The effect of several prevalent cations (including Na+, K+, Mg2+, Ca2+, Al3+, and Fe3+) on the adsorption of monochlorobenzene (MCB) onto bentonite was investigated at the coexistence of nonionic surfactant Tween 80 (T80) in surfactant-enhanced remediation (SER). They are all favorable for MCB and T80 adsorption, especially Mg2+ and Ca2+. Adsorption of MCB is strongly depended on T80 micelles. When its concentration exceeds the solubility, MCB is easier to bind with T80 micelles and be adsorbed by bentonite. Acidic environment can facilitate MCB and T80 adsorption, but the effect of cations on the adsorption is most significant under alkaline conditions. Adsorption capacity of MCB increases first followed by a slight decrease with increasing cations concentrations. The maximum adsorption rate of MCB determined is about 68.4% in a solution containing Mg2+ in the isothermal adsorption of MCB, while it is only 6.8% in a cation -free solution. Various characterizations showed that cations mainly changed the repulsion between bentonite particles and T80 micelles and the agglomeration and structure of bentonite, thus affecting the adsorption of MCB and T80 micelles. Our research demonstrated the nonnegligible promotion of MCB adsorption on bentonite by cations and acidic environment, which will adversely affect SER efficiency.

Onshore pipelines are exposed to corrosion degradation, facilitated by the pipeline's management and surrounding aggressive environmental conditions. Every 2 to 6 years, pipeline operators often conduct In -Line (ILI) inspections to screen for pipe damage using magnetic or ultrasonic sensors. Considering soil and fluid aggressive conditions, and the possibility of false alarms or a miss-detections from the inspection device, new defects, i.e., metal loss at either the inner or outer wall, should be expected to occur between consecutive inspections. Considering the possibility of corrosion coloniesand their significance in the pipeline's reliability assessment, different authors have incorporated new corrosion defects in degradation and further reliability assessments using a Homogeneous Poisson Process. This process assumes that corrosion points are evenly distributed, which can be classified as conservative. This study aims to characterize the main spatial distribution of corrosion defects using the Complete Spatial Randomness (CSR) assumption under hypothesis testing. Additionally, it assesses how is the interaction between new and old defects from a repulsion-attraction perspective, and it proposes an alternative to simulate them for further reliability analyses. The suggested approach was applied in a real case study, obtaining that corrosion defects tend to be clustered and little repelled from those already detected.