Impacts of biochars on bacterial community shifts and biodegradation of antibiotics in an agricultural soil during short-term incubation.

This study investigated the effects of applying different biochars to soil on shifts in the bacterial community, the biodegradation of antibiotics, and their relationships. In total, nine biochars were applied to agricultural soil contaminated with 16 antibiotics. Clustering analysis showed that the responses of bacteria at the genus level to biochars were highly dependent on the biochar feedstock rather than the pyrolysis temperature. Among the antibiotics tested in the study, the biodegradation percentage was lower for tetracyclines (TCs, 6-14%) than sulfonamides (SAs, 8-26%) and quinolones (QLs, 8-24%). For specific individual antibiotics from the same class with similar structures, the high adsorption affinity of soil particles for antibiotics due to hydrophobic interactions (logKow) and electrostatic interactions (pKa) resulted in low biodegradation percentages for antibiotics in the soil. The biodegradation of TCs was affected more by the biochar type (effect size: -10% to 42%) than those of QLs (-26% to 14%) and SAs (-24% to 22%). According to the relationships determined between the bacterial taxonomic composition and biodegradation of antibiotics, Steroidobacter from the phylum Proteobacteria has significant positive correlations with the biodegradation of all SAs (p < 0.01), thereby indicating that Steroidobacter had a high capacity for biodegrading SAs. Significant positive correlations were also detected (p < 0.05) between specific genera (Iamia, Parviterribacter, and Gaiella) from the phylum Actinobacteria and the biodegradation of SAs. No significant positive correlations were found between bacterial genera and the biodegradation percentages for QLs and TCs, possibly due to the specific microorganisms involved in these biodegradation processes. The results in this study provide insights into the biodegradation mechanisms of antibiotics in soil and they may facilitate the development of strategies for the bioremediation of antibiotic-contaminated soil.

Effects of surface-modified biochars and activated carbon on the transformation of soil inorganic nitrogen and growth of maize under chromium stress.

Elevated chromium (Cr) level is challenging agricultural production and affecting soil biochemical process. This study evaluated the effect of amendments including surface-modified biochars (HBC: acid washing, Fe(III)-HBC: ferric iron loading, nZVI-HBC: nanoscale zero-valent iron loading) and activated carbon on hexavalent chromium (Cr(VI)) removal in soil and on N cycling enzyme activities, transformation of soil inorganic nitrogen, and growth of maize under Cr stress. The results showed that amendments increased Cr(VI) removal by 72.9%-96.34% at three levels of spiked Cr(VI) (low: 125 mg kg-1, moderate: 250 mg kg-1, high: 500 mg kg-1). Under low Cr stress, amendments generally significantly decreased urease and nitrite reductase activities but increased nitrate reductase activity (p < 0.05). The NH4+-N content had a significant positive correlation with urease activity (p < 0.01), while both NO2--N and NO3--N were absent correlations with N cycling enzyme studied. Amendments decreased NH4+-N/NO3--N ratio under low Cr stress but increased it under moderate Cr stress, although the difference was not significant. Under high Cr stress, only Fe(III)-HBC significantly increased NH4+-N/NO3--N ratio (p < 0.05). The decrease and increase of NH4+-N/NO3--N ratios indicate the enhancement of nitrification and denitrification, respectively. The increase in Cr(VI) removal by amendments contributed to the increase in the migration of NO3--N from roots to shoots. Amendments (except for nZVI-HBC in soil under low Cr stress) increased maize height by 20%-59%. Under low Cr stress, however, nZVI-HBC significantly decreased maize height by 65% (p < 0.05), indicating the toxic effect of nZVI on maize growth overwhelmed low Cr stress.

Industrial water resources management based on violation risk analysis of the total allowable target on wastewater discharge.

To improve the capabilities of conventional methodologies in facilitating industrial water allocation under uncertain conditions, an integrated approach was developed through the combination of operational research, uncertainty analysis, and violation risk analysis methods. The developed approach can (a) address complexities of industrial water resources management (IWRM) systems, (b) facilitate reflections of multiple uncertainties and risks of the system and incorporate them into a general optimization framework, and (c) manage robust actions for industrial productions in consideration of water supply capacity and wastewater discharging control. The developed method was then demonstrated in a water-stressed city (i.e., the City of Dalian), northeastern China. Three scenarios were proposed according to the city's industrial plans. The results indicated that in the planning year of 2020 (a) the production of civilian-used steel ships and machine-made paper & paperboard would reduce significantly, (b) violation risk of chemical oxygen demand (COD) discharge under scenario 1 would be the most prominent, compared with those under scenarios 2 and 3,

Development of an integrated indicator system to assess the impacts of reclamation engineering on a river estuary.

An integrated indicator system was developed for determining synthetic environmental responses under multiple types of coastal reclamation engineering in the Yellow River estuary, China. Four types of coastal engineering works were analyzed, namely port construction, petroleum exploitation, fishery and aquaculture, and seawall defense. In addition, two areas with limited human disturbances were considered for comparison. From the weights of the response value for each indicator, port construction was determined to be the primary impact contributor among the four engineering works studies. Specifically, hydrodynamic conditions, ecological status, economic costs, and engineering intensity were on average 72.78%, 65.03%, 75.03%, and 66.35% higher than those of other engineering types. Furthermore, fishery and aquaculture impact on water quality was 42.51% higher than that of other engineering types, whereas seawall defense impact on landscape variation was 51.75% higher than that of other engineering types. The proposed indicator system may provide effective coastal management in future.

Microbial nitrification, denitrification and respiration in the leached cinnamon soil of the upper basin of Miyun Reservoir.

Leached cinnamon soil is the main agricultural soil distributed in the North China Plain. In this research, leached cinnamon soil samples were collected in the upper basin of Miyun Reservoir (northeast of Beijing, China). The BaPS method (Barometric Process Separation) was applied to measure nitrification, denitrification and respiration rates. The rates of nitrification, denitrification and respiration were 0-120.35 µg N/kg SDW h, 0-246.86 µg N/kg SDW h and 0.17-225.85 µg C/kg SDW h (Soil Dry Weight, SDW), respectively. The emission rates of CO2 and NxOy through nitrification, denitrification and respiration were 1.00-547.80 and 6.00-4850.65 µmol/h, respectively. The analysis of relationships between nitrification, denitrification and respiration rates indicated that these three microbial processes were interacted, which posed impacts on soil nitrogen availability. As indicated by the results, C:N ratio coupled with content could be taken as the indicators of content, which is usually the predominant form of N available to plants growing in soil. Results showed that content was the highest (i.e., >62.4 mg/kg) when C:N ratio was 5.30-8.40, meanwhile content was 3.71-4.39 mg/kg. Nevertheless, content was the lowest (i.e., <6.40 mg/kg) when C:N ratio was 9.2-12.10, meanwhile content was 3.41-4.35 mg/kg.

An enhanced export coefficient based optimization model for supporting agricultural nonpoint source pollution mitigation under uncertainty.

In this research, an export coefficient based dual inexact two-stage stochastic credibility constrained programming (ECDITSCCP) model was developed through integrating an improved export coefficient model (ECM), interval linear programming (ILP), fuzzy credibility constrained programming (FCCP) and a fuzzy expected value equation within a general two stage programming (TSP) framework. The proposed ECDITSCCP model can effectively address multiple uncertainties expressed as random variables, fuzzy numbers, pure and dual intervals. Also, the model can provide a direct linkage between pre-regulated management policies and the associated economic implications. Moreover, the solutions under multiple credibility levels can be obtained for providing potential decision alternatives for decision makers. The proposed model was then applied to identify optimal land use structures for agricultural NPS pollution mitigation in a representative upstream subcatchment of the Miyun Reservoir watershed in north China. Optimal solutions of the model were successfully obtained, indicating desired land use patterns and nutrient discharge schemes to get a maximum agricultural system benefits under a limited discharge permit. Also, numerous results under multiple credibility levels could provide policy makers with several options, which could help get an appropriate balance between system benefits and pollution mitigation. The developed ECDITSCCP model can be effectively applied to addressing the uncertain information in agricultural systems and shows great applicability to the land use adjustment for agricultural NPS pollution mitigation.

Microbial bioavailability of 2,2',4,4'-Tetrabromodiphenyl ether (BDE-47) in natural sediments from major rivers of China.

Microbial degradation plays a crucial role in eliminating polybrominated diphenyl ethers (PBDEs) in environments. However, the microbial bioavailability of PBDEs in aquatic sediments is not well understood. In this work, the bioavailability of 2,2',4,4'-tetrabromodiphenyl ether (BDE-47), a typical PBDE congener, to PBDE-degrading microorganisms in natural sediments from six Chinese rivers under anaerobic conditions was investigated. The contents of black carbon (BC) and total organic carbon (TOC) in the six sediment samples were in the range of 0.025%-0.30% and 0.03%-3.38%, respectively. BDE-47 desorption from various sediments was fitted well with the first-order three-compartment desorption model. The desorbing fraction of sediment-associated BDE-47 at each desorption time interval exhibited a significant negative correlation with the BC content (p < 0.01). In the sediments, the anaerobic debromination of BDE-47 by microorganisms underwent a stepwise debromination pathway generating mainly three lower brominated congeners (BDE-28, -17 and -4). The microbial debromination ratio of BDE-47 ranged from 4.21% to 7.89% in various sediments after 120 d incubation anaerobically, and it negatively correlated with the content of sediment BC significantly (p < 0.01). However, the desorbing fraction and microbial debromination ratio of BDE-47 only showed weak correlations with the TOC content in sediments (p > 0.05). Furthermore, there was a significant positive correlation of desorbing fraction of BDE-47 from sediments with its microbial debromination ratio (p < 0.01) as well as with the level of its three lower brominated products (p < 0.05) after the first 20 d incubation. This study suggests that the BDE-47 bioavailability to microorganisms in anaerobic river sediments is mainly influenced by the content of sediment BC which controls the desorbing fraction of sediment-associated BDE-47.

A universal calibrated model for the evaluation of surface water and groundwater quality: Model development and a case study in China.

Water quality evaluation is an important issue in environmental management. Various methods have been used to evaluate the quality of surface water and groundwater. However, all previous studies have used different evaluation models for surface water and groundwater, and the models must be recalibrated due to changes in monitoring indicators in each evaluation. Water quality managers would benefit from a universal and effective model based on a simple expression that would be suitable for all cases of surface water and groundwater, and which could therefore serve as a standard method for a region or country. To meet this requirement, we attempted to develop a universal calibrated model based on the radial basis function neural network. In the new model, the units and values of the evaluation indicators for surface water and groundwater are normalized simultaneously to make the data directly comparable. The model's training inputs comprise the normalized value in each of a water quality indicator's grades (e.g., the nitrate contents defined in a regulatory standard for grades I to V) for all evaluation indicators. The central vector of the Gaussian function is used as the average of the evaluation indicators' normalized standard values for the five grades. The final calibrated model is expressed as an equation rather than in a programming language, and is therefore easier to use. We used the model in a Chinese case study, and found that the model was feasible (it compared well with the results of other models) and simple to use for the evaluation of surface water and groundwater quality.