AGS-PRF: Big Data Analytics: Elucidation of Volatile Organic Compounds in Urban Atmosphere

该博士后研究奖学金（PRF）旨在开发一种使用机器学习算法整合大量数据的系统，以提供对城市大气中挥发性有机化合物（VOC）的理解的新见解。本研究的主要目的是：（1）从综合测量中对排放的（一次）和化学形成的（二次）VOC进行分类;（2）调查当地（车辆、室内、工业、垃圾填埋场等）的VOC排放量;（3）研究当地的VOC排放量;（4）研究当地的VOC排放量;（5）研究当地的VOC排放量。和区域（野火、海洋等）主要VOCs的来源;（3）确定特定VOC排放的动态和空间热点：（4）了解初级VOC及其次级VOC产物之间的隐含和非线性关系;以及（5）该奖项反映了NSF的法定使命，并通过使用基金会的智力价值和更广泛的评估，被认为是值得支持的。影响审查标准。

This Postdoctoral Research Fellowship (PRF) is directed towards the development of a system for integrating large amounts of data using machine learning algorithms to provide new insights into the understanding of volatile organic compounds (VOCs) in the urban atmosphere. The results of this effort are expected to help regulatory agencies estimate emissions from non-traditional sources of VOC in the atmosphere and improve the overall accuracy of emission inventories.The objectives of this research focus on: (1) categorizing emitted (primary) and chemically formed (secondary) VOCs from comprehensive measurements; (2) investigating local (vehicles, indoor, industry, landfill, etc.) and regional (wildfire, ocean, etc.) origins of primary VOCs; (3) identifying the dynamic and spatial hotspots of specific VOC emissions; (4) understanding the implicit and nonlinear relationships between primary VOCs and their secondary VOC products; and (5) the influence of environmental factors on primary VOC degradation and secondary VOC formation.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.