Exposure to ambient particulate matter (PM) air pollution is a leading risk factor for morbidity and mortality, associated with up to 8.9 million deaths/year worldwide. Measurement of personal exposure to PM is hindered by poor spatial resolution of monitoring networks. Low-cost PM sensors may improve monitoring resolution in a cost-effective manner but there are doubts regarding data reliability. PM sensor boxes were constructed using four low-cost PM micro-sensor models. Three boxes were deployed at each of two schools in Southampton, UK, for around one year and sensor performance was analysed. Comparison of sensor readings with a nearby background station showed moderate to good correlation (0.61 < r < 0.88, p < 0.0001), but indicated that low-cost sensor performance varies with different PM sources and background concentrations, and to a lesser extent relative humidity and temperature. This may have implications for their potential use in different locations. Data also indicates that these sensors can track short-lived events of pollution, especially in conjunction with wind data. We conclude that, with appropriate consideration of potential confounding factors, low-cost PM sensors may be suitable for PM monitoring where reference-standard equipment is not available or feasible, and that they may be useful in studying spatially localised airborne PM concentrations.

Air Quality (AQ) is a very topical issue for many cities and has a direct impact on citizen health. The AQ of a large UK city is being investigated using low-cost Particulate Matter (PM) sensors, and the results obtained by these sensors have been compared with government operated AQ stations. In the first pilot deployment, six AQ Internet of Things (IoT) devices have been designed and built, each with four different low-cost PM sensors, and they have been deployed at two locations within the city. These devices are equipped with LoRaWAN wireless network transceivers to test city scale Low-Power Wide Area Network (LPWAN) coverage. The study concludes that (i) the physical device developed can operate at a city scale; (ii) some low-cost PM sensors are viable for monitoring AQ and for detecting PM trends; (iii) LoRaWAN is suitable for city scale sensor coverage where connectivity is an issue. Based on the findings from this first pilot project, a larger LoRaWAN enabled AQ sensor network is being deployed across the city of Southampton in the UK.

Exposure to ambient airborne particulate matter is a major risk factor for mortality and morbidity, associated with asthma, lung cancer, heart disease, myocardial infarction, and stroke, and more recently type 2 diabetes, dementia and loss of cognitive function. Less is understood about differential effects of particulate matter from different sources. Underground railways are used by millions of people on a daily basis in many cities. Poor air exchange with the outside environment means that underground railways often have an unusually high concentration of airborne particulate matter, while a high degree of railway-associated mechanical activity produces particulate matter which is physicochemically highly distinct from ambient particulate matter. The implications of this for the health of exposed commuters and employees is unclear. A literature search found 27 publications directly assessing the potential health effects of underground particulate matter, including in vivo exposure studies, in vitro toxicology studies, and studies of particulate matter which might be similar to that found in underground railways. The methodology, findings, and conclusions of these studies were reviewed in depth, along with further publications directly relevant to the initial search results. In vitro studies suggest that underground particulate matter may be more toxic than exposure to ambient/urban particulate matter, especially in terms of endpoints related to reactive oxygen species generation and oxidative stress. This appears to be predominantly a result of the metal-rich nature of underground particulate matter, which is suggestive of increased health risks. However, while there are measureable effects on a variety of endpoints following exposure in vivo, there is a lack of evidence for these effects being clinically significant as may be implied by the in vitro evidence. There is little direct evidence that underground railway particulate matter exposure is more harmful than ambient particulate matter exposure. This may be due to disparities between in vivo exposures and in vitro models, and differences in exposure doses, as well as statistical under powering of in vivo studies of chronic exposure. Future research should focus on outcomes of chronic in vivo exposure, as well as further work to understand mechanisms and potential biomarkers of exposure.

Underground railway stations are known to have elevated particulate matter (PM) loads compared to ambient air. As these particles are derived from metal-rich sources and transition metals may pose a risk to health by virtue of their ability to catalyze generation of reactive oxygen species (ROS), their potential enrichment in underground environments is a source of concern. Compared to coarse (PM₁₀) and fine (PM_2.5) particulate fractions of underground railway airborne PM, little is known about the chemistry of the ultrafine (PM_0.1) fraction that may contribute significantly to particulate number and surface area concentrations. This study uses inductively coupled plasma mass spectrometry and ion chromatography to compare the elemental composition of size-fractionated underground PM with woodstove, roadwear generator, and road tunnel PM. Underground PM is notably rich in Fe, accounting for greater than 40% by mass of each fraction, and several other transition metals (Cu, Cr, Mn, and Zn) compared to PM from other sources. Importantly, ultrafine underground PM shows similar metal-rich concentrations as the coarse and fine fractions. Scanning electron microscopy revealed that a component of the coarse fraction of underground PM has a morphology indicative of generation by abrasion, absent for fine and ultrafine particulates, which may be derived from high-temperature processes. Furthermore, underground PM generated ROS in a concentration- and size-dependent manner. This study suggests that the potential health effects of exposure to the ultrafine fraction of underground PM warrant further investigation as a consequence of its greater surface area/volume ratio and high metal content.

Despite the London Underground (LU) handling on average 2.8 million passenger journeys per day, the characteristics and potential health effects of the elevated concentrations of metal-rich PM_2.5 found in this subway system are not well understood. Spatial monitoring campaigns were carried out to characterise the health-relevant chemical and physical properties of PM_2.5 across the LU network, including diurnal and day-to-day variability and spatial distribution (above ground, depth below ground and subway line). Population-weighted station PM_2.5 rankings were produced to understand the relative importance of concentrations at different stations and on different lines. The PM_2.5 mass in the LU (mean 88 μg m^-3, median 28 μg m^-3) was greater than at ambient background locations (mean 19 μg m^-3, median 14 μg m^-3) and roadside environments in central London (mean 22 μg m^-3, median 14 μg m^-3). Concentrations varied between lines and locations, with the deepest and shallowest submerged lines being the District (median 4 μg m^-3) and Victoria (median 361 μg m^-3 but up to 885 μg m^-3). Broadly in agreement with other subway systems around the world, sampled LU PM_2.5 comprised 47% iron oxide, 7% elemental carbon, 11% organic carbon, and 14% metallic and mineral oxides. Although a relationship between line depth and air quality inside the tube trains was evident, there were clear influences relating to the distance from cleaner outside air and the exchange with cabin air when the doors open. The passenger population-weighted exposure analysis demonstrated a method to identify stations that should be prioritised for remediation to improve air quality. PM_2.5 concentrations in the LU are many times higher than in other London transport Environments. Failure to include this environment in epidemiological studies of the relationship between PM_2.5 and health in London is therefore likely to lead to a large exposure misclassification error. Given the significant contribution of underground PM_2.5 to daily exposure, and the differences in composition compared to urban PM_2.5, there is a clear need for well-designed studies to better understand the health effects of underground exposure.