Characteristics of fine and ultrafine aerosols in the London underground

Indoor air quality in subway microenvironments: Pollutant characteristics, adverse health impacts, and population inequity

Rapidly increasing urbanization in recent decades has elevated the subway as the primary public transportation mode in metropolitan areas. Indoor air quality (IAQ) inside subways is an important factor that influences the health of commuters and subway workers. This review discusses the subway IAQ in different cities worldwide by comparing the sources and abundance of particulate matter (PM2.5 and PM10) in these environments. Factors that affect PM concentration and chemical composition were found to be associated with the subway internal structure, train frequency, passenger volume, and geographical location. Special attention was paid to air pollutants, such as transition metals, volatile/semi-volatile organic compounds (VOCs and SVOCs), and bioaerosols, due to their potential roles in indoor chemistry and causing adverse health impacts. In addition, given that the IAQ of subway systems is a public health issue worldwide, we calculated the Gini coefficient of urban subway exposure via meta-analysis. A value of 0.56 showed a significant inequity among different cities. Developed regions with higher per capita income tend to have higher exposure. By reviewing the current advances and challenges in subway IAQ with a focus on indoor chemistry and health impacts, future research is proposed toward a sustainable urban transportation systems.

Detection of atmospheric aerosols and terrestrial nanoparticles collected in a populous city in southern Brazil

The main objective of this study is to analyze hazardous elements in nanoparticles (NPs) (smaller than 100 nm) and ultrafine particles (smaller than 1 µm) in Porto Alegre City, southern Brazil using a self-made passive sampler and Sentinel-3B SYN satellite images in 32 collection points. The Aerosol Optical Thickness proportion (T550) identification was conducted using images of the Sentinel-3B SYN satellite at 634 points sampled in 2019, 2020, 2021, and 2022. Focused ion beam scanning electron microscopy analyses were performed to identify chemical elements present in NPs and ultrafine particles, followed by single-stage cascade impactor to be processed by high-resolution transmission electron microscopy. This process was coupled with energy-dispersive X-ray spectroscopy and later analysis via secondary ion mass spectrometry. Data was acquired from Sentinel-3B SYN images, normalized to a standard mean of 0.83 µg/mg, at moderate spatial resolution (260 m), and modeled in the Sentinel Application Platform (SNAP) software v.8.0. Statistical matrix data was generated in the JASP software (Jeffreys's Amazing Statistics Program) v.0.14.1.0 followed by a K-means cluster analysis. The results demonstrate the presence of between 1 and 100 nm particles of the following chemical elements: Si, Al, K, Mg, P, and Ti. Many people go through these areas daily and may inhale or absorb these elements that can harm human health. In the Sentinel-3B SYN satellite images, the sum of squares in cluster 6 is 168,265 and in cluster 7 a total of 21,583. The use of images from the Sentinel-3B SYN satellite to obtain T550 levels is of great importance as it reveals that atmospheric pollution can move through air currents contaminating large areas on a global scale.

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.

SARS-CoV2 in public spaces in West London, UK during COVID-19 pandemic

BACKGROUND

Spread of SARS-CoV2 by aerosol is considered an important mode of transmission over distances >2 m, particularly indoors.

OBJECTIVES

We determined whether SARS-CoV2 could be detected in the air of enclosed/semi-enclosed public spaces.

METHODS AND ANALYSIS

Between March 2021 and December 2021 during the easing of COVID-19 pandemic restrictions after a period of lockdown, we used total suspended and size-segregated particulate matter (PM) samplers for the detection of SARS-CoV2 in hospitals wards and waiting areas, on public transport, in a university campus and in a primary school in West London.

RESULTS

We collected 207 samples, of which 20 (9.7%) were positive for SARS-CoV2 using quantitative PCR. Positive samples were collected from hospital patient waiting areas, from hospital wards treating patients with COVID-19 using stationary samplers and from train carriages in London underground using personal samplers. Mean virus concentrations varied between 429 500 copies/m³ in the hospital emergency waiting area and the more frequent 164 000 copies/m³ found in other areas. There were more frequent positive samples from PM samplers in the PM2.5 fractions compared with PM10 and PM1. Culture on Vero cells of all collected samples gave negative results.

CONCLUSION

During a period of partial opening during the COVID-19 pandemic in London, we detected SARS-CoV2 RNA in the air of hospital waiting areas and wards and of London Underground train carriage. More research is needed to determine the transmission potential of SARS-CoV2 detected in the air.