• Energy Research
• SA close
• DE close
• IN close
• Sustainability close

How can urban policies and planning approaches help in achieving a safer mobility and carbon reduction in the transport sector? The attention of planners and policy makers towards the promotion of sustainability and reduction of environmental impacts has grown in recent years. This paper investigates the role that Urban Planning plays in the long term towards a safer and climate friendlier mobility, highlighting the need for integrated approaches gathering spatial planning and mobility management. After a review of several urban policies and planning strategies, initiatives, and approaches, mainly based on the urban scale, the paper presents an urban regeneration case study leading to an increase of pedestrian accessibility at the neighborhood level. This can be seen as a support tool to foster sustainable, safe, and climate friendly mobility in cities. The results of the performed analysis show a dependency of accessibility from two different factors: the distribution of services and the capillarity of the soft mobility network, which can contribute to creating a more walkable space.

Due to climate change and current efforts to reduce emissions in the construction sector, this study evaluates and discusses the results of a comparative cradle-to-grave Life Cycle Assessment (LCA), with a main focus on Global Warming Potential for functionally equivalent carbon-reinforced concrete (CRC) and steel-reinforced concrete (SRC) façade panels for the first time. The novelty of this study is the focus on construction waste and, in particular, the worst-case application of non-recycled construction waste. The use of CRC requires a lower concrete thickness than SRC because the carbon fiber reinforcement does not corrode, in contrast to steel reinforcement. Façade panels of the same geometrical dimensions and structural performance were defined as functional units (FU). Assuming an End-of-Life (EoL) scenario of 50% landfill and 50% recycling, the Global Warming Potential (GWP, given in CO2 equivalent (CO2e)) of the CRC façade (411–496 kg CO2e) is shown to perform better than or equal to the SRC façade (492 kg CO2e). Changing the assumption of CRC to a worst-case scenario, going fully to landfill and not being recycled (single life cycle), turns the GWP results in favor of the SRC façade. Assuming a 50-year service life for the SRC façade panel and relativizing the emissions to the years, the more durable CRC façade performs much better. Finally, depending on the system boundary, the assumed EoL and lifetime, CRC can represent a lower-emission alternative to a functionally equivalent component made of SRC. The most important and “novel” result in this study, which also leads to future research opportunities, is that delicate adjustments (especially concerning EoL scenarios and expected service life) can lead to completely different recommendations for decision-makers. Only by combining the knowledge of LCA experts, structural engineers, and builders optimal decisions can be made regarding sustainable materials and building components.

The Urban Heat Island (UHI) is the phenomenon of altered increased temperatures in urban areas compared to their rural surroundings. UHIs grow and intensify under extreme hot periods, such as during heat waves, which can affect human health and also increase the demand for energy for cooling. This study applies remote sensing and land use/land cover (LULC) data to assess the cooling effect of varying urban vegetation cover, especially during extreme warm periods, in the city of Munich, Germany. To compute the relationship between Land Surface Temperature (LST) and Land Use Land Cover (LULC), MODIS eight-day interval LST data for the months of June, July and August from 2002 to 2012 and the Corine Land Cover (CLC) database were used. Due to similarities in the behavior of surface temperature of different CLCs, some classes were reclassified and combined to form two major, rather simplified, homogenized classes: one of built-up area and one of urban vegetation. The homogenized map was merged with the MODIS eight-day interval LST data to compute the relationship between them. The results revealed that (i) the cooling effect accrued from urban vegetation tended to be non-linear; and (ii) a remarkable and stronger cooling effect in terms of LST was identified in regions where the proportion of vegetation cover was between seventy and almost eighty percent per square kilometer. The results also demonstrated that LST within urban vegetation was affected by the temperature of the surrounding built-up and that during the well-known European 2003 heat wave, suburb areas were cooler from the core of the urbanized region. This study concluded that the optimum green space for obtaining the lowest temperature is a non-linear trend. This could support urban planning strategies to facilitate appropriate applications to mitigate heat-stress in urban area.

The main purpose of this article is to present an overview of the applications of sustainable practices in logistic operations performed by Brazilian companies. To reach this objective, the following steps were carried out: (1) a review of the literature on logistics systems and sustainability in logistics activities; (2) the collection of sustainability reports published by companies that perform logistics operations, which are recognized in Brazil; (3) a content analysis of the reports collected and (4) a discussion of the results, cross-checked with the literature and the extrapolation of conclusions. It was possible to identify 22 sustainable practices, and these practices were grouped into five macro areas. The authors of this paper believe that the findings presented here can be useful for professionals and researchers in the implementation of sustainability practices in logistics systems.

This study uniquely employs a fuzzy-set qualitative comparative analysis (fsQCA) technique to account for complex relationships in consumption. The fsQCA technique assumes that relationships are based on a set–subset relationship. This assumption is fundamental when decision-makers are affected by information asymmetry and are, thus, required to jointly evaluate the credibility and reliability of a range of external signals. This issue also affects consumers in markets for cultural goods, where the quality of products is not known with certainty in advance of the purchase decision. Our study uses fsQCA to establish the effect of different quality signals on consumption in the US market for video game software. Our results show that reviews from professional critics alongside brand extension and multi-platform release strategies act as signals of product quality and, therefore, lead to high sales performance.

This study aimed to realize Sustainable Development Goals (SDGs), i.e., no poverty, zero hunger, and sustainable cities and communities through the implementation of an intelligent cattle-monitoring system to enhance dairy production. Livestock industries in developing countries lack the technology that can directly impact meat and dairy products, where human resources are a major factor. This study proposed a novel, cost-effective, smart dairy-monitoring system by implementing intelligent wireless sensor nodes, the Internet of Things (IoT), and a Node-Micro controller Unit (Node-MCU). The proposed system comprises three modules, including an intelligent environmental parameter regularization system, a cow collar (equipped with a temperature sensor, a GPS module to locate the animal, and a stethoscope to update the heart rate), and an automatic water-filling unit for drinking water. Furthermore, a novel IoT-based front end has been developed to take data from prescribed modules and maintain a separate database for further analysis. The presented Wireless Sensor Nodes (WSNs) can intelligently determine the case of any instability in environmental parameters. Moreover, the cow collar is designed to obtain precise values of the temperature, heart rate, and accurate location of the animal. Additionally, auto-notification to the concerned party is a valuable addition developed in the cow collar design. It employed a plug-and-play design to provide ease in implementation. Moreover, automation reduces human intervention, hence labor costs are decreased when a farm has hundreds of animals. The proposed system also increases the production of dairy and meat products by improving animal health via the regularization of the environment and automated food and watering. The current study represents a comprehensive comparative analysis of the proposed implementation with the existing systems that validate the novelty of this work. This implementation can be further stretched for other applications, i.e., smart monitoring of zoo animals and poultry.

Is it true that a nuclear technology approach to generate electric energy offers a clean, safe, reliable and affordable, i.e., sustainable option? In principle yes, however a technology impact on the environment strongly depends on the actual implementation bearing residual risks due to technical failures, human factors, or natural catastrophes. A full response is thus difficult and can be given first when the wicked multi-disciplinary issues get well formulated and “resolved”. These problems are lying at the interface between: the necessary R&D effort, the industrial deployment and the technology impact in view of the environmental sustainability including the management of produced hazardous waste. As such, this problem is clearly of multi-dimensional nature. This enormous complexity indicates that just a description of the problem might cause a dilemma. The paper proposes a novel holistic approach applying Multi-Criteria Decision Analysis to assess the potential of nuclear energy systems with respect to a sustainable performance. It shows how to establish a multi-level criteria structure tree and examines the trading-off techniques for scoring and ranking of options. The presented framework allows multi-criteria and multi-group treatment. The methodology can be applied to support any pre-decisional process launched in a country to find the best nuclear and/or non-nuclear option according to national preferences and priorities. The approach addresses major aspects of the environmental footprint of nuclear energy systems. As a case study, advanced nuclear fuel cycles are analyzed, which were previously investigated by the Nuclear Energy Agency (NEA/OECD) expert group WASTEMAN. Sustainability facets of waste management, resource utilization and economics are in focus.

Saffron, also known as “the golden spice”, is one of the most expensive crops in the world. The expensiveness of saffron comes from its rarity, the tedious harvesting process, and its nutritional and medicinal value. Different countries of the world are making great economic growth due to saffron export. In India, it is cultivated mostly in regions of Kashmir owing to its climate and soil composition. The economic value generated by saffron export can be increased manyfold by studying the agronomical factors of saffron and developing a model for artificial cultivation of saffron in any season and anywhere by monitoring and controlling the conditions of its growth. This paper presents a detailed study of all the agronomical variables of saffron that have a direct or indirect impact on its growth. It was found that, out of all the agronomical variables, the important ones having an impact on growth include corm size, temperature, water availability, and minerals. It was also observed that the use of IoT for the sustainable cultivation of saffron in smart cities has been discussed only by very few research papers. An IoT-based framework has also been proposed, which can be used for controlling and monitoring all the important growth parameters of saffron for its cultivation.

Soil salinity and the use of saline groundwater are two major constraints in crop production, which covers a ~1.0 billion ha area of arid and semi-arid regions. The improved drainage function of soil can modify the salty growing environment for higher agricultural production. The present study evaluated the effectiveness of cut-soiler-constructed rice residue-filled preferential shallow subsurface drainage (PSSD) to improve the drainage function and its effect on the yield, quality and plant–water relations of mustard over 2019–2021. Cut-soiler-simulated drains were made in a semi-controlled lysimeter (2 × 2 × 3; L*W*H m) as the main plot treatment in a double replicated split–split experiment with two soil types (subplot) and three irrigation water salinities (4, 8 and 12 dS m−1) as the sub-sub-plot treatment. The drainage volume of variable salinity (EC), dependent on the total water input, was substantially higher in the rainy season (April to October), i.e., 16.6, 7.76 and 12.0% during 2018, 2019 and 2020, with 1.7, 0.32 and 0.77 kg salt removal per lysimeter, compared to the post-rainy season. The mustard seed, straw and biological yields were improved by 31.4, 14.41 and 18.08%, respectively, due to a positive effect on plant–water relations. The mustard seeds produced in the cut-soiler-treated plots recorded higher oil, crude fiber and protein contents and a lower erucic acid content. The increase in salt load, by higher-salinity irrigation water, was also efficiently managed by using cut-soiler PSSD. It was found that the saline irrigation water up to 12.0 dS m−1 can be used under such PSSD without any extra salt loading. The present study showed the potential of cut-soiler PSSD in root zone salinity management by improving drainage in salt-affected arid regions.

The promotion of electric vehicles (EVs) is an important measure for dealing with climate change and reducing carbon emissions, which are widely agreed goals worldwide. Being an important operating mode for electric vehicle charging stations in the future, the integrated photovoltaic and energy storage charging station (PES-CS) is receiving a fair amount of attention and discussion. However, how to optimally configure photovoltaic and energy storage capacity to achieve the best economy is essential and a huge challenge to overcome. In this paper, based on the historical data-driven search algorithm, the photovoltaic and energy storage capacity allocation method for PES-CS is proposed, which determines the capacity ratio of photovoltaic and energy storage by analyzing the actual operation data, which is performed while considering the target of maximizing economic benefits. In order to achieve the proposed capacity allocation, the method is as follows: First, the economic benefit model of the charging stations is established, taking the net present value and investment payback period as evaluation indicators; then, by analyzing the operation data of the existing charging station with the target of maximizing economic benefits, the initial configuration capacity is obtained; finally, the capacity configuration is verified through a comprehensive case analysis for the actual operation data. The results show that the capacity configuration obtained through the data analysis features an optimized economic efficiency and photovoltaic utilization. The proposed method can provide a theoretical and practical basis for newly planned or improved large-scale charging stations.