Regulation (EC) No. 1107/2009 and upcoming challenges for exposure assessment of plant protection products--Harmonisation or national modelling approaches?

In the new European Pesticide Regulation (EC) No. 1107/2009, the harmonisation of approaches for estimation of the environmental exposure of pesticides is considered a major goal. Several member states currently require their own models for the calculation of predicted environmental concentrations (PEC) in surface water. The variety of methods makes risk evaluations rather time-consuming for both notifiers and evaluating authorities. In the present study we compare surface water concentrations of 19 compounds using EU and country-specific models and risk assessment approaches to evaluate to which extent the resulting estimated exposure concentrations differ. Our results show that EU and country specific approaches and the resulting surface water concentrations differ considerably regarding basic model assumptions and assessment methods. The results indicate that the aimed harmonisation of risk assessment approaches within the EU will be difficult based on current models. New scenarios may help to achieve a harmonisation taking country-specific features into account.     

Environmental conditions influence egg color of reed warblers <Emphasis Type="Italic">Acrocephalus scirpaceus</Emphasis> and their parasite,the common cuckoo <Emphasis Type="Italic">Cuculus canorus</Emphasis>

The outer layer of the eggshell in birds is in many cases covered by pigments that are assumed to be genetically determined traits with a negligible environmental component. To test the hypothesis that spring environmental conditions (i.e., temperature and rainfall) may affect bird egg pigmentation, we measured by spectrophotometry and photography egg coloration and spottiness on reed warbler (Acrocephalus scirpaceus L.) clutches parasitized by the common cuckoo (Cuculus canorus L.) collected over a period of 24 years and preserved in the Zoological Museum, Copenhagen, Denmark. In addition, we investigated whether spring environmental conditions may influence the coevolutionary relationship between the cuckoo and its host via changes in cuckoo–host egg matching. Generalized mixed models revealed that reed warbler eggs were more brilliant in those springs with a higher rainfall and tended to be bluer and greener in springs with a lower relative temperature. On the other hand, cuckoo eggs were bluer and greener in springs with a higher rainfall. Cuckoo–host egg matching in blue-greenness and spottiness was better in springs with a higher rainfall. These results provide support for the existence of an environmental component on bird egg coloration and suggest that environmental factors may potentially affect the outcome of important features of the arms race between cuckoos and reed warblers.     

Determination of metal accumulation in deposited street dusts in Amman, Jordan

Street dust samples (120 in total) were collected under stable weather conditions during the hot, dry season (August and September) of 2004 from six different localities (industrial, heavy traffic, medium traffic, light traffic, low traffic and rural) in greater Amman, the capital of Jordan. The concentrations of Fe, Cu, Cd, Pb, Zn and Ni in the dusts were determined by atomic absorption spectrophotometry. The high concentrations of Pb, Fe and Zn in the street dust samples were related to both anthropogenic (industrial sources combined with traffic sources) and natural sources. Surprisingly, the concentrations of Cd in the dusts were low. Correlation coefficient analysis and principle component analysis identified three main sources of these elements and the corresponding distributions. The elements Pb, Zn, Cd, Fe, Cu and Ni were mainly derived from industrial sources, with Pb and Zn additionally derived from traffic sources. The street dusts were found to have highly elevated levels of Zn, particularly along the main trunk roads, indicating that the Zn in the street dusts may be derived from traffic sources, especially vehicle tyres. The concentrations of metals in the different street dust samples were found to vary depending on the density of traffic.     

建立省级环境与健康调查及风险评估体系研究思路——以江苏省探索实践为例

以环境与健康调查及风险评估研究为出发点,江苏省于2018年设立了"江苏省环境与健康调查与风险评估体系建设"环保科研重大技术攻关类项目,根据江苏省行业、地区、流域特点以及江苏省环境与健康调查及风险评估工作基础,结合国内环境与健康研究现状,深入开展典型行业、地区、流域环境与健康调查、环境与健康问题分析、环境健康风险评价,建设环境与健康重点实验室,探索并实践环境与健康理念融入环境保护管理的研究任务,为全面开展环境与健康监测业务化运行以及环境健康风险评估进行技术实践和储备,为江苏省环境与健康管理工作提供支撑。     

Regulatory attitudes and environmental innovation in a model combining internal and external R&D

The extent to which environmental regulatory institutions are either ‘green’ or ‘brown’ impacts not just the intensity of regulation at any moment, but also the incentives for the development of new pollution-control technologies. We set up a strategic model of R&D in which a polluter can deploy technologies developed in-house, or license technologies developed by specialist outsiders (an ‘eco-industry’). Polluters exert R&D effort and may even develop redundant technologies to improve the terms on which they procure technology from outside. We find that, while regulatory bias has an ambiguous impact on the best-available technology, strategic delegation to systematically biased regulators can improve social welfare.     

Development of a coupled reservoir operation and water diversion model: Balancing human and environmental flow requirements

Maintaining a natural flow regime helps preserve the health of riverine ecosystems. Conventional studies on reservoir operations have focused mainly on identifying optimal operational schemes for satisfying human water demands. To systematically reflect the ecological effects of both natural and human-induced hydrologic alterations, water diversions downstream of the reservoirs should be considered as well. This research focused on a coupled reservoir operation and water diversion (CROWD) model, created through the integration of a reservoir operation model and a water diversion model. The proposed model considers both human and environmental flow requirements, and represents a compromise that balances ecological protection (preservation of the natural flow regime of a river) and human needs (reduced water shortages). In the reservoir operation model, the reservoir space is divided into three zones and different operating rules are developed for directing reservoir operation when water levels are in different zones; in the water diversion model, different water users are assigned different supply priorities with the instream flows no more than the minimum environmental flows having the highest priority; and the two models are coupled by the water mass balance between the two hydraulic facilities. The non-dominated-sorting genetic algorithm II (NSGA-II) was used to determine the parameters of the developed CROWD model and the model was applied to support the joint operational management of the Tanghe Reservoir and the Liaoyang Diversion in the Tang river basin, China. The resulting reservoir operation and water diversion schemes indicate that the CROWD model is useful for optimizing the operation of reservoirs and water diversion schemes. Moreover, it helps to analyze tradeoffs between human and environmental water needs, resulting in solutions that reduce the risk of water shortages and minimize ecological integrity disturbances.     

Characterization of biological responses under different environmental conditions: A hierarchical modeling approach

A natural river system is organized as a nested hierarchy of interconnected habitats with specific environmental conditions to which the biological community has adapted. Due to this hierarchical structure, identifying the role of different stressors on the biological community is a formidable task. Efforts trying to link stressors to biological integrity have always been bound to the geographic scale of the selected study area, leading to scale-specific results. In this research, an attempt is made to lift this limitation and develop a hierarchical, scale-sensitive methodology that can identify the significant environmental stressors to the biological community at different scales. Sites with similar background environmental conditions are clustered using self-organizing maps (SOM). This is used to identify stressors which affect the biological community throughout the area of study - called environmental gradients or large-scale stressors. Subsequently, these clusters of similar observations (sampling sites) are progressively sub-divided using environmental variables with a significant but localized effect on the biological community - called small-scale stressors. A parent group of sites is split only when the resulting sub-groups have significantly different biological responses. At the end of this recursive sites decomposition procedure, the original set of observations is organized as a tree of environmentally homogeneous groups of observations characterized by unique biological responses to multiple stressors with different geographic extents. The developed hierarchical analysis methodology has been validated using a large-size dataset of environmental observations from the State of Ohio. Our results show that habitat degradation and increased nutrient loading are the large-scale stressors with a widespread impact in Ohio. Other stressors, such as heavy metals, pH or nitrate concentrations have significant albeit localized effects on biological integrity.     

Ecosystem states: Creating a data-derived, ecosystem-scale ecological response model that is explicit in space and time

Increasing difficulties associated with balancing consumptive demands for water and achieving ecological benefits in aquatic ecosystems provide opportunities for new ecosystem-scale ecological response models to assist managers. Using an Australian estuary as a case study, we developed a novel approach to create a data-derived state-and-transition model. The model identifies suites of co-occurring birds, fish, benthic invertebrates and aquatic macrophytes (as ‘states’) and the changing physico-chemical conditions that are associated with each (‘transitions’). The approach first used cluster analysis to identify sets of co-occurring biota. Differences in the physico-chemical data associated with each state were identified using classification trees, with the biotic distinctness of the resultant statistical model tested using analysis of similarities. The predictive capacity of the model was tested using new cases. Two models were created using different time-steps (annual and quarterly) and then combined to capture both longer-term trends and more-recent declines in ecological condition. We identified eight ecosystem states that were differentiated by a mix of water-quantity and water-quality variables. Each ecosystem state represented a distinct biotic assemblage under well-defined physico-chemical conditions. Two ‘basins of attraction’ were identified, with four tidally-influenced states, and another four independent of tidal influence. Within each basin, states described a continuum of relative health, manifest through declining taxonomic diversity and abundances. The main threshold determining relative health was whether freshwater flows had occurred in the region during the previous 339 days. Canonical analyses of principal coordinates tested the predictive capacity of the model and demonstrated that the variance in the environmental data set was well captured (87%) with 52% of the variance in the biological data set also captured. The latter increased to >80% when long- and short-term biological data were analysed separately, indicating that the model described the available data for the Coorong well. This approach thus created a data-derived, multivariate model, where neither states nor transitions were determined a priori. The approach did not over-fit the data, was robust to patchy or missing data, the choice of initial clustering technique and random errors in the biological data set, and was well-received by local natural resource managers. However, the model did not capture causal relationships and requires additional testing, particularly during future episodes of ecological recovery. The approach shows significant promise for simplifying management definitions of ecological condition and, via scenario analyses, can be used to assist in manager decision-making of large, complex aquatic ecosystems in the future.     

Incorporating low-resolution historic species location data decreases performance of distribution models

Developing robust species distribution models is important as model outputs are increasingly being incorporated into conservation policy and management decisions. A largely overlooked component of model assessment and refinement is whether to include historic species occurrence data in distribution models to increase the data sample size. Data of different temporal provenance often differ in spatial accuracy and precision. We test the effect of inclusion of historic coarse-resolution occurrence data on distribution model outputs for 187 species of birds in Australian tropical savannas. Models using only recent (after 1990), fine-resolution data had significantly higher model performance scores measured with area under the receiver operating characteristic curve (AUC) than models incorporating both fine- and coarse-resolution data. The drop in AUC score is positively correlated with the total area predicted to be suitable for the species (R² = 0.163-0.187, depending on the environmental predictors in the model), as coarser data generally leads to greater predicted areas. The remaining unexplained variation is likely to be due to the covariate errors resulting from resolution mismatch between species records and environmental predictors. We conclude that decisions regarding data use in species distribution models must be conscious of the variation in predictions that mixed-scale datasets might cause.     

"参考声级校准法"研究初探

如何解决环境噪声监测系统的自动校准问题,是困扰现阶段我国环境噪声自动监测工作走向实用化的难题.文章首次提出"参考声级校准法"的概念,并利用数字校准的方式实现了自动声级校准,对"参考声级校准法"实现方法作了简要的说明与阐述.