Assessing the impacts of climate change in cities and their adaptive capacity: Towards transformative approaches to climate change adaptation and poverty reduction in urban areas in a set of developing countries

Many cities across the world are facing many problems climate change poses to their populations, communities and infrastructure. These vary from increased exposures to floods, to discomfort due to urban heat, depending on their geographical locations and settings. However, even though some cities have a greater ability to cope with climate change challenges, many struggle to do so, particularly in cities in developing countries. In addition, there is a shortage of international studies which examine the links between climate change adaptation and cities, and which at the same time draw some successful examples of good practice, which may assist future efforts. This paper is an attempt to address this information need. The aim of this paper is to analyse the extent to which cities in a sample of developing countries are attempting to pursue climate change adaptation and the problems which hinder this process. Its goal is to showcase examples of initiatives and good practice in transformative adaptation, which may be replicable elsewhere. To this purpose, the paper describes some trends related to climate change in a set of cities in developing countries across different continents, including one of the smallest capital cities (Georgetown, Guyana) and Shanghai, one the world's most populous cities. In particular, it analyses their degree of vulnerability, how they manage to cope with climate change impacts, and the policies being implemented to aid adaptation. It also suggests the use of transformative approaches which may be adopted, in order to assist them in their efforts towards investments in low-carbon and climate-resilient infrastructure, thereby maximizing investments in urban areas and trying to address their related poverty issues. This paper addresses a gap in the international literature on the problems many cities in developing countries face, in trying to adapt to a changing climate.

Environmental benefits of blue ecosystem services and residents' willingness to pay in Khulna city, Bangladesh

Nature-based solutions for urban problems gaining popularity globally. The well-functioning ecosystem could offer a nature-based solution to many urban problems including water, drainage and flooding problems. Therefore, conservation and restoration of urban blue ecosystem components such as pond scape are crucial. This research taking Khulna city of Bangladesh as a case has examined the low-income fringe community's willingness to pay (WTP) for conservation and restoration of pond scape/blue ecosystem service (BES) in their locality from where they benefit. The various types of ecosystem services enjoyed by the local community were identified. To assess the community's WTP for conservation and restoration of pond scape, the payment card approach of the Contingent Valuation Method (CVM) was used. Three environmental attributes were considered to assess the existing condition of the blue ecosystem services in the study area. Findings show that 54% of respondents are not satisfied with the existing conditions of the ecosystem services resulting from the pond scape. Respondent's WTP for eleven types of service facilities was calculated. Results show that only 65.20% are eager to pay an amount of 38 Tk to 138 Tk per month for different service facilities. It means about one-third of the community people want to be free riders. The influences of different attributes of the respondents on their WTP were also analyzed. Education, income, and house-ownership appear to have a positive significant influence on WTP for conservation and restoration of pond scape in the study area. In line with the findings if policy measures are taken without further delay it would help conserve the remaining pond scape.

Navigating nature's toll: Assessing the ecological impact of the refugee crisis in Cox's Bazar, Bangladesh

The Rohingya crisis in Myanmar's Rakhine state has resulted in a significant influx of refugees into Cox's Bazar, Bangladesh. However, the ecological impact of this migration has received limited attention in research. This study aimed to address this gap by utilizing remote sensing data and machine learning techniques to model the ecological quality (EQ) of the region before and after the refugee influx. To quantify changes in land use and land cover (LULC), three supervised machine learning classification methods, namely artificial neural networks (ANN), support vector machines (SVM), and random forests (RF), were applied. The most accurate LULC maps obtained from these methods were then used to assess changes in ecosystem service valuation and function resulting from the land use changes. Furthermore, fuzzy logic models were employed to examine the EQ conditions before and after the Rohingya influx. The findings of the study indicate that the increased number of Rohingya refugees has led to a 9.58% decrease in forest area, accompanied by an 8.25% increase in settlement areas. The estimated total ecosystem services value (ESV) in the research area was $67.83 million in 2017 and $67.78 million in 2021, respectively. The ESV for forests experienced a significant decline of 21.97%, equivalent to a decrease of $5.33 million. Additionally, the reduction in forest lands has contributed to a 13.58% decline in raw materials and a 14.57% decline in biodiversity. Furthermore, utilizing a Markovian transition probability model, our analysis reveals that the EQ conditions in the area have deteriorated from "very good" or "good" to "bad" or "very bad" following the Rohingya influx. The findings of this study emphasize the importance of integrating ecological considerations into decision-making processes and developing proactive measures to mitigate the environmental impact of such large-scale migrations.

The urban air quality nexus: Assessing the interplay of land cover change and air pollution in emerging South Asian cities

Air quality degradation presents a significant public health challenge, particularly in rapidly urbanizing regions where changes in land use/land cover (LULC) can dramatically influence pollution levels. This study investigates the association between LULC changes and air pollution (AP) in the five fastest-growing cities of Bangladesh from 1998 to 2021. Leveraging satellite data from Landsat and Sentinel-5P, the analysis reveals a substantial increase in urban areas and sparse vegetation, with declines in dense vegetation and water bodies over this period. Urban expansion was most pronounced in Sylhet (22-254%), while Khulna experienced the largest increase in sparse vegetation (2-124%). Dense vegetation loss was highest in Dhaka (20-77%) and water bodies (9-59%) over this period. Concentrations of six major air pollutants (APTs) - aerosol index, CO, HCHO, NO2, O3, and SO2 - were quantified, showing alarmingly high levels in densely populated industrial and commercial zones. Pearson's correlation indicates strong positive associations between APTs and urban land indices (R > 0.8), while negative correlations exist with vegetation indices. Geographically weighted regression modeling identifies city centers with dense urban built-up as pollution hotspots, where APTs exhibited stronger impacts on land cover changes (R2 > 0.8) compared to other land classes. The highest daily emissions were observed for O3 (1031 tons) and CO (356 tons) at Chittagong in 2021. In contrast, areas with substantial green cover displayed weaker pollutant-land cover associations. These findings underscore how unplanned urbanization drives AP by replacing natural land cover with emission sources, providing crucial insights to guide sustainable urban planning strategies integrating pollution mitigation and environmental resilience.