管道中烟道气流动传热及酸凝结规律

针对注烟道气稠油热采中管道输送烟道气酸凝结问题,以连续性方程、能量方程和动量方程为基础建立了烟道气沿管道流动与传热计算模型,计算了烟道气沿管道的压力分布、温度分布和酸凝结点距离,分析了不同入口参数和烟道气成分对管道中烟道气的压力、温度、酸凝结点的影响。结果表明:SO3或水蒸汽含量增加时,烟道气酸凝结点温度提高,凝结点距离减小;入口烟道气压力提高,烟道气压降变小,温降不变,酸凝结点距离减小;入口烟温升高,压降和温降都增大,酸凝结点距离增大;保温层厚度增加,温降减小,酸凝结点距离增大。计算和分析结果表明:减少烟道气中SO3或水蒸汽含量可以有效地增大酸凝结点距离,减轻管道腐蚀问题。     

Hg0 removal from flue gas over different zeolites modified by FeCl3

The elemental mercury removal abilities of three different zeolites (NaA, NaX, HZSM-5) impregnated with iron (III) chloride were studied on alab-scale fixed-bed reactor. X-ray diffraction, nitrogen adsorption porosimetry, Fourier transform infrared spectroscopy, X-ray photoelectron spectroscopy, and temperature programmed desorption (TPD) analy-ses were used to investigate the physicochemical properties. Results indicated that the pore structure and active chloride species on the surface of the samples are the key factors for physisorption and oxidation of Hg⁰, respectively. Relatively high surface area and micropore volume are beneficial to efficient mercury adsorption. The active Cl species generated on the surface of the samples were effective oxidants able to convert elemental mercury (Hg⁰) into oxidized mercury (Hg²⁺). The crystallization of NaCl due to the ion exchange effect during the impregnation of NaA and NaX reduced the number of active Cl species on the surface, and restricted the physisorption of Hg⁰. Therefore, the Hg⁰ removal efficiencies of the samples were inhibited. The TPD analysis revealed that the species of mercury on the surface of FeCl₃-HZSM-5 was mainly in the form of mercuric chloride(HgCl₂), while on FeCl₃-NaX and FeCl₃-NaA it was mainly mercuri coxide(HgO).     

Methane and nitrous oxide emissions from a subtropical coastal embayment (Moreton Bay, Australia)

Surface water methane (CH₄) and nitrous oxide (N₂O) concentrations and fluxes were investigated in two subtropical coastal embayments (Bramble Bay and Deception Bay, which are part of the greater Moreton Bay, Australia). Measurements were done at 23 stations in seven campaigns covering different seasons during 2010-2012. Water-air fluxes were estimated using the Thin Boundary Layer approach with a combination of wind and currents-based models for the estimation of the gas transfer velocities. The two bays were strong sources of both CH₄ and N₂O with no significant differences in the degree of saturation of both gases between them during all measurement campaigns. Both CH₄ and N₂O concentrations had strong temporal but minimal spatial variability in both bays. During the seven seasons, CH₄ varied between 500% and 4000% saturation while N₂O varied between 128 and 255% in the two bays. Average seasonal CH₄ fluxes for the two bays varied between 0.5 ± 0.2 and 6.0 ± 1.5 mg CH₄/(m²·day) while N₂O varied between 0.4 ± 0.1 and 1.6 ± 0.6 mg N₂O/(m²·day). Weighted emissions (t CO₂-e) were 63%-90% N₂O dominated implying that a reduction in N₂O inputs and/or nitrogen availability in the bays may significantly reduce the bays' greenhouse gas (GHG) budget. Emissions data for tropical and subtropical systems is still scarce. This work found subtropical bays to be significant aquatic sources of both CH₄ and N₂O and puts the estimated fluxes into the global context with measurements done from other climatic regions.     

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.     

焦化行业环境风险预测应用

以焦化行业中典型企业——徐州某焦化生产企业年产100万t捣固焦生产线项目为例,采用新的评价体系和数学模式对项目环境风险进行定量的预测评价,在环境风险定量预测方面作出了有益的尝试,对同类焦化行业环境风险预测及防范具有很好的借鉴意义.     

河流氧化亚氮产生和排放研究综述

氧化亚氮(N2O)是仅次于二氧化碳(CO2)和甲烷(CH4)的重要温室气体.由于人类活动对土地的影响导致河流系统中氮的可利用性增加,河流生态系统的N2O排放量正日益增长.本文对国内外河流水体N2O溶存浓度和饱和度、水-气界面排放通量及沉积物-水界面交换通量等数据进行了收集,并总结和分析了河流生态系统中N2O的产生机制及主要影响因子.     

降雨对城市草坪温室气体源汇效应的影响

利用静态箱法研究了夏季降雨对上海市城市草坪温室气体排放的影响,结果表明,晴天上海市城市草坪是N_2O和CO_2的源,CH_4的汇;降雨会削弱N_2O和CO_2排放,使得草坪由CH_4的汇转变为排放源。N_2O通量在晴天和雨后分别为1.37±3.47和1.06±2.67μmol/(m2·h),CO_2通量在晴天和雨后分别为13.33±8.59和6.46±2.61mmol/(m~2·h),CH_4通量在晴天和降雨后分别为-0.08±3.77和0.22±6.27μmol/(m~2·h)。明暗箱对比实验显示,草坪生态系统能有效缓解土壤对大气N_2O和CO_2的贡献。N_2O和CO_2通量与光合有效辐射和温度呈显著负相关(p0.01),CH_4和二者相关性不显著。降雨通过降低光合作用和温度,间接削弱城市草坪CO_2和N_2O的排放。降雨可能通过提高含水率抑制城市草坪对CH_4的吸收,促进其排放。