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Green Energy comes from environmental natural resources which are renewable. Green technology alludes that is earth unneighbourly, created, and utilized in a way with the goal that it does not irritate our condition and conserves natural resources. Its uses are getting a solution for widespread global warming fears and the increasing scarcity of many natural resources. Green energy and technology are interrelated to achieve a stable environment and sustainable development. This paper reviews the studies which are related to green energy and technology and shows the existing scenario, potentialities of using it in Bangladesh. Data identifying strategies are gathered from research papers, government documents, relevant green energy and technology policies, interviews with experts. There are some problems with the growing green energy and technology in the country. Therefore, based on problems, some strategic ideas are recommended in this paper.

Safety experts and transportation departments are focused on reducing road accidents and their societal and economic effects. The most crucial step in establishing a successful road safety practice is identifying dangerous highway zones through the study of crashes and looking at how the location of accidents relates to surrounding geography and other factors. Using the latest cutting-edge GIS analytical methods, this study aims to map the locations of accident hot spots and evaluate the severity and spatial extent of crash occurrences in Ohio. Road traffic crash (RTC) data has been analyzed using sophisticated GIS-based hot spot analysis for decades by safety researchers. Using four years' worth of crash data from the state of Ohio and spatial autocorrelation analysis, this study aims to show how a GIS technique can be used to find places where accidents are likely to happen (2017-2020). The study analyzed and ranked crash hotspot areas using the matching severity levels of RTCs. Cluster zones of high and low crash severity were discovered using the spatial autocorrelation tool and the Getis Ord Gi* statistics tool to evaluate the distribution of RTCs. The analysis used Getis Ord Gi*, the crash severity index, and Moran's I spatial autocorrelation of accident events. The findings indicated that these techniques were useful for identifying and rating crash hotspot locations. Since the sites of the identified accident hotspots are located in significant cities in the state of Ohio, such as Cleveland, Cincinnati, Toledo, and Columbus, the organizations in charge of traffic management should make it their top priority to minimize the negative socioeconomic impact that RTCs have and should also conduct a thorough investigation. This study's contribution is the incorporation of crash severity into hot spot analysis using GIS, which could lead to better-informed decision-making in the realm of highway safety.

As bike-share systems proliferate across the US, their potential as a way of expanding opportunities for those most underserved by the transportation system merits a deeper understanding of its current users. In this study, we examine the rate of bike-share adoption by individuals from different socio-demographic groups and living in different bicycling contexts. We explore how individuals incorporate bike-share service into their travel patterns for different travel purposes and change their use of other modes. Data are from a two-wave survey of bike-share users and a parallel household survey of residents in the Sacramento region. Our modeling results for bike-share adoption and use frequency show that low-income individuals are less likely to adopt bike-share but use the service more frequently than other income groups when they do adopt. Low-income users, people of color, and non-auto owners are more likely than other groups to use bike-share frequently for many trip purposes. Individuals living in areas with a stronger biking culture and surrounded by bike infrastructure are less likely to adopt the service and less likely to use it for purposes other than commuting. All users change their use of other modes when they incorporate bike-share into their travel patterns, but low-income individuals, people of color, and non-auto owners would be more severely impacted if the service were to stop. Our results add new insights into the use of bike-share, a service that can enhance social equity while also addressing sustainability.

The COVID-19 pandemic has had enormous effects on human life and the environment, particularly freshwater ecosystems, on a global scale. Despite its numerous effects, the pandemic has improved the quality of the environment, allowing devastated ecosystems to recover. During the COVID lockdown period, many researchers observed positive amendments in environmental quality in various parts of the world. Due to increased industrialization and urbanization over the past several decades, Dhaka's peripheral rivers have grown highly polluted. In this study, an attempt was made to illustrate the post-covid surface water quality scenario of Bangladesh's hihgly contaminated Turag River. Therefore, for the first time, a GIS-based spatial analysis of water quality index was used to endeavor to quantify 16 water quality parameters (pH, EC, temperature, turbidity, salinity, TDS, DO, Na+, K+ Ca2+, Mg2+ Cl-, Cu, Pb, Fe, and Cd) in the river Turag. Thus, it could serve as a reference work for future researches in Bangladesh. After calculating the WQI for the collected samples, it was determined that the water quality status at all sampling stations was extremely poor because each WQI was greater than 100. Using the Kriging method of interpolation, the encroaching WQS were predicted and visually represented using GIS maps. The findings of this study are particularly concerning, as all recorded WQS samples surpassed the standard limits. Based on these findings, we urged for the rapid deployment of proper water management practices and policies in order to safeguard and manage the water resources.