Commuter PM exposure and estimated life-expectancy loss across multiple transportation modes in Xi'an, China

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.

Exposure to airborne particulate matter during commuting using portable sensors: Effects of transport modes in a French metropolis study case

Outdoor exposure to particulate matter (PM2.5 and PM10) in urban areas can vary considerably depending on the mode of transport. This study aims to quantify this difference in exposure during daily travel, by carrying out a micro-sensor measurement campaign. The pollutant exposure was assessed simultaneously over predefined routes in order to allow comparison between different transport modes having the same starting and ending points. During the six-week measurement campaign, the average reference values for PM background concentrations were 13.72 and 17.92μg/m3 for the PM2.5 and PM10, respectively. The results revealed that the mode with the highest exposure to PM2.5 adjusted to background concentration (PM2.5Norm) was the bus (1.65) followed by metro (1.51), walking (1.33), tramway (1.31), car (1.09) and finally the bike (1.06). For PM10Norm, the tramway had the highest exposure (1.86), followed by walking (1.68), metro (1.65), bus (1.61), bike (1.43) and finally the car (1.39). The level of urbanization around the route and the presence of preferential lanes for public transportation influenced the concentration to which commuters were exposed. For the active modes (bike and walking), we observed frequent variations in concentrations during the trip, characterized by punctual peaks in concentration, depending on the local characteristics of road traffic and urban morphology. Fluctuations in particulate matter inside public transport vehicles were partly explained by the opening and closing of doors during stops, as well as the passenger flows, influencing the re-suspension of particles. The car was one of the least exposed modes overall, with the lowest concentration variability, although these concentrations can vary greatly depending on the ventilation parameters used. These results encourage measures to move the most exposed users away from road traffic, by developing a network of lanes entirely dedicated to cycling and walking, particularly in densely populated areas, as well as encouraging the renewal of motorized vehicles to use less polluting fuels with efficient ventilation systems.

Optimal dynamic pricing for public transportation considering consumer social learning

Effective public transportation pricing strategies are critical to reducing traffic congestion and meeting consumer demand for sustainable urban development. In this study, we construct a dynamic game pricing model and a social learning network model for consumers of three modes of public transportation including metro, bus, and pa-transit. In the model, the metro, bus, and pa-transit operators maximize their profits through dynamic pricing optimization, and consumers maximize their utility by adjusting their travel habits through social learning in the social network. The reinforcement learning algorithm is applied to simulate the model, and the results show that: (1) as consumers' perceived sensitivity to different modes of travel increases, the market share and price of each mode of travel adjust accordingly. (2) When taking into account consumers' social learning behavior, the market share of metros remains high, while the market shares of buses and pa-transit are relatively low. (3) As consumers become more sensitive to their perception of each travel mode, operators invest more resources in improving service quality to gain market share, which in turn affects the price of each travel mode. Our results provide decision support for optimal pricing of urban public transportation.

Health damage assessment of commuters and staff in the metro system based on field monitoring-A case study of Nanjing

Introduction

The metro has emerged as a major mode of transportation. A significant number of commuters and staff in the metro system are exposed to air pollutants because of its shielded environment, and substantial health damage requires quantitative assessment. Previous studies have focused on comparing the health impacts among different transportation modes, overlooking the specific population characteristics and pollutant distribution in metro systems.

Methods

To make improvements, this study implements field monitoring of the metro's air environment utilizing specialized instruments and develops a health damage assessment model. The model quantifies health damage of two main groups (commuters and staff) in metro systems at three different areas (station halls, platforms, and metro cabins) due to particulate matter 10 and benzene series pollution.

Conclusion

A case study of Nanjing Metro Line 3 was conducted to demonstrate the applicability of the model. Health damage at different metro stations was analyzed, and the health damage of commuters and staff was assessed and compared. This study contributes to enhancing research on health damage in the metro systems by providing a reference for mitigation measures and guiding health subsidy policies.

An investigation of the PM2.5 concentrations and cumulative inhaled dose during subway commutes in Changchun, China

Air quality in subway systems is crucial as it affects the health of passengers and staff. Although most tests of PM2.5 concentrations in subway stations have taken place in public areas, PM2.5 is less understood in workplaces. Few studies have estimated the cumulative inhaled dose of passengers based on real-time changes in PM2.5 concentrations as they commute. To clarify the above issues, this study first measured PM2.5 concentrations in four subway stations in Changchun, China, where measuring points included five workrooms. Then, passengers' exposure to PM2.5 during the whole subway commute (20-30 min) was measured and segmented inhalation was calculated. The results showed that PM2.5 concentration in public places ranged from 50 to 180 μg/m3, and was strongly correlated with outdoors. While the PM2.5 average concentration in workplaces was 60 µg/m3, and it was less affected by outdoor PM2.5 concentration. Passenger's cumulative inhalations in single commuting were about 42 μg and 100 μg when the outdoor PM2.5 concentrations were 20-30 μg/m3 and 120-180 μg/m3, respectively. The PM2.5 inhalation in carriages accounted for the largest proportion of the entire commuting, about 25-40%, because of the longer exposure time and higher PM2.5 concentrations. It is recommended to improve the tightness of the carriage and filter the fresh air to improve the air quality inside. The average daily PM2.5 inhaled by staff was 513.53 μg, which was 5-12 times higher than that of passengers. Installing air purification devices in workplaces and reminding staff to take personal protection can positively protect their health.

A systematic review of transportation carbon emissions based on CiteSpace

Transportation sector has become a major contributor to the escalation of carbon emissions and subsequent climate change. In this study, a bibliometric analysis was conducted using CiteSpace on published papers (1991-2022). Then a theoretical framework was proposed through traditional content analysis from three aspects: measurement, mechanism analysis, and low-carbon pathways analysis. The clustering results show that the research topics have involved mainly factor analysis, evaluation, system analysis, control measurement and pollutants. A further summary of the content of the relevant literature shows that there are five main accounting methods for measuring transportation carbon emissions (TCEs), which can be applied to different scenarios. Studies involving the spatio-temporal distribution of TCEs is limited and mainly focus on macroperspectives. The mechanism of TCEs involves three main aspects: system assessment, efficiency measurement, and driver analysis, which serve to identify the internal patterns of TCEs. Finally, the outlook regarding TCEs is presented.

The effect of COVID-19 restrictions on particulate matter on different modes of transport in China

Since the COVID-19 pandemic, ventilation on transport has been improved to control the aerosol transmission. We utilized portable monitors to measure real-time concentrations of PM₁₀, PM_2.5, PM_1.0 and black carbon (BC) on six modes of transport and estimate personal exposures under the epidemic prevention. The mean concentrations of PM₁₀, PM_2.5, PM_1.0 and BC measured on transport were 18.8 ± 19.4, 16.6 ± 16.5, 12.2 ± 10.8 and 4.1 ± 6.9 μg/m³, respectively. It reduced PM levels on subway to apply the full fresh air mode rather than partial recirculation mode. Airplane had the lowest concentrations and the highest decay rates, implying the most efficient ventilation and filtration. PM were higher on intra-city transport than inter-city, and significantly increased on arrival at stations. BC and BC/PM ratios were higher on road transport than rail transport, indicating the contribution of exhaust emissions. The ventilation mode to exchange air with the outside and the positive association between concentrations and decay rates on high-speed train suggested filtration efficiency should be improved simultaneously with enhancing ventilation. Wearing facemasks on transport further protects passengers against PM exposure, which reduced personal exposure concentrations on four modes of transport lower than 10 μg/m³, the World Health Organization guideline.

The health effects of traffic-related air pollution: A review focused the health effects of going green

Traffic-related air pollution (TRAP) is global concern due to both the ecological damage of TRAP and the adverse health effects in Humans. Several strategies to reduce TRAP have been implemented, including the use of sustainable fuels, after-treatment technologies, and new energy vehicles. Such approaches can reduce the exhaust of particulate matter, adsorbed chemicals and a range of gases, but from a health perspective these approaches are not always successful. This review aims to discuss the approaches taken, and to then describe the likely health effects of these changes.

The potential risks and exposure of Qinling giant pandas to polycyclic aromatic hydrocarbon (PAH) pollution

Rapid industrialization and urbanization have created a substantial urban-rural gradient for various pollutants. The Qinling Mountains are highly important in terms of biodiversity, providing habitat for giant pandas, which are endemic to China and are a widely recognized symbol for conservation. Whether polycyclic aromatic hydrocarbon (PAH) exposure risks regarding in situ animal conservation zones are affected by environmental pollution or even enhanced by the mountain-trapping effect requires further research. Our group carried out a large-scale investigation on the area ranging from Xi'an to Hanzhong across the giant panda habitat in the Qinling Mountains by collecting atmosphere, soil, bamboo, and fecal samples from different sites over a two-year period. The total toxicity of atmospheric PAHs and the frequencies of soil PAHs above effect range low (ERL) values showed a decreasing trend from urban areas to the central mountains, suggesting a distance effect from the city. The proportions of total 5- and 6-ring PAHs in the atmosphere were higher in the central mountainous areas than in the urban areas, while this difference was reversed in the soil. Health risk assessments showed that the incremental lifetime carcinogenic risks (ILCR) of PAH exposure by bamboo ingestion ranged from 2.16 × 10^-4 to 3.11 × 10^-4, above the critical level of 10^-4. Bamboo ingestion was the main driver of the PAH exposure risks. The concentration difference between bamboo and fecal samples provided a reference for the level of PAHs absorbed by the panda digestive system. Since the Qinling Mountains possess the highest density of giant pandas and provide habitats to many other endangered animal and plant species, we should not ignore the probability of health risks posed by PAHs. Monitoring the pollution level and reducing the atmospheric emissions of toxic pollutants are recommended actions. Further detailed research should also be implemented on pandas' health effects of contaminant exposure.