唐山市大气颗粒物OC/EC浓度谱分布观测研究

华北重工业城市唐山大气颗粒物污染严重,2009～2011年PM1.1、PM2.1、PM9.0及TSP年均值分别为(75±43)、(106±63)、(221±100)和(272±113)μg.m-3;碳质气溶胶在各粒径段均占较大比重,其中,元素碳(EC)在PM1.1、PM2.1、PM9.0及TSP各粒径段的年均比重分别约为9%、9%、6%和4%,有机碳(OC)年均比重分别为25%、24%、16%和14%.颗粒物浓度谱分布及碳质气溶胶富集量呈显著季节变化,秋冬季节细颗粒物中EC和OC浓度可高达(9±4)、(11±5)和(19±7)、(28±10)μg.m-3,分别占PM2.1的11%、10%和26%、25%;春夏季节EC和OC在粗细粒子中的富集量基本相当,分别为(5±2)、(5±1)和(15±3)、(15±1)μg.m-3,分别约占颗粒物总量的7%、6%和26%、18%.     

三醋酸甘油酯在活性炭上的吸附特性

三醋酸甘油酯在卷烟中主要作为醋酸纤维过滤嘴的增塑剂使用。在不同的温度和相对湿度条件下,研究活性炭对三醋酸甘油酯的吸附机理,探讨了活性炭的孔结构对其吸附性能的影响。结果表明:活性炭吸附三醋酸甘油酯符合Langmuir模型,其饱和吸附量为333 mg/g;高温有利于吸附三醋酸甘油酯,而增加湿度则抑制了三醋酸甘油酯的吸附;在一定范围内,当活性炭孔面积大于三醋酸甘油酯最小截面积的2.8倍时,活性炭对三醋酸甘油酯的吸附量增多,反之减少。因此,较大的微孔孔径有利于活性炭吸附三醋酸甘油酯。     

不同城市功能区地表灰尘Pb水平及粒级行为——以贵阳市为例

本文以我国西南贵州省会城市贵阳为例,对地表按城市功能分区采集灰尘样品,从不同功能区灰尘Pb总量和不同粒级灰尘Pb含量及贡献两个角度探析城市功能对地表灰尘Pb的影响。研究表明,贵阳市地表灰尘Pb平均含量为93.2mg/kg。商贸区和交通区地表灰尘Pb离散度较小,工业区和垃圾站地表灰尘Pb分异较大,住宅区、广场和学校灰尘Pb数据离散度处于中间水平。不同功能区地表灰尘Pb水平存在较大差异,工业区地表灰尘Pb含量显著高于商贸区和垃圾站;广场和学校地表灰尘Pb含量显著高于商贸区和交通区;住宅区Pb含量显著高于交通区。城市功能区从功能和地理位置两个方面影响城区地表灰尘Pb水平。各功能区地表灰尘不同粒级颗粒物中Pb含量存在较大差异,但所有区域地表灰尘中<250μm粒级颗粒物对地表灰尘Pb的贡献基本达到80%。     

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...     

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。     

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.     

The influence of particle size and concentration combined with pH on coagulation mechanisms

In order to evaluate the influence of particle size and particle concentration on the coagulation process, two kinds of particle suspensions, nanoparticles and microparticles,were employed to investigate the effect of particle size on coagulation mechanisms with varying coagulation parameters. Results showed that it is easier for nanoparticles to cause self-aggregation because of Brownian motion, while interception and sedimentation are the mainly physical processes affecting particle transport for microparticles, so they are more stable and disperse more easily. The particle size distribution and particle concentration had distinct influence on the coagulation mechanisms. Under neutral conditions, as the amount of coagulant increased, the coagulation mechanism for nanoparticles changed from charge neutralization to sweep flocculation and the nanoparticles became destabilized, re-stabilized and again destabilized. For microparticles, although the coagulation mechanism was the same as that of nanoparticles, the increased rate of aluminum hydroxide precipitation exceeded the adsorption of incipiently formed soluble alum species, resulting in the disappearance of the re-stabilization zone. Under acidic conditions, Brownian motion dominates for nanoparticles at low particle concentrations, while sweep flocculation is predominant at high particle concentrations. As for microparticles, charge neutralization and sweep flocculation are the mechanisms for low and high particle concentrations respectively.Under alkaline condition, although the mechanisms for both nano-and microparticles are the same, the morphology of flocs and the kinetics of floc formation are different. At low particle concentrations, nanoparticles have larger growth rate and final size of flocs, while at high particle concentrations, nanoparticles have higher fractal dimension and recovery factors.     

Effect of Cu-ZSM-5 catalysts with different CuO particle size on selective catalytic oxidation of N,N-Dimethylformamide

● A series of Cu-ZSM-5 catalysts were tested for DMF selective catalytic oxidation. ● Cu-6 nm samples showed the best catalytic activity and N₂ selectivity. ● Redox properties and chemisorbed oxygen impact on DMF catalytic oxidation. ● Isolated Cu²⁺ species and weak acidity have effects on the generation of N₂. N, N-Dimethylformamide (DMF), a nitrogen-containing volatile organic compound (NVOC) with high emissions from the spray industry, has attracted increasing attention. In this study, Cu-ZSM-5 catalysts with different CuO particle sizes of 3, 6, 9 and 12 nm were synthesized and tested for DMF selective catalytic oxidation. The crystal structure and physicochemical properties of the catalyst were studied by various characterization methods. The catalytic activity increases with increasing CuO particle size, and complete conversion can be achieved at 300–350 °C. The Cu-12 nm catalyst has the highest catalytic activity and can achieve complete conversion at 300 °C. The Cu-6 nm sample has the highest N₂ selectivity at lower temperatures, reaching 95% at 300 °C. The activity of the catalysts is determined by the surface CuO cluster species, the bulk CuO species and the chemisorbed surface oxygen species. The high N₂ selectivity of the catalyst is attributed to the ratio of isolated Cu²⁺ and bulk CuO species, and weak acidity is beneficial to the formation of N₂. The results in this work will provide a new design of NVOC catalytic oxidation catalysts.