基于多源遥感信息的人为热排放量空间化——以浙江省为例

基于自上而下能源清单法,主要考虑工业、交通、建筑和人体新陈代谢这4个热源对人为热的贡献,估算了2010年浙江省68个县市的人为热排放总量.使用DMSP/OLS遥感夜间灯光数据以及阈值法提取出人为热排放的主要区域,并有效减少夜灯像元溢出效应的影响.利用夜间灯光数据和增强型植被指数(EVI)构建人居指数,基于各市县人为热排放总量与其行政区范围内人居指数累计值之间很强的相关关系建立人为热排放量空间化模型,获得了250m分辨率下浙江省2010年城市人为热通量的空间分布.结果显示浙江省各县市的平均人为热排放通量为5.5W/m²,城市高值区一般介于10~40W/m².栅格化的人为热数据可以为城市气候环境的数值模拟研究提供基础数据支持.     

土壤有机碳储量估算的影响因素和不确定性

土壤作为陆地生态系统最大的碳库和碳循环过程的关键环节,其源、汇的变化直接影响全球碳平衡,因此,土壤有机碳储量估算成为生态领域的重要研究内容之一。通过比较不同研究者在不同研究尺度上报道的有机碳储量的研究结果,发现这些研究结果较不一致。分析认为导致土壤有机碳储量评估结果存在较大差异的原因,主要是来自于采样过程中人类干扰以及气候变化等环境要素的波动,特别是研究者所采取的不同估算方法和背景资料。从环境要素（外因）和估算方法（内因）两个角度出发,提出了土壤有机碳储量的研究意义,阐述了造成土壤有机碳储量估算的不确定性和目前研究中存在的问题,并在此基础上,对其未来研究方向和重点进行了展望。     

施工企业内社会资本、情绪智力与安全绩效关系研究

依据资本观、能力观等相关理论,构建了以情绪智力为中介变量的施工企业内社会资本与安全绩效关系的理论模型,并以156家施工企业为调查对象而获取的数据进行多元回归分析。研究结果表明:员工情绪智力在施工企业内社会资本的结构维度、关系维度与安全绩效之间起到完全中介作用,在认知维度与安全绩效之间起到部分中介作用。因此,施工企业应该重视企业内社会资本的积累,同时加强员工情绪智力的提升,提高安全绩效。     

国家历史文化名城地区农业与水文地质的关系

国家历史文化名城地区记录了华夏农耕文明更多的生活经验,论文以这些城市地区为研究对象,通过在全国尺度选取典型群体110 个国家历史文化名城地区为样本,并定义农业水文地质适宜度指标,对各类水文地质与农业活动的空间关系进行了量化。从研究结果来看：各富水程度的松散岩类孔隙含水岩组是农业适宜性较强的水文地质类型;碳酸盐岩类含水岩组的农业适宜性也较强;而岩浆岩类含水岩组以及变质岩类含水岩组等则是农业适宜性较弱的水文地质类型,其中松散岩类孔隙含水岩组的农业水文地质适宜度是岩浆岩类含水岩组以及变质岩类含水岩组的2~3 倍。     

基于用地规划的大型污染场地健康风险评估

以某焦化类大型污染场地苯污染土壤为例,针对S1(单一用地)、S2(多种用地)、S3(考虑建筑设计)3种暴露情景,分析不同情景下场地土壤中苯污染的暴露途径并进行健康风险评估. S1情景下的苯致癌风险为9.2×10-5. 在S2情景下,规划的5个分区中仅E区(居住用地)苯的致癌风险(4.3×10-4)高于可接受水平(1.0×10-6), 考虑到各功能区累积致癌风险,则E区高污染可导致其他4个功能区〔A区(商业用地)、B区(城市绿地)、C区(居住用地)、D区(商业用地)〕的累积致癌风险(分别为6.5×10-6、2.2×10-6、7.3×10-6、2.2×10-5)均高于可接受水平,表明单一用地会低估污染物聚集区的风险. 在S3情景下,A、B、C区土壤中苯的致癌风险(分别为1.2×10-7、2.7×10-7、2.5×10-7)均未超过可接受致癌风险水平;D区由于污染土壤被完全清除,不存在健康风险;E区开发后由剩余土壤产生的苯致癌风险为2.7×10-5,D区受E区影响产生的累积致癌风险(1.5×10-6)高于可接受水平. 进一步分析表明,场地的用地规划与建筑设计等因素将影响风险评估中关键参数(包括污染源浓度、水文地质参数、暴露参数、受体参数等)的取值,从而影响风险评估结果;此外,各功能区之间的风险影响也不容忽视. 对于大型污染场地,结合用地规划进行暴露情景分析与风险评估更为科学合理.      

磷酸三(1,3-二氯-2-丙基)酯对L-02肝细胞氧化应激及凋亡损伤机制

在各类环境介质及生物体甚至人体中都检测到有机磷阻燃剂磷酸三(1,3-二氯-2-丙基)酯(tris(1,3-dichloro-2-propyl)phosphate,TDCPP)的存在,为探究TDCPP对人体健康的毒性作用,选取人体正常肝细胞L-02细胞作为模型,考察在体外暴露条件下TDCPP对L-02细胞的细胞存活率、凋亡、氧化应激以及p53通路相关基因方面的影响。MTT结果显示,24 h、48 h、72h的半数致死浓度(LC50)分别为:116.56μmol·L~(-1)、81.89μmol·L~(-1)、65.11μmol·L~(-1)。TDCPP暴露24 h条件下,随着TDCPP暴露浓度的增加,细胞的凋亡率和活性氧(reactive oxygen species,ROS)水平也逐渐增加,100μmol·L~(-1)浓度条件下凋亡高达25.58%±1.61%,ROS水平是对照组的2.07±0.07倍。实时荧光定量PCR法检测线粒体凋亡通路相关基因的表达情况,在TDCPP刺激下,Bax、caspase-3、caspase-9、p53和Apaf-1相对表达量增加,Bcl-2相对表达量减少。蛋白免疫印迹法检测发现Bax/Bcl-2和caspase-3均随浓度增加而递增。本研究为综合评估TDCPP的生物和环境健康毒理效应提供了实验数据及理论支持。     

How to address data privacy concerns when using social media data in conservation science

Social media data are being increasingly used in conservation science to study human–nature interactions. User-generated content, such as images, video, text, and audio, and the associated metadata can be used to assess such interactions. A number of social media platforms provide free access to user-generated social media content. However, similar to any research involving people, scientific investigations based on social media data require compliance with highest standards of data privacy and data protection, even when data are publicly available. Should social media data be misused, the risks to individual users' privacy and well-being can be substantial. We investigated the legal basis for using social media data while ensuring data subjects’ rights through a case study based on the European Union's General Data Protection Regulation. The risks associated with using social media data in research include accidental and purposeful misidentification that has the potential to cause psychological or physical harm to an identified person. To collect, store, protect, share, and manage social media data in a way that prevents potential risks to users involved, one should minimize data, anonymize data, and follow strict data management procedure. Risk-based approaches, such as a data privacy impact assessment, can be used to identify and minimize privacy risks to social media users, to demonstrate accountability and to comply with data protection legislation. We recommend that conservation scientists carefully consider our recommendations in devising their research objectives so as to facilitate responsible use of social media data in conservation science research, for example, in conservation culturomics and investigations of illegal wildlife trade online.     

Exploring human–nature interactions in national parks with social media photographs and computer vision

Understanding the activities and preferences of visitors is crucial for managing protected areas and planning conservation strategies. Conservation culturomics promotes the use of user-generated online content in conservation science. Geotagged social media content is a unique source of in situ information on human presence and activities in nature. Photographs posted on social media platforms are a promising source of information, but analyzing large volumes of photographs manually remains laborious. We examined the application of state-of-the-art computer-vision methods to studying human–nature interactions. We used semantic clustering, scene classification, and object detection to automatically analyze photographs taken in Finnish national parks by domestic and international visitors. Our results showed that human–nature interactions can be extracted from user-generated photographs with computer vision. The different methods complemented each other by revealing broad visual themes related to level of the data set, landscape photogeneity, and human activities. Geotagged photographs revealed distinct regional profiles for national parks (e.g., preferences in landscapes and activities), which are potentially useful in park management. Photographic content differed between domestic and international visitors, which indicates differences in activities and preferences. Information extracted automatically from photographs can help identify preferences among diverse visitor groups, which can be used to create profiles of national parks for conservation marketing and to support conservation strategies that rely on public acceptance. The application of computer-vision methods to automatic content analysis of photographs should be explored further in conservation culturomics, particularly in combination with rich metadata available on social media platforms.     

Digital data sources and methods for conservation culturomics

Ongoing loss of biological diversity is primarily the result of unsustainable human behavior. Thus, the long-term success of biodiversity conservation depends on a thorough understanding of human–nature interactions. Such interactions are ubiquitous but vary greatly in time and space and are difficult to monitor efficiently at large spatial scales. However, the Information Age also provides new opportunities to better understand human–nature interactions because many aspects of daily life are recorded in a variety of digital formats. The emerging field of conservation culturomics aims to take advantage of digital data sources and methods to study human–nature interactions and thus to provide new tools for studying conservation at relevant temporal and spatial scales. Nevertheless, technical challenges associated with the identification, access, and analysis of relevant data hamper the wider adoption of culturomics methods. To help overcome these barriers, we propose a conservation culturomics research framework that addresses data acquisition, analysis, and inherent biases. The main sources of culturomic data include web pages, social media, and other digital platforms from which metrics of content and engagement can be obtained. Obtaining raw data from these platforms is usually desirable but requires careful consideration of how to access, store, and prepare the data for analysis. Methods for data analysis include network approaches to explore connections between topics, time-series analysis for temporal data, and spatial modeling to highlight spatial patterns. Outstanding challenges associated with culturomics research include issues of interdisciplinarity, ethics, data biases, and validation. The practical guidance we offer will help conservation researchers and practitioners identify and obtain the necessary data and carry out appropriate analyses for their specific questions, thus facilitating the wider adoption of culturomics approaches for conservation applications.     

冬季颗粒物暴露对体育教师自觉症状及肺功能健康影响的研究

拟通过对比冬季雾霾天气颗粒物对户外体育教师和室内教师的自觉症状及肺功能的影响,为高污染天气下室外体育教师的个人防护提供理论参考,为完善颗粒物的人体健康暴露风险评估提供方法支持和理论依据。通过问卷调查和个体颗粒物暴露的研究方法,对80名室外体育教师和80名室内教师的个体呼吸机能状况、自觉症状评价、用力呼气肺活量(FVC)、第1秒用力呼气容量(FEV_1)、FEV_1/FVC、峰流速值(PEF)、肺活量(VC)和每分钟最大通气量(MVV)进行调查和测定,比较户外教师和室内教师、不同教龄和日工作时长以及吸烟史对颗粒物暴露的易感性及在呼吸系统症状、肺通气功能上的差异。研究结果表明,同样的工作时间内,室内和室外教师在个人的颗粒物暴露浓度和剂量上呈现出差异显著性;教龄、日工作时间和吸烟史与个人的自觉症状评价和肺功能指标之间存在着显著的相关关系,具有显著性差异(P 0.05或P 0.01)。以上研究表明,冬季雾霾天气下教师的健康状况受到一定的负面影响,户外体育教师肺功能和自我症状评价状况劣于室内教师;雾霾天气下教龄和日工作时长、肺功能和吸烟史与自我症状评价状况呈负相关。