Background: the aim of this study was to analyze the chronobiology influence on the mechanical, kinematic, and physiological variables in a mountain bike (MTB) time trial. Methods: 16 mountain bike (MTB) male athletes volunteered to participate. Their characteristics were as follows: body mass 70.2 ± 5.4 kg, stature 172.7 ± 4.0 cm, body fat 9.8 ± 3.5%, and VO2max 52.3 ± 3.9 mL/kg/min. Two 20 min MTB maximal protocols were applied, the first one in the morning and a second one in the afternoon period. Results: No differences were found for all the variables studied, except for the pedaling cadence (stroke rate), which showed higher values during the morning protocol (85.06 ± 7.58 vs. 82.63 ± 7.41 rpm; p = 0.044). Significant correlations between morning and afternoon physiological and mechanical variables were observed: heart rate (r = 0.871); external mechanical power—maximum (r = 0.845), mean (r = 0.938), and relative (r = 0.933), as well as in the cadence—stroke rate (r = 0.825). Conclusions: our results reveal a similar impact and significant relationship between morning and afternoon impact concerning the majority of the physiological and mechanical variables, which indicates that the period of the day does not influence the external and internal impact associated with the MTB time trial maximal protocol.

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The environmental impact of a product cannot be evaluated by only the energy required to run it and for consequence the CO2 emitted from its generation. For that reason, Life Cycle Assessments (LCA) are utilized to have an extensive understanding of the impact and have the ability to compare different products. This approach must be made also for passenger vehicle with different propulsion system in the Brazilian context as the urge for electrification of its fleet becomes more intense. This context is aligned with the 17 Sustainable Development Goals from ONU on the deceleration of global warming and the use of less energy, in this case in transportation. Thereby, in this study four tools were analyzed (GREET, GHGenius, BioGrace and VSB). The tool GREET showed a more complete capability for this comparison of CO2 emissions.