土壤环境监测基础点位布设思路与方法

为适应新形势下土壤环境保护工作重点任务和要求,"十三五"期间,中国亟需构建布局合理、功能完备的土壤环境监测网,确定国控监测点位,以说清全国土壤环境质量整体状况、潜在风险状况及变化趋势。通过梳理欧美等发达国家和地区的做法和经验,针对国内土壤环境的实际情况,开展布点尺度和点位优化方法研究,提出了国家尺度上适宜布点尺度,建立了统一的历史点位优化筛选规则,在此基础上,形成了点位的布设思路、原则和方法,并给出了阶段性的布设结果,最后提出了后续进一步完善的方向。     

基于改进的多目标决策的水环境质量综合评价

在对水环境质量综合评价中,多目标决策-理想区间法解决了水环境质量评价标准是区间而非点的缺陷。但是在计算监测点到各理想区间向量的距离时,各水环境质量指标权重直接影响综合评价的结果,通常的确定方法是简单的假设各水环境质量指标的权重相等,这与实际情况相悖。为了解决这一问题,提出了将超标法用于多目标决策法中,利用超标法确定各水环境质量指标的权重,然后将其应用于多目标决策-理想区间法来分析水环境质量等级。并将改进后的多目标决策-理想区间法应用于珠江口及邻近海域的水环境中。基于超标法确定权重的多目标决策-理想区间法与聚类分析相比更有效,与等权重的多目标决策-理想区间法相比,更能体现水环境的污染状况,可应用于各种环境因子的综合评价中。     

基于Monte Carlo的海洋平台圆柱落物落点分析及危险区快速评价*

为实现海洋平台落物风险快速精确评价，针对传统推荐性规范经验化、过于简化、平面化及未体现工程随机性等问题，以圆柱落物为研究对象开展先导研究，基于3D运动理论模型，提出1种采用Monte Carlo方法表征工程随机性以实现危险区快速精确评价的方法，自主开发形成海洋平台圆柱落物危险区快速评价工具（MREDP），着重分析落点分布规律和危险区等级划分。结果表明:落点分布整体呈现“倒工字圆弧型”、两端“一密一疏”、关于X轴对称特点；MREDP快速评价结果可信，评价周期大幅降低；MREDP快速评价危险区相对较大、存在多峰值点，DNVGL-RP-F107推荐危险区相对保守、存在单峰值点。     

Threshold responses of Amazonian stream fishes to timing and extent of deforestation

Deforestation is a primary driver of biodiversity change through habitat loss and fragmentation. Stream biodiversity may not respond to deforestation in a simple linear relationship. Rather, threshold responses to extent and timing of deforestation may occur. Identification of critical deforestation thresholds is needed for effective conservation and management. We tested for threshold responses of fish species and functional groups to degree of watershed and riparian zone deforestation and time since impact in 75 streams in the western Brazilian Amazon. We used remote sensing to assess deforestation from 1984 to 2011. Fish assemblages were sampled with seines and dip nets in a standardized manner. Fish species (n = 84) were classified into 20 functional groups based on ecomorphological traits associated with habitat use, feeding, and locomotion. Threshold responses were quantified using threshold indicator taxa analysis. Negative threshold responses to deforestation were common and consistently occurred at very low levels of deforestation (<20%) and soon after impact (<10 years). Sensitive species were functionally unique and associated with complex habitats and structures of allochthonous origin found in forested watersheds. Positive threshold responses of species were less common and generally occurred at >70% deforestation and >10 years after impact. Findings were similar at the community level for both taxonomic and functional analyses. Because most negative threshold responses occurred at low levels of deforestation and soon after impact, even minimal change is expected to negatively affect biodiversity. Delayed positive threshold responses to extreme deforestation by a few species do not offset the loss of sensitive taxa and likely contribute to biotic homogenization.     

适用于移动平台的河流突发污染溯源算法研究

提出了一种适用于小型移动水质检测平台的一维均一地表水单点源污染物溯源新算法,即通过计算污染物在时间域和空间域的质量浓度导数来反推污染物初始排放点的位置、排放时间及污染物总量.首先,通过算例仿真研究表明,此方法具有较高的溯源精度(与理论距离偏差在10％以内).其次,结合目前移动检测的实际限制(平台长度、取样时间等),对算法中涉及的采样时间、距离等因素的选择进行分析,对移动平台的溯源操作给出了优化建议,以确保有较高的溯源精度.最后,通过实验室水槽缩尺模型试验验证了算法有较高溯源精度(最大偏差在30％以内),从而在原理上证明了该算法适用于特定流域下的移动水质污染溯源.     

MNLR and ANN structural group contribution methods for predicting the flash point temperature of pure compounds in the transportation fuels range

A QSPR method is presented for predicting the flash point temperature (FPT) of pure compounds in the transportation fuels range. A structural group contribution method is used to determine the flash point temperature using two techniques: multivariable nonlinear regression and artificial neural networks. The method was used to probe the structural groups that have significant contribution to the overall FPT of pure compounds and arrive at the set of 37 atom-type structural groups that can best represent the flash point for about 375 substances. The input parameters to the model are the number of occurrence of each of the 37 structural groups in each molecule. The neural network method was the better of the two techniques and can predict the flash point of pure compounds merely from the knowledge of the molecular structure with an overall correlation coefficient of 0.996 and overall average and maximum errors of 1.12% and 6.62%, respectively. The results are compared to the more traditional approach of the SGC method along with other methods in the literature.     

Rapid declines of large mammal populations after the collapse of the Soviet Union

Anecdotal evidence suggests that socioeconomic shocks strongly affect wildlife populations, but quantitative evidence is sparse. The collapse of socialism in Russia in 1991 caused a major socioeconomic shock, including a sharp increase in poverty. We analyzed population trends of 8 large mammals in Russia from 1981 to 2010 (i.e., before and after the collapse). We hypothesized that the collapse would first cause population declines, primarily due to overexploitation, and then population increases due to adaptation of wildlife to new environments following the collapse. The long‐term Database of the Russian Federal Agency of Game Mammal Monitoring, consisting of up to 50,000 transects that are monitored annually, provided an exceptional data set for investigating these population trends. Three species showed strong declines in population growth rates in the decade following the collapse, while grey wolf (Canis lupus) increased by more than 150%. After 2000 some trends reversed. For example, roe deer (Capreolus spp.) abundance in 2010 was the highest of any period in our study. Likely reasons for the population declines in the 1990s include poaching and the erosion of wildlife protection enforcement. The rapid increase of the grey wolf populations is likely due to the cessation of governmental population control. In general, the widespread declines in wildlife populations after the collapse of the Soviet Union highlight the magnitude of the effects that socioeconomic shocks can have on wildlife populations and the possible need for special conservation efforts during such times. Declinación Rápida de las Poblaciones de Mamíferos Mayores después del Colapso de la Unión Soviética     

Flash points measurements and prediction for binary miscible mixtures

Flash point is one of the most important parameters used to characterize the potential fire and explosion hazards for flammable liquids. In this study, flash points of twenty eight binary miscible mixtures comprised eighteen flammable pure components with different compositions were measured by using the closed cup apparatus. The obtained experimental data are further employed to develop simple and accurate models for predicting the flash points of binary miscible mixtures. Based on the vapor–liquid equilibrium theory, the normal boiling point, the standard enthalpy of vaporization, the average number of carbon atoms, and the stoichiometric concentration of the gas phase were selected as the dominant physicochemical parameters that were relevant to the overall flash point property of liquids. With these parameters for pure components as well as the compositions of mixtures, the new form of characteristic physicochemical parameters for mixtures were developed and used as the input parameters for the flash point prediction of mixtures. Both the modeling methods of multiple linear regression (MLR) and multiple nonlinear regression (MNR) were employed to model the possible quantitative relationships between the parameters for mixtures and the flash points of binary miscible mixtures. The resulted models showed satisfactory prediction ability, with the average absolute error for the external test set being 2.506 K for the MLR model and 2.537 K for the MNR model, respectively, both of which were within the range of the experimental error of FP measurements. Model validation was also performed to check the stability and predictivity of the presented models, and the results showed that both models were valid and predictive. The models were further compared to other previously published models. The results indicated the superiority of the presented models and revealed which can be effectively used to predict the FP of binary miscible mixtures, requiring only some common physicochemical parameters for the pure components other than any experimental flash point or flammability limit data as well as the use of the Le Chatelier law. This study can provide a simple, yet accurate way for engineering to predict the flash points of binary miscible mixtures as applied in the assessment of fire and explosion hazards and the development of inherently safer designs for chemical processes.     

Application of AERMOD on near future air quality simulation under the latest national emission control policy of China：A case study on an industrial city

Air quality model can be an adequate tool for future air quality prediction, also atmospheric observations supporting and emission control strategies responders. The influence of emission control policy (emission reduction targets in the national "China’s 12th Five-Year Plan (2011-2015)") on the air quality in the near future over an important industrial city of China, Xuanwei in Yunnan Province, was studied by applying the AERMOD modeling system. First, our analysis demonstrated that the AERMOD modeling system could be used in the air quality simulation in the near future for SO2 and NOx under average meteorology but not for PM10. Second, after evaluating the simulation results in 2008 and 2015, ambient concentration of SO2, NOx and PM10 (only 2008) were all centered in the middle of simulation area where the emission sources concentrated, and it is probably because the air pollutions were source oriented. Last but not least, a better air quality condition will happen under the hypothesis that the average meteorological data can be used in near future simulation. However, there are still heavy polluted areas where ambient concentrations will exceed the air quality standard in near future. In spatial allocation, reduction effect of SO2 is more significant than NOx in 2015 as the contribution of SO2 from industry is more than NOx. These results inspired the regulatory applications of AERMOD modeling system in evaluating environmental pollutant control policy     

哈尔滨市农村生态环境污染防治对策

农村生态环境保护与建设是建设生态文明的重要组成部分,也是重要基础工作。随着农村经济发展,城镇化进程的不断加深,农村的生态环境保护面临巨大压力。为进一步解析哈尔滨市农村污染现状、发展态势和目前存在的问题,阐明了哈尔滨市农村污染防治的意义与必要性,文章在调研当前哈尔滨市农村生态环境存在的问题基础上,对农村面源污染产生的生态环境破坏进行了深入的研究,在充分利用当前国家加大农村环境建设投入的有利机遇基础上,提出了哈尔滨市农村生态环境污染相应的防治对策,为哈尔滨市农村生态文明建设和农村环境保护提供借鉴和参考。