TY - JOUR
T1 - Predicting distribution coefficients for antibiotics in a river water–sediment using quantitative models based on their spatiotemporal variations
AU - Tang, Jinpeng
AU - Wang, Sai
AU - Fan, Jingjing
AU - Long, Shengxin
AU - Wang, Lin
AU - Tang, Chen
AU - Tam, Nora Fungyee
AU - Yang, Yang
N1 - Publisher Copyright:
© 2018 Elsevier B.V.
PY - 2019/3/10
Y1 - 2019/3/10
N2 - Antibiotics are widely used in humans and animals, but their presence in environmental matrices after use is of great concern. Distribution behavior of antibiotics in natural water–sediment systems is influenced by sediment properties, but how these properties, such as surface area, affect their distribution between water and sediment phases remains unclear. The concentrations of antibiotics also vary both spatially and temporally. In this study, a solid/liquid distribution coefficient Kd(pre) was proposed and evaluated in 12 quantitative predicting models based on aquatic field data compared with a bulk coefficient Kd. Results confirmed by the occurrence pattern, concentration levels and spatiotemporal distributions indicated that the characteristics of antibiotics pollution in rural northwestern Guangzhou were generally consistent with previous investigations, suggesting that this investigation was representative of the present aquatic pollution status of antibiotics. The median concentrations were <100 ng·L −1 and 220 ng·g −1 (d.w.) in the water and sediments, respectively. The most pronounced high concentrations of total antibiotic residue found were 778.0 ng·L −1 for sulfonamides (SAs) in water and 1596.9 ng·g −1 (d.w.) for fluoroquinolones (FQs) in sediments at site 13 in December of 2016, probably due to its dense population, high frequency of antibiotic use and low water flow. Moreover, 12 quantitative models were established with a high level of robustness and ability to spatiotemporally predict the Kd for each of the 12 antibiotics. The models revealed that pH, organic matter and specific surface area of sediments played significant roles in influencing the adsorption of SAs, FQs, tetracyclines (TCs) and (macrolides) MLs. Our findings provide insights into the effects of physicochemical properties on distribution of antibiotics, predicting their fate and transport, as well as assessments of exposure and risk of these emerging pollutants to aquatic ecosystems.
AB - Antibiotics are widely used in humans and animals, but their presence in environmental matrices after use is of great concern. Distribution behavior of antibiotics in natural water–sediment systems is influenced by sediment properties, but how these properties, such as surface area, affect their distribution between water and sediment phases remains unclear. The concentrations of antibiotics also vary both spatially and temporally. In this study, a solid/liquid distribution coefficient Kd(pre) was proposed and evaluated in 12 quantitative predicting models based on aquatic field data compared with a bulk coefficient Kd. Results confirmed by the occurrence pattern, concentration levels and spatiotemporal distributions indicated that the characteristics of antibiotics pollution in rural northwestern Guangzhou were generally consistent with previous investigations, suggesting that this investigation was representative of the present aquatic pollution status of antibiotics. The median concentrations were <100 ng·L −1 and 220 ng·g −1 (d.w.) in the water and sediments, respectively. The most pronounced high concentrations of total antibiotic residue found were 778.0 ng·L −1 for sulfonamides (SAs) in water and 1596.9 ng·g −1 (d.w.) for fluoroquinolones (FQs) in sediments at site 13 in December of 2016, probably due to its dense population, high frequency of antibiotic use and low water flow. Moreover, 12 quantitative models were established with a high level of robustness and ability to spatiotemporally predict the Kd for each of the 12 antibiotics. The models revealed that pH, organic matter and specific surface area of sediments played significant roles in influencing the adsorption of SAs, FQs, tetracyclines (TCs) and (macrolides) MLs. Our findings provide insights into the effects of physicochemical properties on distribution of antibiotics, predicting their fate and transport, as well as assessments of exposure and risk of these emerging pollutants to aquatic ecosystems.
KW - Antibiotic
KW - Predictive model
KW - Sediment physicochemical property
KW - Water-sediment distribution coefficient
UR - http://www.scopus.com/inward/record.url?scp=85057261469&partnerID=8YFLogxK
U2 - 10.1016/j.scitotenv.2018.11.163
DO - 10.1016/j.scitotenv.2018.11.163
M3 - Article
C2 - 30577122
AN - SCOPUS:85057261469
SN - 0048-9697
VL - 655
SP - 1301
EP - 1310
JO - Science of the Total Environment
JF - Science of the Total Environment
ER -