Organic micropollutants (OMPs) in drinking water are a growing concern for environmental and public health organizations throughout the world. OMPs — which encompass pharmaceuticals, personal care products, and pesticides — are included in the priority list of contaminants by the U.S. EPA and are a high priority for the European Environmental Agency. The contaminants were not considered a significant threat until recently, said Sairam Sudhakaran, a researcher at King Abdullah University of Science and Technology in Saudi Arabia.
“There were no proven serious health effects of OMPs on humans until now,” said Sudhakaran. “However, OMPs are now a cause of concern, especially for kids in their developmental stage because exposure could affect their growth.”
OMPs can be particularly difficult to remove from drinking water. To determine the most effective method for removal, Sudhakaran and his team conducted a series of studies and published their results in the paper “Appropriate drinking water treatment processes for organic micropollutants removal based on experimental and model studies”.
Considering a variety of factors, Sudhakaran compared several OMP removal processes: adsorption, ozonation and advanced oxidation processes, membrane-based processes reverse osmosis (RO) and nanofiltration, and natural processes river bank filtration and constructed wetland systems.
Here is a summary of what he found.
Chemical Use: Chemicals are a significant component in several of the methods considered in the studies. Membrane processes ranked the highest for chemical use because they require antiscalants. Oxidation, which requires ozone and peroxide, also was noted as being a chemical-intensive process. The natural processes require the least amount of chemicals.
Maintenance: Typically, natural systems are easier to maintain than advanced treatment systems. The studies determined that riverbank filtration requires the least maintenance followed by constructed wetland systems, ozonation, and adsorption. Membrane filtration systems, like reverse osmosis and nanofiltration, are the most maintenance-heavy systems. This is because they require regular backwashing, replacements, and highly skilled professionals to operate.
Speed: The rate at which a process removes contaminants was also considered. Oxidation processes, along with membrane and absorption processes, remove OMPs more rapidly than natural systems, which require longer residence time.
Land Use: Riverbank filtration and constructed wetland processes require large systems, a factor that should be considered by facilities low on space. Membrane, oxidation, and adsorption processes are much more compact.
Waste Discharge: The studies found that the membrane processes generates the most waste discharge due to its high concentration, backwash, and cleaning solutions. This was considered a disadvantage when compared to oxidation and natural systems, which do not have any waste discharge.
Energy Efficiency: Membrane systems required a large amount of energy to achieve the desired pressure and backwashing. The studies determined that membrane systems are the most energy intensive of the considered methods, releasing a considerable amount of CO2 into the environment. Energy use was also high for ozonation systems and adsorption systems.
Public Acceptance: The studies found that constructed wetlands methods are the least accepted by water treatment professionals. However, it was also noted that the process is slowly becoming more recognized for OMP removal. Membrane processes are accepted but are less popular than other processes, as they are not as environment friendly, are more costly, and can be difficult to operate. Oxidation and adsorption techniques are well-accepted and most preferred by industry professionals, according to Sudhakaran’s paper.
Sudhakaran and his team used a multi-criteria analysis considering all of the above factors and other socio-economic, ecological, and technical criteria to determine which methods were the most effective overall. River-bank filtration and ozonation performed best using this analysis.
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