太湖地区稻作系统不同水体硝态氮同位素特征及污染源

为辨别稻作系统不同水体硝态氮来源,选择太湖地区典型稻作区域,应用硝态氮δ15N同位素技术,结合水化学方法(如NO3-, NH4+, TP, Cl-, SO42-),研究水稻施肥之前(4~5月),施肥期(6月),及施肥之后(7~8月)地表水和地下水硝态氮来源.结果表明,地表水和地下水硝态氮含量普遍较高.在施肥期,各水体硝态氮中δ15N均较低,表明该时期农业化肥是水体硝态氮的主要来源.在施氮前期,池塘水δ15N较低,其可能原因是受雨水的影响;而地下水δ15N较高,可能是水体发生了强烈的反硝化.在施肥后期,池塘水δ15N较高可能受养殖废水影响;地下水δ15N较低,可能受农田渗漏水的影响.河水和灌溉水硝态氮δ15N在各时期波动不大,其中河水硝态氮主要来源是生活污水和动物粪肥,但灌溉水硝态氮主要来源于雨水.本研究提出新的Cl-浓度和NO3-/Cl-物质的量比区间以辨别太湖地区水体硝态氮来源.     

Government green procurement spillovers: Evidence from municipal building policies in California

We study how government green procurement policies influence private-sector demand for similar products. Specifically, we measure the impact of municipal policies requiring governments to construct green buildings on private-sector adoption of the US Green Building Council?s Leadership in Energy and Environmental Design (LEED) standard. Using matching methods, panel data, and instrumental variables, we find that government procurement rules produce spillover effects that stimulate both private-sector adoption of the LEED standard and investments in green building expertise by local suppliers. These findings suggest that government procurement policies can accelerate the diffusion of new environmental standards that require coordinated complementary investments by various types of private adopter.     

两种介孔分子筛动态吸附VOCs的研究

采用模板剂法制备了孔道规整、大比表面积的2种介孔分子筛MCM-41和SBA-15,并以甲苯、二甲苯、三甲苯为吸附对象,考察了介孔分子筛动态吸附VOCs的性能.结果表明,增加VOCs分子尺寸和浓度,降低床层温度可大幅提高介孔分子筛吸附性能.SBA-15由于介孔壁上的微孔结构适合吸附低浓度、小分子VOCs;MCM-41更适合吸附高浓度、大分子VOCs.TPD脱附试验表明,VOCs在介孔材料表面150℃下就能基本脱附完全.     

The UN climate change negotiations and the role of the United States: assessing American leadership from Copenhagen to Paris

The role of American leadership in the UN climate negotiations that produced the 2015 Paris Agreement is examined. First, United States (US) climate goals are identified. Then, utilizing unique survey data collected at eight UN climate summits between 2008 and 2015, the extent to which the US was recognized as a leader by potential followers is investigated. Finally, the extent to which US goals are reflected in negotiation outcomes is evaluated. Recognition of the US as a leader varied over time, peaking at the UN climate meetings in Copenhagen and Paris, reflecting US leadership in shaping the outcomes of both meetings. Although the results reveal a divided leadership landscape in which the US must compete for leadership with other actors, such as the European Union and China, US leadership was crucial to the successful adoption of the Paris Agreement.     

^15N isotope fractionation in an aquatic food chain： Bellamya aeruginosa （Reeve） as an algal control agent

15N isotope tracer techniques and ecological modeling were adopted to investigate the fractionation of nitrogen,its uptake and transformation in algae and snail(Bellamya aeruginosa Reeve).Different algal species were found to differ in their uptake of nitrogen isotopes.Microcystis aeruginisa Ktz.demonstrated the greatest 15N accumulation capacity,with the natural variation in isotopic ratio(δ 15N) and the isotope fractionation factor(ε,‰) being the highest among the species investigated.The transformation and utilization of 15N by snails differed depending on the specific algae consumed(highest for Chlorella pyrenoidosa Chick.,lowest for M.aeruginisa).When snails was seeded in the experimental pond,the algae population structure changed significantly,and total algal biomass as well as the concentration of all nitrogen species decreased,causing an increase in water transparency.A model,incorporating several chemical and biological parameters,was developed to predict algal biomass in an aquatic system when snails was present.The data collected during this investigation indicated that the gastropods such as snails could significantly impact biological community and water quality of small water bodies,suggesting a role for biological control of noxious algal blooms associated with eutrophication.     

An improved ion-exchange/diffusion method for ～(15)N isotope tracing analysis of nitrate in surface waters from watersheds

An improved method,suitable for collecting nitrate from surface waters in the watershed for 15 N isotope tracing analysis,was developed on the basis of the anion exchange coupled with diffusion through systematic simulation and comparison experiments.The results showed that the nitrate could be separated and enriched from the waters efficiently by using the improved method.Being simple and practical in operation principle and procedures,cost-economic,and highly efficient in nitrate separation/enrichment,the method met the requirements of δ 15 N mass spectrum analysis and would lay a foundation for the application of 15 N isotope tracing approach to the research on non-point source pollution in watershed.     

伊乐藻和氮循环菌技术对太湖氮素吸收和反硝化的影响

从太湖梅梁湾采集无扰动泥芯样,分别添加固定化氮循环细菌、水生植物伊乐藻建立室内微宇宙,模拟生态修复,探讨不同修复处理下,硝氮的去除机制.采用15N标记结合同位素配对技术测定了各生态模拟柱中的反硝化速率和植物吸收速率.结果表明,不同处理的实验柱反硝化速率差异明显,同时添加了水生植物和固定化氮循环细菌的实验柱反硝化速率最高,为99.35μmol·(m2·h)-1,植物氮吸收速率为36.55μg·(m2·h)-1.沉水植物伊乐藻在自身吸收氮素的同时也提高了耦合硝化反硝化的作用.与植物吸收相比,反硝化过程是主要的氮去除途径.沉水植物与固定化氮循环菌组合生态修复技术促进了湖泊水体氮素的脱除,起到了净化作用.     

基于同位素示踪和分子生物学技术对潮白河沉积物中氮还原功能特征的研究

沉积物氮还原功能对于调控和管理河流氮负荷具有重要作用.本研究选取潮白河不同区域河段表层沉积物作为研究对象,采用¹⁵N同位素示踪技术、16S rRNA扩增子测序和实时荧光定量PCR（qPCR）技术,研究了潮白河沉积物中氮还原过程（反硝化、厌氧氨氧化（anaerobic ammonia oxidation,anammox）和DNRA过程（dissimilatory nitrate reduction to ammonium,异化硝酸盐还原为铵））速率特征、相关功能基因丰度和微生物群落结构特征.结果表明：潮白河沉积物潜在反硝化、anammox、DNRA和N₂O释放速率分别为（25.82±0.98）~（142.32±17.06）、（0.58±0.10）~（4.51±0.78）、（2.91±0.46）~（19.59±4.15）和（-1.09±0.17）~（3.30±0.57）nmol·g^-1·h^-1（以N计,下同）.沉积物氮还原以反硝化过程为主（贡献率71.86%~91.65%）,DNRA也有较高的贡献率（7.03%~25.32%）,anammox过程贡献较小.相关分析表明,氮还原相关功能基因丰度与潮白河沉积物氮还原过程速率存在显著正相关关系,微生物群落中α-变形菌纲、硝基螺旋菌纲、疣微菌纲、脱硫杆菌门、硬壁菌门丰度与沉积物氮还原过程速率存在显著的相关关系.     

SBA-15介孔分子筛负载金属酞菁催化氧化甲醛

采用浸渍法将钴或铁酞菁组装进有序介孔材料SBA-15中,通过XRD和N₂吸附方法对组装体进行了表征,研究了常温常压下,该组装体催化氧化甲醛的活性.结果表明,组装体具有优良的处理甲醛性能.钴酞菁比铁酞菁组装体的催化氧化活性高;钴和铁酞菁的协同作用使组装体具有更强的催化氧化活性,当二者摩尔比为1:1时,催化氧化活性最高;并借鉴金属酞菁处理有机巯醇的原理探讨了金属酞菁催化氧化甲醛的原理.     

Using machine learning to disentangle homonyms in large text corpora

Systematic reviews are an increasingly popular decision‐making tool that provides an unbiased summary of evidence to support conservation action. These reviews bridge the gap between researchers and managers by presenting a comprehensive overview of all studies relating to a particular topic and identify specifically where and under which conditions an effect is present. However, several technical challenges can severely hinder the feasibility and applicability of systematic reviews, for example, homonyms (terms that share spelling but differ in meaning). Homonyms add noise to search results and cannot be easily identified or removed. We developed a semiautomated approach that can aid in the classification of homonyms among narratives. We used a combination of automated content analysis and artificial neural networks to quickly and accurately sift through large corpora of academic texts and classify them to distinct topics. As an example, we explored the use of the word reintroduction in academic texts. Reintroduction is used within the conservation context to indicate the release of organisms to their former native habitat; however, a Web of Science search for this word returned thousands of publications in which the term has other meanings and contexts. Using our method, we automatically classified a sample of 3000 of these publications with over 99% accuracy, relative to a manual classification. Our approach can be used easily with other homonyms and can greatly facilitate systematic reviews or similar work in which homonyms hinder the harnessing of large text corpora. Beyond homonyms we see great promise in combining automated content analysis and machine‐learning methods to handle and screen big data for relevant information in conservation science.