Corrosion rates in pipeline systems statistically increase with higher levels of dissolved oxygen, chloride, sulfate, temperature, and conductivity, while factors like alkalinity and hardness tend to reduce corrosion

Joseph Ozigis Akomodi generally the water quality parameters such as pH, dissolved oxygen, chloride, and sulfate concentrations have a significant statistical correlation with corrosion rates in pipeline systems and this is standard anywhwere across the globe. And the elevated chloride and sulfate levels tend to accelerate corrosion, while low pH increases metal solubility and corrosion risk will be seen andthe dissolved O2 enhances the cathodic reaction, further increasing corrosion rates. Multivariate statistical analyses, including regression models, consistently show that these variables.

Srinivas Kasulla

Joseph Ozigis Akomodi

Changes in water quality parameters statistically exert a significant influence on corrosion rates in pipeline systems, and this relationship can be modeled through advanced environmental and statistical approaches. Elevated levels of chloride ions and sulfates are positively correlated with increased corrosion intensity, as these anions destabilize passive protective layers on metal surfaces. Variations in pH have a non-linear effect: lower pH accelerates general corrosion, while higher pH in combination with high alkalinity may favor scaling but also induce localized pitting under certain conditions. Dissolved oxygen concentration is another critical factor, as it fuels electrochemical reactions, and its statistical interaction with temperature frequently reveals synergistic effects in regression or multivariate analyses. Increased turbidity and total dissolved solids (TDS) are often associated with abrasive and chemical stress, which accelerates material degradation. Statistical tools such as multivariate regression, factor analysis, and time-series modeling provide robust insights into how multiple parameters collectively shape corrosion dynamics. From an environmental protection perspective, such analyses are essential not only for predicting material lifetime and optimizing maintenance strategies but also for mitigating the release of heavy metals and corrosion by-products into the environment, thereby safeguarding both ecosystem health and human well-being.