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On Dec 16, 2020, United Kingdom became the first country to officially have air pollution listed as a cause of death. Increasing epidemiological evidence has linked air pollution to deterioration of human health quality. Despite environmental regulations like the Clean Air Act and emission trading programs, poor air quality claims thousands of lives in the US every year. These damages are a direct consequence of "less bad" engineering, where the objective of engineering is to reduce impacts. The question about how much "less bad" is good enough is left unanswered.Explicit accounting for ecosystems like urban forestry, wetlands and grasslands in engineering decision making can help answer the question. Multiple studies in literature have demonstrated the potential for urban forestry to alleviate air quality issues and provide an opportunity for economically, environmentally and socially win-win solutions. The studies assume an annual average ecological supply capacity to mitigate air pollutants. In practice, ecosystems' capacity varies with meteorological factors like sunlight, weather, season, etc. and tend to exhibit homeorhetic behavior. In contrast, human-made systems are valued for their ability to maintain a set-point and constant utility rate. A framework to bridge the gap between homeorhetic and homeostatic systems is required to take advantage of win-win solutions from ecology.The objective of this work is to establish a framework for design and operation of techno-ecological systems while accounting for spatio-temporal variability and intermittency of ecosystems. The framework can bridge the gap between homeorhetic and homeostatic systems and expand the engineering design space to explicitly include ecosystems and respect their time varying capacity. The work develops a framework by using a case study of air quality regulation for a chloralkali production facility using techno-centric choice of selective catalytic reactor or flue gas desulfurizer and ecological alternative of reforestation.Given the complex nature of the problem, the dissertation breaks down the design and operation problem for techno-ecological synergy (TES) systems in spatial variation and temporal variation. The temporal variation and intermittency problem is further broken down into a retrospective approach and a proactive approach. The former class of problems are relatively easier to solve and provide insight into behavior of TES systems under variability and intermittency. The later proactive problems are more complex and of a practical relevance from an industrial point of view. Multi-objective two-stage stochastic mixed-integer non-linear programming (MINLP) optimization framework is solved for the retrospective class of problems. The solutions from the retrospective approach are used as guiding point to solve an optimal automatic scheduling approach based on supervisory economic model predictive control formulation. The automatic scheduling algorithm comprises of state-of-the-art time-series forecasting and clustering methods. The scheduler is modeled to satisfy multi-scale constraints in real-time adaptive fashion.Finally, the methods developed to incorporate temporal variability are extended to include spatial variation as well. A bi-level simulation optimization problem is set up and solved for spatially explicit land use change optimization and temporally explicit operations optimization. This algorithm lays the foundation for simultaneous design and operations of spatio-temporally explicit TES systems for air quality regulation problems.The analysis on the chloralkali case study, demonstrated that TES solutions can lead to economically and socially win-win solutions. For the synergy to exist, engineering needs to abandon constant steady state operation and match the dynamics of ecosystems on which it relies. Investment in ecosystems can meet demand for air quality regulation services and can provide additional services resulting in positive impacts. The proposed simultaneous design and operation TES framework can facilitate a paradigm shift from "less bad" engineering to net-positive impact manufacturing.This work identifies and solves the practical challenges in techno-ecological synergy, an essential condition for sustainability. Inclusion of ecosystems can provide unique opportunities for the sustainable future. The spatio-temporally explicit TES design and operations framework lays a foundation in mathematical techniques required to utilize such opportunities. |
