上海市郊春节期间大气颗粒物及其组分的粒径分布

利用电称低压冲击仪(ELPI)在线监测上海市嘉定区2009年春节前后不同粒径(50%切割粒径分别为:0.03、0.06、0.11、0.17、0.26、0.40、0.65、1.00、1.60、2.50、4.40、6.80μm)大气颗粒物的粒子数浓度变化.对比春节与非节日期间该地区大气颗粒物(<0.49、0.49—0.95、0.95—1.50、1.50—3.00、3.00—7.20、>7.20μm)中Na、Mg、Al、K、Ca、Ti、V、Cr、Mn、Fe、Co、Ni、Cu、Zn、As、Se、Pb 17种元素,F-、Cl-、NO 2-、SO24-、NO 3-、Na+、NH 4+、K+、Mg2+、Ca2+10种离子与有机碳(OC)、元素碳(EC)质量浓度的粒径分布.结果表明,春节对于大气颗粒物粒子数浓度的影响主要集中在0.11—1.60μm.如果以3.00μm为界将大气颗粒物划分成细(≤3.00μm)和粗(>3.00μm)颗粒物时,春节影响体现在细颗粒的元素为:Na、As、Pb,且主要集中于<0.49μm颗粒中;春节影响集中于大颗粒(>7.20μm)的元素为:Ni、Co;没有受到显著影响的为:Ca、V、Mn、Fe、Z...     

Towards a 3D National Ecological Footprint Geography

In the last decades several indicators have been proposed to guide decision makers and help manage natural capital. Among such indicators is the Ecological Footprint, a resource accounting tool with a biophysical and thermodynamic basis. In our recent paper (Niccolucci et al., 2009), a three dimensional Ecological Footprint (^3DEF) model was proposed to better explain the difference between human demand for natural capital stocks and resource flows. Such ^3DEF model has two relevant dimensions: the surface area (or Footprint size - EF_size) and the height (or Footprint depth - EF_depth). EF_size accounts for the human appropriation of the annual income from natural capital while EF_depth accounts for the depletion of stocks of natural capital and/or the accumulation of stocks of wastes. Building on the 2009 Edition of the National Footprint Accounts (NFA), global trends (from 1961 to 2006) for both EF_size and EF_depth were analyzed. EF_size doubled from 1961 to 1986; after 1986 it reached an asymptotic value equal to the Earth's biocapacity (BC) and remained constant. Conversely, EF_depth remained constant at the “natural depth” value until 1986, the year in which global EF first exceeded Earth's BC. A growing trend was observed after that. Trends in each Footprint land type were also analyzed to better appraise the land type under the higher human induced stress. The usefulness of adopting such ^3DEF model in the National Footprint Accounts was also discussed. In comparing any nation's demand for ecological assets with its own biocapacity in a given year, four hypothetical cases were identified which could serve as the basis for a new Footprint geography based on both size and depth concepts. This ^3DEF model could help distinguish between the use of natural capital flows and the depletion of natural capital stocks while maintaining the structure and advantages of the classical Ecological Footprint formulation.     

Species-specific tuning increases robustness to sampling bias in models of species distributions: An implementation with Maxent

Various methods exist to model a species’ niche and geographic distribution using environmental data for the study region and occurrence localities documenting the species’ presence (typically from museums and herbaria). In presence-only modelling, geographic sampling bias and small sample sizes represent challenges for many species. Overfitting to the bias and/or noise characteristic of such datasets can seriously compromise model generality and transferability, which are critical to many current applications - including studies of invasive species, the effects of climatic change, and niche evolution. Even when transferability is not necessary, applications to many areas, including conservation biology, macroecology, and zoonotic diseases, require models that are not overfit. We evaluated these issues using a maximum entropy approach (Maxent) for the shrew Cryptotis meridensis, which is endemic to the Cordillera de Mérida in Venezuela. To simulate strong sampling bias, we divided localities into two datasets: those from a portion of the species’ range that has seen high sampling effort (for model calibration) and those from other areas of the species’ range, where less sampling has occurred (for model evaluation). Before modelling, we assessed the climatic values of localities in the two datasets to determine whether any environmental bias accompanies the geographic bias. Then, to identify optimal levels of model complexity (and minimize overfitting), we made models and tuned model settings, comparing performance with that achieved using default settings. We randomly selected localities for model calibration (sets of 5, 10, 15, and 20 localities) and varied the level of model complexity considered (linear versus both linear and quadratic features) and two aspects of the strength of protection against overfitting (regularization). Environmental bias indeed corresponded to the geographic bias between datasets, with differences in median and observed range (minima and/or maxima) for some variables. Model performance varied greatly according to the level of regularization. Intermediate regularization consistently led to the best models, with decreased performance at low and generally at high regularization. Optimal levels of regularization differed between sample-size-dependent and sample-size-independent approaches, but both reached similar levels of maximal performance. In several cases, the optimal regularization value was different from (usually higher than) the default one. Models calibrated with both linear and quadratic features outperformed those made with just linear features. Results were remarkably consistent across the examined sample sizes. Models made with few and biased localities achieved high predictive ability when appropriate regularization was employed and optimal model complexity was identified. Species-specific tuning of model settings can have great benefits over the use of default settings.     

Predictors of occupancy trend across spatial scale

Many explorations of extinction probability have had a global focus, yet it is unclear whether variables that explain the probability of extinction at large spatial extents are the same as those at small spatial extents. Thus, we used nearly annual presence-absence records for the most recent 40 years of a 110-year data set from Palenque, Mexico, an area with ongoing deforestation, to explore which of >200 species of birds have probabilities of extirpation that are likely to increase. We assessed associations between long-term trends in species presence (i.e., detection in a given year) and body size, geographic range size, diet, dependence on forest cover, taxonomy, and ecological specialization. Our response variable was the estimated slope of a weighted logistic regression for each species. We assessed the relative strength of each predictor by means of a model ranking scheme. Several variables associated with high extinction probability at global extents, such as large body size or small geographic range size, were not associated with occurrence of birds over time at our site. Body size was associated with species loss at Palenque, but occurrence trends of both very large and very small species, particularly the latter, have declined, or the species have been extirpated. We found no association between declining occurrence trend and geographic range size, yet decline correlated with whether a species depends on forest (mean occupancy trend =-0.0380, 0.0263, and 0.0186 for, respectively, species with high, intermediate, or low dependence on forest) and with complex combinations of diet and foraging strata (e.g., occurrence of canopy insectivores and terrestrial omnivores has increased, whereas occurrence of mid-level frugivores and terrestrial granivores has decreased). Our findings emphasize that analyses of local areas are necessary to explicate extirpation risk at various spatial extents.     

不同粒径土壤中重金属的分布规律

本文选择提钒炼钢厂内部分土壤为研究对象,测定了重金属元素（镉、铜、铬、铅、锌）的含量,并与样品粒度大小的关系进行了探讨,结果表明金属（铜、铬、铅、锌、镉）的浓度最大值出现在粒径较小（100目或160目）的样品中,同时将测定结果与土壤环境质量标准比较,结果表明镉、锌存在污染,其余元素均未超标。     

生物质粒径对负载MgO生物炭吸附水体中磷的影响

为研究生物质粒径对负载MgO芦苇生物炭（MBC）去除水体中磷的速率和能力的影响,以0~0.5、1~2和6~8 mm这3种不同粒径的芦苇颗粒为原料、MgCl₂为改性剂制备MBC,用傅里叶变换红外光谱仪（FTIR）、X射线衍射仪（XRD）和扫描电子显微镜（SEM）等对MBC表征,开展MBC吸附溶液中磷酸盐（PO₄^3--P）动力学和等温线实验以及实验数据模型拟合.结果表明,MBC对溶液中PO₄^3--P的吸附速率随生物质粒径增大而增大,0~0.5、1~2和6~8 mm芦苇颗粒制备的MBC对PO₄^3--P的吸附量在2 h内分别达到平衡吸附量的15.4%、25.8%和80.8%,而生物质粒径对MBC的PO₄^3--P最大吸附量（249.0~254.7 mg·g^-1）无明显影响.6~8 mm芦苇颗粒制备的MBC保留了较完整的芦苇细胞壁结构,且含有丰富的微孔和中孔,形成多层次、规则的、连通性好的孔隙结构.0~0.5 mm和1~2 mm芦苇颗粒制备的MBC孔隙结构较差,孔隙连通性受损,影响了磷酸根离子在MBC内部的扩散速率,限制了对磷的吸附速率.因此,以人工湿地收割的废弃植物芦苇为原料制备MBC用于去除水体中磷时,将芦苇破碎至6~8 mm即可,过度破碎会破坏MBC的孔隙结构,减小MBC对磷的去除速率.     

黄河口湿地表层沉积物中磷赋存形态的分析

于2009年4月在黄河口湿地采集表层沉积物,利用改进后的SEDEX方法对沉积物样品进行了磷形态的分析.结果表明,表层沉积物中总磷含量变化范围为12.12~25.37μmol·g-1,平均值为20.70μmol·g-1,其中自生磷灰石磷和碎屑磷灰石磷为表层沉积物中磷的主要赋存形式.中值粒径与各形态磷含量密切相关,弱吸附态磷、自生磷灰石磷、活性有机磷含量与中值粒径呈显著负相关关系;碎屑磷灰石磷含量与中值粒径呈显著正相关关系.有机质含量影响各形态磷在沉积物中含量,弱吸附态磷、活性有机磷、自生磷灰石磷含量均随TOC含量增加而升高.包括弱吸附态磷、活性有机磷和铁结合态磷在内的生物可利用磷含量变化为1.15~6.74μmol·g-1,平均值为4.27μmol·g-1,占总磷的摩尔分数为6.35%~30.4%.     

不同粒径零价铁活化过硫酸钠氧化降解酸性橙7的影响及动力学研究

以偶氮染料酸性橙7(AO7)为目标污染物,研究了不同粒径零价铁(包括1 mm-ZVI、150μm-ZVI、50 nm-ZVI)对活化过硫酸钠(PS)氧化降解AO7的影响,并探讨了这3种不同粒径的零价铁活化体系中AO7的降解动力学及中间产物.结果表明,3种粒径零价铁均可以高效活化PS氧化降解AO7,反应90 min后,1 mm-ZVI、150μm-ZVI和50 nm-ZVI活化体系对AO7的去除率分别为43%、97%和100%.AO7动力学方程拟合结果表明,1 mm-ZVI和150μm-ZVI活化PS降解AO7是一级反应,50 nm-ZVI活化体系中AO7的降解是二级反应,这3种粒径零价铁活化PS降解AO7的速率常数大小顺序为50 nm-ZVI>150μm-ZVI>1 mm-ZVI.反应过程中1 mm-ZVI反应后主要生成α-Fe2O3和少量Fe3O4,150μm-ZVI表面的腐蚀产物主要是Fe3O4,而50 nm-ZVI的主要氧化物为α-Fe2O3和α-FeOOH.GC/MS检测出AO7降解中间产物有2-萘酚、邻甲酚、3-甲基-4-乙基苯酚、邻苯二甲酰亚胺、邻苯二甲酸等,AO7溶液吸收光谱的变化特征及GC/MS检测结果表明3种粒径零价铁活化PS氧化降解AO7的途径可能存在差异.     

准噶尔盆地南缘黄土磁化率变化规律及影响因素

准噶尔盆地南缘柏杨河典型风成黄土剖面的岩石磁学与粒度研究结果指示该地区黄土磁 性矿物以亚铁磁性矿物为主,主要载磁矿物为粗粒原生强磁性矿物,同时含有少量细粒磁性矿物, 磁性矿物含量远低于黄土高原黄土。磁性矿物磁晶粒度以假单畴和多畴（PSD/MD）为主,后期 成壤过程对磁性矿物颗粒的改造作用很小。柏杨河黄土磁化率增强机制较为复杂,磁学与粒度 的曲线对比表明风动力强度对含磁性矿物较粗颗粒具有分选作用,是导致磁化率变化的重要因 素,但二者的低相关性又暗示了风动力强度在解释磁化率增强机制中的局限性。古尔班通古特 沙漠在末次间冰期以来的收缩与扩张导致的物源变化可能是影响磁化率变化的又一重要因素。     

新疆塔城黄土的形成

中亚黄土是研究区域古气候和古环境变化的重要载体。但是对于受到广泛研究的黄土 高原黄土来说,对中亚东部塔城黄土的报道较少。基于对塔城黄土粒度的系统分析,与伊犁盆 地黄土、典型黄土高原的黄土对比,我们发现无论是粒度频率曲线、粒度结构散点图、还是三 角图,塔城黄土与伊犁盆地清水河黄土较相似,而与黄土高原黄土不同,塔城黄土粒度频率分 布曲线为三峰分布,粒度组成比较分散,分选较差,细、中颗粒含量较少,主要以粗颗粒物质 为主,属近源风成黄土。结合当地地形和现代环流分析,我们认为中亚萨雷耶西克阿特劳沙漠 为塔城黄土提供主要的物源,盛行西风为粉尘的搬运提供足够的动力,向西开口的山间盆地地 形为粉尘的沉积提供有利的沉积中心,这三个条件的共同作用导致了塔城盆地厚层黄土的沉积。