Potential shift of bacterial community structure and corrosion-related bacteria in drinking water distribution pipeline driven by water source switching

As a result of pollution in the present water sources,cities have been forced to utilize cleaner water sources.There are few reports regarding the potential shift of bacterial community structure driven by water source switching,especially that of corrosion-related bacteria.Three types of finished water were used for simulation,the polluted source water from the Qiantang and Dongtiaoxi Rivers(China)was replaced by cleaner water from Qiandao Lake(China).Here,we discussed the transition effects through three simulated reactors.The bacterial characteristics were identified using the highthroughput sequencing and heterotrophic plate count method.It was observed that the level of culturable bacteria declined by 2–3 orders of magnitude after water source switching.The bacterial community released from the pipeline reactor was significantly different under different finished water,and it exhibited large variation at the genus level.Porphyrobacter(58.2%)and Phreatobacter(14.5%)clearly replaced Novosphingobium,Aquabacterium,and Cupriavidus as new dominant genera in system A,which could be attributed to the lower carbon and nitrogen content of the new water source.Although corrosion-inhibiting bacteria decreased after switching,they still maintained dominant in three reactors(6.6%,15.9%,and 19.7%).Furthermore,potential opportunistic pathogens such as Sphingomonas were detected.Our study shows that after transition to a high quality water source,the total culturable bacteria released was in a downtrend,which leads to a great reduction in the risk of bacterial leakage in the produced drinking water.

Modeling iron release from cast iron pipes in an urban water distribution system caused by source water switch

Significant iron release from cast iron pipes in water distribution systems(WDSs),which usually occurs during the source water switch period,is a great concern of water utilities because of the potential occurrence of"red water"and customer complaints.This study developed a new method which combined in-situ water stagnation experiments with mathematical models and numerical simulations to predict the iron release caused by source water switch.In-situ water stagnation experiments were conducted to determine the total iron accumulation in nine cast iron pipes in-service in Beijing when switching the local water to tre ated Danjiangkou Reservior water.Results showe d that the difference in the concentration increment of total iron in 24 hr(ΔCITI,24),i.e.short-term iron release,caused by source water switch was mainly dependent on the difference in the key quality parameters(pH,hardness,nitrate,Larson Ratio and dissolved oxygen(DO))between the two source waters.The iron release rate(RFe)after switch,i.e.long-term iron release,was closely related to the pipe properties as well as the DO and total residual chlorine(TRC)concentrations.Mathematical models ofΔCITI,24 and RFe were developed to quantitatively reveal the relationship between iron release and the key quality parameters.The RFe model could successfully combine with EPANET-MSX,a numerical simulator of water quality for WDSs to extend the iron release modeling from pipe level to network level.The new method is applicable to predicting iron release during source water switch,thus facilitating water utilities to take preventive actions to avoid"red water".

Molecular ecological networks reveal the spatial-temporal variation of microbial communities in drinking water distribution systems

Microbial activity and regrowth in drinking water distribution systems is a major concern for water service companies.However,previous studies have focused on the microbial composition and diversity of the drinkingwater distribution systems(DWDSs),with little discussion on microbial molecular ecological networks(MENs)in different water supply networks.MEN analysis explores the potentialmicrobial interaction and the impact of environmental stress,to explain the characteristics of microbial community structures.In this study,the random matrix theory-based network analysis was employed to investigate the impact of seasonal variation including water source switching on the networks of three DWDSs that used different disinfection methods.The results showed that microbial interaction varied slightly with the seasons but was significantly influenced by different DWDSs.Proteobacteria,identified as key species,play an important role in the network.Combined UV-chlorine disinfection can effectively reduce the size and complexity of the network compared to chlorine disinfection alone,ignoring seasonal variations,which may affect microbial activity or control microbial regrowth in DWDSs.This study provides new insights for analyzing the dynamics of microbial interactions in DWDSs.