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Greater New Orleans is surrounded by wetlands, the Mississippi River and two lakes. Excess rain can only be drained off with pumping systems or by evaporation due to the bowl-like shape of a large part of the city. As part of the solution to make New Orleans climate adaptive, green infrastructure has been implemented that enable rainfall infiltration and evapotranspiration of stored water after Hurricane Katrina in 2005. The long-term efficiency of infiltrating water under sea level with low permeable soils and high groundwater tables is often questioned. Therefore, research was conducted with the full-scale testing method measuring the infiltration capacity of 15 raingardens and 6 permeable pavements installed in the period 2011–2022. The results show a high variation of empty times for raingardens and swales: 0.7 to 54 m/d. The infiltration capacity decreased after saturation (ca 30% decrease in empty time after refilling storage volume) but all the tested green infrastructure met the guideline to be drained within 48 h. This is in contrast with the permeable pavement: only two of the six tested locations had an infiltration capacity higher than the guideline 10 inch/h (254 mm/h). The results are discussed with multiple stakeholders that participated in ClimateCafe New Orleans. Whether the results are considered unacceptable depends on a number of factors, including its intended purpose, site specific characteristics and most of all stakeholder expectations and perceptions. The designing, planning and scheduling of maintenance requirements for green infrastructure by stormwater managers can be carried out with more confidence so that green infrastructure will continue to perform satisfactorily over the intended design life and can mitigate the effects of heavy rainfall and droughts in the future.
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Implementation of green supply chain management (GSCM) has gained increasing attention as businesses seek to balance economic, social, and environmental sustainability. However, its adoption remains uneven across countries, particularly in developing economies such as Indonesia. This study aims to identify the key factors influencing the implementation of GSCM in Indonesian logistics companies using a qualitative approach. Data were collected via structured interviews with 14 senior management professionals from various logistics and supply chain companies. The findings reveal that, while awareness of GSCM exists, its implementation is hindered by high costs, regulatory limitations, inadequate infrastructure, and a lack of shared understanding or strategic prioritization among stakeholders, which points to a deeper organizational and policy disconnect regarding sustainability goals. Conversely, cost efficiency, brand image enhancement, and compliance with emerging regulations are identified as primary drivers of GSCM adoption. The study highlights the need for stronger government policies, financial incentives, and industry-wide collaboration to accelerate the adoption of sustainable supply chain practices. These insights contribute to both theoretical discussions on sustainable supply chain management and practical strategies for improving GSCM implementation in developing economies
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Computers create environmental problems. Their production requires electricity, raw materials, chemical materials and large amounts of water, and supplies (often toxic) waste. They poison dumping sites and pollute groundwater. In addition, the energy consumption in IT is growing exponentially, with and without the use of ‘green’ energy. Increasing environmental awareness within information science has led to discussions on sustainable development. ‘Green Computing’ has been introduced: the study and practice of environmentally sustainable computing or IT. It is necessary to pay attention to the value of the information stored. In this paper, we explored the possibilities of combining Green Computing components with two theories of archival science (Archival Retention Levels and Information Value Chain respectively) to curb unnecessary power consumption. Because in 2012 storage networks were responsible for almost 30 % of total IT energy costs, reducing the amount of stored information by the disposal of unneeded information should have a direct effect on IT energy use. Based on a theoretical analysis and qualitative interviews with an expert group, we developed a ‘Green Archiving’ model, that could be used by organizations to 1] reduce the amount of stored information, and 2] reduce IT power consumption. We used two exploratory case studies to research the viability of this model.
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Developers of charging infrastructure, be it public or private parties, are highly dependent on accurate utilization data in order to make informed decisions where and when to expand charging points. The Amsterdam The Amsterdam University of Applied Sciences in close cooperation with the municipalities of Amsterdam, Rotterdam, The Hague, Utrecht and the metropolitan region of Amsterdam developed both the back- and front-end of a decision support tool. This paper describes the design of the decision support tool and its DataWareHouse architecture. The back-end is based on a monthly update of charging data with Charge point Detail Records and Meter Values enriched with location specific data. The design of the front-end is based on Key Performance Indicators used in the decision process for charging infrastructure roll-out. Implementing this design and DataWareHouse architecture allows all kinds of EV related companies and cities to start monitoring their charging infrastructure. It provides an overview of how the most important KPIs are being monitored and represented in the decision support tool based on regular interviews and decision processes followed by four major cities and a metropolitan region in the Netherlands.
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Almere is a green city where the greenery extends into the centre through a framework of nature, forests, parks and canals. With this green environment, Almere fulfils an important condition for a liveable city, where it is pleasant to live and work. An important goal for the municipality is to challenge its residents to develop a healthy lifestyle by using that green framework.But what really motivates Almeerders to go outside to exercise, enjoy the surroundings and meet each other? Are there sufficient green meeting or sports facilities nearby? Could the routes that connect the living and working environment with the larger parks or forests be better designed? And can those routes simultaneously contribute to climate adaptation?With the Green Escape Challenge, we invited students and young professionals to work on these assignments together.
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Information and Communication Technologies (ICTs) affect the environment in various ways. Their energy consumption is growing exponentially, with and without the use of ‘green’ energy. Increasing environmental awareness within information science has led to discussions on sustainable development. ‘Green Computing’ has been introduced: the study and practice of environmentally sus- tainable computing. This can be defined as ‘designing, manufacturing, using, and disposing of com- puters, servers, and associated subsystems - such as monitors, printers, storage devices, and net- working and communications systems - efficiently and effectively with minimal or no impact on the en- vironment’. Nevertheless, the data deluge makes it not only necessary to pay attention to the hard- and software dimensions of ICTs but also to the value of the data stored. We explore the possibilities to use information and archival science to reduce the amount of stored data. In reducing this amount of stored data, it’s possible to curb unnecessary power consumption. The objectives of this paper are to develop a model (and test its viablility) to [1] increase awareness in organizations for the environ- mental aspects of data storage, [2] reduce the amount of stored data, and [3] reduce power consump- tion for data storage. This model integrates the theories of Green Computing, Information Value Chain (IVC) and Archival Retention Levels (ARLs). We call this combination ‘Green Archiving’. Our explora- tory research was a combination of desk research, qualitative interviews with information technology and information management experts, a focus group, and two exploratory case studies. This paper is the result of the first stage of a research project that is aimed at developing low power ICTs that will automatically appraise, select, preserve or permanently delete data based on their value. Such an ICT will automatically reduce storage capacity and curb power consumption used for data storage. At the same time, data disposal will reduce overload caused by storing the same data in different for- mats, it will lower costs and it reduces the potential for liability.
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Communities worldwide are critically re-examining their seasonal cultures and calendars. As cultural frameworks, seasons have long patterned community life and provided repertoires for living by annual rhythms. In a chaotic world, the seasons - winter, the monsoon and so on - can feel like stable cultural landmarks for reckoning time and orienting our communities. Seasons are rooted in our pasts and reproduced in our present. They act as schemes for synchronising community activities and professional practices, and as symbol systems for interpreting what happens in the world. But on closer inspection, seasons can be unstable and unreliable. Their meanings can change over time. Seasonal cultures evolve with environments and communities’ worldviews, values, technologies and practices, affecting how people perceive seasonal patterns and behave accordingly. Calendars are contested, especially now. Communities today find themselves in a moment of accelerated and intersecting changes - from climate to social, political, and technological - that are destabilizing seasonal cultures. How they reorient themselves to shifting patterns may affect whether seasonal rhythms serve as resources, or lead people down maladaptive pathways. A focus on seasonal cultures builds on multi-disciplinary work. The social sciences, from anthropology to sociology, have long studied how seasons order people’s sense of time, social life, relationship to the environment, and politics. In the humanities, seasons play an important role in literature, art, archaeology and history. This book advances scholarship in these fields, and enriches it with extrascientific insights from practice, to open up exiting new directions in climate adaptation. Critically questions traditional, often-static notions of seasons; re-interpreting them as more flexible, cultural frameworks adapting to changes to our societies and environments.
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In Europe, green hydrogen and biogas/green gas are considered important renewable energy carriers, besides renewable electricity and heat. Still, incentives proceed slowly, and the feasibility of local green gas is questioned. A supply chain of decentralised green hydrogen production from locally generated electricity (PV or wind) and decentralised green gas production from locally collected biomass and biological power-to-methane technology was analysed and compared to a green hydrogen scenario. We developed a novel method for assessing local options. Meeting the heating demand of households was constrained by the current EU law (RED II) to reduce greenhouse gas (GHG) emissions by 80% relative to fossil (natural) gas. Levelised cost of energy (LCOE) analyses at 80% GHG emission savings indicate that locally produced green gas (LCOE = 24.0 €ct kWh−1) is more attractive for individual citizens than locally produced green hydrogen (LCOE = 43.5 €ct kWh−1). In case higher GHG emission savings are desired, both LCOEs go up. Data indicate an apparent mismatch between heat demand in winter and PV electricity generation in summer. Besides, at the current state of technology, local onshore wind turbines have less GHG emissions than PV panels. Wind turbines may therefore have advantages over PV fields despite the various concerns in society. Our study confirms that biomass availability in a dedicated region is a challenge.
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Developers of charging infrastructure, be it public or private parties, are highly dependent on accurate utilization data in order to make informed decisions where and when to expand charging points. The Amsterdam University of Applied Sciences, in close cooperation with the municipalities of Amsterdam, Rotterdam, The Hague, Utrecht, and the Metropolitan Region of Amsterdam Electric, developed both the back- and front-end of a charging infrastructure assessment platform that processes and represents real-life charging data. Charging infrastructure planning and design methods described in the literature use geographic information system data, traffic flow data of non-EV vehicles, or geographical distributions of, for example, refueling stations for combustion engine vehicles. Only limited methods apply real-life charging data. Rolling out public charging infrastructure is a balancing act between stimulating the transition to zero-emission transport by enabling (candidate) EV drivers to charge, and limiting costly investments in public charging infrastructure. Five key performance indicators for charging infrastructure utilization are derived from literature, workshops, and discussions with practitioners. The paper describes the Data Warehouse architecture designed for processing large amounts of charging data, and the web-based assessment platform by which practitioners get access to relevant knowledge and information about the current performance of existing charging infrastructure represented by the key performance indicators developed. The platform allows stakeholders in the decision-making process of charging point installation to make informed decisions on where and how to expand the already existing charging infrastructure. The results are generalizable beyond the case study regions in the Netherlands and can serve the roll-out of charging infrastructure, both public and semi-public, all over the world.
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The development of the World Wide Web, the emergence of social media and Big Data have led to a rising amount of data. Infor¬mation and Communication Technol¬ogies (ICTs) affect the environment in various ways. Their energy consumption is growing exponentially, with and without the use of ‘green’ energy. Increasing envi¬ronmental aware¬ness has led to discussions on sustainable development. The data deluge makes it not only necessary to pay attention to the hard‑ and software di¬mensions of ICTs but also to the ‘value’ of the data stored. In this paper, we study the possibility to methodically reduce the amount of stored data and records in organizations based on the ‘value’ of informa¬tion, using the Green Archiving Model we have developed. Reducing the amount of data and records in organizations helps in allowing organizations to fight the data deluge and to realize the objectives of both Digital Archiving and Green IT. At the same time, methodi¬cally deleting data and records should reduce the con¬sumption of electricity for data storage. As a consequencs, the organizational cost for electricity use should be reduced. Our research showed that the model can be used to reduce [1] the amount of data (45 percent, using Archival Retention Levels and Retention Schedules) and [2] the electricity con¬sumption for data storage (resulting in a cost reduction of 35 percent). Our research indicates that the Green Ar¬chiving Model is a viable model to reduce the amount of stored data and records and to curb electricity use for storage in organi¬zations. This paper is the result of the first stage of a research project that is aimed at devel¬oping low power ICTs that will automa¬tically appraise, select, preserve or permanently delete data based on their ‘value’. Such an ICT will automatically reduce storage capacity and reduce electricity con¬sumption used for data storage. At the same time, data dispos¬al will reduce overload caused by storing the sa¬me data in different for¬mats, it will lower costs and it reduces the po¬tential for liability.
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