We found a match
Your institution may have access to this item. Find your institution then sign in to continue.
- Title
Multiple linear regression model for bromate formation based on the survey data of source waters from geographically different regions across China.
- Authors
Yu, Jianwei; Liu, Juan; An, Wei; Wang, Yongjing; Zhang, Junzhi; Wei, Wei; Su, Ming; Yang, Min
- Abstract
A total of 86 source water samples from 38 cities across major watersheds of China were collected for a bromide (Br) survey, and the bromate (BrO) formation potentials (BFPs) of 41 samples with Br concentration >20 μg L were evaluated using a batch ozonation reactor. Statistical analyses indicated that higher alkalinity, hardness, and pH of water samples could lead to higher BFPs, with alkalinity as the most important factor. Based on the survey data, a multiple linear regression (MLR) model including three parameters (alkalinity, ozone dose, and total organic carbon (TOC)) was established with a relatively good prediction performance (model selection criterion = 2.01, R = 0.724), using logarithmic transformation of the variables. Furthermore, a contour plot was used to interpret the influence of alkalinity and TOC on BrO formation with prediction accuracy as high as 71 %, suggesting that these two parameters, apart from ozone dosage, were the most important ones affecting the BFPs of source waters with Br concentration >20 μg L. The model could be a useful tool for the prediction of the BFPs of source water.
- Subjects
BROMATES; BROMATE removal (Water purification); OZONIZATION; REGRESSION analysis; BROMIDES
- Publication
Environmental Science & Pollution Research, 2015, Vol 22, Issue 2, p1232
- ISSN
0944-1344
- Publication type
Article
- DOI
10.1007/s11356-014-3423-5