厌氧条件下砂壤水稻土N2、N2O、NO、CO2和CH4排放特征

了解厌氧条件土壤反硝化气体(N2、N2O和NO)、CO2和CH4排放特征,是认识反硝化过程机制的基础,并有助于制定合理的温室气体减排措施.定量反硝化产物组成,可为氮转化过程模型研发制定正确的关键过程参数选取方法或参数化方案.本研究选取质地相同(砂壤土)的两个水稻土为研究对象,通过添加KNO3和葡萄糖的混合溶液,将培养土壤的初始NO-3和DOC含量分别调节到50 mg·kg-1和300 mg·kg-1,采用氦环境培养-气体及碳氮底物直接同步测定方法,研究完全厌氧条件下土壤N2、N2O、NO、CO2和CH4的排放特征,并获得反硝化气态产物中各组分的比率.结果表明,在整个培养过程中,两个供试土壤的N2、N2O和NO累积排放量分别为6~8、20和15~18 mg·kg-1,这些气体排放量测定结果可回收土壤NO-3变化量的95%~98%,反硝化气态产物以N2O和NO为主,其中3种组分的比率分别为15%~19%(N2)、47%~49%(N2O)和34%~36%(NO);但反硝化气体产物组成的逐日动态均显现为从以NO为主逐渐过渡到以N2O为主,最后才发展到以N2为主.以上结果说明,反硝化气体产物组成是随反硝化进程而变化的,在以气体产物组成比率作为关键参数计算各种反硝化气体产生率或排放率的模型中,很有必要重视这一点.     

三江平原泥炭沼泽孔隙水甲烷浓度变化动态及其影响因子

湿地土壤孔隙水甲烷浓度变化动态对于揭示湿地碳循环过程具有重要作用.于2012年和2013年对三江平原毛苔草泥炭沼泽不同土壤深度孔隙水甲烷浓度的季节变化动态进行监测,并分析了其关键影响因子.结果表明:植物生长季孔隙水甲烷浓度呈单峰变化趋势,不同土层甲烷浓度峰值(80.45~490.95μmol·L-1)主要集中在湿润的生长季末,但年际间存在显著差异;从土壤剖面来看,土壤融通之后,孔隙水中甲烷浓度随着土壤深度的增加而增加;土壤表层(5 cm和10 cm)甲烷浓度主要受到株高(R2=0.6,p=0.005)和土壤充水孔隙率(R2=0.36,p=0.01)的影响,而深层(20~40 cm)甲烷浓度主要受到土壤温度等因素的综合影响.研究还表明,表层土壤孔隙水甲烷浓度能够解释生长季甲烷排放通量变化的26%~60%,而且短期的极端降雨事件可能不会对甲烷浓度以及甲烷排放产生即时影响,而是出现大约一周的延迟(time lag)现象,这主要取决于实际土壤湿度.     

北京市MODIS气溶胶光学厚度与PM_(10)质量浓度的相关性分析

利用北京地区2012年1—12月NASA MODIS气溶胶光学厚度(AOD)和通过空气污染指数(API)转换得到的PM10质量浓度进行了相关性分析.结果发现,二者的直接相关程度较低,在引入季节变化的气溶胶标高且考虑了气溶胶的垂直分布后,进行标高订正,二者的相关系数有所提高;在考虑了湿度影响因子后,进行湿度订正,二者的相关系数显著提高;引入平均风速、平均气温和平均气压等气象因素,进行多元回归分析,相关系数进一步提高.证实了卫星遥感气溶胶光学厚度在经过垂直和湿度订正并考虑气象因素的情况下,可以作为监测北京地区颗粒物污染物地面分布的一个有效手段.     

环境烟草烟气粒径分布及其对光散射的影响

为了测量典型办公室内环境中环境烟草烟气悬浮颗粒物的数浓度和粒径分布变化,以及其对颗粒光散射的影响,在6.8 m×3.2mx2.8 m的试验间进行试验,采用测量范围为5～1 000 nm的DMS500扫描电迁移率粒径谱仪进行粒径测量.结果表明,不同卷烟样品的烟气粒径分布曲线近似,都可以用对数正态分布函数来描述.4种卷烟样品粒径分布及参数变化速率相似,在4 800 s内数中值粒径CMD平均值从105 nm增大至155 nm,几何标准差GSD平均值从1,58减小至1.45,CMD和GSD的变化趋势近似符合指数函数.利用基于Mueller光散射理论的程序计算烟颗粒对散射光的影响.粒径分布的变化显著改变了颗粒散射光强度,CMD最大使散射光强度增大7倍,GSD引起的强度变化较小.综合考虑烟气颗粒数浓度降低和粒径分布的变化,散射光强度最大增大3倍.     

采空区瓦斯涌出源位置对瓦斯分布影响的数值模拟

根据多孔介质渗流理论,利用Fluent软件,分别对采空区瓦斯在整个采空区均匀涌出、上邻近层及底板遗煤涌出2种情况下采空区瓦斯分布规律进行了数值模拟.结果表明:采空区瓦斯为上邻近层及底板遗煤处涌出时,沿走向方向,靠近上邻近层及底板处高体积分数瓦斯距离工作面较近;沿竖直方向,瓦斯体积分数分布呈钩状,靠近瓦斯涌出源处瓦斯体积分数最高;整个采空区均匀涌出时采空区瓦斯体积分数分布与上邻近层及底板遗煤涌出时有很大差别.因此,为了得到更符合实际情况的瓦斯分布规律,数值模拟时应按照现场实际的瓦斯涌出源位置建立模型.     

土壤及铁锰结核中锰氧化菌的氧化特性分析

利用从土壤铁锰结核及其附近土壤中分离筛选得到的4株锰氧化菌,研究了不同pH、Mn(Ⅱ)初始浓度下菌株的锰氧化效率及生长情况,并用SEM-EDS及TEM对菌株WHS26、GY16形成的生物氧化锰及水羟锰矿进行了表征.结果表明,pH及Mn(Ⅱ)初始浓度对菌株的锰氧化效率均有影响,4株菌在pH 7~8、Mn(Ⅱ)初始浓度为10~20 mmol·L-1时,锰氧化效率最高;GY16、WHS26形成的生物氧化锰的形貌与化学合成的水羟锰矿存在明显差异,前者呈胶膜状附着在菌株表面,后者呈结晶态.该结果可为生物氧化锰应用于重金属污染修复提供技术支撑.     

Prediction of effluent concentration in a wastewater treatment plant using machine learning models

Of growing amount of food waste, the integrated food waste and waste water treatment was regarded as one of the efficient modeling method. However, the load of food waste to the conventional waste treatment process might lead to the high concentration of total nitrogen(T-N) impact on the effluent water quality. The objective of this study is to establish two machine learning models—artificial neural networks(ANNs) and support vector machines(SVMs), in order to predict 1-day interval T-N concentration of effluent from a wastewater treatment plant in Ulsan, Korea. Daily water quality data and meteorological data were used and the performance of both models was evaluated in terms of the coefficient of determination(R~2), Nash–Sutcliff efficiency(NSE), relative efficiency criteria(d rel). Additionally, Latin-Hypercube one-factor-at-a-time(LH-OAT) and a pattern search algorithm were applied to sensitivity analysis and model parameter optimization, respectively. Results showed that both models could be effectively applied to the 1-day interval prediction of T-N concentration of effluent. SVM model showed a higher prediction accuracy in the training stage and similar result in the validation stage.However, the sensitivity analysis demonstrated that the ANN model was a superior model for 1-day interval T-N concentration prediction in terms of the cause-and-effect relationship between T-N concentration and modeling input values to integrated food waste and waste water treatment. This study suggested the efficient and robust nonlinear time-series modeling method for an early prediction of the water quality of integrated food waste and waste water treatment process.     

Predicted no-effect concentrations for mercury species and ecological risk assessment for mercury pollution in aquatic environment

Mercury(Hg) exists in different chemical forms presenting varied toxic potentials. It is necessary to explore an ecological risk assessment method for different mercury species in aquatic environment. The predicted no-effect concentrations(PNECs) for Hg(Ⅱ) and methyl mercury(Me Hg) in the aqueous phase, calculated using the species sensitivity distribution method and the assessment factor method, were 0.39 and 6.5 × 10-3μg/L, respectively. The partition theory of Hg between sediment and aqueous phases was considered, along with PNECs for the aqueous phase to conduct an ecological risk assessment for Hg in the sediment phase. Two case studies, one in China and one in the Western Black Sea, were conducted using these PNECs. The toxicity of mercury is heavily dependent on their forms,and their potential ecological risk should be respectively evaluated on the basis of mercury species.     

Ozone concentrations, flux and potential effect on yield during wheat growth in the Northwest-Shandong Plain of China

Ozone (O₃) concentration and flux (F_o) were measured using the eddy covariance technique over a wheat field in the Northwest-Shandong Plain of China. The O₃-induced wheat yield loss was estimated by utilizing O₃ exposure-response models. The results showed that: (1) During the growing season (7 March to 7 June, 2012), the minimum (16.1 ppbV) and maximum (53.3 ppbV) mean O₃ concentrations occurred at approximately 6:30 and 16:00, respectively. The mean and maximum of all measured O₃ concentrations were 31.3 and 128.4 ppbV, respectively. The variation of O₃ concentration was mainly affected by solar radiation and temperature. (2) The mean diurnal variation of deposition velocity (V_d) can be divided into four phases, and the maximum occurred at noon (12:00). Averaged V_d during daytime (6:00–18:00) and nighttime (18:00–6:00) were 0.42 and 0.14 cm/sec, respectively. The maximum of measured V_d was about 1.5 cm/sec. The magnitude of V_d was influenced by the wheat growing stage, and its variation was significantly correlated with both global radiation and friction velocity. (3) The maximum mean F_o appeared at 14:00, and the maximum measured F_o was − 33.5 nmol/(m²·sec). Averaged F_o during daytime and nighttime were − 6.9 and − 1.5 nmol/(m²·sec), respectively. (4) Using O₃ exposure-response functions obtained from the USA, Europe, and China, the O₃-induced wheat yield reduction in the district was estimated as 12.9% on average (5.5%–23.3%). Large uncertainties were related to the statistical methods and environmental conditions involved in deriving the exposure-response functions.     

Effect of AlCl3 concentration on nanoparticle removal by coagulation

In recent years, engineered nanoparticles, as a new group of contaminants emerging in natural water, have been given more attention. In order to understand the behavior of nanoparticles in the conventional water treatment process, three kinds of nanoparticle suspensions, namely multi-walled carbon nanotube-humic acid (MWCNT-HA), multi-walled carbon nanotube-N,N-dimethylformamide (MWCNT-DMF) and nanoTiO₂-humic acid (TiO₂-HA) were employed to investigate their coagulation removal efficiencies with varying aluminum chloride (AlCl₃) concentrations. Results showed that nanoparticle removal rate curves had a reverse “U” shape with increasing concentration of aluminum ion (Al^3 +). More than 90% of nanoparticles could be effectively removed by an appropriate Al^3 + concentration. At higher Al^3 + concentration, nanoparticles would be restabilized. The hydrodynamic particle size of nanoparticles was found to be the crucial factor influencing the effective concentration range (ECR) of Al^3 + for nanoparticle removal. The ECR of Al^3 + followed the order MWCNT-DMF > MWCNT-HA > TiO₂-HA, which is the reverse of the nanoparticle size trend. At a given concentration, smaller nanoparticles carry more surface charges, and thus consume more coagulants for neutralization. Therefore, over-saturation occurred at relatively higher Al^3 + concentration and a wider ECR was obtained. The ECR became broader with increasing pH because of the smaller hydrodynamic particle size of nanoparticles at higher pH values. A high ionic strength of NaCl can also widen the ECR due to its strong potential to compress the electric double layer. It was concluded that it is important to adjust the dose of Al^3 + in the ECR for nanoparticle removal in water treatment.