大气自净能力指数的气候特征与应用研究

为了定量地评估污染气象条件对空气污染的作用并实现对空气污染潜势的预报,本文在城市大气污染数值预报系统（CAPPS）预报原理的基础上,定义了大气自净能力指数,并分别给出了采用气象站观测资料和通过数值模拟计算大气自净能力指数的方法.基于气象站观测资料的全国大气自净能力指数分析计算表明,全国大气自净能力最差的地区分布在四川盆地和新疆塔里木盆地,大气自净能力最强的地区分布在青藏高原、蒙古高原、云贵高原、以及东北平原和三江平原、山东半岛和海南岛;1961~2017年,京津冀、长三角和珠三角地区的大气自净能力指数呈下降的变化趋势,全年低自净能力日数呈上升的变化趋势.采用大气自净能力指数评估2014年北京APEC会议期间大气污染防控效果,表明在11月8~10日极端不利扩散气象条件发生时,减排措施使北京市空气质量AQI平均降低77%,使京津冀平原地区11个城市的空气质量AQI平均降低37%.基于国家气候中心月动力延伸气候预测模式（DERF2.0）的预报产品和中尺度模式（WRF）,建立了可以预测全国未来40d逐日大气自净能力指数的延伸期-月尺度大气污染潜势预测系统,回报实验表明,在大多数情况下可以提前15d预报出大气重污染过程;月尺度的大气重污染过程预报效果更大程度上取决于月动力延伸气候预测模式（DERF2.0）的预报准确率.     

考虑边界条件不确定性的地下水污染风险分析

为分析边界条件不确定性对地下水污染质运移数值模拟模型输出结果的影响,运用Monte Carlo方法对一算例进行阐明,并从污染风险预报方面对模拟结果进行分析.为减少重复调用模拟模型产生的大量计算负荷,将边界条件（第一类边界条件-水头值）作为随机变量,建立地下水污染质运移数值模拟模型的Kriging替代模型,在保证较高精度的同时,实现了Monte Carlo模拟.结果表明：边界条件的不确定性,对地下水污染质运移数值模拟模型预报的结果有很大影响,考虑与未考虑边界条件不确定性得到的研究区污染羽分布差别较大.对地下水污染质运移数值模拟模型的Monte Carlo模拟结果进行统计与分析,可以评估研究区观测井1,2,3污染物浓度预报结果的可靠程度,并且可以预报出研究区观测井1,2,3遭受不同程度污染的风险.     

反舰导弹命中精度预测与评估

目的解决反舰导弹命中精度受试验航区及靶场试验环境等客观条件制约,难以通过飞行试验得到客观全面评估的问题。方法在对影响反舰导弹命中精度的主要因素进行分析的基础上,利用实际环境条件下的飞行试验数据,构建基于偏最小二乘回归的命中精度模型,实现对反舰导弹各种使用环境条件命中精度的定量评估。结果在构建基于偏最小二乘回归的命中精度模型后,可以实现对90°发射扇面角、20 m/s侧风以及300 km最大射程等实际试验无法考核的边界使用环境条件下反舰导弹的命中精度进行定量评估。结论通过实例分析表明了方法的有效性和可行性,可以实现有小样本条件下对反舰导弹命中精度的评估。     

基于SOM-SVM组合分类器的涂层防护性能研究

目的为避免EIS,EN技术可能出现的问题,建立一个准确、高效的评价模型,以探究现役军用有机涂层防护性能。方法利用电化学阻抗谱(EIS)、电化学噪声(EN)技术分析了两种军车有机涂层在循环暴露试验中的腐蚀行为,提取低频阻抗模值|Z|_(0.1 Hz)与涂层噪声电阻R_n两种电化学评价参数作为自组织神经网络(SOM)的输入训练样本,同时结合支持向量机(SVM)方法建立涂层防护性能组合分类器。结果将涂层失效过程自适应地分为涂层防护性能良好、防护性能下降、基本失效三个阶段。结论所建立的SOM-SVM组合分类器对于辅助分析涂层防护性能具有可行性。     

可靠性强化试验技术在某型伺服作动器研制中的适用性探索

目的探索可靠性强化试验技术在典型机电液一体化产品伺服作动器研制过程中的适用性。方法以某型伺服作动器为研究对象,从故障激发的角度对可靠性强化试验技术的应用进行可行性分析,在响应调查和应力分析的基础上,结合产品的工作特点设计适用于该类伺服作动器的可靠性强化试验方案,包含低温步进应力试验、高温步进应力试验、快速温度循环试验10个循环、振动步进应力试验(包含气锤式三轴向六自由度超高斯随机振动方式及电磁振动台随机振动方式)及综合环境应力试验5个循环,并依此进行试验。结果在快速温度循环试验及综合环境应力试验过程中,均有效地激发出了产品的漏油故障,与相似产品外场暴露的漏油故障模式相吻合。结论可靠性强化试验技术可有效地应用于典型机电液一体化产品伺服作动器的研制过程,设计的可靠性强化试验方案可有效地激发外场出现频率较高的故障,可作为该类产品研制的试验手段之一。     

典型铅锌矿化区不同土地利用类型土壤重金属污染特征与评价

选取云南者海典型铅锌矿区周边冶炼区（A）、粮食主产区（B）、保护区（C）三个区域土壤为研究对象,分析三个区域内林地（LD）和耕地（GD）土壤pH、总碳（TC）、总氮（TN）、总磷（TP）和5种重金属（Hg、Cd、Pb、Zn、Cu）含量,利用典范对应分析（CCA）研究不同土地利用类型下它们之间的关系,基于系统熵值与重金属生物毒性改进灰色聚类评价法对研究区重金属污染程度进行评价。结果表明,A、B、C三区土壤的5种重金属均超过云南省土壤背景值,且含量A区 > B区 > C区,所有土壤样品Hg、Cd、Pb、Zn、Cu平均含量分别为7.24、1.53、1 794、2 892、210 mg/kg;LD土壤重金属含量普遍高于GD。研究区土壤pH总体呈弱酸性,但A区土壤受矿业活动影响呈弱碱性。TC、TN含量和C/N值均表现出LD大于GD,但TP含量表现为GD显著大于LD （P<0.05）。CCA分析表明LD和GD土壤pH与Cd和Cu呈负相关,与Zn和Pb呈正相关,且pH对重金属含量的影响最大;TC、TP与重金属Cd和Cu在LD土壤中呈正相关,在GD土壤中呈负相关。改进灰色聚类评价结果表明重金属污染程度均表现为LD大于GD;A区污染最严重且均呈重度污染,B区次之,C区污染程度最轻。经比较本文改进的灰色聚类评价法在准确性和灵敏度方面优于传统方法。     

Monitoring Air Quality in Mountains: Designing an Effective Network

A quantitatively robust yet parsimonious air-quality monitoring network in mountainous regions requires special attention to relevant spatial and temporal scales of measurement and inference. The design of monitoring networks should focus on the objectives required by public agencies, namely: 1) determine if some threshold has been exceeded (e.g., for regulatory purposes), and 2) identify spatial patterns and temporal trends (e.g., to protect natural resources). A short-term, multi-scale assessment to quantify spatial variability in air quality is a valuable asset in designing a network, in conjunction with an evaluation of existing data and simulation-model output. A recent assessment in Washington state (USA) quantified spatial variability in tropospheric ozone distribution ranging from a single watershed to the western third of the state. Spatial and temporal coherence in ozone exposure modified by predictable elevational relationships ( 1.3 ppbv ozone per 100 m elevation gain) extends from urban areas to the crest of the Cascade Range. This suggests that a sparse network of permanent analyzers is sufficient at all spatial scales, with the option of periodic intensive measurements to validate network design. It is imperative that agencies cooperate in the design of monitoring networks in mountainous regions to optimize data collection and financial efficiencies.     

Economic development and environmental protection: an ecological economics perspective

This paper argues on both theoretical and empirical grounds that, beyond a certain point, there is an unavoidable conflictbetween economic development (generally taken to mean 'materialeconomic growth') and environmental protection. Think for a moment of natural forests, grasslands, marine estuaries, salt marshes, and coral reefs; and of arable soils, aquifers, mineraldeposits, petroleum, and coal. These are all forms of 'natural capital' that represent highly-ordered self-producing ecosystemsor rich accumulations of energy/matter with high use potential (low entropy). Now contemplate despoiled landscapes, eroding farmlands, depleted fisheries, anthropogenic greenhouse gases,acid rain, poisonous mine tailings and toxic synthetic compounds.These all represent disordered systems or degraded forms of energy and matter with little use potential (high entropy). The main thing connecting these two states is human economic activity. Ecological economics interprets the environment-economyrelationship in terms of the second law of thermodynamics. The second law sees economic activity as a dissipative process. Fromthis perspective, the production of economic goods andservices invariably requires the consumption of available energy and matter. To grow and develop, the economynecessarily 'feeds' on sources of high-quality energy/matter first produced by nature. This tends to disorder and homogenizethe ecosphere, The ascendance of humankind has consistently been accompanied by an accelerating rate of ecological degradation, particularly biodiversity loss, the simplificationof natural systems and pollution. In short, contemporary political rhetoric to the contrary, the prevailing growth-oriented global development paradigm is fundamentally incompatible with long-term ecological and social sustainability. Unsustainability is not a technical nor economic problem as usually conceived, but rather a state of systemic incompatibilitybetween a economy that is a fully-contained, growing, dependent sub-system of a non-growing ecosphere. Potential solutions fly inthe face of contemporary development trends and cultural values.     

Risk-Based Prioritization of Air Pollution Monitoring Using Fuzzy Synthetic Evaluation Technique

Air pollution monitoring programs aim to monitor pollutants and their probable adverse effects at various locations over concerned area. Either sensitivity of receptors/location or concentration of pollutants is used for prioritizing the monitoring locations. The exposure-based approach prioritizes the monitoring locations based on population density and/or location sensitivity. The hazard-based approach prioritizes the monitoring locations using intensity (concentrations) of air pollutants at various locations. Exposure and hazard-based approaches focus on frequency (probability of occurrence) and potential hazard (consequence of damage), respectively. Adverse effects should be measured only if receptors are exposed to these air pollutants. The existing methods of monitoring location prioritization do not consider both factors (hazard and exposure) at a time. Towards this, a risk-based approach has been proposed which combines both factors: exposure frequency (probability of occurrence/exposure) and potential hazard (consequence).This paper discusses the use of fuzzy synthetic evaluation technique in risk computation and prioritization of air pollution monitoring locations. To demonstrate the application, common air pollutants like CO, NO_x, PM₁₀ and SO_x are used as hazard parameters. Fuzzy evaluation matrices for hazard parameters are established for different locations in the area. Similarly, fuzzy evaluation matrices for exposure parameters: population density, location and population sensitivity are also developed. Subsequently, fuzzy risk is determined at these locations using fuzzy compositional rules. Finally, these locations are prioritized based on defuzzified risk (crisp value of risk, defined as risk score) and the five most important monitoring locations are identified (out of 35 potential locations). These locations differ from the existing monitoring locations.     

A modular approach to Integrated Assessment modeling

In this paper, we present a new approach to model coupling that probably forms the methodological basis of a new generation of Integrated Assessment models. This approach respects the knowledge and expertise that is embodied in existing models and encourages their gradual evolution. Modularity is the guiding principle. Our approach is distinguished by the way modules are coupled which is based on an interplay of a job control module, a numerical coupling module, and a couple of stand-alone functional modules. The numerical coupling module - the core component - serves to treat the feedbacks between the functional modules. A first implemented example that couples an economic and a climate module by means of a two-phase meta-optimization is presented here. The algorithm and mathematical structure behind are discussed as well as important features such as convergence behavior and reliability.