Reverse Osmosis Modeling Study of Lead and Arsenic Removal from Drinking Water in Tarija and La Paz, Bolivia

Abstract

An investigation of primary water sources in two Bolivian basins identified the presence of heavy metals toxic to health that exceeded the permissible limits for drinking water. Lead deposited in the San Jacinto and Huacata–Tarija reservoirs within the Guadalquivir basin and arsenic in the Milluni–La Paz basin were identified. The work studies reverse osmosis (RO) to remove Pb and As. The main contribution of this research is the development and construction of a mathematical model based on the Spiegler–Kedem concentration polarization model using different concentrations of Pb and As. The model makes it possible to design high conversion facilities (>80%) and optimize the process from the point of view of energy efficiency in future works. The model was developed to also include an Arrhenius temperature adjustment factor that allows for an accurate prediction of the process performance. The experimentation was carried out in two RO pilot plants using polyamide membranes. The model fits correctly with a maximum relative error between the experimental and theoretical flows of 5.4% and 4.4%. Among the benefits of the study, it guarantees the rejection of metals greater than 99%, even at low pressures.

A Comparative Analysis of Statistical Models and Mathematics in Reverse Osmosis Evaluation Processes as a Search Path to Achieve Better Efficiency

“…The Kedem model describes the physical behavior of the reverse osmosis membrane. In experiments on a laboratory scale [42], it was shown that at low pressures, 5 to 10 bar, an efficiency in the removal of heavy metals of up to 99% is achieved.…”

Critical Analysis of Stakeholders in the Municipality of Tarija, Bolivia, in Search of Strategies for Adequate Water Governance to Implement Reverse Osmosis as an Alternative for Generating Safe Water for Its Inhabitants

“…Bolivia has experienced significant population growth and unorganized development, which has led to a growing and sustained process of water contamination in various areas of the country. Similarly, several water sources in the Municipality of Tarija, Bolivia, present toxic contaminants, such as heavy metals, which represent a risk to the public health of the population [4][5][6][7][8].…”

“…Political, social, and cultural differences hinder the implementation of public policies and the execution of investment projects. Recent investigations carried out in Tarija and La Paz, Bolivia [16], demonstrate the effectiveness of the removal of toxic contaminants present in drinking water through reverse osmosis. The results show that reverse osmosis can be implemented at low operating pressures, demonstrating significant sustainability in terms of energy and economic efficiency [16][17][18].…”

“…The management of water and energy resources will be more efficient when "active water citizens" increase environmental awareness by promoting monitoring measures and data collection, which significantly increases public motivation and environmental awareness for the efficient use of natural resources. Economic growth accompanied by global climate change exerts more significant pressure on conventional sources of drinking water, and it is necessary and urgent to create cooperative, sustained, and sustainable projects capable of supplying safe water with fewer risks, lower costs, and better technologies [13][14][15][16][17][18][19][20][21][22][23][24].…”

Mathematical and Statistical Evaluation of Reverse Osmosis in the Removal of Manganese as a Way to Achieve Sustainable Operating Parameters

“…For this reason, an adjustment was made to the temperature factor that was based on the Arrhenius model to prevent this factor from influencing the response variables. Several mathematical models have described the mass transfer and hydrodynamic permeability in RO systems [58]. Using a mathematical model that expresses the performance of the RO process is a mechanism that could help to reduce operating costs [59], but it is also necessary to complement the study of the process through statistical analysis, which focuses on the outputs and inputs to know the behavior of the RO and to be able to optimize it [50].…”