자료유형  

 학위논문

Control Number  

0015490390

International Standard Book Number  

9781085562034

Dewey Decimal Classification Number  

551

Main Entry-Personal Name  

Martin, Cory Ray.

Publication, Distribution, etc. (Imprint  

[Sl] : University of Maryland, College Park, 2018

Publication, Distribution, etc. (Imprint  

Ann Arbor : ProQuest Dissertations & Theses, 2018

Physical Description  

186 p

General Note  

Source: Dissertations Abstracts International, Volume: 81-02, Section: B.

General Note  

Advisor: Zeng, Ning.

Dissertation Note  

Thesis (Ph.D.)--University of Maryland, College Park, 2018.

Restrictions on Access Note  

This item is not available from ProQuest Dissertations & Theses.

Restrictions on Access Note  

This item must not be sold to any third party vendors.

Summary, Etc.  

요약Current inverse modeling-based estimates of carbon dioxide (CO2) fluxes in urban areas typically use a network of 10-20 observation sites featuring high-accuracy gas analyzers that can cost over $100,000 each. Recently, commercially available, low-cost sensors to measure both traditional meteorological quantities and trace gases such as CO2 have become a focus of atmospheric science research. These flux estimations are an ill-posed problem in the sense that, depending on resolution, the mathematical model may be optimizing fluxes for hundreds or even thousands of grid points, with only relatively few observations to use as constraint. Theoretically, by introducing many more observations into the system, the result will better represent the true state of the surface fluxes.This work comprises of three related studies that evaluate the viability of using a low-cost CO2 sensor combined with a mesoscale meteorology model with online tracers, and an advanced ensemble data assimilation technique, to estimate surface fluxes of CO2 in an urban region. First, the SenseAir K30 sensor is evaluated compared to a reference gas analyzer to determine the accuracy and precision of the observations from this sensor. Next, a simulation of atmospheric CO2 is evaluated against observations to understand the error in simulated mole fractions from variations in existing emissions inventories. Finally, a series of observing system simulation experiments (OSSEs) are conducted to understand the sensitivity of estimated CO2 fluxes to the ensemble data assimilation system configuration.From this work, it is found that the K30 sensor can be useful for urban ambient monitoring of CO2 after corrections for environmental factors such as temperature and pressure. Additionally, the modeled CO2 results show that the error in simulated mole fractions is likely larger from meteorological error than it is from uncertainty in emissions. Finally, the OSSEs find that this ensemble data assimilation system using a dense network of lower-accuracy observations can achieve comparable CO2 flux estimation results to that of using a sparse network of high-accuracy observations. However, the configuration of the system, particularly the inflation technique used, can significantly affect the quality of the analyzed fluxes.

Subject Added Entry-Topical Term  

Atmospheric chemistry

Added Entry-Corporate Name  

University of Maryland, College Park Atmospheric and Oceanic Sciences

Host Item Entry  

Dissertations Abstracts International. 81-02B.

Host Item Entry  

Dissertation Abstract International

Electronic Location and Access  

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Control Number  

joongbu:567402