西辽河流域沙土的氨氮解吸行为研究

采用小型回填式土柱淋溶实验方法研究了西辽河流域沙土的氨氮解吸行为。结果表明,西辽河流域沙土的氨氮解吸行为符合Langmuir和Freundlich解吸等温式;沙土氨氮解吸比率Dr在0.44～0.99之间,平均为0.75,解吸迟滞性指数TⅡ在0.05～0.65之间,平均为0.29,沙土对氨氮的解吸迟滞性较强,解吸可逆性较弱。被吸附的氨氮解吸淋失的环境风险较小;沙土氨氮解吸比率Dr与土壤有机质含量、粘粒含量和粗粘粒含量呈极显著负相关,影响程度顺序为:有机质含量>粗粘粒含量>粘粒含量;解吸分配系数k和解吸迟滞性指数与土壤有机质含量分别呈极显著和显著正相关,与粘粒含量和粗粘粒含量没有相关性;草地、农田和林地结构由于土壤有机质和团聚体含量较高,氨氮解吸迟滞性较强,氨氮流失的环境风险较小,沙荒地结构氨氮流失的环境风险较大。     

粉煤灰对混合染料的吸附性能研究

以燃煤废弃物粉煤灰作为吸附剂,对活性红23和分散蓝56混合染料溶液进行吸附性能研究.实验结果表明:粉煤灰优先吸附离子型的活性染料,混合溶液中对活性红23的吸附能够在30 min达到平衡,而对分散蓝56的吸附则需要150 min才能够达到平衡,吸附动力学符合准二级吸附模型.在弱酸性环境中粉煤灰对分散染料的脱色高于碱性环境...     

桑枝基吸附剂的制备及其对阴离子染料的吸附

为了废弃桑枝的资源化,利用3-氯-2-羟丙基三甲基氯化铵(CTA)对桑枝进行醚化改性制备桑枝基吸附剂,通过正交实验优化了吸附剂的制备条件。采用制备的吸附剂吸附水中阴离子染料日落黄,研究了pH值、吸附剂投加量、吸附时间和吸附温度对吸附效果的影响,测定了日落黄在吸附剂上的吸附等温线。结果表明,制备吸附剂的最佳工艺条件为CTA与桑枝粉的质量比为0.5,NaOH与桑枝粉的质量比为1.0,微波功率为300 W,反应时间为3 min。制备的吸附剂对质量浓度为50 mg/L的日落黄的最大吸附去除率达92.0%。日落黄在吸附剂上的等温吸附线可用Langmuir方程和Freundlich方程来描述,饱和吸附容量为18.21 mg/g,吸附易于进行。吸附速率数据可以用准二级吸附动力学方程拟合,说明日落黄在吸附剂上的吸附以化学吸附为主。     

碱改性净水污泥对水中氨氮的吸附效能研究

采用氢氧化钠浸渍法改性净水污泥,研究了碱改性净水污泥对水中NH+4的去除性能.同时,考察了模拟废水pH、吸附剂投加量、NH+4初始浓度、吸附温度及吸附时间对吸附性能的影响.结果表明,当pH为弱酸性或中性,投加碱改性净水污泥20 g·L-1时,在室温下对初始浓度为50 mg·L-1的NH+4模拟废水振荡吸附120 min,可达到氨氮排放二级标准.将实验数据分别用吸附等温模型和动力学模型进行拟合,发现净水污泥对NH+4的吸附符合Langmuir模型和二级动力学模型,且净水污泥对氨氮的吸附包括静电吸引和离子交换两种作用机理.     

白银天然沸石对磷的吸附机理及性能研究

为探明天然沸石对磷的吸附机理,首先利用扫描电镜、X射线衍射、X荧光分析等对甘肃白银产天然沸石进行了表征,然后通过静态实验探讨了吸附时间、磷初始浓度、pH值等因素对沸石除磷性能的影响.研究结果表明：沸石对水溶液中磷的吸附动力学过程符合Pseudo second-order模型;Freudlich和Langmuir模型均可较好地描述沸石对磷的吸附特征;沸石对磷的吸附量随pH值增大而明显减小.     

交联壳聚糖对铀的吸附研究

以壳聚糖(CTS)为原料,在碱性条件下用环氧氯丙烷对壳聚糖进行化学改性,制得不溶水的交联壳聚糖(CCTS)。利用CCTS吸附铀(UO22+),探讨吸附动力学规律以及初始浓度,pH值的影响。实验结果表明,CCTS对UO22+的吸附符合Langmu ir吸附等温模型,并能用准二级速率方程对吸附动力学加以描述。当在CCTS为10 mg,pH为3,UO22+初始浓度为50μg/mL条件下,CCTS对UO22+的吸附去除率为98%以上。     

New Development in Study of the Faustmann Optimal Forest Harvesting

Chinese forest resources have become very scarce in the face of rapid economic growth demand, while the reform of collective forest right system is in full swing across the country. It will directly affect the regeneration level of forest resources and the diverse ecological value functions. In this article, the mainstream model paradigm of forest economics, that is, the basic framework of the Faustmann model and its evolution process are made in a more detailed explanation, especially the extended model in...     

Using the land transformation model to forecast vacant land

Growing or shrinking cities can experience increases in vacant land. As urban populations and boundaries fluctuate, holes can open in once tight urban areas. Many cities chase growth-oriented approaches to dealing with vacancies. It is critical to understand land-use alteration to accurately predict transformations of physical change in order to make better informed decisions about this phenomenon. This research utilizes the land transformation model (LTM), an artificial neural networking mechanism in Geographic Information Systems, to forecast vacant land. Variable influence on vacant land prediction and accuracy of the LTM is assessed by comparing input factors and patterns, using time-series data from 1990 to 2010 in Fort Worth, Texas, USA. Results indicate that the LTM can be useful in simulating vacant land-use changes but more precise mechanisms are necessary to increase accuracy. This will allow for more proactive decisions to better regulate the process of urban decline and regeneration.     

Robustness of Meteorological Droughts in Dynamically Downscaled Climate Simulations

We examine the robustness of a suite of regional climate models (RCMs) in simulating meteorological droughts and associated metrics in present‐day climate (1971‐2003) over the conterminous United States (U.S.). The RCMs that are part of North American Regional Climate Change Assessment Program (NARCCAP) simulations are compared with multiple observations over the climatologically homogeneous regions of the U.S. The seasonal precipitation, climatology, drought attributes, and trends have been assessed. The reanalysis‐based multi‐model median RCM reasonably simulates observed statistical attributes of drought and the regional detail due to topographic forcing. However, models fail to simulate significant drying trend over the Southwest and West. Further, reanalysis‐based NARCCAP runs underestimate the observed drought frequency overall, with the exception of the Southwest; whereas they underestimate persistence in the drought‐affected areas over the Southwest and West‐North Central regions. However, global climate model‐driven NARCCAP ensembles tend to overestimate regional drought frequencies. Models exhibit considerable uncertainties while reproducing meteorological drought statistics, as evidenced by a general lack of agreement in the Hurst exponent, which in turn controls drought persistence. Water resources managers need to be aware of the limitations of current climate models, while regional climate modelers may want to fine‐tune their parameters to address impact‐relevant metrics.     

Predicting occurrence of juvenile shark habitat to improve conservation planning

Fishing and habitat degradation have increased the extinction risk of sharks, and conservation strategies recognize that survival of juveniles is critical for the effective management of shark populations. Despite the rapid expansion of marine protected areas (MPAs) globally, the paucity of shark‐monitoring data on large scales (100s–1000s km) means that the effectiveness of MPAs in halting shark declines remains unclear. Using data collected by baited remote underwater video systems (BRUVS) in northwestern Australia, we developed generalized linear models to elucidate the ecological drivers of habitat suitability for juvenile sharks. We assessed occurrence patterns at the order and species levels. We included all juvenile sharks sampled and the 3 most abundant species sampled separately (grey reef [Carcharhinus amblyrhynchos], sandbar [Carcharhinus plumbeus], and whitetip reef sharks [Triaenodon obesus]). We predicted the occurrence of juvenile sharks across 490,515 km² of coastal waters and quantified the representation of highly suitable habitats within MPAs. Our species‐level models had higher accuracy (? ≥ 0.69) and deviance explained (≥48%) than our order‐level model (? = 0.36 and deviance explained of 10%). Maps of predicted occurrence revealed different species‐specific patterns of highly suitable habitat. These differences likely reflect different physiological or resource requirements between individual species and validate concerns over the utility of conservation targets based on aggregate species groups as opposed to a species‐focused approach. Highly suitable habitats were poorly represented in MPAs with the most restrictions on extractive activities. This spatial mismatch possibly indicates a lack of explicit conservation targets and information on species distribution during the planning process. Non‐extractive BRUVS provided a useful platform for building the suitability models across large scales to assist conservation planning across multiple maritime jurisdictions, and our approach provides a simple for method for testing the effectiveness of MPAs.