Adopted Community Strategies to Offset Utility Crises in a Middle Income Locality of Dhaka, Bangladesh

Because of the spontaneous growth of Dhaka city, the utility crisis is increasing day by day. Therefore problems in utilities are considered centrally with respect to the economy and environment of Dhaka. But the local aspects are totally different from the central viewpoint. In this paper, two most prominent utility crises in Dhaka (i.e. the supply of gas and water) have been explored with their impacts and people’s coping mechanism with these problems has been documented.  The local people have been found adopting various alternative measures, even compromising their daily life cycle to make an adjustment with these problems. Keywords: Dhaka, utility service, gas, water, coping, daily routine

Enhancement of Solar PV Hosting Capacity in a Remote Industrial Microgrid: A Methodical Techno-Economic Approach

To meet the zero-carbon electricity generation target as part of the sustainable development goals (SDG7), remote industrial microgrids worldwide are considering the uptake of more and more renewable energy resources, especially solar PV systems. Estimating the grid PV hosting capacity plays an essential role in designing and planning such microgrids. PV hosting capacity assessment determines the maximum PV capacity suitable for the grid and the appropriate electrical location for PV placement. This research reveals that conventional static criteria to assess the PV hosting capacity fail to ensure the grid’s operational robustness. It hence demands a reduction in the theoretical hosting capacity estimation to ensure grid compatible post-fault voltage and frequency recovery. Energy storage technologies, particularly fast-responsive batteries, can potentially prevent such undesirable scenarios; nevertheless, careful integration is required to ensure an affordable cost of energy. This study proposes a novel methodical techno-economic approach for an off-grid remote industrial microgrid to enhance the PV hosting capacity by integrating battery energy storage considering grid disturbance and recovery scenarios. The method has been validated in an industrial microgrid with a 2.6 MW peak demand in a ready-made garment (RMG) factory having a distinctive demand pattern and unique constraints in remote Bangladesh. According to the analysis, integrating 2.5 MW of PV capacity and a 1.2 MVA battery bank to offset existing diesel and grid consumption would result in an energy cost of BDT 14.60 per kWh (USD 0.1719 per kWh). For high PV penetration scenarios, the application of this method offers higher system robustness, and the financial analysis indicates that the industries would not only benefit from positive environmental impact but also make an economic profit

Factors Associated with Travel Behavior of Millennials and Older Adults: A Scoping Review

This study aims to synthesize knowledge on the travel behavior of millennials and older adults based on literature from 2010 to 2018. The study looks into the different factors that contributed to shaping each generation’s travel behavior. Both qualitative and quantitative studies that fall within the selection criteria are reviewed, with a total of seventy-eight studies selected for review. Thirty-four papers focused on young adults/millennials, 35 included an older adult population, and 9 investigated both younger and older age groups. Six of the studies utilized qualitative methods, 68 applied quantitative methods, and 4 used mixed methods to explore the factors associated with travel behavior. Travel behaviors are explored in terms of mode choice, trip distance, trip frequency, use of alternative transport, ridesharing, and mobility tool ownership. Associated factors are categorized into five themes: personal attributes, geography and built environment, living arrangements and family life, technology adoption, and perceptions and attitudes towards travel options and environment. This study concludes that difference exists between generations in terms of travel behavior, and that the factors that influence each generation’s travel characteristics are either different or differ in their nature of influence (increase/decrease). Finally, based on the reviewed literature, this study proposes future research directions

Investigation of the use of smartphone applications for trip planning and travel outcomes

This paper explores the use of smartphone applications for trip planning and travel outcomes using data derived from a survey conducted in Halifax, Nova Scotia, in 2015. The study provides empirical evidence of relationships of smartphone use for trip planning (e.g. departure time, destination, mode choice, coordinating trips and performing tasks online) and resulting travel outcomes (e.g. vehicle kilometers traveled, social gathering, new place visits, and group trips) and associated factors. Several sets of factors such as socio-economic characteristics and travel characteristics are tested and interpreted. Results suggest that smartphone applications mostly influence younger individuals’ trip planning decisions. Transit pass owners are the frequent users of smartphone applications for trip planning. Findings suggest that transit pass owners commonly use smartphone applications for deciding departure times and mode choices. The study also identifies the limited impact of smartphone application use on reducing travel outcomes, such as vehicle kilometers traveled. The highest impact is in visiting new places (a 48.8% increase). The study essentially offers an original in-depth understanding of how smartphone applications are affecting everyday travel

Exploring Pedestrian Injury Severity by Incorporating Spatial Information in Machine Learning

Using the random forest classification technique, this study explored the role of different factors such as demography, pedestrian and drivers' conditions, collision characteristics, road characteristics, and weather in predicting pedestrian injury severity from automobile-related collisions in Toronto. Spatial information was incorporated in the models to capture spatial autocorrelation. The results revealed the importance of spatial information in predicting pedestrian injury severity. Other important predictors of pedestrian injury severity include aggressive driving, driver's conditions (e.g., inattentive, slowly stopping, driving properly, failing to yield right of way), pedestrian conditions (e.g., normal, inattentive) and dark lighting conditions

Analysis of millennials and older adults’ automobility behavior in Hamilton, Ontario

ABSTRACTThis study explores the automobility behavior of millennials (those born between 1980 and 2000) and older adults (65 years and older) and the factors that influence their automobility behavior using cross-sectional data from Hamilton, Ontario. This study focuses specifically on how automobility behavior of millennials and older adults is shaped by their socio-demographic characteristics, living arrangements, attitudes, and preferences toward transportation modes and residential location characteristics. Results from the binomial and ordinal logistic regressions suggest that depending on whether a millennial or older adult lives alone, with a partner, or in an apartment, their automobility behavior differs. The study also finds that positive attitudes and preferences toward sustainable travel behavior make both generations less auto-oriented, especially millennials. Regarding preferred residential location characteristics, compared to older adults, millennials’ preference toward off-street parking in their residential neighborhood is likely to influence their automobile use. Compared to older adults, living arrangements, attitudes, and preferences influence, to a greater extent, millennials’ attributes of automobility. Further, the study also suggests that living arrangements, attitudes, and preferences can differ among millennials and older adults. Consequently, the impact on each of the attributes of automobility behavior will differ

Impacts of the COVID-19 Pandemic on Active Travel Mode Choice in Bangladesh: A Study from the Perspective of Sustainability and New Normal Situation

The COVID-19 pandemic has caused incredible impacts on people’s travel behavior. Recent studies suggest that while the demand for public transport has decreased due to passengers’ inability to maintain physical distance inside this mode, the demand for private automobile and active transport modes (walking and cycling) has increased during the pandemic. Policymakers should take this opportunity given by the pandemic and encourage people to use active transport more in the new normal situation to achieve sustainable transportation outcomes. This study explores the expected change in active transport mode usage in the new normal situation in Bangladesh based on the data from a questionnaire survey. The study finds that 56% and 45% of the respondents were expected to increase travel by walking and cycling, respectively, during the new normal situation. On the other hand, 19% of the respondents were expected to do the opposite. The study further identifies the factors influencing the expected change in travel by active transport modes during the new normal situation by developing multinomial logistic regression models. Finally, this study proposes policies to increase active transport use beyond the pandemic and ensure sustainable mobility for city dwellers and their well-being

Exploring the Choice of Bicycling and Walking in Rajshahi, Bangladesh: An Application of Integrated Choice and Latent Variable (ICLV) Models

Bangladesh has emphasized active transportation in its transportation policies and has encouraged its population, especially the youth and students, towards bicycling. However, there is a scarcity of studies that have examined the factors important to the choice of active transportation that can be referenced to support the initiative. To address this research gap, in this study, we explore the influence of sociodemographics and latent perceptions of a built environment on the choice to walk and bicycle among students and nonstudents in Rajshahi, Bangladesh. In Rajshahi, we conducted a household survey between July and August, 2017. We used a modeling framework that integrated choice and latent variable (ICLV) models to effectively incorporate the latent perception variables in the choice model, addressing measurement error and endogeneity bias. Our models show that students are influenced by perceptions of safety from crime, while nonstudents are influenced by their perceptions of the walkability of a built environment when choosing a bicycle for commuting trips. For recreational bicycle trips, students are more concerned about the perceptions of road safety, whereas nonstudents are concerned about safety from crime. We find that road safety perception significantly and positively influences walking behavior among nonstudents. Structural equation models of the latent perception variables show that females are more likely to provide lower perceptions of neighborhood walkability, road safety, and safety from crime. Regarding active transportation decisions, overall, we find there is a difference between student and nonstudent groups and also within these groups. The findings of this study can assist in developing a sustainable active transportation system by addressing the needs of different segments of the population. In this study, we also provide recommendations regarding promoting active transportation in Rajshahi