Ambient Air Quality in the Czech Republic

Ambient air quality in the present-day Czech Republic (CR), one of the two succession countries of Czechoslovakia post-1993, was perceived as a major problem with severe human health and environmental consequences, particularly between the 1970s and 1990s. Since that time, the ambient air quality in the CR has improved substantially, due to newly introduced stringent legislation and technical countermeasures. Nevertheless, there are still activities which represent significant emission sources, such as local heating and increased vehicle travel through communities. After a substantial decrease in emissions in both the CR and its neighbouring countries, the levels of some ambient air pollutants from the 2000s are still not satisfactory. In this respect, aerosol, ground-level ozone, and benzo[a]pyrene remain major problems, as they do elsewhere in Europe. The book provides a valuable update both on time trends and spatial changes in ambient air quality, and highlights the recent activities in both monitoring and modelling of principle ambient air pollutants in the CR

Aeronautical engineering. A continuing bibliography with indexes, supplement 127, October 1980

A bibliography containing 431 abstracts addressing various topics in aeronautical engineering is given. The coverage includes engineering and theoretical aspects of design. construction, evaluation, testing, operation, and performance of aircraft (including aircraft engines) and associated components, equipment, and systems. It also includes research and development in aerodynamics, aeronautics, and ground support equipment for aeronautical vehicles

A novel framework for enhancing marine dual fuel engines environmental and safety performance via digital twins

The Internet of Things (IoT) advent and digitalisation has enabled the effective application of the digital twins (DT) in various industries, including shipping, with expected benefits on the systems safety, efficiency and environmental footprint. The present research study establishes a novel framework that aims to optimise the marine DF engines performance-emissions trade-offs and enhance their safety, whilst delineating the involved interactions and their effect on the performance and safety. The framework employs a DT, which integrates a thermodynamic engine model along with control function and safety systems modelling. The DT was developed in GT-ISE© environment. Both the gas and diesel operating modes are investigated under steady state and transient conditions. The engine layout is modified to include Exhaust Gas Recirculation (EGR) and Air Bypass (ABP) systems for ensuring compliance with ‘Tier III’ emissions requirements. The optimal DF engine settings as well as the EGR/ABP systems settings for optimal engine efficiency and reduced emissions are identified in both gas and diesel modes, by employing a combination of optimisation techniques including multi-objective genetic algorithms (MOGA) and Design of Experiments (DoE) parametric runs. This study addresses safety by developing an intelligent engine monitoring and advanced faults/failure diagnostics systems, which evaluates the sensors measurements uncertainty. A Failure Mode Effects and Analysis (FMEA) is employed to identify the engine safety critical components, which are used to specify operating scenarios for detailed investigation with the developed DT. The integrated DT is further expanded, by establishing a Faulty Operation Simulator (FOS) to simulate the FMEA scenarios and assess the engine safety implications. Furthermore, an Engine Diagnostics System (EDS) is developed, which offers intelligent engine monitoring, advanced diagnostics and profound corrective actions. This is accomplished by developing and employing a Data-Driven (DD) model based on Neural Networks (NN), along with logic controls, all incorporated in the EDS. Lastly, the manufacturer’s and proposed engine control systems are combined to form an innovative Unified Digital System (UDS), which is also included in the DT. The analysis of marine (DF) engines with the use of an innovative DT, as presented herein, is paving the way towards smart shipping.The Internet of Things (IoT) advent and digitalisation has enabled the effective application of the digital twins (DT) in various industries, including shipping, with expected benefits on the systems safety, efficiency and environmental footprint. The present research study establishes a novel framework that aims to optimise the marine DF engines performance-emissions trade-offs and enhance their safety, whilst delineating the involved interactions and their effect on the performance and safety. The framework employs a DT, which integrates a thermodynamic engine model along with control function and safety systems modelling. The DT was developed in GT-ISE© environment. Both the gas and diesel operating modes are investigated under steady state and transient conditions. The engine layout is modified to include Exhaust Gas Recirculation (EGR) and Air Bypass (ABP) systems for ensuring compliance with ‘Tier III’ emissions requirements. The optimal DF engine settings as well as the EGR/ABP systems settings for optimal engine efficiency and reduced emissions are identified in both gas and diesel modes, by employing a combination of optimisation techniques including multi-objective genetic algorithms (MOGA) and Design of Experiments (DoE) parametric runs. This study addresses safety by developing an intelligent engine monitoring and advanced faults/failure diagnostics systems, which evaluates the sensors measurements uncertainty. A Failure Mode Effects and Analysis (FMEA) is employed to identify the engine safety critical components, which are used to specify operating scenarios for detailed investigation with the developed DT. The integrated DT is further expanded, by establishing a Faulty Operation Simulator (FOS) to simulate the FMEA scenarios and assess the engine safety implications. Furthermore, an Engine Diagnostics System (EDS) is developed, which offers intelligent engine monitoring, advanced diagnostics and profound corrective actions. This is accomplished by developing and employing a Data-Driven (DD) model based on Neural Networks (NN), along with logic controls, all incorporated in the EDS. Lastly, the manufacturer’s and proposed engine control systems are combined to form an innovative Unified Digital System (UDS), which is also included in the DT. The analysis of marine (DF) engines with the use of an innovative DT, as presented herein, is paving the way towards smart shipping

Investigating the impacts of increased uptake of electric vehicles on air quality and health

PhD ThesisGlobally, nine million deaths per year are attributed to exposure to air pollution, as estimated by the Lancet Commission on Pollution and Health (Landrigan et al., 2018). In the UK, approximately 40,000 deaths per annum are attributed to exposure to PM2.5 and NO2, costing society nearly £20 billion annually from the health-related consequences of people suffering diseases and early deaths (Royal College of Physicians, 2016). Road transport emissions are a major source of air contaminants, and in 2016 they contributed to 12.4% of PM2.5, 11.7% of PM10 and 33.6% of NOx (DEFRA, 2018); the latter contributing 80% of NO2 concentrations at roadsides (DEFRA and DfT, 2017a). Additionally, vehicular emissions account for 24% of greenhouse gas (GHG) emissions (BEIS, 2018a). To mitigate air quality pollutants and GHGs, the UK government’s Road to Zero strategy plans to limit the sale of new cars and vans to ultra-low emissions vehicles (ULEVs), mainly focusing on electric vehicles (EVs), by 2040 with the aim of forming an entire stock of ULEVs by 2050. Currently, the government is investing £1.5 billion in measures dedicated to increasing the penetration of ULEVs and optimising their manufacturing and infrastructure. These measures would result in changes in the vehicle fleet mix and consequently reductions in emissions and pollutant concentrations. A detailed investigation is needed to quantify their impact. In this research, the impact of changes in the vehicle fleet with the increased adoption of EV, on air quality and health was investigated via scenarios that consider different levels of future EV uptake replacing conventional vehicles in Newcastle and Gateshead. Road transport network data for 2010 for the study area was acquired and updated to provide the 2014 Baseline, considering traffic growth for each vehicle class. The Baseline traffic model was validated following the Design Manual for Roads and Bridges criteria. The resulting emissions rates were calculated using an emissions model. The dispersion of pollutants was modelled taking into consideration the effect of meteorological factors. The air quality model was validated following DEFRA Technical Guidance. The 2014 Baseline traffic was updated to business-as-usual (BAU) for 2030. Six future scenarios were developed based on this BAU. These scenarios include: 1. ‘CCC’: Committee on Climate Change proposal for 30% of cars and 38% of vans being electric; 2. ‘E-Bus’: electrification of all buses; 3. ‘E-Car’: electrification of all cars; 4. ‘E-Car_E-Bus’: electrification of all cars and buses; 5. ‘E-Car_E-LGV’: electrification of all cars and LGVs; and 6. ‘All-EV’: electrification of all vehicles. Emission and dispersion models were applied to determine changes in air quality in response to the BAU and the six scenarios. The results indicate that pollution concentrations in 2030 would be reduced to varying extents compared to the 2014 Baseline. The annual mean reductions at the 66 General Practitioner (GP) sites were averaged for all 2030 scenarios across the study and showed a drop of 8 µg/m3 in NO2 levels and 3 µg/m3 in PM10 and PM2.5 levels. The Department of Health recommended dose-response coefficients, which describe the association between exposure to a certain amount of pollutants and the probabilities of being admitted to hospital and early mortality, were applied to the pollutant reductions at each GP site to estimate the number of respiratory hospital admissions at each GP location. Disease burden estimates suggest that the 2030 BAU will reduce hospital admissions by 1,297, representing 13% of the 9,693 cases recorded in 2014. It was noted that a large reduction in hospital admissions would occur due to decreases in NO2 concentrations. In the All-EV ii scenario, hospital admissions are expected to be reduced by 1,377, which could also nearly be achieved either by electrifying all cars and all buses or electrifying all cars and LGVs with a lower cost in relation to All-EV. Reducing premature mortality is estimated to account for 14 to 16 incidents. This study shows that the EV uptake scenarios will result in significant reductions in air pollution emissions and concentrations and consequent hospital admissions compared to BAU taking into consideration the relatively small population of Newcastle and Gateshead

Aeronautical engineering: A continuing bibliography with indexes, supplement 109

This bibliography lists 466 reports, articles, and other documents introduced into the NASA scientific and technical information system in April 1979

Transportation Systems Analysis and Assessment

The transportation system is the backbone of any social and economic system, and is also a very complex system in which users, transport means, technologies, services, and infrastructures have to cooperate with each other to achieve common and unique goals.The aim of this book is to present a general overview on some of the main challenges that transportation planners and decision makers are faced with. The book addresses different topics that range from user's behavior to travel demand simulation, from supply chain to the railway infrastructure capacity, from traffic safety issues to Life Cycle Assessment, and to strategies to make the transportation system more sustainable