城郊土壤共存元素对土壤作物系统Cd、Pb迁移的影响分析——以白银市城郊区为例

通过共存元素对土壤小麦系统Cd、Pb行为影响的调查研究发现：大田条件下共存元素以正对数模式与根系Cd、Pb密切相关,同种元素间相关程度最高;根系Cd、Pb积累主要取决于土壤环境Cd、Pb的含量,共存元素也产生一定的影响,认为要防止重金属通过食物链对人类的危害,就必须降低土壤环境中重金属的总量。     

气相色谱法测定土壤中挥发性硫化物

采用带硫化学发光检测器的气相色谱(GC-SCD),同时分离并测定土壤中硫化氢、羰基硫、甲硫醇、甲硫醚、二硫化碳和二甲基二硫等6种挥发性硫化物。通过优化仪器工作条件,使该方法在0.521μg/L~65.7μg/L范围内线性良好,方法检出限为0.58μg/L~1.76μg/L,标准气体5次测定结果的RSD为0.9%~8.3%。用该方法分析土壤在强还原条件下挥发性硫化物的排放量,结果表明,上述6种挥发性硫化物均有产生,且随培养时间的延长排放速率增加,硫化氢是其主要气体产物,占挥发性硫化物排放总量的79.1%。     

水稻土对Cu~(2+)吸附反应动力学及离子强度和磷酸根的影响

研究了水稻土对Cu2+的吸附反应动力学,并考察了p H和磷酸根2个因素对Cu2+吸附的影响。结果表明:水稻土对Cu2+的吸附反应速率可明显分为快、慢2个阶段,快速阶段主要是Cu2+结合在高亲和力位点,而慢速阶段则是结合在低亲和力位点。提高溶液p H可促进水稻土对Cu2+的吸附,降低溶液p H则将抑制Cu2+的吸附,这主要是因为p H可通过改变水稻土表面电荷的性质以及溶液Cu2+的形态来影响吸附反应。提高离子强度,将降低低p H条件下Cu2+的吸附量,而对高p H条件下Cu2+的吸附量影响较小,这表明水稻土对Cu2+存在很大比例的专性吸附。溶液中磷酸根的存在,可促进水稻土对Cu2+的吸附。本文所得到的研究结果对认识Cu2+在水稻土中的土壤环境行为及其污染控制有一定的理论意义。     

模拟降雨径流作用下红壤坡面侵蚀水动力学机制

土壤侵蚀过程受控于侵蚀外营力和土壤抗侵蚀性能,深入理解坡面流水动力学特性及其侵蚀动力是研究土壤侵蚀动力学机制的基础。利用可变坡土槽,通过不同雨强(60、90和120 mm/h)和径流冲刷(10、15和20 L/min)组合模拟试验,研究了第四纪黏土红壤坡面水流的水动力学特征参数及其与土壤侵蚀量间的关系。结果显示:降雨和径流冲刷影响了坡面产流产沙过程和坡面流水力学特性,其中平均流速v、平均水深h、雷诺数Re和水流功率ω均随降雨强度和上方来水流量的增加而增大,相对水深曼宁糙率n/h则减小,其水力学他参数(弗如德数Fr、阻力系数f和水流剪切力τ)变化规律不明显。坡面水流平均速度取值范围为0.21~0.45 m/s,平均水深取值范围为5.6~9.4 mm,在试验条件下红壤坡面侵蚀水流流态大部分均处于"紊流-急流区"。不论从径流角度看或是从泥沙角度分析,由相对水深和曼宁糙率系数两种水动力因子共同组成的复合水动力特征参数-相对水深曼宁糙率,是表征不同上方来水流量和降雨强度条件下第四纪粘土红壤坡面侵蚀特征的水动力参数。     

Evidence of new particle formation during post monsoon season over a high-altitude site of the Western Ghats,India

The formation of ultrafine particles, their growth, and associated characteristic features has been studied during new particle formation events over a high-altitude station of the Western Ghats during the 2014 post-monsoon season. Most of the events were observed during noon time where particle bursts in the nucleation-mode size range from 5 to 25 nm followed by sustained growth in size. This phenomenon persists for ～4–8 h with a growth rate of 1–2 nm h^–1. Peak concentrations of nucleation-mode particles during the event generally vary from 2300 to 5000 cm^–3. The mean growth rate is 1.4 ± 0.42 nm h^–1, particle formation rate is 1.14 ± 0.22 cm^–3 s^–1, coagulation sink is 0.35 ± 0.22 cm^–3 s^–1, and condensational sink is 15.4 ± 2.6?×?10^–3 s^–1. All these values are comparable with earlier results from Indian region. Comparison of size-segregated particle number concentration during days of new particle formation events and those without new particle formation were carried out showing a distinct variation in nucleation and Aitken mode with least variability associated with the accumulation mode.     

Does Including Soil Moisture Observations Improve Operational Streamflow Forecasts in Snow‐Dominated Watersheds?

Changing climate and growing water demand are increasing the need for robust streamflow forecasts. Historically, operational streamflow forecasts made by the Natural Resources Conservation Service have relied on precipitation and snow water equivalent observations from Snow Telemetry (SNOTEL) sites. We investigate whether also including SNOTEL soil moisture observations improve April‐July streamflow volume forecast accuracy at 0, 1, 2, and 3‐month lead times at 12 watersheds in Utah and California. We found statistically significant improvement in 0 and 3‐month lead time accuracy in 8 of 12 watersheds and 10 of 12 watersheds for 1 and 2‐month lead times. Surprisingly, these improvements were insensitive to soil moisture metrics derived from soil physical properties. Forecasts were made with volumetric water content (VWC) averaged from October 1 to the forecast date. By including VWC at the 0‐month lead time the forecasts explained 7.3% more variability and increased the streamflow volume accuracy by 8.4% on average compared to standard forecasts that already explained an average 77% of the variability. At 1 to 3‐month lead times, the inclusion of soil moisture explained 12.3‐26.3% more variability than the standard forecast on average. Our findings indicate including soil moisture observations increased statistical streamflow forecast accuracy and thus, could potentially improve water supply reliability in regions affected by changing snowpacks.     

Optimization-Based Atmospheric Plume Source Identification

This work applies optimization and an Eulerian inversion approach presented by Bagtzoglou and Baun in 2005 in order to reconstruct contaminant plume time histories and to identify the likely source of atmospheric contamination using data from a real test site for the first time. Present-day distribution of an atmospheric contaminant plume as well as data points reflecting the plume history allow the reconstruction and provide the plume velocity, distribution, and probable source. The method was tested to a hypothetical case and with data from the Forest Atmosphere Transfer and Storage (FACTS) experiment in the Duke experimental forest site. In the scenarios presented herein, as well as in numerous cases tested for verification purposes, the model conserved mass, successfully located the peak of the plume, and managed to capture the motion of the plume well but underestimated the contaminant peak.     

Volatile Organic Compounds from Coal Tar and Soil Vapor Samples at MGP Sites

This study characterized organic compounds found in New York State manufactured gas plant (MGP) coal tar vapors using controlled laboratory experiments from four separate MGP sites. In addition, a limited number of deep (0.3–1.2 m above coal tar) and shallow (1.2–2.4 m above coal tar) soil vapor samples were collected above the in situ coal tar source at three of these sites. A total of 29 compounds were consistently detected in the laboratory-generated coal tar vapors at 50°C, whereas 24 compounds were detected at 10°C. The compounds detected in the field sample results were inconsistent with the compounds found in the laboratory-generated samples. Concentrations of compounds in the shallow soil vapor sample were either non-detectable or substantially lower than those found in deeper samples, suggesting attenuation in the vadose zone. Laboratory-generated data at 50°C compared the (% non-aromatic)/(% aromatic) ratio and indicated that this ratio may provide good discrimination between coal tar vapor and common petroleum distillates.     

渗滤液耦合矿化垃圾制备甲烷氧化菌菌液

利用甲烷氧化菌菌液增加材料中甲烷氧化菌的数量,可以得到高甲烷氧化率的填埋场甲烷生物氧化覆盖材料。研究发现,渗滤液原水和渗滤液处理尾水均能促进甲烷氧化菌的生长,可利用渗滤液耦合矿化垃圾混合培养制备甲烷氧化菌菌液用于填埋场甲烷减排。填埋龄长的渗滤液原水有着较好的培养效果,得到的菌液在4 d内最高甲烷氧化速率达到2.68 mL/h,超过甲烷氧化菌培养液(nitrate minimal salt medium,NMS)的实验结果。渗滤液中总氮、无机碳、总有机碳和Ni元素的含量对甲烷氧化菌的培养过程影响较大,适用于甲烷氧化培养的渗滤液应满足:总氮1 400 mg/L,总有机碳55 mg/L,Ni元素0.4 mg/L,总磷含量较高。     

Estimation of sampling uncertainty for determination of pesticide residues in plant commodities

In order to provide residue data for refining the estimated sampling uncertainty, a coordinated research program was initiated for performing field studies on residues in individual items of leafy vegetables, small and large crops. The trials were carried out in 13 countries with 3 small fruits, 5 large crops, 2 medium/large crops and 3 leafy vegetables. The 25 pesticide active ingredients applied represented the dicarboximide (3), organophosphorus (8), synthetic pyrethroids (5), phthalimides (2), organochlorine (1) and other types of pesticides (6). In addition, 11 supervised field trials were performed in grapes and lettuce by the pesticide manufacturers, and their results were provided for evaluation. The studies represented actual agriculture practice around the world, and provide reliable data for estimation of sampling uncertainty. Based on the 12346 residue data, the best estimate for the relative sampling uncertainty for composite samples, assuming sample size of 10 for small crops and leafy vegetables and 5 for large crops, with 95% confidence limits in brackets are: small commodities: 0.25 (0.20–0.29); Brassica leafy vegetables: 0.20 (0.16–0.24); large commodities: 0.33 (0.29–0.38).