Differential Column Measuring System for Assessing Urban Emissions (using FTIR Spectrometers)

显然，目前的全球变暖是人为温室气体(GHG)排放造成的。因此，监测和减少二氧化碳和甲烷的排放至关重要。如今，大多数城市依靠自下而上的方法来计算总排放量。由于这些估计不是基于直接测量，它们可能具有很大的不确定性，无法识别和定位未知排放源。通过这个项目，我的团队和我将建立一个中尺度监测网络，使用差动柱测量新技术来测量二氧化碳、甲烷、一氧化碳、二氧化氮和臭氧的浓度。这种方法捕捉城市顺风向和迎风向柱量的差异，从而直接反映城市区域内的颗粒物质量负荷。通过这一提议，现有的由两个固定FTIR光谱仪(位于慕尼黑东部和西部)组成的测量系统将扩展为包括一个额外的相同测量系统，以确保不仅可以在西风向测量排放，而且可以在南北风向测量。借助第二个测量系统，传感器网络得到扩展，从而将成为世界上第一个用于测量任何风向的温室气体排放的固定差分柱网络。这将使我们能够准确测量慕尼黑城市地区一段时间内的温室气体排放量，并提供有关内部发电和再分配的信息。除了固定使用外，所请求的系统还可以用于移动，以确定可能的排放源。我们将回答一些关键问题：“慕尼黑几年来二氧化碳、甲烷和二氧化氮排放量的真实测量趋势是什么？”，“排放热点在哪里？”或者“自下而上的估计有多准确？”为此，我的团队不仅将扩展全自动传感器网络，还将开发适合的建模方法(反演模型)，该方法再现颗粒的大气传输，从而回答上述问题。这将是一个全球独一无二的试点项目，并将提供突破性的科学成果。

It is evident that the present global warming is due to anthropogenic greenhouse gas (GHG) emissions. Hence, monitoring and reducing emissions of CO2 and CH4 is essential. Nowadays, most cities rely on bottom-up methods to calculate total emissions. Since these estimates are not based on direct measurements, they can have large uncertainties and are not able to identify and localize unknown emission sources.With this project my group and I will build a mesoscale monitoring network to measure CO2, CH4, CO, NO2, and O3 concentrations using the novel technique of differential column measurements. This method captures the difference in the column amounts downwind and upwind of the city, and therefore directly represents the particle mass loading within an urban domain.By means of this proposal, the existing measurement system consisting of two stationary FTIR spectrometers (in the east and west of Munich) is to be expanded to include an additional identical measurement system to ensure that emissions can not only be measured in the west-eastern, but also in the north-southern wind directions.With the help of this second measurement system, the sensor network is expanded and will thus become the World's first stationary differential column network for measuring greenhouse gas emissions in any wind direction. This will allow us to accurately measure GHG emission rates for Munich’s urban areas over time, and will also yield information about the internal generation and redistribution. In addition to the stationary use, the requested system can also be used mobile to characterize possible emission sources. We will answer key questions such as: "What is the real, measured trend of CO2, CH4 and NO2 emissions in Munich over several years?", "Where are the emission hotspots?" or "How accurate are the bottom-up estimates?"To this end, my group will not only expand the fully automated sensor network but also develop suitable methods for modelling (inversion model), which reproduces the atmospheric transport of the particles and thus answers the questions raised above. It will be a unique pilot project worldwide and will provide ground-breaking scientific results.