Urbanisation is rapidly transforming cities around the world, presenting both opportunities and challenges for sustainable development. With the continued expansion of cities, the need for innovative and eco-friendly solutions has never been more critical. This special themed issue on Urban Green Technologies and Biodiversity seeks to explore the intersection of technology, urban planning, and environmental stewardship in addressing key sustainability challenges.
As our cities expand, pollution, biodiversity loss, and rising carbon dioxide emissions threaten the very foundation of urban life. Recent reports by the World Health Organisation highlight that over 80% of urban residents are exposed to unsafe air quality, exacerbating health crises and environmental degradation (WHO, 2022). This edition presents the most recent research into how green technologies can mitigate these challenges while fostering healthier, more resilient urban environments.
This special themed issue of Municipal Engineer brings five publications that show a diverse range of studies, each contributing to Urban Green Technologies and Biodiversity. The featured papers in this issue address a variety of critical topics, from carrying capacity assessments of urban areas to innovative transportation systems, and showcase cutting-edge methodologies aimed at improving urban sustainability.
As this special themed issue highlights, the path toward sustainable urban development is complex and multifaceted. By leveraging green technologies and focusing on biodiversity, cities can not only mitigate the negative impacts of urbanisation but also enhance the quality of life for their inhabitants. The research presented in this issue emphasises that achieving urban sustainability requires a holistic approach, one that addresses environmental, economic, and social dimensions simultaneously. We encourage readers to explore the papers in this issue and consider how the ideas and methodologies presented can be applied to cities around the world.
Note that the journal publishes its most recent articles Ahead of Print on its Virtual Library homepage if readers would like to study them earlier (https://www.icevirtual-library.com/toc/jmuen/0/0). The outline and key findings of these papers related to this Themed Issue are summarised below.
Enhancing Urban Resilience and Carrying Capacity
Tailor and Tailor (2024) presented research on Evaluating the Urban Population Carrying Capacity of Surat, which introduces a novel probability-satisfaction approach to assessing the limitations of urban infrastructure. Their study provides critical insights into how cities like Surat can optimise resource management to accommodate growing populations while maintaining liveability standards. By integrating factors such as healthcare, solid waste management, and green spaces, the authors offer a comprehensive view of how urban planners can prepare cities for future growth.
Designing Resident-Oriented Public Sports Facilities
Chen et al. (2024) investigate the Resident Demand-Oriented Selection and Spatial Layout Strategy for Public Sports Facilities. By focusing on public health and well-being, this paper offers a framework for the sustainable design of public sports amenities in urban areas. The study outlines strategies for aligning sports facility locations with resident demand, thereby enhancing community engagement and promoting healthier lifestyles while minimising resource waste.
Improving Outdoor Thermal Comfort and Indoor Sunlight
Song et al. (2024) explore How Building Arrangements Can Improve Outdoor Thermal Comfort and Indoor Sunlight. This paper investigates how urban building designs can be optimised to enhance both outdoor and indoor environmental conditions. By analysing the spatial arrangement of buildings, the authors demonstrate how urban planners can use architecture to improve thermal comfort and sunlight exposure, both of which are crucial to sustainable urban living.
Predicting Pavement Surface Conditions
Deneko et al. (2024) present a study on Predicting Pavement Surface Conditions Through Artificial Neural Networks. The authors use advanced machine learning algorithms to predict future pavement conditions, contributing to more sustainable urban infrastructure maintenance. Their model helps forecast the deterioration of pavements, providing urban planners and engineers with valuable data for optimising maintenance schedules and reducing the environmental impact of roadworks.
Transportation Innovation through Bayesian Inference
Another highlight of this issue is the work by Afandizadeh Zargari et al. (2024), who present a robust study on the Estimation of Travel Time in the Helsinki Region Using Sequential Bayesian Inference. This paper introduces advanced methodologies to improve traffic management and reduce congestion in urban settings. Their findings demonstrate how Bayesian models, combined with real-time data, can significantly enhance travel time predictions and reduce the environmental impact of transportation.
Proceedings of the Institution of Civil Engineers — Municipal Engineer 177 (3): 97, https://doi.org/10.1680/jmuen.2024.177.3.97
