Intervention of an Upgraded Ventilation System and Effects of the COVID-19 Lockdown on Air Quality at Birmingham New Street Railway Station

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.

A perspective on persistent toxicants in veterans and amyotrophic lateral sclerosis: identifying exposures determining higher ALS risk

Multiple studies indicate that United States veterans have an increased risk of developing amyotrophic lateral sclerosis (ALS) compared to civilians. However, the responsible etiological factors are unknown. In the general population, specific occupational (e.g. truck drivers, airline pilots) and environmental exposures (e.g. metals, pesticides) are associated with an increased ALS risk. As such, the increased prevalence of ALS in veterans strongly suggests that there are exposures experienced by military personnel that are disproportionate to civilians. During service, veterans may encounter numerous neurotoxic exposures (e.g. burn pits, engine exhaust, firing ranges). So far, however, there is a paucity of studies investigating environmental factors contributing to ALS in veterans and even fewer assessing their exposure using biomarkers. Herein, we discuss ALS pathogenesis in relation to a series of persistent neurotoxicants (often emitted as mixtures) including: chemical elements, nanoparticles and lipophilic toxicants such as dioxins, polycyclic aromatic hydrocarbons and polychlorinated biphenyls. We propose these toxicants should be directly measured in veteran central nervous system tissue, where they may have accumulated for decades. Specific toxicants (or mixtures thereof) may accelerate ALS development following a multistep hypothesis or act synergistically with other service-linked exposures (e.g. head trauma/concussions). Such possibilities could explain the lower age of onset observed in veterans compared to civilians. Identifying high-risk exposures within vulnerable populations is key to understanding ALS etiopathogenesis and is urgently needed to act upon modifiable risk factors for military personnel who deserve enhanced protection during their years of service, not only for their short-term, but also long-term health.

EXHAUST NOISE ANALYSIS RESEARCH FOR A SINGLE-CYLINDER DIESEL ENGINE AND EVALUATION OF NOISE FILTRATION BY SIMULATION

The paper develops an ana lysis of exhaust noise for a single-cylinder diesel engine tested in laboratory conditions. The acoustic signal at the engine exhaust system, for the speed range 1,300 – 2,700 rpm was measured and recorded. The results of the noise recordings were subjected to a processing from which the variation of the noise level depending on the engine speed was obtained. Next, the physiological effect of acoustic filtrations for noise recordings was analyzed by simulation. This allowed the optimization of the exhaust noise, having identified the areas and the optimal attenuation effect. In the performed simulations, it was found that the low frequencies require the highest attenuation background.

Interpolation Method for Visual Simulation of Engine Exhaust Flame

Propulsive force and exhaust fluid temperature are important indicators in the performance of an engine. An investigation of the effects of propellant composition, plane flight conditions, and engine operating environment on rocket thrust and the range of smoke plume temperature can provide references in the design of engine mechanics at the optimization of propellant composition, in monitoring of target identification and in the evolving of stealth of stealth technology. In order to understand the characteristics of the engine tail flame, a visual simulation of the engine tail flame was carried out by combining the engine operating conditions with the tail flame conditions. Based on the advantages of the bicubic spline interpolation algorithm and the Kriging interpolation algorithm, this paper proposes a hybrid interpolation algorithm, which performs color mapping and three-dimensional space separation in the engine plume data set and model, and visualizes the engine and engine plume. The simulation realizes real-time monitoring of the functions of various engine components through characteristic colors. The research results show that the hybrid interpolation method can effectively visualize the engine exhaust flame. The simulated plume has a relatively obvious temperature peak at 0.7 m, and the temperature of the plume flow field is significantly higher than that of the frozen plume flow field by about 200 ~1000 K. This shows that the algorithm in this paper helps to visualize the expression of engine tail flame information.