National Exposure Research Laboratory, Office of Research and Development, U.S. Environmental Protection Agency , Research Triangle Park, North Carolina, United States.
Environ Sci Technol. 2013;47(21):12011-9. doi: 10.1021/es402283j. Epub 2013 Oct 22.
Over the coming decades, new energy production technologies and the policies that oversee them will affect human health, the vitality of our ecosystems, and the stability of the global climate. The GLIMPSE decision model framework provides insights about the implications of technology and policy decisions on these outcomes. Using GLIMPSE, decision makers can identify alternative techno-policy futures, examining their air quality, health, and short- and long-term climate impacts. Ultimately, GLIMPSE will support the identification of cost-effective strategies for simultaneously achieving performance goals for these metrics. Here, we demonstrate the utility of GLIMPSE by analyzing several future energy scenarios under existing air quality regulations and potential CO2 emission reduction policies. We find opportunities for substantial cobenefits in setting both climate change mitigation and health-benefit based air quality improvement targets. Though current policies which prioritize public health protection increase near-term warming, establishing policies that also reduce greenhouse gas emissions may offset warming in the near-term and lead to significant reductions in long-term warming.
在未来几十年，新能源生产技术和监管这些技术的政策将影响人类健康、生态系统的活力以及全球气候的稳定性。GLIMPSE 决策模型框架提供了关于技术和政策决策对这些结果影响的见解。决策者可以使用 GLIMPSE 来确定替代的技术政策未来，检查其空气质量、健康状况以及短期和长期的气候影响。最终，GLIMPSE 将支持识别同时实现这些指标绩效目标的具有成本效益的策略。在这里，我们通过分析现有空气质量法规和潜在 CO2 减排政策下的几种未来能源情景来展示 GLIMPSE 的实用性。我们发现，在设定气候变化缓解和基于健康效益的空气质量改善目标方面，存在着大量的协同效益机会。虽然优先考虑保护公众健康的现行政策会增加近期的变暖，但制定既能减少温室气体排放又能在近期抵消变暖并导致长期变暖显著减少的政策是可能的。
