大气中痕量有机胺测量方法的研究进展

作为大气中最重要的含氮有机化合物,有机胺易与硫酸、硝酸气体生成胺盐,促进新颗粒的形成,同时也可与臭氧、OH自由基、NO₃自由基发生氧化反应,是二次气溶胶的前体物.综述了国内外关于大气有机胺检测技术的研究进展,对常规的离线检测技术和在线质谱技术进行了介绍和对比,重点介绍了质谱法工作原理以及测定大气有机胺的优越性,并对其未来发展进行了展望.     

Impact assessment of the "Grain for Green Project" and discussion on the development models in the mountain-gorge regions

To restore China’s degraded ecological environment, the government has launched an environmental restoration project named the “Grain for Green Project” (GGP) in 1999. From 1999 to 2010, the government will spend 40 billion dollars to convert 147 million ha of croplands and 173 million ha of wastelands into forestlands and grasslands in 25 provinces, municipalities and autonomous regions. A primary goal is to replace cropping and livestock grazing in fragile areas with trees and grass. Given the tremendous scale and great number of participants in the project, the attitudes of the affected farmers and the future development in the area where GGP is implemented have a direct influence on the success of the project. To gain a clear idea about the farmers’ attitudes towards the project and put forward the development models for the forestlands converted from croplands, two case sites in the mountain-gorge region in Nujiang River are selected as the study areas, and the methods of field survey and semi-structured interview are adopted to make interviews with more than 100 households in 2002 and 2003 in order to quantify the farmers’ opinions about the GGP and how it has affected their livelihood, socio-cultural and industrial structures, etc. The results are as follows: 1) the project has a certain influence on the farmers with better economic basis and exerts greater influence on the farmers living in the low-elevation regions than on those living in the regions with middle-high elevation; 2) the production models of the local farmers has changed from cultivation and animal husbandry to forestry and sidelines due to the project and the income structure has changed from animal husbandry as main income source to state subsidy and sideline as main income sources; 3) the reduction in the grain income and decrease in the quantity of livestock because of the project have led to the diminution in the total income of the farmers; 4) the project has resulted in changes in the lifestyles and architecture styles of the local farmers, and the traditional “huotang” culture has gone away after the implementation of the project; 5) energy utilization has changed from firewood to methane and electricity in the wake of the implementation of the project. The above-mentioned study results have indicated that the GGP has truly exerted influence on the livelihood and production of the local farmers. Therefore, it is very necessary to make a research into the development models in the forestlands converted from croplands to resolve the problems of the farmers’ livelihood and production. The study results will provide some references for the sustainable development of the mountain-gorge regions.     

The challenges of integrating explainable artificial intelligence into GeoAI

Although explainable artificial intelligence (XAI) promises considerable progress in glassboxing deep learning models, there are challenges in applying XAI to geospatial artificial intelligence (GeoAI), specifically geospatial deep neural networks (DNNs). We summarize these as three major challenges, related generally to XAI computation, to GeoAI and geographic data handling, and to geosocial issues. XAI computation includes the difficulty of selecting reference data/models and the shortcomings of attributing explanatory power to gradients, as well as the difficulty in accommodating geographic scale, geovisualization, and underlying geographic data structures. Geosocial challenges encompass the limitations of knowledge scope—semantics and ontologies—in the explanation of GeoAI as well as the lack of integrating non-technical aspects in XAI, including processes that are not amenable to XAI. We illustrate these issues with a land use classification case study.     

鄂尔多斯盆地子北地区长6段油藏成藏条件及主控因素

分析了鄂尔多斯盆地子北地区延长组长6段油层构造特征、沉积相分布及砂体展布特征,从烃源岩、储层、盖层等方面对长6段油藏成藏条件进行了探讨,并就油藏类型、主控因素及成藏期次进行了讨论。结果表明:子北地区长6段油藏具有较好的生、储、盖配置关系,主要受沉积微相及储层物性控制;长6段油气主要储存在长61、62、63段河道砂体内,油藏类型主要为岩性圈闭;长6段油藏主控因素有主分流河道、储层物性及其非均质性、原油分布;长6段油层中,油气包裹体均一温度分布呈双峰状,主要在100℃~110℃和130℃~140℃;利用热演化史与流体包裹体均一温度法对油气成藏期次进行判断,长7段烃源岩生成的油气在早白垩世运移并大量聚集至长6段油层组,形成长6段油藏。     

移植操作胁迫对天鹅湖大叶藻存活、生长及光合色素含量的影响

2009年4月利用植株枚订移植法在山东荣成天鹅湖海域开展大叶藻植株移植,于5~10月监测移植大叶藻植株的存活率,并逐月采集自然和移植大叶藻植株,比较了植株生长、叶绿素含量和类胡萝卜素含量的变化,分析了移植操作胁迫对大叶藻存活、生长、叶绿素含量和类胡萝卜素含量的影响。结果显示,移植后1~2个月,移植植株的平均成活率较高,至移植后4个月,平均成活率降至57.8%,之后保持稳定。移植后6个月内,叶长移植植株均极显著低于自然植株;根长和茎节长在移植后1个月时移植植株显著低于自然植株,移植2个月后与自然植株无明显差异,甚至显著高于自然植株;叶绿素含量和类胡萝卜素含量在移植后1个月时移植植株显著低于自然植株,移植2个月后则与天然植株无明显不同,甚至显著高于自然植株,但10月份移植植株的叶绿素含量明显下降。结果表明,移植操作对大叶藻植株的地上部分产生了严重的胁迫作用和较长的胁迫时间,而移植植株的地下部分及叶片叶绿素和类胡萝卜素在经过短期胁迫后,能够通过自身的补偿机制分别实现快速生长和显著增加,从而利于植株的扎根、固着和提高植株的光合作用能力。     

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广西沿海超高层建筑进行气象灾害风险评估必要性

通过列举国内外超高层建筑遭受气象灾害的案例,结合广西气象灾害风险区划资料,分析大风、台风、龙卷风、暴雨、雷电（雷击）、强降温等灾害与沿海超高层建筑的关系,以及可能造成的影响和潜在的风险,论述了超高层建筑进行气象灾害风险评估可实现最大安全与最小投资的统一.以期为广西沿海开展“超高层建筑气象灾害风险评估”工作提供理由和依据.     

基于卷积神经网络的地铁保护区风险源识别北大核心CSCD

城市轨道交通沿线的风险源识别是防止违规作业导致的安全事故的重要手段。为解决传统识别方法效率低、漏检率高、成本大等问题,本文基于无人机地铁保护区巡检系统,采用卷积神经网络对无人机采集的影像数据进行风险源识别。首先介绍无人机影像获取的流程,并在原始影像数据的基础上,通过数据增强的方式制作多角度、多尺度的风险源数据集;然后使用卷积神经网络建立风险源识别模型,对无人机采集影像中的风险源进行自动识别和定位。试验结果表明,多角度、多尺度风险源数据集的建立进一步提升了模型的识别准确率,且比传统方法具有效率高、成本低等优点。     

青海德尔尼铜(锌钴)矿床硫化物Cu同位素组成及矿床成因探讨

青海德尔尼铜(锌钴)矿床产出在北西或北西西向超镁铁质岩带中,对其矿床成因长期以来一直存在争议。文中对德尔尼矿床主矿体不同类型硫化物矿石的Cu同位素组成进行了分析,通过与现代海底正在形成的赋存在超镁铁质岩(蛇纹石化橄榄岩)中的块状硫化物矿床进行类比,从构造背景和矿床地质角度探讨了矿床成因,得出以下主要认识:(1)阿尼玛卿构造带可能存在大型拆离断层,超镁铁质岩体和硫化物矿体的产出均与北西向发育的长期活动拆离断层有关;(2)德尔尼矿床属古代海相火山成因块状硫化物矿床,为赋存在超镁铁质岩体中的一个特殊类型(或称为"德尔尼型");(3)硫化物原生矿石Cu同位素组成均为负值,呈富轻Cu同位素特征,表明矿床经历了广泛的后期热液叠加过程。德尔尼矿床控矿构造、岩体特征和后期叠加成矿过程的深入研究不仅对矿床成因认识和找矿具有重要意义,而且为现代海底慢速-超慢速扩张洋中脊超镁铁质岩热液系统成矿研究提供了参考。