Climate change adaptation planning for Global South megacities: the case of Dhaka

Megacities in low- and middle-income countries face unique threats from climate change as vulnerable populations and infrastructure are concentrated in high-risk areas. This paper develops a theoretical framework to characterize adaptation readiness in Global South cities and applies the framework to Dhaka, Bangladesh, a city with acute exposure and projected impacts from flooding and extreme heat. To gather case evidence from Dhaka we draw upon interviews with national and municipal government officials and a review of planning documents and peer-reviewed literature. We find: (1) national-level plans propose a number of adaptation strategies, but urban concerns compete with priorities such as protection of coastal assets and agricultural production; (2) municipal plans focus on identifying vulnerability and impacts rather than adaptation strategies; (3) interviewees suggest that lack of coordination among local government (LG) organizations and lack of transparency act as barriers for municipal adaptation planning, with national plans driving policy where LGs have limited human and financial resources; and (4) we found limited evidence that national urban adaptation directives trickle down to municipal government. The framework developed offers a systematic and standardized means to assess and monitor the status of adaptation planning in Global South cities, and identify adaptation constraints and opportunities.     

Statistical inference using the g or K point pattern spatial statistics

Spatial point pattern analysis provides a statistical method to compare an observed spatial pattern against a hypothesized spatial process model. The G statistic, which considers the distribution of nearest neighbor distances, and the K statistic, which evaluates the distribution of all neighbor distances, are commonly used in such analyses. One method of employing these statistics involves building a simulation envelope from the result of many simulated patterns of the hypothesized model. Specifically, a simulation envelope is created by calculating, at every distance, the minimum and maximum results computed across the simulated patterns. A statistical test is performed by evaluating where the results from an observed pattern fall with respect to the simulation envelope. However, this method, which differs from P. Diggle's suggested approach, is invalid for inference because it violates the assumptions of Monte Carlo methods and results in incorrect type I error rate performance. Similarly, using the simulation envelope to estimate the range of distances over which an observed pattern deviates from the hypothesized model is also suspect. The technical details of why the simulation envelope provides incorrect type I error rate performance are described. A valid test is then proposed, and details about how the number of simulated patterns impacts the statistical significance are explained. Finally, an example of using the proposed test within an exploratory data analysis framework is provided.     

Fungal inoculum properties: extracellular enzyme expression and pentachlorophenol removal in highly contaminated field soils

This study was conducted to improve the pentachlorophenol (PCP) bioremediation ability of white-rot fungi in highly contaminated field soils by manipulating bioaugmentation variables. These were the dry weight percentage of fungal inoculum addition (31-175 g kg(-1)), PCP concentration (100-2137 mg kg(-1) PCP), fungal inoculum formulation, and time (1-7 wk). Five fungal isolates were used: the New Zealand isolates Trametes versicolor (L.: Fr.) HR131 and Trametes sp. HR577; the North American isolates Phanerochaete chrysosporium Burds. (two isolates) and Phanerochaete sordida (Karst.) Erikss. & Ryv. Pentachlorophenol removal, manganese peroxidase, and laccase activity, and the formation of chloroanisoles in the contaminated field soils were measured. The majority of PCP removed by the Trametes isolates was in the first week after bioaugmentation. The maximum PCP removal by the fungi varied from 50 to 65% from a 1065 mg kg(-1) PCP contaminated field soil. Pentachlorophenol was preferentially converted to pentachloroanisole (PCA) by the Phanerochaete isolates (>60%), while 2 to 9% of the PCP removed by two Trametes isolates was converted to PCA. A pH increase was measured following bioaugmentation that was dependent on PCP concentration, fungal inoculum addition, and formulation. This, together with rapid initial PCP removal, possibly changed the bioavailability of the remaining PCP to the fungi and significantly decreased the sequestering of PCP in the contaminated field soils. The research supports the conclusion that New Zealand Trametes spp. can rapidly remove PCP in contaminated field soils. Bioavailability and extractability of PCP in the contaminated field soil may significantly increase after bioaugmentation.     

Analysis of polychlorobiphenyls from used transformers for polychlorodibenzofurans

The results of analyses for polychlorodibenzofuran (PCDF) content in two samples of polychlorobiphenyl (PCB) from used electrical transformers are presented and discussed. In neither sample was there evidence for enhanced PCDF concentrations even though one of them had been subjected to overheating while in service.     

Polychlorodibenzo-p-dioxins and dibenzofurans in technical pentachlorophenol - results of a collaborative analytical exercise

Results of analyses of eight samples of technical pentachlorophenol conducted by three different analytical methods are presented and discussed.     

STRATIFICATION VARIABILITY IN THREE MORPHOMETRICALLY DIFFERENT LAKES UNDER IDENTICAL METEOROLOGICAL FORCING1

ABSTRACT: Synoptic water temperature measurements were taken in three temperate lakes located within 25 km of one another to study the effects of morphometry (and changes in weather) on seasonal and short-term thermal stratification characteristics. Two of the lakes had nearly the same surface areas and two had nearly identical mean depths; all were exposed to identical weather conditions. The dominance of weather over morphometry on the water surface temperature response was illustrated by the synoptic measurements in two different years. Stratification structure was also found to be dominated by weather for sufficiently deep lakes. Surface area effects were most subtle but explainable as sheltering effects. The onset of stratification was not, as traditionally described, a simple, gradual response of a lake to the annual solar radiation cycle. Rather it depends on a series of alternating heating, cooling, and mixing cycles similar to annual and diel cycles but with a period of approximately five days. These were in direct response to the passage of major weather systems and displayed no apparent time lag. No comparable synoptic water temperature data set could be found in the literature.     

The 4Cs of adaptation tracking: consistency,comparability, comprehensiveness,coherency

Adaptation tracking seeks to characterize, monitor, and compare general trends in climate change adaptation over time and across nations. Recognized as essential for evaluating adaptation progress, there have been few attempts to develop systematic approaches for tracking adaptation. This is reflected in polarized opinions, contradictory findings, and lack of understanding on the state of adaptation globally. In this paper, we outline key methodological considerations necessary for adaptation tracking research to produce systematic, rigorous, comparable, and usable insights that can capture the current state of adaptation globally, provide the basis for characterizing and evaluating adaptations taking place, facilitate examination of what conditions explain differences in adaptation action across jurisdictions, and can underpin the monitoring of change in adaptation over time. Specifically, we argue that approaches to adaptation tracking need to (i) utilize a consistent and operational conceptualization of adaptation, (ii) focus on comparable units of analysis, (iii) use and develop comprehensive datasets on adaptation action, and (iv) be coherent with our understanding of what constitutes real adaptation. Collectively, these form the 4Cs of adaptation tracking (consistency, comparability, comprehensiveness, and coherency).     

Vulnerability to the health effects of climate variability in rural southwestern Uganda

Vulnerability to the health impacts of climate change will be shaped by the existing burden of ill- health and is expected to be highest in poor and socio-economically marginalized populations. Sub-Saharan Africa, in particular, is considered a highly vulnerable region. This paper analyses the vulnerability and adaptive capacity of rural Bakiga communities in southwestern Uganda to climate-sensitive health risks. The objectives were threefold: i) identify key climate-sensitive, community-identified health priorities; ii) describe and characterize determinants of sensitivity to these health priorities at the individual, community and regional levels; and iii) assess the adaptive capacity of Bakiga. Data collection employed a combination of individual and key informant interviews, biographies, future storylines, and Photovoice. Three key health risks were identified by the study communities (malaria, food insecurity, and gastrointestinal illnesses) – all affected by local climatic and environmental conditions, livelihoods, land use changes, and socio-economic conditions. Adaptation within these communities is dependent on their capacity to reduce sensitivities to identified health challenges among the potential of increasing exposures. Crop diversification, reducing deforestation, expanding of livestock rearing, transfer of traditional knowledge, and access to affordable health services are among potential strategies identified. We demonstrate significant existing vulnerabilities to present day climate-related health risks and highlight the importance of non-climatic processes and local conditions in creating sensitivity to health risks. Our place-based understanding is useful to inform interventions or policies aimed to reduce exposure and sensitivity and support adaptive capacity as the conditions these communities face are consistent with many other sub-Saharan African countries.