Sequential Measurement of Intermodal Variability in Public Transportation PM2.5 and CO Exposure Concentrations

Air pollution exposure in active versus passive travel modes across five continents: A Bayesian random-effects meta-analysis

Epidemiological studies on health effects of air pollution usually estimate exposure at the residential address. However, ignoring daily mobility patterns may lead to biased exposure estimates, as documented in previous exposure studies. To improve the reliable integration of exposure related to mobility patterns into epidemiological studies, we conducted a systematic review of studies across all continents that measured air pollution concentrations in various modes of transport using portable sensors. To compare personal exposure across different transport modes, specifically active versus motorized modes, we estimated pairwise exposure ratios using a Bayesian random-effects meta-analysis. Overall, we included measurements of six air pollutants (black carbon (BC), carbon monoxide (CO), nitrogen dioxide (NO2), particulate matter (PM10, PM2.5) and ultrafine particles (UFP)) for seven modes of transport (i.e., walking, cycling, bus, car, motorcycle, overground, underground) from 52 published studies. Compared to active modes, users of motorized modes were consistently the most exposed to gaseous pollutants (CO and NO2). Cycling and walking were the most exposed to UFP compared to other modes. Active vs passive mode contrasts were mostly inconsistent for other particle metrics. Compared to active modes, bus users were consistently more exposed to PM10 and PM2.5, while car users, on average, were less exposed than pedestrians. Rail modes experienced both some lower exposures (compared to cyclists for PM10 and pedestrians for UFP) and higher exposures (compared to cyclist for PM2.5 and BC). Ratios calculated for motorcycles should be considered carefully due to the small number of studies, mostly conducted in Asia. Computing exposure ratios overcomes the heterogeneity in pollutant levels that may exist between continents and countries. However, formulating ratios on a global scale remains challenging owing to the disparities in available data between countries.

Relative contributions of ambient air and internal sources to multiple air pollutants in public transportation modes

Commuters are often exposed to relatively high air pollutant concentrations in public transport microenvironments (TMEs) because of their proximity to emission sources. Previous studies have mainly focused on assessing the concentrations of air pollutants in TMEs, but few studies have distinguished between the contributions of ambient air and internal sources to the exposure of commuters to air pollutants. The main objective of this study was to quantify the contributions of ambient air and internal sources to the measured particulate matter and gaseous pollutant concentrations in selected TMEs in Hong Kong, a high-rise, high-density city in Asia. A sampling campaign was conducted to measure air pollutant concentrations in TMEs in Hong Kong in July and November 2018 using portable air quality monitors. We measured the concentrations of each pollutant in different TMEs and quantified the infiltration of particulate matter into these TMEs. The double-decker bus had the lowest particulate matter concentrations (mean PM1, PM2.5, and PM10 concentrations of 5.1, 9.5, and 13 μg/m3, respectively), but higher concentrations of CO (0.9 ppm), NO (422 ppb), and NO2 (100 ppb). For all the TMEs, about half of the PM2.5 were PM1 particles. The Mass Transit Railway (MTR) subway system had a PM2.5/PM10 ratio of about 0.90, whereas the PM2.5/PM10 ratio was about 0.60-0.70 for the other TMEs. The MTR had infiltration factor estimates <0.4 for particulate matter, lower than those of the double-decker bus and minibus. The MTR had the highest contribution from internal sources (mean PM1, PM2.5, and PM10 concentrations of 4.6, 13.4, and 15.8 μg/m3, respectively). This study will help citizens to plan commuting routes to reduce their exposure to air pollution and help policy-makers to prioritize effective exposure reduction strategies.

A review of personal exposure studies in selected Asian countries' public transport microenvironments: lessons learned and future directions

This comprehensive paper conducts an in-depth review of personal exposure and air pollutant levels within the microenvironments of Asian city transportation. Our methodology involved a systematic analysis of an extensive body of literature from diverse sources, encompassing a substantial quantity of studies conducted across multiple Asian cities. The investigation scrutinizes exposure to various pollutants, including particulate matters (PM10, PM2.5, and PM1), carbon dioxide (CO2), formaldehyde (CH2O), and total volatile organic compounds (TVOC), during transportation modes such as car travel, bus commuting, walking, and train rides. Notably, our review reveals a predominant focus on PM2.5, followed by PM10, PM1, CO2, and TVOC, with limited attention given to CH2O exposure. Across the spectrum of Asian cities and transportation modes, exposure concentrations exhibited considerable variability, a phenomenon attributed to a multitude of factors. Primary sources of exposure encompass motor vehicle emissions, traffic dynamics, road dust, and open bus doors. Furthermore, our findings illuminate the influence of external environments, particularly in proximity to train stations, on pollutant levels inside trains. Crucial factors affecting exposure encompass ventilation conditions, travel-specific variables, seat locations, vehicle types, and meteorological influences. The culmination of this rigorous review underscores the need for standardized measurements, enhanced ventilation systems, air filtration mechanisms, the adoption of clean energy sources, and comprehensive public education initiatives aimed at reducing pollutant exposure within city transportation microenvironments. Importantly, our study contributes to the growing body of knowledge surrounding this subject, offering valuable insights for policymakers and researchers dedicated to advancing air quality standards and safeguarding public health.

A Comparison of Particulate Exposure Levels during Taxi, Bus, and Metro Commuting among Four Chinese Megacities

Exposure to inhalable particulate matter pollution is a hazard to human health. Many studies have examined the in-transit particulate matter pollution across multiple travel modes. However, limited information is available on the comparison of in-transit exposure among cities that experience different climates and weather patterns. This study aimed to examine the variations in in-cabin particle concentrations during taxi, bus, and metro commutes among four megacities located in the inland and coastal areas of China. To this end, we employed a portable monitoring approach to measure in-transit particle concentrations and the corresponding transit conditions using spatiotemporal information. The results highlighted significant differences in in-cabin particle concentrations among the four cities, indicating that PM concentrations varied in an ascending order of, and the ratios of different-sized particle concentrations varied in a descending order of CS, SZ, GZ, and WH. Variations in in-cabin particle concentrations during bus and metro transits between cities were mainly positively associated with urban background particle concentrations. Unlike those in bus and metro transit, in-cabin PM concentrations in taxi transit were negatively associated with urban precipitation and wind speed. The variations in particle concentrations during the trip were significantly associated with passenger density, posture, the in-cabin location of investigators, and window condition, some of which showed interactive effects. Our findings suggest that improving the urban background environment is essential for reducing particulate pollution in public transport microenvironments. Moreover, optimizing the scheduling of buses and the distribution of bus stops might contribute to mitigating the in-cabin exposure levels in transit. With reference to our methods and insights, policymakers and other researchers may further explore in-transit exposure to particle pollution in different cities.

Atmospheric inverse estimates of CO emissions from Zhengzhou, China

Carbon monoxide (CO) is an important gas that affects human health and causes air pollution. However, the estimates of CO emissions in China are still subject to large uncertainties. Based on the CO mass concentration and the coupled Weather Research and Forecast (WRF) and Stochastic Time-Inverted Lagrangian Transport (STILT) model (WRF-STILT), this study estimates the CO emissions over Zhengzhou, China. The results show that the mean CO mass concentration was 1.17 mg m^-3 from November 2017 to February 2018, with a clear diurnal variation. There were two periods of rapidly increasing CO concentration in the diurnal variation, which are 06:00-09:00 and 16:00-20:00 local time. The footprint analysis shows that the observation site is highly influenced by local emissions. The most influential regions to the site observations are northeast and northwest Zhengzhou, which are associated with the geographical barrier of the Taihang Mountains in the north and narrow Fenwei Plain in the west. The inversion result shows that the actual emissions are lower than the inventory estimates. Using the optimal scaling factors, the WRF-STILT simulations of CO concentration agree closely with the CO measurements with the linear fitting regression equation y = 0.87x + 0.15. The slopes of the linear fitting regressions between the WRF-STILT-simulated CO concentrations determined using the optimal emissions and the observations range from 0.72 to 0.89 for four months, and all the fitting results passed the significance test (P < 0.001). These results indicate that the new optimal emissions derived with the scaling factors could better represent the real emission conditions than the a priori emissions if the WRF-STILT model is assumed to be reliable.

Indoor Exposure to Ambient Particles and Its Estimation Using Fixed Site Monitors

Ambient PM_2.5 concentrations measured at fixed site monitors (FSM) are often biased with respect to exposure concentrations because of spatial variability and infiltration. Based on comparison of ambient concentrations from 14 FSMs and of exposure concentrations measured indoors and outdoors at two schools in Hong Kong for winter and summer seasons, the magnitude and sources of exposure error based on using FSMs as a surrogate for exposure are quantified. An approach for bias correcting surrogate exposure estimates from FSMs is demonstrated. The approach is based on a proximity factor (PF) that accounts for differences in spatial locations, proximity to emissions and deviation from dominant wind direction, and an infiltration factor (IF) that varies by season. The combination of the PF and IF reduce bias in mean school exposure estimates from ±90% to ±20%. Bias in exposure estimates from using FSMs as surrogates tend to be smaller for which the exposure site and FSM are aligned with wind direction, have similar sampling height, and are in close proximity. The methodology demonstrated to assess concordance between FSMs and exposure measurement sites can be applied more broadly to help reduce exposure error, which may help to interpret seasonal variations in health estimates.

Characterization of PM2.5 exposure concentration in transport microenvironments using portable monitors

Recently, portable monitors have been increasingly used to quantify air pollutant concentrations at high spatiotemporal resolution. A sampling campaign was conducted to measure the fine particulate matter (PM_2.5) and carbon monoxide (CO) exposure concentrations in transport microenvironments (TMEs) in Hong Kong in January and June 2015 using TSI DustTrak and Q-Trak portable monitors. The objectives were to: (1) calibrate DustTrak and Q-Trak; (2) evaluate variability between seasons and microenvironments; (3) estimate indoor/outdoor relationships; and (4) determine minimum sample size. Calibration equations, obtained through side-by-side measurement against stationary reference methods in winter and summer, were applied to correct the measured PM_2.5 data set. In general, PM_2.5 concentrations in all TMEs were significantly higher in winter than in summer. The mean PM_2.5 concentration in winter was lower for underground sections of the Mass Transit Railway (MTR) metro system (31 μg/m³) than for other TMEs, whereas in summer TMEs had mean PM_2.5 concentrations in the range of 10-15 μg/m³, with above-ground MTR train as an exception, at 23 μg/m³. PM_2.5 concentrations measured in TMEs were strongly correlated with nearby air quality monitoring stations (AQMSs) measurements in winter, but in summer there was little correlation. The minimum sample size estimates varied more among TMEs in summer versus winter because of the differences in PM_2.5 concentration distributions related to changes in ambient PM_2.5 concentrations and ventilation practices. This study provides a feasible protocol on the calibration and application of portable monitors in TME air quality measurement and develops a method for estimating minimum sample size.