School of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138;
School of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138.
Proc Natl Acad Sci U S A. 2018 Jul 17;115(29):7491-7496. doi: 10.1073/pnas.1803715115. Epub 2018 Jul 2.
With the pending withdrawal of the United States from the Paris Climate Accord, cities are now leading US actions toward reducing greenhouse gas emissions. Implementing effective mitigation strategies requires the ability to measure and track emissions over time and at various scales. We report CO emissions in the Boston, MA, urban region from September 2013 to December 2014 based on atmospheric observations in an inverse model framework. Continuous atmospheric measurements of CO from five sites in and around Boston were combined with a high-resolution bottom-up CO emission inventory and a Lagrangian particle dispersion model to determine regional emissions. Our model-measurement framework incorporates emissions estimates from submodels for both anthropogenic and biological CO fluxes, and development of a CO concentration curtain at the boundary of the study region based on a combination of tower measurements and modeled vertical concentration gradients. We demonstrate that an emission inventory with high spatial and temporal resolution and the inclusion of urban biological fluxes are both essential to accurately modeling annual CO fluxes using surface measurement networks. We calculated annual average emissions in the Boston region of 0.92 kg C·m·y (95% confidence interval: 0.79 to 1.06), which is 14% higher than the Anthropogenic Carbon Emissions System inventory. Based on the capability of the model-measurement approach demonstrated here, our framework should be able to detect changes in CO emissions of greater than 18%, providing stakeholders with critical information to assess mitigation efforts in Boston and surrounding areas.
随着美国即将退出《巴黎气候协定》，城市现在正在引领美国采取行动减少温室气体排放。实施有效的缓解策略需要有能力随着时间的推移和在不同的尺度上测量和跟踪排放。我们根据逆模式框架中的大气观测结果，报告了 2013 年 9 月至 2014 年 12 月马萨诸塞州波士顿市区的 CO 排放情况。来自波士顿及其周边地区的五个站点的 CO 连续大气测量数据与高分辨率的自上而下的 CO 排放清单以及拉格朗日粒子扩散模型相结合，用于确定区域排放。我们的模型-测量框架纳入了人为和生物 CO 通量的子模型的排放估计值，以及根据塔架测量值和模拟的垂直浓度梯度组合在研究区域边界处开发的 CO 浓度幕。我们证明，具有高时空分辨率的排放清单以及包括城市生物通量对于使用地面测量网络准确模拟年度 CO 通量都是必不可少的。我们计算出波士顿地区的年平均排放量为 0.92 kg C·m·y（95%置信区间：0.79 至 1.06），比人为碳排放系统清单高 14%。基于此处展示的模型-测量方法的能力，我们的框架应该能够检测到 CO 排放变化大于 18%，为利益相关者提供评估波士顿及周边地区减排工作的关键信息。
