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    From Transfer to Knowledge Co-Production: A Transdisciplinary Research Approach to Reduce Black Carbon Emissions in Metro Manila, Philippines
    (Basel : MDPI, 2020) Tõnisson, Liina; Kunz, Yvonne; Kecorius, Simonas; Madueño, Leizel; Tamayo, Everlyn Gayle; Casanova, Dang Marviluz; Zhao, Qi; Schikowski, Tamara; Hornidge, Anna-Katharina; Wiedensohler, Alfred; Macke, Andreas
    Air pollution, which kills an estimated 7 million people every year, is one of the greatest environmental health risks of our times. Finding solutions to this threat poses challenges to practitioners and policymakers alike. Increasing awareness on the benefits of transdisciplinary research in solution-oriented sustainable development projects has led to the establishment of the research project “A Transdisciplinary Approach to Mitigate Emissions of Black Carbon” (TAME-BC). This paper introduces the TAME-BC research setup that took place with Metro Manila, Philippines, case study. The approach integrates BC measurements with technological, socio-political, and health aspects to improve the scientific state of the art, policymaking, transport sector planning, and clinical studies related to air pollution health effects. The first pillar in the setup presents an (1) air quality assessment through aerosol measurements and instrumentation, complemented by a (2) description and assessment of the current policies, technologies, and practices of the transport sector that is responsible for pollution levels in the Philippines, as well as a (3) BC exposure and associated health impacts assessment. The fourth pillar is intercrossing, fostering (4) knowledge co-creation through stakeholder involvement across scales. We argue that this transdisciplinary approach is useful for research endeavors aiming for emission mitigation in rapidly urbanizing regions beyond Metro Manila.
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    Integrated Solutions for the Water-Energy-Land Nexus: Are Global Models Rising to the Challenge?
    (Basel : MDPI, 2019) Johnson, Nils; Burek, Peter; Byers, Edward; Falchetta, Giacomo; Flörke, Martina; Fujimori, Shinichiro; Havlik, Petr; Hejazi, Mohamad; Hunt, Julian; Krey, Volker; Langan, Simon; Nakicenovic, Nebojsa; Palazzo, Amanda; Popp, Alexander; Riahi, Keywan; van Dijk, Michiel; van Vliet, Michelle; van Vuuren, Detlef; Wada, Yoshihide; Wiberg, David; Willaarts, Barbara; Zimm, Caroline; Parkinson, Simon
    Increasing human demands for water, energy, food and materials, are expected to accentuate resource supply challenges over the coming decades. Experience suggests that long-term strategies for a single sector could yield both trade-offs and synergies for other sectors. Thus, long-term transition pathways for linked resource systems should be informed using nexus approaches. Global integrated assessment models can represent the synergies and trade-offs inherent in the exploitation of water, energy and land (WEL) resources, including the impacts of international trade and climate policies. In this study, we review the current state-of-the-science in global integrated assessment modeling with an emphasis on how models have incorporated integrated WEL solutions. A large-scale assessment of the relevant literature was performed using online databases and structured keyword search queries. The results point to the following main opportunities for future research and model development: (1) improving the temporal and spatial resolution of economic models for the energy and water sectors; (2) balancing energy and land requirements across sectors; (3) integrated representation of the role of distribution infrastructure in alleviating resource challenges; (4) modeling of solution impacts on downstream environmental quality; (5) improved representation of the implementation challenges stemming from regional financial and institutional capacity; (6) enabling dynamic multi-sectoral vulnerability and adaptation needs assessment; and (7) the development of fully-coupled assessment frameworks based on consistent, scalable, and regionally-transferable platforms. Improved database management and computational power are needed to address many of these modeling challenges at a global-scale.