Benzene Exposure Assessment at Indoor, Outdoor and Personal Levels. The French Contribution to the Life MACBETH Programme

Many VOC represent hazards to human health through chronic exposure. Recent European and world-wide legislation proposes limit values for ambient concentrations of these compounds. However, very little experimental data exists for true population exposure. In 1996, the European MACBETH initiative set out to measure population exposure to benzene in six European cities. This study details the French contribution to this program. Six campaigns were carried out, each comprising measurements at 100 outdoor sites and the participation of 50 non-smoking volunteers who wore personal samplers and had passive monitors installed in their homes. Iso-concentration maps were drawn for each campaign and the results showed that outdoor concentrations were significantly lower than indoors. Almost 75% of the volunteers were exposed to mean concentrations higher than the limit value of 5µgm³. It is demonstrated that personal exposure levels cannot be deduced simply by combining indoor and outdoor background concentrations. It is also shown that there is need for better knowledge of the contributions to overall exposure of outdoor microenvironments and the authors hope that future European directives will take this into account.     

石墨炉法测定铅的基体改进剂的选择

通过一系列实验,选择了石墨炉法测定铅的最佳基体改进剂,并确定了使用该基体改进剂的最佳灰化温度和原子化温度。     

A New Approach to Plant Diversity Assessment Combining HPLC Data, Simplex Mixture Design and Discriminant Analysis

The quantitative assessment of plant diversity and its monitoring with time represent a key environmental issue for management and conservation of natural resources. Assessment of plant diversity could be based on chemical analyses of secondary metabolites (e.g. flavonoids, terpenoids), because of the substantial quantitative and qualitative between-individual variability in such compounds. At a geographical scale, the plant populations become widely dispersed, and their monitoring from numerous routine individual analyses could become restricting. To overcome such constraint, this study develops a multivariate calibration model giving the relative frequency of a particular taxon from a simple high-performance liquid chromatography (HPLC) analysis of a plant mixture. The model was built from a complete set of mixtures combining different taxons, according to an experimental design (Scheffé’s matrix). For each mixture, a reference HPLC pattern was simulated by averaging the individual HPLC profiles of the constitutive taxons. The calibration models, based on Bayesian discriminant analysis (BDA), gave statistical relationships between the contributions of each taxon in mixtures and reference HPLC patterns of these mixtures. Finally, these models were validated on new mixtures by using outside plants. This new biodiversity survey approach is illustrated on four chemical taxons (four chemotypes) of Astragalus caprinus (Fabaceae). The more differentiated the taxon, the better predicted its contributions (in mixtures) were by BDA calibration model. This new approach could be very useful for a global routine survey of plant diversity.     

高速公路交通噪声预测模型探讨

针对我国当前广泛使用的2种高速公路噪声预测模型《06规范》预测模型与《09导则》预测模型在预测时比较研究,重点利用环境现状监测数据分别对2种模型验证与对比分析.结果表明,2种模型预测值与实测值相差3dB ～5dB,车流量＞ 300辆/h,《09导则》更接近实测值;在夜间车流量＜300辆/h,《06规范》更接近实测值,2种模型结合采用《06规范》计算的车速,距离衰减考虑车流量的大小,在此基础上应用《09导则》,预测结果与实测值更为接近.     

中国人口集疏格局与形成机制研究

人口集聚和疏散是人口空间分布格局最直观和最集中的体现,基于人口集聚度的中国人口集疏的空间格局和形成机制的研究,有助于准确把握中国人口空间分布的基本脉络,具有重要的学术价值和实践意义。研究采用了人口集聚度分级评价的方法,依据人口集聚度的不同,将各个地区划分为不同等级的人口集聚区,并对其分别讨论。在此基础上,结合中国人口分布格局、自然条件的空间分布格局、人居环境自然适宜性评价结果以及经济发展格局和城市化格局,对中国的人口集疏的空间格局进行了归纳,并进一步对相应的形成机制进行了探讨,得出了我国人口分布的空间不平衡日益加剧,并呈现沿海、沿江、沿线集聚的态势的基本结论,并对我国人口分布集疏格局的形成进行了探讨,提出了自然因素奠定我国人口分布的基本格局,而经济发展不平衡与城市化成为人口集聚的动力的观点。     

Using the land transformation model to forecast vacant land

Growing or shrinking cities can experience increases in vacant land. As urban populations and boundaries fluctuate, holes can open in once tight urban areas. Many cities chase growth-oriented approaches to dealing with vacancies. It is critical to understand land-use alteration to accurately predict transformations of physical change in order to make better informed decisions about this phenomenon. This research utilizes the land transformation model (LTM), an artificial neural networking mechanism in Geographic Information Systems, to forecast vacant land. Variable influence on vacant land prediction and accuracy of the LTM is assessed by comparing input factors and patterns, using time-series data from 1990 to 2010 in Fort Worth, Texas, USA. Results indicate that the LTM can be useful in simulating vacant land-use changes but more precise mechanisms are necessary to increase accuracy. This will allow for more proactive decisions to better regulate the process of urban decline and regeneration.     

Predicting occurrence of juvenile shark habitat to improve conservation planning

Fishing and habitat degradation have increased the extinction risk of sharks, and conservation strategies recognize that survival of juveniles is critical for the effective management of shark populations. Despite the rapid expansion of marine protected areas (MPAs) globally, the paucity of shark‐monitoring data on large scales (100s–1000s km) means that the effectiveness of MPAs in halting shark declines remains unclear. Using data collected by baited remote underwater video systems (BRUVS) in northwestern Australia, we developed generalized linear models to elucidate the ecological drivers of habitat suitability for juvenile sharks. We assessed occurrence patterns at the order and species levels. We included all juvenile sharks sampled and the 3 most abundant species sampled separately (grey reef [Carcharhinus amblyrhynchos], sandbar [Carcharhinus plumbeus], and whitetip reef sharks [Triaenodon obesus]). We predicted the occurrence of juvenile sharks across 490,515 km² of coastal waters and quantified the representation of highly suitable habitats within MPAs. Our species‐level models had higher accuracy (? ≥ 0.69) and deviance explained (≥48%) than our order‐level model (? = 0.36 and deviance explained of 10%). Maps of predicted occurrence revealed different species‐specific patterns of highly suitable habitat. These differences likely reflect different physiological or resource requirements between individual species and validate concerns over the utility of conservation targets based on aggregate species groups as opposed to a species‐focused approach. Highly suitable habitats were poorly represented in MPAs with the most restrictions on extractive activities. This spatial mismatch possibly indicates a lack of explicit conservation targets and information on species distribution during the planning process. Non‐extractive BRUVS provided a useful platform for building the suitability models across large scales to assist conservation planning across multiple maritime jurisdictions, and our approach provides a simple for method for testing the effectiveness of MPAs.     

Vertical migration of radionuclides in undisturbed grassland soils

Literature data on numerical values obtained for the parameters of the two most popular models for simulating the migration of radionuclides in undisturbed soils have been compiled and evaluated statistically. Due to restrictions on the applicability of compartmental models, the convection–dispersion equation and its parameter values should be preferred. For radiocaesium, recommended values are derived for its effective convection velocity and dispersion coefficient. Data deficiencies still exist for radionuclides other than caesium and for soils of non-temperate environments.     

Modelling plant species richness using functional groups

Conservation biologists increasingly rely on spatial predictive models of biodiversity to support decision-making. Therefore, highly accurate and ecologically meaningful models are required at relatively broad spatial scales. While statistical techniques have been optimized to improve model accuracy, less focus has been given to the question: How does the autecology of a single species affect model quality? We compare a direct modelling approach versus a cumulative modelling approach for predicting plant species richness, where the latter gives more weight to the ecology of functional species groups. In the direct modelling approach, species richness is predicted by a single model calibrated for all species. In the cumulative modelling approach, the species were partitioned into functional groups, with each group calibrated separately and species richness of each group was cumulated to predict total species richness. We hypothesized that model accuracy depends on the ecology of individual species and that the cumulative modelling approach would predict species richness more accurately. The predictors explained plant species richness by ca. 25%. However, depending on the functional group the deviance explained varied from 3 to 67%. While both modelling approaches performed equally well, the models of the different functional groups highly varied in their quality and their spatial richness pattern. This variability helps to improve our understanding on how plant functional groups respond to ecological gradients.