In this work, stable water-based zinc oxide (ZnO), titania (TiO2), and multi-walled carbon nanotube (MWCNT) nanofluids are prepared and examined as CO2 absorbents in a polypropylene hollow fiber membrane contactor. Different operating variables, such as liquid flow rate, gas flow rate, and concentration of nanoparticles, and their effects on CO2 molar flux are investigated. The long-term stability of nanofluids is monitored using ultraviolet–visible spectroscopy. Also, ζ-potential measurements and sediment photography are applied to confirm the results of nanofluid stability. Dynamic light scattering is used to determine the size distribution of dispersed nanoparticles. The results show that the increase in the nanoparticle concentration to 0.15 wt % has a favorable effect on CO2 absorption efficiency as a result of the increase in Brownian motion and other related mechanisms. However, it adversely affects the CO2 absorption by lowering the nanofluid stability at higher concentrations. The obtained results reveal that ZnO nanofluid is the most effective nanofluid in all experimental conditions. At low liquid flow rates of about 10 mL/min, ZnO nanofluid could augment CO2 absorption efficiency by 130%, while both TiO2 and MWCNT nanofluids could enhance it by 60% with respect to distilled water. Possible mechanisms regarding mass transfer augmentation are also discussed.

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To increase the amount of bicycling as a mode of transport, many countries are developing placed based bicycling plans and strategies. However, this approach necessitates considering a fine-scale mapping of bicycling patterns and a detailed description of urban spaces. The rise of new data and technologies offers much promise to planners and researchers to access diverse and richer sources of information to optimise the bicycling network design. This review aims to comprehensively examine the role of data and technology in bicycling planning, historical changes in using data-driven approaches, and current domains in the existing body of research in bicycling planning from 1990 to 2021. For this, a systematic literature review has been conducted according to PRISMA framework. A total number of 1022 studies was analysed and synthesised with the VOS Viewer and CiteSpace platforms. Upon completing the review, we extracted the most-used datasets, tools, and methodologies. The results of the systematic review reveal three evolutionary phases in using data-driven approaches from 1990 to 1999, 2000 to 2009, and 2010 to 2021. In addition, we identified six knowledge domains in using data-driven approaches in bicycling planning that is (i) smart city, (ii) infrastructure, (iii) built environment, (iv) decision making, (v) people, and (vi) safety.

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