This thesis focuses on addressing the challenge of managing the climate impact of system engineering projects within a large global industrial company. The research design is a case study within the selected company, and it integrates qualitative and quantitative methodologies to provide a holistic understanding of environmental challenges. The principal objective is to provide direction on efficient management of system engineering projects’ environmental footprint delivered by large global industrial companies. This is achieved by quantifying greenhouse gas emissions and identifying critical factors that significantly influence environmental outcomes. Based on the results together with the qualitative results from the interviews, effective countermeasures have been developed to reach set science-based emission reduction targets aligned with the Paris Agreement. The research has contributed to a better understanding of the climate impact of system engineering projects, provided guidance on measuring their environmental impact and offered strategies for reducing GHG emissions to mitigate climate change risks. The thesis further delves into various relevant concepts, including system engineering, science-based emission reduction targets, carbon footprint analysis, motivators and barriers for greenhouse gas emissions reductions and the decarbonization of system engineering projects.  The research underscores the importance of user-friendly calculations of CO2e emissions aligned with ISO standards. It also emphasizes the necessity of addressing emissions throughout the value chain and optimizing key components for achieving successful outcomes. Furthermore, standardization and incorporating environmental considerations during the design phases are highlighted as important aspects supporting science-based emission reduction targets. To conclude, this research aims to provide valuable insights into effectively managing the climate impact of system engineering projects in a large global industrial company. It offers practical strategies, recommendations, and considerations to support a company's sustainability goals and environmental commitments.

Over the past decades, cost-effectiveness principle or cost-benefit analysis has been employed oftentimes as a typical assessment tool for the expansion of drinking water utility. With changing public awareness of the inherent linkages between climate change, population growth and economic development, the addition of global change impact in the assessment regime has altered the landscape of traditional evaluation matrix. Nowadays, urban drinking water infrastructure requires careful long-term expansion planning to reduce the risk from global change impact with respect to greenhouse gas (GHG) emissions, economic boom and recession, as well as water demand variation associated with population growth and migration. Meanwhile, accurate prediction of municipal water demand is critically important to water utility in a fast growing urban region for the purpose of drinking water system planning, design and water utility asset management. A system analysis under global change impact due to the population dynamics, water resources conservation, and environmental management policies should be carried out to search for sustainable solutions temporally and spatially with different scales under uncertainties. This study is aimed to develop an innovative, interdisciplinary, and insightful modeling framework to deal with global change issues as a whole based on a real-world drinking water infrastructure system expansion program in Manatee County, Florida. Four intertwined components within the drinking water infrastructure system planning were investigated and integrated, which consists of water demand analysis, GHG emission potential, system optimization for infrastructure expansion, and nested minimax-regret (NMMR) decision analysis under uncertainties. In the water demand analysis, a new system dynamics model was developed to reflect the intrinsic relationship between water demand and changing socioeconomic iv environment. This system dynamics model is based on a coupled modeling structure that takes the interactions among economic and social dimensions into account offering a satisfactory platform. In the evaluation of GHG emission potential, a life cycle assessment (LCA) is conducted to estimate the carbon footprint for all expansion alternatives for water supply. The result of this LCA study provides an extra dimension for decision makers to extract more effective adaptation strategies. Both water demand forecasting and GHG emission potential were deemed as the input information for system optimization when all alternatives are taken into account simultaneously. In the system optimization for infrastructure expansion, a multiobjective optimization model was formulated for providing the multitemporal optimal facility expansion strategies. With the aid of a multi-stage planning methodology over the partitioned time horizon, such a systems analysis has resulted in a full-scale screening and sequencing with respect to multiple competing objectives across a suite of management strategies. In the decision analysis under uncertainty, such a system optimization model was further developed as a unique NMMR programming model due to the uncertainties imposed by the real-world problem. The proposed NMMR algorithm was successfully applied for solving the real-world problem with a limited scale for the purpose of demonstration.