Sustainable engineering design methods utilize a life cycle perspective to avoid causing unintentional harm by shifting environmental issues outside the analysis boundary. However, these methods ignore the role played by nature in supporting engineering activities and therefore neglect the fact that currently most human activities demand more ecosystem goods and services than can be supplied without contributing to ecological degradation and loss of natural capital. Landscape design studies focus on implementing agricultural systems that increase the supply of ecosystem services, but do not consider the demand for ecosystem services within the analysis boundary and moreover do not extend to the life cycle scale. Accounting for ecosystem service supply and demand enables decision making that keeps human activities within the carrying capacity of supporting ecosystem services, but considering only a single, local scale leads to a risk of creating excess demand outside the analysis boundary.
The recently developed Techno-Ecological Synergy (TES) framework accounts for the regenerative capacity of ecological systems by quantifying the demand and supply of ecosystem services at multiple spatial scales. The balance, or lack thereof, between ecosystem service supply (S) and demand (D) is expressed as a sustainability index, (S - D)/D, which is applicable to a variety of ecosystem services at any relevant scale. The TES framework focuses on adjusting both the supply and demand of ecosystem services, allowing design decisions that “do more good” rather than “less bad”. However, TES lacks proper connection with life cycle methods and data, and is yet to be explored as a tool for sustainable engineering design, although it has been incorporated into landscape design applications. In an engineering design context, TES involves simultaneously designing engineering systems and supporting ecosystems in order to increase relevant sustainability indexes. The design for TES approach is expected to yield both economic and ecological benefits because of a reduction in need of engineered inputs to supply the same services.
This work introduces a methodology for sustainable engineering design that combines the TES framework with the process-to-planet (P2P) multi-scale modeling framework. The P2P modeling framework integrates detailed engineering models at the equipment scale with empirical life cycle models at the regional scale and a coarse economic model at the national scale. The techno-economic P2P framework is extended with ecological models and data at the local, regional and national scales, and the degree of TES within the system is quantified with sustainability index metrics at relevant scales. The resulting P2P-TES framework models interactions between engineering design decisions at the local scale, impacts at the life cycle scale and ecosystem service supply and demand at all scales. As a result, the P2P-TES framework can be used to make both engineering and ecological design decisions, and in particular can be used for the simultaneous design of engineering systems and supporting ecosystems at multiple scales.
Within the P2P-TES framework, ecological models capture the supply of services and techno-economic models capture the demand. The dependence of the demand and supply of ecosystem services on ecological and engineering design decisions is likewise captured. Sustainability indices at multiple scales can thus be quantified as functions of decision variables, allowing the indices to be utilized within an optimization formulation. For instance, P2P-TES systems can be designed for minimizing ecological overshoot by constraining relevant sustainability indices to be greater than or equal to zero, which corresponds to scenarios in which the supply of ecosystem services is at least equal to the demand. Such constraints can be applied at any scale, although for some services, demand and supply is strictly local, and therefore some sustainability index constraints are relevant only at certain scales.
The P2P-TES framework is demonstrated with the design of a renewable energy production system consisting of a land use stage and a biomass conversion stage. Designing the system requires choosing from several agricultural and technological land use options; agricultural land use options are combined with a relevant biomass conversion process for energy generation. This case study is intended to demonstrate that making design decisions without accounting for ecosystem service supply results in designs with lower overall sustainability and potentially lower profits than designs that utilize TES.
At the land use stage, agricultural land use options involve biomass cropping systems followed by conversion of the biomass to energy products, while technological options involve installing either wind turbines or solar panels and producing electricity without implementing the biomass conversion stage. 10,000 acres of farmland is available for the land use stage as well as 3.5 additional acres suitable for establishing a runoff treatment wetland. One plot of land capable of housing a single biomass conversion process is available. Adjacent to the site is 27 acres of barren land suitable for reforestation with a variety of native tree species that can provide local carbon and nitrogen sequestration services.
The system is designed over a twenty-year period, with the restriction that both the land use options and biomass conversion options remain constant over the entire period. The system is first optimized for maximum profits to find the economically optimal system design; this is the base case scenario against which other optimal designs are compared. A traditional sustainability optimum system is obtained by minimizing emissions production at the life cycle scale. Finally, the optimum system under TES is obtained by maximizing the twenty-year cumulative sustainability index at the regional scale.
The traditional sustainability and TES objectives are expected to yield different optimal system designs. Under traditional sustainable design, total emissions production (demand for ecosystem services) is minimized whether the emissions are produced at the local scale, the life cycle scale or otherwise, and only engineering decision variables are optimized. This approach does result in net reduction in ecosystem service demand but does not necessarily result in zero demand overshoot. It is possible to have a system optimized for minimum ecosystem service demand that still demands more services than can be supplied without contributing to ecological degradation and loss of natural capital. On the other hand, TES design maximizes excess ecosystem service supply by optimizing both engineering and ecological decision variables, and can lead to designs that shift demand from the life cycle to the local scale where the demand can be met or exceeded by local designed ecosystems. On the other hand, designing for traditional sustainability will not necessarily have the same effect and may result in higher ecosystem service demand at larger scales. For instance, implementing solar panels to produce electricity generates virtually no local demand but relatively high life cycle demand due to an energy and emissions-intensive manufacturing pathway. Installing solar panels thus creates ecosystem service demand that is spatially dispersed and difficult to balance by designing supporting ecosystems.
The supply of ecosystem services is not a fixed rate but rather varies over time. For instance, carbon sequestration due to switching from a conventionally tilled to a no till farming management practice is negligible for the first few years, then positive for up to twenty years before leveling off and becoming negligible again. Similarly, a huge amount of carbon is stored in the biomass of trees for decades and the sequestration rate of trees increases with tree growth. On the other hand, the demand for ecosystem services is created almost entirely by technological activities and tends to remain fairly constant over time. Similar to how the cash flow of engineering projects is analyzed over the lifetime of the project, the cumulative supply and demand of ecosystem services must also be analyzed over a relevant time period. This is demonstrated by determining the cumulative ecosystem service supply and demand at several discrete time periods for all optimal systems, which is used to capture the dynamic nature of ecological systems and to determine the ecosystem service payback period, or number of years of system operation required to achieve zero ecosystem service demand overshoot. This analysis is expected to yield the insight that economically optimal systems have an ecosystem service payback period that is significantly longer than the expected lifetime of the system, while systems designed for TES sustainability have ecosystem service payback periods less than or equal to the expected lifetime. An ecosystem service payback period of less than the system’s expected lifetime implies that implementing such a system will result in a net increase in the supply of ecosystem services over time.
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