基于ANN的土壤重金属分布和污染评价研究

农田土壤重金属污染与备受关注的农产品安全问题有密切联系,因此对其进行研究意义重大。以江苏省南通市为研究区,利用采样点实测数据,借助神经网络模型(ANN)并结合3S技术对问题进行研究,从而对土壤重金属的空间动态分布进行描述,并对各个空间位点重金属的污染状况进行评价。结果表明,神经网络模型能够智能地学习各个样点的空间位置与该点各重金属含量之间的映射关系和预先设计好的分类评价模式,并能够稳健地对各个空间插值点处的重金属含量和各个位点的重金属污染状况进行预测和评价。结论显示,南通市大部分农田土壤重金属污染较轻,但也存在局部地区的严重污染。结论与实际情况相符,表明神经网络模型可以为农田土壤重金属的研究提供一个新的思路和方法。     

Phast validation of discharge and atmospheric dispersion for pressurised carbon dioxide releases

The consequence modelling package Phast examines the progress of a potential incident from the initial release to the far-field dispersion including the modelling of rainout and subsequent vaporisation. The original Phast discharge and dispersion models allow the released substance to occur only in the vapour and liquid phases. The latest versions of Phast include extended models which also allow for the occurrence of fluid to solid transition for carbon dioxide (CO₂) releases.As part of two projects funded by BP and Shell (made publicly available via CO2PIPETRANS JIP), experimental work on CO₂ releases was carried out at the Spadeadam site (UK) by GL Noble Denton. These experiments included both high-pressure steady-state and time-varying cold releases (liquid storage) and high-pressure time-varying supercritical hot releases (vapour storage). The CO₂ was stored in a vessel with attached pipework. At the end of the pipework a nozzle was attached, where the nozzle diameter was varied.This paper discusses the validation of Phast against the above experiments. The flow rate was predicted accurately by the Phast discharge models (within 10%; considered within the accuracy at which the BP experimental data were measured), and the concentrations were found to be predicted accurately (well within a factor of two) by the Phast dispersion model (UDM). This validation was carried out with no fitting whatsoever of the Phast extended discharge and dispersion models.     

Validation of discharge and atmospheric dispersion for unpressurised and pressurised carbon dioxide releases

This paper discusses the validation of discharge and subsequent atmospheric dispersion for both unpressurised and pressurised carbon dioxide releases using the consequence modelling package Phast.The paper first summarises the validation of the Phast dispersion model (UDM) for unpressurised releases. This includes heavy gas dispersion from either a ground-level line source (McQuaid wind-tunnel experiments) or an area source (Kit-Fox field experiments). For the McQuaid experiments minor modifications of the UDM were made to support line sources. For the Kit Fox experiments steady-state and 20-s finite-duration releases were simulated for both neutral and stable conditions. Most accurate predictions of the concentrations for finite duration releases were obtained using the UDM Finite Duration Correction method.Using experiments funded by BP and Shell and made available via DNV's CO2PIPETRANS JIP, the paper secondly summarises the validation of the Phast discharge and dispersion models for pressurised CO₂ releases. This modelling accounted for the possible presence of the solid CO₂ phase following expansion to atmospheric pressure. These experiments included both high-pressure steady-state and time-varying cold releases (liquid storage) and high-pressure time-varying supercritical hot releases. Both the flow rate and the concentrations were found to be predicted accurately.The above validation was carried out with no fitting whatsoever of the Phast extended discharge and dispersion models.     

Sensitivity analysis of the two dimensional application of the Generic Ecological Model (GEM) to algal bloom prediction in the North Sea

Harmful algae can cause damage to co-existing organisms, tourism and farmers. Accurate predictions of algal future composition and abundance as well as when and where algal blooms may occur could help early warning and mitigating. The Generic Ecological Model is an instrument that can be applied to any water system (fresh, transitional or coastal) to calculate the primary production, chlorophyll-a concentration and phytoplankton species composition. It consists of physical, chemical and ecological model components which are coupled together to build one generic and flexible modelling tool. In this paper the model has been analyzed to assess sensitivity of the simulated chlorophyll-a concentration to a subset of ecologically significant input factors. Only a small number of approaches could be considered as suitable for several reasons including the model complexity, engagement of numerous interacting parameters and relatively long time of a single simulation. Thus, sensitivity analysis has been carried out with the use of the Morris method and later enriched by the computation of the correlation ratios of the selected parameters on the model response at more than a few locations in the modelled area. The obtained results are in agreement with expert knowledge of the ecological processes in the North Sea and correspond well with local characteristics.     

Policy relevance of three integrated assessment tools—A comparison with specific reference to agricultural policies

The Common Agricultural Policy (CAP), a system of market support instruments, direct income transfers, and rural development measures, has been put through an ongoing reform process in recent decades. This paper introduces three policy impact assessment tools (SIAT, SEAMLESS-IF, MEA-Scope tool) and analyses how these tools have responded to a number of challenges for integrated assessment modelling as reported in the international literature. Significant progress has been made with regard to modelling linkages whereas other challenges, particularly those related to issues of scale and uncertainty management, require further efforts. It is also analysed which CAP instruments are represented and what kinds of effects can be analysed at different scales. Market instruments and direct payments are comparatively well represented, while the ability to model rural development measures is mostly beyond the scope of these tools. Because each tool has found a different solution for coping with the common challenges of integrated assessment modelling, the choice of one of the tools for a particular application depends strongly on the policy questions being asked. The SIAT provides the big picture via its ability to represent broad changes in policy instruments with EU-wide cross-sector impacts. The most comprehensive analysis of agricultural policy instruments can be obtained with SEAMLESS-IF. The MEA-Scope tool complements the other two approaches with detailed regional profiles.     

Impact of the quality of climate models for modelling species occurrences in countries with poor climatic documentation: a case study from Bolivia

The quality of climate models has largely been overlooked as a possible source of uncertainty that may affect the outcomes of species distribution models, especially in the tropics, where comparatively few climatic stations are available. We compared the geographical discrepancies and potential conservation implications of using two different climate models (Saga and Worldclim) in combination with the species modelling approach Maxent in Bolivia. We estimated ranges of selected bird and fern species biogeographically restricted to either humid montane forest of the northern Bolivian Andes or seasonal dry tropical forests (in the Andes and southern lowlands). Saga and Worldclim predicted roughly similar climate patterns of temperature that were significantly correlated. Precipitation layers of both climate models were also roughly similar, but showed important differences. Species ranges estimated with Worldclim and Saga likewise produced different results. Ranges of species endemic to humid montane forests estimated with Saga had higher AUC (Area under the curve) values than those estimated with Worldclim, which for example predicted the occurrence of humid montane forest bird species near Lake Titicaca, an area that is clearly unsuitable for these species. Likewise, Worldclim overpredicted the occurrence of fern and bird species in the lowlands of the Chapare region and well south of the Andean Elbow, where more seasonal biomes occur. By contrast, Saga predictions were coherent with the known distribution of humid montane forests in the northern Bolivian Andes. Estimated ranges of species endemic to seasonal dry tropical forests predicted with Saga and Worldclim were not statistically different in most cases. However, detailed comparisons revealed that Saga was able to distinguish fragments of seasonal dry tropical forests in rain-shadow valleys of the northern Bolivian Andes, whereas Worldclim was not. These differences highlight the neglected influence of climate layers on modelling results and the importance of using the most accurate climate data available when modelling species distributions.     

Enhancing generic ecological model for short-term prediction of Southern North Sea algal dynamics with remote sensing images

Physically based numerical modelling follows from the basic understanding of the underlying mechanisms and is often represented by a set of (partial differential) equations. It is one of the main approaches in population dynamics modelling. The emphasis of the model introduced in this paper is on the simulation of short-term spatial and temporal dynamics of harmful algal bloom (HAB) events. Total suspended matter (TSM) concentration is one of the dominant factors for harmful algal bloom (HAB) prediction in North Sea. However, the modelling of suspended matter contains a high degree of uncertainty in this area. Therefore, this research aims to achieve a better estimation for the short-term prediction of harmful algal bloom development in both space and time by using spatially distributed TSM retrieved from remotely sensed images as physically based model inputs. In order to supply complete spatially covered datasets for the physically based model instrument: generic ecological model (GEM), this research retrieves TSM information from MERIS images by means of proper estimation techniques including biharmonic splines and self-learning cellular automata. A better estimation of HAB spatial pattern development is achieved by adding spatially distributed TSM data as inputs to original GEM model, and it proved that chlorophyll-a concentration in this area is very sensitive to TSM concentration.     

Role of behavioural factors in green supply chain management implementation in Indian mining industries

Green supply chain management (GSCM) integrates ecological concepts with those of supply chain management in order to minimize energy and material usage and to reduce adverse impacts of supply chain activities on the environment. GSCM implementation in mining industries depends largely upon certain factors which are influenced by human behaviours. Human behaviour is dynamic in nature and the relationships between them continuously evolve and change. In this ever-changing context, therefore, identifying and ranking the behavioural factors that affect GSCM implementation becomes essential. This can be taken as a reference by the decision makers while deciding the hierarchy of action necessary for effective implementation of green practices in mining supply chains. The present research attempts to explore various behavioural factors affecting GCSM practices and their interactions which help to attain green-enabled needs. Interpretive structural modelling (ISM) is employed in this research to extract the interrelationships among the identified behavioural factors.     

A new approach to assessment and management of the impact from medical liquid radioactive waste

The Swedish regulations concerning disposal of clinical radioactive waste are currently under revision and a graded approach is proposed for risk limitation purposes. To assist the revision procedures, a screening study was performed to estimate public exposures from liquid releases from hospitals to public sewers. The results showed that doses to sewage workers were above the dose constraint of 100muSva(-1) especially for (131)I and (99m)Tc. Hence, a dynamic model, LUCIA, was developed for realistic assessments in which radionuclide transportation in sewers was modelled. Probabilistic simulations were performed to obtain probability distributions of radionuclide concentrations in sludge. Concurrently, estimates of the effective doses to sewage workers decreased significantly and were below 10muSva(-1) except for (111)In and (131)I. However, the Kd-coefficients representing the partition of radioactivity between water and sludge in sewers are highly uncertain for (111)In. As shown by sensitivity studies, these values are the major determinant of the exposures in sewers.