秸秆还田对双季稻产量及氮磷径流损失的影响

为探索减少稻田氮磷流失的有效耕作措施,以南方典型黄壤双季稻田为研究对象,采用田间长期定位观测试验,研究了连续7 a(2008—2014年)秸秆还田(RFS)替代38.7%的N、40.8%的P₂O₅和42.7%的K₂O晚稻化肥投入与常规化肥(RF)处理对双季稻产量、地表径流中ρ(TN)、ρ(NH₄+-N)、ρ(NO₃--N)、ρ(TP)、ρ(DP)(DP为溶解态总磷)的影响.结果表明:与常规化肥处理相比,秸秆还田处理不仅可从源头上减少晚稻化肥投入,还可降低稻田径流液中氮、磷养分含量,分别使TN和TP流失量减少12.6%、9.7%;氮流失主要以DIN(可溶性无机氮)为主,DIN/TN(DIN输出量在TN输出量中所占比例)为66.2%～70.8%;磷流失主要以DP(可溶性磷酸盐)为主,DP/TP(DP输出量在TP输出量中所占比例)为60.1%～65.9%;秸秆还田处理下早稻较常规化肥处理有增产趋势,增幅为4.5%～10.1%,晚稻有减产风险,但减产差异不显著,平均减幅为6.3%.因此,秸秆长期还田是一种秸秆资源有效利用和节肥增效减失的耕作方式.      

黄土高原不同土地利用类型有机碳和黑碳的储量及意义

以黄土高原为研究对象,研究三种不同利用方式的表层土壤样品(0—20 cm),分析其有机碳(soil organic carbon,简称SOC)和黑碳(black carbon,简称BC)的含量、分布特征及其储量变化及意义。研究表明,黄土高原不同利用方式土壤有机碳和黑碳含量的平均值分别为:玉米地8.01 g?kg~(-1)和1.01 g?kg~(-1),林地6.80 g?kg~(-1)和0.59 g?kg~(-1),未利用地5.01 g?kg~(-1)和0.43 g?kg~(-1),有机碳和黑碳的含量均为玉米地最高,未利用地最低;耕地和自然土壤表土有机碳储量分别为0.796 Pg和0.710 Pg,表土黑碳储量分别为0.0858 Pg和0.0730 Pg,耕地相对于自然土壤有机碳和黑碳的储量分别增大12.1%和17.5%;说明黄土高原耕地是一个碳汇,起着固定碳的作用;采用推荐的管理实践活动和合理的土地利用方式,能够增加土壤碳储量,提高土壤质量和农作物产量,抵消部分二氧化碳的排放。     

超重力环境下脱除工业气体中H2S的研究

以空气和H2S的混合物模拟含H2S的工业气体,以碳酸钠溶液为脱硫碱液,PDS 为脱硫催化剂,用超重力设备取代传统填料塔进行脱硫实验,分别考察了气体流量、液体流量、超重力因子、原料气中H2S含量等对脱硫率的影响.结果表明,超重力环境下工 业气体中的H2S脱除效果较好,脱硫效率可以达到99%以上,其中原料气流量对脱硫率影响...     

Release of Pb adsorbed on graphene oxide surfaces under conditions of Shewanella putrefaciens metabolism

In this study, Pb(II) was used as a target heavy metal pollutant, and the metabolism of Shewanella putrefaciens (S. putrefaciens) was applied to achieve reducing conditions to study the effect of microbial reduction on lead that was preadsorbed on graphene oxide (GO) surfaces. The results showed that GO was transformed to its reduced form (r-GO) by bacteria, and this process induced the release of Pb(II) adsorbed on the GO surfaces. After 72 hr of exposure in an S. putrefaciens system, 5.76% of the total adsorbed Pb(II) was stably dispersed in solution in the form of a Pb(II)-extracellular polymer substance (EPS) complex, while another portion of Pb(II) released from GO-Pb(II) was observed as lead phosphate hydroxide (Pb₁₀(PO₄)₆(OH)₂) precipitates or adsorbed species on the surface of the cell. Additionally, increasing pH induced the stripping of oxidative debris (OD) and elevated the content of dispersible Pb(II) in aqueous solution under the conditions of S. putrefaciens metabolism. These research results provide valuable information regarding the migration of heavy metals adsorbed on GO under reducing conditions due to microbial metabolism.     

Adsorption of sulfonamides on lake sediments

Sulfonamides (SAs) are one class of the most widely used antibiotics around the world. Their fate and transport in the aquatic environment is of great concern. In this study, adsorption of four SAs—sulfadiazine (SD), sulfamethoxazole (SMZ), sulfadimethoxine (SDM) and sulfamethazine (SM2)—in single-solute and multi-solute systems on sediments of Dianchi (DC) Lake and Taihu (TH) Lake, China was investigated with batch experiments. In the single-solute adsorption system, the Langmuir model and the dual-mode model described the adsorption process better than the Freundlich model. Model fitness was better on DC sediment than on TH sediment. The order of adsorption capacity approximately followed a decreasing order of SDM>SD>SM2>SMZ on both sediments, which was likely attributed to the distinctly different water solubility of the four SAs. In the multi-solute system, the order of adsorption capacity was SM2>SDM>SD>SMZ, which was probably related to the compound speciation caused by the pH values of the experimental solution. In the multi-solute system, both competitive and cooperative adsorption played important roles in the adsorption of sulfonamides on sediments.     

Evaluation on exposures to particulate matter at a junior secondary school: a comprehensive study on health risks and effective inflammatory responses in Northwestern China

Air pollutant measurement and respiratory inflammatory tests were conducted at a junior secondary school in Xi’an, Northwestern China. Hazardous substances including particulate matters (PMs), black carbon (BC) and particle-bounded polycyclic aromatic hydrocarbons (PAHs) were quantified both indoors and outdoors of the school. Source characterization with organic tracers and particle-size distribution demonstrated that the school’s air was mostly polluted by combustion emissions from the surrounding environment. The evaluation of health assessment related to air quality was conducted by two methods, including potential risk estimation of air pollutants and direct respiratory inflammatory test. The incremental lifetime cancer risks associated with PAHs were estimated and were 1.62 × 10⁻⁶ and 2.34 × 10⁻⁶, respectively, for indoor and outdoor fine PMs. Both the values exceeded the threshold value of 1 × 10⁻⁶, demonstrating that the carcinogenic PAHs are a health threat to the students. Respiratory inflammatory responses of 50 students who studied in the sample classroom were examined with a fractional exhaled nitric oxide (FeNO) test, with the aid of health questionnaires. The average FeNO concentration was 17.4 ± 8.5 ppb, which was slightly lower than the recommended level of 20 ppb established by the American Thoracic Society for children. However, a wide distribution and 6% of the values were > 35 ppb, suggesting that the potentials were still high for eosinophilic inflammation and responsiveness to corticosteroids. A preliminary interpretation of the relationship between air toxins and respiratory inflammatory response demonstrated the high exposure cancer risks and inflammatory responses of the students to PMs in the city.

     

酸析—撞击流旋转填料床强化Fenton试剂氧化法预处理二硝基甲苯生产废水

采用酸析—撞击流旋转填料床( IS-RPB)强化Fenton试剂氧化法预处理二硝基甲苯(DNT)生产废水.最佳工艺条件为:酸析工段废水pH 1.0,IS-RPB转速1 500 r/min,FeSO4加入量0.06 mol/L,H2O2加入量0.45mol/L,反应温度40 ℃,反应时间4h.在该条件下处理DNT生产废水,COD去除率可达98.95％,硝基化合物去除率达98.32％,BOD5/COD为 0.65.经该方法预处理后的DNT生产废水可适用于生化法进行后续处理.     

陕西省自然灾害的减灾对策

陕西地质地理条件复杂,自然灾害频繁而严重。本文概括分析了省内自然灾害的主要类型和分布特点,简要回顾了近几十年减灾工作的成绩,在此基础上着重讨论了今后减灾工作的对策和减灾目标。     

Water quality prediction of copper-molybdenum mining-beneficiation wastewater based on the PSO-SVR model

● Data acquisition and pre-processing for wastewater treatment were summarized. ● A PSO-SVR model for predicting COD_eff in wastewater was proposed. ● The COD_eff prediction performances of the three models in the paper were compared. ● The COD_eff prediction effects of different models in other studies were discussed. The mining-beneficiation wastewater treatment is highly complex and nonlinear. Various factors like influent quality, flow rate, pH and chemical dose, tend to restrict the effluent effectiveness of mining-beneficiation wastewater treatment. Chemical oxygen demand (COD) is a crucial indicator to measure the quality of mining-beneficiation wastewater. Predicting COD concentration accurately of mining-beneficiation wastewater after treatment is essential for achieving stable and compliant discharge. This reduces environmental risk and significantly improves the discharge quality of wastewater. This paper presents a novel AI algorithm PSO-SVR, to predict water quality. Hyperparameter optimization of our proposed model PSO-SVR, uses particle swarm optimization to improve support vector regression for COD prediction. The generalization capacity tested on out-of-distribution (OOD) data for our PSO-SVR model is strong, with the following performance metrics of root means square error (RMSE) is 1.51, mean absolute error (MAE) is 1.26, and the coefficient of determination (R²) is 0.85. We compare the performance of PSO-SVR model with back propagation neural network (BPNN) and radial basis function neural network (RBFNN) and shows it edges over in terms of the performance metrics of RMSE, MAE and R², and is the best model for COD prediction of mining-beneficiation wastewater. This is because of the less overfitting tendency of PSO-SVR compared with neural network architectures. Our proposed PSO-SVR model is optimum for the prediction of COD in copper-molybdenum mining-beneficiation wastewater treatment. In addition, PSO-SVR can be used to predict COD on a wide variety of wastewater through the process of transfer learning.     

萘降解菌NAP_A的分离、降解性能和分子系统学研究

该文研究降解多环芳烃类环境污染物的微生物资源、降解活性和分子系统特征.利用萘-无机盐选择性培养基分离萘降解菌,用培养技术和气相色谱法检测菌株对底物的利用和降解情况,用分子克隆技术获得菌株的16S rRNA基因并测序,用DNAMAN软件对菌株的16S rRNA基因序列进行比对和系统发育分析.从淄博张店污水处理厂的活性污泥中分离到一株能降解萘的菌株NAP_A.此菌株在30 ～35 ℃和pH 7条件下较快的降解底物萘,其中30 ℃下,10 d内可以将初始质量浓度为320 mg·L-1的萘降解90％± 4.5％.对菌株NAP_A的16S rRNA基因进行了克隆和测序(EU142847),基于菌株NAP_A和相关菌株的16S rRNA基因进行系统发育分析,结果表明菌株NAP_A位于苍白杆菌属的分枝中,其中与假中间苍白杆菌种的同源性最高,可达99％,因此推断NAP_A菌是一株假中间苍白杆菌.此前并无苍白杆菌属成员降解多环芳烃的报道.这是首例苍白杆菌属成员降解多环芳烃的报道,对今后在环境污染防治中开发利用此类细菌具有指导意义.