Integration of system dynamics approach toward deepening and broadening the life cycle sustainability assessment framework:a case for electric vehicles.

Abstract

Purpose Quantitativelife cycle sustainable assessment requires a complex and multidimensional understanding, which cannot be fully covered by the current portfolio of reductionist-oriented tools. Therefore, there is a dire need on a new generation of modeling tools and approaches that can quantitatively assess the economic, social, and environmental dimensions ofsustainabilityin anintegratedway. To thisend, thisresearchaimstopresentapracticalandnovelapproachfor (1)broadeningtheexistinglifecyclesustainabilityassessment (LCSA) framework by considering macrolevel environmental, economic, and social impacts (termed as the triple bottom line),simultaneously,(2)deepeningtheexistingLCSAframework by capturing the complex dynamic relationships betweensocial,environmental,andeconomicindicatorsthrough causal loop modeling, (3) understanding the dynamic complexity of transportation sustainability for the triple bottom line impacts of alternative vehicles, and finally (4) investigating the impacts of various vehicle-specific scenarios as a novel approach for selection of a macrolevel functional unit consideringallofthecomplexinteractionsintheenvironmental, social, and economic aspects. Methods To alleviate these research objectives, we presented anovelmethodologytoquantifymacrolevelsocial,economic, and environmental impacts of passenger vehicles from an integrated system analysis perspective. An integrated dynamic LCSA model is utilized to analyze the environmental, economic, and social life cycle impact as well as life cycle cost of alternative vehicles in the USA. System dynamics modeling is developed to simulate the US passenger transportation system and its interactions with economy, the environment, and society. Analysis covers manufacturing and operation phase impacts of internal combustion vehicles (ICVs), hybrid electric vehicles (HEVs), plug-in hybrid electric vehicles (PHEVs), and battery electricvehicles(BEVs). Intotal,seven macrolevel indicators are selected; global warming potential, particulate matter formation, photochemical oxidant formation, vehicle ownership cost, contribution to gross domestic product, employment generation, and human health impacts. Additionally, contribution of vehicle choices to global atmospheric temperature rise and public welfare is investigated. Results and discussion BEVs are found to be a better alternative for most of sustainability impact categories. While some of the benefits such as contribution to employment and GDP, CO2 emission reduction potential of BEVs become greater toward 2050, other sustainability indicators including vehicle ownershipcostand human healthimpactsofBEVs arehigher than the other vehicle types on 2010s and 2020s. While the impactsharesofmanufacturingand operation phasesare similarintheearlyyearsof2010s,thecontributionofmanufacturing phase becomes higher as the vehicle performances increase toward 2050. Analysis results revealed that the US transportationsector,alone,cannotreducetherapidlyincreasing atmospheric temperature and the negative impacts of the globalclimate change, eventhoughtheentirefleet is replaced with BEVs. Reducing the atmospheric climate change requires much more ambitious targets and international collaborative efforts. The use of different vehicle types has a small impact on public welfare, which is a function of income, education, and life expectancy indexes. Conclusions The authors strongly recommend that the dynamiccomplexandmutualinteractionsbetweensustainability indicators should be considered for the future LCSA framework. This approach will be critical to deepen the existing LCSA framework and to go beyond the current LCSA understanding, which provide a snapshot analysis with an isolated view of all pillars of sustainability. Overall, this research is a first empirical study and an important attempt toward developing integrated and dynamic LCSA framework for sustainable transportation research