Understanding the potential for selective natural organic matter removal by ion exchange

P Finkbeiner,J Redman,V Patriarca,G Moore,B Jefferson,P Jarvis

doi:10.1016/j.watres.2018.09.042

P Finkbeiner, J Redman + Show 4 more

Open Access

https://doi.org/10.1016/j.watres.2018.09.042

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Abstract

Dissolved organic carbon (DOC) removal from a river water source was investigated using ion exchange (IEX), coagulation and membrane filtration. This research linked the variable charge characteristics of the organic compounds present in the source water with removal by IEX and coagulation. The raw water charge density fluctuated considerably (between 5.4 and 10.7 meq mgDOC−1) and controlled removal of the charge loading. Importantly, charge density was not correlated with the organic carbon concentration. The combined IEX and coagulation process reduced the specific DBP-FP (sDBP-FP) of the final water, with values as low as 18 μg mgDOC−1 for both haloacetic acids and trihalomethanes. IEX removed a particular fraction of NOM that 1) enhanced coagulation efficiency, providing increased removal of overall DOC; and 2) enabled coagulation to subsequently remove higher levels of specific components of NOM that have a high DBP-FP. The component of NOM removed by IEX that had a positive impact on coagulation was identified to be charged low molecular weight organic compounds of all hydrophobicity levels, resulting in a reduced specific DBP-FP compared to coagulation alone.

Highlights

Climate change impact studies are largely based on climatic projections simulated by climate models
The three sets are: a subset of five CMIP5 GCMs used in the ISIMIP; a subset of Euro-CORDEX simulations performed by one Regional climate models (RCMs) with common driving models as the ISIMIP; and, a set of new high-resolution AGCM simulations including the common driving
The three sets are: a subset of five CMIP5 GCMs used in the ISIMIP; a subset of Euro-CORDEX simulations performed by one RCM with common driving models as the ISIMIP; and, a set of new high-resolution AGCM simulations including the common driving GCMs of the first two subsets

Summary

Introduction

Climate change impact studies are largely based on climatic projections simulated by climate models. This inevitably leads to compromises in terms of the number of models used. These constraints, combined with the need for the most representative sample, have led to the development of methods for the identification of fewer. Water 2018, 10, 1331 representative models [1,2] These models constitute a subset of a larger model ensemble and are considered to account for a significant space of the potential climate changes as simulated by the total ensemble, with the benefit of reducing the number of laborious impact simulations. Downsizing of the ensemble involves several risks, such as omitting part of the uncertainty of the original ensemble and skewing regional or seasonal climate change signals towards the model subset [3]

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