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

很明显，目前的全球变暖是由于人为温室气体（GHG）排放。因此，监测和减少CO2和CH 4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，它们可能有很大的不确定性，并不能识别和定位未知的排放源。通过这个项目，我的团队和我将建立一个中尺度监测网络，测量CO2，CH 4，CO，NO2和O3浓度使用差分柱测量的新技术。该方法捕捉了城市下风向和上风向柱量的差异，因此直接表示了城市区域内的颗粒质量负荷。现有的测量系统由两个固定的FTIR光谱仪组成（在慕尼黑的东部和西部）将被扩大，包括一个额外的相同的测量系统，以确保排放量不仅可以在西部测量-在第二个测量系统的帮助下，传感器网络得到了扩展，将成为世界上第一个用于测量任何风向温室气体排放的固定差分柱网络。这将使我们能够准确地测量慕尼黑城市地区随时间的温室气体排放率，并将产生有关内部生成和再分配的信息。除了固定使用外，所要求的系统还可以移动的使用，以表征可能的排放源。我们将回答一些关键问题，例如：“慕尼黑几年来二氧化碳、甲烷和二氧化氮排放量的真实的测量趋势是什么？“、“排放热点在哪里？或者“自下而上的估计有多准确？““为此，我的团队不仅将扩大全自动传感器网络，还将开发合适的建模方法（反演模型），重现颗粒的大气传输，从而回答上述问题。这将是一个独特的全球试点项目，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.