-processing, processing and post-processing phases. Both personal and area monitoring were performed to measure airborne concentrations of respirable crystalline silica, VOCs and respirable particulate matter during the operator’s shift. Three days were allocated to monitor emissions, personal exposure and area concentrations during coating, while monitoring of the AM process was conducted over a period of five days, where three identical parts were printed. Results: Respirable sized particles were found in all three sand types (virgin, coated and used), with virgin sand having the highest respirable content compared to other sands; d(0.9) = 3.98 ± 0.72 μm vs d(0.9) = 115.00 ± 95.15 μm and d(0.9) = 6.51 ± 2.71 μm, respectively. The quartz content for the three sand types ranged from 92.6 to 97.6%, which made it the dominant mineral. The coating and AM machines were confirmed to emit particles 0.3 μm, 0.5 μm, 1 μm and 0.01 - ~ 1.0 μm. in size. Particulate emissions data indicated that the particle emissions for particles 0.3 μm, 0.5 μm and 1 μm and 0.01 - ~ 1.0 μm in size, increased considerably during the cleaning of the coating machine filter as well as during the opening of the bay door. The particle number concentrations of 0.3 μm, 0.5 μm, 1 μm and 0.01 - ~ 1.0 μm sized particles were higher during the third day of printing compared to the other days, as a result of increased particle number concentrations during post-processing and pre-processing. When comparing the phases, the average particle number concentration was significantly higher during pre-processing compared to other phases. There were no significant differences in emission rates (ERs) but the average ERs for particles 0.3 μm and 0.01 - ~ 1.0 μm in size were slightly higher during pre-processing followed by post-processing and then processing. Personal exposure to respirable crystalline silica during cleaning of the coating machine with compressed air exceeded the South African time weighted average occupational exposure limit-control limit (TWA OEL-CL) of 0.1 mg/m3 (0.112 mg/m³). During cleaning of the AM machine, personal exposure to respirable crystalline silica surpassed the action level (0.07 mg/m3). The personal exposures to HCS (respirable crystalline silica, respirable dust and VOCs) measured during the AM processes were below 10% of their respective OELs. Conclusion: The feedstock material used (silica sand) was regarded as a primary source of exposure. The amount of respirable sized particles found in the silica sand coupled with quartz content of > 90%, made the feedstock material a risk to the health of the AM operator. Both the cleaning methods used during coating and printing led to increased personal exposure to respirable crystalline silica. The AM operator was overexposed to respirable crystalline due to the use of compressed air to clean the filter, and was exposed to respirable crystalline silica exceeding the action level due to the use of a broom when cleaning the AM machine room. The cleaning methods were therefore classified as tasks with the highest risks. Particulate emissions were higher during pre-processing compared to other processes and is of concern since emissions of particles 0.3 μm, 0.5 μm, 1 μm and 0.01 - ~ 1.0 μm in size are a risk to the health of the AM operator as they may deposit in the alveoli, resulting in respiratory dysfunctions. In an attempt to minimise exposure to HCSs during the AM of sand moulds, 18 recommendations were made to the AM facility. Due to overexposure caused by cleaning activities using compressed air, the key recommendation made was for the AM operator to clean the filters in an isolated glove box in order to reduce exposure to respirable crystalline silica, a confirmed human carcinogen. Masters

Graphene is a one-atom-thick sheet of carbon atoms arranged in a honeycomb pattern and its unique and amazing properties make it suitable for a wide range of applications ranging from electronic devices to food packaging. However, the biocompatibility of graphene is dependent on the complex interplay of its several physical and chemical properties. The main aim of the present study is to highlight the importance of integrating different characterization techniques to describe the potential release of airborne graphene flakes in a graphene processing and production research laboratory. Specifically, the production and processing (i.e., drying) of few-layer graphene (FLG) through liquid-phase exfoliation of graphite are analysed by integrated characterization techniques. For this purpose, the exposure measurement strategy was based on the multi-metric tiered approach proposed by the Organization for Economic Cooperation and Development (OECD) via integrating high-frequency real-time measurements and personal sampling. Particle number concentration, average diameter and lung deposition surface area time series acquired in the worker's personal breathing zone (PBZ) were compared simultaneously to background measurements, showing the potential release of FLG. Then, electron microscopy techniques and Raman spectroscopy were applied to characterize particles collected by personal inertial impactors to investigate the morphology, chemical composition and crystal structure of rare airborne graphene flakes. The gathered information provides a valuable basis for improving risk management strategies in research and industrial laboratories.

This study concerns the levels of particulate matter (PM2.5 and PM1) released by residential stoves inside the home during &lsquo, real world&rsquo, use. Focusing on stoves that were certified by the UK&rsquo, s Department of Environment, Food, and Rural Affairs (DEFRA), PM sensors were placed in the vicinity of 20 different stoves over four weeks, recording 260 uses. The participants completed a research diary in order to provide information on time lit, amount and type of fuel used, and duration of use, among other details. Multivariate statistical tools were used in order to analyse indoor PM concentrations, averages, intensities, and their relationship to aspects of stove management. The study has four core findings. First, the daily average indoor PM concentrations when a stove was used were higher for PM2.5 by 66.24% and PM1 by 69.49% than those of the non-use control group. Second, hourly peak averages are higher for PM2.5 by 55.34% and for PM1 by 57.09% than daily averages, showing that PM is &lsquo, flooding&rsquo, into indoor areas through normal use. Third, the peaks that are derived from these &rsquo, incidents are associated with the number of fuel pieces used and length of the burn period. This points to the opening of the stove door as a primary mechanism for introducing PM into the home. Finally, it demonstrates that the indoor air pollution being witnessed is not originating from outside the home. Taken together, the study demonstrates that people inside homes with a residential stove are at risk of exposure to high intensities of PM2.5 and PM1 within a short period of time through normal use. It is recommended that this risk be reflected in the testing and regulation of residential stoves.

Urbanisation and industrialisation led to the increase of ambient particulate matter (PM) concentration. While subsequent regulations may have resulted in the decrease of some PM matrices, the simultaneous changes in climate affecting local meteorological conditions could also have played a role. To gain an insight into this complex matter, this study investigated the long-term trends of two important matrices, the particle mass (PM2.5) and particle number concentrations (PNC), and the factors that influenced the trends. Mann-Kendall test, Sen's slope estimator, the generalised additive model, seasonal decomposition of time series by LOESS (locally estimated scatterplot smoothing) and the Buishand range test were applied. Both PM2.5 and PNC showed significant negative monotonic trends (0.03-0.6 mg m(-3).yr(-1) and 0.40-3.8 x 10(3) particles. cm(-3). yr(-1), respectively) except Brisbane (+0.1 mg m(-3). yr(-1) and +53 particles. cm(-3). yr(-1), respectively). For the period covered in this study, temperature increased (0.03-0.07 degrees C.yr(-1)) in all cities except London; precipitation decreased (0.02-1.4 mm.yr(-1)) except in Helsinki; and wind speed was reduced in Brisbane and Rochester but increased in Helsinki, London and Augsburg. At the change-points, temperature increase in cold cities influenced PNC while shifts in precipitation and wind speed affected PM2.5. Based on the LOESS trend, extreme events such as dust storms and wildfires resulting from changing climates caused a positive step-change in concentrations, particularly for PM2.5. In contrast, among the mitigation measures, controlling sulphur in fuels caused a negative step-change, especially for PNC. Policies regarding traffic and fleet management (e.g. low emission zones) that were implemented only in certain areas or in a progressive uptake (e.g. Euro emission standards), resulted to gradual reductions in concentrations. Therefore, as this study has clearly shown that PM2.5 and PNC were influenced differently by the impacts of the changing climate and by the mitigation measures, both metrics must be considered in urban air quality management. (C) 2020 Elsevier Ltd. All rights reserved.

A monoethanolamine (MEA) aerosol growth model was developed to quantify the aerosol growth factor in an amine-based CO2 capture absorber that considers the gas-liquid interactions, and it is empirically validated by measuring the aerosol particle size and concentration. The aerosol growth model, using sucrose as the aerosol nuclei instead of sulfuric acid to prevent the corrosion of the test equipment, accurately predicted that the outlet aerosol size increased to the same level regardless of the sucrose concentration. It also found that particle concentration was the primary factor affecting aerosol growth and amine emissions. We found an inverse relationship between aerosol particle concentration and the aerosol size, while the MEA emissions were proportional to particle concentration.

Cyclists' exposure to air pollutants near roadways has been associated with numerous health effects. While the adverse health effects concerning aerosols have traditionally been assessed with data of particle mass concentrations, it appears that the number concentration is also another important indicator of toxicity. Thus, to holistically evaluate one?s exposure to aerosol particles, assessments should be based on mass concentrations and number concentrations. In order to assess individual cyclists' exposure as they move through space and time, spatiotemporal high-resolution approaches are needed. Therefore, a mobile, fast-response monitoring platform was developed that uses a cargo bicycle as a base. Data of particle mass concentrations (PM1, PM2.5, PM10) and particle number concentrations (PN10) were collected along two different routes, one characterized by high-intensity vehicle traffic and one by low-intensity vehicle traffic. While high spatiotemporal heterogeneity was observed for all measured quantities, the PN10 concentrations fluctuated the most. High concentrations of PN10 could be clearly associated with vehicle traffic. For PM2.5, this relation was less pronounced. Mean particle concentrations of all measures were significantly higher along the high-traffic route. Comparing route exposures, the inhalation of PM2.5 was similar between both routes, whereas along the high-traffic route, cyclists were exposed to twice the particle number. We conclude that the cargo bike, featuring high-frequency mobile measurements, was useful to characterize the spatial distribution of mass concentrations and number concentrations across an urban environment. Overall, our results suggest that the choice of route is a key factor in reducing cyclists' exposure to air pollution. Fil: Carreras, Hebe Alejandra. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto Multidisciplinario de Biología Vegetal. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas Físicas y Naturales. Instituto Multidisciplinario de Biología Vegetal; Argentina Fil: Ehrnsperger, Laura. University Of Münster; Alemania Fil: Klemm, Otto. University Of Münster; Alemania Fil: Paas, Bastian. University Of Münster; Alemania

Sub-micron aerosols are a vital air pollutant to be measured because they pose health effects. These particles are quantified as particle number concentration (PN). However, PN measurements are not always available in air quality measurement stations, leading to data scarcity. In order to compensate this, PN modeling needs to be developed. This paper presents a PN modeling framework using sensitivity analysis tested on a one year aerosol measurement campaign conducted in Amman, Jordan. The method prepares a set of different combinations of all measured meteorological parameters to be descriptors of PN concentration. In this case, we resort to artificial neural networks in the forms of a feed-forward neural network (FFNN) and a time-delay neural network (TDNN) as modeling tools, and then, we attempt to find the best descriptors using all these combinations as model inputs. The best modeling tools are FFNN for daily averaged data (with R 2 = 0.77 ) and TDNN for hourly averaged data (with R 2 = 0.66 ) where the best combinations of meteorological parameters are found to be temperature, relative humidity, pressure, and wind speed. As the models follow the patterns of diurnal cycles well, the results are considered to be satisfactory. When PN measurements are not directly available or there are massive missing PN concentration data, PN models can be used to estimate PN concentration using available measured meteorological parameters.

One of the most important functions of air conditioning systems in operating rooms is to protect occupants against pathogenic agents transported by air. This protection is done by simultaneously controlling the air distribution, temperature, humidity, filtration and infiltration from other areas etc. Due to their low price, simple installation, operation and maintenance, window/wall air conditioning system have largely been used in operating rooms in Brazil, even if these types of equipment only recirculate the air inside the room without appropriate filtration and renovation with outdoor air. In this context, this work aims to analyse the performance of the window/wall air conditioning systems on indoor air ventilation in operating rooms by measuring particle number concentrations and carbon dioxide concentrations during different surgical procedures, in a single surgical room and in the nearby areas (corridor) for two cases: single surgery and two subsequent surgeries. In addition, the efficiency of the analysed air conditioning system was evaluated by comparing the ventilation level calculated in the surgical room with the ventilation required in order to maintain the carbon dioxide concentration within acceptable levels. The results showed that this type of air conditioning system is not appropriate for use in operating rooms since it cannot provide an adequate level of ventilation. The CO2 concentrations during surgeries, in fact, significantly exceeded acceptable values and a simultaneous increase in particle number concentration was observed. The results also showed that there is a high risk of contamination between subsequent surgeries in the same surgical room, due to residues of contaminants transported by the particles emitted during the surgeries that were not removed from the operating room by the air conditioning system. The particle number concentration measured in the second surgery, in fact, was approximately six times higher than in the first surgery.

Exposure models are needed to evaluate health effects of long-term exposure to ambient ultrafine particles (UFP

Indoor school gyms are environments characterized by high concentrations of different airborne particulate and gaseous pollutants. In particular, like other naturally-ventilated school environments, in addition to indoor pollutants children can be exposed to sub-micron particles and gaseous pollutants emitted by outdoor sources and penetrating the building envelope; moreover, high concentrations of super-micron particles can be reached due to the resuspension phenomena related to the physical activity performed therein. The present paper aims to evaluate the effect of different ventilation methods (natural ventilation, manual airing) and the use of air purifiers in reducing the indoor concentrations of different airborne particles and gaseous pollutants in school gyms. To this end, an experimental campaign was performed in two naturally-ventilated school gyms in Barcelona (Spain) of different volumes and different distance to major urban roads. Indoor and outdoor measurements of particle number, black carbon and PM1–10 concentrations were performed as well as indoor measurements of CO2 and NO2 concentrations. The study revealed that the use of air purifiers with windows kept closed (natural ventilation) can lead to a significant reduction in terms of indoor-to-outdoor concentration ratios. In the smaller gym (air changes per hour of the purifiers, ACH, equal to 9.2 h−1) the I/O ratios were reduced by 93% and 95% in terms of particle number and PM1–10, respectively; whereas in the larger school gym (ACH = 1.7 h−1) the corresponding reductions were 70% and 84%. For manual airing scenarios, the effect of the air purifiers on outdoor-generated sub-micron particles is reduced; in particular, for low ACH values (i.e. ACH = 1.7 h−1), the reduction is quite negligible (6%).

The prediction of the particle number concentration and liquid/ice water content of cloud is significant for many aspects of atmospheric science. However, given the uncertainties in the initial and boundary conditions and imperfections of microphysical schemes, the accurate prediction of these microphysical properties of cloud is still a big challenge. The ensemble approach may be a viable way to reduce forecast uncertainties. In this paper, a large-scale stratiform cloud precipitation process is studied by comparing results of a 10-member ensemble forecast model with aircraft observation data. By means of the ensemble average, the prediction of bulk parameters such as liquid water content and ice water content can be improved in comparison with the control member, but the particle number concentrations are still one to two orders of magnitude less than those from observations. Intercomparison of raindrop size spectra reveals a big distinction between observations and predictions for particles with a diameter less than 1000 μm.

Worldwide around 7 million annual deaths are due to air pollution. Among all pollutants, Ultrafine Particles (UFP) cause strong adverse effects. In this paper, the dispersion of UFP is studied in the wake of car models characterized by different rear slant angles (?). Velocities and UFP concentrations are collected in a wind tunnel. The influence of the flow topology on the dispersion of these UFP is discussed. The results indicate that its structure strongly influences their dispersion. Whatever the rear slant angle is, the size of the recirculation region is a key parameter governing the dispersion of these UFP. For ? ?= ?0°, the flow is almost symmetric and concentration levels are higher and homogeneous in the close wake. The recirculation region is the largest one. The dispersion is enhanced in both horizontal and spanwise directions. For ? ?= ?25°, the flow is attached on the rear slant leading to a strong downwash effect. The volume of the recirculation region is the smallest. Longitudinal vortices develop from the edges of car model entrapping particles. Particle Number Concentration field is no more symmetric. For ? ?= ?35°, results are almost similar to those obtained for ? ?= ?0°. Comparisons with previous studies are discussed and possible applications are suggested.; Dans le monde, environ 7 millions de décès annuels sont dus à la pollution de l'air. Parmi tous les polluants, les particules ultrafines (UFP) provoquent des effets négatifs importants. Dans cet article, la dispersion de l'UFP est étudiée dans le sillage des modèles de voitures caractérisé par différents angles d'inclinaison arrière. Les vitesses et les concentrations d'UFP sont recueillies dans une soufflerie. L'influence de la topologie de l'écoulement sur la dispersion de ces UFP est discutée. Les résultats indiquent que son La structure influence fortement leur dispersion. Quel que soit l'angle d'inclinaison arrière, la taille de la zone de recirculation est un paramètre clé régissant la dispersion de ces UFP. Pour ? ? 0_, le flux est presque symétrique et la concentration sont plus élevés et homogènes dans le sillage proche. La région de recirculation est la plus grande. Le site La dispersion est améliorée à la fois dans le sens horizontal et dans le sens de l'envergure. Pour ? ? 25_, le flux est attaché à l'arrière ce qui entraîne un fort effet d'entraînement. Le volume de la zone de recirculation est le plus petit. Longitudinal Les tourbillons se développent à partir des bords des modèles de voitures en emprisonnant des particules. Le champ de concentration du nombre de particules n'est plus symétrique. Pour ? ? 35_, les résultats sont presque similaires à ceux obtenus pour ? ? 0_. Comparaisons avec les études précédentes sont discutées et des applications possibles sont suggérées.

Marine traffic in harbors can be responsible for significant atmospheric concentrations of ultrafine particles (UFPs), which have widely recognized negative effects on human health. It is therefore essential to model and measure the time evolution of the number size distributions and chemical composition of UFPs in ship exhaust to assess the resulting exposure in the vicinity of shipping routes. In this study, a sequential modelling chain was developed and applied, in combination with the data measured and collected in major harbor areas in the cities of Helsinki and Turku in Finland, during winter and summer in 2010&ndash, 2011. The models described ship emissions, atmospheric dispersion, and aerosol dynamics, complemented with a time&ndash, microenvironment&ndash, activity model to estimate the short-term UFP exposure. We estimated the dilution ratio during the initial fast expansion of the exhaust plume to be approximately equal to eight. This dispersion regime resulted in a fully formed nucleation mode (denoted as Nuc2). Different selected modelling assumptions about the chemical composition of Nuc2 did not have an effect on the formation of nucleation mode particles. Aerosol model simulations of the dispersing ship plume also revealed a partially formed nucleation mode (Nuc1, peaking at 1.5 nm), consisting of freshly nucleated sulfate particles and condensed organics that were produced within the first few seconds. However, subsequent growth of the new particles was limited, due to efficient scavenging by the larger particles originating from the ship exhaust. The transport of UFPs downwind of the ship track increased the hourly mean UFP concentrations in the neighboring residential areas by a factor of two or more up to a distance of 3600 m, compared with the corresponding UFP concentrations in the urban background. The substantially increased UFP concentrations due to ship traffic significantly affected the daily mean exposures in residential areas located in the vicinity of the harbors.

Ultrafine particles (UFP), harmful to human health, are emitted at high levels from motorized traffic. Bicycle commuting is increasingly encouraged to reduce traffic emissions and increase physical activity, but higher breathing rates increase inhaled UFP concentrations while in traffic. We assessed exposure to UFP while cycling along a fixed 8.5 km inner-city route in Copenhagen, on weekdays over six weeks (from September to October 2020), during morning and afternoon rush-hour, as well as morning non-rush-hour, traffic time periods starting from 07:45, 15:45, and 09:45 h, respectively. Continuous measurements were made (each second) of particle number concentration (PNC) and location. PNC levels were summarized and compared across time periods. We used generalized additive models to adjust for meteorological factors, weekdays and trends. A total of 61 laps were completed, during 28 days (∼20 per time period). Overall mean PNC was 18,149 pt/cm3 (range 256–999,560 pt/cm3) with no significant difference between morning rush-hour (18003 pt/cm3), afternoon rush-hour (17560 pt/cm3) and late morning commute (17560 pt/cm3) [p = 0.85]. There was substantial spatial variation of UFP exposure along the route with highest PNC levels measured at traffic intersections (∼38,000-42000 pt/cm3), multiple lane roads (∼38,000-40000 pt/cm3) and construction sites (∼44,000-51000 pt/cm3), while lowest levels were measured at smaller streets, areas with open built environment (∼12,000 pt/cm3), as well as at a bus-only zone (∼15,000 pt/cm3). UFP exposure in inner-city Copenhagen did not differ substantially when bicycling in either rush-hour or non-rush-hour, or morning or afternoon, traffic time periods. UFP exposure varied substantially spatially, with highest concentrations around intersections, multiple lane roads, and construction sites. This suggests that exposure to UFP is not necessarily reduced by avoiding rush-hours, but by avoiding sources of pollution along the bicycling route.

Background: Although epidemiological studies have reported associations between mortality and both ambient air pollution and air temperature, it remains uncertain whether the mortality effects of air pollution are modified by temperature and vice versa. Moreover, little is known on the interactions between ultrafine particles (diameter ≤ 100 nm, UFP) and temperature. Objective: We investigated whether the short-term associations of particle number concentration (PNC in the ultrafine range (≤100 nm) or total PNC ≤ 3000 nm, as a proxy for UFP), particulate matter ≤ 2.5 μm (PM2.5) and ≤ 10 μm (PM10), and ozone with daily total natural and cardiovascular mortality were modified by air temperature and whether air pollution levels affected the temperature-mortality associations in eight European urban areas during 1999–2013. Methods: We first analyzed air temperature-stratified associations between air pollution and total natural (nonaccidental) and cardiovascular mortality as well as air pollution-stratified temperature-mortality associations using city-specific over-dispersed Poisson additive models with a distributed lag nonlinear temperature term in each city. All models were adjusted for long-term and seasonal trend, day of the week, influenza epidemics, and population dynamics due to summer vacation and holidays. City-specific effect estimates were then pooled using random-effects meta-analysis. Results: Pooled associations between air pollutants and total and cardiovascular mortality were overall positive and generally stronger at high relatively compared to low air temperatures. For example, on days with high air temperatures (>75th percentile), an increase of 10,000 particles/cm3 in PNC corresponded to a 2.51% (95% CI: 0.39%, 4.67%) increase in cardiovascular mortality, which was significantly higher than that on days with low air temperatures (50th percentile), both heat- and cold-related mortality risks increased. Conclusion: Our findings showed that high temperature could modify the effects of air pollution on daily mortality and high air pollution might enhance the air temperature effects. Keywords: Ultrafine particles, Particulate matter, Ozone, Air temperature, Mortality, Effect modification

Exposure assessment is a key stage in the risk assessment/management of engineered nanomaterials. Although different sampling strategies and instruments have been used to define the occupational exposure to nano-scale materials, currently there is no international consensus regarding measurement strategy, metrics and limit values. In fact, the assessment of individual exposure to engineered nanomaterials remains a critical issue despite recent innovative developments in personal monitors and samplers. Hence, we used several of these instruments to evaluate the workers' personal exposure in a large research laboratory where engineered nanomaterials are produced, handled, and characterized in order to provide input data for nanomaterial exposure assessment strategies and future epidemiological studies. The results obtained using personal monitors showed that the workplace concentrations of engineered nanomaterials (lung deposited surface area and particle number concentrations) were quite low in all the different workplaces monitored, with short spikes during the execution of some specific job tasks. The sampling strategy was been adopted on the basis of an Organisation for Economic Cooperation and Development (OECD) suggestion for a tiered approach and was found to be suitable for determining the individual exposure and for identifying possible sources of emission, even those with very low emission rates. The use of these instruments may lead to a significant improvement not only in the exposure assessment stage but, more generally, in the entire risk assessment and management process.

Background Air pollution in subway environments is a growing concern as it often exceeds WHO recommendations for indoor air quality. Ultrafine particles (UFP), for which there is still no regulation nor a standardized exposure monitoring method, are the strongest contributor to this pollution when the number concentration is used as exposure metric. Objectives We aimed to assess the real-time UFP number concentration in the personal breathing zone (PBZ) of three types of underground Parisian subway professionals and analyze it using a novel Bayesian spline approach. Consecutively, we investigated the effect of job, week day, subway station, worker location, and some further events on UFP number concentrations. Methods The data collection procedure originated from a longitudinal study and lasted for a total duration of 6 weeks (from October 7 to November 15, 2019, i.e. two weeks per type of subway professionals). Time-series were built from the real-time particle number concentration (PNC) measured in the PBZ of professionals during their work-shifts. Complementarily, contextual information expressed as Station, Environment, and Event variables were extracted from activity logbooks completed for every work-shift. A Bayesian spline approach was applied to model the PNC within a Bayesian framework as a function of the mentioned contextual information. Results Overall, the Bayesian spline method suited a real-time personal PNC data modeling approach. The model enabled estimating the differences in UFP exposure between subway professionals, stations, and various locations. Our results suggest a higher PNC closer to the subway tracks, with the highest PNC on subway station platforms. Studied event and week day variables had a lesser influence. Conclusion It was shown that the Bayesian spline method is suitable to investigate individual exposure to UFP in underground subway settings. This method is informative for better documenting the magnitude and variability of UFP exposure, and for understanding the determinants in view of further regulation and control of this exposure.

Exposure to ultrafine particles has been associated with short- and long-term effects on human health. The object of this paper was to assess Particle Number Concentration (PNC) and size distribution in a university environment and study the indoor/outdoor relationships. Measurements were carried out using co-located (indoor/outdoor) condensation particle counters and size spectrometers during two seasonal periods characterized by different meteorological conditions at five selected classrooms different for size, capacity, floor and use destination. PNC was dominated by particles in the ultrafine mode both indoor and outdoor. The indoor/outdoor ratios were on average between 1 and 1.2 in the summer and between 0.6 and 0.9 in the winter. Mostly the differences found among classrooms could be related to the condition of use (i.e., crowding, natural air exchange, air conditioning, seasonality). Only little differences were found among PNC measured immediately outside the classrooms. Based on information taken during the measurement campaigns, on the classrooms condition of use, it was possible to assess as a source of indoor particles in the coarse mode, the presence of students and teachers.

The natural processes of interactions between aerosol particles in the ambient air through which they agglomerate is a vast area of chamber research and are inherent to many industries and are often inter-connected with transport engineering. Further improvement of symmetric methods for aerosol particle number and mass concentration reduction made it possible to create various synergic techniques. The study used a 1.9 TDI diesel internal combustion engine, which was supplied with diesel (D100) and second-generation biofuels (NExBTL100) with the EGR exhaust system on and off. Measurements were performed using a Bruel and Kjær “Type 9727” system for measurement of vibrations, a scanning mobility particle sizer (SMPS) and an original agglomeration chamber. The three modes of particle size distributions were observed in the size range from 10 to 470 nm for both D100 and NExBTL100 fuels with and without the use of the EGR system. The application of 21.3 kHz frequency sound with SPL 144.1 dB changed the NExBTL100 generated aerosol particle number concentration but did not sufficiently affect the concentration of D100 emitted particles. The greatest agglomeration effect (21.7 ± 10.0%) was observed in the range of extremely small NExBTL100 derived particles (10–70 nm) when used in combination with an EGR system.

Particulate matter exposure may cause adverse health effects. Although ultrafine particulate matter (UFP) is hypothesised to be particularly health relevant, the number of studies into personal UFP exposure is limited. Aim To increase insight where and when most UFP exposure occurs, in terms of exposure levels and peaks in microenvironments, time of day and activities, to support development of abatement strategies to reduce exposure. Methods UFP exposure and GPS tracks were recorded continuously for 5 days in 12 healthy volunteers. GPS data was processed to assign context information, and linked to UFP data. Results Participants spent most time indoors (>90%), mainly at home (approx. 80%). Mean particle number concentration (particles/cm3) was highest in motorized transport (20.5 × 103), followed by other indoor environments (16.5 × 103), and lower at home (11.2 × 103) and walking outdoors (9.0 × 103). Due to the large proportion of time spent indoors, exposure indoors contributed most to total exposure (nearly 90%). Exposure during motorized transport showed a speed dependency, most likely linked to exposure on larger busier roads. Using a 95th percentile cut-off for concentration elevations lasting at least 5 min for peak-detection, 98 peaks were identified, mainly during daytime. These contributed substantially to total exposure (25%) while accounting for only 3.4% of total time. Of this peak contribution 88% occurred indoors (mainly at home) and 12% outdoors. Conclusions UFP exposure shows clear differences between microenvironments. Peaks contribute substantially to total exposure. Measures to prevent peak exposures could contribute to substantial exposure reduction. © 2017 Elsevier Ltd

In the frame of the OFFICAIR project, office buildings were investigated across Europe to assess how the office workers are exposed to different particulate matter (PM) characteristics (i.e. PM2.5 mass concentration, particulate oxidative potential (OP) based on ascorbate and reduced glutathione depletion, trace element concentration and total particle number concentration (PNC)) within the buildings. Two offices per building were investigated during the working hours (5 consecutive days; 8 h per day) in two campaigns. Differences were observed for all parameters across the office buildings. Our results indicate that the monitoring of the PM2.5 mass concentration in different offices within a building might not reflect the spatial variation of the health relevant PM characteristics such as particulate OP or the concentration of certain trace elements (e.g., Cu, Fe), since larger differences were apparent within a building for these parameters compared to that obtained for the PM2.5 mass concentration in many cases. The temporal variation was larger for almost all PM characteristics (except for the concentration of Mn) than the spatial differences within the office buildings. These findings indicate that repeated or long-term monitoring campaigns are necessary to have information about the temporal variation of the PM characteristics. However, spatial variation in exposure levels within an office building may cause substantial differences in total exposure in the long term. We did not find strong associations between the investigated indoor activities such as printing or windows opening and the PNC values. This might be caused by the large number of factors affecting PNC indoors and outdoors. © 2017 Elsevier B.V.

The health effects of long-term exposure to ultrafine particles (UFPs) are poorly understood. Data on spatial contrasts in ambient ultrafine particles (UFPs) concentrations are needed with fine resolution. This study aimed to assess the spatial variability of total particle number concentrations (PNC, a proxy for UFPs) in the city of Rome, Italy, using land use regression (LUR) models, and the correspondent exposure of population here living. PNC were measured using condensation particle counters at the building facade of 28 homes throughout the city. Three 7-day monitoring periods were carried out during cold, warm and intermediate seasons. Geographic Information System predictor variables, with buffers of varying size, were evaluated to model spatial variations of PNC. A stepwise forward selection procedure was used to develop a “base” linear regression model according to the European Study of Cohorts for Air Pollution Effects project methodology. Other variables were then included in more enhanced models and their capability of improving model performance was evaluated. Four LUR models were developed. Local variation in UFPs in the study area can be largely explained by the ratio of traffic intensity and distance to the nearest major road. The best model (adjusted R2 = 0.71; root mean square error = ±1,572 particles/cm³, leave one out cross validated R2 = 0.68) was achieved by regressing building and street configuration variables against residual from the “base” model, which added 3% more to the total variance explained. Urban green and population density in a 5,000 m buffer around each home were also relevant predictors. The spatial contrast in ambient PNC across the large conurbation of Rome, was successfully assessed. The average exposure of subjects living in the study area was 16,006 particles/cm³ (SD 2165 particles/cm³, range: 11,075–28,632 particles/cm³). A total of 203,886 subjects (16%) lives in Rome within 50 m from a high traffic road and they experience the highest exposure levels (18,229 particles/cm³). The results will be used to estimate the long-term health effects of ultrafine particle exposure of participants in Rome.

Determination of intra-urban spatial variations in air pollutant concentrations for exposure assessment requires substantial time and monitoring equipment. The objective of this study was to establish if short-duration measurements of air pollutants can be used to estimate longer-term pollutant concentrations. We compared 5-min measurements of black carbon (BC) and particle number (PN) concentrations made once per week on 5 occasions, with 4 consecutive 1-week average nitrogen dioxide (NO2) concentrations at 18 locations at a range of distances from busy roads in Glasgow, UK. 5-min BC and PN measurements (averaged over the two 5-min periods at the start and end of a week) explained 40 - 80%, and 7 - 64% respectively, of spatial variation in the intervening 1-week NO2 concentrations for individual weeks. Adjustment for variations in background concentrations increased the percentage of explained variation in the bivariate relationship between the full set of NO2 and BC measurements over the 4-week period from 28% to 50% prior to averaging of repeat measurements. The averages of five 5-min BC and PN measurements made over 5 weeks explained 75% and 33% respectively of the variation in average 1-week NO2 concentrations over the same period. The relatively high explained variation observed between BC and NO2 measured on different time scales suggests that, with appropriate steps to correct or average out temporal variations, repeated short-term measurements can be used to provide useful information on longer-term spatial patterns for these traffic-related pollutants.

Important health relevance has been suggested for ultrafine particles (UFP) and ozone, but studies on long-term effects are scarce, mainly due to the lack of appropriate spatial exposure models. We designed a measurement campaign to develop land use regression (LUR) models to predict the spatial variability focusing on particle number concentration (PNC) as indicator for UFP, ozone and several other air pollutants in the Augsburg region, Southern Germany. Three bi-weekly measurements of PNC, ozone, particulate matter (PM10, PM2.5), soot (PM2.5abs) and nitrogen oxides (NOx, NO2) were performed at 20 sites in 2014/15. Annual average concentration were calculated and temporally adjusted by measurements from a continuous background station. As geographic predictors we offered several traffic and land use variables, altitude, population and building density. Models were validated using leave-one-out cross-validation. Adjusted model explained variance (R2) was high for PNC and ozone (0.89 and 0.88). Cross-validation adjusted R2 was slightly lower (0.82 and 0.81) but still indicated a very good fit. LUR models for other pollutants performed well with adjusted R2 between 0.68 (PMcoarse) and 0.94 (NO2). Contrary to previous studies, ozone showed a moderate correlation with NO2 (Pearson's r=-0.26). PNC was moderately correlated with ozone and PM2.5, but highly correlated with NOx (r=0.91). For PNC and NOx, LUR models comprised similar predictors and future epidemiological analyses evaluating health effects need to consider these similarities.

Understanding the spatio-temporal variation of short lived climate pollutants (SLCP) over cities is critical to protect public health and mitigate climate change. There is a lack of knowledge about the distribution of SLCP in South America, mainly in medium-sized cities (3 , fine particles PM 2.5 , and particle number PN) were analyzed by using descriptive statistics, diurnal cycles, time-space correlations, and establishing linkages with traffic rates and with wind conditions. Hourly mean (±standard deviation) BC concentrations ranged from 0.58 (±0.54) in the suburban area to 3.43 (±2.69) µg m −3 at the street canyon site (10,150 vehicles d −1 on weekdays), showing a high spatio-temporal variability even at short scales. PN (mean of 17,469 cm −3 ) and NOx (mean of 51.58 µg m −3 ) concentrations tracked BC levels and traffic rates, particularly the number of diesel buses at the canyon site. PM 2.5 and O 3 levels presented a lower spatial variability, with poor correlation with traffic rates in the canyon and were more tied to regional sources. NOx, BC, and PN showed the highest reduction potentials connected to the abatement of traffic emissions in the city center, particularly by targeting heavy-duty diesel vehicles. The reduction of PM 2.5 and O 3 concentrations is more challenging due to a significant regional contribution that requires cutting down emissions at state, national or even transboundary scales.

The aim of the presented work was the assessment of occupational exposure to nanoparticles and ultrafine particles during selected processes of using construction materials.The tests were carried out at the following workplaces: abrasion and pouring of 2 products - nanomortar and nanocrete. Measurements were carried out using the following devices: DiSCmini measurer, GRIMM 1.109 optical counter and DustTrak monitor. The number, surface area, mass concentration and size distribution were analyzed.DiSCmini measurements showed that the mean number concentration of particles during the analyzed processes ranged of 1.4×104-1.0×105 particles/cmsup3/sup, and the highest one was during nanomortar abrasion. The mean particles diameters during the processes ranged 28.9-47.1 nm depending on the process. An increase in the average value of the particles surface area concentration was observed, the largest value was found during nanomortar abrasion - 255.9 μmsup2/sup/cmsup3/sup. The size distributions analysis (GRIMM 1.109) showed that the dimensions of particles released in the processes had a wide range, however the majority of particles were in the range of 60-145 nm. The analysis of the mass concentration (DustTrak) showed that the fraction of particles1 μm was minimum 50% of the total analyzed particles during the process.During the processes under study, a large increase in all analyzed parameters describing the emission of ultrafine particles was observed. This allows to conclude that the smallest particles emitted during the using of nanostructures containing construction materials may be a potential health risk factor for people exposed to these materials. Med Pr. 2019;70(1):67-88.Procesy użytkowania i obróbki materiałów budowlanych zawierających nanomateriały mogą być związane z emisją do środowiska pracy dużej liczby cząstek o wymiarach nanometrowych, które są potencjalnym źródłem narażenia zawodowego na te struktury. Celem pracy była ocena emisji nanocząstek i cząstek ultradrobnych podczas wybranych procesów obróbki materiałów budowlanych.Badania przeprowadzono na stanowiskach ścierania i przesypywania materiałów budowlanych, stosując 2 produkty – nanozaprawę oraz nanobeton. Pomiary wykonano z zastosowaniem następującej aparatury: mierników DiSCmini, licznika GRIMM 1.109 i monitora DustTrak. Analizowano stężenia liczbowe, powierzchniowe i masowe cząstek oraz ich rozkłady wymiarowe.Pomiary przeprowadzone za pomocą DiSCmini wykazały, że średnie stężenie liczbowe cząstek podczas analizowanych procesów mieściło się w zakresie 1,4×104−1,0×105 cząstek/cmsup3/supi było najwyższe podczas ścierania nanozaprawy. Średnie średnice cząstek emitowanych podczas procesów były mniejsze (28,9−47,1 nm w zależności od procesu) niż średnice cząstek tła. Jednocześnie obserwowano wzrost średniej wartości stężenia powierzchniowego cząstek proporcjonalny do liczby cząstek, którego największą wartość – 255,9 μmsup2/sup/cmsup3/sup– stwierdzono podczas ścierania nanozaprawy. Z analizy rozkładów wymiarowych (GRIMM 1.109) wynika, że zakres wymiarów cząstek uwalnianych w omawianych procesach był szeroki, jednak w przypadku ich największej liczby wynosił 60−145 nm. Analiza udziału masowego (DustTrak) poszczególnych frakcji wymiarowych aerozolu wykazała, że udział cząstek1 μm wynosił przynajmniej 50% ogółu analizowanych cząstek.Podczas badanych procesów obserwowano duży wzrost wszystkich analizowanych parametrów opisujących emisję cząstek ultradrobnych. Pozwala to wnioskować, że cząstki emitowane podczas obróbki materiałów budowlanych zawierających nanostruktury mogą stanowić potencjalny czynnik ryzyka zdrowotnego u osób narażonych na te materiały. Med. Pr. 2019;70(1):67–88.

PhD (Occupational Hygiene), North-West University, Potchefstroom Campus Background: Additive Manufacturing (AM) is the process of joining feedstock materials one layer at a time in order to produce objects from a three dimensional (3D) computer aided design (CAD). Powder bed fusion (PBF) and direct energy deposition (DED) are two widely applied powder based metal AM processes used commercially in the South African AM industry. A number of studies have investigated small desktop polymer material extrusion fused deposition modelling (FDMTM) 3D printers and found that these printers are high emitters of particulate matter and volatile organic compounds. Chamber studies have been of value by contributing to a better understanding of emissions from FDMTM desktop printers. However, despite the numerous studies on particulate matter emissions from desktop FDMTM printers there is an unbridged gap to identify the hazardous chemical substance emissions from and the respiratory exposure of AM operators when utilising metal powders in AM. AM processes takes place in three distinct phases, namely the pre-processing, processing and post-processing phases, and occupational exposure may occur during each of these three phases since most tasks are manually performed by the AM operator. To date only one study has investigated particle emissions from and exposure to metals during PBF while there is no published literature on emissions or exposure from DED. PBF and DED are applied in South Africa and therefore, the investigation of particle emissions from and personal exposure of AM operators to hazardous chemical substances (metals) is needed. Aims and objectives: The general research aim of this thesis was to assess the emissions of and occupational exposure to hazardous chemical substances (particles and metals) associated with two metal powder based AM process categories (powder bed fusion and direct energy deposition) at three South African institutions utilising AM. The specific objectives were: (i) to establish the physico-chemical characteristics (particle size, shape and elemental composition) of virgin and used metal powders, used during powder bed fusion and direct energy deposition, and the relevance thereof to AM operators’ health. (ii) to assess particle emissions and respiratory metal exposure of AM operators when using three titanium powders and maraging steel during the pre- processing, processing and post-processing phases of AM at three AM facilities utilising PBF. (iii) to assess particle emissions and respiratory metal exposure of AM operators when using two stainless steel powders during DED at an AM facility. Methods: Samples of virgin and used (recycled) titanium and maraging steel as well as used stainless steel powders, along with their respective safety data sheets (SDSs) were collected from three AM facilities in South Africa utilising PBF and DED. Powder samples were characterised in terms of particle size distribution (PSD), particle shape and elemental composition. Real time monitoring devices, namely a Condensation Particle Counter (0.01 to > 1 μm) and an Airborne Particle Counter (0.30 to 10.00 μm) were used to investigate particle emissions [particle number concentrations (p/m3)] during PBF and DED process phases. The concentration of metals in the workplace air was established by means of static area monitoring according to the National Institute for Occupational Safety and Health (NIOSH) 7300 method using a closed-faced cassette (CFC). Personal (AM operator) respiratory exposure to metals used the same NIOSH method. Ethics approval for this study was obtained from the Health Research Ethics Committee of the North-West University (NWU-00004-16-A1). Researchers followed well know occupational hygiene methods, and other state of the art methods nor currently used in occupational hygiene compliance monitoring. Personal exposure to metals < 300 nm in size was assessed by using a nanoparticle respiratory deposition sampler. Results: Only one of the three titanium powers PSD was in accordance with the SDS. From the SEM images, thoracic sized (< 10 μm) and respirable sized (< 4 μm) particles were observed in powders from all three facilities. The elemental composition analysis (XRD analysis) of the investigated powders differed from the composition stated in the respective SDSs. Particles ≤ 1 μm were present in the workplace air. Increases in particle number concentrations were observed during specific pre- and post-processing tasks such as cleaning and powder sieving which led to an increase in particle emissions with the highest particle number concentration of 6.12 x 1010 p/m3 (0.01 to > 1 μm) measured during the post-processing phase of PBF with titanium. Tasks such as unloading of the AM machines led to particle concentrations (0.01 to > 1 μm) as high as 5.98 x 1010 p/m3 during PBF with maraging steel and 5.75 x 1010 p/m3 during DED of stainless steel. Static area monitoring indicated low concentrations of metals in the work place atmosphere during PBF and DED. During both PBF and DED, AM operators were exposed to detectable concentrations of metals including aluminium, chromium, copper, iron, nickel, titanium and vanadium, including metals < 300 nm in size. Full shift metal exposure was calculated for comparisons with occupational exposure limits (OELs) of all detected metals. AM operators’ personal respiratory exposure was < 1.04% of the time weighted average OELs (TWA-OELs) when using titanium powders, and < 3.60% of the respective TWA-OELs and < 9.01% of threshold limit value (TLVs®) during the use of maraging steel. Exposure to Ni, a human carcinogen, was the highest. Conclusion: There is a shortage of studies reporting particle emissions from and AM operators’ respiratory exposure to metals resulting from use of titanium and metals powders used in PBF and DED. Inadequate information in the SDSs may mislead employers and AM operators’ regarding the protection of AM operator health, and therefore, powder characterisation should form an integral part of risk assessments at each facility. During the pre-and post-processing phases of PBF and DED, particles were emitted during phase specific tasks such as cleaning, sieving, and unloading of the AM machine. When particle number concentrations during the processing phase from PBF and DED were compared to FDM™ printers, it was found that particle number concentrations emitted from FDMs™ were approximately five to nine times higher. The maximum particle number concentrations emitted from DED were 3% lower than that of PBF. Low concentrations of metals were present in the workplace atmosphere throughout the use of titanium, maraging steel and stainless steel powders. Although no OELs were exceeded, AM operators were exposed to detectable concentrations of metals, including metals < 300 nm in size. The findings of this study serve as a starting point to create awareness of AM operator exposure associated with metal AM, and to assist industrial AM facilities in identifying hazards and implementing phase and task specific control measures during PBF and DED using titanium powders and metal powders. Eleven recommendations are made for the attention of all role players including AM powder manufacturers/suppliers, employers (AM facilities) and AM operators/employees in an effort to reduce particle emissions from and AM operator’s respiratory exposure to metals. Along with the recommendations, specific limitations experienced during the study were also identified along with recommendations for future studies. Doctoral

Epidemiological studies have linked both traffic-related air pollution (TRAP) and noise to adverse health outcomes, including increased blood pressure, myocardial infarction, and respiratory health. The high correlation between these environmental exposures and their measurement challenges have constrained research on how simultaneous exposure to TRAP and traffic noise interact and possibly enhance each other&rsquo, s effect. The objective of this study was to deploy two novel personal sensors for measuring ultrafine particles (UFP, &lt, 100 nm diameter) and noise to concurrently monitor real-time exposures. Personal UFP monitors (PUFP, Enmont, LLC) were paired with NEATVIBEwear&trade, (Noise Exposure, Activity-Time and Vibration wearable), a personal noise monitoring device developed by the authors (Douglas Leaffer, Steve Doroff). A field-test of PUFP monitors co-deployed with NEATVIBEwear logged UFP, noise and ambient temperature exposure levels at 1-s resolution in an adolescent population in Cincinnati, OH to measure real-time exposures in microenvironments (transit, home, school). Preliminary results show that the concurrent measurement of noise exposures with UFP is feasible in a sample of physically active adolescent participants. Personal measurements of UFP and noise, measured prospectively in future studies, will enable researchers to investigate the independent and/or joint-effects of these health-relevant environmental exposures.

The aim of this study was to (a) develop a method for converting particle number concentrations (PNC) obtained by Dylos to PM2.5 mass concentrations, (b) compare this conversion with similar methods available in the literature, and (c) compare Dylos PM2.5 obtained using all available conversion methods with gravimetric samples. Data were collected in multiple residences in three European countries using the Dylos and an Aerodynamic Particle Sizer (APS, TSI) in the Netherlands or an optical particle counter (OPC, GRIMM) in Greece. Two statistical fitted curves were developed based on Dylos PNC and either an APS or an OPC particle mass concentrations (PMC). In addition, at the homes of 16 volunteers (UK and Netherlands), Dylos measurements were collected along with gravimetric samples. The Dylos PNC were transformed to PMC using all the fitted curves obtained during this study (and three found in the literature) and were compared with gravimetric samples. The method developed in the present study using an OPC showed the highest correlation (Pearson (R) = 0.63, Concordance (? c ) = 0.61) with gravimetric data. The other methods resulted in an underestimation of PMC compared to gravimetric measurements (R = 0.65-0.55, ? c = 0.51-0.24). In conclusion, estimation of PM2.5 concentrations using the Dylos is acceptable for indicative purposes. © 2019 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd

Can mitigating only particle mass, as the existing air quality measures do, ultimately lead to reduction in ultrafine particles (UFP)? The aim of this study was to provide a broader urban perspective on the relationship between UFP, measured in terms of particle number concentration (PNC) and PM2.5 (mass concentration of particles with aerodynamic diameter < 2.5 μm) and factors that influence their concentrations. Hourly average PNC and PM2.5 were acquired from 10 cities located in North America, Europe, Asia, and Australia over a 12-month period. A pairwise comparison of the mean difference and the Kolmogorov-Smirnov test with the application of bootstrapping were performed for each city. Diurnal and seasonal trends were obtained using a generalized additive model (GAM). The particle number to mass concentration ratios and the Pearson's correlation coefficient were calculated to elucidate the nature of the relationship between these two metrics. Results show that the annual mean concentrations ranged from 8.0 × 103 to 19.5 × 103 particles·cm−3 and from 7.0 to 65.8 μg·m−3 for PNC and PM2.5, respectively, with the data distributions generally skewed to the right, and with a wider spread for PNC. PNC showed a more distinct diurnal trend compared with PM2.5, attributed to the high contributions of UFP from vehicular emissions to PNC. The variation in both PNC and PM2.5 due to seasonality is linked to the cities' geographical location and features. Clustering the cities based on annual median concentrations of both PNC and PM2.5 demonstrated that a high PNC level does not lead to a high PM2.5, and vice versa. The particle number-to-mass ratio (in units of 109 particles·μg−1) ranged from 0.14 to 2.2, >1 for roadside sites and, “GEMMA Center in the framework of Project MIUR – Dipartimenti di Eccellenza 2018–2022” funding for measurements in Milan site. Appendix A

Exposure to ultrafine particles (UFPs size &lt, 100 nm) in life and work environments can contribute to adverse health effects also in terms of health burden of related diseases over time. The choice of parameters which better characterize UFPs is challenging, due to their physical-chemical properties and their variable size. It is also strictly related to the availability of different instrumental techniques. In the present study we focus on real time high frequency (1 Hz) UFPs particle size distribution (PSD) and their relationship with total particle number concentration (TPNC) and mean particle diameter (Davg) as a contribution characterizing by size the human exposure to UFPs in an indoor site of the University of Rome “Sapienza” (Italy). Further considerations about UFPs contribution to nucleation mode (NM) and accumulation mode (AM) have been highlighted, also in order to investigate the contribution of polycyclic aromatic hydrocarbons (PAHs) surface-adsorbed on indoor air particles (pPAHs). High indoor TPNC values were registered during the rush hours (early morning and mid/late afternoon) according to the outdoor influences originated from anthropogenic activities. AM mainly contribute to the indoor TPNC during working days showing high correlation with pPAHs. These findings may provide useful indications in terms of occupational exposure to UFPs since there are many evidences that indoor exposures to such pollutants may be associated with adverse health effects also in working environments.

Continuous measurements of particle number size distributions in the size range from 10 nm to 800 nm were performed from 2015 to 2019 at the ECO Environmental-Climate Observatory of Lecce (Global Atmosphere Watch Programme/Aerosol, Clouds and Trace Gases Research Infrastructure (GAW/ACTRIS) regional station). The main objectives of this work were to investigate the daily, weekly and seasonal trends of particle number concentrations and their dependence on meteorological parameters gathering information on potential sources. The highest total number concentrations were observed during autumn-winter with average values nearly twice as high as in summer. More than 52% of total particle number concentration consisted of Aitken mode (20 nm &lt, particle diameter (Dp) &lt, 100 nm) particles followed by accumulation (100 nm &lt, Dp &lt, 800 nm) and nucleation (10 nm &lt, 20 nm) modes representing, respectively, 27% and 21% of particles. The total number concentration was usually significantly higher during workdays than during weekends/holidays in all years, showing a trend likely correlated with local traffic activities. The number concentration of each particle mode showed a characteristic daily variation that was different in cold and warm seasons. The highest concentrations of the Aitken and accumulation particle mode were observed in the morning and the late evening, during typical rush hour traffic times, highlighting that the two-particle size ranges are related, although there was significant variation in the number concentrations. The peak in the number concentrations of the nucleation mode observed in the midday of spring and summer can be attributed to the intensive formation of new particles from gaseous precursors. Based on Pearson coefficients between particle number concentrations and meteorological parameters, temperature, and wind speed had significant negative relationships with the Aitken and accumulation particle number concentrations, whereas relative humidity was positively correlated. No significant correlations were found for the nucleation particle number concentrations.

The aim of this study was to explore the relationships among the particle number concentration (PNC), noise, and traffic conditions. Field measurements were conducted to measure the temporal variabilities of the noise levels and PNC over 24 h in a location adjacent to three main traffic roads in Seoul, Korea. The PNC was measured in the range of 0.3 to 10 &micro, m. The noise data was measured by utilizing both the overall levels and spectral characteristics. Traffic data including volumes and speeds of vehicles on the roads were also collected. The results showed that the correlations among the three key parameters varied depending on changes in the noise frequency and particle size. The noise levels at 100&ndash, 200 Hz were positively correlated with traffic volume and submicron particles. In contrast, they exhibited inverse correlations with the traffic speed and the number of larger particles (&gt, 2.5 &micro, m). Compared to noise levels at 100&ndash, 200 Hz, noise levels at 1&ndash, 2 kHz exhibited reverse relationships between the traffic and PNC. Submicron particles (0.3&ndash, 1.0 &micro, m) tended to be more strongly associated with noise levels during the daytime, while those greater than 2.5 &micro, m maintained relatively stable correlations with the noise throughout the day. The findings address the importance of temporal and spectral-specific monitoring of air and noise pollutants for a better understanding of the exposure of the community to air and noise pollution.

As part of the Observations and Modeling of the Green Ocean Amazon (GoAmazon 2014/5) Experiment, detailed aerosol and trace gas measurements were conducted near Manaus, a metropolis located in the central Amazon Basin. Measurements of aerosol particles and trace gases were done downwind Manaus at the sites T2 (Tiwa Hotel) and T3 (Manacapuru), at a distance of 8 and 70 km from Manaus, respectively. Based on in-plume measurements closer to Manaus (site T2), the chemical signatures of city emissions were used to improve the interpretation of pollutant levels at the T3 site. We derived chemical and physical properties for the city's atmospheric emission ensemble, taking into account only air masses impacted by the Manaus plume at both sites, during the wet and dry season Intensive Operating Periods (IOPs). At T2, average concentrations of aerosol number (CN), CO and SO2 were 5500 cm−3 (between 10 and 490 nm), 145 ppb and 0.60 ppb, respectively, with a typical ratio ΔCN/ΔCO of 60–130 particles cm−3 ppb−1. The aerosol scattering (at RH < 60%) and absorption at 637 nm at T2 ranged from 10 to 50 M m−1 and 5–10 M m−1, respectively, leading to a mean single scattering albedo (SSA) of 0.70. In addition to identifying periods dominated by Manaus emissions at both T2 and T3, the plume transport between the two sampling sites was studied using back trajectory calculations. Results show that the presence of the Manaus plume at site T3 was important mainly during the daytime and at the end of the afternoons. During time periods directly impacted by Manaus emissions, an average aerosol number concentration of 3200 cm−3 was measured at T3. Analysis of plume evolution between T2 and T3 indicates a transport time of 4–5 h. Changes of submicron organic and sulfate aerosols ratios relative to CO (ΔOA/ΔCO and ΔSO4/ΔCO, respectively) indicate significant production of secondary organic aerosol (SOA), corresponding to a 40% mass increase in OA and a 30% in SO4 mass concentration. Similarly, during air mass arrival at T3 the SSA increased to 0.83 from 0.70 at T2, mainly associated with an increase in organic aerosol concentration. Aerosol particle size distributions show a strong decrease in the Aitken nuclei mode (10–100 nm) during the transport from T2 to T3, in particular above 30 nm, as a result of efficient coagulation processes into larger particles. A decrease of 30% in the particle number concentration and an increase of about 50 nm in geometric mean diameter were observed from T2 to T3 sites. The study of the evolution of aerosol properties downwind of the city of Manaus improves our understanding of how coupling of anthropogenic and biogenic sources may be impacting the sensitive Amazonian atmosphere. © 2018 The Authors