---
author: Sam White
toc-title: Contents
toc-depth: 5
toc-location: left
date: 2018-04-24 19:43:15+00:00
layout: post
slug: total-alkalinity-calculations-yaaminis-ocean-chemistry-samples
title: Total Alkalinity Calculations - Yaamini's Ocean Chemistry Samples
categories:
  - 2018
  - Miscellaneous
tags:
  - TA
  - titrator
  - total alkalinity
---

I ran a subset of Yaamini's ocean chemistry samples on our T5 Excellence titrator (Mettler Toledo) at the beginning of April. The subset were samples taken from the beginning, middle, and end of the experiment. The rationale for this was to assess whether or not total alkalinity (TA) varied across the experiment. If there was little variation, then there'd likely be no need to run all of the samples. However, should there be temporal differences, then all samples should be processed.

Data analysis was performed in the following R Project:





  * [20180424_yaamini_TA](https://owl.fish.washington.edu/Athaliana/20180424_yaamini_TA/)



The R Project above was initially copied from the R Project for our titrator on GitHub:



  * [https://github.com/RobertsLab/titrator](https://github.com/RobertsLab/titrator)



Three separate, data-file-specific versions of the `TA_calculations.R` script were created and run:





  * [20180402_TA_calculation-01.R](https://owl.fish.washington.edu/Athaliana/20180424_yaamini_TA/scripts/20180402_TA_calculation-01.R)



  * [20180402_TA_calculation-02.R](https://owl.fish.washington.edu/Athaliana/20180424_yaamini_TA/scripts/20180402_TA_calculation-02.R)



  * [20180403_TA_calculation.R](https://owl.fish.washington.edu/Athaliana/20180424_yaamini_TA/scripts/20180403_TA_calculation.R)






Salinity values (PSU) were collected from the following spreadsheet (Google Sheet) and manually entered in each of the R scripts:





  * [Manchester Water Chemistry Data](https://docs.google.com/spreadsheets/d/1NimY1gQFM8eR_wdkM5__nEw3JwEhihmIBHiOqXnBYJ4/edit#gid=84274380)



Specifically, the TA calculations were performed using the `seacarb` library, with the `at()` function.



##### Results:



<table >

<tr >
  sample_names
  TA_values (μmol/kg)
</tr>

<tbody >
<tr >
  
<td >H1 A 2/20/17
</td>
  
<td >2390.88423
</td>
</tr>
<tr >
  
<td >H2 A 2/20/17
</td>
  
<td >2393.39207
</td>
</tr>
<tr >
  
<td >T1 A 2/20/17
</td>
  
<td >2367.78791
</td>
</tr>
<tr >
  
<td >T2 A 2/20/17
</td>
  
<td >2319.39360
</td>
</tr>
<tr >
  
<td >T3 A 2/20/17
</td>
  
<td >2309.88602
</td>
</tr>
<tr >
  
<td >T4 A 2/20/17
</td>
  
<td >2287.72108
</td>
</tr>
<tr >
  
<td >T5 A 2/20/17
</td>
  
<td >2336.14773
</td>
</tr>
<tr >
  
<td >T6 A 2/20/17
</td>
  
<td >2298.36327
</td>
</tr>
<tr >
  
<td >H1 A 3/20/17
</td>
  
<td >2870.73309
</td>
</tr>
<tr >
  
<td >H2 A 3/20/17
</td>
  
<td >2760.49972
</td>
</tr>
<tr >
  
<td >T1 A 3/20/17
</td>
  
<td >2930.29308
</td>
</tr>
<tr >
  
<td >T2 A 3/20/17
</td>
  
<td >2925.95472
</td>
</tr>
<tr >
  
<td >T3 A 3/20/17
</td>
  
<td >2896.55123
</td>
</tr>
<tr >
  
<td >T4 A 3/20/17
</td>
  
<td >2769.72514
</td>
</tr>
<tr >
  
<td >T5 A 3/20/17
</td>
  
<td >2743.33934
</td>
</tr>
<tr >
  
<td >T6 A 3/20/17
</td>
  
<td >2727.94064
</td>
</tr>
<tr >
  
<td >H1 A 4/4/17
</td>
  
<td >2770.20971
</td>
</tr>
<tr >
  
<td >H2 A 4/4/17
</td>
  
<td >2656.27437
</td>
</tr>
<tr >
  
<td >T1 A 4/4/17
</td>
  
<td >2801.77913
</td>
</tr>
<tr >
  
<td >T2 A 4/4/17
</td>
  
<td >2822.51611
</td>
</tr>
<tr >
  
<td >T3 A 4/4/17
</td>
  
<td >2800.87387
</td>
</tr>
<tr >
  
<td >T4 A 4/4/17
</td>
  
<td >2584.60933
</td>
</tr>
<tr >
  
<td >T5 A 4/4/17
</td>
  
<td >2645.37017
</td>
</tr>
<tr >
  
<td >T6 A 4/4/17
</td>
  
<td >2604.22677
</td>
</tr>
</tbody>
</table>

Well, it certainly looks like there's some variation across the experiment. It's likely that all remaining samples will need to be processed. Will pass along data to Yaamini for her to evaluate.
