City and Environment Interactions最新文献

Since the 1950s, African cities in a quest for modernity and prosperity have been urgently playing catch up to deal with the increasing demand for adequate urban systems and infrastructure. At the turn of the 21st century, many spatial planning models, technological trends, environmental challenges, and socio-economic realities are influencing African cities’ dynamics largely causing confusion and a lack of consistent planning policies. To efficiently guide a coherent and coordinated vision, frame an integrated long-term spatial logic, and give a precise direction for sustainable urban development, this paper aims to develop a localized and contextualised analysis of urban planning challenges and development strategies shaping African cities. The study provides a broad perspective looking at the potentiality of spatial planning practices to envision and transform urban life by prospecting integrated urban planning and development strategies to face increasing urban challenges in Africa. Through Systematic Literature Review (SLR) and machine-learning tools, the study brings, for the first time, consolidated and updated knowledge of urban planning practices in Africa. We analysed 243 urban studies, published between 2000 and 2023, in 107 African cities. We identified and scrutinised 17 most pressing urban challenges and 16 most applied urban strategies to address those challenges. Accordingly, the study’s findings suggest shifting the spatial planning paradigm towards urban resilience as an interoperable system of different spatial planning policies and their relevant urban development strategies. Furthermore, the study’s key arguments are to improve urban infrastructure and optimize existing cities to reverse environmental degradation and guide urban fast transformation to adapt and mitigate growing climate change catastrophes.

The study of the relationship between biotic elements and communities within the literature of urban identity in the context of urban planning and design is presently constrained. This research aimed to elucidate the role of biotic elements in community identity through an investigation into the case of bats in the city center. Various data collection methods were employed, encompassing documentation (including the scrutiny of texts and images), observation, and interviews. The research concentrated on the city of Watansoppeng, Indonesia, conducting semi-informal interviews with purposively selected residents, such as cultural leaders, academics, and officials from pertinent institutions. The research variables comprised history, collective memory, and culture, and the analysis adopted a biocultural approach. Digital qualitative analysis was conducted using Atlas.ti 23 software. The findings underscored the significant role played by bats in shaping community identity in Watansoppeng. These nocturnal creatures contribute substantially to the development of the community's historical narrative across generations, including the emergence of myths associating them with signaling impending disasters in the city. Moreover, bats function as custodians of the collective memory of the community, serving as reminders of the glory of the Soppeng Kingdom and the greatness of their First King. The interaction between bats and the community is also reflected in various cultural expressions, spanning language and linguistics, literature, cultural materials, science and technology, economic relations, social interactions, and belief systems.

Cloud and rainfall distributions in urban spaces have implications for planning, hydrological response, reservoir management, renewable energy generation, transportation, and agricultural productivity. Studies have confirmed that large urban areas can initiate or modify precipitation, but there are still questions about the role of city size and atmospheric interactions. The majority of case study approaches have focused on large cities or urban clusters and have largely ignored small to moderate sized cities. Herein, an analysis of the Augusta, Georgia metropolitan statistical area is conducted. Using a gridded, daily multi-sensor precipitation dataset and satellite-based cloud cover climatology, the warm seasons (June, July, and August) covering the period from 2002 to 2019 were analyzed using spatial comparisons within an upwind-downwind framework and z-score statistics. Such methodologies have been published for larger urban areas. We confirmed that a moderate-sized city like Augusta, Georgia and neighboring Aiken, South Carolina is associated with spatial patterns consistent with the “urban rainfall effect” (URE) and possibly an “urban cloud effect” (UCE). Contextual analysis of other local mesoscale signatures related to nearby water bodies are also provided as a sanity check on process identification.

The United States government sponsored the Home Owners’ Loan Corporation (HOLC) in the 1930s to assess and grade neighborhoods based on perceived financial risk. The grades were influenced by the presence of minority racial groups, immigrants, and residents with lower socioeconomic statuses and, even though the practice was eventually outlawed, the impact on low income and underrepresented minorities is still prevalent today. This study was designed to assess spatial patterns and intensity of flood risk to (a) HOLC grade, (b) proximity to coastal zones, (c) intensity of vegetative cover, and (d) relationship to buried (ghost) streams and wetlands to determine which variable has the most impact on flood risk. Flood risk data, acquired from First Street Foundation’s Flood Factor dataset, was summarized by HOLC grade, and ghost streams and wetlands were digitized from historical maps and aggregated by HOLC grade. The results show flood risk is higher in C and D graded neighborhoods, compared to A and B. Regardless of HOLC grade, neighborhoods near the Detroit River and Lake St. Claire have 10 times higher flood risk than inland neighborhoods. Interestingly, B-graded neighborhoods exhibit minimal impact from buried rivers and wetlands, but that risk increases substantially if there is a history of stream or wetland burial within a D graded neighborhood. Flood risk is disproportionately distributed, caused in part by outlawed, racist housing policies. Understanding where risk is highest can help identify optimum locations for adaptation measures to minimize flood damage in these neighborhoods.

Green spaces such as forests, grasslands, and croplands (including gardens) can be found in urban environments. Although they benefit human and animal well-being, they have become threatened due to rapid urban growth and unplanned development. Yet, little attention has been given to studying the dynamics of urban green spaces in sub-Saharan Africa. In this study, we examined the dynamics of land use and land cover (LULC) change and fragmentation (especially, green spaces) within the second fastest urbanising city in Ghana, Tamale. In particular, we focused our analyses on its urban core (∼5 km radius around the city centre) due to its relevance to urban economy and society. Landsat data was used to estimate fragmentation metrics of past and future LULC changes in the study area from 1990 to 2052. We found clear patterns of green space decline and fragmentation within the urban core: i.e., green spaces became patchy over time and the pattern was expected to continue in the future. Additionally, we found the built-up class benefited from the decline of green spaces with the latter being significantly negatively correlated with human population size. Our investigation reveals that protected forests and tree plantations contributed to a significant proportion of available green spaces in the urban core. However, these areas were becoming increasingly threatened by forest reserve downsizing, indiscriminate activities (e.g., logging and encroachment), and sale of public lands to private developers, practices commonly associated with population growth. Hence, the enforcement of relevant local legislations (e.g., the 2016 Land Use and Spatial Planning Act [Act 925]) coupled with the integration of urban initiatives and policies that encourage green spaces are needed to ensure the sustainability of urban ecosystems for the well-being of humans and the environment.

Plant biotechnology methods can be used in urban environments. Cell selection, genetic engineering, and micropropagation hold great promise among biotechnological methods. Two main applications for the use of cell selection for urban plants are possible in future. The first is the use of this technology in urban greening to improve plant resistance. The second is phytoremediation of contaminated urban soils. Micropropagation can be used for urban plant reproduction. The use of genetic engineering is promising for obtaining new varieties of urban plants with high ornamental qualities. When using genetic engineering techniques, environmental risks should be taken into account. The use of biotechnology for the urban environment will contribute to the development of applied biotechnology, urban biology, urban natural sciences and urban technical sciences. Future ornamental urban plants will change, but they will always play an important role in people's lives.

Episodic floods, attributable primarily to climate change, global warming, and sea level rise, have worsened and continue to be a significant threat to life. Building resilience and improving the adaptive capacities of communities under threat will require institutional and cross-agency collaboration. This paper assessed institutional arrangements for mitigating and adapting to climate change-related flood risk in GAMA, Ghana. Using a descriptive cross-sectional survey, the study collected and analysed data from 65 private businesses and governmental, community, and civil society organisations to assess how institutions collaborate in preparing and adapting to flood risks in the study area. The study finds that frequent flooding, destruction of property and lives, and regular community agitations have triggered high-level consciousness, institutional arrangements, and collaboration within and among communities to build capacity and resilience. In addition, organisations have been educating indigenes on flood preparedness, providing relief items to support flood victims, and conducting training and research. Organisations have also supported communities in developing sandbags, planning sea defence mechanisms, providing rescue and evacuation assistance, providing transportation and logistics, and relocating stranded flood victims. Despite these efforts, the lack of adequate funding and logistics, coupled with the absence of proper consultation and involvement of most organisations in making national-level decisions on climate change and flood-related issues, have rendered flood management efforts less effective. This paper makes the case that proactive and collaborative flood responses should replace reactive and individual approaches to improve flood control efficacy and minimise casualties and property losses.

Bangkok, the capital city of Thailand, has experienced a degradation in air quality. In particular, ozone (O₃) concentrations frequently exceed Thailand’s National Ambient Air Quality standards. Various policies have been developed to manage air quality at near-surface levels; however, the assessment of air quality above these levels has been neglected. Analysis of O₃ concentrations and its precursors measured at various altitudes revealed that the vertical structures of the pollutants in Bangkok were stratified. While NO_x concentrations decreased with height, O₃ concentrations increased. These results emphasize the importance of air quality management above ground level, particularly in megacities with high-rise buildings, such as Bangkok. Assuming that the O₃ formation regime over Bangkok is VOC-limited, a simple model was developed based on a linear regression method to estimate the changes in O₃ concentrations with height. We found that the simple model was able to capture the variation in O₃ concentrations at 30, 75, and 110 m above ground level, with an R² of 0.48–0.65. Although the simple model had some difficulty estimating the magnitude of O₃ concentrations, the estimated O₃ values from the model were reasonable for capturing vertical O₃ trends. Using this approach, policymakers can visualize the vertical distribution of pollutants, which will be useful in designing air quality management plans.

In Sub-Saharan Africa, many cities are facing an increased risk of heat due to climate change and rapid urbanization. This poses a particular threat in areas with limited adaptive capacity. However, there is a lack of comprehensive heat risk assessment in the region, possibly due to the absence of high-resolution weather data. This study aims to address this gap by proposing and demonstrating a methodology for mapping high-risk areas in a tropical humid city, specifically focusing on Lagos, Nigeria. The approach utilises advanced numerical modelling techniques and open-source geospatial data.

The urbanised Weather Research and Forecasting (WRF) model is employed to simulate Humidex-based heat stress during a specific heatwave event in March 2020. Open-source high resolution geospatial datasets were used to assess heat exposure and vulnerability. The urban areas were classified based on the Local Climate Zone (LCZ) scheme. Spatial analysis techniques, including Moran’s I test and Optimized Hot Spot Analysis (OHSA), were used to identify spatial clustering patterns and hot spots of heat risk areas.

Moreover, using Gi* statistics in OHSA, the risk layer was categorised into hot, cold, and non-significant spots at various levels of significance (90 %, 95 %, and 99 %). Mapping the hot spots at the highest confidence level of 99 % identified Critical Heat Risk Zones (CHRZ), covering an area of approximately 423 km². The results showed significant heat risk in highly urbanised LCZs. Further investigation indicated that the largest proportion of high-risk zones corresponded to densely populated and highly urbanised LCZs- LCZ3 (59 %), LCZ 6(21 %), and LCZ 7(17 %). Notably, these areas coincide with two well-known slums in Lagos, emphasizing the need for targeted interventions and planning measures in these areas.

The findings highlight the magnitude and extent of heat risk within the city and emphasize the urgent need for targeted climate change adaptation and mitigation strategies in the identified high-risk zones.

Accurate and timely evaluation and assessment of emission data and its impact on environmental status has been a key challenge due to the conventional manual approach utilized for independently computing most emission parameters. To resolve this long-standing issue, we proposed an Artificial Intelligence (AI)-driven Decision Tree model to adequately classify Environmental Protection Agency (EPA) status based on multiple Emission Parameters. The model's performance was systematically evaluated using multiple emission parameters obtained from a two-stroke motorcycle dataset collected in Nigeria across various metrics such as K-S Statistics, Confusion Matrix, Correlation Heat Map, Decision Tree, Validation Curve, and Threshold Plot. The K-S Statistics plot's experimental results showed a considerable correlation between HC, CO, and the target variable, with values ranging from 0.75 to 0.80. At the same time, CO₂ and O₂ do not correlate with the target variable with values between 0.00 and 0.09. The Confusion Matrix revealed that the proposed model has an overall accuracy of 99.9% with 481 true positive predictions and 75 true negative predictions, indicating the effectiveness of the proposed AI-driven model. In conclusion, our proposed AI-driven model can effectively classify EPA status based on multiple emission parameters with high accuracy, which may spur positive advancement in policy enhancement for proper environmental management.