City and Environment Interactions最新文献

Principal component analysis (PCA) can reduce the subjectivity of Water quality index (WQI) models by reducing parametric dimension and has gained immense attention in exploring water quality among researchers. Therefore, this study focuses on developing a novel WQI model for 4 Dhaka-based rivers namely Buriganga, Turag, Balu, and Shitalakhya following PCA as a method for selecting and weighting water quality parameters. The dataset includes 12 water quality parameters from 19 sites of these rivers sourced from the Department of Environment (DoE), Bangladesh. Correlation analysis followed by PCA, was conducted to decrease the parameter count from 12 to 7. The Measure of Sampling Adequacy (MSA) was found to be 0.853 in the Kaiser-Meyer-Olkin (KMO) test and Bartlett’s test of sphericity was significant at an alpha level of 0.05 indicating the dataset was suitable for factor analysis. Sub-indexing was introduced with the quality rating curves provided by the National Sanitation Foundation (NSF)-WQI model and modified rating curves for specific parameters with statistical dispersion. The calculated WQI values for 209 samples ranged from 36 (Bad) to 82 (Good) on a scale of 100. More than 70 % of the samples were in the medium or bad, and the rest were in the good category. The trend in WQI across the rivers indicated higher values during the wet season, attributed to the dilation from local rainfall. By incorporating a well-distributed dataset spanning several years, this statistical approach effectively minimizes the subjectivity and bias in developing WQI models for rivers in Dhaka, contributing to more robust future model development. Moreover, this study introduces a modern approach for assessing the river water quality of Dhaka city that can be incorporated into the river pollution control strategies.

More extreme, frequent and longer heat waves negatively affect people all around the world, and especially inhabitants of urban areas which face even higher temperatures due to the urban heat island effect. A precondition to develop adaptation strategies to counteract adverse effects of heat in cities is to gain knowledge about the urban temperature distribution. One approach that has been applied in various cities is the implementation of dense urban temperature measurement networks. Since financial resources are usually limited, such networks consist of cost-effective measurement devices whose (daytime) data quality is prone to errors due to radiative influences. This was also the case in Zürich, Switzerland, where an urban temperature network with 272 measurement stations was operated from 2019 to 2021. In this study, we present a radiation correction method to enhance the data quality for practical use. Applying the proposed correction method led to a reduction in mean RMSE from 1.47 K to 0.57 K and in the overall mean bias from +0.88 K to +0.04 K. Following from that, we use the corrected database for two application cases: i) As a spatially and temporally high-resolution validation dataset for the physics-based large eddy simulation model PALM and ii) as input data for a geostatistical land use regression model. The analysis shows that the daytime radiation correction is crucial to detect the negative bias of the PALM model, which is most pronounced in the highly built-up area of Zürich, and to enhance the quality of the daytime land use regression. The developed radiation correction presented in this study can also be applied for other urban temperature networks that are facing similar challenges.

This research focuses on the dynamic interplay between blue-green public spaces, urban food environments, and cultural place branding in the Setu Babakan area of Jakarta, home to the Betawi Cultural Village. While the area functions as a multi-faceted public asset, encompassing both Green Open Space (GOS) and Blue Open Space (BOS), the actual utilization of these spaces reveals disparities. Employing mixed methods, this study aims to holistically capture the complexities surrounding utilizing Setu Babakan’s blue-green spaces from the vantage points of visitor perceptions, street vendors, and governmental policies. The study found that both visitors and street vendors were highlighting the need for equitable access to this vital public amenity. Factors such as accessibility and population density of vendors within the neighborhood area complicate the quest for socio-spatial equality. The presence of 6 (six) distinct types of warungs or street vendor stalls, which spontaneously emerge in the transitional zones between blue-green public spaces and private community lands, underscores the local government’s challenge in crafting policies that achieve legal and inclusive socio-spatial fairness. This study suggests that Setu Babakan embodies a unique confluence of cultural, social, and environmental values, offering a blueprint for how multifunctional public spaces can cater to diverse urban needs while fostering community well-being. As such, it calls for regulatory clarity, suggesting implementing formalized guidelines like temporary permits or designated zones to harmonize the competing demands of the informal economy and environmental sustainability.

Today, urban flood resilience constitutes an academic and political discourse as well as a ‘proposed state’ to be achieved within urban management, planning, and development. Matola, a major Mozambican coastal city, has witnessed many floods, mainly caused by rainfall, the most devastating of which happened in 2000. This study analyses the actions the urban planners took during that major flood event, what flood mitigation and adaptation strategies and measures for increased flood resilience they have developed since that flood event, and the contribution of urban planning to building flood resilience under financial and technical constraints. The study is based on interviews with 32 urban planners from Matola and observations in the field. In addition to financial limitations, the main challenge in promoting flood resilience in Matola is the deficient and insufficient coordination in mitigation and adaptation actions among urban planners, political elites, and members of low-income urban communities, who use floodplain areas for purposes that contradict resilience-building actions. During the 2000 floods, mitigation actions were carried out by rescuing people and goods and placing them in accommodation centres. After the 2000 floods, gradual adaptation strategies and measures were carried out, such as hiring and training staff, designing a new urban plan, gradual resettlement, opening drainage channels, and allocating water pumping systems in some areas to promote flood resilience. The study concludes that urban planning contributed significantly to the building and promotion of flood resilience in Matola: the strategies and measures taken so far have contributed significantly to reducing the exposure and vulnerability to flooding of the population, their assets, and urban infrastructure, as well as improving the ecosystem in lowlands and coastal protection wetlands. The study brings a contribution from retrospective and prospective resilience thinking to the debate on building and promoting resilience in urban socio-ecological systems, showing the role of urban planners, and planning and management activity since the 2000 floods, and perspectives on the future. The study demonstrates that the development of competences or technical skills to plan and manage strategies and measures to promote resilience is a key factor in promoting socio-ecological resilience.

Excess heat is generated from different industrial processes and from urban infrastructure (sewage water, transport, datacentres and buildings). Thirty-five percent of the European energy demand for heating and cooling could be met by excess heat. Today, however, this energy reserve is barely exploited. There are known barriers to excess heat recovery but limited information on stakeholder interactions in the early stages of excess heat collaborations and on successful collaborations. Sweden is world champion in terms of excess heat recovery into district heating systems, and the country has a long tradition in this field (dating back to the 1970 s). By studying two cases, we shed light on success factors in the early stages and in successful collaborations. We identify that the main success factors for excess heat recovery are (i) trust between the collaborating partners, (ii) the involvement of as many stakeholders across the DH (District Heating) value chain as possible (in the decision-making process), (iii) the establishment of joint goals, and (iv) the identification of a business model allowing for a win-win solution that prioritizes excess heat recovery and secures funding for the necessary investments. Excess heat recovery investments have features similar to those of other investments in climate change mitigation, making the success factors relevant to applications beyond the case of excess heat recovery.

Anthropogenic pressures that have been reduced by the COVID-19 measures have had spatially and temporally differentiated impact on the atmospheric environment.

We investigated the relationship between NO₂ level data and COVID-19 restrictions with a focus on 27 European Union member states.

Nationally, the NO₂ level change was an average of −10 % in 2020/2019, while the 2021/2020 increase averaged + 11.4 %. The direction of these changes is clear, but magnitude varies considerably by geographical area. A significant proportion of the population was affected by the year-on-year changes in emissions.

The severity of the restrictions did not play a relevant role in the extent of emission changes, but measures themselves had an impact on the overall reduction in NO₂ levels in 2020. In many regions, the reduction in stringency of 2021 restrictions has led to a recurrent deterioration in ambient air quality, with NO₂ levels reaching, and in some cases exceeding, previous levels.

Urbanization presents numerous societal challenges and exacerbates environmental issues. It is crucial to comprehend the current state and future direction of cities to formulate strategies and actions that mitigate negative consequences while ensuring a prosperous future for citizens. This study presents a universally applicable method for selecting indicators to gauge urban environmental sustainability. It aims to aid in structuring thinking for understanding and implementing Sustainable Development Goals (SDGs) within urban settings, using Norway as a case study but with a clear potential for broader applications. To achieve this, a comprehensive literature survey was conducted to gain insight into how urban environmental sustainability is conceptualized and operationalized in Norway. This involved assessing the key environmental challenges, as well as the strategies and action plans associated with them. Standardized sustainable cities' indicators served as references, which were then tailored to the municipal level to address the identified environmental challenges specific to Norwegian cities. Furthermore, the study discussed the proposed indicators for tracking the progress and state of these specific environmental challenges. In doing so, it establishes a foundation for comprehending environmental issues and establishing connections between indicators and environmental strategies and action plans in the urban sustainability context. Importantly, the methodologies and indicators we have unveiled in this study are designed to be applicable to cities beyond Norway, offering a scalable and adaptable approach for evaluating environmental challenges internationally. This work proposes a novel approach for evaluating the status and trends of environmental challenges by employing targeted indicators. These indicators can be expanded to include social and economic dimensions, enabling decision-makers and stakeholders to prioritize actions towards urban sustainability.

Growth of the city’s population induces changes to airflow and pollutant and dust dispersion process, which is significantly affected by barriers and consequently influences human health and life. Therefore, it is necessary to investigate the airflow pattern using simulation approaches. In this study, the computational fluid dynamics (CFD) using the Reynolds Averaged Navier-Stokes (RANS) equations as a powerful numerical modeling tool, and Log-law and Power-law empirical models, along with several auxiliary data (DEM data) and several relevant software tools (Google Mapper, Sketchup 17, Rhinoceros 5, and Solid Works 19) were employed to simulate wind velocity and pressure distributions over a large-scale complex terrain and buildings in Gouyom to Shahrak-e Golestan, Shiraz, Iran. Validation procedure was performed through monthly measured wind velocity at seven elevations of 3, 6, 9, 10, 12, 15, and 18 m in three representative locations over a year using a digital handheld anemometer (UNI-T UT361) that was capable to measure wind velocity in the range of 2 to 30 m s⁻¹ with an accuracy of 3%+0.5 The CFD results better agreed with the experimental data in real situations than those of the other two applied numerical models (Power-law and Log-law). Furthermore, wind velocity in three prescribed lines of different heights (5 m, 10 m, and 20 m) with different topographies and buildings had more fluctuations from the beginning of the study area to nearly 6 km. The turbulence intensity profiles also confirmed the mentioned issues. Results revealed that the minimum and maximum pressures were observed in the crest and flat surfaces, respectively. The CFD numerical simulation approach is recommended to predict airflow characteristics (wind velocity and pressure distributions), model soil erosion by wind, and present solutions to reduce the airflow pattern change-induced hazards.