| 英文摘要: | Potential climate change mitigation is typically framed in both public and scientific discussions as an undertaking whose costs are local, near-term and acute, and whose returns are global, far-term and uncertain. This characterization may be true for long-lived greenhouse gases (LLGHGs) such as carbon dioxide, nitrous oxide and methane, but it is not true of compounds that are considered short-lived local pollutants (SLLPs) such as particulate matter, black carbon, sulfur dioxide and tropospheric ozone. These short-lived pollutants impact atmospheric conditions and air quality through different mechanisms over a range of spatial and temporal scales. LLGHGs and SLLPs are often co-emitted by the same processes, albeit in widely differing quantities and combinations, but to date, scientists and policymakers have largely treated these different types of emissions as both interchangeable and separable. This approach is incomplete because individual emissions species rarely can be mitigated in isolation and the net global and regional impacts of different mitigation portfolios should consider the sum of both LLGHG and SLLP effects. A full understanding of environmental impacts, and of mitigation costs and benefits, requires that SLLPs and LLGHGs be considered together, and thus is the focus of this project. Additionally, this project will contribute to the development of the scientific workforce by training several undergraduate and graduate students to work on interdisciplinary research of societal importance.
This project will utilize a coupled systems approach to understanding the joint roles of LLGHGs and SLLPs in the dynamics of natural (atmospheric) and human (policymaking) systems, as well as in the processes that connect them. The objectives of this project are to 1) characterize the joint emissions of SLLPs and LLGHGs across, space, time and sector, 2) build analytical infrastructure that enables integrated analysis that is useable to both scientists and policy makers, 3) understand the mechanisms driving regional differences in the atmospheric concentrations and radiative forcing induced by identical emissions, 4) build a dynamical framework explaining the spatial pattern and magnitude of global response to individual SLLP hotspots, 5) assemble and merge novel state-of-the-art data on environmental conditions with data on agricultural and health outcomes, 6) use spatial econometrics to derive location-specific exposure-response relationships for atmospheric conditions on human health and crop yields, 7) fully couple the human and natural dynamics systems to iteratively understand how local and global costs and benefits, based on realistic implementations of national mitigations commitments, their atmospheric effects, and their locally-specific health and crop yield impacts, drive national optimal mitigation levels and overall global mitigation. |