Statistical interpolation model for the description of ground pollution due to the TCDD produced in the 1976 chemical accident at seveso in the heavily contaminated zone “A”;

The influence of NTA on chromium genetic activity was studied in the D7 strain of Saccharomyces cerevisiae. At low dose (subgenotoxic) of sodium chromate (CrVI) (5mM), NTA increased the point mutation while at higher dose (25 mM) of chromate in the presence of NTA a decrease of point reverse mutation was observed. Probably NTA affected either the uptake of Cr(VI) favouring the intracellular reduction to Cr(III), or the recombinational repair of DNA breaks induced by chromate oxiding activity.

An increase of point (reverse) mutation was obtained in the experiments with NTA and chromium chloride, suggesting the hypothesis that NTA might interact with Cr(III) forming NTA‐Cr(III) complexes able to permeate cellular membranes and bind to DNA. In addition NTA genetic inactivity was confirmed.     

Regression models for octanol‐water partition coefficients,and for bioconcentration in fish

Octanol‐water partition coefficients (P) of a number of organochlorine insecticides (OCs) are presented. The merits of log‐log regressions between experimental ? values and calculated estimates of P, solute activity coefficients in water, solute molecular surface area data, and reversed‐phase liquid‐chromatographic net retention data, are critically evaluated for several classes of pollutants: polycyclic aromatic hydrocarbons (PAHs), chlorinated benzenes, chlorinated biphenyls and OCs. Special attention is paid to the predictive accuracy of such semi‐empirical regressions in connection with possible effects of solute molecular shape and polarity.

Finally, bioconcentration and ‐accumulation of hydrophobic pollutants in fish are briefly discussed.     

An approach to calculating allowable watershed pollutant loads

To improve the management of discharge pollutants loads in the reservoirs’ watershed, an approach of the allowable pollutants loads calculation and its allocation, based on the water environment model, was proposed. Establishment of the approach framework was described at first. Under the guidance of this framework, two major steps were as follows: modeling and scenario analysis were involved and should be applied to support the decision of discharge loads management; Environmental Fluid Dynamic Code (EFDC) model was selected as the kernel model in this framework. In modeling step, spatial discretization for establishing cell map in model, data preprocessing, parameter calibration and uncertainty analysis (which is considered as the significantly relevant factor of the margin of safety (MOS)), were conducted. As a result of the research, the model-based approach presented as a combination of estimation and precise calculation, which contributed to scenario analysis step. Some integrated modules, such as scenario simulation, result analysis and plan optimization were implemented as cycles in the scenario analysis. Finally, allowable pollutant loads under various conditions were calculated. The Chaihe Reservoir in Liaoning Province, China was used as a case study for an application of the approach described above. Results of the Chaihe reservoir water quality simulation, show good agreement with field data and demonstrated that the approach used in the present study provide an efficient and appropriate methodology for pollutant load allocation.     

沱江流域总氮面源污染负荷时空演变

根据四川省沱江流域水环境受总氮（TN）面源严重污染的现状,采用排污系数法估算2007~2017年该流域来自各面源污染源的TN污染负荷,并利用空间重心统计法和空间分析技术揭示沱江流域TN污染负荷时空分布特征及转移趋势,以期为相关部门精准防控和预警沱江流域面源污染提供理论依据.结果表明,2007~2017年畜禽养殖污染源对整个流域的TN污染负荷贡献率每年均在45%以上,是TN面源污染的主要污染源.农村生活和农村生活垃圾污染源的贡献率呈逐年减少趋势,农田固废和农田径流污染源的贡献率则呈增加趋势.TN总污染负荷总体呈下降趋势,2010年污染负荷最大,达到5.7×10⁴ t,2017年最小,为4.69×10⁴ t.污染负荷在空间上的异质性变化及降雨径流的不均匀分布驱使畜禽养殖、农田固废类和农田径流污染源的TN污染负荷重心由西北向东南方向移动,流域东南部是畜禽养殖、农田固废类和农田径流TN污染的重点防控区域.东南部各区县的农业人口大量向城市人口转化,进而驱动农村生活和农村生活垃圾污染源的TN污染负荷重心由东南向西北方向转移,其转移范围高达66.35 km²,由此确定的最小边界圆是污染源污染负荷变化的重点识别区域,沱江流域西北部则是农村生活和农村生活垃圾TN污染的重点防控区域.本研究拓展了环境科学领域对流域污染负荷时空演变的探究方法,对于改善水环境质量,促进流域经济可持续发展具有重要意义.     

The representation of cyanobacteria life cycle processes in aquatic ecosystem models

Two simplified versions of a numerical life cycle model for diazotrophic cyanobacteria (of the order Nostocales) are developed and evaluated. Both consider two-life cycle stages, one growing, nitrogen-fixing stage and one stage that combines the resting, germinating and vegetative stages. The versions differ in the vertical resolution of the non-diazotrophic stage: version 1 collects the biomass in one layer at the bottom, version 2 considers sinking and rising of biomass explicitly. The results of the two versions are compared with a complex cyanobacteria life cycle model which describes four different life cycle stages each with two internal quotas for energy and nitrogen. The two simplified approaches show a good agreement with respect to the main characteristics of cyanobacteria dynamics (timing and duration of blooms, magnitude of nitrogen fixation, interannual variability). Our model study shows that both simplified approaches are suitable to be implemented into three-dimensional coastal or lake models.     

An Integrated Monte Carlo Methodology for the calibration of water quality models

This paper proposes an Integrated Monte Carlo Methodology (IMCM) to solve the parameter estimation problem in water quality models. The methodology is based on Bayesian approach and Markov Chain Monte Carlo techniques and it operates by means of four modules: Markov Chain Monte Carlo (MCMC), Moving Feasible Ranges (MFR), Statistical Analysis of the Joint Posterior Distribution (SAD) and Uncertainty Propagation Analysis (UPA). The main innovation of the new proposal lies in the combination of MCMC and MFR modules which provides the joint posterior distribution of the calibrated parameters following the classical Bayesian approach. While MCMC module, based on Shuffled Complex Evolution Metropolis (SCEM-UA) algorithm, is specially designed to sample complex joint posterior shapes within certain parameter ranges, the MFR readjusts these ranges until the coverage of the feasible parameter space is guaranteed. Once the joint posterior distribution is properly defined, the SAD provides the parameter statistics and the UPA performs an analysis of the uncertainty propagation through the model. The possibilities of the new proposal have been tested on the basis of a simple model featuring different activated sludge batch experiments. IMCM has been implemented in Matlab and it is prepared to be easily connected to any software package.     

Matching the Multiple Scales of Conservation with the Multiple Scales of Climate Change

Abstract:  To anticipate the rapidly changing world resulting from global climate change, the projections of climate models must be incorporated into conservation. This requires that the scales of conservation be aligned with the scales of climate-change projections. We considered how conservation has incorporated spatial scale into protecting biodiversity, how the projections of climate-change models vary with scale, and how the two do or do not align. Conservation planners use information about past and current ecological conditions at multiple scales to identify conservation targets and threats and guide conservation actions. Projections of climate change are also made at multiple scales, from global and regional circulation models to projections downscaled to local scales. These downscaled projections carry with them the uncertainties associated with the broad-scale models from which they are derived; thus, their high resolution may be more apparent than real. Conservation at regional or global scales is about establishing priorities and influencing policy. At these scales, the coarseness and uncertainties of global and regional climate models may be less important than what they reveal about possible futures. At the ecoregional scale, the uncertainties associated with downscaling climate models become more critical because the distributions of conservation targets on which plans are founded may shift under future climates. At a local scale, variations in topography and land cover influence local climate, often overriding the projections of broad-scale climate models and increasing uncertainty. Despite the uncertainties, ecologists and conservationists must work with climate-change modelers to focus on the most likely projections. The future will be different from the past and full of surprises; judicious use of model projections at appropriate scales may help us prepare.     

Applying Hierarchical Loglinear Models to Nonfatal Underground Coal Mine Accidents for Safety Management

Underground mining is considered to be one of the most dangerous industries and mining remains the most hazardous occupation. Categorical analysis of accident records may present valuable information for preventing accidents. In this study, hierarchical loglinear analysis was applied to occupational injuries that occurred in an underground coal mine. The main factors affecting the accidents were defined as occupation, area, reason, accident time and part of body affected. By considering subfactors of the main factors, multiway contingency tables were prepared and, thus, the probabilities that might affect nonfatal injuries were investigated. At the end of the study, important accident risk factors and job groups with a high probability of being exposed to those risk factors were determined. This article presents important information on decreasing the number accidents in underground coal mines.