燃煤电厂排放细颗粒物的水溶性无机离子特征综述

当前我国面临严重的大气细颗粒物(PM2.5)污染,燃煤电厂是大气中PM2.5的重要来源之一.为了实现国家"十一五"和"十二五"规划对二氧化硫(SO2)和氮氧化物(NOx)的总量减排目标,燃煤电厂大规模安装烟气脱硫和脱硝设施,这虽然减少了气态污染物转化生成的二次PM2.5,但另一方面也会对烟气中PM2.5的物理化学特征产生影响,有可能增加一次PM2.5的排放.本文综述了燃煤电厂排放PM2.5及其水溶性离子的粒径分布特征,重点介绍了脱硫和脱硝这两种烟气处理设施对燃煤电厂排放PM2.5的影响原理及相关研究结果,特别是对细颗粒物中水溶性离子(如SO2-4、Ca2+和NH+4)的影响.在目前我国PM2.5污染十分严重和燃煤电厂大量安装脱硫和脱硝装置的背景下,定量研究脱硫和脱硝对PM2.5排放特征的影响具有十分重要的意义.     

染料探针技术对二级出水中优势污染物的定量检测

分别以刚果红和中性红为染料探针,建立了牛血清蛋白质(BSA)和海藻酸多糖(SA)含量与共振光散射(RLS)发射光谱强度间的线性关系;以甲苯胺蓝为染料探针,建立了腐殖酸(HA)含量与紫外吸光度间的线性关系;优化了3种标准物质的检测浓度范围及溶液p H值条件;考察了染料探针分析方法对标准物的二元和三元混合样品中的回收率.结果表明在适宜的浓度范围内,BSA、HA、SA浓度与染料探针光谱强度间的线性相关系数R0.98,3种标准物在混合样品中的回收率不小于95%,标准误差低于0.11%.以紫外光谱和3D-EEM光谱特征作为城市污水二级出水样品中蛋白质、多糖和腐殖酸的定性依据,确认了4种二级出水样品中的优势污染物.通过染料-探针技术与国标法测得的多糖和蛋白质质量浓度的相对偏差在1.2%~0.04%之间.     

长江上游典型农业源溪流溶存氧化亚氮(N2O)浓度特征及影响因素

随着农业非点源氮（N）污染的加剧,农田周边溪流成为重要的活性N汇和潜在的氧化亚氮（N₂O）排放源.为查明长江上游农业源溪流中溶存N₂O浓度的全年动态变化特征,于2014年12月~2015年10月开展紫色土丘陵区典型农田源头溪流N₂O浓度的连续采样观测,采用水-气顶空平衡-气相色谱法测定顶空气体中N₂O浓度,根据相关参数计算出本研究水体中的溶存N₂O浓度,并同步测定溪流水体物理化学指标,分析水中溶存N₂O浓度的主要影响因素.结果表明,长江上游紫色土丘陵区的典型农业源溪流的硝态氮（NO₃^--N）是最主要的活性N赋存形态（年均1.45 mg·L^-1）,溪流水体溶存N₂O质量浓度（以N计）全年平均为0.57 μg·L^-1（范围0.26~1.28 μg·L^-1）,冬、春、夏和秋季的均值分别为0.63、0.45、0.53和0.64 μg·L^-1,但季节间无显著差异.溪流水体溶存N₂O浓度全年都处于过度饱和状态（饱和度年平均为203.9%,范围109.7%~546.5%）,可见,农业源溪流全年均为潜在的N₂O释放源.溪流溶存N₂O浓度的变化主要由水体NO₃^--N浓度决定,N₂O的主要产生机制为反硝化作用;溪流季节平均N₂O饱和度在夏、秋季显著高于冬、春季,水中溶存N₂O饱和度的变化主要受水温和NO₃^--N浓度的共同影响.研究还发现农业源溪流中溶存N₂O浓度在4~10月（湿润季节）间波动明显,较强降雨可促使其水中NO₃^--N浓度在雨后短期内升高,进而促进水体反硝化作用,导致雨后溪流中溶存N₂O浓度的增加.     

基于河岸带地球化学特征的河水-地下水交互边界识别——以广州市流溪河为例

河水-地下水交互作用对河流水质净化、流域水生态健康和河岸土地合理规划具有重要意义.本文以广州市流溪河为研究对象,实时监测河水和河岸带地下水基本理化指标并采集水样和土样进行水体主离子、氮形态、金属离子浓度、氘(δD)氧(δ~(18)O)同位素和土壤渗透系数(K)测试分析.结果表明:监测期间以河水侧向补给地下水为主,对地下水水位的影响范围在距河岸10 m内;距河岸1 m处地下水溶解氧(DO)浓度、电导率(EC)和氧化还原电位(ORP)变化明显,变异系数(n=7)分别为30.9%、42.0%和44.4%.河水和河岸带地下水水化学类型均为HCO_3-Ca型,受碳酸盐岩风化控制.河水入渗补给地下水初期,河岸带含水层向还原环境转化(ORP平均下降92.25 mV),非饱和带Mn氧化物发生还原性溶解,地下水中Mn~(2+)浓度逐渐增加并达最大值(0.52 mg·L~(-1));基于δD、δ~(18)O和Cl~-浓度的混合模型估算的河水对距河岸5 m处地下水的贡献率分别为10.4%、11.6%和11.5%,表明监测断面河水-地下水交互边界约在距河岸5 m处.     

基于好氧甲烷氧化菌的反硝化效能及微生物群落研究

采用气体循环序批式生物膜反应器（gcSBBR）,构建反硝化型甲烷好氧氧化（AME-D）系统.考察了进水氮负荷的影响,发现氮负荷为0.075kg/（m³·d）时,硝酸盐氮去除率达到98.93%,其反硝化速率为74.25mg/（L·d）,系统的甲烷日平均消耗量为35.91%（初期为50%）;扫描电子显微镜（SEM）分析结果显示,系统中的微生物主要以短杆菌（12~18 μm）为主,并存在少量的丝状菌（长150~200μm）;16S rRNA高通量测序结果显示,该系统中的甲烷氧化菌为Methylocaldum、Methylomonas、Methylococcus和Methylococcaceae_unclassified,反硝化菌为Denitratisoma、Hydrogenophaga、Azoarcus、Thiobacillus和Rhodobacter,其中主要的功能微生物为Methylocaldum、Denitratisoma和Hydrogenophaga,系统对氮的去除是由好氧甲烷氧化菌与反硝化菌协同实现.此外,系统中存在大量以甲醇和甲基胺类物质为生长基质的Methylophilaceae_uncultured（30.4%）.     

基于热异常遥感的冀南城市群工业能耗及大气污染

选取冀南城市群为研究区,基于2012~2016年VⅡRS卫星数据热异常点产品,结合工业能源消耗量、工业废气排放量以及空气质量数据,利用统计分析和空间分析探讨热异常点辐射强度的变化规律及其与工业能源消耗、污染物排放之间的关系.结果表明,热异常点的辐射强度可以表征工业能源消耗量,并间接反映工业生产规模与污染排放水平.辐射强度越大,工业生产规模越大.辐射强度与工业SO₂排放量呈较高的正相关,与NO_x排放量呈中度线性相关.PM₁₀、SO₂及NO₂浓度与工业能源消耗和热异常点辐射强度灰色关联度均较高.工业生产活动产生的污染物中,颗粒物对大气污染的贡献最高,其次为SO₂.2012~2016年,邯郸、石家庄以及廊坊的工业生产空间分布呈逐年收缩聚集的趋势,保定和沧州的工业生产分别出现向南、向西迁移趋势.     

Morphology, composition, and sources of individual aerosol particles at a regional background site of the YRD, China

Aerosol samples were collected at Lin'an, a background site of Yangtze River Delta(YRD).Morphology, size, composition, and mixing state of individual aerosol particles were characterized by transmission electron microscopy(TEM) coupled with energy dispersive X-ray spectroscopy(EDS), and the soluble ions of PM_(1.0) were studied by aerosol mass spectrometer(AMS). The daily average AMS mass concentrations of sulfate, nitrate, and ammonium were about 5.8, 8.6, and 5.6 μg/m~3, respectively. Individual aerosol particles were classified into seven types: S-rich, K-rich, organic matter(OM), soot, fly ash, metal, and mineral. S-rich particles were dominant in all size bins, and 51%(by number) of S-rich particles were internally mixed with other particles. The fraction of organic coating particles was 13.7% in morning, 25.2% in afternoon, and 11% in evening, suggesting that the strong photochemical process during afternoon produced more secondary organic aerosols(SOA) on the surface of inorganic particles. Fly ash and metal particles were abundant during the day, suggesting the influence of emissions from coal-fired power plants and steel plants. The results indicate that the intense industrial emissions in the YRD significantly transported to the background areas. PM_(2.5) concentration may be lower in background air than in urban air but complex mixing state of aerosol particles indicates that the long-range transported particles substantially influenced the background air quality.     

Temporal variability of visibility and its parameterizations in Ningbo, China

Simultaneous and continuous measurements of visibility, meteorological parameters and air pollutants were carried out at a suburban site in Ningbo from June 1, 2013 to May 31,2015. The characteristics of visibility and their relationships with air pollutants and meteorological factors were investigated using multiple statistical methods. Daily visibility ranged from 0.6 to 34.1 km, with a mean value of 11.8 km. During the 2-year experiment,43.4% of daily visibility was found to be less than 10.0 km and only 9.2% was greater than 20.0 km. Visibility was lower in winter with a frequency of 53.4% in the range of 0.0–5.0 km.Annual visibility had an obvious diurnal variation, with the lowest and highest visibility being 7.5 km at approximately 06:00 local time and 15.6 km at approximately 14:00 local time, respectively. Multiple correspondence analysis(MCA) indicated that the different ranges of visibility were significantly affected by different levels of pollutants and meteorological conditions. Based on the analyses, visibility was found to be an exponential function of PM_(2.5) concentrations within a certain range of relative humidity. Thus, nonlinear models combining multiple linear regressions with exponential regression were subsequently developed using the data collected from June 2014 to May 2015, and the data from June 2013 to May 2014 was used to evaluate the performance of the model. It was demonstrated that the derived models can quantitatively describe the relationships between visibility, air quality and meteorological parameters in Ningbo.     

Visible-light-driven photocatalytic inactivation of bacteriophage f2 by Cu-TiO2 nanofibers in the presence of humic acid

Pathogenic viruses in drinking water are great threats to public health. Visible-light-driven photocatalysis is a promising technology for virus inactivation. However, the existing photocatalytic antiviral research studies have mostly been carried out in single-component systems, neglecting the effect of natural organic matter, which exists widely in actual water bodies. In this paper, electrospun Cu-TiO₂ nanofibers were prepared as photocatalysts, and their photocatalytic antiviral performance in the presence of humic acid (HA) was comprehensively studied for the first time. The properties of the reaction mixture were measured during the reaction. In addition, the safety, reliability and stability of photocatalytic disinfection in the mixed system were evaluated. The results showed that the virus removal efficiency decreased with the increase of the HA concentration. The type of reaction solution, such as PBS buffer solution or water, did not affect the removal efficiency noticeably. Under acidic conditions, the electrostatic forces between photocatalysts and viruses were strengthened, leading to higher virus removal efficiency. As the reaction time went on, the pH value in the solution increased first and then tended to be stable, the conductivity remained stable, and the dissolved oxygen increased first and then decreased. The safety test showed that the concentration of Cu ions released into the solution was lower than specified by the international standards. No photoreactivation was observed, and the addition of HA significantly reduced the reutilization efficiency of the photocatalysts.     

水泥-电力行业的产业共生网络构建及区域案例研究

水泥工业作为工业生态系统的汇,能够多样化地利用其他行业的副产物,这种典型的产业共生模式可以通过减少资源和能源的消耗带来显著的CO₂减排效果.由于产业共生在水泥行业具有一定的普遍性及巨大的CO₂减排潜力,所以对水泥工业产业共生现状的了解与分析就显得尤为重要;而通过对产业共生现状的全面了解,才能对现有水泥行业产业共生的程度进行分析,并以此为参照,对未来不同政策与情景下的CO₂减排潜力进行量化与评估.为实现对产业共生实际情况的模拟,以水泥-电力行业的产业共生为例,采用最优化的方法,提出了一套基于一般统计数据来模拟产业共生实际情况的系统方法,将技术、经济与政策3类不同的决策变量影响纳入模型,以模拟出最接近真实情景的产业共生情况.为验证模型的有效性,对新乡市水泥-电力行业实际的产业共生情况进行分析.结果表明:新乡市水泥-电力行业间存在普遍的产业共生现象,实地调查中有77.8%（21家）的水泥制造企业利用粉煤灰作为水泥制造的原材料.将一般统计数据与实地调查数据对比发现,一般统计数据能较好地反映企业实际物质投入产出情况;利用一般统计数据,模型对新乡市产业共生网络结构模拟的准确率高达92.6%,显示该模型能较为有效地对产业共生的实际情况进行模拟.