Towards resource-efficient management of asphalt waste in Lombardy region (Italy): Identification of effective strategies based on the LCA methodology

Abstract

This study presents a comparison of alternative strategies for managing asphalt waste currently implemented in Lombardy Region (Italy). The waste under study is the one arising from deconstruction and milling of old pavements not containing tar, and, hereafter, it is referred as reclaimed asphalt pavement (RAP). The life cycle assessment (LCA) methodology was applied to the regional system to evaluate its current performance, to identify critical aspects and to suggest actions for improving it. As first step, the amount of RAP generated and recycled within the region was computed by elaborating raw waste data annually collected by the regional agency for the environmental protection. Roughly 1 million tonne of RAP was managed in Lombardy in 2014; most of it was recovered/recycled and only 1% was directly landfilled. Data revealed that RAP was mainly recovered as unbound aggregate for road bases and sub-bases or fillings (52.5%) whereas RAP addition into new asphalt mixtures was less widespread (39.4%). In this case, RAP was mostly recycled in stationary hot mix asphalt (HMAs) and cold mix asphalt (CMAs) plants. Hence, the present LCA focused on these two types of techniques. Primary data on both processes were directly collected from some investigated facilities to set out the current scenario. Sensitivity analyses were then performed to find out the key parameters and their influence on the LCA outcome. Results indicate that recycling RAP in hot/cold mixes is significantly more beneficial than its recovery as unbound material. Moreover, hot recycling provides better environmental performance than cold processes performed at stationary plants, despite the lower RAP addition (20% in HMAs vs 80% in CMAs); this is mainly due to the use of stabilizing agents in the production of CMAs and to the lower field performance of CMAs compared to virgin HMAs. Based on these results, a best-case scenario has been developed to quantify the benefits arising from the suggested actions.