A Green’s Function Approach to Black Carbon: Ensembles of Policy Analysis in Southeast Asia

Abstract: Multi-criteria decision-making requires evaluating policies impact on multiple factors, including environmental ones, which can be a computationally prohibitive exercise. Here, we diagnose Green's functions from a chemical transport model, establishing an approach that allows users to evaluate the transport of black carbon across large ensembles of scenarios with low computational cost. 

We use this approach to evaluate the impact of early retirement scenarios for coal plants in four countries in Southeast Asia. We assess the impacts that individual plants and scenarios have on both black carbon and CO2 concentrations and their temperature impacts. 

We show that groups of 30 of the 367 plants are responsible for 19.4% of the increase in black carbon concentration per megawatt of energy produced in the region, and 17.8% of the temperature increase per megawatt of energy produced in the region. Thus these plants could be prioritized for early closure to obtain the greatest benefits for pollution and temperature in terms of the plants' capacity.

Plain Language Summary: It is difficult to model the possible environmental impacts of a large range of policies because it can require a large amount of computational power. In this work, we use impulse response functions based on a chemical transport model to establish a less computationally intense approach for evaluating policy impacts on black carbon. 

We use this approach to evaluate the impact of early retirements of coal plants across four countries in Southeast Asia. We look at their impact on black carbon and carbon dioxide concentrations, and their temperature impacts. 

We show that groups of 30 of the 367 plants are responsible for 19.4% of the increase in black carbon concentration per megawatt of energy produced in the region, and 17.8% of the temperature increase per megawatt of energy produced in the region. These plants could be prioritized for early closure to obtain the greatest benefits for pollution and temperature in terms of the plants' capacity.