Abstract. A deflation module of soil and sand dust loading, especially for Asian dust (called yellow sand or Kosa), has been designed to provide explicit information on emission intensity for use in modeling long-range transport of yellow sand over East Asia. In contrast to previous modules for Sahara and Australian deserts, it includes three major predictors, the friction velocity, the surface humidity, and the dominant weather system. Comparison of the deflation module results, using these three parameters together or separately, with observed data on dust deflation in April and July 1988, shows that the best estimate can be obtained by considering the three predictors together when we take the minimum of the total error ratio as the selection criteria. It indicates that last two predictors provide a limitation for deflation and can decrease the number of false declarations from 23 to 7%, especially in the wet season. A regional long-range transport model for Kosa is introduced, which considers various parameters such as particle size, transport, diffusion, and removal in detail. The model results show a reasonable agreement with the observations during Kosa episodes in April 1988. A size-resolved analysis explains the peculiar multi layered vertical distribution of dust at large distances from the source areas; that is, for fine particles one peak appears close to the ground, while the other is in the middle troposphere.

BackgroundPredicting species’ potential geographical range by species distribution models (SDMs) is central to understand their ecological requirements. However, the effects of using different modeling techniques need further investigation. In order to improve the prediction effect, we need to assess the predictive performance and stability of different SDMs.MethodologyWe collected the distribution data of five common tree species (Pinus massoniana, Betula platyphylla, Quercus wutaishanica, Quercus mongolica and Quercus variabilis) and simulated their potential distribution area using 13 environmental variables and six widely used SDMs: BIOCLIM, DOMAIN, MAHAL, RF, MAXENT, and SVM. Each model run was repeated 100 times (trials). We compared the predictive performance by testing the consistency between observations and simulated distributions and assessed the stability by the standard deviation, coefficient of variation, and the 99% confidence interval of Kappa and AUC values.ResultsThe mean values of AUC and Kappa from MAHAL, RF, MAXENT, and SVM trials were similar and significantly higher than those from BIOCLIM and DOMAIN trials (p<0.05), while the associated standard deviations and coefficients of variation were larger for BIOCLIM and DOMAIN trials (p<0.05), and the 99% confidence intervals for AUC and Kappa values were narrower for MAHAL, RF, MAXENT, and SVM. Compared to BIOCLIM and DOMAIN, other SDMs (MAHAL, RF, MAXENT, and SVM) had higher prediction accuracy, smaller confidence intervals, and were more stable and less affected by the random variable (randomly selected pseudo-absence points).ConclusionsAccording to the prediction performance and stability of SDMs, we can divide these six SDMs into two categories: a high performance and stability group including MAHAL, RF, MAXENT, and SVM, and a low performance and stability group consisting of BIOCLIM, and DOMAIN. We highlight that choosing appropriate SDMs to address a specific problem is an important part of the modeling process.

Surveys were conducted in factories in China where workers were engaged in the production of rubber boots or plastic-coated wire or in printing work, and were exposed to xylene vapors. Based on the data on exposure as monitored by personal diffusive sampling, 175 xylene-exposed workers (107 men and 68 women) were selected as those (1) who underwent all examinations and (2) for whom the sum of the three xylene isomers accounted for 70% or more of the total exposure (on a ppm basis). The intensity of exposure was such that the sum of the three isomer concentrations was 14 ppm as a geometric mean and 21 ppm as an arithmetic mean. As controls, 241 nonexposed workers (116 men and 125 women) were recruited either from the same factories or from factories in the same regions. There was an increased prevalence of subjective symptoms in the exposed workers which were apparently related to the effects on the central nervous system and to the local effects on the eyes, the nose, and the throat, although dose-dependency of the symptoms was evident in only a limited number of cases, possibly because the intensity of exposure was rather low. It was further observed that the findings of hematology and serum biochemistry in respect of liver and kidney functions were generally negative, showing that xylenes are not toxic to the hematopoietic organs, the liver, or the kidney.

Many studies predict that climate change will cause species movement and turnover, but few have considered the effect of climate change on range fragmentation for current species and/or populations. We used MaxEnt to predict suitable habitat, fragmentation and turnover for 134 amphibian species in China under 40 future climate change scenarios spanning four pathways (RCP2.6, RCP4.5, RCP6 and RCP8.5) and two time periods (the 2050s and 2070s). Our results show that climate change may cause a major shift in spatial patterns of amphibian diversity. Amphibians in China would lose 20% of their original ranges on average; the distribution outside current ranges would increase by 15%. Suitable habitats for over 90% of species will be located in the north of their current range, for over 95% of species in higher altitudes (from currently 137–4,124 m to 286–4,396 m in the 2050s or 314–4,448 m in the 2070s), and for over 75% of species in the west of their current range. Also, our results predict two different general responses to the climate change: some species contract their ranges while moving westwards, southwards and to higher altitudes, while others expand their ranges. Finally, our analyses indicate that range dynamics and fragmentation are related, which means that the effects of climate change on Chinese amphibians might be two-folded.

This study uses molecular dynamics simulations to investigate the intrinsic thermal vibrations of a single-walled carbon nanotube (SWNT) modelled as a clamped cantilever. Using an elastic model defined in terms of the tube length, the tube radius and the tube temperature, the standard deviation of the vibrational amplitude of the tube's free end is calculated and the Young's modulus of the SWNT evaluated. The numerical results reveal that the value of the Young's modulus is independent of the tube length, but decreases with increasing tube radius. At large tube radii, the Young's modulus value approaches the in-plane modulus of graphene, which can be regarded as an SWNT of infinitely large radius. The results also indicate that the Young's modulus is insensitive to changes in the tube temperature at temperatures of less than approximately 1100 K, but decreases significantly at higher temperatures.

No abstract

The following is a report on software developed to create virtual species for the study of species distribution modelling (SDM). SDMvspecies provides several methods to create virtual species. The package is designed to be simple and intuitive, even for users who are not familiar with the R language. SDMvspecies is available online free of charge from .

: Subjective symptoms, hematology, serum biochemistry and other clinical signs were investigated in 56 dry-cleaning workers exposed to tetrachloroethylene at 20 ppm (as a geometric mean of 8-hr time-weighted average), and the results were compared with the findings in 69 non-exposed controls from the same factories. There were exposure-related increases in the prevalence of subjective symptoms during the work as well as in the past 3 month period, whereas there was no significant changes in hematology.Effects of the exposure on liver and kidney functions were also negative as judged by emission enzyme activities, BUN and creatinine in the serum.