Characteristics of fine and ultrafine aerosols in the London underground.

Underground railway systems are recognised spaces of increased personal pollution exposure. We studied the number-size distribution and physico-chemical characteristics of ultrafine (PM0.1), fine (PM0.1-2.5) and coarse (PM2.5-10) particles collected on a London underground platform. Particle number concentrations gradually increased throughout the day, with a maximum concentration between 18:00 h and 21:00 h (local time). There was a maximum decrease in mass for the PM2.5, PM2.5-10 and black carbon of 3.9, 4.5 and ~ 21-times, respectively, between operable (OpHrs) and non-operable (N-OpHrs) hours. Average PM10 (52 µg m-3) and PM2.5 (34 µg m-3) concentrations over the full data showed levels above the World Health Organization Air Quality Guidelines. Respiratory deposition doses of particle number and mass concentrations were calculated and found to be two- and four-times higher during OpHrs compared with N-OpHrs, reflecting events such as train arrival/departure during OpHrs. Organic compounds were composed of aromatic hydrocarbons and polycyclic aromatic hydrocarbons (PAHs) which are known to be harmful to health. Specific ratios of PAHs were identified for underground transport that may reflect an interaction between PAHs and fine particles. Scanning transmission electron microscopy (STEM) chemical maps of fine and ultrafine fractions show they are composed of Fe and O in the form of magnetite and nanosized mixtures of metals including Cr, Al, Ni and Mn. These findings, and the low air change rate (0.17 to 0.46 h-1), highlight the need to improve the ventilation conditions.

Understanding the effects of roadside hedges on the horizontal and vertical distributions of air pollutants in street canyons.

Built-up environments limit air pollution dispersion in street canyons and lead to complex trade-offs between green infrastructure (GI) usage and its potential to reduce near-road exposure. This study evaluated the effects of an evergreen hedge on the distribution of particulate matter (PM1, PM2.5, PM10), black carbon (BC) and particle number concentrations (PNCs) in a street canyon in West London. Instrumentation was deployed around the hedge at 13 fixed locations to assess the impact of the hedge on vertical and horizontal concentration distributions. Changes in concentrations behind the hedge were measured with reference to the corresponding sampling point in front of the hedge for all sets of measurements. Results showed a significant reduction in vertical concentrations between 1 and 1.7 m height, with maximum reductions of -16% (PM1 and PM10) and -17% (PM2.5) at âˆ¼1 m height. Horizontal concentrations revealed two zones between the building façade and the hedge, with opposite trends: (i) close to hedge (within 0.2 m), where a reduction of PM1 and PM2.5 was observed, possibly due to dilution, deposition and the barrier effect; and (ii) 0.2-3 m from the hedge, showing an increase of 13-37% (PM1) and 7-21% (PM2.5), possibly due to the blockage effect of the building, restricting dispersion. BC showed a significant reduction at breathing height (1.5 m) of between -7 and -50%, followed by -15% for PNCs in the 0.02-1 µm size range. The ELPI + analyser showed a peak of âˆ¼30 nm. The presence of the hedge led to a âˆ¼39 ± 32% decrease in total PNCs (0.006-10 µm), suggesting a greater removal in different modes, such as a 83 ± 12% reduction in nucleation mode (0.006-0.030 µm), 74 ± 15% in ultrafine (≤0.1 µm), and 34 ± 30% in accumulation mode (0.03-0.3 µm). These findings indicate graded filtering of particles by GI in a near-road street canyon environment. This insight will guide the improved design of GI barriers and the validation of microscale dispersion models.

Temporary reduction in fine particulate matter due to 'anthropogenic emissions switch-off' during COVID-19 lockdown in Indian cities.

The COVID-19 pandemic elicited a global response to limit associated mortality, with social distancing and lockdowns being imposed. In India, human activities were restricted from late March 2020. This 'anthropogenic emissions switch-off' presented an opportunity to investigate impacts of COVID-19 mitigation measures on ambient air quality in five Indian cities (Chennai, Delhi, Hyderabad, Kolkata, and Mumbai), using in-situ measurements from 2015 to 2020. For each year, we isolated, analysed and compared fine particulate matter (PM2.5) concentration data from 25 March to 11 May, to elucidate the effects of the lockdown. Like other global cities, we observed substantial reductions in PM2.5 concentrations, from 19 to 43% (Chennai), 41-53% (Delhi), 26-54% (Hyderabad), 24-36% (Kolkata), and 10-39% (Mumbai). Generally, cities with larger traffic volumes showed greater reductions. Aerosol loading decreased by 29% (Chennai), 11% (Delhi), 4% (Kolkata), and 1% (Mumbai) against 2019 data. Health and related economic impact assessments indicated 630 prevented premature deaths during lockdown across all five cities, valued at 0.69 billion USD. Improvements in air quality may be considered a temporary lockdown benefit as revitalising the economy could reverse this trend. Regulatory bodies must closely monitor air quality levels, which currently offer a baseline for future mitigation plans.

Studying human exposure to vehicular emissions using computational fluid dynamics and an urban mobility simulator: The effect of sidewalk residence time, vehicular technologies and a traffic-calming device.

A computational system consisting of an urban mobility simulator, validated fluid dynamics and an integral exposure model, is proposed to obtain cyclist and pedestrian exposure to PMx and NOx. Pedestrian activities in the urban anthroposphere include walking and running. The computational experiments take place in a computer-generated urban canyon, subject to emissions from diesel and gasoline Euro 5 and Euro 6 vehicular technologies, in continuous and stop-and-go traffic scenarios, and three wind directions at two speeds. The exposure time in the computational domain of slow and fast pedestrians were obtained. Slow pedestrians had exposure times around 17% more than fast pedestrians due to their higher sidewalk residence time. Runners and cyclists decreased their exposures by 57% and 73% respectively compared with walkers. Two traffic scenarios are implemented: one due the presence of a hump and another without a hump. The presence of the hump, increased exposure and fuel consumption by 60% per heavy duty vehicle, about 44-48% per light duty vehicle and about 54-71% per passenger car. Vehicular technology had a large influence on exposure: Heavy duty-Euro 6 vehicle decreased 86% the exposure to PM2.5 and 66% to NOX with respect to Euro 5. The proposed computational system provides information on how wind velocity influenced the inhomogeneous pollutant distribution in the street-canyon, causing exposure to be dependent on pedestrian route location. Microscale sidewalk areas in the order of meters containing higher concentrations were thus located. The cleanest routes in the urban canyon were identified. When the wind intensity doubled from 2 to 4 m s-1, exposure concentration decreased around 45%. The proposed system provides a computational platform to study urban atmospheric fluids, scenarios such as pedestrian routes, vehicular technologies, traffic velocities, meteorological conditions and urban morphology affecting pollution exposure.