Fuzzy optimization model for enhanced weathering networks using industrial waste
Enhanced weathering is a negative emissions technology based on the accelerated weathering of alkaline minerals. Such materials can be reduced to a fine powder and applied to land sinks to maximize the area exposed for reaction with rainwater and dissolved CO2. The carbon is captured in the form of bicarbonate ions in the runoff, which ultimately carries it to the ocean for virtually permanent sequestration. Enhanced weathering has been demonstrated in proof-of-concept laboratory and field tests, but scale-up to a level that delivers significant CO2 removal is still an engineering challenge that requires a system-level perspective. Future enhanced weathering networks should be planned like industrial supply chains, taking into account constraints in the supply of alkaline minerals and the availability of land sinks. Optimization of such networks should also take into account techno-economic uncertainties that are inherent in any emerging technology. To fill this research gap, this work develops a fuzzy mixed-integer linear programming model for optimal planning of enhanced weathering networks. The model is capable of handling multiple conflicting objectives and accounting for system uncertainties. The use of the model is illustrated with two case studies. First, a pedagogical example is solved; then, the model is demonstrated for a realistic scenario which shows that 0.69% of Taiwan’s CO2 emissions can be offset by the use of blast furnace slag for enhanced weathering.