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Time and costs are often the most critical constraints in implementing a development impact fee (DIF) for local infrastructure installation planning in South Korea. For this reason, drafting quality plan alternatives and calculating precise DIFs for improvement remain challenging. This study proposes an application of a procedural modeling method using CityEngine as an alternative to traditional methods, which rely on AutoCAD. A virtual low-density suburban development project in Jeju, South Korea was used to compare the workability of the two methods. The findings suggest that procedural modeling outperforms the other approach by significantly reducing the number of steps and commands required in the planning process. This paper also argues that procedural modeling provides real-time 2- and 3-dimensional modeling and design evaluation and allows for a more efficient assessment of plan quality and calculation of DIF. We also argue for the need to diffuse procedural modeling to better support local planning practices.

As cities attempt to ameliorate urban green inequities, a potential challenge has emerged in the form of green gentrification. Although practitioners are central to urban greening and associated gentrification, there has yet to be an exploration of practitioner perspectives on the phenomenon. We fill this gap with an online survey of 51 urban greening practitioners in Metro Vancouver and the Greater Toronto Area. Most respondents defined green gentrification as the displacement of vulnerable residents due to the installation or improvement of green space that attracts wealthy in-movers and increases property values. They were most likely to identify greening as driving green gentrification, with a minority identifying other systemic drivers with greening in a secondary role. Although 39 of 51 participants had some familiarity with green gentrification, most reported low confidence in their understanding of the concept, little evidence of using the concept in their work, and moderate concern that their work is implicated in green gentrification. The gentrification issues most encountered by practitioners were changes to neighbourhood character and uneven investment in public infrastructure, and those working in domains linked to planning, equity, and engagement were most likely to encounter gentrification issues. Practitioners experienced multiple barriers to addressing green gentrification, including limited institutional capacity, limited access to data and relevant information, policy/mandate restriction, and lack of engagement tools. Results indicate that practitioners have a moderate understanding of green gentrification but do not often use the concept in their work, despite their potential to contribute to or exacerbate it. This suggests some resistance to critiques of urban greening practice, a failure of scholarly critiques of urban greening to influence policy change, and the need for stronger research theory and research co-creation involving practitioners and academia.

[...]we are building out sidewalks as well, last year, DOTI oversaw installation of 9.4 miles of new sidewalk (three miles installed by private development) in the City and County of Denver. The further up in government you go, the more detached the understanding becomes. [...]design requirements at the state level are a bit different from what you experience at the local level, and especially at the federal level. The role of local government is instrumental in incorporating community input and feedback so that building projects can provide the most benefits to the right people. [...]the update supports healthy and active ways for people to enjoy the outdoors and stay healthy.

Climate change and increasing extreme temperatures present unique challenges to persons experiencing homelessness (PEH), including heightened physical and psychological harm. While green and urban infrastructure has emerged as one possible mitigation strategy, homeless populations are rarely included in municipal disaster planning or infrastructure research. This study used in-depth interviews with PEH (N = 42) during the summers of 2022 and 2023. Questions were designed around phenomenological methods to explore the individuals’ firsthand descriptions of the lived experience of coping during extreme temperatures within a mid-size city in the Southeastern United States. Our findings highlight how social exclusion within the built environment reduces PEH’s adaptive capacity and increases the physical and psychological risks of extreme temperatures, namely through limiting and policing scarce resources and restricting the mobility of PEH. In contrast, public transit provided relief from extreme temperatures. Implications from our findings include the need for attention on inclusive green urban infrastructure, including increased placement and access to shade, public water, mixed-use daytime sheltering models, and the installation of lockers to increase capacity to maintain supplies and gear necessary for enduring extreme temperatures. Findings also highlight the challenges of designing inclusive green infrastructure and the importance of de-stigmatizing homelessness and building more housing and income support to increase adaptive capacity for an entire community in the context of a rapidly warming climate.

New techniques and methods for energy storage are required for the transition to a renewable power supply, termed “Energiewende” in Germany. Energy storage in the geological subsurface provides large potential capacities to bridge temporal gaps between periods of production of solar or wind power and consumer demand and may also help to relieve the power grids. Storage options include storage of synthetic methane, hydrogen or compressed air in salt caverns or porous formations as well as heat storage in porous formations. In the ANGUS+ project, heat and gas storage in porous media and salt caverns and aspects of their use on subsurface spatial planning concepts are investigated. The optimal dimensioning of storage sites, the achievable charging and discharging rates and the effective storage capacity as well as the induced thermal, hydraulic, mechanical, geochemical and microbial effects are studied. The geological structures, the surface energy infrastructure and the governing processes are parameterized, using either literature data or own experimental studies. Numerical modeling tools are developed for the simulation of realistically defined synthetic storage scenarios. The feasible dimensioning of storage applications is assessed in site-specific numerical scenario analyses, and the related spatial extents and time scales of induced effects connected with the respective storage application are quantified. Additionally, geophysical monitoring methods, which allow for a better spatial resolution of the storage operation, induced effects or leakages, are evaluated based on these scenario simulations. Methods for the assessment of such subsurface geological storage sites are thus developed, which account for the spatial extension of the subsurface operation itself as well as its induced effects and the spatial requirements of adequate monitoring methods.

This paper presents an optimization model for the charging infrastructure of electric vehicles (EV) designed to minimize installation costs, maximize the utilization of photovoltaic energy, reduce dependency on the electrical grid, and optimize charging times. The model utilizes methodologies such as Linear Optimal Power Flow (LOPF) to align EV charging schedules with the availability of renewable energy sources. Key inputs for the model include Photovoltaic (PV) production profiles, EV charging demands, specifications of the chargers, and the availability of grid energy. The framework integrates installation costs, grid energy consumption, and charging duration into a weighted objective function, ensuring energy balance and operational efficiency while adhering to budgetary constraints. Five distinct optimization scenarios are analyzed to evaluate the trade-offs between cost, charging duration, and reliance on various energy sources. The simulation results obtained from Cadi Ayyad University validate the model’s effectiveness in balancing costs, enhancing charging performance, and increasing dependence on solar energy. This approach provides a comprehensive solution for the development of sustainable and cost-effective EV charging infrastructure.

Urban and regional development is indispensable from energy systems that function in a sustainable and resilient manner. The generation of renewable energy has seen significant upturn in the last decade. Renewables can be exploited to meet the global energy needs and climate change mitigation goals. Therefore, development of urban and regional energy systems must take into account the possibilities and challenges posed by the increasing penetration of the renewable. The achievement of goals of the energy system in the context of transition to low-carbon energy society rises numerous complex decisions over development of infrastructure and technologies. Although renewable energy devices generate clean energy, they also change landscape. The term of energy-scape encourages discussion about interactions between the energy system and the environment, and other ecosystem services at local level. The paper reviews previous studies analysing energy-scape elements and provides the insights towards the transition to low-carbon energy and low-carbon society in general. The systematic literature review allows clearly outlining the problem and gives reliable background for further studies. The main contribution of the article to the existing literature is the creation of framework for the analysis and assessment of new renewable energy technologies installation and infrastructure. The presented framework can be applied for all renewable energy technologies and infrastructure in both urban and rural areas and allows to attain a decision acceptable to the local community.

The rapid growth of electric vehicles (EVs) demands a robust and efficient charging infrastructure. To address this, we propose a particle swarm optimization algorithm designed for optimal placement and sizing of EV charging stations. This study hypothesizes that comprehensive consideration of uncertainties in vehicle types, user behaviors, road dynamics, and environmental impacts will enhance infrastructure effectiveness. Our method integrates data from road networks, driver patterns, station owners, and EV manufacturers to meet diverse charging requirements. Results indicate that 14 fast charging stations are needed along the studied freeway, with a total installation cost of $289,820 and annual operational costs of $4,223,050, leading to annual CO 2 emissions of 1,843,572.57 kg. This strategic approach balances technical, environmental, and economic criteria, providing an essential tool for policymakers and urban planners in establishing sustainable EV charging networks.

As research in smart homes and activity recognition is increasing, it is of ever increasing importance to have benchmarks systems and data upon which researchers can compare methods. While synthetic data can be useful for certain method developments, real data sets that are open and shared are equally as important. This paper presents the E-care@home system, its installation in a real home setting, and a series of data sets that were collected using the E-care@home system. Our first contribution, the E-care@home system, is a collection of software modules for data collection, labeling, and various reasoning tasks such as activity recognition, person counting, and configuration planning. It supports a heterogeneous set of sensors that can be extended easily and connects collected sensor data to higher-level Artificial Intelligence (AI) reasoning modules. Our second contribution is a series of open data sets which can be used to recognize activities of daily living. In addition to these data sets, we describe the technical infrastructure that we have developed to collect the data and the physical environment. Each data set is annotated with ground-truth information, making it relevant for researchers interested in benchmarking different algorithms for activity recognition.

Explorations of the benefits for businesses in terms of customer experience or improvements in staff wellbeing from installing and retro‐fitting green infrastructure (GI) in a European city context have been lacking. This paper reports on a two‐year longitudinal mixed methods study in a district of central London evaluating the changes resulting from the installation of a mixture of greening schemes for different types of business sectors and their staff members. Business managers, particularly from retail and leisure sectors, perceived increases in customer footfall and sales in relation to the improvements. Providing accessible green space in office settings led to improvements in morale, team interaction and workplace satisfaction among staff members able to access the improvements. Increased GI was seen as improving uptake of company environmental policies such as energy saving or recycling among staff by their managers. Impacts of neighbourhood GI schemes on staff wellbeing were mixed, with increased greening leading to improved self‐reported workplace happiness and greater interaction with nature spaces but not changes in overall measurements of staff wellbeing. Overall, the findings indicate that GI could represent a worthwhile investment for UK and European businesses through these combinations of direct and indirect returns adding to the known environmental benefits improving urban green spaces can provide.