Theoretical and Applied Climatology

, Volume 127, Issue 3–4, pp 627–642 | Cite as

Quantifying the local influence at a tall tower site in nocturnal conditions

  • David WerthEmail author
  • Robert Buckley
  • Gengsheng Zhang
  • Robert Kurzeja
  • Monique Leclerc
  • Henrique Duarte
  • Matthew Parker
  • Thomas Watson
Original Paper


The influence of the local terrestrial environment on nocturnal atmospheric CO2 measurements at a 329-m television transmitter tower (and a component of a CO2 monitoring network) was estimated with a tracer release experiment and a subsequent simulation of the releases. This was done to characterize the vertical transport of emissions from the surface to the uppermost tower level and how it is affected by atmospheric stability. The tracer release experiment was conducted over two nights in May of 2009 near the Department of Energy’s Savannah River Site (SRS) in South Carolina. Tracer was released on two contrasting nights—slightly stable and moderately stable—from several upwind surface locations. Measurements at the 329-m level on both nights indicate that tracer was able to mix vertically within a relatively short (∼24 km) distance, implying that nocturnal stable conditions do not necessarily prevent vertical dispersion in the boundary layer and that CO2 measurements at the tower are at least partly influenced by nearby emissions. A simulation of the tracer release is used to calculate the tower footprint on the two nights to estimate the degree to which the local domain affects the tower readings. The effect of the nocturnal boundary layer on the area sampled by the tower can be seen clearly, as the footprints were affected by changes in stability. The contribution of local sources to the measurements at the tower was minimal, however, suggesting that nocturnal concentrations at upper levels are contributed mostly by regional sources.


Planetary Boundary Layer Stable Boundary Layer Boundary Layer Height Nocturnal Boundary Layer Turbulence Kinetic Energy Budget 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



This document was prepared by members of the Savannah River National Laboratory (SRNL) in conjunction with work accomplished under Contract No. DE-AC09-08SR22470 with the U.S. Department of Energy. Funding support was provided to SRNL, the University of Georgia and Brookhaven National Laboratory by the DOE Office of Science – Terrestrial Carbon Processes program.

Compliance with ethical standards


This work was prepared under an agreement with and funded by the U.S. Government. Neither the U. S. Government or its employees, nor any of its contractors, subcontractors or their employees, makes any express or implied: 1. warranty or assumes any legal liability for the accuracy, completeness, or for the use or results of such use of any information, product, or process disclosed; or 2. representation that such use or results of such use would not infringe privately owned rights; or 3. endorsement or recommendation of any specifically identified commercial product, process, or service. Any views and opinions of authors expressed in this work do not necessarily state or reflect those of the United States Government, or its contractors, or subcontractors.


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Copyright information

© Springer-Verlag Berlin Heidelberg (outside the USA) 2015

Authors and Affiliations

  • David Werth
    • 1
    Email author
  • Robert Buckley
    • 1
  • Gengsheng Zhang
    • 2
  • Robert Kurzeja
    • 1
  • Monique Leclerc
    • 2
  • Henrique Duarte
    • 2
  • Matthew Parker
    • 1
  • Thomas Watson
    • 3
  1. 1.Savannah River National LaboratoryAikenUSA
  2. 2.Laboratory for Atmospheric and Environmental PhysicsUniversity of GeorgiaGriffinUSA
  3. 3.Tracer Technology GroupBrookhaven National LaboratoryUptonUSA

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