Urban Growth Research Articles

Comparative Analysis of Household Residential Preferences Across Neighbourhood Densities in Nairobi, Kenya

Rapid urban growth in Nairobi city outstrips demand and provision of adequate housing. The demand for housing in an area is dependent on the satisfaction of the resident’s needs and wants. This paper examines the residential preferences of residents in three residential estates, low, medium, and high densities in Nairobi City, Kenya. Data was collected by use of questionnaires that were administered to 267 households. Primary data was collected for this study. The data collected was analysed using factor analysis and ordinal regression. Data was presented in the form of tables. The results indicate residential preferences among high, medium and low-density areas vary. The most preferred factors for low-density residents were safety and security, open spaces and facilities; while the residents in high-density areas preferred housing diversity, local employment and close proximity to the workplace. The least preferred factor for low-density residents was close proximity to work place since they own cars hence they are more willing to commute while high-density residents prioritize proximity to work to minimize transportation costs. Residential preferences varied by density, age, gender, education and years lived in an estate. Preference for safer neighbourhoods with open spaces and facilities was high for residents in low-density areas while preference for neighbourhoods with housing diversity, local employment and close proximity to workplaces was high among the residents in high-density estates. These insights underscore the importance of addressing the varied needs and preferences of different demographic groups in urban planning and housing policy to create more equitable and livable communities in Nairobi in order to limit housing mismatch. This study contributes to the planning studies by firming up empirical evidence from developing countries that have high populations in urban areas

Pengaruh Faktor-Faktor Perilaku Konsumen terhadap Keputusan Pembelian Produk Frozen Food di Adam Frozen Food Kabupaten Bekasi

Bekasi Regency is one of the metropolitan areas in Indonesia with rapid population and urban growth. The majority of Bekasi Regency residents have a busy lifestyle with a busy work routine. This time limitation makes Bekasi Regency residents need practical food products such as frozen food. Frozen food products are the right choice because they are easy to store, durable, and quick to serve. One of the frozen food stores in Bekasi Regency is Adam Frozen Food, which sells frozen food products as a solution to meet food needs without spending excessive time and energy. Competition in the frozen food industry is getting tighter with many offering similar products with competitive quality and prices. With this condition, research is needed to understand the factors of consumer behavior in purchasing frozen food products at Adam Frozen Food, Bekasi Regency. The purpose of this research is to analyze the influence of cultural factors, social factors, personal factors and psychological factors on purchasing decisions for frozen food products at Adam Frozen Food. The sampling method used the Lemeshow formula with 100 respondents. The data analysis used is multiple linear regression. The results showed that cultural factors, social factors, personal factors and psychological factors simultaneously influenced the variable purchasing decisions for frozen food products at Adam Frozen Food. Social factors, personal factors and psychological factors partially influence the decision to purchase frozen food products at Adam Frozen Food. Meanwhile, cultural factors partially have no effect on purchasing decisions for frozen food products at Adam Frozen Food.

Addressing Urban Sprawl: is Densification the Solution? A Case Study of Sétif, Algeria

Objectives: The rapid and uncontrolled urban growth in Sétif, northeastern Algeria, has resulted in horizontal densification, continual expansion, and the conversion of agricultural land into urban areas. This transformation highlights the need for effective territorial strategies to manage urban growth sustainably. The primary objective of this study is to promote urban densification through concepts like "inward urbanisation" and "building the city within the city," aiming to optimise land use and counter the negative impacts of urban sprawl. Methods: To address the challenges of urban sprawl and its environmental impacts, the study employs a morphological approach. A Geographic Information System (GIS) is utilised in conjunction with data from the General Census of Population and Housing (RGPH) to analyse spatiotemporal changes in Sétif. This methodological approach enables a detailed examination of the city's morphological and demographic evolution, providing insights into patterns of urban expansion and densification. Results: The findings reveal various strategies for urban development in Sétif, focusing on alternatives to traditional urban density and sprawl. The study identifies and suggests the implementation of new, dense, and hybrid urban forms that align with sustainable development goals. These urban forms are designed to enhance the city’s livability while respecting societal needs and environmental considerations. The strategies proposed address the necessity for adaptable urban designs that support a more compact, resource-efficient city model. Conclusion: This research underscores the importance of rethinking urban planning strategies to manage rapid urbanisation in Sétif. The proposed strategies are essential for transforming Sétif into a dense, sustainable, and appealing urban environment. The study advocates for a shift from expansive urban growth to a densification model that promotes sustainability and aligns with the evolving expectations of the city’s residents.

Applying Topological Information for Routing Commercial Vehicles Around Traffic Congestion

The growth of urbanization, population, and economic activity has led to a substantial increase in freight transportation demand, exceeding the capacity of existing infrastructure and creating new challenges across various regions. This has resulted in significant traffic congestion, increased travel times, and higher operational costs for commercial vehicle fleets. Leveraging topological data, such as road networks and traffic patterns, can enable more efficient routing strategies to navigate around congested areas. This study presents a comprehensive approach to truck rerouting strategy by integrating spatial analysis, truck characteristics, traffic conditions, road geometry, and cost–benefit analysis to select alternative routes suitable for commercial vehicle fleets. Incorporating real-time traffic information and predictive analytics, commercial vehicle operators can optimize their routes, reduce fuel consumption, and improve overall delivery efficiency. Three case studies were presented to demonstrate the proposed diversion decision framework. Two scenarios were designed for each case study: a base scenario with no diversion and an optimized scenario with a diversion strategy. The travel times, fuel consumption, and economic impacts between the two scenarios were compared and quantified as a total annual saving of USD 52 million. This approach goes beyond selecting alternative routes and provides decision makers with measurable benefits that justify diversion strategies.

The Potential of Internal Migration to Shape Rural and Urban Populations Across Africa, Asia, and Latin America

AbstractSubnational divergence in the age and sex structures of populations can have far‐stretching consequences for development: from marriage markets to the potential for violence to economic growth. With urbanization and the demographic transition still underway, rural and urban populations continue to differ across low‐ and middle‐income countries. We examine the extent by which internal migration contributes to these differences, from 1970 to 2014 using estimates of migration between rural and urban sectors based on census data from 45 countries. We found that despite heavily delineated migration profiles by age and sex, internal migration does not alter sex and age structures of rural and urban populations. All the same, internal migration does increase urban growth in Asia and Latin America and the Caribbean. In contrast, in Africa, internal migration has little leverage with the urban transition. Across the continents, there is a potential for de‐urbanization, driven by a rural/urban gap in fertility. As such, the rural population may continue to constitute a significant proportion of national populations, necessitating critical investments to ensure they are not left behind.

Green energy using oscillatory baffled reactors: advances in biodiesel production from high free fatty acid karanja oil

Abstract The global demand for sustainable and ecologically friendly energy sources has spurred biodiesel research. Civilization, urbanization, and population growth have drastically boosted transportation energy consumption. Energy demand is causing fossil fuel crises. Replace petroleum diesel to solve energy and environmental problems. Biofuels have very vast scope in the area of energy sector. Karanja oil, derived from the seeds of the Karanja tree (Pongamia pinnata), is a promising biodiesel feedstock due to its high Free Fatty Acid content. This study uses Oscillatory Baffled Reactor (OBR) to produce biodiesel from Karanja oil. The feedstock is high-FFA Karanja oil trans-esterified in two steps. In OBR, reaction time is only 15 min, whereas in conventional reactor it takes 1–2 h to produce biodiesel. Optimizing biodiesel synthesis involved varying H2SO4 concentrations from 1 vol% to 5 vol% and 0.3 to1.0 wt% of NaOH concentration for first and second step respectively. Oil-to-alcohol molar ratios 1:6, 1:9 and 1:12. Optimization occurs at 1:12 oil-to-alcohol ratio, 1 vol% H2SO4 catalyst, and 0.6 wt% NaOH catalyst. Studies have also examined how catalyst concentration and oil: alcohol molar ratio affect biodiesel conversion and physical qualities such kinetic viscosity, specific gravity, and acid value. This study shows that OBR can increase biodiesel production from high-FFA Karanja oil, which further opens up opportunities for additional study and improvement.

Comparing the accuracy of 3D urban olive tree models detected by smartphone using LiDAR sensor, photogrammetry and NeRF: a case study of ’Ascolana Tenera’ in Italy

Abstract. Rapid urban growth makes green space management crucial to improve citizens’ well-being. Urban olive trees characterize the Italian landscapes and their culture. This study explores different methodologies for urban tree assessment in this context, using an iPhone 14 Pro Max. These included: 1) its integrated Light Detection and Ranging (LiDAR) sensor using the Recon3D app, 2) its camera with Structure from Motion (SfM) techniques, and 3) its camera for generating 3D models using Neural Radiance Fields (NeRF). Additionally, a professional Mobile Laser Scanner (MLS), was used for comparison. Total height (H), canopy base height (CBH) and canopy volume (CV) measurements were extracted using both CloudCompare and allometric formulas. The main aim of this paper is to compare the 3D models of olive trees obtained from low-cost sensors with those generated from the MLS, which is a more accurate device but comes with significantly higher costs. The results, in terms of RMSE (iPhone LiDAR - H: 0.46 m, CBH: 0.12 m, CV: 15.66 m3; iPhone-SfM - H: 0.95 m, CBH: 0.19 m, CV: 25.85 m3; iPhone-NeRF - H: 1.26 m, CBH: 0.31 m, CV: 33.79 m3), bias and volume differences, reveal that the smartphone, in all the methodologies, tends to underestimate measurements as the size of the trees increases. This is due to the higher MLS range of acquisition. Despite these limitations, low-cost solutions like smartphone-based methods can be a viable alternative given their economic accessibility.

Long-term trends and future projections of larynx cancer burden in China: a comprehensive analysis from 1990 to 2030 using GBD data

Larynx cancer poses a significant public health challenge in China, with rising incidence and mortality rates over the past decades. Understanding the long-term trends and underlying factors is crucial for effective intervention and policy formulation. Data were utilized from the global burden of disease (GBD) Study 2021 to analyze the incidence, prevalence, mortality, disability-adjusted life years (DALYs), years lived with disability (YLDs), and years of life lost (YLLs) due to larynx cancer in China from 1990 to 2021. Joinpoint regression analysis identified key changes in trends, while age-period-cohort (APC) analysis and decomposition analysis quantified the contributions of aging, epidemiological changes, and population growth to these trends. Our study found a significant increase in the incidence and prevalence of larynx cancer in China, particularly among males. The age-standardized incidence rate (ASIR) and age-standardized mortality rate (ASMR) for males were substantially higher than those for females. Decomposition analysis revealed that aging was the primary driver of increasing incidence and mortality rates, while epidemiological changes had a mitigating effect. Joinpoint analysis identified periods of rapid urbanization and economic growth as key turning points for increased incidence. Bayesian APC models projected a continued upward trend in incidence rates up to 2030. The rising burden of larynx cancer in China underscores the need for targeted public health interventions, including smoking cessation programs, environmental pollution control, and early detection strategies. Addressing gender disparities and implementing effective prevention measures are crucial to mitigating the impact of larynx cancer in China.

A Fermatean Fuzzy SWARA-TOPSIS Methodology based on SCOR model for Autonomous Vehicle Parking Lot Selection

Population growth in crowded cities and the resulting increase in vehicle use have led to the problem of insufficient parking. When public parking lots and urban growth are not in coordination, vehicles park on the street and close the crosswalks. In the coming years, this problem will become more complicated with the addition of autonomous vehicles (AVs) to urban traffic. This study addresses the research question of how to effectively select AV parking lots in urban areas experiencing population growth and increased vehicle usage. For this aim, a hybrid Multi-Criteria Decision Making (MCDM) methodology, combining SWARA (Step-wise Weight Assessment Ratio Analysis) and TOPSIS (Technique for Order Preference by Similarity) approaches in a Fermatean Fuzzy (FF) environment is proposed. The decision hierarchy based on the SCOR model has been developed to determine and construct the evaluation criteria. Then, a case study analysis has been applied to selected districts in Istanbul, which is Turkiye's most populous and developing city. Operating expenses, safety and security, and land costs are determined as the most important factors. As a result of the detailed fuzzy analysis, which districts should primarily be chosen for AV parking lots in Istanbul is determined and finally, the robustness and validity of the results obtained by the sensitivity analysis being questioned. The study contributes by providing insights into AV parking lot selection, demonstrating the efficacy of the proposed methodology, and highlighting the importance of addressing this issue in urban planning.

Ecosystem service value in the context of urbanization: comparison among economic-social regions of Vietnam

Urbanization is one of the important features of socio-economic development and it has a major impact on the value of ecosystem services (ESV). This study aims to quantify ESV for the entire country of Vietnam with the research unit being 6 socio-economic regions. This can be considered the first study in Vietnam to quantify the ESV for the entire country. The study calculated the annual urban land growth index (AI) and the annual urban land expansion rate (AER) to determine the urbanization status in the six study areas. The study collected input data from JAXA for four years: 1990, 2000, 2010, and 2020. Research results show that urban land area tended to increase and forest land area decreased sharply. The AI and AER indicated that the period 2000–2010 was a period of rapid growth in Vietnam. Meanwhile, the ESV for all of Vietnam increased year by year. The period 2000–2010 witnessed a growth in ESV about 2.35 times higher than the period 1990–2000, and about 0.1% lower than the period 2010–2020. Overall, MKD was the region showing strong growth in ESV from 1990 to 2020. Compared to that, NMR was the region with the largest decline in the 20 years from 1990 to 2010, and CHR in the past 10 years. This research contributes to enriching reference sources for Vietnamese and world researchers to have a broader view of ESV as well as the annual urban growth rate in Vietnam from 1990 to 2020.

Assessing De Facto Wastewater Reuse and Its Implications for Water Quality in Yangtze Basin (2014-2021)

De facto wastewater reuse is the incidental presence of treated wastewater in a water supply source. Unplanned indirect wastewater reuse, which is also called de facto reuse, occurs when wastewater is discharged into surface water upstream of the intakes of suitable drinking water treatment plants. Although this discharged wastewater may increase the water quality risks for downstream water supplies, they contribute to the water supply source as an additional in-stream flow. Therefore, proper wastewater management is crucial to ensure access to safe water and address the challenges due to urbanization and population growth. There are detailed data on the infrastructure and river flows in some countries, but this study examined the use of a more limited dataset in other countries and specifically assessed the de facto reuse in the Yangtze River Basin in China. GIS modelling was used to calculate the streamflow of Yangtze River from the DEM, while macro water consumption data was used to estimate the wastewater discharges, and this methodology solved the problem that the outcome was limited by the lack of gauging stations at more locations and lack of precise geospatial location of drinking water intakes or wastewater discharges. Under an average-flow condition, Chongqing in the upper reaches had de facto reuses that increased from 0.57% in 2014 to 0.60% in 2021; Wuhan in the middle reaches had de facto reuses, which increased from 1.56% in 2014 to 1.64% in 2021; Shanghai, which is located in the estuary of the Yangtze River, increased its de facto reuse from 2.35% in 2014 to 2.51% in 2021. Under low-flow conditions, the de facto reuse of Chongqing, Wuhan, and Shanghai in 2021 was 1.7%, 4.9%, and 7.4%, respectively. This relatively high level of de facto reuse is consistent with the estimation of unintended treated wastewater contributions to streams and growing risk of drinking water quality in the Yangtze River Basin. This research estimated de facto reuse in the Yangtze River Basin and showed the feasibility of using limited infrastructure datasets to assess de facto reuse and the modeling methods allow identification of river reaches most impacted by wastewater, and perhaps suggest prioritization for investments in additional wastewater treatment in reaches with high de facto reuse.

Spatio-temporal land use/land cover change analysis and assessment of urban heat island in Ghana: A focus on the Greater Accra Region

The expansion of cities coupled with economic development over the years has transformed many locations into hotspots for massive urban populace. The Greater Accra Region which is the capital city of Ghana is no exception. The urban population growth rate in the region has expanded extensively at the expense of increasingly vegetation cover. As a result, there is an increasing need to investigate urban resilience, land use/land cover (LULC) change, and urban heat islands (UHI) dynamics in the region. The aim of this study is to analyze multi-spectral Landsat images of 2000 and 2020 to examine the LULC change and the UHI trend across the Greater Accra Region of Ghana. The results from the analysis show a significant change in the spatial trend of land surface temperature (LST) and UHI between the years 2000 and 2020. Spatial distribution of LST from 0°C to 28°C and 17°C to 33°C in the years 2000 and 2020 respectively were observed. Urban areas dominated more than half of the study area in 2020, covering 85% (equivalent to 3160 sq. km), and reflecting a 20% increase from the year 2000 to 2020. During the same period, sparse and dense forested areas decreased by 10% (373 sq. km) and 4% (146 sq. km) with a 5% reduction in bare land (equivalent to 177 sq. km). The spatio-temporal analysis revealed a significant surge in the population of urban areas within the study area. The UHI areas also increased from 13.20% in 2000 to 18.20% in 2020. On the other hand, non-UHI areas decreased from 86.80% to 81.80% during the same period. The successful contribution of this research demonstrates the usefulness of spatial models as tools in generating LULC maps for assessing UHI to facilitate future sustainable city planning.

Assessing the impact of urbanization and economic growth on terrestrial carbon storage based on remote sensing: evidence from the yangtze river economic belt

Assessing the impact of urbanization and economic growth on terrestrial carbon storage based on remote sensing: evidence from the yangtze river economic belt

Investigating the Need for Urban Air Mobility in Tehran City

The increase in urbanization has led to the creation of dense population in urban areas, along with economic development and the increase in vehicles, which has led to an increase in demand and consequently an increase in many challenges regarding mobility and infrastructure. Solving these challenges or reducing the effects of these challenges can have significant effects on people's daily lives. Various solutions have always been proposed to solve these challenges, some of which have been successful and some of which have not. In the city of Tehran, too, challenges have arisen due to the rapid growth of urbanization, population, and vehicles, and solutions have been proposed to solve these challenges or improve the conditions, but due to the current conditions in Tehran, these solutions have not been able to appear as successful as they should be. In this paper, by examining the conditions of Tehran in terms of noise pollution, energy and fuel consumption, air pollution, traffic conditions, public and road transportation, it is proved that Tehran needs a new mode of transportation. According to today's needs of Tehran, this new mode of transportation can be an urban air mobility (UAM) that can be used in areas such as passenger and goods transportation. The presence of this mode of transportation in the transportation system of Tehran, in addition to improving the level of transportation of this city, helps to improve and even solve the challenges of today's transportation in Tehran, such as the high noise pollution of this city.

Improving Housing Sustainability Through an Innovative Approach

The need for housing has always been a concern for societies throughout history, and for a long time, providing suitable housing has been a challenge not only for individuals but also for governments. Housing is a fundamental human need; however, access remains a significant challenge, especially for low-income families. Rapid urbanization exacerbates this issue and highlights the need for innovative and sustainable housing strategies that can support urban growth and improve living conditions for these families. This literature review examines housing strategies such as mixed-use developments, incremental housing, low-rent housing, retrofitting, micro-housing, co-housing, and green building through a comprehensive literature search and thematic analysis to address housing challenges comprehensively. The findings suggest that these strategies can significantly enhance spatial equity and promote sustainable urban development. This paper contributes to the existing body of knowledge by providing practical recommendations for policymakers, urban planners, and housing advocates, aiming to strengthen inclusive, equitable, and sustainable cities. The study emphasizes that appropriate design techniques, new materials, and technologies not only increase housing sustainability but also enhance affordability by reducing life cycle costs. This research establishes the link between sustainability and affordability in housing design and offers insights that can be adapted and applied in other areas with low-income groups.

A Review of Environmental Conditions between Planned and Unplanned Urbanization with Special Emphasis on Kalyani and Ranaghat Urban Areas

Urban settlements in India are generally classified as planned or unplanned as opposed to planned or unplanned urban areas due to land use and taking into account various factors including physical social and economic considerations and land use patterns. Rapid urban growth in India, mostly in an unplanned fashion, is currently a major problem. Urban growth occurs through replacement of vegetation, agricultural areas, wetlands, etc. This results in an unprecedented increase in heat, which dominates the microclimate of urban areas and creates an environmental crisis. Geospatial technology plays a unique role in planned and unplanned urban areas of West Bengal by monitoring spatio-temporal changes in urban heat by estimating land surface temperature and analyzing built-in indices of vegetation cover. It can be classified as NDVI and NDBI suggests that urban heat is controlled by surface character which is analyzed for proper planning for sustainability of urban areas

An integrated approach of support vector machine (SVM) and weight of evidence (WOE) techniques to map groundwater potential and assess water quality

This study addresses the critical need for effective groundwater (GW) management in Muzaffarabad, Pakistan, amidst challenges posed by rapid urbanization and population growth. By integrating Support Vector Machine (SVM) and Weight of Evidence (WOE) techniques, this study aimed to delineate GW potential zones and assess water quality. This study fills the gap in applying advanced machine learning and geostatistical methods for accurate GW potential mapping. Eight thematic layers based on topography, hydrology, geology, and ecology were utilized to compute the GW potential model. Additionally, water quality analysis was performed on collected samples. The findings indicate that flat and gently sloping terrains, areas with an elevation range of 611 –687 m, and concave slope geometries are associated with higher GW potential. Additionally, proximity to drainage and high-density lineament zones contribute to increased GW potential. The results showed that 31.1% of the area had excellent GW potential according to the WOE model, whereas the SVM model indicated that only 20.3% fell in the excellent potential zone. Results showed that both models performed well in the delineating GW potential zones. Nevertheless, the application of the SVM method is highly recommended which will be benefited in GW resources management related to urban planning. The study also evaluates the spatial distribution of GW quality, with a focus on physical and chemical parameters, including electrical conductivity, pH, turbidity, total dissolved solids, calcium, magnesium, chloride, nitrate, and sulphate. Bacterial contamination assessment reveals that 76% of spring water samples (30 out of 39 samples) are contaminated with E.coli, raising public health concerns. Based on the chemical analysis of GW samples the study identified exceedances of WHO guidelines for calcium in two samples, magnesium in seven samples, sulphate in ten samples, and nitrate levels were below the WHO guideline across all samples. These results highlight localized chemical contamination issues that require targeted remediation efforts to safeguard water quality for public health.

Review of IoT Systems for Air Quality Measurements Based on LTE/4G and LoRa Communications

The issue of air pollution has recently come to light due to rapid urbanization and population growth globally. Due to its impact on human health, such as causing lung and heart diseases, air quality monitoring is one of the main concerns. Improved air pollution forecasting techniques and systems are needed to minimize the human health impact. Systems that fall under the Internet of Things (IoT) topology have been developed to assess and track numerous air quality metrics. This paper presents a review of IoT systems for air quality measurements, where the emphasis is placed on systems with LTE/4G and LoRa communication capabilities. Firstly, an overview of the IoT monitoring system is provided with recent technologies in the market. A critical review is provided of IoT systems regarding air quality using LTE/4G and LoRa communications systems. Lastly, this paper presents a market analysis of commercial IoT devices in terms of the costs, availability of the device, particulate matter each device can measure, etc. A comparative study of these devices is also presented on LTE/4G and possibly LoRa communications systems.

Future Site Suitability for Urban Waste Management in English Bazar and Old Malda Municipalities, West Bengal: A Geospatial and Machine Learning Approach

The rapid urbanization occurring globally has significantly intensified the challenges of waste management in densely populated metropolitan areas. A growing amount of waste has become a major concern for municipal authorities and local governments due to the limited availability of suitable land. Geospatial techniques, such as Geographic Information Systems (GISs) and remote sensing, combined with machine learning, play a crucial role in identifying suitable sites for urban waste management. These techniques assist planners in making well-informed decisions that strike a balance between environmental preservation and urban expansion by examining spatial data on land use, population density, and environmental concerns. Geospatial tools provide a data-driven basis for policy and urban planning, ensuring effective land use, reducing ecological hazards, and promoting sustainable urban growth for municipalities such as English Bazar and Old Malda. It can also pose serious threats to the environment, public health, and communities. Focusing on the English Bazar and Old Malda Municipalities in India, this paper examines the use of geospatial technologies to identify suitable sites for waste disposal. The research aims to address the complex processes of waste generation, collection, and disposal in urban environments. Using GIS and a Multi-Criteria Decision Analysis (MCDA) approach, the study employs the Analytic Hierarchy Process (AHP) alongside the Random Forest (RF) model and a machine learning (ML) technique to identify potential waste disposal sites within the English Bazar and Old Malda Municipalities in the Malda district. Eight key criteria were considered in the site selection process: land elevation; distances from surface water, roads, railways, and urban areas; groundwater depth; land use and land cover; and distance from sensitive and restricted areas. AHP analysis showed that 8%, 26%, and 27% of the sites were categorized as very highly suitable, moderately suitable, and unsuitable, respectively. Meanwhile, 38%, 17%, and 13% of the areas were classified as unsuitable, moderately suitable, and very highly suitable according to the RF model. The overall accuracy and Kappa coefficient indicated that the AHP method (overall capacity of 83.83% and Kappa coefficient of 0.7894) was slightly better than the RF model (overall capacity of 80.61% and Kappa coefficient of 0.7474) for site suitability analysis. This research underscores the broad relevance of geospatial technology in creating resilient and environmentally sustainable cities while offering valuable guidance on effectively allocating waste disposal sites. The findings provide crucial insights for urban planners and decision-makers, facilitating the identification of optimal locations for sustainable waste management in urban settings.

Healthcare waste management and antimicrobial resistance: a critical review

ABSTRACT The rapid growth of populations and urbanization has led to a significant increase in healthcare waste, posing serious health risks. A search on Google Scholar identified seven relevant articles from Ethiopia that examine the relationship between improper waste management in healthcare facilities (HCFs) and the rise of antimicrobial resistance (AMR) genes. This review aims to highlight key concepts, evidence sources, and knowledge gaps specific to the Ethiopian context. The unsafe disposal of antibiotics through leaks and solid waste has contributed to what some are calling a ‘silent pandemic,’ raising concerns about emerging infectious diseases. Studies have revealed alarming rates of infectious agents and AMR in healthcare wastewater. Isolates of C. jejuni, Escherichia coli, Enterococcus faecalis, and Enterococcus faecium from various healthcare waste sites in Ethiopia demonstrate high levels of AMR genes. Additionally, research indicates that HCFs produce significant amounts of waste, with high per-person daily waste production rates. Leachate from landfills containing this waste can negatively affect soil health, biological activity, water quality, agriculture, animal health, and human well-being. To mitigate these risks, effective waste management practices and the promotion of alternative antimicrobial use are essential strategies for reducing the emergence of pandemic diseases in developing countries.