City and Environment Interactions最新文献

Though essential in combating climate change, conserving biodiversity and providing myriad ecosystem services, urban parks in Africa, are challenged by rezoning, encroachment and other pressures. Furthermore, research on urban park tree diversity, dominant species and carbon stocks of parks in developing countries in Africa are scanty. This study assessed the carbon stocks, tree species diversity and stand structure in public parks within Kumasi metropolis. In each selected park, four 40 × 40 m plots were randomly sampled. The heights, diameters, and crown width of all woody vegetation with a diameter at breast height (DBH) greater than 10 cm, were measured and carbon stocks determined. The stand density (p = 0.0546), DBH (p = 0.004), total tree height (p = 0.01), basal area, and carbon stocks (p = 0.018) differed significantly among parks. The carbon stocks of the parks were 80.73 ± 8.77, 45.10 ± 4.83, 76.26 ± 30.19 and 9.59 ± 2.13 MgCha⁻¹ at Kumasi Zoological Garden, KNUST Botanical Garden, Royal Golf Course, and Rattray Park, respectively. With an average of 53.88 ± 11.70 MgCha⁻¹ and 43 species, the public parks in Kumasi have the potential to alleviate climate challenges and conserve biodiversity. The park species composition slightly deviates from the 10/20/30 benchmark stipulated for urban forests. Increasing park tree cover by restoring degraded sections of parks with tree species with high carbon densities, increasing the area and number of parks per city, adopting integrated park management approaches and plans backed by appropriate legislation and policies in cities in Africa could significantly enhance urban climate resilience, conserve biodiversity, and mediate mitigation and adaptation to warmer cities.

Urbanization has resulted in a significant accumulation of waste in densely populated areas. Effective household waste separation practices within urban areas are crucial for advancing the concept of circular economy. The informal system has contributed remarkably to urban material circulation, but it has not been appropriately valued. Through the partnership among the municipal solid waste authorities, condominium building residents, and waste pickers, the latter can be engaged in the community to assist in household waste separation. This initiative would not only enhance their income and reduce probable occupational risks but also augment the recycling rate in the community. Based on the insights from the current waste picker assignment policy in Taichung City, this study has established a mathematical programming model by considering the overall waste separation volume and proximal distance to the neighborhood, facilitating the assignment of individual waste picker to multiple communities within the neighborhood area. Consequently, concerned waste pickers may increase their income and avoid the constraints of picking up recyclables in high-occupational-risk areas. Additionally, it may reduce the volume of unsorted garbage in the community. According to the findings of case studies, the developed model could obtain an optimal solution or acceptable approximate solution in a short timeframe. In contrast to the outcomes from the existing waste picker assignment policy, the application of the developed model could increase the total volume of sorted recyclables, which was directly proportional to the income of waste pickers, by 2.3–2.6 times.

With more than 75% of the European Union’s population living in urban areas covering 21.5% of the EU territory, the importance of climate-resilient cities, towns and suburbs has increased dramatically. However, the rising impact of human-induced land-use changes on ecosystem services (ES) poses a major challenge to the urban environment. This study focuses on scenario development for nature-based solutions (NbS) in a European town with its intense development area. The concept is exemplified in a town in Croatia, Grad Velika Gorica (GVG), that like many others cities undergoes urbanisation processes with limited resources. It serves as a showpiece for the influence of NbS, in particular street trees along various paths.

Using spatial analysis and modelling, the approach explores NbS for future urbanisation. The results, supported by quantitative analysis, show that 49% of cycle lanes and footpaths in GVG can be shaded by strategically planted street trees. The shading scenario analysis provides a nuanced perspective on the potential of NbS, offering insights into the key tasks for a climate-resilient city and opportunities towards equitable, green and healthy urban areas.

In the context of urbanisation processes and climate adaptation, the study is in line with the overarching objectives of the European Commission which emphasises the need for sustainable NbS alternatives to address environmental challenges. The findings contribute to the framework of informed decision-making towards urban climate resilience. It also supports the pursuit of a sustainable local governance for climate-adjusted environmental quality in urban planning. As towns and cities grapple with the imperative of balancing urban development with environmental protection, this research highlights the central role of NbS, particularly street trees, in shaping climate-resilient and more sustainable urban environments for human well-being in cities.

Due to climate change, future weather conditions will become more extreme. During recent years, several severe damages have been caused by heavy rainfalls in combination with riverine events. Even though the effects of compound events are known to be influential for flood hazard, the method for investigating these types of events is a novel area of expertise. In this study, a methodology was developed to investigate a watercourse, acting as a part of a stormwater drainage system in an urban coastal area, in a hydrodynamic model to find areas prone to flooding. The method was applied for Ståstorpsån in Trelleborg, Sweden. The model was a unified model for seasonal variability and compound events with scenarios developed based on series of data representing normal values of the boundary conditions rainfall, river flow and sea level. The result was analysed graphically and statistically as a flood hazard. The data used was based on data collected during the past 10 years for rain and sea level and 16 years of simulated river flow. The constructed rain events from gauge data all had a return time of less than 10 years. Therefore, the chosen events are considered to represent normal levels. For Trelleborg, the results from the hydrodynamic model indicate that compound events will increase the flood hazard with anincreasing time horizon. The visual analysis converges with earlier flood events, and hotspots are generally seen around bridges and culverts. For the studied area, there is a large seasonal variation in the flood hazard and with climate change, all seasons will cause more severe flood hazards. The effects experienced during a summer event, which is the most severe event today, are to be expected for all seasons in 2100. The effect seen during summer eventsis a combination of all three drivers. However, rain intensity is likely to be more influential for normal events. When a certain threshold value for sea level is reached, sea level becomes the most influential driver, overtaking the other drivers in importance.

Understanding and evaluating possible changes in thermal conditions of urban settlements are crucial for risk assessment, adaptation to climate change and sustainable urban development. This study presents the results of a micro-scale measurement campaign conducted in Vienna, Austria, to investigate the effects of natural and artificial surfaces on temperature and humidity variability. The observational data set is used for the evaluation of the newly developed building-resolving urban climate model system PALM. Dragino LHT65 LoRaWAN air temperature and humidity sensors were installed to monitor local-scale variations. On selected summer days, drones equipped with thermal imaging cameras were used to provide hourly surface temperature. The monitoring data show higher temperatures near buildings and overall strong spatial and temporal variations. The model demonstrates the capability to simulate the main thermal characteristics of the study area, although it slightly overestimates temperatures at night. Compared to the measurements, it has a less pronounced spatial variability in air temperature and relative humidity, but a larger one in surface temperature. The analysis confirmed that the urban climate model has the potential to appropriately assess microclimate conditions and therefore, contribute to future-oriented urban planning.

Ecological services in metropolitan areas are degrading more quickly due to changes in LULC brought about by urban expansion. To make a sustainable choice about the ideal location, however, merging the existing simulation approach with LULC optimization approaches involves several intricate procedures. Therefore, the goal of this study is to develop a unique technique that can forecast urban expansion over an extended period and to link with optimization of LULC techniques so as to make meaningful decisions on the impacts of urbanization on loss of biodiversity. In this study, three primary procedures were used: (1) an SVM-based supervised classification technique for LULC classification; (2) a Markov chain and cross-tabulation method for the examination of LULC trends in space and time, (3) utilizing the CA-Markov approach to forecast urban growth. By using Landsat imagery of 2008, 2015, and 2023, the study determined how urban cover changed over time, and what kind of LULC-to-urban transition occurred. The study revealed that uncontrolled and haphazard urban expansion was observed in the Sululta sub-city, which could have disastrous repercussions on physical, biological and urban ecosystem. The %age of urban area increased from 9.04% in 2008 to 13.07% in 2015. However, because of the internally displaced people from the Ethio-Somali Region, who have been resettled there since 2017, the ratio of urban areas grew from 13.7% in 2015 to 24.65% in 2023. Furthermore, by 2040, the sub-city will have grown by 27.69 %. The kappa coefficient statistics of the three classified images of the years 2008, 2015, and 2023 were 93.3 %, 97.5%, and 97.5 %, respectively. To identify the areas that would be covered by future city growth, it is advised that this innovative technique be integrated with optimizing land use strategies.

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.