City and Environment Interactions最新文献

The surface of cities is often warmer than the surface of their surroundings. This phenomenon is known as the surface urban heat island (SUHI) effect and has several adverse implications. Studies have shown that the SUHI effect tends to be weaker if urban form is characterized by sprawl or polycentrism. These findings suggest that urban heat could be mitigated if a city is less compact. By analyzing high-resolution remote-sensing land surface temperature (LST) and land-cover data for 293 European cities, this study shows that — contrary to many previous findings — sprawling or polycentric urban forms do not necessarily lead to a decrease of LSTs over urban areas. In southern European cities, sprawl could even lead to the warming of urban areas during specific daytimes, highlighting the importance of considering environmental and regional contexts when determining the role of urban form in heat mitigation. It is also crucial to consider the predominant type of land cover surrounding a city since sprawl into forested areas could have a very different effect than sprawl into agricultural areas. These results illustrate the complexity of urban form related heat mitigation and that policy- and decision-makers have to consider local and regional contexts when steering urban form.

Extreme heatwaves represent a health hazard that is expected to increase in the future, and which particularly affects urban populations worldwide due to intensification by urban heat islands. To analyze the impact of such extreme heatwaves on urban areas, urban climate models are a valuable tool. This study examines the performance of the urban climate model MUKLIMO_3 in modelling spatial air temperature patterns in the greater urban area of Bern, Switzerland, a city in complex topography, during three distinct extreme heatwaves in 2018 and 2019 over a total of 23 days. The model is validated using low-cost air temperature data from 79 (2018) and 84 (2019) measurement sites. The intercomparison of the three extreme heatwaves shows that during the first extreme heatwave 2019 at lower elevation regions in the outskirts of the city, modelled air temperature was higher than observation, which was likely due to pronounced mesoscale cold air advection. During calm and dry days, the air temperature distribution was modelled realistically over all three extreme heatwaves investigated. During daytime, modelled air temperatures were lower across all evaluation sites and all extreme heatwaves when compared to the measured values, with highest median air temperature differences of −3.7 K to −4.8 K found in the late afternoon. At night, MUKLIMO_3 generally shows a slowed cooling, so that higher air temperatures were modelled when compared to measured values, with median air temperature biases of +1.5 K to +2.8 K at midnight. By sunrise, the model biases continuously decreased, so that the lowest air temperatures at 7 a.m. were modelled with a bias of +0.2 K to +0.7 K. Peak biases exceed 7 K both during day and night. In sum, our results show that MUKLIMO_3 allows to realistically model the urban air temperature distributions during the peaks of the heatwaves investigated with the highest day and night air temperatures, which may assist in the development of heat mitigation measures to reduce the impacts of heat extremes and improve public health in cities with complex topography.

In a natural landscape, when rainfall reaches the Earth’s surface, water either percolates into the ground or it flows as run-off finally reaching a water body such as a lake or a river. Due to rapid urbanization, the natural landcover in the cities is being replaced with impervious surfaces which significantly alters the natural patterns and processes of urban landscape resulting in mismanagement of storm water and hence the flooding issues. Integrated Blue-Green Infrastructure (BGI), a landscape conservation approach with nested networks of blue and green spaces (permeable pavements, bioswales, rain gardens, urban tree cover, small ponds and wetlands) can provide an alternative approach to conventional storm water management along with its multiple environmental benefits. The objective of this paper is to develop a geospatial technology-based approach for the identification of BGI network by employing graph theory and gravity model for sustainable storm water management in the city of Ahmedabad, India. The study introduces a replicable approach by integrating five key criteria i.e., slope, drainage density, land cover, hydrologic soil group and proximity to roads for Suitability Analysis, selecting core patches as nodes in a GIS environment and identifying corridors by employing the least cost path function followed by assessment of selected corridors using gravity model. Analysis of land surface characteristics reveals that Ahmedabad has a high suitability for the implementation of BGI. A variety of blue and green open spaces throughout the city such as parks, gardens and lakes form the node which are connected by a network of corridors developed by the least cost path model and gravity model. The methods and practices adopted in this research represented an innovative approach for the implementation of BGI networks for storm water management in an urban landscape.

Tehran is one of the most populous and polluted cities in Iran with a fossil fuel-dependent economy. This paper aims to assess a techno-economic and environmental feasibility of biomass-based power plant in off-grid mode to present optimal planning for reliable electrification to Tehran. To achieve this goal, size optimization and sensitivity analysis of the proposed hybrid renewable electric system (HRES) is performed by simulating a model in HOMER software to determine the most economical and environment-friendly HRES for the studied area. The assessment criteria for selection of optimal architecture are based on the lowest of net present cost (NPC), cost of energy (COE), and carbon emission quantity (CEQ). Accordingly, HOMER proposes the seven feasible HRES that among them, the biomass generator (BG), photovoltaic (PV) and Wind turbine (WT) hybrid system including 3,181 kW PV panels, 4300 kW WT, a 5,100 kW BG, 17,035 kWh battery storage and 4,415 kW converters is the most optimum power system. Besides, the aforesaid system has COE of 0.281 $/kWh and NPC of 113 M$. Techno-economic comparison of seven systems shows that the integration of PV and WT with biomass systems could be an effective method to make a cost-optimal and reliable HRES, especially in a large scale city- for low-carbon and climate-resilient communities.

In response to the adverse consequences of urbanisation, including the production of over 70% of global emissions and the increase in social inequalities, cities have set ambitious missions to devise a set of innovative solutions in their transition to a circular economy. This exploratory research examines the conditions that should be met for such missions to trigger the development of an innovative system that could support cities in such a transition. While several studies have been conducted on the narrative of the circular economy as a 'way of doing', this article adopts the circular economy as a 'way of thinking'. To further explore the conceptual diversity of the circular economy, this article uses rapid ethnography as a method in the context of a Dutch region by pursuing a circular mission. The results highlight that a mission alone is not enough to create an innovative and inclusive system as the underlying narrative lacks congruence; this, thus, suggests that the circular economy may not be the most compelling narrative for the mission of cities toward a more sustainable development.

Urban sustainability and urban resilience are at the forefront of current urban studies since cities play a crucial role in sustainability and climate-related transformations. Hungarian cities face almost the same challenges regarding climate change as their European counterparts; however, their considerable socio-economic sensitivity makes them highly vulnerable. This study aims to comparatively analyze urban sustainability and heatwave vulnerability in the case of Hungarian cities by applying a mixed approach - min–max feature scaling and fuzzy method. In order to reveal the hidden relationships between the highly interconnected aspects of sustainability and vulnerability dimensions, min–max feature scaling and fuzzy logic have been applied. The selected set of indicators encompasses statistical data regarding socio-economic aspects, moreover as relevant climate change and environmental issues, namely heatwave duration predictions and imperviousness density. The applied fuzzy logic approach reveals interdependencies between the analyzed aspects and maps spatial characteristics regarding the evaluated cities. Applying the min–max feature scaling method shows high sustainability scores regarding Budapest and Western regions, while overall vulnerability performances were lower in cities from less developed regions. However, the applied fuzzy methodology contributes to defining more homogenous performances by distinguishing only two sustainability categories and reducing variability in the case of heatwave vulnerability.

Eco-industrial parks (EIP) are an organization of businesses grouped around material needs and outputs. Functional synergies need to be formed that benefit both or multiple companies in these grouped organizations. Such synergies may be in the form of sharing resources, materials, infrastructure, information, or industrial ecology principles in the form of one entity using the by-product of another entity as input. There are environmental, economic as well as societal gains to be realized through eco-industrial parks. A meta-analysis was conducted to assess EIP success to date, as well as to report experienced advantages of EIPs in practice. Many EIP projects failed to come to fruition or have transformed and fallen back on traditional industrial practices. Close examination of such cases provides valuable lessons for future EIP projects and provides insight into why eco-industrial parks have historically high failure rates in the United States. The study offers a summary and critical analysis of success factors for EIP development (e.g., geographic requirements, stakeholder involvement and dedication, community involvement, and regulatory system/agency support). In addition, the strategies and methods for future success of eco-industrial parks (e.g., agent-based modeling, optimization modeling, non-competitive waste stream selection) are discussed. Agent-based modeling can identify true costs and benefits and enable monitoring of EIPs during their operation. Use of optimization techniques may be applied to overcome the complexity of multi-objective mathematical models aiming to balance the needs of multiple firms and multiple resources being allocated among them. Non-competitive waste streams can alleviate various social concerns between firms in an EIP conglomerate, due to reduced competition and mutual benefit such as re-utilizing waste that is traditional expensive to eliminate, reducing disposal costs, and raw material sourcing costs.

Because biogas systems may take many forms, utilizing different feedstock and finding different end uses for the biogas, it is becomes difficult to produce explanations, inferences, and conclusions about biogas systems in general, which is why concepts for specific types of biogas systems are needed. This paper introduces the concept of the Nordic biogas model, an urban waste-based biogas system where biogas is upgraded to biomethane and used as transport fuel and the digestate applied as biofertilizer on farmland. The Nordic biogas model has three functions, namely, renewable transport fuel production, waste management service, and biofertilizer production that all bring secondary and tertiary positive societal effects, such as reduced climate gas emissions and productivity benefits to industry. This has implications for environmental and sustainability assessment of the Nordic biogas model as the multi-functionality must be considered when choosing reference scenarios, system boundary, and indicators to use within assessments. Finally, the paper discusses policy recommendations for supporting the implementation of the Nordic biogas model. Such policy should respect the multi-functionality of the Nordic biogas model by creating coherent policy mixes that neither neglect nor over-compensate for the multi-functionality of the Nordic biogas model.

The research paper provides an assessment of spatial differences of vulnerability levels for the population Moscow to possible natural and man-made hazards, taking into account the actual population size and aspects of its intraday spatial movement. In addition to official statistical sources, we used data of mobile operators, which made it possible to characterize the localization of subscribers at a certain point in time with the maximal degree of reliability. Thus, it helped us to significantly correct and clarify the current concepts of the population in Moscow. According to the cluster analysis’ results, the potentially most vulnerable areas of Moscow were identified, and grouped into six types. The cluster analysis and typology were based on the characteristics of the density of the existing population, the regime of population fluctuations and the deviation of population indicators from the data of official statistics. In order to man-made risk assessment consideration of sanitary protection zones (SPZ) of industrial and utility facilities of the city have been added to the idea of ​​the population vulnerability. The results of the study show the inconsistency of existing approaches to risk assessment based on official social statistics. The paper also first presents the typology of urban areas of Moscow, which sheds light on the main features of its spatial structure in the context of potential vulnerability of citizens to natural and man-made emergencies.