Zarrar Khan, Ph.D.

Dr. Zarrar Khan brings over a decade of experience in climate and energy modeling and advancing sustainable energy solutions, climate mitigation, and resilience initiatives worldwide. He has worked in the U.S., Latin America, Europe, the Middle East, and Asia to help transform groundbreaking research into tangible global impact. Khan has played pivotal roles in developing national climate strategies, enhancing local capacities, and fostering lasting stakeholder relationships. His collaborative efforts to address complex challenges include working with the World Bank, Green Climate Fund, World Resources Institute, U.S. Agency for International Development (USAID), Department of Energy (DOE), Department of State (DOS), and Inter-American Development Bank (IDB). Khan’s scholarly work has been cited over 600 times, demonstrating his impact on global climate resilience and policy development.

In his role at Abt Global, Khan leads initiatives focused on enhancing resilience against climate impacts through integrated adaptation & mitigation efforts. He oversees comprehensive climate feasibility studies, contributes to strategic adaptations for sustainable urban management, and evaluates vulnerabilities for policy reforms. Khan aids in finding solutions for climate-related projects across Abt’s global portfolio, such as assessing rainwater harvesting systems in Mexico City and evaluating food waste implications in Nationally Determined Contribution (NDC) scenarios in Bangladesh.

Before joining Abt, Khan served as a computational climate change scientist at Pacific Northwest National Laboratory (PNNL), where he was the principal investigator on critical projects like net-zero pathways in Southeast Asia and the Subnational Climate Action Leaders Exchange. These projects, among others, exemplify his leadership in coordinating international collaboration, developing integrated modeling analyses, and spearheading capacity-building initiatives. His innovative model integration and stakeholder engagement approaches have shaped climate action strategies across geographies. 

Expertise

• Climate mitigation & adaptation 
• Integrated assessment modeling
• Data analysis and analytics
• Capacity building and training
• Reproducible research

Key Projects

• Enhancing resilience in Mexico City against climate impacts on water
• Analyzing food waste in Bangladesh’s NDC scenarios for Feed the Future
• Net-zero pathways analysis in Southeast Asia
• Pakistan Energy Task Force for USAID
• Global Change Intersectoral Modeling System (GCIMS) for U.S. DOE

Publications

• “Waite, T., Pradhan, B.B., Winyuchakrit, P., Khan, Z., Weber, M., Pressburger, L., Chaichaloempreecha, A., Rajbhandari, S., Pita, P., Westphal, M.I. and Jonvisait, A., 2024. Stakeholder-driven carbon neutral pathways for Thailand and Bangkok: integrated assessment modeling to inform multilevel climate governance. Frontiers in Energy Research, 12  https://doi.org/10.3389/fenrg.2024.1335290 
• McManamay, R.A., Vernon, C.R., Chen, M., Thompson, I., Khan, Z., and Narayan, K.B. (2024). "Dynamic urban land extensification is projected to lead to imbalances in the global land-carbon equilibrium." Communications Earth & Environment, 5(1), p.70. https://doi.org/10.1038/s43247-024-01231-y
• Ahsan, H., Khan, Z., Snyder, A., Kyle, P., and Vernon, C. (2023). "osiris: An R package to process climate impacts on agricultural yields for the Global Change Analysis Model." Journal of Open Source Software, 8(85), p.5226. https://doi.org/10.21105/joss.05226
• Yarlagadda, B., Wild, T., Zhao, X., Clarke, L., Cui, R., Khan, Z., Birnbaum, A., and Lamontagne, J. (2023). "Trade and Climate Mitigation Interactions Create Agro‐Economic Opportunities With Social and Environmental Trade‐Offs in Latin America and the Caribbean." Earth's Future, 11(4), p.e2022EF003063. https://doi.org/10.1029/2022EF003063
• Khan, Z., Thompson I.F., Vernon, C.R., Graham, N.T., Wild, T., and Chen, M. (2023). "Global monthly sectoral water use for 2010-2100 at 0.5° resolution across alternative futures." Nature Scientific Data, 10, 201. https://doi.org/10.1038/s41597-023-02086-2