Integrating ecosystem services and life cycle assessment: a framework accounting for local and global (socio-)environmental impacts

Purpose: Human activities put pressure on our natural ecosystems in various ways, such as globally through the spread of emissions or locally through the degradation of species-rich landscapes. However, life cycle assessment (LCA) studies that integrate ecosystem services (ES) are still in the minority because of intrinsic differences in data, modelling, and interpretation. This study aims to overcome these challenges by developing and testing a framework that comprehensively evaluates the (socio-)environmental impacts of human activities. Methods: LCA and ecosystem services assessment (ESA) were integrated in two different ways: (1) both methodologies run in parallel and results are combined, and (2) LCA as a driving method where ES are integrated. Because local ESA studies contain the most accurate information but will not be available for all processes in the value chain, it was necessary to advance the life cycle impact assessment method ReCiPe 2016 including three new midpoint impact categories (terrestrial provision, regulation, and cultural ES) and site-generic CFs based on the Ecosystem Services Valuation Database to account for changes in regulating, cultural and provisioning ES due to land use, for the remaining processes in the value chain. Monetary valuation is used to aggregate at the areas of protection (AoP). Results and discussion: A comprehensive LCA$_{+ES}$-ESA sustainability assessment framework is developed to account for local and global impacts due to human activities on three AoPs (natural resources, ecosystem quality, and human health and well-being), of which the results are expressed in monetary terms. The framework is able to visualize all benefits and burdens accounted for through the handprint/footprint approach. A simplified terrestrial case study on Scots pinewood shows the applicability of the proposed framework, resulting in a handprint (€$_{2022}$ 9.81E+02) which is four times larger than the footprint (€$_{2022}$ 2.31E+02) for 1 kg of wood produced. Challenges related to the framework such as data availability and database shortcomings (i.e., beyond land use) and ES interrelations are discussed. Conclusion: While classical LCA studies focus more on burdens, this framework can also take into account benefits, such as the provision of ecosystem services (or the value of the functional unit of the study). Although the integration of both LCA and ESA has been increasingly explored recently, until now no framework has been available that can incorporate results from local ESA, site-specific ESA, and classical LCA studies, which is considered highly relevant to decision-making

Brain-Machine Interfaces: The Perception-Action Closed Loop

A brain-machine interface (BMI) is about transforming neural activity into action and sensation into perception (Figure 1). In a BMI system, neural signals recorded from the brain are fed into a decoding algorithm that translates these signals into motor outputs to control a variety of practical devices for motor-disabled people [1]-[5]. Feedback from the prosthetic device, conveyed to the user either via normal sensory pathways or directly through brain stimulation, establishes a closed control loop