Urban Population Growth Research Articles

Hit the Road: Spatial Characteristics of Labor Absorption in South Africa

Unequal spatial concentration is at the heart of economic imbalance in South Africa. This research aimed at spatially characterizing labor absorption patterns and exploring the link to spatial development. Labor absorption is often used as an indicator of labor market well-being and for many countries, the indicator is often more insightful than the unemployment rate. The research used secondary data to create a longitudinal data set of labor absorption, functional literacy, the ratio of urban population and gross domestic product growth rate, among others, at a municipal level. Exploratory spatial data analysis and thematic mapping were undertaken to illustrate the characteristics of the labor market, while spatial grouping created clusters of municipalities based on labor absorption. A positive upward trend was observed between labor absorption and the share of people in an urban area; that is, the more urban an area, the higher the labor absorption rate. Furthermore, the spatial clustering of municipalities highlighted linear patterns and when this was overlayed with roads and development corridors, clearly indicated the impact of regional spillovers. The findings suggest a more integrated focus on regional innovation policy to reduce spatial disparities in the economic landscape.

A Building Information Modeling-Based Life Cycle Assessment of the Embodied Carbon and Environmental Impacts of High-Rise Building Structures: A Case Study

High-rise buildings represent technological, urban, and life-style trends of the modern urban landscape, yet there are limited data regarding their embodied carbon and environmental impacts, particularly when compared to low- or mid-rise buildings. Given that the projected growth of the global urban population by 2050 requires cities with higher density and potentially a greater number of high-rise buildings, it is crucial to develop a clear understanding of the embodied carbon and environmental impacts of high-rise buildings. The primary structural materials used in high-rise buildings are reinforced concrete and structural steel. As of today, over 99% of tall buildings’ structures are built from those two materials. This article utilizes a building information modeling (BIM)-based life cycle assessment (LCA) in Revit and Tally to examine the embodied carbon and environmental impacts of an actual high-rise building structure case study in Chicago that uses a hybrid concrete steel structure. The results show that the embodied carbon and environmental impacts of the high-rise building structure are dominated by the impacts of the product stage in the building’s life cycle and by concrete being the main structural material. Specifically, this study reveals that concrete constitutes a substantial 91% share of the total mass of the building structure, with a 74% contribution to the life cycle global warming potential, 53% to the acidification potential, 74% to the eutrophication potential, 74% to the smog formation potential, and 68% to the non-renewable energy usage. On the other hand, steel accounts for 9% of the building’s structure mass, estimated to constitute 26% of the global warming potential, 47% of the acidification potential, 26% of the eutrophication potential, 26% of the smog formation potential, and 32% of the non-renewable energy usage.

Regional-scale landslide risk assessment in Central Asia

Abstract. Landslides are widespread phenomena that occur in any terrestrial area with slopes, causing massive property damage and, in the worst-case scenario, loss of human life. This propensity to suffer losses is particularly high for developing countries due to their urban development, population growth and drastic land use changes. Social and economic consequences of landslides can be reduced through detailed planning and management strategies, which can be aided by risk analysis. In this study, we performed a detailed quantitative risk analysis for landslides in the whole of Central Asia (4 000 000 km2). Landslide-induced risk was computed, using a 200 m spatial resolution, in terms of exposed population and expected economic losses to buildings and linear infrastructures (roads and railways). The purpose of our study is to produce the first regional-scale landslide risk assessment for Central Asia in order to inform regional-scale risk mitigation strategies, and it represents an advanced step in the landslide risk analysis for extremely broad areas.

Effect of Agricultural Land Function Transfer on Urban Development in North Kuta District

Land use change in general concerns the transformation in allocating land resources from one designation to another. The aims of this study were (1) to identify problems with the conversion of agricultural land, especially paddy fields (2) to analyze its spatial pattern and the influencing factors, and (3) to analyze policies related to the conversion of agricultural land. This study used a qualitative approach, collecting data using interviews, observation, and documentation techniques. The data analysis technique used is descriptive qualitative. The research was conducted in North Kuta District, Badung Regency. The conclusions from this study are (1) the conversion of agricultural land to non-agricultural use is strongly influenced by the dynamics of very rapid urban growth, both from a demographic, economic, and physical perspective. 2) The spatial pattern of the conversion of paddy fields is influenced by socio-economic factors, including urban population growth, growth and shifts in economic structure, growth of land-using agricultural households, and changes in the area of land tenure. 3) The policy related to controlling the conversion of agricultural land is the consistency of the implementation of the District RDTR as the key to preventing the conversion of agricultural land to non-agricultural land.

An emprical study to investigate the size of non-governmental organizations in OECD countries

This study aimed to analyze the factors affecting the size of non-governmental organizations (NGOs) from a multinational perspective. Empirical analyses were conducted through econometric modeling, and the data of the 17 countries from 2003 to 2019 were used. The data was obtained from the World Bank and OECD database. We used advanced panel data estimation techniques (CUP-FM and CUP-BC) to obtain long-run coefficients. GDP per capita, general government final consumption expenditure, adult education at tertiary level, and Gini index growth declined grants by private agencies and NGOs? contribution to GDP (GinGDP) initially but after a threshold level, GinGDP increased with growth at later stages of these variables. Urban population growth, employment, and foreign population have reducing effect on the size of NGOs. The size of NGOs has bidirectional causality relationship between GDP per capita, adult population at tertiary education level, employment to population ratio, and Gini index; and unidirectional causality between urban population growth, general government final consumption expenditure, and foreign population.

Картографирование шумового загрязнения урбанизированных территорий как инструмент формирования комфортной среды обитания человека

The article considers the issues of balanced functioning of urbanized territories (including urban environments) as objects of social ecology. The aim of this work is to analyze the current state of the urban environment in terms of noise pollution and the creation of thematic environmental maps of urban noise pollution. Using statistical methods, the authors justified the need for such maps and identified the main problems arising in their development. It was empirically confirmed that noise pollution has significantly increased across Russia against the backdrop of a steady growth in urban population. The experience of Russian developers of noise pollution maps was analyzed, showing how these maps can help in creating a comfortable living environment. The medical-ecological approach and statistical data analysis revealed a correlation between noise pollution in urbanized areas and negative social consequences for the population living in these areas. These consequences include not only an increase in diseases, such as cardiovascular and nervous system disorders, but also a general reduction in active life years. A unique aspect of the study is the approach to the problem from the perspective of creating spaces with positive soundscapes in urban environments and reflecting these on noise pollution maps. The necessity of such research is driven by the specifics of human adaptive mechanisms, which are unable to quickly adjust to changes in the environment. The conclusion is made that to mitigate the impact of noise pollution on the physical and psychological state of individuals, it is necessary to change the pattern of urban development towards an expanded understanding of functional zoning in urban areas.

Does Freedom of Domestic Movement Impact Forest Loss? A Cross-National Analysis

On the one hand, previous research argues that growth in rural populations leads to forest loss from clearing trees to make room for the growing population and their farming needs. On the other hand, research is also concerned with how deforestation drives people out of rural areas, leading to overurbanization. From this work, it is clear that the movement of people has an important relationship to forest loss, but it is less clear what the autonomy of people is in this process. Put differently, more focus has been put on state-level economic and environmental factors than political factors when considering the impact of domestic migration on forest loss. Although there has been substantial work on how political factors, like democracy, impact forest loss, there is less research on how political rights, like freedom of domestic movement, may impact forest loss. To build on this research, we test the impact of freedom of domestic movement and democracy on forest loss from 2001 to 2014 for a sample of 107 low- and middle-income nations. We find support for the idea that having more freedom of movement decreases forest loss in more democratic nations compared to less democratic nations. We also find that both rural and urban population growth, among others, is associated with higher levels of forest loss. Together, our findings suggest that the freedom of domestic movement should be taken into consideration in addition to population growth from actual domestic movement when researching forest loss.

Classification of Urban Functional Zones Based on Multiple Data Sources

With the rapid development of cities, more and more people are flocking to them. Therefore, cities require good planning to meet the needs of all urban residents. The first step in planning a city is to classify the functional areas of the city. This article introduces a method for classifying urban functional areas in the context of rapid urban population growth, aiming to plan cities better and meet population needs. Based on remote sensing, social perception, and multi-source data, corresponding classification methods were explored, and their roles in urban functional area classification were analyzed. Research has found that focusing remote sensing images on local areas, utilizing social perception data uploaded by passersby, and complimentary use of multi-source data can all improve classification accuracy. The exploration of these methods helps to classify urban functional areas more accurately, providing a better basis for future urban development planning and alleviating the pressure brought by urban population growth.

A generative approach to explore residential urban form potential based on environmental performance for energy efficiency

The United Nations predicts that by 2050, 70% of people will live in cities, which will bring significant environmental challenges, including climate change and resource depletion. In India, the residential sector account for 30% of total energy consumption. Therefore, it is crucial to optimize energy use in residential structures to address urban population growth, density, and energy efficiency. This study explores the use of genetic algorithms for multi-objective optimization in the design of energy efficient residential urban forms linking urban population growth and environmental concerns. Urban form significantly influences energy consumption within neighborhoods. However, introducing genetic algorithms into urban planning, a field not typically associated with such computational methods, presents considerable challenges. This research addresses complexities such as simulating and optimizing energy use by focusing on the control of solar radiation and the enhancement of natural daylight within residential neighborhoods. It further seeks to enhance the quality of life in open spaces by improving the sky view factor and the sense of spaciousness, adding another layer of complexity to the optimization. In response to these complexities, a framework is developed using the Biomorpher plugin, integrating genetic algorithms in Grasshopper. This research, carried out in Ahmedabad, India, progresses in two primary phases. The experiment progresses in two phases: first, developing prototypes considering factors like Floor Space Index and building types; and second, refining these through multiple design iterations based on environmental criteria. The study generates a diverse range of optimized scenarios, such as low-rise, mid-rise, and high-rise densities, to understand the relationship between residential form and energy consumption. The research identifies energy-efficient configurations through analysis, offering adaptable solutions tailored to specific environmental and spatial contexts.Additionally, it offers a replicable methodology for urban designers and policymakers.

Land Cover Change of Klaja Karst Watershed, General Santos City, Philippines

Effective land management and sustainable development necessitate an understanding of land usage’s scope and mechanism. This study aims to identify changes in land cover in the Klaja Karst watershed due to urbanization, development, and ongoing population growth, as well as to create projections for the area’s land cover twenty (20) years from the completion of the study. The study created land cover maps spanning 2003 to 2020 to investigate patterns and changes in the area’s land cover. Furthermore, projection maps for 2030 and 2040 were created using a dataset derived from the abovementioned maps. The predicted maps show steady growth of perennial crop cover and built-up areas. The most prominent variables leading to this increase are urbanization, population growth, and overall development. The city’s residents, on the other hand, have relied on the growth of perennial crops to meet their demands and produce sustenance. Conversely, the increase in built-up areas and perennial crops has reduced the coverage of other land types, particularly annual crops, open forests, and grasslands. Based on the information presented above, the researcher devised an action plan that prioritized improved land management, conservation, and utilization. The plan calls for strengthening the implementation of environmental laws and policies, providing farmers with additional farm inputs, financial assistance, and promoting co-management of the study area with neighboring municipalities. Part of the consideration is the formation of a Watershed Management Council for the Klaja Karst Watershed, as well as the possibility of declaring the study area a local conservation area and developing a long-term strategy. In general, the study and its findings represent a significant step forward not only for the city and region but also for a wide range of sectors, particularly land planners and environmentalists who are developing management plans that are economically viable, socially acceptable, and environmentally sustainable.

Catalysing water treatments: A Comprehensive Examination of sludge, its treatment and Energy Valorisation Solutions

The escalating production of sewage sludge in WasteWater Treatment Plant (WWTP) due to urban population growth and its management poses a substantial risk to the energetic and environmental efficiency of WWTP. This paper aims to explore the potential for sludge as a renewable energy source to reduce reliance on traditional energy through a systematic literature review of peer-reviewed articles and case studies. This overview demonstrated that various treatment methods such as anaerobic digestion, incineration, gasification, and pyrolysis are the most used and the most promising in terms of their energy outputs and effectiveness. The paper discussed the complexity of sludge composition, its financial burden on WWTP, and the crucial role in the success of these systems. Moreover, a comparative analysis of the different valorisation techniques was conducted that highlighted the energy production potential existing within each method and its underlying constraints while emphasising on the proper sludge management for overall efficiency. Finally, this paper recommended the need for sustainable, cost-effective approaches, considering legal standards for efficient WWTP.

Enhancing Urban Mobility through Traffic Management with UAVs and VLC Technologies

This paper introduces a groundbreaking approach to transform urban mobility by integrating Unmanned Aerial Vehicles (UAVs) and Visible Light Communication (VLC) technologies into traffic management systems within smart cities. With the continued growth of urban populations, the escalating traffic density in large cities poses significant challenges to the daily mobility of citizens, rendering traditional ground-based traffic management methods increasingly inadequate. In this context, UAVs provide a distinctive perspective for real-time traffic monitoring and congestion detection using the YOLO algorithm. Through image capture and processing, UAVs can rapidly identify congested areas and transmit this information to ground-based traffic lights, facilitating dynamic traffic control adjustments. Moreover, VLC establishes a communication link between UAVs and traffic lights that complements existing RF-based solutions, underscoring visible light’s potential as a reliable and energy-efficient communication medium. In addition to integrating UAVs and VLC, we propose a new communication protocol and messaging system for this framework, enhancing its adaptability to varying traffic flows. This research represents a significant stride toward developing more efficient, sustainable, and resilient urban transportation systems.

Analysis of Urbanisation’s Relationship with Clean Water Supply Ecosystem Services in Sukoharjo Regency, Indonesia

The phenomenon of urban population growth is a global concern which will result in a decrease in the value of ecosystem services in an area. Sukoharjo Regency is an area affected by the development of Surakarta City; therefore, rapid growth is taking place. The objective of this study is to investigate the interplay between urbanization, ecosystem services, and the provision of clean water in Sukoharjo Regency in 2022. The methods used in the study were calculating the percentage of the urban population to determine the level of urbanisation, AHP and overlay to ascertain the ecosystem service score, together with cross-tabulation to establish the relationship between these two variables. The result of this study is that the level of urbanisation produces a pattern that districts in the north tend to comprise a higher level. The clean water supply ecosystem services in Sukoharjo Regency obtained results dominated by the low to medium level. The situation regarding the level of urbanisation and ecosystem services in Sukoharjo Regency reveals a relationship where an increase in the level of urbanisation will reduce the value of ecosystem services.

Characteristics of Green Roof and Vertical Greening Systems and Its Application Prospect in Hong Kong

Under the background of urban population growth and increasingly prominent urban environmental problems. Green infrastructure in line with sustainable development is considered a possible solution. This paper aims to study the application of green roofs (GR) and vertical greening systems (VGS) in densely developed cities, such as Tokyo and Singapore, and provide a reference for Hong Kong. This study believes that GR and VGS have great potential in alleviating urban environmental problems in Hong Kong and can effectively provide more green development space. At the same time, it plays an active role in alleviating the urban heat island effect, reducing air pollution and energy consumption. Currently, there are some urgent problems with the application of GR and VGS in Hong Kong, such as construction cost recovery, hidden dangers of public safety, and technical construction difficulties. In addition, this paper suggests that Hong Kong should provide more investment and support for GR and VGS in legislation and technology to promote their promotion and popularization.

Analysis of Urban Rail Transit Short-term Passenger Flow Forecast and Its Optimization

With the growth of urban population and the increase of car ownership, the number of cars continues to increase, leading to traffic congestion becoming a major problem in many cities around the world. Traffic congestion not only wastes time, but also increases air pollution and energy consumption. To address these challenges, governments and transportation authorities around the world have begun to adopt advanced technical models and big data based approaches. By using the power of intelligent data analysis, this paper enables people to understand rail transit more deeply, establish an ARIMA model for short-term prediction, optimize traffic flow, and improve the overall performance of the system. Through the final experimental results, it is found that the trend of rail transit passenger volume in the next few days is increasing, but its growth trend is not as high as that of the previous few days. The ARIMA model infers that the peak period in the next few days may not be as high as that of the previous few days.

Navigating urban day-ahead energy management considering climate change toward using IoT enabled machine learning technique: Toward future sustainable urban

The rapid evolution of technology and urban population growth has led to a significant increase in energy consumption, particularly in electricity production. However, the ability to meet energy demands, especially during peak periods, is constrained by various factors including environmental concerns, technological limitations, and economic constraints. Effective energy management strategies are crucial to mitigate these challenges and ensure a sustainable energy future. One promising approach is the implementation of demand response programs. In this context, we explore the potential of Home Energy Management Systems (HEMS) leveraging modern Internet of Things (IoT) technology. HEMS systems are at the forefront of research and development in the field of smart grids (SGs), offering capabilities in demand-side management and power availability control. These systems achieve efficient energy usage by optimizing the operation of home appliances (HAs). To further enhance the performance of HEMS, this study introduces a novel metaheuristic known as the Grey Wolf and Crow Search Optimization Algorithm (GWCSOA). This algorithm is employed to determine the optimal scheduling of HAs within the HEMS framework. Additionally, we utilize MATLAB and ThingSpeak modules to implement and test the HEMS design. The proposed HEMS, integrated with GWCSOA, demonstrates remarkable capabilities in reducing daily power costs, minimizing the peak-to-average ratio (PAR), and enhancing consumer satisfaction. The findings of this study indicate that the devised system holds the promise of substantially diminishing both power expenses and microgrid emissions. Through the optimization of Home Energy Management Systems (HEMS) operations, this methodology plays a vital role in realizing a sustainable urban energy ecosystem. This aligns seamlessly with the overarching objectives of combating climate change and securing the enduring sustainability of our cities. The proposed HEMS, integrated with GWCSOA, demonstrates remarkable capabilities in reducing daily power costs by an average of 25.98 %, minimizing the peak-to-average ratio (PAR) by 30 %, and enhancing consumer satisfaction. The outcomes of this research reveal that the developed system has the potential to significantly reduce both power costs and microgrid emissions. By optimizing HEMS operations, this approach contributes to achieving a sustainable urban energy ecosystem, aligning with the goals of addressing climate change and ensuring the future sustainability of our cities.

Towards Global Food Security: Vertical Farming as an Innovative Solution

Vertical farming is becoming the focus of attention as an innovative solution to the challenge of global food security. Urbanization and rapid population growth give rise to the need for efficient agricultural approaches to land use. This research aims to investigate the potential and impact of vertical farming on global food security through a descriptive qualitative approach. The data used in the research comes from various relevant previous research and studies. This research method involves the process of collecting data from scientific literature and previous studies, which are then processed by researchers to produce relevant findings. Through descriptive qualitative analysis, this research highlights the contribution of land use efficiency, adaptation to urban environments, and integration of advanced technologies in the context of vertical farming. The results of this research then found that vertical farming is not only an alternative but also a significant step forward in the transformation of the global agricultural sector. Supportive agricultural regulations and policies, as well as adapting technology to the local environment, are critical challenges in implementing vertical farming. However, opportunities for developing innovations in vertical farming system design and active stakeholder involvement provide a strong foundation for the growth of this industry. This research highlights that vertical farming has great potential to have a positive impact on global food security, by understanding and overcoming existing challenges.

Investigating the Key Aspects of a Smart City through Topic Modeling and Thematic Analysis

In recent years, the emergence of the smart city concept has garnered attention as a promising innovation aimed at addressing the multifactorial challenges arising from the concurrent trends of urban population growth and the climate crisis. In this study, we delve into the multifaceted dimensions of the smart city paradigm to unveil its underlying structure, employing a combination of quantitative and qualitative techniques. To achieve this, we collected textual data from three sources: scientific publication abstracts, news blog posts, and social media entries. For the analysis of this textual data, we introduce an innovative semi-automated methodology that integrates topic modeling and thematic analysis. Our findings highlight the intricate nature of the smart city domain, which necessitates examination from three perspectives: applications, technology, and socio-economic perspective. Through our analysis, we identified ten distinct aspects of the smart city paradigm, encompassing mobility, energy, infrastructure, environment, IoT, data, business, planning and administration, security, and people. When comparing the outcomes across the three diverse datasets, we noted a relative lack of attention within the scientific community towards certain aspects, notably in the realm of business, as well as themes relevant to citizens’ everyday lives, such as food, shopping, and green spaces. This work reveals the underlying thematic structure of the smart city concept to help researchers, practitioners, and public administrators participate effectively in smart city transformation initiatives. Furthermore, it introduces a novel data-driven method for conducting thematic analysis on large text datasets.

Assessment of the future environmental carrying capacity using machine learning algorithms

Globally, ecological overshoot has become more prevalent. Enhancing biocapacity has become critical to resolving ecological demand overshoot in sustainable urban development. However, most of the prior research has focused on minimizing environmental carrying capacity (ECC) while ignoring the potential of carbon footprint, population growth, and land cover (LULC). This research assessed the past and projected changes in bio-capacity and bio-productivity dynamics in Khulna City due to land use and land cover (LULC) transformations spanning from 2000 to 2035. Support Vector Machine algorithms were utilized for the classification of LULC, and LULC, bio-capacity and bio-productivity predictions were made using Cellular Automata-Artificial Neural Network models. Results revealed that built-up and cropland area expansion led to an increase in carbon emissions by 43,000 tons/year and bio-productive land by 1100 gha, while a decrease in bio-capacity from 0.09 gha to 0.06 gha occurred during 2000–2020. The prediction shows that by 2021, population growth and urban growth will exceed Khulna City's bio-capacity, and by 2035, bio-capacity (without built-up cover) will decrease to 0.00 gha. The R2 values (–0.67 and –0.91) indicate the strong negative influence of population growth and urbanization on the optimization capacity of soil surfaces. The study demonstrates that Khulna's present urban growth and population growth will result in irreversible ecological collapse, with dire consequences for humans in thenear future.However, the findings facilitate the potential for the decision makers including policymakers, planners, and environmentalists to enhance local land use practices, thereby addressing CO2 emissions and their associated consequences meriting further study.

Sustainable Energy from Waste: A Feasibility Study in Miri, Malaysia

The growth of urban populations, industrialization, and economic development has led to a surge in solid waste production. When local recycling infrastructure falls short, much of this waste ends up in landfills, causing environmental and social challenges. This study aims to assess the feasibility of converting municipal solid waste (MSW) into energy, with a focus on combustion chamber modeling in Miri, Sarawak. Data on MSW composition are obtained from secondary sources. Ansys Fluent software is used to model the combustion chamber, and simulations are conducted to explore temperature, turbulence, and species distribution. MSW composition illustrates higher substantial fractions, with 39.8% being food waste, followed by 20.7% plastic/rubber. Calorific values range from 4652 kJ/kg for food waste to 32564 kJ/kg for plastic/rubber. Combustion simulations result in maximum flue gas temperatures of 1500 °C, 1200 °C, and 1800 °C under varying air inlet conditions. Turbulence intensities on the grate range from 125% to 174% for these air inlet configurations. The study concludes that moisture content significantly affects calorific value and heat generation during combustion. Higher turbulence intensities lead to increased reaction rates and heat generation, improving the energy efficiency of the process.