Oil spill cleanup cost estimation—Developing a mathematical model for marine environment

The field of oil spill cost modelling is not as well explored as desirable. Generally speaking, the existing models have either low accuracy, in that their predictions are far from the real cost, or low applicability, in that they are only valid under very specific conditions; such as in one particular country. This work strives to construct a model that is functional in a global scope and still possess a high level of accuracy. The resulting attempt is in many ways superior to the publicly available competitors, not only because of its predictive capacity but also because the model is quick to use, and its input variables should be readily available to any informed user. The model is more accurate comparing with similar available models. However, further study is needed to modify it to obtain more realistic results.     

Three-Dimensional Modelling of Concentration Fluctuations in Complicated Geometry

The strong fluctuating component in the measured concentration time series of a dispersing gaseous pollutant in the atmospheric boundary layer, and the hazard level associated to short-term concentration levels, demonstrate the necessity of calculating the magnitude of turbulent fluctuations of concentration using computational simulation models. Moreover the computation of concentration fluctuations in cases of dispersion in realistic situations, such as built-up areas or street canyons, is of special practical interest for hazard assessment purposes. In this paper, the formulation and evaluation of a model for concentration fluctuations, based on a transport equation, are presented. The model is applicable in cases of complex geometry. It is included in the framework of a computational code, developed for simulating the dispersion of buoyant pollutants over complex geometries. The experimental data used for the model evaluation concerned the dispersion of a passive gas in a street canyon between 4 identical rectangular buildings performed in a wind tunnel. The experimental concentration fluctuations data have been derived from measured high frequency concentrations. The concentration fluctuations model is evaluated by comparing the model's predictions with the observations in the form of scatter plots, quantile-quantile plots, contour plots and statistical indices as the fractional bias, the geometrical mean variance and the factor-of-two percentage. From the above comparisons it is concluded that the overall model performance in the present complex geometry case is satisfactory. The discrepancies between model predictions and observations are attributed to inaccuracies in prescribing the actual wind tunnel boundary conditions to the computational code.     

计算毒理学在内分泌干扰物筛选上的应用和展望

内分泌干扰物通过干扰内分泌系统导致多种疾病,如生殖疾病、肥胖症甚至癌症。然而,面对环境中大量潜在的内分泌干扰物,传统的体外、体内评估方法由于成本高、耗时长等问题,难以实现内分泌干扰物的高通量筛查。计算毒理学逐渐发展成为被美国环保局(Environmental Protection Agency,EPA)、经济合作与发展组织(Organization for Economic Co-operation and Development,OECD)等机构所推荐的内分泌干扰物筛选与预测方法。本文综述了计算毒理学在内分泌干扰物筛选上的进展,主要包括分子对接和分子动力学模拟的应用,并对有害结局路径(adverse outcome pathway,AOP)的方法进行介绍和展望。     

农药环境风险评估中常用的计算毒理学模型软件

农药的大量使用为我国带来了严重的环境和健康问题,仅依靠传统生物测试和环境监测的方法已经不能满足农药风险评估的需要。利用计算毒理学模型,可以实现农药的高通量风险评估。本文主要介绍了农药环境风险评估中常用免费的EPI Suite、QSAR Toolbox和PBT Profiler等定量结构-活性关系(Quantitative Structure-Activity Relationship,QSAR)模型软件和SCIGROW、PRZM-GW、China-PEARL和EQC等环境多介质模型软件,以期能为农药的风险评估和科学管理提供参考。     

A Comprehensive Python Toolkit for Accessing High‐Throughput Computing to Support Large Hydrologic Modeling Tasks

The National Flood Interoperability Experiment (NFIE) was an undertaking that initiated a transformation in national hydrologic forecasting by providing streamflow forecasts at high spatial resolution over the whole country. This type of large‐scale, high‐resolution hydrologic modeling requires flexible and scalable tools to handle the resulting computational loads. While high‐throughput computing (HTC) and cloud computing provide an ideal resource for large‐scale modeling because they are cost‐effective and highly scalable, nevertheless, using these tools requires specialized training that is not always common for hydrologists and engineers. In an effort to facilitate the use of HTC resources the National Science Foundation (NSF) funded project, CI‐WATER, has developed a set of Python tools that can automate the tasks of provisioning and configuring an HTC environment in the cloud, and creating and submitting jobs to that environment. These tools are packaged into two Python libraries: CondorPy and TethysCluster. Together these libraries provide a comprehensive toolkit for accessing HTC to support hydrologic modeling. Two use cases are described to demonstrate the use of the toolkit, including a web app that was used to support the NFIE national‐scale modeling.     

Monod kinetics rather than a first-order degradation model explains atrazine fate in soil mini-columns: Implications for pesticide fate modelling

Pesticide transport models commonly assume first-order pesticide degradation kinetics for describing reactive transport in soil. This assumption was assessed in mini-column studies with associated batch degradation tests. Soil mini-columns were irrigated with atrazine in two intermittent steps of about 30 days separated by 161 days application of artificial rain water. Atrazine concentration in the effluent peaked to that of the influent concentration after initial break-through but sharply decreased while influx was sustained, suggesting a degradation lag phase. The same pattern was displayed in the second step but peak height and percentage of atrazine recovered in the effluent were lower. A Monod model with biomass decay was successfully calibrated to this data. The model was successfully evaluated against batch degradation data and mini-column experiments at lower flow rate. The study suggested that first-order degradation models may underestimate risk of pesticide leaching if the pesticide degradation potential needs amplification during degradation.     

Inferring chemical effects on carbon flows in aquatic food webs: Methodology and case study

The majority of ecotoxicological enclosure experiments monitor species abundances at different chemical concentrations. Here, we present a new modelling approach that estimates changes in food web flows from such data and show that population- and food web level effects are revealed that are not apparent from abundance data alone. For the case of cypermethrin in freshwater enclosures, photosynthesis and excretion (d⁻¹) of phytoplankton at 3.643 μg L⁻¹ cypermethrin were 30% lower and 100% higher than in the control, respectively. The ingestion rate of mesozooplankton (d⁻¹) was 6 times higher in the treated enclosures than in the control as food concentration increased with insecticide exposure. With increasing cypermethrin concentrations, nanoflagellates progressively relied on phytoplankton as their main food source, which rendered the food web less stable. We conclude that this tool has excellent potential to analyse the wealth of enclosure data as it only needs species abundance and general constraints.     

The contribution of ship emissions to air pollution in the North Sea regions

As a consequence of the global distribution of manufacturing sites and the increasing international division of labour, ship traffic is steadily increasing and is becoming more and more important as an origin of air pollution.This study investigates the impact of ship emissions in coastal areas of the North Sea under conditions of the year 2000 by means of a regional chemistry transport model which runs on a sufficiently high resolution to study air pollution in coastal regions. It was found that northern Germany and Denmark in summer suffer from more than 50% higher sulphate, nitrate and ammonium aerosol concentrations due to contributions from ships. The implementation of a sulphur emission control area (SECA) in the North Sea, as it was implemented at the end of 2007, directly results in reduced sulphur dioxide and sulphate aerosol concentrations while nitrate aerosol concentrations are slightly increased.     

Improving inverse model fitting in trees—Anisotropy,multiplicative effects,and Bayes estimation

Model fitting for individual-based effects in forests has some problems. Because samples measuring the separate influence of each individual are rarely available, the measured value in the sample represents the influence of all surrounding individual trees. Therefore, it is helpful to build inverse models that use the spatial pattern of the variable as well as that of the source trees. For example, since seed dispersal is influenced by wind effects, a model is discussed describing anisotropic effects to ensure an unbiased estimate of the total fruit number. Further, we present a model describing the absorption of radiation by trees. In this case a multiplicative combination of individual effects yields the total effect. Our approach uses logarithmic transformations of the original data to model multiplicative combinations as sum of transformed single effects. For fitting model parameters we propose an approach based on Bayesian statistics, to ensure ecologically interpretable parameters.     

QSAR trout toxicity models on aromatic pesticides

The pesticides originally designed to kill target organisms are dangerous for many other wild species. Since they are applied directly to the environment, they can easily reach the water basins and the topsoil. A dataset of 125 aromatic pesticides with well-expressed aquatic toxicity towards trout was subjected to quantitative structure activity relationships (QSAR) analysis aimed to establish the relationship between their molecular structure and biological activity. A literature data for LC₅₀ concentration killing 50% of fish was used. In addition to the standard 2D-QSAR analysis, a comparative molecular field analysis (CoMFA) analysis considering the electrostatic and steric properties of the molecules was also performed. The CoMFA analysis helped the recognition of the steric interactions as playing an important role for aquatic toxicity. In addition, the transport properties and the stability of the compounds studied were also identified as important for their biological activity.