OrgAlkCalc.py: Estimation of organic alkalinity quantity and acid-base properties titration dataset

Organic alkalinity (OrgAlk) titration data collected using modified Global Ocean Acidification Observing Network (GOA-ON) total alkalinity (TA) titration apparatus is presented in this data article. This titration data was processed using OrgAlkCalc.py, a bespoke Python based non-linear least squares curve fitting program that estimates the quantity and associated acid-base properties of OrgAlk. This allows user to provide estimations of the concentrations and apparent dissociation constants of OrgAlk for inclusion in carbonate system calculations where TA is an input parameter, with the aim to minimize OrgAlk associated error propagation to calculated parameters. The reuse potential of data presented is through its use in user familiarization with OrgAlkCalc.py, allowing carbonate chemistry researchers who utilize GOA-ON TA titration apparatus to gain insights into the quantity and acid-base properties of OrgAlk.

本数据文章展示了采用改良的全球海洋酸化观测网络（Global Ocean Acidification Observing Network，简称GOA-ON）总碱度（Total Alkalinity，简称TA）滴定装置收集的有机碱度（Organic Alkalinity，简称OrgAlk）滴定数据。这些滴定数据经过OrgAlkCalc.py程序的加工处理，该程序是一款基于Python的定制非线性最小二乘曲线拟合软件，用于估算OrgAlk的量及其相关的酸碱性质。这使得用户能够提供OrgAlk的浓度和表观解离常数的估计值，以便将其纳入碳酸盐系统计算中，其中TA作为输入参数，旨在最小化OrgAlk相关误差在计算参数中的传播。所提供数据的重用潜力在于其用于用户对OrgAlkCalc.py的熟悉，使利用GOA-ON TA滴定装置的碳酸盐化学研究人员能够深入了解OrgAlk的量和酸碱性质。