Sparging chamber test results of radon activity from laboratory experiments to optimize chamber configuration for Radon-222 analysis

Website: https://www.bco-dmo.org/dataset/827014
Data Type: experimental
Version: 0
Version Date: 2020-10-19

Project
» Collaborative Research: Development of a Submersible, Autonomous Rn-222 Survey System (Submersible Rn-222)
ContributorsAffiliationRole
Peterson, Richard N.Coastal Carolina UniversityPrincipal Investigator
Breier, JohnWoods Hole Oceanographic Institution (WHOI)Co-Principal Investigator
Copley, NancyWoods Hole Oceanographic Institution (WHOI BCO-DMO)BCO-DMO Data Manager

Abstract
These data were collected in order to optimize a new method for degassing dissolved radon-222 from water. The general premise is the use of a sparging chamber (‘Bell’) that is deployed underwater and uses bubbles to degas the radon. This dataset includes the experimental (Bell) results. See also the control dataset (https://www.bco-dmo.org/dataset/826844). See methodology outlined in Peterson et al., 2013 (Journal of Radioanalytical and Nuclear Chemistry). The sparging chamber is connected to a commercially-available radon-in-air monitor (RAD7; Durridge Co.) via a closed air loop. Air exiting the RAD7 circulates to the bottom of the sparging chamber where it enters via aquarium bubblers. The bubbles rise through the sparging chamber and accumulate in a headspace, from which air is pumped through desiccant back to the RAD7. Our control to which we compare the sparging chamber is the commercially-available RAD-Aqua (Durridge Co.) which sprays a water sample into a chamber rather than using bubbles. Otherwise, the setups are similar. Data contained herein are various laboratory testing configurations to optimize dimensions of the sparging chamber, number and type of bubblers, and any benefits from adding an additional sprayer capability to the top of the sparging chamber. All configurations tested are accompanied by a number of replicates.


Coverage

Temporal Extent: 2010-09-21 - 2012-08-02

Dataset Description

These data were collected in order to optimize a new method for degassing dissolved radon-222 from water. This dataset includes the experimental (Bell) results. See also the control dataset (https://www.bco-dmo.org/dataset/826844). The general premise is the use of a sparging chamber (‘Bell’) that is deployed underwater and uses bubbles to degas the radon. 


Methods & Sampling

See methodology outlined in Peterson et al., 2013 (Journal of Radioanalytical and Nuclear Chemistry). The sparging chamber is connected to a commercially-available radon-in-air monitor (RAD7; Durridge Co.) via a closed air loop.  Air exiting the RAD7 circulates to the bottom of the sparging chamber where it enters via aquarium bubblers.  The bubbles rise through the sparging chamber and accumulate in a headspace, from which air is pumped through desiccant back to the RAD7.  

Our control to which we compare the sparging chamber is the commercially-available RAD-Aqua (Durridge Co.) which sprays a water sample into a chamber rather than using bubbles.  Otherwise, the setups are similar.

Data contained herein are various laboratory testing configurations to optimize dimensions of the sparging chamber, number and type of bubblers, and any benefits from adding an additional sprayer capability to the top of the sparging chamber.  All configurations tested are accompanied by a number of replicates.


Data Processing Description

BCO-DMO Processing Notes:
- data submitted in 57 Excel files, Sheet name "Bell_2675" and an Excel file "Sample Summary.xlsx", sheet "Run Summary", and extracted to csv
- the 57 files were concatenated and joined with the summary file, adding columns: Date, Chamber, Bubblers, Sprayer_Status, Water_Source, Bell_RAD7_SN, Exchanger_RAD7_SN.
- added conventional header with dataset name, PI name, version date
- modified parameter names to conform with BCO-DMO naming conventions
- added 'ISO_DateTIme' column, re-formatted date from m/d/yyyy to yyyy-mm-dd
- in 'Chamber' column, replaced " with -inch
- replaced #DIV/0! with nd for /no data'
- formatted date-time column to ISO_DateTime (yyyy-mm-ddTHH:MM:SS)


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Related Publications

Peterson, R. N., Breier, J. A., Harmon, L. R., Brusa, J., & Hutchins, P. R. (2013). Development of a sparging chamber for field radon analysis. Journal of Radioanalytical and Nuclear Chemistry, 298(2), 1347–1357. doi:10.1007/s10967-013-2589-5
Results

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Parameters

ParameterDescriptionUnits
resource_namefile name of originally submitted Excel file; suffix -1 indicates first sheet; suffix -2 indicates second sheet unitless
DateISO-formatted date when data was logged (yyyy-mm-dd) unitless
Chamberdescription of the sparging chamber: height and width?? unitless
Bubblers?number and type of bubblers: default = ??; micro = ??; bubblestone = an aqurium air stone was used to create bubbles unitless
Sprayer_Statusindicates whether a spray chamber was employed or not unitless
Water_Sourcewater source; tap water ; high to low = ??; withers swash = ?? unitless
Bell_RAD7_SNserial number of Bell RAD7 Radon detector unitless
Exchanger_RAD7_SNserial number of the Exchanger RAD7 Radon detector unitless
TestRAD7 test (cycle) number unitless
ISO_DateTimeISO-formatted date and time when data was logged (yyyy-mm-ddTHH:MM:SS) unitless
Year2 digit year during which data was logged None
Month2 digit month during which data was logged None
Day2 digit day of the month during which data was logged None
Hour2 digit hour of the day (24 hour clock) during which data was logged None
Min2 digit minute of the hour during which data was logged None
Tot_CountTotal numbers of counts logged by the RAD7 during the cycle counts
Live_TimeTime during which active counting occurred for the cycle minutes
Win_A_pcntPercentage of total counts falling in Window A (radon sniff mode) percent
Win_B_pcntPercentage of total counts falling in Window B (thoron 1 window) percent
Win_C_pcntPercentage of total counts falling in Window C (radon Po-214 window) percent
Win_D_pcntPercentage of total counts falling in Window D (thoron 2 window) percent
HVHigh voltage level volts
HV_duty_cycleHigh voltage duty cycle percent
TempAir temperature within RAD7 degrees Celsius
RelHumidityRelative humidity of sampled air percent
Leak_currLeakage current milliAmps
Batt_VoltBattery voltage volts
Pump_CurrAir pump current draw milliAmps
Flags_ByteBit 0 indicates whether pump is in Timed Mode; Bit 1 indicates whether pump is On continuously; Bit 2 is not defined; Bit 3 indicates whether tone is in Geiger mode; Bit 4 indicates whether beeper is activated; Bit 5 indicates if spectrum will print after each test; Bit 6 indicates if there are multiple (recycle) tests; Bit 7 indicates whether RAD7 is in Sniff test mode unitless
Bq_m3Radon Concentration in sampled air becquerels per cubic meter (Bq/m3)
Error_2sigma2-sigma uncertainty of the radon concentration in sampled air becquerels per cubic meter (Bq/m3)
Units_ByteBits 0 and 1 indicate the concentration unit: 00 = counts per minute; 01 = number of counts; 10 = Bq/m3; 11 = pCi/L; Bit 2 through Bit 6 are not defined; Bit 7 indicates the temperature unit (0 = deg. F; 1 = deg. C) unitless
Elapsed_TimeAmount of time elapsed into the entire measurement minutes
Count_Rate_Win_A_cpmThe total counts multiplied by the % in window A (divided by 100); then divided by the Live_Time counts per minute
Win_A_error1-sigma uncertainty of the Window A count rate (taken as the square root of the total counts multiplied by the % in window A (divided by 100); all of which is then divided by the Live Time) counts per minute
Rn_Activity_Air_dpm_LRadon activity in the air calculated as the count rate in window A divided by the RAD7 Sniff Mode sensitivity; then multiplied by 2.22 to convert from pCi/L to dpm/L decays/minute/liter (dpm/L)
Air_error1-sigma uncertainty of the radon activity in the air (taken as column AB divided by the RAD7 Sniff mode sensitivity then multiplied by 2.22 to convert from pCi/L to dpm/L decays/minute/liter (dpm/L)
Water_TempTemperature of the water; measured via an Onset Corp. HOBO water level logger degrees Celsius
Conversion_FactorSolubility coefficient for radon; calculated as 0.105+0.405*EXP(-0.0502*Water Temp) unitless
Rn_Activity_Water_dpm_LRadon activity in the water calculated as the radon activity in air multiplied by the solubility coefficient decays/minute/liter (dpm/L)
Water_error1-sigma uncertainty of the radon activity in the water (taken as column AD multiplied by the solubility coefficient decays/minute/liter (dpm/L)
Smoothed3-point smoothing function for the radon activity in water decays/minute/liter (dpm/L)
pcnt_EquilibrationPercentage of radon activity in water measured by the Bell relative to that measured by the Exchanger (control) percent


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Instruments

Dataset-specific Instrument Name
HOBO water level data logger (Onset Corp.)
Generic Instrument Name
Temperature Logger
Generic Instrument Description
Records temperature data over a period of time.

Dataset-specific Instrument Name
RAD7 radon-in-air monitors (Durridge Co.)
Generic Instrument Name
RAD-7 Radon Detector
Dataset-specific Description
Data presented here were analyzed with 4 different RAD7 radon-in-air monitors (Durridge Co.).  These instruments were calibrated annually by the manufacturer.  Relevant serial numbers and corresponding Sniff Mode Sensitivities (in pCi/L) are: 2172: 0.236 2604: 0.383 2675: 0.224 2685: 0.401  
Generic Instrument Description
The DURRIDGE RAD7 is a radon and thoron detector. The RAD7 is a computer-driven electronic detector, with pre-programmed set-ups for common tasks. It's built to withstand everyday use in the field. A rugged case encloses the detector, which is self-contained and self-sufficient. The RAD7 comes with a built-in air pump, rechargeable batteries, and a wireless infrared printer. (https://durridge.com/products/rad7-radon-detector/)


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Project Information

Collaborative Research: Development of a Submersible, Autonomous Rn-222 Survey System (Submersible Rn-222)


Coverage: Coastal Carolina University; Woods Hole Oceanographic Institution


The PI's request funding to develop a submersible system capable of in situ 222Rn analysis while deployed from a remotely-operated vehicle (ROV) or autonomous underwater vehicle (AUV). Such a system would allow researchers to conduct high-resolution radon surveying through 3-D grids of bottom water and later return to sites of interest to measure a 222Rn time-series in order to quantify SGD fluxes. The system design relies on a new technique to sparge radon, while submerged, from the water for analysis via bubbling a closed air loop through a contained water column. Preliminary evidence shows this to be a viable approach.

Submarine groundwater discharge (SGD) is quickly gaining recognition as an important delivery mechanism of new and recycled nutrients to the coastal ocean. Chemical tracers such as 222Rn and radium isotopes offer excellent utility at detecting groundwater discharge zones and quantifying associated fluxes in nearshore (shallow) waters, but the traditional approaches to sampling and measuring these tracers become progressively less useful as the water column deepens, stratification strengthens, and physical mixing becomes more complex. In deeper waters (1) of the continental shelf where outcropping geological units can focus SGD, and (2) around critical habitats like coral reef ecosystems, one?s ability to measure these tracers is limited to grab sampling-scale resolution. Such resolution is generally not sufficient to understand the pathways, driving forces, and rates of these discharges, nor is it conducive to quantifying associated nutrient delivery fluxes. Prior to assessing the global significance of SGD, then, there exists great need for a tool capable of in situ, continuous measurement of geochemical tracers of SGD in deeper waters of the continental shelf.

Broader Impacts:

Since this proposed study develops a new research tool available for other scientists, the success of this study will have a large and broad impact on SGD studies in important deep basins, hydrothermal studies quantifying hydrothermal flow, and deep-water circulation and mixing studies using Rn-222 as a tracer. The investigators have included a plan for outreach to sponsor a two-semester, senior Design Clinic team of 3-4 undergraduate female engineering students from Smith College's Picker Engineering Program. This undergraduate team will gain experience working on a real-world engineering problem and this project will likewise benefit from their engineering contribution. Breier has undertaken a similar collaboration with Smith College for the NDSF microbial mat sampler project and the results to both sides have been outstanding. Breier and Singh will also mentor a MIT/WHOI Joint Program Ph.D. student as part of this project, with the hope that one of the Smith College engineering students may make this transition. Peterson will also serve as an undergraduate mentor.



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Funding

Funding SourceAward
NSF Division of Ocean Sciences (NSF OCE)
NSF Division of Ocean Sciences (NSF OCE)

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