Constructing transferable and interpretable machine learning models for black carbon concentrations

Black carbon (BC) has received increasing attention from researchers due to its adverse health effects. However, in-situ BC measurements are often not included as a regulated variable in air quality monitoring networks. Machine learning (ML) models have been studied extensively to serve as virtual sensors to complement the reference instruments. This study evaluates and compares three white-box (WB) and four black-box (BB) ML models to estimate BC concentrations, with the focus to show their transferability and interpretability. We train the models with the long-term air pollutant and weather measurements in Barcelona urban background site, and test them in other European urban and traffic sites. Despite the difference in geographical locations and measurement sites, BC correlates the strongest with particle number concentration of accumulation mode (PNacc, r = 0.73-0.85) and nitrogen dioxide (NO2, r = 0.68-0.85) and the weakest with meteorological parameters. Due to its similarity of correlation behaviour, the ML models trained in Barcelona performs prominently at the traffic site in Helsinki (R2 = 0.80-0.86; mean absolute error MAE = 3.90-4.73 %) and at the urban background site in Dresden (R2 = 0.79-0.84; MAE = 4.23-4.82 %). WB models appear to explain less variability of BC than BB models, long short-term memory (LSTM) model of which outperforms the rest of the models. In terms of interpretability, we adopt several methods for individual model to quantify and normalize the relative importance of each input feature. The overall static relative importance commonly used for WB models demonstrate varying results from the dynamic values utilized to show local contribution used for BB models. PNacc and NO2 on average have the strongest absolute static contribution; however, they simultaneously impact the estimation positively and negatively at different sites. This comprehensive analysis demonstrates that the possibility of these interpretable air pollutant ML models to be transfered across space and time.

Infectivity of exhaled SARS-CoV-2 aerosols is sufficient to transmit covid-19 within minutes

Exhaled SARS-CoV-2-containing aerosols contributed significantly to the rapid and vast spread of covid-19. However, quantitative experimental data on the infectivity of such aerosols is missing. Here, we quantified emission rates of infectious viruses in exhaled aerosol from individuals within their first days after symptom onset from covid-19. Six aerosol samples from three individuals were culturable, of which five were successfully quantified using TCID50. The source strength of the three individuals was highest during singing, when they exhaled 4, 36, or 127 TCID50/s, respectively. Calculations with an indoor air transmission model showed that if an infected individual with this emission rate entered a room, a susceptible person would inhale an infectious dose within 6 to 37 min in a room with normal ventilation. Thus, our data show that exhaled aerosols from a single person can transmit covid-19 to others within minutes at normal indoor conditions.

Ambient air particulate total lung deposited surface area (LDSA) levels in urban Europe

This study aims to picture the phenomenology of urban ambient total lung deposited surface area (LDSA) (including head/throat (HA), tracheobronchial (TB), and alveolar (ALV) regions) based on multiple path particle dosimetry (MPPD) model during 2017-2019 period collected from urban background (UB, n = 15), traffic (TR, n = 6), suburban background (SUB, n = 4), and regional background (RB, n = 1) monitoring sites in Europe (25) and USA (1). Briefly, the spatial-temporal distribution characteristics of the deposition of LDSA, including diel, weekly, and seasonal patterns, were analyzed. Then, the relationship between LDSA and other air quality metrics at each monitoring site was investigated. The result showed that the peak concentrations of LDSA at UB and TR sites are commonly observed in the morning (06:00-8:00 UTC) and late evening (19:00-22:00 UTC), coinciding with traffic rush hours, biomass burning, and atmospheric stagnation periods. The only LDSA night-time peaks are observed on weekends. Due to the variability of emission sources and meteorology, the seasonal variability of the LDSA concentration revealed significant differences (p = 0.01) between the four seasons at all monitoring sites. Meanwhile, the correlations of LDSA with other pollutant metrics suggested that Aitken and accumulation mode particles play a significant role in the total LDSA concentration. The results also indicated that the main proportion of total LDSA is attributed to the ALV fraction (50 %), followed by the TB (34 %) and HA (16 %). Overall, this study provides valuable information of LDSA as a predictor in epidemiological studies and for the first time presenting total LDSA in a variety of European urban environments.

Indoor Exposure and Regional Inhaled Deposited Dose Rate during Smoking and Incense Stick Burning-The Jordanian Case as an Example for Eastern Mediterranean Conditions

Tobacco smoking and incense burning are commonly used in Jordanian microenvironments. While smoking in Jordan is prohibited inside closed spaces, incense burning remains uncontrolled. In this study, particle size distributions (diameter 0.01-25 µm) were measured and inhaled deposited dose rates were calculated during typical smoking and incense stick-burning scenarios inside a closed room, and the exposure was summarized in terms of number and mass concentrations of submicron (PN_Sub) and fine particles (PM_2.5). During cigarette smoking and incense stick-burning scenarios, the particle number concentrations exceeded 3 × 10⁵ cm^-3. They exceeded 5 × 10⁵ cm^-3 during shisha smoking. The emission rates were 1.9 × 10¹⁰, 6.8 × 10¹⁰, and 1.7 × 10¹⁰ particles/s, respectively, for incense, cigarettes, and shisha. That corresponded to about 7, 80, and 120 µg/s, respectively. Males received higher dose rates than females, with about 75% and 55% in the pulmonary/alveolar during walking and standing, respectively. The total dose rates were in the order of 10¹²-10¹³ #/h (10³-10⁴ µg/h), respectively, for PN_Sub and PM_2.5. The above reported concentrations, emissions rates, and dose rates are considered seriously high, recalling the fact that aerosols emitted during such scenarios consist of a vast range of toxicant compounds.

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

To convey the severity of ambient air pollution level to the public, air quality index (AQI) is used as a communication tool to reflect the concentrations of individual pollutants on a common scale. However, due to the enhanced air pollution control in recent years, air quality has improved, and the roles of some air pollutant species included in the existing AQI as urban air pollutants have diminished. In this study, we suggest the current AQI should be revised in a way that new air pollution indicators would be considered so that it would better represent the health effects caused by local combustion processes from traffic and residential burning. Based on the air quality data of 2017-2019 in three different sites in Helsinki metropolitan area, we assumed the statistical distributions of the current indicators (NO₂ and PM_2.5) and the proposed particulate indicators (BC, LDSA and PNC) were related as they have similar sources in urban regions despite the varying correlations between the current and proposed indicators (NO₂: r = 0.5-0.85, PM_2.5: r = 0.28-0.72). By fitting the data to an optimal distribution function, together with expert opinions, we improved the current Finnish AQI and determined the AQI breakpoints for the proposed indicators where this robust statistical approach is transferrable to other cities. The addition of the three proposed indicators to the current AQI would decrease the number of good air quality hours in all three environments (largest decrease in urban traffic site, ~22 %). The deterioration of air quality class appeared more severe during peak hours in the urban traffic site due to vehicular emission and evenings in the detached housing site where domestic wood combustion often takes place. The introduction of the AQI breakpoints of the three new indicators serve as a first step of improving the current AQI before further air quality guideline levels are updated.

Deposition potential of 0.003-10 µm ambient particles in the humidified human respiratory tract: Contribution of new particle formation events in Beijing

Ultrafine particles (UFPs) usually explosive growth during new particle formation (NPF) events. However, the risk of exposure to UFPs on NPF days has been ignored due to the prevalence of mass-based air quality standards. In this study, the daily deposited doses, i.e., the daily deposited particle number dose (D_PNd), mass dose (D_PMd), and surface area dose (D_PSd), of ambient particles in the human respiratory tract in Beijing were evaluated based on the particle number size distribution (3 nm-10 µm) from June 2018 to May 2019 utilizing a Multiple-Path Particle Dosimetry Model (MPPD) after the hygroscopic growth of particles in the respiratory tract had been accounted for. Our observations showed a high frequency (72.6%) of NPF on excellent air quality days, with daily mean PM_2.5 concentrations less than 35 μg m^-3. The daily D_PNd on excellent air quality days was comparable with that on polluted days, although the D_PMd on excellent air quality days was as low as 15.6% of that on polluted days. The D_PNd on NPF days was ~1.3 times that on non-NPF days. The D_PNd in respiratory tract regions decreased in the order: tracheobronchial (TB) > pulmonary (PUL) > extrathoracic (ET) on NPF days, while it was PUL > TB > ET on non-NPF days. The number of deposited nucleation mode particles, which were deposited mainly in the TB region (45%), was 2 times higher on NPF days than that on non-NPF days. Our results demonstrated that the deposition potential due to UFPs in terms of particle number concentrations is high in Beijing regardless of the aerosol mass concentration. More toxicological studies related to UFPs on NPF days, especially those targeting tracheobronchial and pulmonary impairment, are required in the future.

Non-linear models for black carbon exposure modelling using air pollution datasets

Black carbon (BC) is a product of incomplete combustion, present in urban aerosols and sourcing mainly from road traffic. Epidemiological evidence reports positive associations between BC and cardiovascular and respiratory disease. Despite this, BC is currently not regulated by the EU Air Quality Directive, and as a result BC data are not available in urban areas from reference air quality monitoring networks in many countries. To fill this gap, a machine learning approach is proposed to develop a BC proxy using air pollution datasets as an input. The proposed BC proxy is based on two machine learning models, support vector regression (SVR) and random forest (RF), using observations of particle mass and number concentrations (N), gaseous pollutants and meteorological variables as the input. Experimental data were collected from a reference station in Barcelona (Spain) over a 2-year period (2018-2019). Two months of additional data were available from a second urban site in Barcelona, for model validation. BC concentrations estimated by SVR showed a high degree of correlation with the measured BC concentrations (R² = 0.828) with a relatively low error (RMSE = 0.48 μg/m³). Model performance was dependent on seasonality and time of the day, due to the influence of new particle formation events. When validated at the second station, performance indicators decreased (R² = 0.633; RMSE = 1.19 μg/m³) due to the lack of N data and PM_2.5 and the smaller size of the dataset (2 months). New particle formation events critically impacted model performance, suggesting that its application would be optimal in environments where traffic is the main source of ultrafine particles. Due to its flexibility, it is concluded that the model can act as a BC proxy, even based on EU-regulatory air quality parameters only, to complement experimental measurements for exposure assessment in urban areas.

A holistic modeling framework for estimating the influence of climate change on indoor air quality

The IPCC 2021 report predicts rising global temperatures and more frequent extreme weather events in the future, which will have different effects on the regional climate and concentrations of ambient air pollutants. Consequently, changes in heat and mass transfer between the inside and outside of buildings will also have an increasing impact on indoor air quality. It is therefore surprising that indoor spaces and occupant well-being still play a subordinate role in the studies of climate change. To increase awareness for this topic, the Indoor Air Quality Climate Change (IAQCC) model system was developed, which allows short and long-term predictions of the indoor climate with respect to outdoor conditions. The IAQCC is a holistic model that combines different scenarios in the form of submodels: building physics, indoor emissions, chemical-physical reaction and transformation, mold growth, and indoor exposure. IAQCC allows simulation of indoor gas and particle concentrations with outdoor influences, indoor materials and activity emissions, particle deposition and coagulation, gas reactions, and SVOC partitioning. These key processes are fundamentally linked to temperature and relative humidity. With the aid of the building physics model, the indoor temperature and humidity, and pollutant transport in building zones can be simulated. The exposure model refers to the calculated concentrations and provides evaluations of indoor thermal comfort and exposure to gaseous, particulate, and microbial pollutants.

Estimation of the Seasonal Inhaled Deposited Dose of Particulate Matter in the Respiratory System of Urban Individuals Living in an Eastern Mediterranean City

In this study, we present an estimation for the inhaled deposited dose rate in adult males and females during common exposure scenarios to urban background aerosols in an Eastern Mediterranean city (Amman, Jordan) based on a one-year database of measured particle number size distribution. The dose rates show seasonal variations reflecting the physical characteristics (i.e., modal structure) of the particle number size distribution. An additional factor was the varying deposition fraction (DF) for different regions and different human activities (exercising versus resting). The total dose rate was 3 × 10⁹-65 × 10⁹ particles/h (PM_2.5 and PM₁₀ doses 1-22 µg/h and 9-210 µg/h; respectively) depending on the gender, activity, and season. Based on the particle number metrics, the inhaled deposited dose in the head, Tracheobronchial, and alveolar were 7-16%, 16-28%, and 56-76%; respectively. Based on the PM_2.5 metric, the corresponding dose rate was 9-41%,13-19%; and 46-72% respectively. As for the PM₁₀ metric, they were 25-75%, 7-35%, and 15-55%; respectively.

A global observational analysis to understand changes in air quality during exceptionally low anthropogenic emission conditions

This global study, which has been coordinated by the World Meteorological Organization Global Atmospheric Watch (WMO/GAW) programme, aims to understand the behaviour of key air pollutant species during the COVID-19 pandemic period of exceptionally low emissions across the globe. We investigated the effects of the differences in both emissions and regional and local meteorology in 2020 compared with the period 2015-2019. By adopting a globally consistent approach, this comprehensive observational analysis focuses on changes in air quality in and around cities across the globe for the following air pollutants PM_2.5, PM₁₀, PMC (coarse fraction of PM), NO₂, SO₂, NOx, CO, O₃ and the total gaseous oxidant (OX = NO₂ + O₃) during the pre-lockdown, partial lockdown, full lockdown and two relaxation periods spanning from January to September 2020. The analysis is based on in situ ground-based air quality observations at over 540 traffic, background and rural stations, from 63 cities and covering 25 countries over seven geographical regions of the world. Anomalies in the air pollutant concentrations (increases or decreases during 2020 periods compared to equivalent 2015-2019 periods) were calculated and the possible effects of meteorological conditions were analysed by computing anomalies from ERA5 reanalyses and local observations for these periods. We observed a positive correlation between the reductions in NO₂ and NOx concentrations and peoples' mobility for most cities. A correlation between PMC and mobility changes was also seen for some Asian and South American cities. A clear signal was not observed for other pollutants, suggesting that sources besides vehicular emissions also substantially contributed to the change in air quality. As a global and regional overview of the changes in ambient concentrations of key air quality species, we observed decreases of up to about 70% in mean NO₂ and between 30% and 40% in mean PM_2.5 concentrations over 2020 full lockdown compared to the same period in 2015-2019. However, PM_2.5 exhibited complex signals, even within the same region, with increases in some Spanish cities, attributed mainly to the long-range transport of African dust and/or biomass burning (corroborated with the analysis of NO₂/CO ratio). Some Chinese cities showed similar increases in PM_2.5 during the lockdown periods, but in this case, it was likely due to secondary PM formation. Changes in O₃ concentrations were highly heterogeneous, with no overall change or small increases (as in the case of Europe), and positive anomalies of 25% and 30% in East Asia and South America, respectively, with Colombia showing the largest positive anomaly of ~70%. The SO₂ anomalies were negative for 2020 compared to 2015-2019 (between ~25 to 60%) for all regions. For CO, negative anomalies were observed for all regions with the largest decrease for South America of up to ~40%. The NO₂/CO ratio indicated that specific sites (such as those in Spanish cities) were affected by biomass burning plumes, which outweighed the NO₂ decrease due to the general reduction in mobility (ratio of ~60%). Analysis of the total oxidant (OX = NO₂ + O₃) showed that primary NO₂ emissions at urban locations were greater than the O₃ production, whereas at background sites, OX was mostly driven by the regional contributions rather than local NO₂ and O₃ concentrations. The present study clearly highlights the importance of meteorology and episodic contributions (e.g., from dust, domestic, agricultural biomass burning and crop fertilizing) when analysing air quality in and around cities even during large emissions reductions. There is still the need to better understand how the chemical responses of secondary pollutants to emission change under complex meteorological conditions, along with climate change and socio-economic drivers may affect future air quality. The implications for regional and global policies are also significant, as our study clearly indicates that PM_2.5 concentrations would not likely meet the World Health Organization guidelines in many parts of the world, despite the drastic reductions in mobility. Consequently, revisions of air quality regulation (e.g., the Gothenburg Protocol) with more ambitious targets that are specific to the different regions of the world may well be required.

Evaluating the Theoretical Background of STOFFENMANAGER® and the Advanced REACH Tool

STOFFENMANAGER^® and the Advanced REACH Tool (ART) are recommended tools by the European Chemical Agency for regulatory chemical safety assessment. The models are widely used and accepted within the scientific community. STOFFENMANAGER^® alone has more than 37 000 users globally and more than 310 000 risk assessment have been carried out by 2020. Regardless of their widespread use, this is the first study evaluating the theoretical backgrounds of each model. STOFFENMANAGER^® and ART are based on a modified multiplicative model where an exposure base level (mg m⁻³) is replaced with a dimensionless intrinsic emission score and the exposure modifying factors are replaced with multipliers that are mainly based on subjective categories that are selected by using exposure taxonomy. The intrinsic emission is a unit of concentration to the substance emission potential that represents the concentration generated in a standardized task without local ventilation. Further information or scientific justification for this selection is not provided. The multipliers have mainly discrete values given in natural logarithm steps (…, 0.3, 1, 3, …) that are allocated by expert judgements. The multipliers scientific reasoning or link to physical quantities is not reported. The models calculate a subjective exposure score, which is then translated to an exposure level (mg m⁻³) by using a calibration factor. The calibration factor is assigned by comparing the measured personal exposure levels with the exposure score that is calculated for the respective exposure scenarios. A mixed effect regression model was used to calculate correlation factors for four exposure group [e.g. dusts, vapors, mists (low-volatiles), and solid object/abrasion] by using ~1000 measurements for STOFFENMANAGER^® and 3000 measurements for ART. The measurement data for calibration are collected from different exposure groups. For example, for dusts the calibration data were pooled from exposure measurements sampled from pharmacies, bakeries, construction industry, and so on, which violates the empirical model basic principles. The calibration databases are not publicly available and thus their quality or subjective selections cannot be evaluated. STOFFENMANAGER^® and ART can be classified as subjective categorization tools providing qualitative values as their outputs. By definition, STOFFENMANAGER^® and ART cannot be classified as mechanistic models or empirical models. This modeling algorithm does not reflect the physical concept originally presented for the STOFFENMANAGER^® and ART. A literature review showed that the models have been validated only at the ‘operational analysis’ level that describes the model usability. This review revealed that the accuracy of STOFFENMANAGER^® is in the range of 100 000 and for ART 100. Calibration and validation studies have shown that typical log-transformed predicted exposure concentration and measured exposure levels often exhibit weak Pearson’s correlations (r is <0.6) for both STOFFENMANAGER^® and ART. Based on these limitations and performance departure from regulatory criteria for risk assessment models, it is recommended that STOFFENMANAGER^® and ART regulatory acceptance for chemical safety decision making should be explicitly qualified as to their current deficiencies.

COVID-19 Pandemic Development in Jordan-Short-Term and Long-Term Forecasting

In this study, we proposed three simple approaches to forecast COVID-19 reported cases in a Middle Eastern society (Jordan). The first approach was a short-term forecast (STF) model based on a linear forecast model using the previous days as a learning data-base for forecasting. The second approach was a long-term forecast (LTF) model based on a mathematical formula that best described the current pandemic situation in Jordan. Both approaches can be seen as complementary: the STF can cope with sudden daily changes in the pandemic whereas the LTF can be utilized to predict the upcoming waves' occurrence and strength. As such, the third approach was a hybrid forecast (HF) model merging both the STF and the LTF models. The HF was shown to be an efficient forecast model with excellent accuracy. It is evident that the decision to enforce the curfew at an early stage followed by the planned lockdown has been effective in eliminating a serious wave in April 2020. Vaccination has been effective in combating COVID-19 by reducing infection rates. Based on the forecasting results, there is some possibility that Jordan may face a third wave of the pandemic during the Summer of 2021.

Technical control of nanoparticle emissions from desktop 3D printing

Material extrusion (ME) desktop 3D printing is known to strongly emit nanoparticles (NP), and the need for risk management has been recognized widely. Four different engineering control measures were studied in real-life office conditions by means of online NP measurements and indoor aerosol modeling. The studied engineering control measures were general ventilation, local exhaust ventilation (LEV), retrofitted enclosure, and retrofitted enclosure with LEV. Efficiency between different control measures was compared based on particle number and surface area (SA) concentrations from which SA concentration was found to be more reliable. The study found out that for regular or long-time use of ME desktop 3D printers, the general ventilation is not sufficient control measure for NP emissions. Also, the LEV with canopy hood attached above the 3D printer did not control the emission remarkably and successful position of the hood in relation to the nozzle was found challenging. Retrofitted enclosure attached to the LEV reduced the NP emissions 96% based on SA concentration. Retrofitted enclosure is nearly as efficient as enclosure attached to the LEV (reduction of 89% based on SA concentration) but may be considered more practical solution than enclosure with LEV.

Assessment of exposure determinants and exposure levels by using stationary concentration measurements and a probabilistic near-field/far-field exposure model

Background: The Registration, Evaluation, Authorization and Restriction of Chemicals (REACH) regulation requires the establishment of Conditions of Use (CoU) for all exposure scenarios to ensure good communication of safe working practices. Setting CoU requires the risk assessment of all relevant Contributing Scenarios (CSs) in the exposure scenario. A new CS has to be created whenever an Operational Condition (OC) is changed, resulting in an excessive number of exposure assessments. An efficient solution is to quantify OC concentrations and to identify reasonable worst-case scenarios with probabilistic exposure modeling. Methods: Here, we appoint CoU for powder pouring during the industrial manufacturing of a paint batch by quantifying OC exposure levels and exposure determinants. The quantification was performed by using stationary measurements and a probabilistic Near-Field/Far-Field (NF/FF) exposure model. Work shift and OC concentration levels were quantified for pouring TiO 2 from big bags and small bags, pouring Micro Mica from small bags, and cleaning. The impact of exposure determinants on NF concentration level was quantified by (1) assessing exposure determinants correlation with the NF exposure level and (2) by performing simulations with different OCs. Results: Emission rate, air mixing between NF and FF and local ventilation were the most relevant exposure determinants affecting NF concentrations. Potentially risky OCs were identified by performing Reasonable Worst Case (RWC) simulations and by comparing the exposure 95 th percentile distribution with 10% of the occupational exposure limit value (OELV). The CS was shown safe except in RWC scenario (ventilation rate from 0.4 to 1.6 1/h, 100 m 3 room, no local ventilation, and NF ventilation of 1.6 m 3/min). Conclusions: The CoU assessment was considered to comply with European Chemicals Agency (ECHA) legislation and EN 689 exposure assessment strategy for testing compliance with OEL values. One RWC scenario would require measurements since the exposure level was 12.5% of the OELV.

Particle number emission rates of aerosol sources in 40 German households and their contributions to ultrafine and fine particle exposure

More representative data on source-specific particle number emission rates and associated exposure in European households are needed. In this study, indoor and outdoor particle number size distributions (10-800 nm) were measured in 40 German households under real-use conditions in over 500 days. Particle number emission rates were derived for around 800 reported indoor source events. The highest emission rate was caused by burning candles (5.3 × 10¹³  h^-1 ). Data were analyzed by the single-parameter approach (SPA) and the indoor aerosol dynamics model approach (IAM). Due to the consideration of particle deposition, coagulation, and time-dependent ventilation rates, the emission rates of the IAM approach were about twice as high as those of the SPA. Correction factors are proposed to convert the emission rates obtained from the SPA approach into more realistic values. Overall, indoor sources contributed ~ 56% of the daily-integrated particle number exposure in households under study. Burning candles and opening the window leads to seasonal differences in the contributions of indoor sources to residential exposure (70% and 40% in the cold and warm season, respectively). Application of the IAM approach allowed to attribute the contributions of outdoor particles to the penetration through building shell and entry through open windows (26% and 15%, respectively).

Nano-Magnetic NiFe2O4 and Its Photocatalytic Oxidation of Vanillyl Alcohol-Synthesis, Characterization, and Application in the Valorization of Lignin

Here, we report on a phyto-mediated bimetallic (NiFe₂O₄) preparation using a Boswellia carterii extract, which was characterized by XRD, FT-IR, TGA, electron microscopy, magnetic spectroscopy, and Mössbauer spectroscopy measurements. The prepared nano-catalysts were tested for oxidation of lignin monomer molecules-vanillyl alcohol and cinnamyl alcohol. In comparison with previously reported methods, the nano NiFe₂O₄ catalysts showed high photocatalytic activity and selectivity, under visible light irradiation with a nitroxy radical initiator (2,2,6,6-tetramethylpiperidinyloxy or 2,2,6,6-tetramethylpiperidine 1-oxyl; TEMPO) at room temperature and aerobic conditions. The multifold advantages of the catalyst both in terms of reduced catalyst loading and ambient temperature conditions were manifested by higher conversion of the starting material.

Indoor Model Simulation for COVID-19 Transport and Exposure

Transmission of respiratory viruses is a complex process involving emission, deposition in the airways, and infection. Inhalation is often the most relevant transmission mode in indoor environments. For severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the risk of inhalation transmission is not yet fully understood. Here, we used an indoor aerosol model combined with a regional inhaled deposited dose model to examine the indoor transport of aerosols from an infected person with novel coronavirus disease (COVID-19) to a susceptible person and assess the potential inhaled dose rate of particles. Two scenarios with different ventilation rates were compared, as well as adult female versus male recipients. Assuming a source strength of 10 viruses/s, in a tightly closed room with poor ventilation (0.5 h-1), the respiratory tract deposited dose rate was 140-350 and 100-260 inhaled viruses/hour for males and females; respectively. With ventilation at 3 h-1 the dose rate was only 30-90 viruses/hour. Correcting for the half-life of SARS-CoV-2 in air, these numbers are reduced by a factor of 1.2-2.2 for poorly ventilated rooms and 1.1-1.4 for well-ventilated rooms. Combined with future determinations of virus emission rates, the size distribution of aerosols containing the virus, and the infectious dose, these results could play an important role in understanding the full picture of potential inhalation transmission in indoor environments.

Sensitivity Analysis for Predicting Sub-Micron Aerosol Concentrations Based on Meteorological Parameters

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.

Input-Adaptive Proxy for Black Carbon as a Virtual Sensor

Missing data has been a challenge in air quality measurement. In this study, we develop an input-adaptive proxy, which selects input variables of other air quality variables based on their correlation coefficients with the output variable. The proxy uses ordinary least squares regression model with robust optimization and limits the input variables to a maximum of three to avoid overfitting. The adaptive proxy learns from the data set and generates the best model evaluated by adjusted coefficient of determination (adjR²). In case of missing data in the input variables, the proposed adaptive proxy then uses the second-best model until all the missing data gaps are filled up. We estimated black carbon (BC) concentration by using the input-adaptive proxy in two sites in Helsinki, which respectively represent street canyon and urban background scenario, as a case study. Accumulation mode, traffic counts, nitrogen dioxide and lung deposited surface area are found as input variables in models with the top rank. In contrast to traditional proxy, which gives 20-80% of data, the input-adaptive proxy manages to give full continuous BC estimation. The newly developed adaptive proxy also gives generally accurate BC (street canyon: adjR² = 0.86-0.94; urban background: adjR² = 0.74-0.91) depending on different seasons and day of the week. Due to its flexibility and reliability, the adaptive proxy can be further extend to estimate other air quality parameters. It can also act as an air quality virtual sensor in support with on-site measurements in the future.

Elemental Contamination in Indoor Floor Dust and Its Correlation with PAHs, Fungi, and Gram+/- Bacteria

In this study, we performed elemental analysis for floor dust samples collected in Jordanian microenvironments (dwellings and educational building). We performed intercorrelation and cluster analysis between the elemental, polyaromatic hydrocarbon (PAH), and microorganism concentrations. In general, the educational building workshops had the highest elemental contamination. The age of the dwelling and its occupancy played a role on the elemental contamination level: older and more occupied dwellingshad greater contamination. The elemental contamination at a dwelling entrance was observed to be higher than in the living room. We found exceptionally high concentrations for Fe and Mn in the educational workshop and additionally, Hg, Cr, and Pb concentrations exceeded the limits set by the Canadian Council of Ministers of the Environment. According to the cluster analysis, we found three major groups based on location and contamination. According to the enrichment factor (EF) assessment, Al, Co, Mn, Ti, and Ba had EF < 2 (i.e., minimal enrichment) whereas P, S, Pb, Sb, Mo, Zn, Hg, and Cu had EF > 40 (i.e., extremely enriched). In contrast, Ca and P were geogenically enriched. Furthermore, significant Spearman correlations indicated nine subgroups of elemental contamination combined with PAHs and microbes.

Source specific exposure and risk assessment for indoor aerosols

Poor air quality is a leading contributor to the global disease burden and total number of deaths worldwide. Humans spend most of their time in built environments where the majority of the inhalation exposure occurs. Indoor Air Quality (IAQ) is challenged by outdoor air pollution entering indoors through ventilation and infiltration and by indoor emission sources. The aim of this study was to understand the current knowledge level and gaps regarding effective approaches to improve IAQ. Emission regulations currently focus on outdoor emissions, whereas quantitative understanding of emissions from indoor sources is generally lacking. Therefore, specific indoor sources need to be identified, characterized, and quantified according to their environmental and human health impact. The emission sources should be stored in terms of relevant metrics and statistics in an easily accessible format that is applicable for source specific exposure assessment by using mathematical mass balance modelings. This forms a foundation for comprehensive risk assessment and efficient interventions. For such a general exposure assessment model we need 1) systematic methods for indoor aerosol emission source assessment, 2) source emission documentation in terms of relevant a) aerosol metrics and b) biological metrics, 3) default model parameterization for predictive exposure modeling, 4) other needs related to aerosol characterization techniques and modeling methods. Such a general exposure assessment model can be applicable for private, public, and occupational indoor exposure assessment, making it a valuable tool for public health professionals, product safety designers, industrial hygienists, building scientists, and environmental consultants working in the field of IAQ and health.

Particle emission rates during electrostatic spray deposition of TiO2 nanoparticle-based photoactive coating

Here, we studied the particle release rate during Electrostatic spray deposition of anatase-(TiO₂)-based photoactive coating onto tiles and wallpaper using a commercially available electrostatic spray device. Spraying was performed in a 20.3m³ test chamber while measuring concentrations of 5.6nm to 31μm-size particles and volatile organic compounds (VOC), as well as particle deposition onto room surfaces and on the spray gun user hand. The particle emission and deposition rates were quantified using aerosol mass balance modelling. The geometric mean particle number emission rate was 1.9×10¹⁰s^-1 and the mean mass emission rate was 381μgs^-1. The respirable mass emission-rate was 65% lower than observed for the entire measured size-range. The mass emission rates were linearly scalable (±ca. 20%) to the process duration. The particle deposition rates were up to 15h^-1 for <1μm-size and the deposited particles consisted of mainly TiO₂, TiO₂ mixed with Cl and/or Ag, TiO₂ particles coated with carbon, and Ag particles with size ranging from 60nm to ca. 5μm. As expected, no significant VOC emissions were observed as a result of spraying. Finally, we provide recommendations for exposure model parameterization.

Floor dust bacteria and fungi and their coexistence with PAHs in Jordanian indoor environments

Floor dust samples were collected from Jordanian indoor environments (eight dwellings and an educational building) in Amman. Quantitative PCR (qPCR) analyses of selected fungal and bacterial groups were performed. The bacterial and fungal concentrations were also correlated with PAHs concentrations, which were previously measured in the same samples by using GC-MS. The bacterial and fungal concentrations varied significantly among and within the tested indoor environments. Based on the collected samples in the entrance area of the dwellings, the largest variation was found in Gram-negative bacteria and total fungi concentration. The lowest bacterial and fungal concentrations were found in the dwelling that was least occupied and the most recently built. At the educational building, the Gram-positive bacteria concentrations were lower than those observed in the dwellings. Unlike for bacteria, we observed significant negative correlation with some polycyclic aromatic hydrocarbons (PAHs). This calls for further studies investigating biodegradation of PAHs in house dust and presence of potentially health hazardous PAH metabolites. Since biocontamination in floor dust has been given relatively little to no attention in the MENA region we recommend that more extensive measurements be conducted in the future with chemical and biological analysis of floor dust contaminants and their exposure indoors.

Indoor-to-outdoor relationship of aerosol particles inside a naturally ventilated apartment - A comparison between single-parameter analysis and indoor aerosol model simulation

The indoor-to-outdoor relationship of aerosol particles is affected by several mechanisms including penetration, ventilation rate, dry deposition rate and sources. Understanding the effect of these factors is essential for a deeper knowledge of the indoor-to-outdoor relationship. In real-life conditions, it is difficult to analyze these factors in a naturally ventilated environment. In this study, a naturally ventilated and an occupied apartment was used to investigate the indoor-to-outdoor relationship of aerosol particles by applying two different techniques; single-parameter analysis and indoor aerosol model simulation. The indoor aerosol model simulation approach can describe the effect of these factors based on high time-resolution calculations and it is a powerful and robust approach. Single parameter analysis is very simple to apply but it is valid under certain conditions. In the absence of indoor activities (i.e. nighttime) and based on the particle number concentrations, the I/O ratio was <1 during spring but ~1.2 during winter. Based on the indoor aerosol model simulation results for the coarse fraction, the penetration factor (P) was 0.3-1, the ventilation rate (λ) was 0.1-2h^-1, and the deposition rate (λ_d) was ~0.15h^-1. The coarse particles concentration was strongly affected by indoor activities. During extreme mechanical activities (e.g. vacuum cleaning), the concentration increased by a factor of 9 (source strength ~160particles/h). During children play, the coarse fraction concentration increased by a factor of 3 (source strength ~10particles/h). Spraying an insect pesticide increased the coarse fraction concentration by a factor of 9 (source strength ~420particles/h). Water-pipe tobacco smoking produced huge amounts of both micron and submicron particulate matter; it caused the coarse fraction concentration to significantly increase by a factor of 18 (source strength ~140particles/h). The use of natural gas heater affected the submicron fraction only and did not affect the micron fraction.

Chemical investigation and quality of urban dew collections with dust precipitates

The quality and chemical composition of urban dew collections with dust precipitates without pre-cleaning of the collecting surface WSF (white standard foil) were investigated for 16 out of 20 collected samples with collected volumes ranging from 22 to 230 ml. The collection period was from March to July 2015 at an urban area, Jubaiha, which is located in the northern part of the capital city Amman, Jordan. The obtained results indicated the predominance of Ca²⁺ and SO₄^2- ions (ratio 2.2:1) that originated from Saharan soil dust; where the collected samples were alkaline (mean pH = 7.35) with high mineralization (429.22 mg/L) exceeding the previously reported dew values in Amman-Jordan. A relocation of NaCl and to a less extent Mg²⁺ from sea to land by Saharan wind is indicated by the percent sea-salt fraction calculations (over 100 and 52, respectively). The collected samples exhibited high total organic carbon (TOC) values ranging from 11.86 to 74.60 mg/L, presence of particulate settled material with turbidity ranging from 20.10 to 520.00 NTU, and presence of undesired elements like boron (mean = 1.48 mg/L) that made it different in properties from other dew water collections at clean surfaces, and exceeding the standard limits for drinking water for these parameters set by Jordanian Drinking Water standards (JS286/2015)/WHO standard. The quality of this water is more close to that for raw or agricultural water but if it is meant to be used as potable source of water, at least sand and activated charcoal filters are needed to purify it.

Occupational health risk assessment and exposure to floor dust PAHs inside an educational building

Polycyclic aromatic hydrocarbons (PAHs) settled in floor dust play an important role in human health. Although many studies investigated occupational exposure to PAHs, no attempts have been made to report PAHs concentrations as well as their health risk assessment inside an educational building in Jordan. Therefore, the main objective of this study is to report the PAHs concentrations in floor dust and evaluate their exposure and health risk inside the Department of Physics of the University of Jordan. The total PAHs concentrations ranged from 714 to 5246ng/g. The high concentrations were observed inside some offices, where tobacco smoking took place. One of those offices was previously renovated and some petrochemical liquids were used to remove the remaining glue from a previous carpet. Interestingly, the PAHs inside these offices were higher than those reported inside lecture rooms and the workshop area, where extensive activates of heavy machinery and use of petroleum products (such as lubricating oils). This implies that the health effects of exposure to tobacco smoking inside small micro-environmental places that are poorly ventilated can be very harmful. We also made a simple exposure and health risk assessment for the ingested dust (hand-to-mouth) by calculating the Estimated Daily Intake (EDI) and benzo(a)pyrene equivalent carcinogenic power (BaPE). The total EDI was less than 3.75ng/kg-bw/day whereas the BaPE was less than 385ng/g. These values are lower than what was reported in some previous studies in Europe and Asia.

Activity Pattern of Urban Adult Students in an Eastern Mediterranean Society

Knowledge of human activity patterns is needed in air pollution exposure and health risk assessment. However, human activity patterns have never been evaluated in the Eastern Mediterranean societies. Therefore, we investigated the activity pattern of 285 subjects (17-63 years) in Amman, Jordan during October to November, 2015. The subjects spent >80% of their time indoors during weekend days and >85% on workdays. They spent ~4.8% and ~5.7% in transportation during weekend days and workdays, respectively. Males had a different activity pattern than females on weekend days, but both genders had similar activity patterns on workdays. On workdays, males spent less time indoors than females. The activity pattern found in this study is a bit different than that for North Americans and Europeans, who spend more time indoors and in transit. The activity pattern found in this study was very different than that observed for Koreans, who spent about 59% and 67% indoors on workdays and weekend, respectively. The main outcomes of this survey can be utilized in human exposure studies. This study and the upcoming future studies have been encouraged and supported by the regional WHO office in Amman.

Exposure to airborne particles and volatile organic compounds from polyurethane molding, spray painting, lacquering, and gluing in a workshop

Due to the health risk related to occupational air pollution exposure, we assessed concentrations and identified sources of particles and volatile organic compounds (VOCs) in a handcraft workshop producing fishing lures. The work processes in the site included polyurethane molding, spray painting, lacquering, and gluing. We measured total VOC (TVOC) concentrations and particle size distributions at three locations representing the various phases of the manufacturing and assembly process. The mean working-hour TVOC concentrations in three locations studied were 41, 37, and 24 ppm according to photo-ionization detector measurements. The mean working-hour particle number concentration varied between locations from 3000 to 36,000 cm⁻³. Analysis of temporal and spatial variations of TVOC concentrations revealed that there were at least four substantial VOC sources: spray gluing, mold-release agent spraying, continuous evaporation from various lacquer and paint containers, and either spray painting or lacquering (probably both). The mold-release agent spray was indirectly also a major source of ultrafine particles. The workers’ exposure can be reduced by improving the local exhaust ventilation at the known sources and by increasing the ventilation rate in the area with the continuous source.

Characterization of exposure to carbon nanotubes in an industrial setting

While production and use of carbon nanotubes (CNTs) is increasing, workers exposure to CNTs is expected to increase as well, with inhalation being potentially the main pathway for uptake. However, there have been few studies reporting results about workers' personal exposure to CNTs. In this study, worker exposure to single-walled CNTs (SWCNTs) during the production of conductive films in a modern up-scaling factory was assessed. Particulate matter concentrations (2.5-10 μm) and concentrations of CO and CO2 were monitored by using real-time instruments. Workers' exposure levels to SWCNTs were qualitatively estimated by analyzing particle samples by transmission electron microscopy (TEM). TEM samples identified high aspect ratio (length/width > 500) SWCNTs in workplace air. SWCNT concentrations estimated from micrographs varied during normal operation, reactor use without local exhaust ventilation (LEV), and cleaning between 1.7×10(-3), 5.6 and 6.0×10(-3) SWCNT cm(-3), respectively. However, during cleaning it was unclear whether the SWCNTs originated from the cleaning itself or from other reactor openings. We were unable to quantify the SWCNT emissions with online particle instrumentation due to the SWCNT low concentrations compared to background particle concentrations, which were on average 2.6±1.1×10(3)cm(-3). However, CO concentrations were verified as a good indicator of fugitive emissions of SWCNTs. During normal operation, exposure levels were well below proposed limit values (1.0×10(-2) fibers cm(-3) and 1 µg m(-3)) when LEV was used. Based on the results in this study, the analysis of TEM grids seems to be the only direct method to detect SWCNTs in workplace air.

Range-finding risk assessment of inhalation exposure to nanodiamonds in a laboratory environment

This study considers fundamental methods in occupational risk assessment of exposure to airborne engineered nanomaterials. We discuss characterization of particle emissions, exposure assessment, hazard assessment with in vitro studies, and risk range characterization using calculated inhaled doses and dose-response translated to humans from in vitro studies. Here, the methods were utilized to assess workers' risk range of inhalation exposure to nanodiamonds (NDs) during handling and sieving of ND powder. NDs were agglomerated to over 500 nm particles, and mean exposure levels of different work tasks varied from 0.24 to 4.96 µg·m(-3) (0.08 to 0.74 cm(-3)). In vitro-experiments suggested that ND exposure may cause a risk for activation of inflammatory cascade. However, risk range characterization based on in vitro dose-response was not performed because accurate assessment of delivered (settled) dose on the cells was not possible. Comparison of ND exposure with common pollutants revealed that ND exposure was below 5 μg·m(-3), which is one of the proposed exposure limits for diesel particulate matter, and the workers' calculated dose of NDs during the measurement day was 74 ng which corresponded to 0.02% of the modeled daily (24 h) dose of submicrometer urban air particles.

Modeling regional deposited dose of submicron aerosol particles

We developed a simple model to calculate the regional deposited dose of submicron aerosol particles in the respiratory system. This model incorporates measured outdoor and modeled indoor particle number size distributions, detailed activity patterns of three age groups (teens, adults, and the elderly), semi-empirical estimation of the regional deposition fraction, hygroscopic properties of urban aerosols, and reported breathing minute volumes. We calculated the total and regional deposited dose based on three concentration metrics: particle number (PN), mass (PM), and surface area (PSA). The 24-h total deposited dose of fine particles in adult males was around 40 μg (57×109 particles, 8×102 mm(2)) and 41 μg (40×109 particles, 8×102 mm(2)) on workdays and weekends, respectively. The total and regional 24-h deposited dose based on any of the metrics was at most 1.5 times higher in males than in females. The deposited dose values in the other age groups were slightly different than in adults. Regardless of the particle size fraction or the deposited dose metric, the pulmonary/alveolar region received the largest fraction of the deposited dose. These values represent the lowest estimate of the deposited dose and they are expected to be higher in real-life conditions after considering indoor sources of aerosol particles and spatial variability of outdoor aerosols. This model can be extended to youngsters (<12 years old) after gaining accurate information about the deposition fraction inside their respiratory system and their breathing pattern. This investigation is foreseen to bridge the gap between exposure and response in epidemiological studies.

Association of ozone and particulate air pollution with out-of-hospital cardiac arrest in Helsinki, Finland: evidence for two different etiologies

Out-of-hospital cardiac arrest (OHCA) has been previously associated with exposure to particulate air pollution. However, there is uncertainty about the agents and mechanisms that are involved. We aimed to determine the association of gases and particulates with OHCA, and differences in pollutant effects on OHCAs due to acute myocardial infarction (AMI) vs those due to other causes. Helsinki Emergency Medical Services provided data on OHCAs of cardiac origin (OHCA_Cardiac). Hospital and autopsy reports determined whether OHCAs were due to AMI (OHCA_MI) or other cardiac causes (OHCA_Other). Pollutant data was obtained from central ambient monitors. A case-crossover analysis determined odds ratios (ORs) for hourly lagged exposures (Lag 0-3) and daily lagged exposures (Lag 0d-3d), expressed per interquartile range of pollutant level. For OHCA_Cardiac, elevated ORs were found for PM(2.5) (Lag 0, 1.07; 95% confidence interval (CI): 1.01-1.13) and ozone (O(3)) (Lag 2d, 1.18; CI: 1.03-1.35). For OHCA_MI, elevated ORs were found for PM(2.5) (Lag 0, 1.14; CI: 1.03-1.27; Lag 0d, 1.17; CI: 1.03-1.33), accumulation mode particulate (Acc) (Lag 0d, 1.19; CI: 1.04-1.35), NO (Lag 0d, 1.07; CI: 1.01-1.13), and ultrafine particulate (Lag 0d, 1.27; CI: 1.05-1.54). For OHCA_Other, elevated ORs were found only for O(3) (Lag 1d, 1.26; CI: 1.07-1.48; Lag 2d, 1.30; CI: 1.11-1.53). Results from two-pollutant models, with one of the pollutants either PM(2.5) or O(3), suggested that associations were primarily due to effects of PM(2.5) and O(3), rather than other pollutants. The results suggest that air pollution triggers OHCA via two distinct modes: one associated with particulates leading to AMI and one associated with O(3) involving etiologies other than AMI, for example, arrhythmias or respiratory insufficiency.

Activity pattern of a selected group of school occupants and their family members in Helsinki-Finland

The daily time-spent in different environments is an important factor in calculation of personal exposure to air pollutants. Despite this importance, the amount of research done on this topic is rather limited, especially in North Europe where the climate is rather cold. In this study, we gathered detailed information via a standard questionnaire to report the residence time and place of 167 subjects (between 2 and 93 years old) lived in Helsinki during three time periods in winter and spring 2009. Subjects spent 81%-92% of their time indoors and up to ~15% of their time outdoors. The daily time-spent in different environments was affected by several factors: ambient temperature, type of day (workday or weekend/holiday), gender, and age. Therefore, the differences occur individually and can be explained by these factors. For example, subjects spent more time at home on weekends than workdays because obviously the majority of our subjects did not have work on weekends. The time-spent at kindergarten/school/work increased with age until retirement. Females spent more time at home than males. After all, the activity pattern found in this study is rather similar to those previously reported in Germany and North America.

Concept to estimate regional inhalation dose of industrially synthesized nanoparticles

The use of nanoparticles (NPs) in industry is increasing rapidly, but knowledge of the occupational health and safety aspects of NPs is still limited. This is because quantitative NP exposure levels are scarce, and the metrics to describe doses are unclear. This study presents one method for estimating workers' calculated regional inhalation dose of deposited particles from size-fractionated concentrations. It was applied to estimate workers' regional inhalation dose rates and doses separately for NPs and NPs with background particles during NP synthesis. Dose analysis was performed in units of particle number (particles and particles min(-1)), active surface area (μm(2) and μm(2) min(-1)), and mass (ng and ng min(-1)) for three respiratory regions: head airways, tracheobronchial, and alveolar. It was found that in NP synthesis NPs were deposited mainly in the alveolar region in all units. However, when the dose of all particles was examined, it was found that dose and the main deposition region were mainly defined by the synthesized NPs for particle number, as active surface area was described by both NPs and background particles, and mass by background particles. This study provides fundamental data for NP inhalation exposure risk assessment, regulations, dose metrics for NP synthesis, and a basis for defining metrics of dose-biological response and helps us understand the magnitude of doses in NP synthesis. It also illustrates the necessity to obtain size-fractionated measurements of NP concentrations to support accurate dose estimation.

Road dust emissions from paved roads measured using different mobile systems

Very few real-world measurements of road dust suspension have been performed to date. This study compares two different techniques (referred to as Sniffer and Emma) to measure road dust emissions. The main differences between the systems are the construction of the inlet, different instruments for recording particulate matter (PM) levels, and different loads on the wheel axes (the weight of Sniffer was much higher than that of Emma). Both systems showed substantial small-scale variations of emission levels along the road, likely depending on-road surface conditions. The variations observed correlated quite well, and the discrepancies are likely a result of variations in dust load on the road surface perpendicular to the driving direction that cause variations in the measurements depending on slightly different paths driven by the two vehicles. Both systems showed a substantial influence on the emission levels depending on the type of tire used. The summer tire showed much lower suspension than the winter tires (one nonstudded and one studded). However, the relative importance of the nonstudded versus studded tire was rather different. For the ratio of studded/nonstudded, Emma shows higher values on all road sections compared with Sniffer. Both techniques showed increased emission levels with increasing vehicle speed. When the speed increased from 50 to 80 km hr(-1), the relative concentrations increased by 30-170% depending on the tire type and dust load. However, for road sections that were very dirty, Sniffer showed a much higher relative increase in the emission level with the nonstudded tire. Sniffer's absolute concentrations were mostly higher than Emma's. Possible reasons for the differences are discussed in the paper. Both systems can be used for studying relative road dust emissions and for designing air quality management strategies.

Facing the key workplace challenge: assessing and preventing exposure to nanoparticles at source

Nanomaterials present new challenges to understanding, predicting, and managing potential health risks in occupational environments. In this study, we characterize the key physical processes related to formation and growth of nanoparticles. The main focus is on various occupational environments, as these are known to be major environments with nanoparticles in indoor air. The protection of people potentially to be exposed to nanoparticles is one of the key issues in terms of risk assessment and prevention. Two of the main protection techniques that are discussed and characterized are ventilation and filtration, which are widely used in practical applications.

131. SIRT3 IN OVARIAN CELLS IS ALTERED BY MATERNAL AGE AND OVARIAN RESERVE

Maternal age and reduced AMH levels affect the follicular environment and consequently oocyte viability. The Sirtuin family of protein deacetylases are able to regulate various cellular functions involved in the ageing process in other tissues. In particular, SIRT3 is related to longevity in several cell types and regulates mitochondrial function, however, its presence and role in ovarian cells remains unknown. This study therefore, investigated the presence of SIRT3 in granulosa and cumulus cells, from patients undergoing IVF, and determined the impact of maternal age and low AMH on SIRT3 levels. Granulosa and cumulus cells were collected from women (n = 36), after informed consent, and classified into 3 groups; A (<35 years, normal AMH), B (>40 years (advanced maternal age), normal AMH) and C (<35 years, low AMH). The presence of SIRT3 was determined by q-PCR (expressed as fold-change) or immunohistochemistry. SIRT3 was present in the ovarian cells of all patients analysed. SIRT3 gene expression was reduced in granulosa cells from women with low AMH (0.67 ± 0.17) compared to women with normal AMH (1.00 ± 0.23; P < 0.05). In cumulus cells, levels were reduced with advanced maternal age (0.81 ± 0.08) compared to women <35 years (1.00 ± 0.22; P < 0.05). SIRT3 protein co-localised with mitochondria in the ovarian cells, confirming previous findings for other cell types. In comparison to women <35 years with normal AMH, image analysis determined that SIRT3 protein levels were significantly reduced in the granulosa and cumulus cells from women of advanced maternal age by 21.4% and 31.8% and in women with low AMH by 34.1% and 47.2% respectively. This is the first study to demonstrate SIRT3 presence in human ovarian cells. The observation that SIRT3 levels are altered by advanced maternal age or low AMH (reduced ovarian reserve) implicate its role in ovarian ageing and plausibly in the decrease in oocyte viability observed in these women.

Sentinel node SPECT-CT in breast cancer. Can we expect any additional and clinically relevant information?

The AIM of this study was to determine the additional value of SPECT/CT in sentinel node scintigraphy in breast cancer. Furthermore, it was our question to determine, whether the low-dose computed tomography component (LD-CT) can be used for axillary lymph node staging of clinically negative patients.

PATIENTS, METHODS

51 patients with invasive breast cancer <3 cm in diameter were included in our prospective investigation. SPECT/CT was performed on a dedicated scanner 30 minutes after subareolar injection of (99m)Tc-Nanocoll. Axillary staging with CT(LD) was performed using standard CT-criteria. SLN were allocated to an axillary level using SPECT alone and SPECT/CT. Additionally, the number of SLN on CT(LD) corresponding to the scintigraphic hot node was notified for each patient and compared to the number of SLN found with the gamma probe.

RESULTS

In 45/51 evaluable patients SLN could be localised in level I in 43 patients and in level II in two patients (all positive) using SPECT-CT, whereas a clear allocation could not be obtained by SPECT alone. The number of SLN was discrepant between SPECT and CT(LD) in 13/45 patients. The number of SLN detected with the gamma probe (n = 68) not significantly differed from the number of SLN detected by CT(LD) (n = 65) but was significantly higher than with SPECT (n = 51). CT(LD) yielded a sensitivity of 35.7%, a specificity of 83.9%, a positive predictive value (PPT) of 50%, a negative predictive value (NPV) of 74.3% and a diagnostic accuracy of 68.9% for axillary staging with CT(LD).

CONCLUSION

The additional information of SPECT/CT allows a more accurate characterization of the SN concerning size, depth and anatomical location. CT(LD) when performed during (99m)Tc-Nanocoll sentinel-SPECT/CT is not suitable for axillary staging in breast cancer patients with clinical negative axilla due to its low sensitivity and moderate specificity. Therefore, it does not influence the decision for SNB or ALND. The limited resolution of SPECT leads to an underestimation of the number of SLN compared to CT(LD) and the gamma probe.