Purpose: This study aims to numerically study the forced convection effects on a two-dimensional microchannel filled with a porous material containing the water/FMWCNT nanofluid. The upper and lower microchannel walls were fully insulated thermally along 15 per cent of their lengths at each end of the microchannel, with the in-between length being exposed to a constant temperature. The slip velocity boundary condition was applied along the microchannel walls. Design/methodology/approach: The Navier–Stokes equations were discretized before being solved numerically via a FORTRAN computer code. The following ranges were considered for the studied parameters: slip factor (B) equal to 0.001, 0.01 and 0.1; Reynolds number (Re) between 10 and 100; solid nanoparticle mass fraction (ϕ) between 0.0012 and 0.0025; Darcy number (Da) between 0.001 and 0.1; and porosity factor (ε) between 0.4 and 0.9. Findings: Increasing the Da caused a greater increase in the velocity profile than increasing Re, whereas increasing porosity did not affect the velocity profile growth at all. Originality/value: This paper is the continuation of the authors’ previous studies. Using the water/FMWCNT nanofluid as the working fluid in microchannels is among the achievements of this study.

The transportation sector contributes significantly to global greenhouse gas emissions, so it is crucial to assess and measure the sustainability of transportation systems. In this context, this study was conducted to develop an integrated index through the use of the multi‐criteria decision analysis method. The method combines existing discrete indexes into one comprehensive evaluation of public transportation, resulting in the sustainable transport planning index (STPI). In the STPI model, sustainability of transportation systems is assessed based on social, economic, and environmental factors that support the implementation of zero emission busses. The weight of each indicator is determined through the analytical hierarchy process, where expert judgment is used to assess the relative importance of each indicator. Normalization of indicators is performed to ensure comparability and consistency. The final STPI index is calculated as the weighted average of the normalized indicators. The STPI model reduces bias in the decision‐making process by considering multiple aspects and utilizing a structured approach to transport planning. The results of this method can provide valuable insights for decision‐makers, public transport agencies, government ministries, the private sector, and other stakeholders. As case study model, the STPI model was applied to the public transport system of the United Kingdom from 2007 to 2019, however; the methodology and lessons learned are applicable to all countries that are in the process of assembling data sets to weigh trade‐offs and inclusions in relation to sustainable transit such as accessibility and health impacts.