Ivan Kantor

Eco-industrial networks are a concept which has received study for almost 30 years as a strategy for improving economics of production facilities while reducing waste. This study focuses on developing a generalized modeling framework in terms of mixed-integer nonlinear programming of an eco-industrial network. The problem is formulated as a multi-objective optimization with the objective to reduce life-cycle emissions and maintaining favourable economics. This model lends itself as a developmental tool to assess environmental and economic feasibility of applying eco-park concepts to new construction projects. In addition, the model is formulated to determine feasible transportation distances between facilities, select the appropriate transportation technologies and is built with the intention of modification toward stochastic import/export pricing. The sensitivity of the network configuration to variances in the weighting factors placed on economics or environmental emissions is discussed and the results from multiple weighting scenarios are presented. These results show that the estimated reductions in cost and emissions are less significant than those from previously published work but are founded upon a more realistic network model. Based on our findings, the cost for the integrated set of facilities is shown to be reduced by 24% while the emission reduction is observed at 12.7% for the base scenario examined by the earlier models. These results show less promise than the earlier findings but represent a more realistic assessment of the proposed network. The tools developed by this research present a novel approach to facility planning and policy development for chemical industries. As such, the framework presented herein has the potential to impact facility construction/operation and public policy governing industrial producers; additionally, this research contributes an empirical approach for assessing the practicality of establishing eco-industrial networks and provides an approach for further analyses.

Excessive electricity consumption during peak demand periods has been shown to be expensive for utility
companies and can affect the stability of the electricity grid. Shifting peak electricity consumption to offpeak
periods has attracted the interest of governments, utility companies, equipment manufacturers and
residents. Individual, hourly, household data from Ontario, Canada are used to explore the potential for
households to install electricity storage systems by manipulating two financial policy triggers. Results
show that households with higher daily and on-peak consumption realize net benefits atlower deviations
from the current pricing regimes than do those with lower consumption. Benefits for households can be
realized by manipulating either of the policy triggers considered, although the feasibility of these policy
decisions is not explored. Repurposed Li-ion batteries require complete subsidy on re-purposing and
installation of the system with a $29 kWhcapacity−1 subsidy or a differential of 19.5 ¢ kWh−1 between
on- and off-peak commodity rates for 10% of households to achieve net benefits. Systems with new
ZnMnO2 batteries require a $44 kWhcapacity−1 subsidy in addition to a complete installation subsidy or a
differential of 16.5 ¢ kWh−1 between on- and off-peak commodity prices to achieve the same proportion
of households with net benefits.

ABSTRACT Eco-industrial networks are a concept which has received study for almost 30 years as a strategy for improving economics of production facilities while reducing waste. This study focuses on developing a generalized modeling framework in terms of mixed-integer nonlinear programming of an eco-industrial network. The problem is formulated as a multi-objective optimization with the objective to reduce life-cycle emissions and maintaining favourable economics. This model lends itself as a developmental tool to assess environmental and economic feasibility of applying eco-park concepts to new construction projects. In addition, the model is formulated to determine feasible transportation distances between facilities, select the appropriate transportation technologies and is built with the intention of modification toward stochastic import/export pricing. The sensitivity of the network configuration to variances in the weighting factors placed on economics or environmental emissions is discussed and the results from multiple weighting scenarios are presented. These results show that the estimated reductions in cost and emissions are less significant than those from previously published work but are founded upon a more realistic network model. Based on our findings, the cost for the integrated set of facilities is shown to be reduced by 24% while the emission reduction is observed at 12.7% for the base scenario examined by the earlier models. These results show less promise than the earlier findings but represent a more realistic assessment of the proposed network. The tools developed by this research present a novel approach to facility planning and policy development for chemical industries. As such, the framework presented herein has the potential to impact facility construction/operation and public policy governing industrial producers; additionally, this research contributes an empirical approach for assessing the practicality of establishing eco-industrial networks and provides an approach for further analyses.