This review synthesises the current state-of-the-art in air quality (AQ) research relating to current monitoring and modeling methods focused on transport hub (TH) settings. Air pollution characteristics from monitoring studies revealed that higher concentrations of PM2.5 (12.4-147.8 mu g/m3) and SO2 (54.1-78.3 mu g/m3) dominated AQ issues in ports. Train terminals were impacted by NO2 (52.2-472.5 mu g/m3), with VOCs (123-973 ppb) and UFPs (5 x 103 to 4.8 x 106 particles/cm3) considerably higher at airports. Bivariate polar plots, data filtration techniques, and regression models were considered relatively simple, resource-efficient, and effective source apportionment methods to assess AQ (SO2, NO2 and UFP) from sources in and around THs. Speciated receptor modelling was more expensive, but is suitable for complex environments to evaluate multi-pollutant (PM and VOCs) conditions. Gaussian models demonstrated better agreement than Eulerian and Lagrangian models at airports, with Eulerian models slightly outperforming Gaussian models in port settings. Additionally, Eulerian was the most effective methods to model secondary pollutants and over long distances. Limited AQ research focused on small-scale semi-enclosed THs, such as bus and train terminals, with an additional knowledge gap of indoor AQ in port and airport buildings. Improved characterisation of pollutants like VOCs, BC, and PAHs would benefit climate and health impact assessments at THs, with the integration of AI offering a means to enhance monitoring and management AQ at Tin these settings in the future.

Microbial communities are found throughout the biosphere, from human guts to glaciers, from soil to activated sludge. Understanding the statistical properties of such diverse communities can pave the way to elucidate the common mechanisms ...Multiple ecological forces act together to shape the composition of microbial communities. Phyloecology approaches—which combine phylogenetic relationships between species with community ecology—have the potential to disentangle such forces but are often ...

The emission benefits of shifting towards battery electric vehicles have so far been hampered by a trend towards sports utility vehicles (SUVs). This study assesses the current and future emissions from SUVs and their potential impact on public health and climate targets. We modelled five scenarios of varying SUV sales and electrification rates, and projected associated carbon dioxide (CO2) and nitrogen oxide (NOx) emissions. Multiple linear regression was used to determine the relationship between vehicle characteristics and emissions. Cumulative CO2 emissions were valued using the social cost of carbon approach. Life table analyses were used to project and value life years saved from NOx emission reductions. Larger SUVs were disproportionately high emitters of CO2 and NOx. Replacing these with small SUVs achieved significant benefits, saving 702 MtCO2e by 2050 and 1.8 million life years from NO2 reductions. The largest benefits were achieved when combined with electrification, saving 1181 MtCO2e and gaining 3.7 million life years, with a societal value in the range of GBP 10–100s billion(s). Downsizing SUVs could be associated with major public health benefits from reduced CO2 and NOx emissions, in addition to the benefits of electrification. This could be achieved by demand-side mass-based vehicle taxation and supply-side changes to regulations, by tying emission limits to a vehicle’s footprint rather than its mass.

Many rail services around the world continue to use diesel as the primary fuel source and enclosed railway stations have been identified as a possible hotspot for exposure to harmful diesel exhaust exposures. Little is known about the occupational exposure to air pollution for railway station workers due to their mobility around the station and variations in station design. A detailed understanding of the concentration of black carbon (BC), a diesel exhaust tracer, inside railway stations and the factors driving occupational exposures is required to minimize occupational exposure. Real-time personal exposure to BC was measured during 60 work-shifts encompassing different roles at three large enclosed railway stations of different design in London, Birmingham and Edinburgh (UK). Sampling was conducted by the train station workers over a period of 27 days between January 2017 to October 2018. Worker shift-mean BC exposures ranged 0.6-20.8 mu gm(-3) but 1-min peak exposures reached 773 mu gm(-3), with train dispatchers experiencing the highest BC exposures. Station design, job role, and frequency of diesel trains were the main drivers of occupational BC exposure. Elevated exposures for some station workers indicate that mitigation measures to reduce their exposure should be implemented to lower the risk of occupational health impacts. These could include improving ventilation and reducing engine emissions.

•Contemporary climate - health relationships for 3 major UK cities are studied and projected to 2060•Ambulance dispatch data is used as the health metric•Significant differences in health-related outcomes are observed for the different cities•Implications of future climate projections for cities within the same country are significant.•Predictive models of climate related ambulance dispatches need to be bespoke for individual cities.

High NO2 concentrations (long term average of 383 µg/m3 in 2016/2017) recorded at Birmingham New Street railway station have resulted in the upgrade of the bi-directional fan system to aid wind dispersion within the enclosed platform environment. This paper attempts to examine how successful this intervention has been in improving air quality for both passengers and workers within the station. New air pollution data in 2020 has enabled comparisons to the 2016/2017 monitoring campaign revealing a 23–42% decrease in measured NO2 concentrations. The new levels of NO2 are below the Occupational Health standards but still well above the EU Public Health Standards. This reduction, together with a substantial decrease (up to 81%) in measured Particulate Matter (PM) concentrations, can most likely be attributed to the new fan system effectiveness. Carbon Monoxide levels were well below Occupational and Public Health Standards at all times. The COVID-19 pandemic “initial lockdown” period has also allowed an insight into the resultant air quality at lower rail-traffic intensities, which produced a further reduction in air pollutants, to roughly half the pre-lockdown concentrations. This study shows the scope of improvement that can be achieved through an engineering solution implemented to improve the ventilation system of an enclosed railway station. Further reduction in air pollution would require additional approaches, such as the removal of diesel engine exhaust emissions via the adoption of electric or diesel-electric hybrid powered services.

Birmingham New Street railway station in the UK has recently undergone a substantial redevelopment at a cost of more than £600 million. However, the unique underground tunnel geography of the platforms has remained virtually unchanged, which means that diesel exhaust gases are effectively trapped causing a daily build-up of air pollution in the station. A new ventilation system has been installed consisting of 98 bi-directional fans that are meant to disperse any air pollution out of the station. Unfortunately, the fans were triggered by carbon dioxide levels that do not significantly correlate with more serious air pollutants such as nitrogen oxides. In August 2018, new workplace exposure limits (WELs) were introduced for nitrogen monoxide (NO) and nitrogen dioxide (NO2). However, during a recent measurement campaign, one of the new WELs would have been exceeded on most days. Network Rail has undertaken to introduce a number of interventions, including the installation of new nitrogen monoxide/dioxide sensors to drive the ventilation system together with new sonic wind sensors, encouraging train operating companies to switch off idling diesel engines and encouraging more electric/hybrid trains.

The World Health Organization has highlighted that the number of deaths worldwide due to road accidents increases every year. It recommends that countries improve road safety for all people by providing sustainable and safe transport systems by 2030, efforts are especially required within Low Middle-Income Countries (LMICS). This study is the first to investigate the impact of rainfall on road accidents in Thailand. Thai emergency data were collected from the National Institute for Emergency Medicine (NIEM) between 2012 to 2018. A time-series design with generalized linear model (GLM) was applied to analyse the associations between road accidents and rainfall. The results are reported using relative risk (RR) at 95% confidence intervals compared with dry days. The effects of long-term trends, seasonality, day of the weeks, public holidays and other meteorological factors were controlled in the GLM. A meta-analysis was applied to summarise the estimate effect of rain groups stratified by the Northern and Southern provinces. Findings reported a significant increase in road accidents due to high rainfall levels both in the Southern and the Northern provinces. The pooled estimate risks in the Southern provinces have higher estimated risks than the Northern provinces. Both Northern and Southern provinces showed the rain group with 10 -20 mm/day having the highest pooled estimated risk with RR = 1.052, (95% CI: 1.026 -1.079) and RR = 1.062, (95% CI: 1.043 -1.082), respectively, while surprisingly, heavy rain with more than 20 mm/day reported a reduction of risks. Road accidents can therefore be associated with rainfall. It is recommended that rainfall is factored into ambulance forecast models and warning systems, allowing for improvements in ambulance service efficiency. Policymakers need to integrate road safety policies that reduce road accidents in wet weather.

This chapter is concerned with the relationship between the climate of London and the French artist Monet at the turn of the twentieth century. Monet's 'London Series' will be deconstructed in the light of contemporary weather, climate, and culture. The modernist view that the behaviour of the atmosphere was predictable did not make significant strides until the beginning of the twentieth century when Bjerknes in Norway led the way for Richardson in England to publish Weather Prediction by Numerical Process. Victorian London fog was probably the most famous global meteorological phenomenon of the nineteenth and twentieth centuries. The deconstruction of Monet's 'London Series' has shown that its paintings are an accurate souvenir of the perils of air pollution in London and as such they are a unique representation of the winter climate of London at that time, combining realism and naturalism.

A number of systematic reviews have investigated the association between air pollutants and health impacts, these mostly focus on morbidity and mortality from hospital data. Previously, no reviews focused solely on ambulance dispatch data. These data sets have excellent potential for environmental health research. For this review, publications up to April 2019 were identified using three main search categories covering: ambulance services including dispatches; air pollutants; and health outcomes. From 308 studies initially identified, 275 were excluded as they did not relate to ambulance service dispatches, did not report the air pollutant association, and/or did not study ambient air pollution. The main health outcomes in the remaining 33 studies were cardiac arrest (n = 14), cardiovascular (n = 11) and respiratory (n = 10) dispatches. Meta-analyses were performed to summarise pooled relative risk (RR) of pollutants: particulate matter less than 2.5 and 10 mu m (PM2.5, PM10), the fraction between PM10 and PM2.5 (coarse) and suspended particulate matter (SPM) per 10 mu g/m(3) increase, carbon monoxide (CO) per 1 ppm increase and of sulphur dioxide (SO2), nitrogen dioxide (NO2), and ozone (O-3) per 10 ppb increment and ambulance dispatches. Statistically significant associations were found for ambulance dispatch data for all-respiratory and PM2.5 at 1.03 (95% CI:1.02-1.04) and at 1.10 (95% CI:1.00-1.21) for asthma and NO2 associations. For dispatches with subsequent paramedic assessment for cardiac arrest with PM2.5, CO and coarse dispatches at 1.05 (95% CI:1.03-1.08), 1.10 (95% CI:1.02-1.18) and 1.04 (95% CI:1.01-1.06) respectively. For dispatches with subsequent physician diagnosis for all-respiratory and PM2.5 at 1.02 (95% CI:1.01-1.03). In conclusion, air pollution was significantly associated with an increase in ambulance dispatch data, including those for cardiac arrest, all-respiratory, and asthma dispatches. Ambulance services should plan accordingly during pollution events. Furthermore, efforts to improve air quality should lead to decreases in ambulance dispatches. (C) 2019 Elsevier Ltd. All rights reserved.

Urban heat advection (UHA) can extend the climatic impact of a city into the surrounding countryside. This may lead to an intensification of already well‐documented urban heat island (UHI) impacts on health and infrastructure, and challenge the representativeness of long‐term reference temperature records taken near urban areas. However, previous UHA studies have been unable to accurately quantify surface‐level UHA due to challenges arising from complex urban land‐use patterns. To address this, the numerical Weather Research and Forecasting (WRF) mesoscale model coupled with the Building Energy Parameterization urban canopy scheme is used to simulate meteorological fields for idealized land‐use cases. Hypothetical square cities (up to 32 km in size) are simulated for a year's period. A time‐mean 2‐m temperature field (representing the canopy UHI) shows that the mean UHI intensity (up to 4.3 °C [SD 1.7 °C]), wind speed <3.9 m/s) is linearly related to the logarithm of city size. This finding, entirely derived from numerical modelling, is consistent with the log‐linear relationships previously found in the observational data of many cities in the world. A UHA methodology was then applied to the temperature fields to separate UHA from the UHI, with up to 2.9 °C (SD 1.7 °C) of UHA found downwind of the largest city size. For this hypothetical city size, an UHA intensity of 0.5 °C is found up to 24‐km downwind from the urban boundary. In addition, the UHA‐distance profiles along the central horizontal transect for various urban sizes are found to follow a scaling rule as a good approximation. As a result, the findings of this paper can be used as a starting point for climate impact assessments for areas surrounding urban areas without the need for complex, computation‐intensive simulations.

Air pollution from diesel emissions is becoming an increased international concern, and whilst attention has been primarily focused on the automotive industry, concerns have also been raised about emissions from diesel rail vehicles. This paper reports an extensive series of measurements made at the Birmingham New Street station, a major rail interchange in the Midlands of England, with a mix of diesel and electric train movements, which is of particular concern because of the enclosed nature of the platforms. This study was undertaken in collaboration with Network Rail to better understand the environment in and around the station over a longer period to provide a more detailed analysis of the complex environment at the station. The station environment has been considered in terms of the European Union (EU) and Department of Environment, Food and Rural Affairs (DEFRA) limits as part of the monitoring methodology, but it should be noted that these limits do not apply in this environment as the Management of Health and Safety at Work Regulation 1999 and the Control of Substances Hazardous to Health Regulations 2002 are applicable. The monitoring campaign consisted of diffusion tube measurements to measure nitrogen dioxide at a large number of different locations throughout and around the station. These were followed by detailed measurements of oxides of nitrogen, particulate matter, carbon dioxide and black carbon (a diesel tracer) at a smaller number of sites at the platform level. The results are analysed to give concentrations over a wide variety of time scales, and long- and short-term averages. The effects of ambient wind conditions and individual train movements are also considered. Recommendations are made for possible remedial measures and for future work to more fully understand the physical mechanisms involved.

The association between episodes of extreme temperature and ambulance 999 calls has not yet been properly quantified. In this study we propose a statistical physics-based method to estimate the true mean number of ambulance 999 calls during episodes of extreme temperatures. Simple arithmetic mean overestimates the true number of calls during such episodes. Specifically, we apply the physics-based framework of nonextensive statistical mechanics (NESM) for estimating the probability distribution of extreme events to model the positive daily variation of ambulance calls. In addition, we combine NESM with the partitioned multiobjective method (PMRM) to determine the true mean of the positive daily difference of calls during periods of extreme temperature. We show that the use of the standard mean overestimates the true mean number of ambulance calls during episodes of extreme temperature. It is important to correctly estimate the mean value of ambulance 999 calls during such episodes in order for the ambulance service to efficiently manage their resources.

Ambulance services are in operation around the world and yet, until recently, ambulance data has only been used for operational purposes rather than for assessing public health. Ambulance call-out data offers new and valuable (near) real-time information that can be used to assess the impact of environmental conditions, such as temperature, upon human health. A detailed analysis of London ambulance data at a selection of dates between 2003 and 2015 is presented and compared to London temperature data. In London, the speed of ambulance response begins to suffer when the mean daily air temperature drops below 2 °C or rises above 20 °C. This is explained largely by the increased number of calls past these threshold temperatures. The baseline relationships established in this work will inform the prediction of likely changes in ambulance demand (and illness types) that may be caused by seasonal temperature changes and the increased frequency and intensity of extreme/severe weather events, exacerbated by climate change, in the future.

In 2012, the World Health Organization's International Agency for Research on Cancer (IARC) reclassified diesel engine exhaust and related ambient air pollution to be carcinogenic and associated with increased mortality from lung cancer. This could have critical consequences for both public and occupational health in enclosed railway stations where ventilation is often inadequate. Recent policies encouraging a shift to public transport, along with increasing passenger and train numbers, have led to a variety of co-benefits, including improved health and well-being from increased walking and cycling. This paper considers the unintended consequences of a reduction of air quality in crowded enclosed railway stations and concludes with a number of possible interventions to ensure that public health is not affected, especially by air pollution from stationary diesel trains. Pollution from electric trains can also lead to poor air quality due to the production of metal-rich ultrafine particles from brake linings, friction between wheel and rail, and from overhead pantographs. Current occupational health standards are not suitable for enclosed railway stations and need to be reconsidered in the light of the IARC findings. More measurements of the levels of particulates and nitrogen dioxide in enclosed railway stations need to be undertaken and published.

Weather and climate networks traditionally follow rigorous siting guidelines, with individual stations located away from frost hollows, trees or urban areas. However, the diverse nature of the UK landscape suggests that the feasibility of siting stations that are truly representative of regional climate and free from distorting local effects is increasingly difficult. Whilst the urban heat island is a well-studied phenomenon and usually accounted for, the effect of warm urban air advected downwind is rarely considered, particularly at rural stations adjacent to urban areas. Until recently, urban heat advection (UHA) was viewed as an urban boundary-layer process through the formation of an urban plume that rises above the surface as it is advected. However, these dynamic UHA effects are shown to also have an impact on surface observations. Results show a significant difference in temperatures anomalies (\(p\,< \,0.001\)) between observations taken downwind of urban and rural areas. For example, urban heat advection from small urbanized areas (\(\sim \)1\(\,\hbox {km}^{2}\)) under low cloud cover and wind speeds of 2–3\(\,\hbox {m}\,\hbox {s}^{-1}\) is found to increase mean nocturnal air temperatures by 0.6\(\,^{\circ }\hbox {C}\) at a horizontal distance of 0.5 km. Fundamentally, these UHA results highlight the importance of careful interpretation of long-term temperature data taken near small urban areas.

Recent studies have identified the significance of urban heat advection (UHA) as the process whereby heat, originally generated through urban modifications to the Earth's surface, is transported downwind of urban areas. Current techniques to separate UHA from local heat signals do not exclude the additional potential impacts of regional heat advection (RHA). For example, large‐scale coastal effects, in addition to latitude and longitude variations, could cause downwind temperature gradients to exist. In this study, the numerical Weather Research and Forecasting (WRF) model coupled with the Building Effect Parameterization (BEP) urban scheme is used to simulate meteorological fields for Birmingham, UK, at a high horizontal resolution (1 km2). The model is run over six case‐studies to provide over 1600 h of simulations (called ‘urban‐case’), and evaluated using a unique high‐resolution dataset from 32 weather stations across Birmingham. The UHA component is decomposed from RHA by conducting a second set of simulations (called ‘rural‐case’), where all urban land‐use is replaced with vegetation. Simulated directional ‘rural‐case’ time‐mean temperature fields, that show RHA, are then subtracted from the equivalent ‘urban‐case’ time‐mean fields. This effectively separates UHA from RHA and shows that a significant portion of heat, previously attributed to UHA in mesoscale modelling, is found to be due to RHA. Using the new methodology, a UHA signal up to 1.9 °C is found largely confined to within, and several kilometres downwind of, the urban areas. These UHA effects highlight the importance of using wind direction segmentation when determining local climate.