Environmental and Health Effects of Ventilation in Subway Stations: A Literature Review

Carbon based nanocomposites, surface functionalization as a promising material for VOCs (volatile organic compounds) treatment

Urban residential and industrial growth development affects sustainable and healthful indoor environments. Environmental issues are a global problem. The deterioration of indoor air quality has prompted the creation of several air cleansing techniques. This review explains how carbon-based materials have influenced the development of air purification systems using photocatalysis. These carbon-based materials offer unique properties and advantages in VOC removal processes. Biochar, produced from biomass pyrolysis, provides an environmentally sustainable solution with its porous structure and carbon-rich composition. Carbon quantum dots, with their quantum confinement effects and tunable surface properties, show promise in VOC sensing and removal applications. Polymers incorporating reduced graphene oxide demonstrate enhanced adsorption capabilities owing to the synergistic effects of graphene and polymer matrices. Activated carbon fibers, characterized by their high aspect ratio and interconnected porosity, provide efficient VOC removal with rapid kinetics. With their unique electronic and structural properties, graphitic carbon nitrides offer opportunities for photocatalytic degradation of VOCs under visible light. Catalysts integrated with MXene, a two-dimensional nanomaterial, exhibit enhanced catalytic activity for VOC oxidation reactions. Using various carbon-based materials in VOC removal showcases the versatility and effectiveness of carbon-based approaches in addressing environmental challenges associated with indoor air pollution. Metal-organic-framework materials are carbon-based compounds. It examines the correlation between VOC mineralization and specific characteristics of carbon materials, including surface area, adsorption capability, surface functional groups, and optoelectronic properties. Discussions include the basics of PCO, variables influencing how well catalysts degrade, and degradation mechanisms. It explores how technology will improve in the future to advance studies on healthy and sustainable indoor air quality.

Exposure to fine particulate matter in the New York City subway system during home-work commute

The New York City (NYC) subway system accommodates 5.5 million daily commuters, and the environment within the subway is known to have high concentrations of fine particulate matter (PM2.5) pollution. Naturally, subway air pollution varies among individuals according to their mobility patterns, introducing the possibility of inequality in PM2.5 exposure. This study aims to evaluate individual and community-level exposure to subway PM2.5. We simulated the intracity home-to-work trip patterns using the Longitudinal Employer-Household Dynamics (LEHD) records of 3.1 million working commuters across 34,169 census blocks in four boroughs (Manhattan, Brooklyn, Queens, and the Bronx) of NYC. We incorporated the on-platform and on-train measured PM2.5 concentration data for the entire subway system. The mean underground platform concentration in the city was 139 μg/m3 with a standard deviation of 25 μg/m3, while the on-train concentration when underground was 99 μg/m3 with a standard deviation of 21 μg/m3. Using a network model, we determined the exposure of individual commuters during their daily home-work trips. We quantified the mean per capita exposure at the census block level by considering the proportion of workers within the blocks who rely on the subway for their work commute. Results indicate statistically significant weak positive correlation between elevated subway PM2.5 exposure and economically disadvantaged and racial minority groups.

Long-term exposure to PM10 and respiratory health among Parisian subway workers

Exposure to ambient PM10 may increase the risk of chronic obstructive pulmonary disease (COPD) and lung function decline. We evaluated the long-term exposure to PM10 and its relationship with COPD prevalence and lung function in Parisian subway workers. Participants were randomly selected from a 15,000-subway worker cohort. Individual annual external exposure to PM10 (ePM10) was estimated using a company-specific job-exposure-matrix based on PM10 measurements conducted between 2004 and 2019 in the Parisian subway network. Mean annual inhaled PM10 exposure (iPM10) was modeled as function of ePM10 exposure, inhalation rate, and filtration efficiency of the respiratory protection used. COPD diagnosis was performed in March-May 2021 based on post-bronchodilator spirometry. The relationship between iPM10 and outcomes was assessed using logistic and linear regression models, adjusted for exposure duration and potential confounders. Amongst 254 participants with complete data, 17 were diagnosed as COPD. The mean employment duration was 23.2 ± 7.3years, with annual mean ePM10 of 71.8 ± 33.7 μg/m3 and iPM10 of 0.59 ± 0.27 μg/shift, respectively. A positive but statistically non-significant association was found for COPD prevalence with iPM10 (OR = 1.034, 95%-CI = 0.781; 1.369, per 100 ng/shift) and ePM10 (OR = 1.029, 95%-CI = 0.879; 1.207, per 10 μg/m3). No decline in lung function was associated with PM10 exposure. However, forced expiratory volume during the first second and forced vital capacity lower than normal were positively associated with exposure duration (OR = 1.125, 95%-CI = 1.004; 1.260 and OR = 1.171, 95%-CI = 0.989; 1.386 per year, respectively). Current smoking was strongly associated with COPD prevalence (OR = 6.85, 95%-CI = 1.87; 25.10) and most lung function parameters. This is the first study assessing the relationship between long-term exposure to subway PM10 and respiratory health in subway workers. The risk estimates related with subway PM10 exposure are compatible with those related to outdoor PM10 exposure in the large recent studies. Large cohorts of subway workers are necessary to confirm these findings.

Job Exposure Matrix, a Solution for Retrospective Assessment of Particle Exposure in a Subway Network and Their Long-Term Effects

INTRODUCTION

Health effects after long-term exposure to subway particulate matter (PM) remain unknown due to the lack of individual PM exposure data. This study aimed to apply the job exposure matrix (JEM) approach to retrospectively assess occupational exposure to PM in the Parisian subway.

METHODS

Job, the line and sector of the transport network, as well as calendar period were four JEM dimensions. For each combination of these dimensions, we generated statistical models to estimate the annual average PM10 concentration using data from an exhaustive inventory of the PM measurement campaigns conducted between 2004 and 2020 in the Parisian subway and historical data from the Parisian air pollution monitoring network. The resulting JEM and its exposure estimates were critically examined by experts using the uncertainty analysis framework.

RESULTS

The resulting JEM allows for the assignment of the estimated annual PM10 concentration to three types of professionals working in the subway: locomotive operators, station agents, and security guards. The estimates' precision and validity depend on the amount and quality of PM10 measurement data used in the job-, line-, and sector-specific models. Models using large amounts of personal exposure measurement data produced rather robust exposure estimates compared to models with lacunary data (i.e., in security guards). The analysis of uncertainty around the exposure estimates allows for the identification of the sources of uncertainty and parameters to be addressed in the future in order to refine and/or improve the JEM.

CONCLUSIONS

The JEM approach seems relevant for the retrospective exposure assessment of subway workers. When applied to available data on PM10, it allows for the estimation of this exposure in locomotive operators and station agents with an acceptable validity. Conversely, for security guards, the current estimates have insufficient validity to recommend their use in an epidemiological study. Therefore, the current JEM should be considered as a valid prototype, which shall be further improved using more robust measurements for some jobs. This JEM can also be further refined by considering additional exposure determinants.

Inequality in behavioural heat adaptation: an empirical study with mobility data from the transport system in New York City, NY, USA

BACKGROUND

Heat exposure, which can negatively affect human health and wellbeing, is heterogeneous within US cities. However, little is known about who can avoid heat stress by adjusting their everyday behaviour. We aimed to analyse the effect of ambient temperature on mobility, specifically subway (ie, the underground railway system) use, in New York City, NY, USA, during 2014-19.

METHODS

For this empirical study, subway use across New York City was measured with turnstile data from the New York City Metropolitan Transportation Authority between Jan 1, 2014, and Dec 31, 2019. Passenger numbers were then aggregated to the zip code tabulation area (ZCTA) level. Daily observational climate data were obtained from the US National Weather Service between Jan 1, 2014, and Dec 31, 2019. Socioeconomic data at the ZCTA level originated from the American Community Survey 2019. We extracted data on population age, ethnicity, commuting, employment, median household income, rent, and health-insurance coverage. We used a fixed-effects panel-regression model to assess the influence of temperature on subway use in New York City, which was the main outcome of our study.

FINDINGS

We obtained data for 438 subway stations across New York City. After data cleaning and preprocessing, the final aggregated data sample consisted of 238 508 instances of subway use in 1955 days across 6 years for 122 ZCTAs, with 168 days missing in the raw data and 67 days removed as outliers. The results of the fixed-effects panel-regression analysis showed a strong, non-linear effect of daily maximum temperature on subway use. Subway use was highest at 11·5°C and substantially decreased for temperatures that were colder and warmer than that, with reductions reaching 6·5% (95% CI 2·5-10·5) for the coldest temperature (ie, -6·5°C) and 10·5% (6·0-14·0) for the hottest temperature (ie, 34·5°C). Reductions differed between weekdays and weekends, when residents generally had more freedom to adjust their behaviour. Neighbourhoods that were at a socioeconomic disadvantage experienced smaller or no reductions in mobility in heat; mobility increased in neighbourhoods with beach access.

INTERPRETATION

Our study showed that temperature had a strong, non-linear effect on subway use, but the magnitude of the effect on subway use was heterogeneous across areas of the city on warm days. Weaker avoidance of heat stress correlated with less privilege, indicating compounding health risks. Everyday behavioural adaptation to heat is therefore an effect pathway that contributes to unequal heat effects and should be explored in future research.

FUNDING

The Volkswagen Foundation and the Werner Siemens Foundation.

Subway station dust-induced pulmonary inflammation may be due to the dysfunction of alveolar macrophages: Possible contribution of bound elements

With its increasing value as a means of public transportation, the health effects of the air in subway stations have attracted public concern. In the current study, we investigated the pulmonary toxicity of dust collected from an air purifier installed on the platform of the busiest subway station in Seoul. We found that the dust contained various elements which are attributable to the facilities and equipment used to operate the subway system. Particularly, iron (Fe), chromium (Cr), zirconium (Zr), barium (Ba), and molybdenum (Mo) levels were more notable in comparison with those in dust collected from the ventilation chamber of a subway station. To explore the health effects of inhaled dust, we first instilled via the trachea in ICR mice for 13 weeks. The total number of pulmonary macrophages increased significantly with the dose, accompanying hematological changes. Dust-laden alveolar macrophages and inflammatory cells accumulated in the perivascular regions in the lungs of the treated mice, and pulmonary levels of CXCL-1, TNF-α, and TGF-β increased clearly compared with the control. The CCR5 and CD54 level expressed on BAL cell membranes was also enhanced following exposure to dust, whereas the CXCR2 level tended to decrease in the same samples. In addition, we treated the dust to alveolar macrophages (known as dust cells), lysosomal and mitochondrial function decreased, accompanied by cell death, and NO production was rapidly elevated with concentration. Moreover, the expression of autophagy- (p62) and anti-oxidant (SOD-2)-related proteins increased, and the expression of inflammation-related genes was dramatically up-regulated in the dust-treated cells. Therefore, we suggest that dysfunction of alveolar macrophages may importantly contribute to dust-induced inflammatory responses and that the exposure concentrations of Cr, Fe, Mo, Zr, and Ba should be considered carefully when assessing the health risks associated with subway dust. We also hypothesize that the bound elements may contribute to dust-induced macrophage dysfunction by inhibiting viability.

Particulate matter concentration and composition in the New York City subway system

This study investigated the concentration and composition of particulate matter (PM2.5) in the New York City subway system. Realtime measurements, at a one-second cadence, and gravimetric measurements were performed inside train cars along 300 kilometers of nine subway lines, as well as on 333 platforms from 287 subway stations. The mean (±SD) PM2.5 concentration on the underground platforms was 142 ± 69 μg/m3 versus 29 ± 20 μg/m3 for aboveground stations. The average Concentrations inside train cars were 88 ± 14 μg/m3 when traveling through underground tunnels and platforms and 29 ± 31 μg/m3 while on aboveground tracks. The particle composition analysis of filtered samples was done using X-ray fluorescence (XRF), revealing that iron made up approximately 43% of the total PM2.5 mass on station platforms, around 126 times higher than the outdoor ambient iron concentration. Other trace elements include silicon, sulfur, copper, nickel, aluminum, calcium, barium, and manganese. Considering the very high iron content, the comparative analysis of the measured concentration versus the standards set by the Environmental Protection Agency (US EPA) is questionable since those limits are largely based on particulate matter from fossil fuel combustion. Health impact analysis of iron-based particles will complement the study results presented here.

Transmission mitigation of COVID-19: Exhaled contaminants removal and energy saving in densely occupied space by impinging jet ventilation

The pandemic of COVID-19 and its transmission ability raise much attention to ventilation design as indoor-transmission outstrips outdoor-transmission. Impinging jet ventilation (IJV) systems might be promising to ventilate densely occupied large spaces due to their high jet momentum. However, their performances in densely occupied spaces have rarely been explored. This study proposes a modified IJV system and evaluates its performance numerically in a densely occupied classroom mockup. A new assessment formula is also proposed to evaluate the nonuniformity of target species CO₂. The infector is assumed as the manikin with the lowest tracer gas concentration in the head region. The main results include: a) Indoor air quality (IAQ) in the classroom is improved significantly compared with a mixing ventilation system, i.e., averaged CO₂ in the occupied zone (OZ) is reduced from 1287 ppm to 1078 ppm, the OZ-averaged mean age of air is reduced from 439 s to 177 s; b) The mean infection probability is reduced from 0.047% to 0.027% with an infector, and from 0.035% to 0.024% with another infector; c) Cooling coil load is reduced by around 21.0%; d) Overall evaluation indices meet the requirements for comfortable environments, i.e., the temperature difference between head and ankle is within 3 °C and the OZ-averaged predictive mean vote is in the range of -0.5 - 0.5; e) Thermal comfort level and uniformity are decreased, e.g., overcooling near diffuser at ankle level. Summarily, the target system effectively improves IAQ, reduces exhaled-contaminant concentration in head regions, and saves energy as well.

CO2 in indoor environments: From environmental and health risk to potential renewable carbon source

In the developed world, individuals spend most of their time indoors. Poor Indoor Air Quality (IAQ) has a wide range of effects on human health. The burden of disease associated with indoor air accounts for millions of premature deaths related to exposure to Indoor Air Pollutants (IAPs). Among them, CO₂ is the most common one, and is commonly used as a metric of IAQ. Indoor CO₂ concentrations can be significantly higher than outdoors due to human metabolism and activities. Even in presence of ventilation, controlling the CO₂ concentration below the Indoor Air Guideline Values (IAGVs) is a challenge, and many indoor environments including schools, offices and transportation exceed the recommended value of 1000 ppm_v. This is often accompanied by high concentration of other pollutants, including bio-effluents such as viruses, and the importance of mitigating the transmission of airborne diseases has been highlighted by the COVID-19 pandemic. On the other hand, the relatively high CO₂ concentration of indoor environments presents a thermodynamic advantage for direct air capture (DAC) in comparison to atmospheric CO₂ concentration. This review aims to describe the issues associated with poor IAQ, and to demonstrate the potential of indoor CO₂ DAC to purify indoor air while generating a renewable carbon stream that can replace conventional carbon sources as a building block for chemical production, contributing to the circular economy.

Data Analysis and Optimization of Thermal Environment in Underground Commercial Building in Zhengzhou, China

Underground commercial buildings have received increasing attention as an emerging place of consumption. However, previous studies on underground commercial buildings have mainly focused on the impact of a specific environment on comfort or energy consumption. Few studies have been conducted from the perspective of functional use. The purpose of this paper is to investigate, in terms of functional angles, the indoor thermal environment and air quality of an underground commercial building in Zhengzhou, China, and put forward an optimal control strategy of ventilation organization. The results showed that the relative humidity of the underground shopping mall was generally above 60%, and the average temperature of 29.1 °C led to a thermal comfort problem in the catering area in summer. Meanwhile, the concentration of CO2 exceeded the allowed figures during the peak of the customer flow rate, and PM2.5 concentration in the catering area also exceeded the standard, by 43.3% and 33.3%, respectively. Furthermore, to solve the indoor thermal environment and air quality problems found in the field measurements, this study assessed the air distribution by adopting three different air supply schemes for the catering area. Optimization results showed that compared with the ceiling supply, the side supply scheme kept the air temperature 0.4 °C cooler in summer and 0.5 °C warmer in winter. The temperature uniformity increased by 5.4% and 3.7%, and the velocity uniformity increased by 6.5% and 8.8%, respectively. This study can provide theoretical support for thermal environment construction and ventilation organization control of underground commercial buildings.

Seasonal variations of the airborne microbial assemblages of the Seoul subway, South Korea from 16S and ITS gene profiles with chemical analysis

In this study, we determined the seasonal airborne microbial diversity profiles at SMRT stations by sequencing the 16S rRNA and ITS. Particulate matter samples were collected from air purifiers installed in the platform area of the SMRT subway stations. Three stations that included the most crowded one were selected for the sampling. The sampling was done at each season during 2019. After extracting the total DNA from all seasonal samples, PCR was performed with Illumina overhang adapter primers for the V3-V4 region of the 16S rRNA gene and ITS2 region of the ITS gene. The amplified products were further purified, and sequencing libraries were made. Sequencing was carried with the Illumina Miseq Sequencing system (Illumina, USA) followed by in-depth diversity analyses. The elemental composition of the particulate matter samples collected from the different subway stations were obtained using a WD-XRF spectrometer. The SMRT microbiome showed extensive taxonomic diversity with the most common bacterial genera at the subway stations associated with the skin. Overall, the stations included in this study harbored different phylogenetic communities based on α- and β-diversity comparisons. Microbial assemblages also varied depending upon the season in which the samples were taken and the station. Major elements present at the subway stations were from aerosols generated between wheels and brake cushions and between the catenaries and the pantographs. This study shows that the microbial composition of the SMRT subway stations comes from a diverse combination of environmental and human sources, the season and the lifestyle of commuters.

Close contact behavior-based COVID-19 transmission and interventions in a subway system

During COVID-19 pandemic, analysis on virus exposure and intervention efficiency in public transports based on real passenger's close contact behaviors is critical to curb infectious disease transmission. A monitoring device was developed to gather a total of 145,821 close contact data in subways based on semi-supervision learning. A virus transmission model considering both short- and long-range inhalation and deposition was established to calculate the virus exposure. During rush-hour, short-range inhalation exposure is 3.2 times higher than deposition exposure and 7.5 times higher than long-range inhalation exposure of all passengers in the subway. The close contact rate was 56.1 % and the average interpersonal distance was 0.8 m. Face-to-back was the main pattern during close contact. Comparing with random distribution, if all passengers stand facing in the same direction, personal virus exposure through inhalation (deposition) can be reduced by 74.1 % (98.5 %). If the talk rate was decreased from 20 % to 5 %, the inhalation (deposition) exposure can be reduced by 69.3 % (73.8 %). In addition, we found that virus exposure could be reduced by 82.0 % if all passengers wear surgical masks. This study provides scientific support for COVID-19 prevention and control in subways based on real human close contact behaviors.

Fire Risk Assessment of Subway Stations Based on Combination Weighting of Game Theory and TOPSIS Method

With the rapid development of urban modernization, traffic congestion, travel delays, and other related inconveniences have become central features in people’s daily lives. The development of subway transit systems has alleviated some of these problems. However, numerous underground subway stations lack adequate fire safety protections, and this can cause rescue difficulties in the event of fire. Once the fire occurs, there will be huge property losses and casualties. In addition, this can have a vicious impact on sustainable development. Therefore, in order to make prevention in advance and implement targeted measures, we should quantify the risk and calculate the fire risk value. In this study, through consulting experts and analysis of data obtained from Changzhou Railway Company and the Emergency Management Bureau, the fire risk index system of subway stations was determined. We calculated the index weight by selecting the combination weighting method of game theory to eliminate the limitations and dependence of subjective and objective evaluation methods. The idea of relative closeness degree in TOPSIS method iwas introduced to calculate the risk value of each subway station. Finally, the subway station risk value model was established, and the risk values for each subway station were calculated and sorted. According to expert advice and the literature review, we divided the risk level into five levels, very high; high; moderate; low and very low. The results shown that 2 subway stations on Line 1 have very high fire risk, 2 subway stations on Line 1 have high fire risk, 2 subway stations on Line 1 have moderate fire risk, 8 subway stations on Line 1 have low fire risk, and 13 subway stations on Line 1 have very low fire risk. We hope that through this evaluation model method and the results to bring some references for local rail companies. Meanwhile, this evaluation model method also promotes resilience and sustainability in social development.

A Real-Time Comparison of Four Particulate Matter Size Fractions in the Personal Breathing Zone of Paris Subway Workers: A Six-Week Prospective Study

We developed a Bayesian spline model for real-time mass concentrations of particulate matter (PM10, PM2.5, PM1, and PM0.3) measured simultaneously in the personal breathing zone of Parisian subway workers. The measurements were performed by GRIMM, a gravimetric method, and DiSCmini during the workers’ work shifts over two consecutive weeks. The measured PM concentrations were analyzed with respect to the working environment, the underground station, and any specific events that occurred during the work shift. Overall, PM0.3 concentrations were more than an order of magnitude lower compared to the other PM concentrations and showed the highest temporal variation. The PM2.5 levels raised the highest exposure concern: 15 stations out of 37 had higher mass concentrations compared to the reference. Station PM levels were not correlated with the annual number of passengers entering the station, the year of station opening or renovation, or the number of platforms and tracks. The correlation with the number of station entrances was consistently negative for all PM sizes, whereas the number of correspondence concourses was negatively correlated with PM0.3 and PM10 levels and positively correlated with PM1 and PM2.5 levels. The highest PM10 exposure was observed for the station platform, followed by the subway cabin and train, while ticket counters had the highest PM0.3, PM1, and PM2.5 mass concentrations. We further found that compared to gravimetric and DiSCmini measurements, GRIMM results showed some discrepancies, with an underestimation of exposure levels. Therefore, we suggest using GRIMM, calibrated by gravimetric methods, for PM sizes above 1μm, and DiSCmini for sizes below 700 nm.

Spatial modeling for radon concentrations in subway stations in Seoul, Korea

This study examined the environmental and geological determinants of radon concentration in subway stations by applying a spatial statistical model to the integrated GIS database. The data were collected for 237 underground subway stations located inside the city of Seoul, South Korea and used for mapping to illustrate the spatial distribution of airborne radon exposure and analysis of potential contribution of station-specific and geological determinants. A Bayesian conditional autoregressive regression (CAR) model was developed to explain the radon concentrations, and the predicted radon surface was generated and visualized to identify hotspot regions where elevated radon exposure is likely to be present in underground settings. The findings include: (1) subway stations located within granite bedrock maintained relatively higher radon concentrations; (2) underground radon emanation is not only controlled by lithology and the associated uranium content of the rocks and soil, but also by structural factors which facilitate easy migration of radon from deeper parts of the earth's crust; (3) radon risks would be elevated if the underground facility is constructed too deep without any control measure; and (4) not only the foundation of an underground facility but also the nature of the soil and rocks in the vicinity helps determine whether or not dangerous levels of radon gas are likely to accumulate inside. This modeling effort is expected to provide guidelines regarding the identification of future station locations with a lower radon risk and the mandatory installation of adequate radon reduction systems for the underground space where people stay or commute for long periods of time.

A Review of Ventilation and Environmental Control of Underground Spaces

Because of rapid urbanization, traffic problems, and other factors, underground spaces have been used more in the twenty-first century. Large underground spaces are required for underground city, metro, tunnel, mine, industrial and agricultural engineering, and civil air defense engineering. Underground spaces with varying thermal, ventilation, and lighting environments can face problems of comfort, health, and safety. High temperatures, high humidity, difficulty in flue gas emission, harmful microorganisms, radon, and physical and psychological problems are examples of issues. Air quality control technologies for underground spaces, such as ventilation, dehumidification, natural energy utilization, smoke extraction, and ventilation resistance reduction, are discussed. Ventilation for smoke-proofing/evacuation is also extensively addressed.

Application of the Bayesian spline method to analyze real-time measurements of ultrafine particle concentration in the Parisian subway

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.

Improving Comfort and Health: Green Retrofit Designs for Sunken Courtyards during the Summer Period in a Subtropical Climate

The sunken courtyard has long been used in underground spaces and provides an important outdoor environment. It introduces natural elements to create a pleasant space for human activities. However, this study measured a typical sunken courtyard and found potential problems of excessive solar radiation and accumulated air pollutants in summer when at an acceptable outdoor temperature for human activities. To improve the comfort and health of a sunken courtyard, this research proposes some green retrofit designs. Firstly, compared with green wall, water and a tree, sunshade is a primary measure to improve thermal comfort. Combining sunshade, a green wall and water reduces the temperature by up to 5.6 °C in the activity zone during the hottest hour. Secondly, blocking/guiding wind walls can effectively improve the wind environment in a sunken courtyard, but only when the wind direction is close to the prevailing wind. A blocking wind wall was better at affecting velocity and uniformity, while the guiding wind wall was more efficient at discharging air pollutants. This study initially discusses the climate-adaptive design of underground spaces in terms of green, thermal comfort and natural ventilation. Designers should generally integrate above/underground and indoor/outdoor spaces using natural and artificial resources to improve comfort and health in underground spaces.

Particle and metal exposure in Parisian subway: Relationship between exposure biomarkers in air, exhaled breath condensate, and urine

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/m³ for PM10 and PM2.5, respectively), while station agents had the highest UFP exposure (1.97 × 10⁴ particles/cm³). 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.

Will modal shift occur from subway to other modes of transportation in the post-corona world in developing countries?

Developing countries are more fragile in the face of the crippling Covid-19 pandemic. Transportation is one of the major industries that has been hardly hit worldwide, and it is more worrying for these countries that already have challenges such as high modal share of private cars, air pollution, and high fatalities due to car accidents. This paper is one of its first kinds that studies the impact of this pandemic on the transportation of Tehran, the capital of Iran, which is one of the forefronts of the battle. In the first step and to get better insights from the travel behavior of passengers due to the pandemic, an online questionnaire is developed and distributed. Priorities for mode choice before and during the pandemic decrease and increase in the share of different modes and the impact of having a high-risk person in the family is studied. Subway had the most decrease and private cars had the highest increase. Hence, two logit models are developed to explain the variables that affect shifting away from the subway and shifting to private cars. Based on the results, a follow-up survey some months later and ridership trends of public transportation during the pandemic, four scenarios are envisaged for the post-corona world, the most probable one is highlighted and policies are recommended to better manage the situation.

Correlation between levels of airborne endotoxin and heavy metals in subway environments in South Korea

This study aimed to evaluate the exposure levels and variation in airborne endotoxin and heavy metals such as aluminum, chromium (Cr), iron (Fe), manganese (Mn), nickel (Ni), zinc, and lead (Pb) in the three different South Korean subway environments (driver room, station office, and underground tunnel) and identify subway characteristics influencing endotoxin and heavy metals levels. Air samples were collected and analyzed using the kinetic Limulus Amebocyte Lysate assay and inductively coupled plasma mass spectrometers. The geometric mean was determined for endotoxin levels (0.693 EU/m³). It was also found that Fe (5.070 µg/m³) had the highest levels in subway environments while Pb (0.008 µg/m³) had the lowest levels. Endotoxin levels were higher in the underground tunnel and lower in the station office; the total heavy metal levels showed the same pattern with endotoxin levels. Endotoxins and total heavy metal levels were higher in the morning than at night. Positive correlations were found between endotoxin and Cr, Fe, Mn, and Ni levels. Given the correlation between airborne endotoxins and heavy metals, further studies with larger sample sizes are needed to identify the correlation between levels of airborne endotoxin and heavy metals.

Respiratory Disease Occupational Biomonitoring Collaborative Project (ROBoCoP): A longitudinal pilot study and implementation research in the Parisian transport company

The ROBoCoP project is launched within the EU COST Action CA16113 "CliniMARK" aiming to increase the number of clinically validated biomarkers and focused on chronic obstructive pulmonary disease (COPD) biomarker development and validation. ROBoCoP encompasses two consecutive studies consisting of a pilot study followed by a field study. The pilot study is a longitudinal exposure assessment and biomarker study aiming at: 1-understanding the suitability of the candidate biomarkers in surveying populations at risk such as workers exposed to COPD causing agents; 2-determining the best sampling plan with respect to the half-life of the candidate biomarkers; 3-implementing and validating the sampling procedures and analytical methods; 4-selecting the best suitable biomarkers to be measured in the field. Each study participant is surveyed every day during the 6-8 h work-shifts for two consecutive weeks. The field study has an implementation research designe that enabled us to demonstrate the applicability of the standardized protocol for biomarker measurements in occupational settings while also assessing the biomarkers' validity. ROBoCoP will focus on particulate matter (PM) exposure measurements, exposure biomarkers and a series of effect biomarkers, including markers of lipoperoxidation: 8-isoprostane, malondialdehyd in exhaled breath condensate (EBC) and urine, potential markers of nitrosative stress: NO2-, NO3- and formate anion in EBC; markers of DNA oxidation: 8-hydroxy-2'deoxyguanosine in EBC and urine, marker of genotoxicity: micronuclei in buccal cells, and oxidative potential in exhaled air (OPEA). OPEA appears particularly promising as a clinical biomarker for detecting COPD, and will be tested independently and as part of a biomarker panel. COPD diagnosis will be performed by an experienced occupational physician according to international diagnostic standards and confirmed by a pulmonologist.This research will include approximatively 300 underground subway workers randomly selected from the personnel registry of a large Parisian transport company. Underground subways are suggested as the most PM polluted urban transport environment. We believe this occupational exposure is relevant for biomonitoring of workers and early detection of respiratory diseases.

Air change rate effects on the airborne diseases spreading in Underground Metro wagons

The effect of the rate of change of fresh air inside passengers' wagons for Underground Metro on the spreading of airborne diseases like COVID-19 is investigated numerically. The study investigates two extreme scenarios for the location of the source of infection within the wagon with four different air change rates for each. The first scenario considers the source of infection at the closest point to the ventilation system while the other places the infection source at the farthest point from the wagon ventilation system. The effect of the wagon windows' status (i.e. closed or open) is also studied. It is found that under all conditions, open windows are always favored to decrease the infection spreading potential. A higher air change rate also decreases the infection spreading up to a certain value, beyond which the effect is not noticeable. The location of the infection source was found to greatly affect the infection spreading as well. The paper gives recommendations on the minimum air change rate to keep the infection spreading potentials to a minimum considering different times the passengers stay in the wagon.

Evaluation and comparison of the indoor air quality in different areas of the hospital

The levels of indoor air pollutants are increasing. However, the indoor air quality of only operating rooms, intensive care units, and radiology departments is usually monitored in hospitals. Hence, we aimed to evaluate the indoor air quality of an otorhinolaryngology outpatient clinic and compare air quality indices among different areas in a hospital.We prospectively measured indoor air quality using air quality sensors in different areas of a hospital from February 1, 2019 to January 31, 2020. Carbon dioxide (CO2), total volatile organic compounds (VOCs), particulate matter with diameter of <2.5 μm (PM2.5), and nitrogen dioxide concentrations were measured in the otorhinolaryngology clinic, orthopedic clinic, and reception area. The intervention efficacy was compared between otorhinolaryngology clinics employing and not employing air-cleaners.The overall concentrations of CO2, VOCs, and PM2.5 in the otorhinolaryngology clinic were significantly higher than those in the orthopedic clinic or reception area. The indoor air quality was the worst in winter. The intervention effect was observed only in PM2.5 concentrations in otorhinolaryngology clinics employing an air-cleaner.Medical practitioners and patients are frequently exposed to ambient indoor air pollution in otorhinolaryngology clinics. Hence, health-related strategies to protect against ambient indoor air pollution in otorhinolaryngology clinics are warranted.

Oxidative Stress From Exposure to the Underground Space Environment

There are a growing number of people entering underground spaces. However, underground spaces have unique environmental characteristics, and little is known about their effects on human health. It is crucial to elucidate the effects of the underground space environment on the health of humans and other organisms. This paper reviews the effects of hypoxia, toxic atmospheric particles, and low background radiation in the underground space environment on living organisms from the perspective of oxidative stress. Most studies have revealed that living organisms maintained in underground space environments exhibit obvious oxidative stress, which manifests as changes in oxidants, antioxidant enzyme activity, genetic damage, and even disease status. However, there are few relevant studies, and the pathophysiological mechanisms have not been fully elucidated. There remains an urgent need to focus on the biological effects of other underground environmental factors on humans and other organisms as well as the underlying mechanisms. In addition, based on biological research, exploring means to protect humans and living organisms in underground environments is also essential.

Biological fluid dynamics of airborne COVID-19 infection

ABSTRACT

We review the state of knowledge on the bio-fluid dynamic mechanisms involved in the transmission of the infection from SARS-CoV-2. The relevance of the subject stems from the key role of airborne virus transmission by viral particles released by an infected person via coughing, sneezing, speaking or simply breathing. Speech droplets generated by asymptomatic disease carriers are also considered for their viral load and potential for infection. Proper understanding of the mechanics of the complex processes whereby the two-phase flow emitted by an infected individual disperses into the environment would allow us to infer from first principles the practical rules to be imposed on social distancing and on the use of facial and eye protection, which to date have been adopted on a rather empirical basis. These measures need compelling scientific validation. A deeper understanding of the relevant biological fluid dynamics would also allow us to evaluate the contrasting effects of natural or forced ventilation of environments on the transmission of contagion: the risk decreases as the viral load is diluted by mixing effects but contagion is potentially allowed to reach larger distances from the infected source. To that end, our survey supports the view that a formal assessment of a number of open problems is needed. They are outlined in the discussion.

GRAPHIC ABSTRACT