Comparison of the SidePak personal monitor with the Aerosol Particle Sizer (APS)

The aim of this study was to compare the performance of the TSI Aerodynamic Particle Sizer (APS) and the TSI portable photometer SidePak to measure airborne oil mist particulate matter (PM) with aerodynamic diameters below 10 μm, 2.5 μm and 1 μm (PM(10), PM(2.5) and PM(1)). Three SidePaks each fitted with either a PM(10), PM(2.5) or a PM(1) impactor and an APS were run side by side in a controlled chamber. Oil mist from two different mineral oils and two different drilling fluid systems commonly used in offshore drilling technologies were generated using a nebulizer. Compared to the APS, the SidePaks overestimated the concentration of PM(10) and PM(2.5) by one order of magnitude and PM(1) concentrations by two orders of magnitude after exposure to oil mist for 3.3-6.5 min at concentrations ranging from 0.003 to 18.1 mg m(-3) for PM(10), 0.002 to 3.96 mg m(-3) for PM(2.5) and 0.001 to 0.418 mg m(-3) for PM(1) (as measured by the APS). In a second experiment a SidePak monitor previously exposed to oil mist overestimated PM(10) concentrations by 27% compared to measurements from another SidePak never exposed to oil mist. This could be a result of condensation of oil mist droplets in the optical system of the SidePak. The SidePak is a very useful instrument for personal monitoring in occupational hygiene due to its light weight and quiet pump. However, it may not be suitable for the measurement of particle concentrations from oil mist.     

An update of the Worldwide Integrated Assessment (WIA) on systemic insecticides. Part 3: alternatives to systemic insecticides

Environmental Science and Pollution Research - Over-reliance on pesticides for pest control is inflicting serious damage to the environmental services that underpin agricultural productivity. The...     

An update of the Worldwide Integrated Assessment (WIA) on systemic insecticides

Environmental Science and Pollution Research -     

Comparison and ranking of different modelling techniques for prediction of site index in Mediterranean mountain forests

Forestry science has a long tradition of studying the relationship between stand productivity and abiotic and biotic site characteristics, such as climate, topography, soil and vegetation. Many of the early site quality modelling studies related site index to environmental variables using basic statistical methods such as linear regression. Because most ecological variables show a typical non-linear course and a non-constant variance distribution, a large fraction of the variation remained unexplained by these linear models. More recently, the development of more advanced non-parametric and machine learning methods provided opportunities to overcome these limitations. Nevertheless, these methods also have drawbacks. Due to their increasing complexity they are not only more difficult to implement and interpret, but also more vulnerable to overfitting. Especially in a context of regionalisation, this may prove to be problematic. Although many non-parametric and machine learning methods are increasingly used in applications related to forest site quality assessment, their predictive performance has only been assessed for a limited number of methods and ecosystems.In this study, five different modelling techniques are compared and evaluated, i.e. multiple linear regression (MLR), classification and regression trees (CART), boosted regression trees (BRT), generalized additive models (GAM), and artificial neural networks (ANN). Each method is used to model site index of homogeneous stands of three important tree species of the Taurus Mountains (Turkey): Pinus brutia, Pinus nigra and Cedrus libani. Site index is related to soil, vegetation and topographical variables, which are available for 167 sample plots covering all important environmental gradients in the research area. The five techniques are compared in a multi-criteria decision analysis in which different model performance measures, ecological interpretability and user-friendliness are considered as criteria.When combining these criteria, in most cases GAM is found to outperform all other techniques for modelling site index for the three species. BRT is a good alternative in case the ecological interpretability of the technique is of higher importance. When user-friendliness is more important MLR and CART are the preferred alternatives. Despite its good predictive performance, ANN is penalized for its complex, non-transparent models and big training effort.     

Stages in Dutch regional policy: 1945–1984

This paper discusses the major developments in regional policy in the Netherlands by relating the policy instruments and locations to stages in the socio‐economic and political development of the Netherlands from 1945 onwards. It concludes that, at present, the spatial dimension of economic policy has lost importance, and the support for peripheral regions is restricted.     

Including adaptation costs and climate change damages in evaluating post-2012 burden-sharing regimes

Many studies have been published to evaluate the consequences of different post-2012 emission allocation regimes on regional mitigation costs. This paper goes one step further and evaluates not only mitigation costs, but also adaptation costs and climate change damages. Three post-2012 emission allocation regimes (Contraction & Convergence, Multistage and Common but differentiated convergence) and two climate targets (2°C and 3°C above the pre-industrial level) are considered. This explorative analysis shows that including these other cost categories could lead to different perspectives on the outcomes of allocation regimes. Up to 2050, the poorest regions have negative mitigation costs under all allocation regimes considered, as they benefit from emission trading. However, these regions also suffer from the most severe climate impacts. As such, the financial flows due to emission trading from developed to developing countries created under these allocation regimes could also be interpreted as compensation of climate change damages and adaptation costs. In the longer run, the sum of climate change damages, adaptation costs and mitigation costs are the highest in the poorest regions of Sub-Saharan Africa and South Asia, for both climate targets and practically all emission allocation regimes.     

Trade-offs and synergies in joint knowledge creation for coastal management: insights from ecology-oriented sand nourishment in the Netherlands

In order to successfully inform environmental management, environmental research needs to balance legitimacy, credibility, and salience. This paper aims to identify trade-offs and synergies between these three attributes in collaborative research for environmental management, and draws lessons for organizing such research. Empirically, it draws on a study of a research program on the ecological effects of coastal protection through sand nourishment. Our findings suggest that the legitimacy and salience of knowledge creation, particularly in an interactive governance context, are complementary. At the same time, we found trade-offs between practical relevance and fundamental knowledge creation, as well as between issue diversity and the depth and quality of scientific inquiry. Balancing the legitimacy, credibility, and salience of knowledge may be enabled by interactive knowledge creation involving policy-makers, experts and stakeholders. We conclude that successful management-oriented environmental research, particularly in the case of wicked problems, requires both a careful design of arrangements for stakeholder engagement, and well- established linkages to broader regulatory and institutional contexts.     

Demarcating coastal vegetation buffers with multicriteria evaluation and GIS at Saldanha Bay, South Africa

The Saldanha-Langebaan coastal zone forms an integral part of the South African coastal resource base. As elsewhere in the world, an acute need exists to balance development and economic growth and conservation in the coastal zone as an exploitable resource frontier area. Vegetated buffers and greenways are conservation concepts that have been used with great success in such conservation efforts. They are applied in the study area through the use of a Geographic Information System (GIS) as spatial decision-support system to legitimize the demarcation of a vegetated buffer zone. The method of multicriteria evaluation, as applied here, incorporates public decision-making in constructing an objective model for buffer zone demarcation. Representatives from interested and affected parties participated in model construction and calibration, resulting in the spatial delimitation of a multifunctional vegetated buffer. It conforms to a range of functional criteria and can serve as an environmental element in coastal conservation planning frameworks.     

Statistical uncertainty in hazardous terrestrial concentrations estimated with aquatic ecotoxicity data

Since chemicals’ ecotoxic effects depend for most soil species on the dissolved concentration in pore water, the equilibrium partitioning (EP) method is generally used to estimate hazardous concentrations (HC50) in the soil from aquatic toxicity tests. The present study analyzes the statistical uncertainty in terrestrial HC50s derived by the EP-method. For 47 organic chemicals, we compared freshwater HC50s derived from standard aquatic ecotoxicity tests with porewater HC50s derived from terrestrial ecotoxicity tests. Statistical uncertainty in the HC50s due to limited species sample size and in organic carbon–water partitioning coefficients due to predictive error was treated with probability distributions propagated by Monte Carlo simulations. Particularly for specifically acting chemicals, it is very important to base the HC50 on a representative sample of species, composed of both target and non-target species. For most chemical groups, porewater HC50 values were approximately a factor of 3 higher than freshwater HC50 values. The ratio of the porewater HC50/freshwater HC50 was typically 3.0 for narcotic chemicals (2.8 for nonpolar and 3.4 for polar narcotics), 0.8 for reactive chemicals, 2.9 for neurotoxic chemicals (4.3 for AChE agents and 0.1 for the cyclodiene type), and 2.5 for herbicides–fungicides. However, the statistical uncertainty associated with this ratio was large (typically 2.3 orders of magnitude). For 81% of the organic chemicals studied, there was no statistical difference between the hazardous concentration of aquatic and terrestrial species. We conclude that possible systematic deviations between the HC50s of aquatic and terrestrial species appear to be less prominent than the overall statistical uncertainty.     

Exposure to rubber process dust and fume since 1970s in the United Kingdom; influence of origin of measurement data

The objective of this study was to compare measured concentrations of rubber process dust and rubber fume originating from different sources in the British rubber manufacturing industry. Almost 8000 exposure measurements were obtained from industry-based survey results collected by the British Rubber Manufacturers' Association (BRMA), and covering the years 1977 to 2002, and from a series of small surveys contained in the Health and Safety Executive's (HSE) National Exposure Database (HSE-NEDB) from 1980 to 2002. The analysis investigated temporal trends in the exposure concentrations and the underlying main factors responsible for these changes. Analyses were carried out using hierarchical linear mixed effects models. Average personal exposures to rubber process dust and rubber fumes were respectively a factor 2 and 4 higher for the HSE-NEDB data when compared to data originating from the industry (BRMA data). Personal exposure to rubber process dust decreased on average by 4.1% (95% CI 4.7-3.6) annually for the BRMA data and slightly less at 2.3% (95% CI 5.2-0.7%) per annum for the HSE-NEDB data. Personal exposure to rubber fume also showed a downward temporal trend of 2.9% (95% CI 3.6-2.3%) and 4.8% (95% CI 7.4-2.1%) annually for the BRMA and HSE-NEDB data, respectively. These trends differed considerably between departments. No major changes in the estimated temporal trends in exposure concentrations were observed after including the presence of local exhaust ventilation in the models for any department in the BRMA and HSE-NEDB datasets. Lack of information on the quality and status of the local exhaust ventilation is the most likely explanation for this. In conclusion, even though there were relatively similar downward time trends in both rubber process dust and fume concentrations in both datasets, the source of exposure data was an important determinant of average exposure concentrations present in the British rubber manufacturing industry. Lack of detailed auxiliary information on company size, reason for sampling, measurement strategy and other potentially important determinants of exposure prevented an explanation for the observed differences in exposure level.