5 research outputs found
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Economic Optimization of Historic Preservation in National Parks: Future Transitions for Climate Change and Cultural Resources
Climate change is increasingly posing great challenges to coastal cultural resources. Adapting from the Optimal Preservation (OptiPres) Model developed by Xiao et al. (2019) that prioritizes historic preservation for 17 historic buildings at Cape Lookout National Seashore across a 30-planning horizon, this study advances the OptiPres model to integrate a new management objective to identify the optimal adaptation plans to maximize the number of historical buildings receiving climate-focused adaptation actions and evaluate the trade-offs of adaptation actions under different budget scenarios. The results of this study not only calculate the changes in quantitative values of historical resources following preservation and adaptation treatments but also provide park managers guidance on how to prioritize climate adaptation decisions for historical resources under limited budgets. Moreover, the OptiPres Model enhances the transparency of values embedded in decision-making, supports the prioritization of climate-focused adaptation actions in historical preservation, and is transferable to other coastal parks
A systematic model identification method for chemical transformation pathways – the case of heroin biomarkers in wastewater
Abstract This study presents a novel statistical approach for identifying sequenced chemical transformation pathways in combination with reaction kinetics models. The proposed method relies on sound uncertainty propagation by considering parameter ranges and associated probability distribution obtained at any given transformation pathway levels as priors for parameter estimation at any subsequent transformation levels. The method was applied to calibrate a model predicting the transformation in untreated wastewater of six biomarkers, excreted following human metabolism of heroin and codeine. The method developed was compared to parameter estimation methods commonly encountered in literature (i.e., estimation of all parameters at the same time and parameter estimation with fix values for upstream parameters) by assessing the model prediction accuracy, parameter identifiability and uncertainty analysis. Results obtained suggest that the method developed has the potential to outperform conventional approaches in terms of prediction accuracy, transformation pathway identification and parameter identifiability. This method can be used in conjunction with optimal experimental designs to effectively identify model structures and parameters. This method can also offer a platform to promote a closer interaction between analytical chemists and modellers to identify models for biochemical transformation pathways, being a prominent example for the emerging field of wastewater-based epidemiology