水中总氮测定方法存在问题的研究及改进

碱性过硫酸钾消解紫外分光光度法测定水中总氮采用的消解器皿是玻璃比色管,易造成空白偏高、结果偏低等问题。采用双圆柱状的消解杯对水样进行消解。结果表明,消解杯消解水中总氮,线性相关系数均大于0.999,检出限为0.05 mg/L,相对标准偏差小于5%,相对误差为0.88%~1.00%;改进后的消解器皿具有较好的精密度和准确度,能够更加准确测定水中总氮的含量。     

淮河支流污染物综合降解系数动态测算

确定河流污染物综合降解系数动态变化规律对提高水环境容量测算精度和水环境管理具有重要意义。通过现场模拟法,采用一维稳态模型测算了淮河支流洪河五沟营-塔桥乡河段COD、氨氮和总磷在枯水期、平水期和丰水期的综合降解系数,COD、氨氮和总磷降解系数在各水期的关系为枯水期平水期丰水期,提出了建议值并利用实测浓度对计算结果进行了检验,结果表明,不同水期综合降解系数吻合情况较好。     

Diffusion pollution from livestock and poultry rearing in the Yangtze Delta,China

BACKGROUND: The Yangtze Delta is one of the most developed regions in China and includes Shanghai, eight cities in Jiangsu province and eight cities in Zhejiang province. Meat consumption in this region has increased with economic growth, and most of the consumed meat is produced locally. The water quality of surface waters has deteriorated in recent years. An example was the huge blue-green algae bloom in Tai Lake in late May 2007, which affected millions of people's daily drinking water. However, animal husbandry is considered to be one of the main pollution sources. METHODS: Pollutants (NH3-N, total phosphorus (TP), and total nitrogen (TN)) excreted by livestock and poultry, and the resultant COD (chemical oxygen demand) and BOD (biochemical oxygen demand), were estimated using two different methods based on different data sets. RESULTS: The number of livestock and poultry has remained stable in the Yangtze Delta over the four years from 1999 to 2002, with the average number of pigs, cattle, sheep and poultry being 21.1 M, 0.4 M, 7.7 M and 597.6 M, respectively. Pollutants in livestock and poultry excreta estimated by Method I were: 0.12 Mt NH3-N, 0.11 Mt TP and 0.29 Mt TN, resulting in COD and BOD of 1.34 Mt and 1.30 Mt, respectively, while the estimations based on Method II were: 0.18 Mt NH3-N, 0.15 Mt TP and 0.40 Mt TN, resulting in COD and BOD of 1.95 Mt and 1.80 Mt, respectively. DISCUSSION: Pollutants excreted annually by livestock and poultry in the Yangtze Delta are estimated to be: 0.17 Mt NH3-N, 0.16 Mt TP and 0.42 Mt TN, giving rise to a COD of 1.86 Mt and a BOD of 1.72 Mt. Approximately 25% of this pollution was estimated to enter water bodies, which means that the annual pollutant load is 43,700 t NH3-N, 39,400 tTP, 104,600t TN with a COD of 465,000 tand a BOD of 430,100 t. Pollutants from animal husbandry were similar in magnitude to those from industrial wastewater. Pigs produced the most pollution, followed by poultry, cattle and sheep. The pollution load from animal husbandry in the Yangtze Delta is about twice the average level of the whole of China. CONCLUSIONS: Domestic wastewater was the main pollution source in the Yangtze Delta, followed by pollution from raising livestock and poultry and from industrial wastewater. The pollution load in Shanghai and Jiaxing were the greatest, followed by 7 cities of Jiangsu province (except Suzhou) and other cities of Zhejiang province and Suzhou. Pigs and poultry produced about 90% of the total pollutants from animal husbandry. RECOMMENDATIONS AND PERSPECTIVES: The local governments, especially in Shanghai and Jiaxing, should focus their attention on the pollution produced by livestock and poulrry. Controlling pollution from pigs and poultry will have the greatest impact in this region. Control of pollution will be facilitated by the development of large-scale livestock and poultry farming units and a shift away from small scale husbandry.     

供水管网生物膜有机物的二氯乙腈与二氯乙酰胺生成特性

在饮用水输配系统中,来源于管壁生物膜的有机物可能耗氯并生成消毒副产物(DBPs),包括二氯乙腈(DCAN)与二氯乙酰胺(DCAcAm)等高毒性含氮DBPs(N-DBPs).研究考察管网常见的细菌与其胞外聚合物(EPS)以及模拟管壁生物膜氯化与氯胺化后DCAN与DCAcAm的生成,并与天然有机物(NOM)和水源水有机物进行比较.结果显示,铜绿假单胞菌、恶臭假单胞菌与藤黄微球菌与氯反应生成的DCAN、DCAcAm浓度分别为1.48～2.02、0.21～0.38μg·mg~(-1)(mg~(-1)以TOC计),高于同反应条件下NOM的生成量;相比于氯化反应,3株细菌细胞氯胺化生成的DCAN与DCAcAm浓度明显更低.3株菌的EPS也是氯与氯胺化反应生成DCAN与DCAcAm的前体物,且其氯胺化反应生成的DCAcAm浓度高于氯化反应生成的.与NOM、水源水相比,模拟管壁生物膜氯化后生成的N-DBPs与三氯甲烷(TCM)浓度比更高,表明生物膜有机物比NOM与水源水有机物更倾向生成DCAN与DCAcAm类N-DBPs,且模拟管壁生物膜氯胺化的DCAcAm生成量高于氯化反应的,说明管壁生物膜有机物是供水管网系统中DCAN与DCAcAm类N-DBPs的重要前体物.     

降水空间异质性对非点源关键源区识别面积变化的影响

针对地形起伏和降水空间差异较大的农业区非点源污染问题,基于SWAT模型评估了阿什河流域在异质性降水和均匀降水两种情景下总氮、总磷关键源区空间变化规律,统计了两种情景下识别的关键源区面积变化,并分析其与降水特征参数的关系.结果表明,降水量一定时,两种情景下识别的总氮、总磷关键源区面积变化趋势大致相同,且总磷关键源区面积不易受降水空间异质性的影响,但总氮关键源区面积却明显受到其影响.对各年份总氮和总磷关键源区面积与降水特征参数的相关分析表明,总磷关键源区面积与当年降水量呈显著正相关,而总氮关键源区面积却与前一年降水量呈显著正相关.研究结果对进一步探讨降水这一重要驱动因子的不确定性对非点源污染关键源区的影响,以及农业非点源污染的治理具有重要意义.     

基于不同废污泥源的短程反硝化快速启动及稳定性

为探究不同废污泥源快速启动短程反硝化和实现稳定NO_2~--N积累的可行性,在3个完全相同的SBR反应器(S1、S2和S3)分别接种:实验室城市污水反硝化除磷系统排泥、城市污水厂剩余污泥及河涌底泥,比较其短程反硝化启动快慢和NO_2~--N积累特性,考察系统短程反硝化活性和NO_3~--N→NO_2~--N转化性能,并从微生物学角度分析反应器功能菌群特征.结果表明,在乙酸钠为唯一碳源、高碱度和适宜COD/NO_3~--N比进水条件下,3个SBR短程反硝化反应器在短时间内均能够成功启动,系统平均NO_3~--N→NO_2~--N转化率为S1 S2 S3(75. 92% 73. 36% 69. 90%).同时发现持续低温条件下S1和S2呈现不同程度的短程反硝化性能恶化趋势,但S3能够稳定维持良好NO_2~--N积累性能.微生物高通量测序表明,变形菌门和拟杆菌门居PD系统主导地位,3个短程反硝化反应器NO_2~--N积累关键功能菌属Thauera属丰度差异明显:S3 S1 S2(25. 09% 4. 71% 3. 60%),表明S3具备稳定高效的NO_2~--N积累性能,同时高丰度Thauera属可能是维持低温短程反硝化活性的重要原因.     

河岸过滤中氨氮的削减及其浓度对细菌与氨氧化微生物的影响

通过小试滤柱模拟河岸过滤,结合荧光定量PCR和高通量测序等手段研究了河岸过滤对氨氮的削减效能和进水氨氮浓度对细菌与氨氧化微生物的影响.结果表明,低浓度（0.2 mg·L^-1）氨氮未被削减,较高浓度（1.0 mg·L^-1和2.0 mg·L^-1）氨氮的削减率可达70%.进水处细菌丰度随氨氮浓度升高而增加,细菌群落组成随氨氮浓度升高发生规律性变化.出水处氨氧化古菌（Ammonia oxidizing archaea,AOA）丰度与氨氮浓度呈负相关,氨氧化细菌（Ammonia oxidizing bacteria,AOB）丰度与氨氮浓度无显著相关关系;进水处AOA-α多样性与氨氮浓度呈正相关,但AOB-α多样性与氨氮浓度呈负相关;进水处AOA群落组成受氨氮浓度影响,而进、出水处AOB群落组成均受氨氮浓度影响.可见,进水氨氮浓度会影响河岸过滤对氨氮的削减效能,还会影响细菌、氨氧化微生物的丰度及群落结构,AOB对氨氮浓度的变化比AOA更敏感.     

科技创新投入对环境全要素生产率的影响机制

使用2004~2015年的中国280个地级市的面板数据,对科技创新投入与环境全要素生产率间的非线性关系、内部影响机理和空间异质性进行分析,结果显示：科技创新投入与环境全要素生产率之间呈现倒N型关系,两个拐点的位置分别为7.722（2257.47万元）和9.610（14913.17万元）;在外部资本进入、污染治理、市场规模效应3种影响路径中,科技创新投入影响下的外部资本进入对环境全要素生产率依然存在污染避难所的负向效应,科技创新投入与外部资本间效应为0.1363,外部资本与环境全要素生产率间效应为-0.0065;科技创新投入能够增强企业的污染治理技术并提高环境全要素生产率,三者间前后效应分别为-0.0277和-0.0311;科技创新的投入与高效益增强了市场规模效应,有效促进生产结构的转型进而提高环境全要素生产率,三者间前后效应为0.0186和0.4346.空间异质性中,外部资本进入与溢出效应带来的污染避难所负效应在中部地区显著,在西部和东北部地区不显著,而污染天堂正效应在东部地区存在但不显著;污染创新治理投入的技术正溢出效应在东部和西部地区效应显著,在中部和东北部不显著;科技创新投入与市场需求规模效应在空间区域无差异且显著为正.建议依据科技创新投入的不同影响路径来实施空间差异化策略.     

红树林土壤解磷菌的分离鉴定及解磷特性

从罗源湾红树林根际土壤中分离解磷菌,筛选出洋葱伯克霍尔德菌（Burkholderia cepacia, NR 113645.1）和短小芽孢杆菌（Bacillus pumilus, NR 043242.1）,研究它们的解磷特性和动态解磷过程. HPLC结果表明, B. cepacia菌液上清中含葡萄糖酸、丙酮酸、乳酸、乙酸、丁二酸, 这些有机酸的产生导致磷酸盐溶解. B.pumilus菌液上清中仅检测到少量的葡萄糖酸, 因此该菌溶磷效果不佳. 在细菌动态溶磷过程中发现, 经B. cepacia菌处理的磷酸钙, 其X射线衍射（XRD）特征峰强度随时间的增长降低, 显微镜图像显示磷酸钙颗粒随时间增长变小, 甚至消失. 而经B.pumilus菌处理的结果表明, 在试验期间内磷酸钙峰强度和颗粒大小没有明显变化. 细菌产生有机酸是溶解磷酸盐的重要前提, 这是解决板结土壤中难溶性磷源转化为生物可利用磷源问题的关键.     

Responses of nitrification performance, triclosan resistome and diversity of microbes to continuous triclosan stress in activated sludge system

Triclosan(TCS) is commonly found in wastewater treatment plants,which often affects biological treatment processes.The responses of nitrification,antibiotic resistome and microbial community under different TCS concentrations in activated sludge system were evaluated in this study.The experiment was conducted in a sequencing batch reactor(SBR)for 240 days.Quantitative PCR results demonstrated that the abundance of ammonium oxidizing bacteria could be temporarily inhibited by 1 mg/L TCS and then gradually recovered.And the abundances of nitrite oxidizing bacteria(NOB) under 2.5 and 4 mg/L TCS were three orders of magnitude lower than that of seed sludge,which accounted for partial nitrification.When the addition of TCS was stopped,the abundance of NOB increased.The mass balance experiments of TCS demonstrated that the primary removal pathway of TCS changed from adsorption to biodegradation as TCS was continuously added into the SBR system.Moreover,TCS increased the abundance of mexB,indicating the efflux pump might be the main TCS-resistance mechanism.As a response to TCS,bacteria could secrete more protein(PN) than polysaccharide.Three-dimensional excitation-emission matrix revealed that tryptophan PN-like substances might be the main component in PN to resist TCS.High-throughput sequencing found that the relative abundances of Paracoccus,Pseudoxanthomonas and Thauera increased,which could secrete extracellular polymeric substances(EPS).And Sphingopyxis might be the main TCS-degrading bacteria.Overall,TCS could cause partial nitrification and increase the relative abundances of EPS-secreting bacteria and TCS-degrading bacteria.