环境监测站INTRANET建设研究

研究探讨了环境监测站内部网络 (Intranet)建设方案、Web数据库开发应用方案、网站的规划方法、结构与内容 ,对其经济性、技术合理性、适用性作了阐述。     

餐饮源有机颗粒物排放特征

餐饮油烟是大气有机颗粒物的重要来源之一.本研究在深圳市内选择了西餐、茶餐厅、职工食堂和韩式料理这4种类型的餐馆,通过对这4类餐厅的外场采样,分析各类型餐厅油烟中有机颗粒物的化学组成,筛选了餐饮油烟污染源的有机特征组分.结果表明,各餐馆排放的PM_2.5中,有机物占60%以上.在所有定量的有机组分之中,脂肪酸含量最高,其次是二元羧酸和正构烷烃,而多环芳烃、甾醇和单糖等有机组分的含量较低.颗粒物的有机组成特征受到菜系的影响,西餐厅和韩式料理排放脂肪酸、正构烷烃和多环芳烃等有机物含量较高,但却排放了低含量的甾醇和单糖,茶餐厅和职工食堂则相反.餐饮源颗粒物中Fla/(Fla+Pyr)和LG/(Gal+Man)的比值受菜系影响较小,也区别于其他污染源的特征比值,可以作为餐饮源潜在的示踪物.餐饮源为深圳市大气颗粒物贡献了大量的脂肪酸和二元羧酸.     

夜间建筑施工噪声扰民监测方法探讨

以一家夜间施工工地为例 ,通过对现有夜间建筑施工噪声测量方法及国家和深圳经济特区有关噪声污染定义的分析 ,阐述了夜间施工工地噪声扰民监测方法     

大气气溶胶酸度和酸化缓冲能力研究

为了掌握大气气溶胶与酸性降水的关系 ,分析和研究了中国北方和南方不同观测点可吸入颗粒物 (PM10 )的酸度 ,并利用微量酸碱滴定的方法测定了其酸化缓冲能力。结果表明大气气溶胶具有一定的酸度 ,同时对酸化的缓冲能力非常低 ,甚至可以促进降水的酸化 ,这种污染特征也是上述观测点发生酸性降水的重要原因之一。     

工业居民混合区降尘含量的灰色GM(1,1)预测

本文采有灰色理论中的预测方法,以９０—９４年度的降尘监测数据为基础,建立了邯郸市工业居民混合区降尘含量的ＧＭ（１,１）预测模型,其数学表达式为：＾Ｘ（１）（ｋ＋１）＝５６０２９ｅ００５６４１２ｋ－５３０８３,经三种方法对模型精度检验,由模式计算的预测值与历年的实测值的平均相对误差仅为－０００８％,关联度系数γ＝０９０５,后验差比值Ｃ＝００３,模型精度为一级,经与９５年度预测值与实测值对比验证,误差２７４％,说明本模型能真实地反映该区降尘的发展变化规律,预测数据可作为制定该区降尘防治规划的依据。     

Conservation resource allocation,small population resiliency,and the fallacy of conservation triage

Some conservation prioritization methods are based on the assumption that conservation needs overwhelm current resources and not all species can be conserved; therefore, a conservation triage scheme (i.e., when the system is overwhelmed, species should be divided into three groups based on likelihood of survival, and efforts should be focused on those species in the group with the best survival prospects and reduced or denied to those in the group with no survival prospects and to those in the group not needing special efforts for their conservation) is necessary to guide resource allocation. We argue that this decision-making strategy is not appropriate because resources are not as limited as often assumed, and it is not evident that there are species that cannot be conserved. Small population size alone, for example, does not doom a species to extinction; plants, reptiles, birds, and mammals offer examples. Although resources dedicated to conserving all threatened species are insufficient at present, the world's economic resources are vast, and greater resources could be dedicated toward species conservation. The political framework for species conservation has improved, with initiatives such as the UN Sustainable Development Goals and other international agreements, funding mechanisms such as The Global Environment Facility, and the rise of many nongovernmental organizations with nimble, rapid-response small grants programs. For a prioritization system to allow no extinctions, zero extinctions must be an explicit goal of the system. Extinction is not inevitable, and should not be acceptable. A goal of no human-induced extinctions is imperative given the irreversibility of species loss.     

生态意识变迁的考察与草地畜牧业可持续发展--以内蒙古锡林郭勒退化草地为例

目前，内蒙古草地生态环境破坏严重。且总体上呈不断恶化的态势。这种状况的持续不仅严重影响和翻约着本地区经济和社会的总体发展。同时也威胁着包括北京在内的整个华北地区的生态安全。其内在的深层次的根源就在于包括生态意识在内的人们的文化价值观发生了“扭曲”。本文针对锡林郭勒退化草地现状与历史的分析．揭示了其中的文化特征与哲学内涵．并且指出生态意识的确立和生态文化的形成对于保护草地、建设草地的现实意义。     

CDS—Ⅱ系列除尘脱硫一体化装置

根据我国的国情开发、研制了CDS-Ⅱ系列除尘、脱硫一体化装置，论述了该装置研制的原则，介绍了该装置的技术指标及特点，并用实例加以说明。     

连接管件的先进塑性成形技术试验研究

介绍了 3种先进的连接管件成形技术 ,即小弯曲半径管内压推弯成形技术、球形管接头的胀形成形技术和管件的内径滚压成形技术 ,对其基本成形过程进行了描述 ,并通过铝合金、不锈钢和钛合金管件的成形试验获得了主要工艺参数对成形的影响规律 ,结果表明采用这些方法成形所需的连接管件是非常有效的     

Influencing factors and prediction of ambient Peroxyacetyl nitrate concentration in Beijing, China

Peroxyacyl nitrates (PANs) are important secondary pollutants in ground-level atmosphere. Accurate prediction of atmospheric pollutant concentrations is crucial to guide effective precautions for before and during specific pollution events. In this study, four models based on the back-propagation (BP) artificial neural network (ANN) and multiple linear regression (MLR) methods were used to predict the hourly average PAN concentrations at Peking University, Beijing, in 2014. The model inputs were atmospheric pollutant data and meteorological parameters. Model 3 using a BP-ANN based on the original variables achieved the best prediction results among the four models, with a correlation coefficient (R) of 0.7089, mean bias error of ? 0.0043 ppb, mean absolute error of 0.4836?ppb, root mean squared error of 0.5320?ppb, and Willmott's index of agreement of 0.8214. Based on a comparison of the performance indices of the MLR and BP-ANN models, we concluded that the BP-ANN model was able to capture the highly non-linear relationships between PAN concentration and the conventional atmospheric pollutant and meteorological parameters, providing more accurate results than the traditional MLR models did, with a markedly higher goodness of R. The selected meteorological and atmospheric pollutant parameters described a sufficient amount of PAN variation, and thus provided satisfactory prediction results. More specifically, the BP-ANN model performed very well for capturing the variation pattern when PAN concentrations were low. The findings of this study address some of the existing knowledge gaps in this research field and provide a theoretical basis for future regional air pollution control.