大型气候环境实验室上部运输系统的方案设计

目的设计出满足气候环境实验室的上部运输系统。方法根据国内外实验室上部运输系统的设计经验,结合实际使用情况,设计出满足实验室使用条件的上部运输系统方案。结果设计出的上部运输系统直接参与各环境试验的运输、吊装工作,满足气候实验室的环境条件,且具有安全可靠、便于操作维护等特点。结论设计出的上部运输系统满足气候环境实验室的使用要求。     

基于支持向量回归模型的水稻田甲烷排放通量预测研究

利用静态箱和气相色谱仪法获取水稻田甲烷排放通量数据,选取大气温度、土壤5 cm深温度、土壤pH、土壤Eh、土壤含水量和地表生物量作为影响因子.应用建立在结构风险最小化优化上的支持向量回归(ε-SVR)模型,采用留一法交叉检核网格搜索法(LOOCV)优化ε-SVR预测模型的参数,采用k折交叉检验的方法依据平均相对误差(MRE)和均方根误差(RMSE)对模型的精度进行验证,并与BP人工神经网络(BP-ANN)模型比较,评价ε-SVR预测模型的准确性.结果表明,通过LOOCV选择最优的惩罚因子C和损失系数ε,并由此构建的ε-SVR预测模型预测值和实测值具有很好的一致性,通过11折交叉验证后,测试样本的平均MRE为44%,平均RMSE为16.21 mg·(m2·h)-1.通过与BP-ANN模型比较,预测值和实际值相关系数达0.863,各项指标均优于BP-ANN预测模型,说明ε-SVR模型能够适用于水稻田甲烷排放通量的预测.     

构建环境应急决策支持系统的思考

环境应急决策支持系统通过数据库子系统、模型库子系统、方法库子系统、对话管理子系统等获取各种决策信息,通过大气环境预测、水环境预测、环境风险评价、三维污染仿真等模型获得数据支持信息。实现环境应急决策支持、应急救援方案、健康评价与灾后评估、信息在线发布等应用功能,为有关部门进行环境应急决策、采取污染控制措施、减轻污染危害提供方便、快捷、有效的技术支持。     

基于多目标空间分析的危险废物决策支持模型研究

我国日益增长的危险废物对于环境安全和人体健康都构成极大威胁,如何高效、科学的对危险废物从产生到最终处置的全过程进行管理和决策是我国危险废物管理工作面临的重要问题。区域危险废物的管理和环境风险控制是一个涉及到废物特性、自然环境和社会经济等诸多因素的综合决策过程。文章通过综合考虑危险废物处理处置过程中的环境影响因素、经济因素和环境风险因素,结合空间分析技术和多目标决策的方法,设计了一个危险废物多目标空间决策支持模型,并以广州为例进行了模拟应用。危险废物管理的决策者根据不同的侧重点,通过本模型在备选废物处理处置中心中确定建设地点,同时能够使用本模型选择危险废物的最佳运输路径。本模型为危险废物管理和决策支持提供了一种直观、科学和实用的支持,具有一定的理论和现实意义。     

Effects of support acidity on the reaction mechanisms of selective catalytic reduction of NO by CH4 in excess oxygen

The reaction mechanisms of selective catalytic reduction (SCR) of nitric oxide (NO) by methane (CH₄) over solid superacid-based catalysts were proposed and testified by DRIFTS studies on transient reaction as well as by kinetic models. Catalysts derived from different supports would lead to different reaction pathways, and the acidity of solid superacid played an important role in determining the reaction mechanisms and the catalytic activities. Higher ratios of Br?nsted acid sites to Lewis acid sites would lead to stronger oxidation of methane and then could facilitate the step of methane activation. Strong Br?nsted acid sites would not necessarily lead to better catalytic performance, however, since the active surface NO_y species and the corresponding reaction routes were determined by the overall acidity strength of the support. The reaction routes where NO₂ moiety was engaged as an important intermediate involved moderate oxidation of methane, the rate of which could determine the overall activity. The reaction involving NO moiety was likely to be determined by the step of reduction of NO. Therefore, to enhance the SCR activity of solid superacid catalysts, reactions between appropriate couples of active NO_y species and activated hydrocarbon intermediates should be realized by modification of the support acidity.     

数据挖掘在应急救援决策支持中的应用研究

本文分析了数据挖掘技术在应急预测与报警、动态安全风险分析、事故动态演化过程分析和应急综合评价中的选择标准,并以火电厂锅炉过热器为例,阐述了数据挖掘技术在应急救援业务中的具体应用,以及基于数据挖掘的应急救援与辅助决策支持系统的功能和体系结构.     

中国土地利用碳排放变化及协调分区

土地利用变化所产生的碳排放已成为地区碳排放的主要来源之一,为了探究其变化以全国30个省市为研究对象,基于2001～2019年MODIS的MCD12Q-LUCC数据,通过碳排放系数法,聚类与异常值分析法,从碳排放经济贡献系数、碳生态承载系数及二者的耦合协调关系等角度探讨了近19年间全国各省土地利用碳排放的空间特征并进行了分区研究.结果表明：(1) 2000～2019年全国土地利用碳排放量增长显著,但在2011年后碳排放量增长率变得平缓,而碳汇量的增长则相对缓慢,二者间的差距仍较大.(2)聚类与异常值分析显示研究期内全国各省市土地利用碳排放高值集聚中心由广东、江苏等省份转移到河北、山西、内蒙古等省份且集聚状态越来越明显.(3)全国各省市碳排放经济贡献系数呈现南高北低的空间特征,生态承载系数则呈现出由西高东低逐渐发展为中高东低,北部次之的特征,两者的耦合协调度呈现出下降的趋势.(4)本文基于碳排放经济贡献和碳生态承载,将各省划分为低碳保持区、经济发展区、碳汇发展区和综合优化区这4类,并提出各自的发展建议,争取实现碳中和与低碳可持续发展.     

基于关联向量机回归的水质预测模型

提出了一种基于关联向量机回归的水质时间序列预测模型,并以该模型对氢离子浓度指数(p H值)、溶解氧(DO)、高锰酸盐指数(CODMn)和氨氮(NH3-N)4种重要水质指标进行预测.首先采用国家环保部发布的四川攀枝花龙洞水质自动监测数据进行实验,对该模型的有效性进行了验证;然后将关联向量机回归预测模型与支持向量机回归预测模型进行比较.为了比较不同核函数的预测效果,实验中预测模型的核函数分别采用了线性函数和高斯函数.实验结果表明,关联向量机回归模型的预测效果不亚于支持向量机回归模型;且在给出预测值时,还能同时给出预测结果的可信程度.     

A multi-level characterization method for the assessment of urban ecological risks

Urban ecological risk characterization is the final step in risk assessment and an important foundation upon which risk managers build risk aversion, risk control, and emergency handling strategies. In this study, we reviewed present risk characterization methods and proposed a multi-level characterization method for the assessment of urban ecological risks. The new characterization method consists of four elements: urban ecological risk sources, risk source probabilities, assessment endpoint indicators, and assessment endpoint indicator probabilities. Using this method, results of risk assessments can be organized into different levels of detail to meet different risk management goals.     

Software for prioritizing conservation actions based on probabilistic information

Marxan is the most common decision-support tool used to inform the design of protected-area systems. The original version of Marxan does not consider risk and uncertainty associated with threatening processes affecting protected areas, including uncertainty about the location and condition of species’ populations and habitats now and in the future. We described and examined the functionality of a modified version of Marxan, Marxan with Probability. This software explicitly considers 4 types of uncertainty: probability that a feature exists in a particular place (estimated based on species distribution models or spatially explicit population models); probability that features in a site will be lost in the future due to a threatening process, such as climate change, natural catastrophes, and uncontrolled human interventions; probability that a feature will exist in the future due to natural successional processes, such as a fire or flood; and probability the feature exists but has been degraded by threatening processes, such as overfishing or pollution, and thus cannot contribute to conservation goals. We summarized the results of 5 studies that illustrate how each type of uncertainty can be used to inform protected area design. If there were uncertainty in species or habitat distribution, users could maximize the chance that these features were represented by including uncertainty using Marxan with Probability. Similarly, if threatening processes were considered, users minimized the chance that species or habitats were lost or degraded by using Marxan with Probability. Marxan with Probability opens up substantial new avenues for systematic conservation planning research and application by agencies.