区域地下水不同深度微生物群落结构特征

为了揭示区域地下水不同深度微生物群落结构特征及其与地下水环境相互作用关系,选取北京琉璃河地区,采集不同深度地下水样品,用于水化学分析和微生物16S rRNA基因V4-V5区测序.水化学分析结果显示,地下水中8种主要离子浓度随深度增加均呈减小趋势,Cl^-、SO₄^2-、NO₃^-变化规律显著,工业较发达区NO₃^-浓度达155.30mg/L,SO₄^2-浓度达321.00mg/L,部分浅层地下水受NO₃^-和SO₄^2-污染.微生物分析结果显示,地下水中微生物群落多样性受深度影响显著,随深度增加微生物群落组成丰富.地下水中优势菌门为Proteobacteria （26.2%~95.2%）,优势菌属为Pseudomonas（1.5%~32.2%）,不同深度微生物菌属组成差异明显,浅层、中层和深层地下水特有菌属数目分别为74,60,54.NO₃^-、SO₄^2-、深度是影响地下水微生物群落的主要因子,且NO₃^-、SO₄^2-浓度受地下水深度影响程度大.地下水深度是影响微生物群落结构差异的重要原因.     

Air pollution characteristics and their relationship with emissions and meteorology in the Yangtze River Delta region during 2014–2016

With rapid economic growth and urbanization, the Yangtze River Delta(YRD) region in China has experienced serious air pollution challenges. In this study, we analyzed the air pollution characteristics and their relationship with emissions and meteorology in the YRD region during 2014–2016. In recent years, the concentrations of all air pollutants, except O_3,decreased. Spatially, the PM_(2.5), PM_(10), SO_2, and CO concentrations were higher in the northern YRD region, and NO_2 and O_3 were higher in the central YRD region. Based on the number of non-attainment days(i.e., days with air quality index greater than 100), PM_(2.5) was the largest contributor to air pollution in the YRD region, followed by O_3, PM_(10), and NO_2.However, particulate matter pollution has declined gradually, while O_3 pollution worsened.Meteorological conditions mainly influenced day-to-day variations in pollutant concentrations. PM_(2.5) concentration was inversely related to wind speed, while O_3 concentration was positively correlated with temperature and negatively correlated with relative humidity.The air quality improvement in recent years was mainly attributed to emission reductions.During 2014–2016, PM_(2.5), PM_(10), SO_2, NO_x, CO, NH_3, and volatile organic compound(VOC)emissions in the YRD region were reduced by 26.3%, 29.2%, 32.4%, 8.1%, 15.9%, 4.5%, and0.3%, respectively. Regional transport also contributed to the air pollution. During regional haze periods, pollutants from North China and East China aggravated the pollution in the YRD region. Our findings suggest that emission reduction and regional joint prevention and control helped to improve the air quality in the YRD region.     

从生物群落到生态系统综合保护：国家公园生态系统完整性保护的理论演变

自然保护事业已经进入人与自然和谐的综合保护阶段,突破传统生物群落保护的要素式思维,从生态特征、生态系统健康和自组织能力等视角系统实施生态系统完整性保护,已基本成为共识。中国经历了长期部门化割裂管理,在国家公园体制建设过程中开始由分散走向统一,要求将山水林田湖草作为生命共同体进行生态系统完整性保护。基于集合种群等空间生态学理论,提出国家公园生态系统完整性不仅意味着内部自然空间的完整,更需着眼国家生态安全的大局和自然保护地体系的战略布局。国家公园只有成为生态地理区的节点并辐射周边区域,有效平衡行政区域之间以及人与自然之间的关系,才能真正实现完整生态系统的长效保护。目前,国内既有研究在指导全域布局和平衡人地关系方面仍考虑不足,试点过程中还存在管理型技术方法欠缺、空间边界受限于行政边界、未能从全局着眼构建以国家公园为核心的生态系统完整性网络、未充分考虑差异化的人地关系等问题。未来需要着眼大局,有效平衡国家公园及其周边区域的关系、不同行政区域之间的关系、国家公园人与自然的关系,从而实现生态系统完整性的长效保护。     

基于LEI和MSPA的南昌市城市扩张类型与生态景观类型变化关联分析

中国正处于城市化快速发展阶段,城市扩张导致大量生态景观日益破碎,分析城市扩张类型与生态景观类型的变化及其关联机制能为改善生态环境提供指导。以南昌市为研究区,采用景观扩张指数（LEI）和形态学空间格局分析法（MSPA）识别南昌市的城市扩张类型和生态用地景观类型,并通过建立缓冲区带分析城市扩张类型与生态景观类型变化的关联特征。结果表明：（1）南昌市城市扩张主要以边缘型扩张为主,生态用地以“核心”形态为主;（2）不同圈层的城市扩张类型和生态景观类型的关系在不同发展阶段差异显著;（3）在城市扩张过程中,总体上生态景观越加破碎,边缘型扩张会加速大型绿色斑块的减小,飞地型扩张促进绿色景观单元的破碎化,填充型扩张则有弱化这一过程的作用。研究结果可为控制城市无序扩张提供可靠的理论参考,并为研究区的城市有序扩张和生态环境保护提供决策依据。     

基于随机森林模型的中国近地面NO2浓度估算

NH₃针对传统近地面NO₂浓度空间模拟过程中NO₂浓度与其影响要素之间关系的复杂非线性机制解释不充分的缺陷,本研究基于随机森林（RF）算法、融合多源地理要素开展了近地面NO₂浓度空间分布模拟研究.以卫星OMI对流层NO₂柱浓度数据和多源地理要素（道路交通、气象因子、土地利用/覆盖、地形高程、人口数量）为输入变量,近地面NO₂浓度为输出变量,利用RF算法构建近地面NO₂浓度反演模型.通过对比地面观测数据与传统土地利用回归模型（LUR）检验RF模型的有效性,基于所构建的最优RF模型在不同时间尺度下模拟分析中国大陆地区近地面NO₂浓度空间分布特征.结果表明：（1）集成多源地理要素的RF回归模型精度高,月均模型整体拟合度R² 0.85,RMSE 6.08μg/m³,交叉验证的R² 0.84,RMSE 6.33μg/m³,显著高于LUR模型（拟合R² 0.53,RMSE 10.48μg/m³,交叉验证的R² 0.53,RMSE 10.49μg/m³）; （2）地面NO₂浓度与预测变量呈现显著的复杂非线性与时间尺度依赖关系,卫星OMI柱浓度对模型影响程度最大,重要性指标IncMSE介于97.40%~116.54%,多源地理特征变量对RF模型同样具有不可忽视的贡献力（IncMSE在23.34%~47.53%之间）;（3）中国大陆地区NO₂污染程度较高,年均模拟浓度为24.67μg/m³,存在明显季节性空间差异,NO₂浓度冬季（31.85μg/m³） > 秋季（24.86μg/m³） > 春季（23.24μg/m³） > 夏季（18.75μg/m³）,呈现以华北平原为高值中心、向外围逐渐减轻的空间分布格局.较已有研究揭示对流层NO₂柱浓度宏观分布特征,本研究对近地面NO₂污染特征的研究成果对于合理制定污染防控策略、降低居民暴露健康损害具有指导意义.     

微生物-生物促生剂协同修复河道底泥——促生剂投量对修复效果的影响

采用5个110L的模拟河道反应器,在投加菌剂的基础上（底泥稳定后向底泥和水中分别注射浓度为0.09%和0.03%的菌剂）,生物促生剂投量分别设计为0.08,0.09,0.10和0.11g/L,单独投加菌剂组作为空白实验.通过为期四十余天的实验研究微生物与促生剂协同作用时的修复效果.结果表明,促生剂投量为0.10g/L时,上覆水COD去除率69%高于其余各组;各协同修复组上覆水中NO₃^--N基本无积累,且促生剂投量为0.11g/L时NO₃^--N去除率最高,可达96%;40d内各组底泥TOC,TN含量变化不显著,延长反应时间至84d,各协同修复组底泥TOC,TN去除率均有明显提升.各协同修复组脲酶活性均波动下降,蛋白酶活性在15d左右时达到峰值,增幅可达106%~237%.通过高通量测序技术发现,43d时Desulfuromonas,Pseudomonas,Treponema_2,Blvii28_wastewater-sludge_group等主要功能菌群的相对丰度与空白实验组相比均增加,且促生剂投量为0.10g/L可使微生物群落向更适宜降解去除氮素及有机质的方向演替,有效改善底泥环境.协同修复对底泥,上覆水水质及微生物群落有良好改善效果,且促生剂投量为0.1g/L时整体修复情况更为理想.     

氯化石蜡产品中短链和中链同系物的指纹分布

使用气相色谱-电子捕获负化学电离质谱（GC-ECNI-MS）,对包含CP-42、CP-52和CP-70三种常见氯含量的22个CPs产品进行了测定,分析了不同氯含量的CPs产品中短链氯化石蜡（SCCPs）和中链氯化石蜡（MCCPs）同系物的分布模式.SCCPs同系物呈现5种分布特征,分别是CP-42型、三类CP-52型和CP-70型,MCCPs同系物呈现4种分布特征,分别是CP-42型和三类CP-52型,CP-70产品中MCCPs同系物未呈现出一致的分布规律.CPs生产原料石蜡中烷烃的成分组成和CPs生产工艺的不同,是造成产品同系物分布模式不一致的原因.通过统计学分析,得到CPs产品中SCCPs和MCCPs同系物的指纹分布,这是开展环境中CPs的源解析、迁移转化、归趋和毒性风险评价等研究的有利工具.     

Simultaneous quantification of fifty-one odor-causing compounds in drinking water using gas chromatography-triple quadrupole tandem mass spectrometry

A wide range of compounds with various structural features can cause taste and odor(TO)problems in drinking water. It would be desirable to determine all of these compounds using a simple analytical method. In this paper, a sensitive method combining liquid–liquid extraction(LLE) with gas chromatography-triple quadrupole tandem mass spectrometry(GC–MS/MS)was established to simultaneously analyze 51 odor-causing compounds in drinking water,including organic sulfides, aldehydes, benzenes, phenols, ethers, esters, ketones, nitrogenous heterocyclic compounds, 2-methylisoborneol and geosmin. Three deuterated analogs of target analytes, dimethyl disulfide-d6, benzaldehyde-d6 and o-cresol-3,4,5,6-d4,were used to correct the variations in recovery, and five isotope-labeled internal standards(4-chlorotoluene-d4, 1, 4-dichlorobenzene-d4, naphthalene-d8, acenaphthene-d10, phenanthrene-d10 respectively) were used prior to analysis to correct the variations arising from instrument fluctuations and injection errors. The calibration curves of the target compounds showed good linearity(R2 0.99, level = 7),and method detection limits(MDLs) below 1/10 of the odor threshold concentrations were achieved for most of the odorants(0.10–20.55 ng/L). The average recoveries of most of the analytes in tap water samples were between 70% and 120%, and the method was reproducible(RSD 20%, n = 7). Additionally, concentrations of odor-causing compounds in water samples collected from three drinking water treatment plants(DWTPs) were analyzed by this method.According to the results, dimethyl trisulfide, dimethyl disulfide and indole were considered to be the key odorants responsible for the swampy/septic odor. 2-Methylisoborneol and geosmin were detected as the main odor-causing compounds for musty/earthy odor in DWTP B.     

Statistical regression modeling for energy consumption in wastewater treatment

Wastewater treatment is one of critical issues faced by water utilities, and receives more and more attentions recently. The energy consumption modeling in biochemical wastewater treatment was investigated in the study via a general and robust approach based on Bayesian semi-parametric quantile regression. The dataset was derived from a municipal wastewater treatment plant, where the energy consumption of unit chemical oxygen demand (COD) reduction was the response variable of interest. Via the proposed approach, the comprehensive regression pictures of the energy consumption and truly influencing factors, i.e., the regression relationships at lower, median and higher energy consumption levels were characterized respectively. Meanwhile, the proposals for energy saving in different cases were also facilitated specifically. First, the lower level of energy consumption was closely associated with the temperature of influent wastewater, and the chroma-rich wastewater also showed helpful in the execution of energy saving. Second, at median energy consumption level, the COD-rich wastewater played a determinative role in the reduction of energy consumption, while the higher quality of treated water led to slightly energy intensive. Third, the higher level of energy consumption was most likely to be attributed to the relatively high temperature of wastewater and total nitrogen (TN)-rich wastewater, and both of the factors were preferably to be avoided to alleviate the burden of energy consumption. The study provided an efficient approach to controlling the energy consumption of wastewater treatment in the perspective of statistical regression modeling, and offered valuable suggestions for the future energy saving.