• Energy Research
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Cities have been struggling for many years with many transport problems, including the impact of carbon monoxide emitted by vehicles on the environment, traffic jams, high energy consumption, numerous accidents or high infrastructure costs. There is also a dynamic growth of vehicles on the roads, which is why an increasing number of cities are introducing intelligent transportation systems (ITS), which is part of the concept of smart cities. This paper proposes a new matrix to assess the effects of the ITS implementation in the context of a concept Smart City, which consists of five criteria: (1) movement speed; (2) safety; (3) environmental; (4) economic; (5) satisfaction and amenities for society/passengers. In this new approach the benchmark values of the indicators assigned to the criteria are involved and, therefore, it is possible to determine the level of effectiveness of the ITS in public transport that uses low-carbon energy. This research used literature studies to establish the criteria of effectiveness of ITS as well as a case study, namely public transport that uses low-carbon energy in a Polish city, which had the largest fleet of electric buses in Poland and implements and uses an ITS. Both, the theoretical and the empirical research results demonstrate the usefulness and potency of the proposed matrix to assess the effects of the ITS implementation in cities in the context of the development of a smart city. In that way, the proposed approach may be a useful tool for measuring the effects of ITS implementation in cities.

The future of road transportation systems faces fundamental changes concerning technological progress and business models. Automated and electric vehicles are coming into the market and evolving towards a service-based mobility system with promises to tackle energy and environmental issues in the mobility sector. Although recent studies have begun to explore the potential impact of shared and privately owned automated and electric vehicles (AEVs) mostly from an operational perspective, little is known about the life cycle impact of such future transport systems. To fill this gap, this paper aims to compare the life cycle environmental impacts of shared vs privately owned AEVs in a regional context. A life cycle assessment (LCA) approach is developed to appraise impact categories with a direct effect on human health, ecosystems, and resources availability. Given that automated vehicles are not yet being used massively, the LCA is applied to synthetic travel demand data to assess the characteristics of privately-owned AEVs and the results of an optimization model that determines the vehicle fleet and driving patterns of shared AEVs serving a regional case-study in the central region of Portugal. Two different vehicle seating capacities - one passenger (non-ridesharing) and four passengers (ridesharing) – are considered to evaluate shared mobility systems. Results show that shared mobility systems yield a potential reduction of up to 42% (with 4 passengers per vehicle) of the system's environmental impacts compared to privately owned automated vehicles. Human toxicity, mineral resource scarcity, and marine and freshwater ecotoxicity are the impact categories with a higher potential of reduction. ; Transport and Planning

Abstract Alternative vehicle technologies have a great potential to minimize the transportation-related environmental impacts, reduce the reliance of the U.S. on imported petroleum, and increase energy security. However, they introduce new uncertainties related to their environmental, economic, and social impacts and certain challenges for widespread adoption. In this study, a novel method, uncertainty-embedded dynamic life cycle sustainability assessment framework, is developed to address both methodological challenges and uncertainties in transportation sustainability research. The proposed approach provides a more comprehensive, system-based sustainability assessment framework by capturing the dynamic relations among the parameters within the U.S. transportation system as a whole with respect to its environmental, social, and economic impacts. Using multivariate uncertainty analysis, likelihood of the impact reduction potentials of different vehicle types, as well as the behavioral limits of the sustainability potentials of each vehicle type are analyzed. Seven sustainability impact categories are dynamically quantified for four different vehicle types (internal combustion, hybrid, plug-in hybrid, and battery electric vehicles) from 2015 to 2050. Although impacts of electric vehicles have the largest uncertainty, they are expected (90% confidence) to be the best alternative in long-term for reducing human health impacts and air pollution from transportation. While results based on deterministic (average) values indicate that electric vehicles have greater potential of reducing greenhouse gas emissions, plug-in hybrid vehicles have the largest potential according to the results with 90% confidence interval.

Electricity supply in India is from a centralized grid. Many parts of the country experience grid interruptions. Life cycle energy and environmental analysis has been done for a 27 kWp photovoltaic system which acts as grid backup for 3 h outage in an Indian urban residential scenario. This paper discusses energy requirements and carbon emission for a PV storage system for five different battery technologies in Indian context. This can be used as a metric for comparative analysis for new batteries, with an undeveloped market. The energy requirements for the components are quantified and are compared in terms of energy payback time (EPBT) and Net Energy Ratio (NER). All the calculations are done for Indian context. EPBT is found to be in the range of 2–4.5 years for all the systems, while NER is in the range of 6.6–2.52. NaS has the highest emission factor of 0.67 kgCO2/kWh and the least for NiCd (0.091 kgCO2/kWh). These factors can be used to select a PV battery option and to target selection of materials and systems based on the reported values.

Observational estimates and numerical models both indicate a significant overall decline in marine oxygen levels over the past few decades. Spatial patterns of oxygen change, however, differ considerably between observed and modelled estimates. Particularly in the tropical thermocline that hosts open-ocean oxygen minimum zones, observations indicate a general oxygen decline, whereas most of the state-of-the-art models simulate increasing oxygen levels. Possible reasons for the apparent model-data discrepancies are examined. In order to attribute observed historical variations in oxygen levels, we here study mechanisms of changes in oxygen supply and consumption with sensitivity model simulations. Specifically, the role of equatorial jets, of lateral and diapycnal mixing processes, of changes in the wind-driven circulation and atmospheric nutrient supply, and of some poorly constrained biogeochemical processes are investigated. Predominantly wind-driven changes in the low-latitude oceanic ventilation are identified as a possible factor contributing to observed oxygen changes in the low-latitude thermocline during the past decades, while the potential role of biogeochemical processes remains difficult to constrain. We discuss implications for the attribution of observed oxygen changes to anthropogenic impacts and research priorities that may help to improve our mechanistic understanding of oxygen changes and the quality of projections into a changing future. This article is part of the themed issue ‘Ocean ventilation and deoxygenation in a warming world’.

It is extremely important to understand which role Arctic fossil fuel resources will play in the development and geopolitics of the Arctic region. The article analyses the recent trends in the world energy supply with special focus on renewable energy and future demand for fossil fuels. Focusing on the Arctic LNG projects it comes to the conclusion that there is a growing possibility that the majority of Arctic oil and natural gas will be kept in the ground. Such an outcome would strongly influence the sustainable development and geopolitics of the region.

Recent regulatory requirements for shipping emissions control have led to the adoption of Liquefied Natural Gas (LNG) as a marine fuel and the design of LNG-fuelled vessels. Considering the potential safety implications due to system failure/unavailability, this study aims at the safety analysis of a low-pressure LNG fuel feeding system using a novel model-based methodology. The proposed methodology is based on the functional system modelling, leading to the failure diagrams development, and combines the use of Failure Modes, Effects, and Criticality Analysis (FMECA) and Fault Tree Analysis (FTA), which are performed in MADe™ and PTC Windchill software environments. The FMECA results are employed to identify the investigated system critical components and failures as well as specifying the top events for the subsequently performed FTA, which evaluates the top events failure rates. The system critical components identification leads to the system design modification targeting reduced safety metrics. This study results demonstrate that the evaporator, pressure build-up unit, sensors, and cryogenic valve assemblies are the most critical components of the investigated system, whilst the enhanced system design exhibits a failure rate reduced by 69% in comparison to the baseline system. This study reveals the advantages of the developed methodology along with some limitations of the employed tools and contributes to the quantitative safety analysis and design of ship complex systems.

In an era of environmental and socio-economic crisis, sustainable transport planning is vital as ever, especially given that the transport sector is responsible for the greatest part of total air pollution and greenhouse gas emissions. New vehicle technologies, such as autonomous and electric vehicles, emerge as promising alternatives, creating, however, both opportunities and challenges and raising questions relating to their performance. Can these new vehicle technologies really perform better than conventional ones in terms of sustainable mobility? Which one of them constitutes the optimum solution? How does each alternative perform with regard to different evaluation criteria, such as air pollution or road safety? In order to answer such questions, and to select the optimum solution, a comparison between autonomous, electric, autonomous electric and conventional vehicles is executed, based on a set of social, economic and environmental criteria. For this purpose, a new decision-aiding methodology, allowing for a holistic evaluation of the alternatives through a comprehensive literature review and experts’ participation, is applied. It is mainly based on the combined application of two hybrid multi-criteria analysis models, creating a more solid background towards optimum decision-making, thus constituting an important decision support tool for project appraisal and funding within the framework of sustainability in any sector.

This paper presents a life cycle assessment (LCA) of photovoltaic (PV) solar modules which have been integrated into electric vehicle applications, also called vehicle integrated photovoltaics (VIPV). The LCA was executed by means of GaBi LCA software with Ecoinvent v2.2 as a background database, with a focus on the global warming potential (GWP). A light utility electric vehicle (LUV) named StreetScooter Work L, with a PV array of 930 Wp, was analyzed for the location of Cologne, Germany. An operation time of 8 years and an average shadowing factor of 30% were assumed. The functional unit of this LCA is 1 kWh of generated PV electricity on-board, for which an emission factor of 0.357 kg CO2-eq/kWh was calculated, whereas the average grid emissions would be 0.435 kg CO2-eq/kWh. Hence, charging by PV power hence causes lower emissions than charging an EV by the grid. The study further shows how changes in the shadowing factor, operation time, and other aspects affect vehicle’s emissions. The ecological benefit of charging by PV modules as compared to grid charging is negated when the shadowing factor exceeds 40% and hence exceeds emissions of 0.435 kg CO2-eq/kWh. However, if the operation time of a vehicle with integrated PV is prolonged to 12 years, emissions of the functional unit go down to 0.221 kg CO2-eq/kWh. It is relevant to point out that the outcomes of the LCA study strongly depend on the location of use of the vehicle, the annual irradiation, and the carbon footprint of the grid on that location.

Particulate matter export fuels benthic ecosystems in continental margins and the deep sea, removing carbon from the upper ocean. Gelatinous zooplankton biomass provides a fast carbon vector that has been poorly studied. Observational data of a large-scale benthic trawling survey from 1994 to 2005 provided a unique opportunity to quantify jelly-carbon along an entire continental margin in the Mediterranean Sea and to assess potential links with biological and physical variables. Biomass depositions were sampled in shelves, slopes and canyons with peaks above 1000 carcasses per trawl, translating to standing stock values between 0.3 and 1.4 mg C m(2) after trawling and integrating between 30,000 and 175,000 m(2) of seabed. The benthopelagic jelly-carbon spatial distribution from the shelf to the canyons may be explained by atmospheric forcing related with NAO events and dense shelf water cascading, which are both known from the open Mediterranean. Over the decadal scale, we show that the jelly-carbon depositions temporal variability paralleled hydroclimate modifications, and that the enhanced jelly-carbon deposits are connected to a temperature-driven system where chlorophyll plays a minor role. Our results highlight the importance of gelatinous groups as indicators of large-scale ecosystem change, where jelly-carbon depositions play an important role in carbon and energy transport to benthic systems.