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ABL Parameterization

Sensor Networks

Large Eddy Simulations

Multiscale Atmospheric Simulations

Urban Micrometeorology and Energy Studies

Turbulence Structure

Distributed Sensor Networks

Past observational work has mainly focused on understanding individual processes under idealized conditions by deploying a limited number of sensing stations at carefully selected locations. This approach, while useful, is not suited for "real-world" applications where a range of environmental processes are interacting in complex domains. To help us move in the direction of sensing solutions for the "real-world", significant research and development activities have focused in the past decade on distributed sensor networks. These networks overcome many of the shortcomings of other sensing approaches such as: limited spatial coverage of point sensors, ground-truthing requirements and limited spatial resolution of satellite data, limited temporal resolution of aircraft data, ...

A distributed sensor network consists of many "nodes" each with a set of sensors that are selected depending on the medium and problem being investigated. Such a distributed sensing approach can:

  • Continuously monitor the environment with high spatial and temporal resolutions.

  • In combination with models of different complexity, provide information about the general environmental conditions over the monitored area (possibly in real-time).

  • Automatically manage the data and provide concise, relevant information to end-users.

For such extensive observational networks to be realistic and affordable, the large majority of the nodes and sensors should be low-cost, low-maintenance, low-power and should allow for wireless data transmission. At the same time, the networks should integrate any available high-end stations with more sophisticated, new-generation sensors. With collaborators at Princeton (Jim Smith, Mark Zondlo, and Gerard Wysocki), we are planning to deploy such a wireless sensor network over the Princeton campus and to develop of new-generation trace-gas sensors that will be integrated in this network. This project greatly benefits from sensor system development efforts at the MIRTHE (Mid-Infrared Technologies for Health and the Environment) center at Princeton.

This project, the Sensor Network over Princeton (SNOP), will partially use technologies developed by collaborators at the Ecole Polytechnique Federale de Lausanne (http://sensorscope.epfl.ch). The stations (see pictures below) will includes the following sensors: 1) temperature and relative air humidity, 2) soil moisture and temperature probe 3) soil pore pressure, 4) incoming and reflected solar radiation, 5) surface temperature, 6) wind speed and direction, and 7) precipitation.

The sensor network will have significant impacts on the Princeton Sustainability Initiative in the fields of energy, water and carbon:

Energy: The data collected will be used to simulate heat exchange between the buildings and the atmosphere and estimate energy consumption loads. This will allow us to detect the most important parameters affecting energy consumption (e.g. wind speed, air temperature and humidity, incoming radiation, ...)

Water: The measurement stations will yield direct measurements of precipitation, direct (eddy covariance) and indirect (using measured soil moisture, air relative humidity, and wind speed) measurements of evaporation, and water storage in the soil (soil moisture), which can then be used with the campus hydrological model developed by collaborators in the The Hydrometeorology Research Group.

Carbon: A CO2 sensor, based on a QC laser operating at a wavelength near 4.3 μm to probe the strongest fundamental absorption band of CO2, will be developed by Mark Zondlo and Gerard Wysocki from MIRTHE. In contrast to existing sensors, only a very simple, robust, and inexpensive, optomechanical arrangement is needed. By probing two absorption lines of two carbon dioxide isotopes (12CO2 and 13CO2) that have vastly different temperature dependencies, the sensors will also yield highly accurate (0.1 K) and fast temperature (10 Hz) measurements. In combination with other data in the network, these sensors will thus allow us to probe ambient CO2 concentrations and air temperature, two measurements critical for determining surface fluxes of CO2 and heat.

 

Sensor Network Over Princeton (SNOP)

Princeton campus is used as a test bed for field campaigns and for development of environmental systems under MIRTHE (Mid-Infrared Technologies for Health and the Environment). Sensing instruments deployed include:

Eddy-Covariance (EC) station: A standard EC station was deployed on the roof of B-Wing, Engineering Quad, measuring meteorological quantities such as wind, atmospheric/surface temperature, relative humidity, four-component radiative budgets and turbulent heat (sensible + latent) and trace gas (CO2) fluxes.

Scintillometer: A small aperture scintillometer crosses Olden street, measuring wind drag and vertical fluxes of sensible heat.

Wireless sensor network (Sensorscope): A network of (11) sensorscope stations was deployed at the roof and ground level around E-Quad building, measuring wind, temperature, humidity, soil moisture, precipitation and solar radiation. To view the real time distribution of the stations and data, visit http://efm.princeton.edu/snop

SODAR/RASS: deployed at
Forestal campus, measuring atmospheric boundary layer (ABL) profiles of wind and temperature.

last update on: August 05, 2011 14:02,  contact webmaster

Contact Information

Elie Bou-Zeid
Department of Civil & Environmental Engineering
Princeton University, C326 EQuad
Princeton, NJ 08544, USA

phone  :  +1-609-258-5429
fax        :  +1-609-258-2799
email   :  
ebouzeid@princeton.edu
web      :  http://efm.princeton.edu/