Changes in wet bulb globe temperature and risk to heat-related hazards in Bangladesh.

The rise in temperatures and changes in other meteorological variables have exposed millions of people to health risks in Bangladesh, a densely populated, hot, and humid country. To better assess the threats climate change poses to human health, the wet bulb globe temperature (WBGT) is an important indicator of human heat stress. This study utilized high-resolution reanalysis data from the fifth-generation European Centre for Medium-Range Weather Forecasts (ECMWF ERA5) to analyze the spatiotemporal changes in outdoor WBGT across Bangladesh from 1979 to 2021, employing Liljegren's model. The study revealed an increase in the annual average WBGT by 0.08-0.5 °C per decade throughout the country, with a more pronounced rise in the southeast and northeast regions. Additionally, the number of days with WBGT levels associated with high and extreme risks of heat-related illnesses has shown an upward trend. Specifically, during the monsoon period (June to September), there has been an increase of 2-4 days per decade, and during the pre-monsoon period (March to May), an increase of 1-3 days per decade from 1979 to 2021. Furthermore, the results indicated that the escalation in WBGT has led to a five-fold increase in affected areas and a three-fold increase in days of high and extreme heat stress during the monsoon season in recent years compared to the earlier period. Trend and relative importance analyses of various meteorological variables demonstrated that air temperature is the primary driver behind Bangladesh's rising WBGT and related health risks, followed by specific humidity, wind speed, and solar radiation.

Impact of climate change on dengue incidence in Singapore: time-series seasonal analysis.

This study aimed to identify the meteorological factors that contribute to dengue epidemics. The monthly incidence of dengue was used as the outcome variable, while maximum temperature, humidity, precipitation, and sunshine hours were used as independent variables. The results showed a consistent increase in monthly dengue cases from 2013 to 2021, with seasonal patterns observed in stationary time-series data. The ARIMA (2, 1, 3) × seasonal (0, 1, 2)12 model was used based on its lowest Akaike Information Criterion (AIC) values. The analysis revealed that a 1-unit increase in rainfall was positively correlated with a small 0.062-unit increase in dengue cases, whereas a 1-unit increase in humidity was negatively associated, leading to a substantial reduction of approximately 16.34 cases. This study highlights the importance of incorporating weather data into national dengue prevention programs to enhance public awareness and to promote recommended safety measures.

Nutrient and heavy metal dynamics in the coastal waters of St. Martin's island in the Bay of Bengal.

Seasonal variation observations were conducted in the coastal waters of St. Martin's Island in the Bay of Bengal to examine the influence of physical processes and the distribution pattern of nutrients in the ocean water. Pollution evaluation indices, health index and statistical techniques were incorporated to assess the heavy metal contamination. Two seasons, cool dry winter and pre-monsoon hot, were considered for sampling from 12 stations around the island. The Cool dry winter season has higher nutrient concentrations than the Pre-monsoon Hot season. The concentration of nutrients appeared as follows: Silicate > Nitrate > Ammonia > Phosphate > Nitrite. PCA and Pearson's Correlation showed that fresh water from nearby rivers, deep water upwelling, and, in some situations, modest anthropogenic sources are crucial. Hence, low DO and phosphate levels during the pre-monsoon hot season indicate there is a planktonic process like photosynthesis prevailing. The island's north-western and south-eastern regions have higher nutrient concentrations, which may be seasonal and due to wind action. Pb, Cu, As, Cr, Cd, and Zn were also considered to comprehend the island's geo-chemical perspectives and ecological and human health risks. The Pre-monsoon Heavy Metal Pollution Index (HPI) and Heavy Metal Evaluation Index (HEI) demonstrated that some places are much higher than the threshold limit, even though no significantly higher value was detected in the cool winter season. The Nemerow Index, the Total Ecological Risk Index (TERI), indicated that heavy metal contamination was severe to moderate and low to moderate. Finally, Pearson's correlation showed the association between physical and chemical characteristics, similar to PCA and Pearson's correlation for nutrients and heavy metals. Thus, this research may help shed light on the state of the seas around St. Martin's Island. This study may also provide explicit insights for the authority to take the necessary measures to preserve marine ecology and the associated terrestrial ecosystem.

Simplified engineering geomorphic unit-based seismic site characterization of the detailed area plan of Dhaka city, Bangladesh.

Severe failure of improperly designed and poorly constructed structures may occur due to the amplified and prolonged ground motion during an earthquake, and hence prediction of the ground motion characteristics at the soil surface is crucial. In this study, based on the prepared simplified engineering geomorphic map, we performed a one-dimensional (1D) nonlinear site response analysis for seismic site characterization of the recently proposed Detailed Area Plan (DAP) area of Dhaka City, the Capital of Bangladesh. The engineering geomorphic unit-based map was prepared from image analysis and verified with the collected borehole data and surface geology map. The study area was classified into three major geomorphic units and seven sub-units subject to the subsurface soil profiles. Nine earthquake time histories, seven from the PEER NGA WEST2 data set and two synthetics, and seven identified subsurface soil profiles were used for nonlinear site response analysis, along with the BNBC 2020 uniform hazard spectrum as the target spectrum. For the selected earthquake ground motions, the near-surface soil response of the DAP area showed de-amplification of acceleration in the short period and amplification of acceleration in the long period. The amplified long-period acceleration could cause severe damage in inappropriately designed and poorly constructed long-period structures. The outcome of this study could be used to prepare a seismic risk-sensitive land use plan for the future development of the DAP of Dhaka City.

Relationship between Urban Environmental Components and Dengue Prevalence in Dhaka City-An Approach of Spatial Analysis of Satellite Remote Sensing, Hydro-Climatic, and Census Dengue Data.

Dengue fever is a tropical viral disease mostly spread by the Aedes aegypti mosquito across the globe. Each year, millions of people have dengue fever, and many die as a result. Since 2002, the severity of dengue in Bangladesh has increased, and in 2019, it reached its worst level ever. This research used satellite imagery to determine the spatial relationship between urban environmental components (UEC) and dengue incidence in Dhaka in 2019. Land surface temperature (LST), urban heat-island (UHI), land-use-land-cover (LULC), population census, and dengue patient data were evaluated. On the other hand, the temporal association between dengue and 2019 UEC data for Dhaka city, such as precipitation, relative humidity, and temperature, were explored. The calculation indicates that the LST in the research region varies between 21.59 and 33.33 degrees Celsius. Multiple UHIs are present within the city, with LST values ranging from 27 to 32 degrees Celsius. In 2019, these UHIs had a higher incidence of dengue. NDVI values between 0.18 and 1 indicate the presence of vegetation and plants, and the NDWI identifies waterbodies with values between 0 and 1. About 2.51%, 2.66%, 12.81%, and 82% of the city is comprised of water, bare ground, vegetation, and settlement, respectively. The kernel density estimate of dengue data reveals that the majority of dengue cases were concentrated in the city's north edge, south, north-west, and center. The dengue risk map was created by combining all of these spatial outputs (LST, UHI, LULC, population density, and dengue data) and revealed that UHIs of Dhaka are places with high ground temperature and lesser vegetation, waterbodies, and dense urban characteristics, with the highest incidence of dengue. The average yearly temperature in 2019 was 25.26 degrees Celsius. May was the warmest month, with an average monthly temperature of 28.83 degrees Celsius. The monsoon and post-monsoon seasons (middle of March to middle of September) of 2019 sustained higher ambient temperatures (>26 °C), greater relative humidity (>80%), and at least 150 mm of precipitation. The study reveals that dengue transmits faster under climatological circumstances characterized by higher temperatures, relative humidity, and precipitation.

Drought dynamics of Northwestern Teesta Floodplain of Bangladesh: a remote sensing approach to ascertain the cause and effect.

Drought is an affliction for a region that primarily depends on agriculture as economic activity. Commonly monitoring and characterizing of drought is performed by only analyzing the meteorological aspect, assuming precipitation as the primary source of water. However, in riverine Bangladesh, this can lead to an erroneous conclusion, as there is a multitude of available water sources. Consequently, in this study, vegetation condition (Standard Vegetation Index), soil moisture (Soil Moisture Index), and precipitation (Standard Precipitation Index) are separately investigated from 2003 to 2019, in the Northwestern Teesta floodplain. Subsequently, statistical regression analysis is performed to determine the relationships between different aspects of drought. In addition, information obtained from field visits and expert opinions has also been assimilated. Analysis of vegetation and soil moisture condition presents a progressively improving scenario. However, SPI shows an incessant decline in meteorological drought conditions, especially after 2007. Evidently, regression analysis does not provide any indication of an interrelationship between the studied agricultural and meteorological parameters. Presumably, this absence is instigated because the study area is highly irrigated as the groundwater table is suitably near the surface and the existence of nearby Teesta river allows for the utilization of surface water. Moreover, the cropping pattern is shifting toward crops that require much less water and to places where soil moisture is scarce. Thus, this study addresses the gap in knowledge regarding the nature of agricultural drought and the dynamics of different aspects of drought which will be invaluable for the water management and agricultural policy in the study area as well as other regions with a similar backdrop.