{'fraction_non_alphanumeric': 0.010282776349614395, 'fraction_numerical': 0.0, 'mean_word_length': 5.711206896551724, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Integrated multiscale modeling of economic-environmental systems for assessing Biocomplexity of material use

Sustainability assessment of industrial products and processes requires joint consideration of economic, environmental, and social aspects that span multiple spatial and temporal scales. Proper understanding of the complex interrelations at multiple scales is critical for formulating effective policies and long term sustainability. Existing methods for technology assessment and policy analysis tend to focus on a single scale. This work focuses on the need for the integrated multiscale modeling of industrial and economic systems. The broader goal is the development of a framework for the design of industrial processes and analyzing the effect of government policies. We are specifically using the economic input-output model for this work. This work will presents an approach for integrating the coarse scale EIO model with the fine scale engineering process models. The utility of the proposed framework is illustrated with the example of a cogeneration plant generating electricity and steam and operating under the disruptive scenario of the carbon tax. While the EIO model is used for estimating the price dimension, a fundamental physical model based on thermodynamic conservation laws and first principles is utilized for the cogeneration plant. The results and benefits of the proposed integrated multiscale optimization framework are compared with existing engineering optimization approaches that ignore price-demand interactions.