The main goal of this study is to provide a thorough environmental sustainability analysis of the construction, traffic, and maintenance of a 45.6-km section of the ‘Manu Road’, an unpaved tropical road that is currently being built in the vicinity of Manu National Park, in the region of Madre de Dios, Peru.

Life cycle assessment (LCA) using a set of 18 different impact categories was selected to conduct the environmental analysis. Modelling of machinery and vehicle emissions, as well as dust emissions, was performed to account for site-specific characteristics in terms of road construction and traffic. Similarly, direct land use changes were modelled with a particular emphasis on the decay of deforested biomass during construction. A set of different scenarios for the production system were considered to account for uncertainty regarding vehicle transit, amount of deforested biomass, and emission standards.

Construction, maintenance, and traffic of the Manu Road varied considerably depending on methodological assumptions. Deforestation due to direct land use changes appears to be the main environmental hotspot in terms of climate change, whereas in the remaining impact categories, traffic was the main carrier of environmental burdens.

To the best of our knowledge, this study is the first LCA that focuses on the construction, maintenance, and traffic in a tropical rainforest environment. Despite the low requirements in terms of materials and technology to build this road, its derived environmental impacts are relevant in terms of climate change and particulate matter formation due to deforestation and dust emissions, respectively. Unpaved roads represent a relevant proportion of the entire road network worldwide, especially in developing tropical countries, playing a crucial role in the transportation of raw materials. Furthermore, road infrastructure is expected to expand explosively in the decades to come. Therefore, we suggest that LCA studies can and should improve the planning of road infrastructure in terms of life cycle inventories.