g-C_3N_4/C@Bi_2MoO_6复合光催化剂的制备及其光催化活性

通过水热合成法和液相沉积法制备g-C_3N_4/C@Bi_2MoO_6复合光催化剂,并采用X射线衍射、扫描电子显微镜、氮气吸脱附、紫外-可见漫反射等技术对其进行表征。研究了可见光下g-C_3N_4/C@Bi_2MoO_6催化降解罗丹明B(Rh B)的影响因素,并对其光催化反应机理进行初步探讨。实验结果表明:g-C_3N_4掺杂量为60%(w)时g-C_3N_4/C@Bi_2MoO_6的光催化活性最高;在60%g-C_3N_4/C@Bi_2MoO_6的投加量为1.00 g/L、初始Rh B质量浓度为2.50 mg/L、可见光照射150 min的条件下,Rh B的降解率达到97.90%;在g-C_3N_4/C@Bi_2MoO_6光催化降解体系中,h~+和·O_2~-是主要活性物种。     

Preliminary studies on potential remediation of acid mine drainage‐impacted soils by amendment with drinking‐water treatment residuals

Mining operations result in a wide range of environmental impacts: acid mine drainage (AMD) and acid sulfate soils being among the most common. Due to their acidic pH and high soluble metal concentrations, both AMD and acid sulfate soils can severely damage the local ecosystems. Proper post‐mining management practices are necessary to control AMD‐related environmental issues. Current AMD‐impacted soil treatment technologies are rather expensive and typically not environmentally sustainable. We conducted a 60‐day bench‐scale study to evaluate the potential of a cost‐effective and environment‐friendly technology in treating AMD‐impacted soils. The metal binding and acid‐neutralizing capacity of an industrial by‐product, drinking water treatment residuals (WTRs) were used for AMD remediation. Two types of locally generated WTRs, an aluminum‐based WTR (Al‐WTR) and a lime‐based WTR (Ca‐WTR) were used. Highly acidic AMD‐impacted soil containing very high concentrations of metals and metalloids, such as iron, nickel, and arsenic, was collected from the Tab‐Simco coal mine in Carbondale, Illinois. Soil amendment using a 1:1 Al‐ and Ca‐WTR mix, applied at 5 and 10 percent rates significantly lowered the soluble and exchangeable fractions of metals in the AMD‐impacted soil, thus lowering potential metal toxicity. Soil pH increased from an extremely acidic 2.69 to a near‐neutral 6.86 standard units over the 60‐day study period. Results from this preliminary study suggest the possibility of a successful scale‐up of this innovative, cost‐effective, and environmentally sustainable technology for remediating AMD‐impacted acid sulfate soils.     

Water Management Decision Making in the Face of Multiple Forms of Uncertainty and Risk

In the Wasatch Range Metropolitan Area of Northern Utah, water management decision makers confront multiple forms of uncertainty and risk. Adapting to these uncertainties and risks is critical for maintaining the long‐term sustainability of the region's water supply. This study draws on interview data to assess the major challenges climatic and social changes pose to Utah's water future, as well as potential solutions. The study identifies the water management adaptation decision‐making space shaped by the interacting institutional, social, economic, political, and biophysical processes that enable and constrain sustainable water management. The study finds water managers and other water actors see challenges related to reallocating water, including equitable water transfers and stakeholder cooperation, addressing population growth, and locating additional water supplies, as more problematic than the challenges posed by climate change. Furthermore, there is significant disagreement between water actors over how to best adapt to both climatic and social changes. This study concludes with a discussion of the path dependencies that present challenges to adaptive water management decision making, as well as opportunities for the pursuit of a new water management paradigm based on soft‐path solutions. Such knowledge is useful for understanding the institutional and social adaptations needed for water management to successfully address future uncertainties and risks.     

Irrigation Water Allocation Using an Inexact Two‐Stage Quadratic Programming with Fuzzy Input under Climate Change

Agricultural irrigation accounts for nearly 70% of the total water use around the world. Uncertainties and climate change together exacerbate the complexity of optimal allocation of water resources for irrigation. An interval‐fuzzy two‐stage stochastic quadratic programming model is developed for determining the plans for water allocation for irrigation with maximum benefits. The model is shown to be applicable when inputs are expressed as discrete, fuzzy or random. In order to reflect the effect of marginal utility on benefit and cost, the model can also deal with nonlinearities in the objective function. Results from applying the model to a case study in the middle reaches of the Heihe River basin, China, show schemes for water allocation for irrigation of different crops in every month of the crop growth period under various flow levels are effective for achieving high economic benefits. Different climate change scenarios are used to analyze the impact of changing water requirement and water availability on irrigation water allocation. The proposed model can aid the decision maker in formulating desired irrigation water management policies in the wake of uncertainties and changing environment.     

Optimization of extraction of oil and biodiesel from Thespesia populnea seed oil by alkali catalyst in India

Thespesia populnea oil was new source of biodiesel. Crude Thespesia populnea oil was used as feedstock for biodiesel production by alkali-catalyzed methanolysis. The reaction in the presence of NaOH as catalyst was carried out to investigate the optimum conditions and to study the effects of variables on the reaction. A methanol to oil ratio of 6:1, sodium methoxide catalyst concentration of 1.5%, mixing intensity of 250 rpm and reaction temperature of 60°C offered the best Thespesia populnea seed oil methyl esters (biodiesel) yield (92.6%). The methyl ester content under these optimum conditions was 92.6% w/w, and all of the measured properties of the Thespesia populnea biodiesel (TPME) met the international standards ASTM D 6751-02. The results reveal that all of the reaction variables in this study had positive effects on the reaction. The results of the present study indicated that TPME could be a potential alternative to petrodiesel     

Evaluating anthropogenic N inputs to diverse lake basins: A case study of three Chinese lakes

The environmental degradation of lakes in China has become increasingly serious over the last 30 years and eutrophication resulting from enhanced nutrient inputs is considered a top threat. In this study, a quasi-mass balance method, net anthropogenic N inputs (NANI), was introduced to assess the human influence on N input into three typical Chinese lake basins. The resultant NANI exceeded 10 000 kg N km⁻² year⁻¹ for all three basins, and mineral fertilizers were generally the largest sources. However, rapid urbanization and shrinking agricultural production capability may significantly increase N inputs from food and feed imports. Higher percentages of NANI were observed to be exported at urban river outlets, suggesting the acceleration of NANI transfer to rivers by urbanization. Over the last decade, the N inputs have declined in the basins dominated by the fertilizer use but have increased in the basins dominated by the food and feed import. In the foreseeable future, urban areas may arise as new hotspots for nitrogen in China while fertilizer use may decline in importance in areas of high population density.

Electronic supplementary material

The online version of this article (doi:10.1007/s13280-015-0638-8) contains supplementary material, which is available to authorized users.     

pH对沟渠沉积物截留农田排水沟渠中氮、磷的影响研究

通过摇瓶动态实验和箱体静止实验,研究了不同pH条件下沟渠沉积物对农田流失氮、磷的截留效应,分析了pH对氮、磷截留效应及其界面交换作用的影响.结果表明:在实验pH变化范围内,沟渠沉积物对NH 4-N的吸附量和NO-2-N的硝化量以及对TN的截留率都是随着pH的增加而增加;沟渠沉积物对总溶解性磷(TDP)的吸附量随着pH的增加而增加,TP的截留率在5 d前随pH的增加而增加,但在此后基本不发生变化;在不同的pH下,通过影响微生物的活动直接或间接影响氮的界面交换行为,同时pH通过影响沉积物的吸附作用和离子交换作用来影响磷在沉积物-水界面的交换行为.阐明pH对沟渠沉积物氮、磷截留效应的影响有助于掌握氮、磷在农田排水沟渠中的迁移转化机理,从而对控制农业面源污染具有重要的意义.     

N和P对锥状斯氏藻(Scrippsiellat trochoidea)生长及孢囊形成的影响

在实验室设置了5个N、P浓度梯度,研究了它们对锥状斯氏藻（Scrippsiella trochoidea）营养细胞生长和孢囊形成的综合效应。结果表明,当N、P浓度分别超过10和1．5μg／L时,就能维持锥状斯氏藻一定的种群数量,而在高N、P浓度组（N浓度为500μg／L,P浓度为74μg／L组）的生长势态明显优于其他浓度组,稳定生长期持续时间较长,且有着较高的细胞比生长速率。孢囊一般在营养细胞达到稳定生长期后开始形成,但低营养盐浓度组孢囊开始形成的时间较早。各试验组孢囊形成率相近,最终形成率为17．8％～35．6％。     

Spatiotemporal Variability of Modeled Watershed Scale Surface‐Depression Storage and Runoff for the Conterminous United States

This study explores the viability of using simulated monthly runoff as a proxy for landscape‐scale surface‐depression storage processes simulated by the United States Geological Survey’s National Hydrologic Model (NHM) infrastructure across the conterminous United States (CONUS). Two different temporal resolution model codes (daily and monthly) were run in the NHM with the same spatial discretization. Simulated values of daily surface‐depression storage (treated as a decimal fraction of maximum volume) as computed by the daily Precipitation‐Runoff Modeling System (NHM‐PRMS) and normalized runoff (0 to 1) as computed by the Monthly Water Balance Model (NHM‐MWBM) were aggregated to monthly and annual values for each hydrologic response unit (HRU) in the CONUS geospatial fabric (HRU; n = 109,951) and analyzed using Spearman’s rank correlation test. Correlations between simulated runoff and surface‐depression storage aggregated to monthly and annual values were compared to identify where which time scale had relatively higher correlation values across the CONUS. Results show Spearman’s rank values >0.75 (highly correlated) for the monthly time scale in 28,279 HRUs (53.35%) compared to the annual time scale in 41,655 HRUs (78.58%). The geographic distribution of HRUs with highly correlated monthly values show areas where surface‐depression storage features are known to be common (e.g., Prairie Pothole Region, Florida).     

Mitigating Impact of Devils Lake Flooding on the Sheyenne River Sulfate Concentration

Devils Lake is a terminal lake located in northeast North Dakota. Because of its glacial origin and accumulated salts from evaporation, the lake has a high concentration of sulfate compared to the surrounding water bodies. From 1993 to 2011, Devils Lake water levels rose by ~10 m, which flooded surrounding communities and increased the chance of an overspill to the Sheyenne River. To control the flooding, the State of North Dakota constructed two outlets to pump the lake water to the river. However, the pumped water has raised concerns about of water quality degradation and potential flooding risk of the Sheyenne River. To investigate these perceived impacts, a Soil and Water Assessment Tool (SWAT) model was developed for the Sheyenne River and it was linked to a coupled SWAT and CE‐QUAL‐W2 model that was developed for Devils Lake in a previous study. While the current outlet schedule has attempted to maintain the total river discharge within the confines of a two‐year flood (36 m³/s), our simulation from 2012 to 2018 revealed that the diversion increased the Sheyenne River sulfate concentration from an average of 125 to >750 mg/L. Furthermore, a conceptual optimization model was developed with a goal of better preserving the water quality of the Sheyenne River while effectively mitigating the flooding of Devils Lake. The optimal solution provides a “win–win” outlet management that maintains the efficiency of the outlets while reducing the Sheyenne River sulfate concentration to ≤600 mg/L.