An innovative strategy for inducing Anammox from partial nitrification process in a membrane bioreactor.

Anaerobic ammonium oxidation (Anammox) was an innovative process for nitrogen removal. In this study, CuO nanoparticles (NPs) was step-wise increasingly added to an MBR-based partial nitrification system, to investigate its feasibility for inducing Anammox and establishing autotrophic nitrogen removal system. Results showed that when CuO NPs was elevated to 5 mg L-1, Anammox was successfully induced. The relative abundance of Nitrosomonas reached 13.73% while Candidatus Kuenenia increased to 4.79% from 0.46%, these two bacteria cooperatively contributed to the autotrophic nitrogen removal and improved the nitrogen removal rate (NRR) to 0.56 kg m-3 d-1 in 20 mg L-1 NPs. However, 50 mg L-1 NPs deeply suppressed the functional bacteria and decreased NRR to 0.14 kg m-3 d-1. Finally, the NPs removal, transformation and adsorption in the system were evaluated. It was concluded that CuO NPs in low concentration (5 mg L-1) was effective for inducing Anammox and contributed to the survival of Anammox bacteria. The mechanism for inducing Anammox was attributed to the aggregation of CuO NPs which enabled the attached growth of AAOB as well as the suitable survival condition supplied by MBR.

Acute and persistent toxicity of Cd(II) to the microbial community of Anammox process.

In this study, the short- and long-term effects of Cd(II) on the bioactivity, nitrogen removal and microbial community of the anaerobic ammonia oxidation (Anammox) process were investigated by step-wise increasing Cd(II). The self-recovery ability of Anammox was also studied after long-term exposure in Cd(II). The bioactivity of anaerobic ammonia-oxidizing bacteria (AAOB) within short-term exposure of Cd(II) were detected by batch experiments. Results showed that Cd(II) had both acute and persistent toxicity to Anammox, the IC50 in short-term exposure was calculated as 5.43 mg L-1. Long-term exposure led to the microbial diversity increase, as well as the relative abundance decrease of AAOB in Anammox system. AAOB was continuously suppressed by Cd(II) in 1-20 mg L-1, while it had self-adaption to Cd(II) in 1-10 mg L-1. Anammox biofilm showed prominent adsorbing ability for cadmium, and the cadmium in biofilm was the key factor affecting Anammox.

Effect of zinc oxide nanoparticles on nitrogen removal, microbial activity and microbial community of CANON process in a membrane bioreactor.

In this study, a membrane bioreactor (MBR) was adopted for completely autotrophic nitrogen removal over nitrite (CANON) process. Zinc oxide nanoparticles (ZnO NPs) was step-wise increased to analyze the influence on nitrogen removal, microbial activity and microbial communities. Finally ZnO NPs was removed to study its recovery capability. The bioactivities of ammonia-oxidizing bacteria (AOB), anaerobic ammonia-oxidizing bacteria (AAOB) and nitrite-oxidizing bacteria (NOB) were detected by batch experiments. Results showed that the ZnO NPs with low concentration (≤5mgL-1) was profitable for nitrogen removal while the high concentration performed inhibition, and it lowered the abundance of both AOB and NOB while enhanced that of AAOB. ZnO NPs with high concentration (≥10mgL-1) suppressed both AOB and AAOB, and long-term exposure within ZnO NPs led to microbial diversity decrease. The inhibition threshold of ZnO NPs on CANON process was 10mgL-1, and the profitable concentration was 1mgL-1.

Identifying repeat DUI crash factors using state crash records.

The objective of this study is to identify high risk factors that are closely related to repeat DUI crashes using readily available information from the state crash records. Survival analysis was used and a Cox proportional hazards model was developed using the police-reported crash records in the state of Louisiana. A variety of variables were found to be significant in predicting repeat DUI crashes. The factors included the characteristics of the drivers (gender, race, and age), the types of the vehicle (light truck/pick up truck or other), the characteristics of the crash (hit-and-run, driver violations, and whether the driver is arrested), the type of location (residential area or other), and the characteristics of the roadway (highway type and roadway type). This study provides a comprehensive picture of the repeat DUI crashes. The model can quantitatively predict the relative hazards of repeat DUI crashes. It can be used to identify the characteristics of the crash-involved DUI drivers who are at greatest risk of being involved in a subsequent DUI crash, allowing to apply appropriate remedial measures to reduce the risk.