Design guidelines and control indicators for low-carbon highway service stations on the southern edge of the Qinghai-Tibet Plateau

• Physical & indoor environment study of high-altitude, low-oxygen highway stations. • Address data gaps on highway service station morphology in plateau cold climates. • Develop tailored simulation & evaluation methods for unique operations. • Provide theoretical support for station design in extreme climates worldwide. The climatic conditions along the southern edge of the Qinghai-Tibet Plateau are similar to those of most plateau cold regions in the world, which are mainly distributed in the famous plateaus in the middle and low latitudes of the world. The road infrastructure in these areas generally underdeveloped, and tourist service facilities are scarce. Therefore, optimizing the building shape parameters of highway service stations in high-altitude, cold regions is of great significance for reducing operational energy consumption and carbon emissions, as well as for improving the quality of transportation infrastructure. However, the influence of shape parameters on the energy consumption and carbon emissions of plateau service station buildings is rarely involved in related research. In this study, 14 highway service stations located on the southern edge of the Qinghai-Tibet Plateau were surveyed and mapped, and the prototype of the service station was extracted. The sensitivity of different plane shape indexes and facade shape indexes to building energy consumption and building carbon emission evaluation indexes was quantitatively analyzed by energy consumption simulation, and the prediction model of building energy consumption and carbon emission was established. The results indicate that the building south window-wall ratio has the most significant effect on both energy consumption and carbon emissions. Orienting the building directly to the north was found to be the most energy-efficient configuration. The final comparison of the 448 simulation results with the baseline model revealed a maximum energy savings rate and carbon reduction rate of 50.13%.