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Projecting state-level air pollutant emissions using an integrated assessment model: GCAM-USA

机译:使用综合评估模型预测州一级的空气污染物排放:GCAM-USA

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摘要

Integrated Assessment Models (IAMs) characterize the interactions among human and earth systems. IAMs typically have been applied to investigate future energy, land use, and emission pathways at global to continental scales. Recent directions in IAM development include enhanced technological detail, greater spatial and temporal resolution, and the inclusion of air pollutant emissions. These developments expand the potential applications of IAMs to include support for air quality management and for coordinated environmental, climate, and energy planning. Furthermore, these IAMs could help decision makers more fully understand tradeoffs and synergies among policy goals, identify important cross-sector interactions, and, via scenarios, consider uncertainties in factors such as population and economic growth, technology development, human behavior, and climate change. A version of the Global Change Assessment Model with U.S. state-level resolution (GCAM-USA) is presented that incorporates U.S.-specific emission factors, pollutant controls, and air quality and energy regulations. Resulting air pollutant emission outputs are compared to U.S. Environmental Protection Agency 2011 and projected inventories. A Quality Metric is used to quantify GCAM-USA performance for several pollutants at the sectoral and state levels. This information provides insights into the types of applications for which GCAM-USA is currently well suited and highlights where additional refinement may be warranted. While this analysis is specific to the U.S., the results indicate more generally the importance of enhanced spatial resolution and of considering national and sub-national regulatory constraints within IAMs.
机译:综合评估模型(IAM)表征了人与地球系统之间的相互作用。 IAM通常已用于调查全球到大陆范围内的未来能源,土地使用和排放途径。 IAM发展的最新方向包括增强技术细节,提高空间和时间分辨率以及纳入空气污染物排放。这些发展扩展了IAM的潜在应用,包括支持空气质量管理以及协调的环境,气候和能源计划。此外,这些IAM可以帮助决策者更充分地理解政策目标之间的权衡和协同作用,确定重要的跨部门互动,并通过情景考虑诸如人口与经济增长,技术发展,人类行为和气候变化等因素的不确定性。提出了具有美国州级决议的全球变化评估模型(GCAM-USA),其中包含了美国特定的排放因子,污染物控制以及空气质量和能源法规。将产生的空气污染物排放量与美国环境保护署2011年和预计的存量进行比较。质量指标用于量化部门和州级几种污染物的GCAM-USA性能。该信息提供了有关GCAM-USA当前最适合的应用程序类型的见解,并着重指出了需要进一步改进的地方。尽管此分析特定于美国,但结果更普遍地表明了增强空间分辨率以及考虑IAM中国家和地方以下法规限制的重要性。

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