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According to a report by the World Bank published in April 2018, air pollution in Tehran incurs annual loss of billions of dollars and over 4,000 premature deaths from exposure to fine particles ambient concentrations. Particulate matter (PM), one of the primary pollutants from diesel exhaust, is associated with many different types of respiratory and cardiovascular effects, and premature mortality. The main objective of this study is to evaluate the cost effectiveness of retrofitting existing city diesel bus fleet in Tehran with best available Diesel particulate filters (DPFs) available in the market. The report provides an updated assessment on the diesel retrofit solutions for an ageing diesel city bus fleet in Tehran based on publicly available information. The economic benefits of DPF installed in buses are evaluated with standard techniques of environmental economics, and technological assumptions about how much PM emissions can be avoided and control costs. The report highlights a number of national, regional and local examples of effective emission control program that exhibit best practices from around the world. Also, it presents important features and global experiences of successful retrofit program on heavy-duty diesel vehicles (HDDVs), including benefit-cost analysis from several case studies to help Tehran city leadership in taking informed economic and policy decisions. Finally, it recommends a set of critical actions to the government both at the national and local level for implementation of an effective emission control programs.

This paper presents a tradeoff analysis in terms of accuracy and computational cost between different architectures of artificial neural networks for the State of Charge (SOC) estimation of lithium batteries in hybrid and electric vehicles. The considered layouts are partly selected from the literature on SOC estimation, and partly are novel proposals that have been demonstrated to be effective in executing estimation tasks in other engineering fields. One of the architectures, the Nonlinear Autoregressive Neural Network with Exogenous Input (NARX), is presented with an unconventional layout that exploits a preliminary routine, which allows setting of the feedback initial value to avoid estimation divergence. The presented solutions are compared in terms of estimation accuracy, duration of the training process, robustness to the noise in the current measurement, and to the inaccuracy on the initial estimation. Moreover, the algorithms are implemented on an electronic control unit in serial communication with a computer, which emulates a real vehicle, so as to compare their computational costs. The proposed unconventional NARX architecture outperforms the other solutions. The battery pack that is used to design and test the networks is a 20 kW pack for a mild hybrid electric vehicle, whilst the adopted training, validation and test datasets are obtained from the driving cycles of a real car and from standard profiles.

This study investigates the perspectives of researchers and business professionals on the Physical Internet (PI) and its application in city logistics. Through a two-part survey involving 83 participants from Europe and the United States, the research explores the perceived key elements for PI's successful implementation, its potential to enhance the efficiency and sustainability of urban logistics operations, and the main challenges to its adoption. The findings reveal a general optimism about PI's potential, with technology, collaboration, and infrastructure identified as critical success factors. However, concerns regarding costs, resistance to change, and technological limitations are also highlighted. The study concludes with suggestions for increasing awareness and fostering cross-sector collaboration to realize PI's full potential in transforming urban logistics. Presented at the 10th International Physical Internet Conference (IPIC 2024) 29-31 May 2024, Savannah, GA USA

The intense growth of cities affects their inhabitants to a considerable extent. The issues facing the traveling population include congestion and growing harmful emissions. Urban transport requires changes towards eco-friendly solutions. However, even though new forms of traveling (sharing services) are being implemented, their integration with public transport remains problematic. On account of the large number of available services combined with the absence of their integration, city inhabitants are faced with the dilemma of choosing between one or several transport modes which would enable them to make the given trip. The main goal of this article is to propose a model for integration of different transport services which could support those who intend to travel in the decision-making process. Therefore, the parameters of a model of urban sharing services were identified and classified. The parameters discussed in the paper with reference to an extensive literature review describe how individual sharing services are functioning. What has also been identified is the location-specific factors as well as those related to the potential area of operation which affect the integration with public transport. In order to take all the relevant parameters into account and find a solution to the problem at hand, a multi-criteria decision-making approach has been proposed. To this end, scores and weights determining their impact on the model have been established. For purposes of the solution in question, the relevant calculations were conducted by referring to an actual need to travel between selected locations.

Research to date has suggested that both individual marine species and ecological processes are expected to exhibit diverse responses to the environmental effects of climate change. Evolutionary responses can occur on rapid (ecological) timescales, and yet studies typically do not consider the role that adaptive evolution will play in modulating biological responses to climate change. Investigations into such responses have typically been focused at particular biological levels (e.g., cellular, population, community), often lacking interactions among levels. Since all levels of biological organisation are sensitive to global climate change, there is a need to elucidate how different processes and hierarchical interactions will influence species fitness. Therefore, predicting the responses of communities and populations to global change will require multidisciplinary efforts across multiple levels of hierarchy, from the genetic and cellular to communities and ecosystems. Eventually, this may allow us to establish the role that acclimatisation and adaptation will play in determining marine community structures in future scenarios.

AbstractAccelerated warming and melting of Arctic sea-ice has been associated with significant increases in phytoplankton productivity in recent years. Here, utilizing a multiproxy approach, we reconstruct an annually resolved record of Labrador Sea productivity related to sea-ice variability in Labrador, Canada that extends well into the Little Ice Age (LIA; 1646 AD). Barium-to-calcium ratios (Ba/Ca) and carbon isotopes (δ13C) measured in long-lived coralline algae demonstrate significant correlations to both observational and proxy records of sea-ice variability, and show persistent patterns of co-variability broadly consistent with the timing and phasing of the Atlantic Multidecadal Oscillation (AMO). Results indicate reduced productivity in the Subarctic Northwest Atlantic associated with AMO cool phases during the LIA, followed by a step-wise increase from 1910 to present levels—unprecedented in the last 363 years. Increasing phytoplankton productivity is expected to fundamentally alter marine ecosystems as warming and freshening is projected to intensify over the coming century.

Multiport power converters integrate three or more energy devices into a single (potentially highly controllable and efficient) hub. These characteristics suggest that multiport power converters may be valuable for the decarbonisation of distribution networks, where the increase of converter-interfaced devices has degraded system reliability and efficiency. This review analyses the suitability of a wide range of multiport power converter solutions for four example distribution network applications (where previous studies have focussed on a limited range of topologies or applications) and the research areas that can progress their maturity. A review of grid codes and standards overviews the base capability that multiport power converters are likely to require, some of which are carried forward as requirements for a novel comparison tool. The comparison tool is developed to qualify and score reviewed topologies in terms of a range of features that are weighted for the applications. Isolated and partially-isolated topologies perform well due to their flexibility to be configured for the specifications and their operational capabilities (including modularity and voltage decoupling). Further research should focus on the complex control interactions between ports and scaling of these topologies for medium voltages. In contrast, many direct current non-isolated topologies do not qualify due to their low flexibility to be configured for the applications. This suggests that future research could focus on the development of a more flexible non-isolated multiport power converter configuration to take advantage of the high efficiency and low footprint that these topologies might otherwise offer for low voltage applications. This project was funded by the Innovate UK Horizon Europe Guarantee application number 10039599. This work was also funded by the European Union's Horizon Europe research and innovation programme in the framework of the project “iPLUG” with grant agreement 101069770. . Peer Reviewed