基于统计学方法的南方某市管网水水质特征研究

为综合解析南方某市管网末梢水水质的时空变化特征、识别主要响应指标及指标间相关性,以该市近4年供水管网末梢水水质监测数据为研究对象,利用主成分分析法和对应分析法对管网末梢水质进行了特征研究。主成分分析法评价结果表明:该市管网末梢水年度总体水质存在差异,其中以2016年为最佳;夏秋季节更易发生水质异常现象,5~9月应加强管网末梢水水质管控;区域上看已完成深度处理改造的梅林水厂供水覆盖区管网末梢水水质最优,南山水厂供水覆盖区管网末梢水水质最差;水质指标硫酸盐、氯化物、硬度之间,Fe、浊度、总氯之间具有相对其他水质指标更高的相关性。对应分析法结果表明:管网末梢水水质主要响应指标可重点关注Fe、浊度、耗氧量、总氯和硫酸盐;其中Fe、浊度、耗氧量呈正相关性强,上述指标与硫酸盐、总氯呈负相关性。     

Nitrogen enrichment in runoff sediments as affected by soil texture in Beijing mountain area

Enrichment ratio (ER) is widely used in nonpoint source pollution models to estimate the nutrient loss associated with soil erosion. The objective of this study was to determine the ER of total nitrogen (ER_N) in the sediments eroded from the typical soils with varying soil textures in Beijing mountain area. Each of the four soils was packed into a 40 by 30 by 15 cm soil pan and received 40-min simulated rainfalls at the intensity of 90 mm h^?1 on five slopes. ER_N for most sediments were above unity, indicating the common occurrence of nitrogen enrichment accompanied with soil erosion in Beijing mountain area. Soil texture was not the only factor that influenced N enrichment in this experiment since the ER_N for the two fine-textured soils were not always lower. Soil properties such as soil structure might exert a more important influence in some circumstances. The selective erosion of clay particles was the main reason for N enrichment, as implied by the significant positive correlation between the ER of total nitrogen and clay fraction in eroded sediments. Significant regression equations between ER_N and sediment yield were obtained for two pairs of soils, which were artificially categorized by soil texture. The one for fine-textured soils had greater intercept and more negative slope. Thus, the initially higher ER_N would be lower than that for the other two soils with coarser texture once the sediment yield exceeded 629 kg ha^?1.     

河流多生境自然塑造技术在北运河流域再生水河道修复中的应用研究

遵循"基于自然的解决方案(Natural based solution)"理念,本研究开发了由渗滤型边滩、生态跌水和近自然河溪构成的河流多生境自然塑造技术及系统,并在北运河流域的再生水河道台头沟实施了工程应用与示范.结果表明,该技术与系统具有良好的水质净化效果,对氨氮、总氮、总磷和化学需氧量的平均削减率分别为62.15...     

潮汐流-潜流人工湿地对城市污染水体中氮的去除

为了探索人工湿地对城市污染水体的除氮效果,构建潮汐流(TF)与潜流(SF)人工湿地模拟组合(TF-SF),探讨水生植物和微生物群落对氮的去除效果的影响.结果 表明,TF-SF对氨氮和总氮都有较好的处理效果,去除率分别为55.59％-78.59％和57.52％-81.29％.黄菖蒲地上部分氮积累量分别为195.05、111.18 mg·株-1,地下部分氮积累量分别为36.44、32.01 mg·株-1,黄菖蒲对污染水体中的氮去除发挥着重要作用.高通量测序分析表明,TF中黄菖蒲根部表现出较高的微生物丰富度、多样性,不动杆菌属、硝化螺菌属和亚硝化单胞菌属是人工湿地中主要的脱氮菌属,是氮去除的主要驱动者.     

水稻土中甲硫氨酸分解释放挥发性含硫气体的影响因素

为了探讨水稻土中含硫气体产生和释放的途径 ,在室内培养条件下 ,测定了南京水稻土中含硫气体的释放 .从该淹水土壤中测出 3种含硫气体 ;羰基硫 (COS)、二甲基硫 (DMS)和少量硫化氢 (H₂S)气体 .当土壤中加入甲硫氨酸后 ,DMS气体的释放量有了明显增加 ,此外还有大量甲硫醇 (CH₃SH)和二甲基二硫 (DMDS)气体测出 .而 COS在好氧条件 (普通大气淹水 )下的释放量明显增加 ,在厌氧条件 (充氮淹水 )下的释放量变化不明显 ;只有 H₂S的释放量几乎没变 .这些结果表明 ,甲硫氨酸的分解可能是 COS、DMS、CH₃SH和 DMDS的产生源之一 ,且释放含硫气体的种类明显不同于胱氨酸和半胱氨酸 .在好氧 (普通大气 )条件下 ,DMDS和 CH₃SH的释放量低于厌氧情况 (充氮气 )下的释放量 ,DMS则高于厌氧条件下的释放量 .这表明 ,水稻土中甲硫氨酸分解产生 DMDS和 CH3SH需较强的还原条件 ,产生这 2种气体的微生物需要严格的厌氧条件 .产生 DMS的微生物则比前者需要高一些的含氧量 .土壤 pH值和含水量及光照对甲硫氨酸分解释放含硫气体均有影响 .各含硫气体在持水率 50%、普通大气、光照条件下的释放量明显高于无光照条件下的释放量 .     

PTFE/C三相电极氧阴极还原法生产过氧化氢

设计了隔膜体系电解槽,制作了聚四氟乙烯(PTFE)/碳黑三相气体扩散电极,系统研究了隔膜、电流密度、电极间距、初始溶液酸度、电解质、空气量和时间等因素对过氧化氢累积产生浓度和电流效率的影响。结果表明,在有隔膜体系,电流密度为70 m A/cm2,电极间距为1 cm,初始p H=0.5,电解质为0.10 mol/L Na2SO4溶液,空气量为40 m L/min的条件下,电解时间1 h时过氧化氢累积浓度最高可至20 096.05 mg/L,此时对应的电流效率为63.37%。在确定的最佳条件下,进行电解液循环实验,1 h时电流效率升高到98.4%,12 h之后,过氧化氢累积浓度为46 042.43 mg/L。实验原位产生的高浓度酸性过氧化氢溶液可以直接应用于Fenton试剂。     

Characteristics, evolution, and regional differences of biomass burning particles in the Sichuan Basin, China

The Sichuan Basin has experienced serious air pollution from fine particulate matter (PM_2.5) in the past few years with biomass burning has been identified as a major source of PM_2.5 in this region. We used single particle aerosol mass spectrometer to investigate the characteristics of biomass burning particles in three interacting cities representing different types of urban environment in the Sichuan Basin. A total of 739,794, 279,610, and 380,636 biomass burning particles were detected at Ya'an, Guang'an, and Chengdu, which represented 42%, 69%, and 61%, respectively, of the total number of particles. We analyzed the chemical composition, transportation, and evolution of biomass burning particles. The contribution of K-elemental carbon and K-secondary inorganic particles was highest in Ya'an (36%) and Guang'an (47%), respectively, reflecting the important role of fresh biomass burning particles and long-distance transport in these two cities. Air masses originating from different directions corresponded to different levels of PM_2.5 and the contributions of polluted clusters increased significantly on polluted days. Fresh and secondary inorganic biomass burning particles increased pollution at Ya'an and Guang'an, respectively, but dominated different stages of pollution in Chengdu. K-nitrate particles were formed by photochemical reactions, whereas K-sulfate particles were formed by both photochemical and liquid-phase reactions. Investigation of the degree of particle aging showed that there were more fresh particles at Ya'an and more aged particles at Guang'an. These results are useful in helping our understanding of the characteristics of biomass burning particles and evaluating their role in PM_2.5 pollution in the Sichuan Basin.     

甘肃省景观地球化学特征初探

分析了甘肃省境内的地球化学景观特征 ,将甘肃省划分为 6个不同的地球化学景观区 ,并依据甘肃省地质矿产局 2 0余年的 1:2 0万水系沉积物测量资料 ,统计出各景观区元素含量的算数平均值及标准离差 ,与全国相应元素的水系沉积物背景值进行了对比。     

不同面积小流域山洪泥石流预报模型研究——以北京市密云县为例

针对北京市密云县境内密云水库上游山洪泥石流发生特点,以系统科学为基本思想,将Bayes判别分析法引入山区小流域山洪泥石流预报模型建立之中。通过对北京市密云县境内密云水库上游影响山洪泥石流发生的系统内部要素和其外部环境条件进行综合分析,选择影响山洪泥石流发生的前15d实效降雨量和当日降雨量作为预报模型因子,分别建立了三种不同流域面积范围的山洪泥石流预报模型,所建立的山洪泥石流预报模型适用的流域面积范围分别为0.30～2.00 km2、2.00～5.00 km2和5.00～15.42 km2。经检验,三组预报模型的正确率分别为86.4%、92.9%和83.3%,均满足了Bayes判别分析法所规定的其验证正确率的要求,表明模型可以应用于研究区域不同流域面积范围的山洪泥石流预报。预报模型的建立为北京市密云县境内密云水库上游山洪泥石流的即时预报提供了一种简捷易行方法。     

北方沙尘对四川盆地环境空气质量影响和特征分析

利用沙尘天气资料和颗粒物浓度、激光雷达监测数据以及后向轨迹,分析浮尘天气的气象特征及传输路径,构建了浮尘天气对四川盆地各城市大气环境质量影响的量化指标,并利用该量化指标分析了浮尘天气对四川盆地各城市大气环境的影响,得出2013—2015年浮尘对四川盆地PM_(10)年均质量浓度的贡献,2013—2015年约为4.82、1.00、0.56μg/m~3;浮尘对PM_(10)年均质量浓度的贡献川西区域最大,川东北区域次之,川中区域最小,其贡献量分别为3.5、2.2、1.4μg/m~3。同时还进一步分析浮尘对区域PM_(10)影响差异的原因。