Research and application of method of oxygen isotope of inorganic phosphate in Beijing agricultural soils

Phosphorus (P) in agricultural ecosystems is an essential and limited element for plants and microorganisms. However, environmental problems caused by P accumulation as well as by P loss have become more and more serious. Oxygen isotopes of phosphate can trace the sources, migration, and transformation of P in agricultural soils. In order to use the isotopes of phosphate oxygen, appropriate extraction and purification methods for inorganic phosphate from soils are necessary. Here, we combined two different methods to analyze the oxygen isotopic composition of inorganic phosphate (δ¹⁸O_P) from chemical fertilizers and different fractions (Milli-Q water, 0.5 mol L^?1 NaHCO₃ (pH = 8.5), 0.1 mol L^?1 NaOH and 1 mol L^?1 HCl) of agricultural soils from the Beijing area. The δ¹⁸O_P results of the water extracts and NaHCO₃ extracts in most samples were close to the calculated equilibrium value. These phenomena can be explained by rapid P cycling in soils and the influence of chemical fertilizers. The δ¹⁸O_P value of the water extracts and NaHCO₃ extracts in some soil samples below the equilibrium value may be caused by the hydrolysis of organic P fractions mediated by extracellular enzymes. The δ¹⁸O_P values of the NaOH extracts were above the calculated equilibrium value reflecting the balance state between microbial uptake of phosphate and the release of intracellular phosphate back to the soil. The HCl extracts with the lowest δ¹⁸O_P values and highest phosphate concentrations indicated that the HCl fraction was affected by microbial activity. Hence, these δ¹⁸O_p values likely reflected the oxygen isotopic values of the parent materials. The results suggested that phosphate oxygen isotope analyses could be an effective tool in order to trace phosphate sources, transformation processes, and its utilization by microorganisms in agricultural soils.     

Deep learning architecture for air quality predictions

With the rapid development of urbanization and industrialization, many developing countries are suffering from heavy air pollution. Governments and citizens have expressed increasing concern regarding air pollution because it affects human health and sustainable development worldwide. Current air quality prediction methods mainly use shallow models; however, these methods produce unsatisfactory results, which inspired us to investigate methods of predicting air quality based on deep architecture models. In this paper, a novel spatiotemporal deep learning (STDL)-based air quality prediction method that inherently considers spatial and temporal correlations is proposed. A stacked autoencoder (SAE) model is used to extract inherent air quality features, and it is trained in a greedy layer-wise manner. Compared with traditional time series prediction models, our model can predict the air quality of all stations simultaneously and shows the temporal stability in all seasons. Moreover, a comparison with the spatiotemporal artificial neural network (STANN), auto regression moving average (ARMA), and support vector regression (SVR) models demonstrates that the proposed method of performing air quality predictions has a superior performance.     

碱激发胶凝材料及其固化Pb^2＋的试验研究

对碱激胶凝材料（碱-偏高岭土、碱-矿渣和碱-粉煤灰）与水-水泥体系固化Ph^2＋进行了试验研究,其中水-水泥体系为对比样。结果表明：对于相同稠度的碱激发胶凝材料,即使Pb^2＋含量达到2．4％,除了碱-粉煤灰的抗压强度略低外,其他都达到30MPa以上,满足填埋或做建筑基材的使用要求;与水泥相比,碱激发胶凝材料能显著降低重金属离子（Ph^2＋）浸出浓度,其规律性与其NH4交换容量大小的规律性一致,与其固化体的抗压强度的大小没有相关性。     

Carbon isotope analysis for source identification of atmospheric formaldehyde and acetaldehyde in Dinghushan Biosphere Reserve in South China

Formaldehyde and acetaldehyde are two most abundant carbonyls in ambient air. Biogenic emission has been proposed as a significant source other than anthropogenic emissions and atmospheric secondary formation. Here at a forest site in South China, the carbon isotopic compositions of formaldehyde and acetaldehyde emitted from leaves of three tree species (Litsea rotundifolia, Canarium album and Castanea henryi) were measured in comparison with the bulk carbon isotopic compositions of tree leaves. δ¹³C data of the emitted aldehydes (from ?31‰ to ?46‰) were quite different for tree species, which were all more depleted in ¹³C than the tree-leaf bulk δ¹³C values (from ?27‰ to ?32‰). Formaldehyde in ambient air at the forest site had δ¹³C values different from those of leaf-emitted formaldehyde, indicating other sources for ambient formaldehyde apart from direct emission from leaves, most probably the photooxidation of biogenic hydrocarbon like isoprene and monoterpene. The δ¹³C differences of acetaldehyde between ambient data and those of tree leaves emission were less than 1‰, implying direct biogenic emission as the dominant source.     

Incorporating layer- and local-scale heterogeneities in numerical simulation of unsaturated flow and tracer transport

This study characterizes layer- and local-scale heterogeneities in hydraulic parameters (i.e., matrix permeability and porosity) and investigates the relative effect of layer- and local-scale heterogeneities on the uncertainty assessment of unsaturated flow and tracer transport in the unsaturated zone of Yucca Mountain, USA. The layer-scale heterogeneity is specific to hydrogeologic layers with layerwise properties, while the local-scale heterogeneity refers to the spatial variation of hydraulic properties within a layer. A Monte Carlo method is used to estimate mean, variance, and 5th, and 95th percentiles for the quantities of interest (e.g., matrix saturation and normalized cumulative mass arrival). Model simulations of unsaturated flow are evaluated by comparing the simulated and observed matrix saturations. Local-scale heterogeneity is examined by comparing the results of this study with those of the previous study that only considers layer-scale heterogeneity. We find that local-scale heterogeneity significantly increases predictive uncertainty in the percolation fluxes and tracer plumes, whereas the mean predictions are only slightly affected by the local-scale heterogeneity. The mean travel time of the conservative and reactive tracers to the water table in the early stage increases significantly due to the local-scale heterogeneity, while the influence of local-scale heterogeneity on travel time gradually decreases over time. Layer-scale heterogeneity is more important than local-scale heterogeneity for simulating overall tracer travel time, suggesting that it would be more cost-effective to reduce the layer-scale parameter uncertainty in order to reduce predictive uncertainty in tracer transport.     

铁改性海泡石除锑的影响因素研究

选择廉价海泡石, 用氯化铁对其改性。研究铁改性海泡石对锑的吸附特性。结果表明,氯化铁浓度、吸附时间、初始锑浓度以及温度等因素对锑的吸附影响较大,溶液初始pH影响不明显。在初始锑浓度50 mg/L,pH 6.8,5%氯化铁改性海泡石投加量为2 g/L,吸附90 min, 温度35℃下,吸附量可达21.6 mg/g。海泡石对吸附锑具有缓冲特性,溶液的初始pH值在3.1～10.1范围时,吸附后溶液的最终pH值为8～8.5。IMS吸附锑是放热过程。改性后海泡石比表面积增大,表面羟基数量增加,导致其吸附能力增强。通过XRD谱图并未发现铁晶体的存在。     

微生物絮凝剂改善城市污水厂浓缩污泥脱水性能的研究

采用酱油曲霉(Aspergillus sojae)产生的微生物絮凝剂(MBF)作为污泥絮凝脱水剂,对城市污水处理厂浓缩污泥进行调理,确定该絮凝剂对浓缩污泥脱水的处理工艺参数为：微生物絮凝液最佳投加体积为6%～8%（体积比）,发挥絮凝作用的最适污泥温度为28～32℃,最适pH为6～7。经微生物絮凝剂调理的污泥在3 000 r/min离心9 min,污泥脱水率高达82.7%,滤饼含水率降低至77.3%,污泥脱水后体积减至原来的1/5左右。     

脉冲电晕反应器结构对乙硫醇消除效果的影响

研究了脉冲电晕等离子体反应器结构的变化对乙硫醇消除效果的影响规律。结果表明,在反应器内设置折流板,可以增加气流的湍动程度,有利于活性粒子与污染物的充分接触,从而提高消除率。高压电极间距对电晕区范围及消毒效果有较大影响,间距较小将导致各电极产生的电场相互干扰明显,消除率减小;而电极间距过大,虽然电极间电场分布相互干扰小,但是反应器内可排布的电极数减少,总电晕区减少,消除率也减小。根据实验结果,电极间距设置为50 mm比较合理。另外,在相同的电场强度和脉冲频率下,毛刺形高压电极比线电极结构能耗低,能量利用率高。     

三氯生在碳纳米管上的吸附

药品和个人护理用品(PPCPs)已成为一个引起广泛关注的新的环境问题。采用碳纳米管（CNTs）对水溶液中的三氯生进行吸附处理,考察了碳纳米管粒径及用量、温度、pH、振荡时间等因素对三氯生去除率的影响。研究结果表明,碳纳米管能快速吸附水中的三氯生,粒径较小的碳纳米管可获得较高的三氯生去除率;低温有利于吸附反应的进行;pH在6.5～7.0时,三氯生的去除率可达97%。三氯生在碳纳米管上的吸附可以很好地用Langmuir和Freundlich吸附等温方程进行描述。