Occurrence, spatial distribution and ecological risks of antibiotics in soil in urban agglomeration

Antibiotics in soil environment are regarded as emerging pollutants and have introduced increasing risks to soil ecosystem and human health in rapid urbanization areas. Identifying the occurrence and spatial variability of antibiotics in soils is an urgent issue in sustaining soil security. In this study, antibiotics in soils were investigated and analyzed in BeijingTianjin-Hebei urban agglomeration. The occurrence, spatial distribution, and related affecting factors of antibiotics in soils were identified and ecological risks of antibiotics in soil environment were assessed. Results showed that(1) The mean concentration of soil antibiotics in Beijing-Tianjin-Hebei urban agglomeration was 21.79 μg/kg. Land use substantially affected the occurrence and concentration of antibiotics in soils. Concentrations of antibiotics in cropland and orchard soils were 2-3 times higher than the other land use types.(2)The concentrations of antibiotics in soils in Beijing-Tianjin-Hebei urban agglomeration presented a spatial pattern of high values in southeast, and low values in northwest. Spatial variability of antibiotics in soils was closely related to the application of organic fertilizer and wastewater irrigation as well as topographical features. Furthermore, soil properties and land management policy had substantial influences on soil antibiotics, and soil heavy metals may aggravate the accumulation of antibiotics in soils.(3) Ecological risks assessment of antibiotics in soils demonstrated that erythromycin(ERY), sulfamethoxazole(SMX), and doxycycline(DOX) may introduce high risks to soil ecosystem health, and more attention should be paid to the areas with intensive human activities that had potential high risk to soil ecosystem health. This study suggests that scientific land and soil management should be considered to prevent soil antibiotic pollution and sustain soil security in urban agglomeration.

Erosion and covered zones altered by surface coverage effects on soil nitrogen and carbon loss from an agricultural slope under laboratorysimulated rainfall events

Soil erosion,one of the most serious environmental concerns,might remove topsoil and essential element from terrestrial land.However,few attentions have been given to investigating how soil erosion regimes affect soil carbon and nitrogen loss.Therefore,this study investigated the effects of surface coverage rates(83%,67%,50%,33%,17%and 0%)and two positions(up-and downslope)on erosion regimes and its associated soil nitrogen and carbon loss under a sequence of six rainfalls(R1-R6).These results showed that the sediment concentrations with 33%(R4)and 17%(R5)coverage downslope were significantly lower than those with coverage upslope,whereas there was no significant difference between the runoff rates of the two slopes.Thus,surface coverage at different positions induced two soil erosion regimes(deposition-and transport-dominated processes).Dynamics of the DON and DIN concentrations indicated different release processes of soil nitrogen into runoff.The DON contributed to a substantial amount of soil nitrogen loss,which accounted approximately 81%of the organic form.The SBOC is significantly correlated with sediment-enriched clay particles from the deposition-dominated processes and is higher than that from the transport-dominated processes.The DOC is significantly correlated with Rr for transport-dominated processes.These results illustrated the critical role of erosion regimes in soil organic carbon loss in dissolved or sediment-bound form.It is concluded that erosion/covered zones altered by surface coverage could produce transport-and deposition-dominated erosion regimes and consequently affect soil carbon and nitrogen loss.In addition,these results demonstrated that surface coverage pattern may efficiently control soil erosion and soil carbon and nitrogen loss.

Evaluation of alternative surface runoff accounting procedures using SWAT model

For surface runoff estimation in the Soil and Water Assessment Tool(SWAT)model,the curve number(CN)procedure is commonly adopted to calculate surface runoff by dynamically updating CN values based on antecedent soil moisture condition(SCSI)in field.From SWAT2005 and onward,an alternative approach has become available to apply the CN method by relating the runoff potential to daily evapotranspiration(SCSII).While improved runoff prediction with SCSII has been reported in several case studies,few investigations have been made on its influence to water quality output or on the model uncertainty associated with the SCSII method.The objectives of the research were:(1)to quantify the improvements in hydrologic and water quality predictions obtained through different surface runoff estimation techniques;and(2)to examine how model uncertainty is affected by combining different surface runoff estimation techniques within SWAT using Bayesian model averaging(BMA).Applications of BMA provide an alternative approach to investigate the nature of structural uncertainty associated with both CN methods.Results showed that SCSII and BMA associated approaches exhibit improved performance in both discharge and total NO3 predictions compared to SCSI.In addition,the application of BMA has a positive effect on finding well performed solutions in the multi-dimensional parameter space,but the predictive uncertainty is not evidently reduced or enhanced.Therefore,we recommend additional future SWAT calibration/validation research with an emphasis on the impact of SCSII on the prediction of other pollutants.