科学大数据开放共享机制研究及其对环境信息共享的启示

科学大数据得以充分利用和增值的前提是开放共享,而影响数据开放共享的关键问题是共享机制.本文首先分析了科学大数据的产生方式、数据类型、投资方式、管理主体和服务定位及其与共享程度的关系.进一步在分析国内外自上而下和自下而上科学数据共享通用机制与原则的基础上,结合国家地球系统科学数据共享平台、全球变化科学数据出版等实践,提出了数据汇交、数据出版、数据联盟和服务激励四种数据共享机制,并分析了每种机制中的关键问题及具体做法.最后,结合云计算、"互联网+"等新一代信息技术和思维,对环境保护大数据共享机制提出四点建议,即:国家统一投资建设的环境保护核心业务数据强制汇交机制,其他部委、机构环境保护相关数据联盟交换机制,企业、科学家个人数据出版等激励机制,以及社会公众数据的"众创机制".     

基于数据融合的风机风量值无线监测技术研究

为了解决主要通风机在测风量过程中在线实时监测等问题,建立了以无线传输技术为基础的三层传输系统框架,并将改进的数据融合算法引入到风量值数据处理当中,通过选取阙值区间利用二次曲线函数来消除阙值点处相互支持的模糊性,取得最优融合传感器组,并对实测数据进行抗干扰实验分析。实验结果表明,无线传输方式有利于风量数据的在线实时监测;改进的数据融合算法能及时有效地消除传感器的测量偏差、提高风量数据的测量精确度。研究结果对煤矿主要通风机风量在线远程监测具一定的理论价值和实用意义。     

中国畜牧业全生命周期温室气体排放时空特征分析

运用生命周期评价方法,选取家畜胃肠道发酵、粪便管理系统、畜禽饲养环节耗能、饲料粮种植、饲料粮运输加工和畜禽产品屠宰加工6大环节,采用面板数据测算和分析1990~2011年中国及2011年国内各地区畜牧业温室气体排放特征.研究表明,22年间,中国畜牧业全生命周期及各个环节的CO2当量排放量均呈现上升趋势,尤其是畜禽饲养耗能、饲料粮种植、饲料粮运输加工和畜禽屠宰加工环节的增长更为显著,但历年饲料粮运输加工和畜禽屠宰加工环节占畜牧业全生命周期CO2当量排放总量的比重均低于1%和0.05%;家畜胃肠道发酵和粪便管理系统环节占畜牧业全生命周期CO2当量排放总量的比重呈下降趋势;22年间,反刍家畜的CO2当量排放量占55.25%,非反刍畜禽占44.75%.2011年,国内省域间内蒙古、辽宁和云南的畜牧业全生命周期CO2排放当量和排放强度均位居全国前10位;西部地区畜牧业全生命周期CO2当量排放量所占比重最大,并且西部地区的排放强度最高;农区畜牧业全生命周期CO2当量排放量占63.88%,牧区占14.07%,但牧区的排放强度最高,农区最低.     

A measure of sustainability of Brazilian agribusiness using directional distance functions and data envelopment analysis

The social and environmental impacts caused by the modernization of Brazilian agribusiness have evoked a growing interest in the search of balance between social-economics development and the adequate use of natural resources, driving the country to sustainable development. Therefore, the main aim of this article is to estimate a set of indicators of relative efficiency in the Brazilian agricultural sector, which satisfy the concept of Pareto optimality, potentiates simultaneously both economic, ecological dimensions and social functions. To reach this purpose, the method of directional distance functions and data envelopment analysis was applied. These indicators confirm, in different ways, the hypothesis that it is possible to perform consistent productive strategies with the maximization of social welfare, despite the apparent antagonism among these three dimensions. In addition, it is shown that efficient Brazilian states tend to combine the three dimensions in different ways. Hence, it can be concluded that several equilibrium taken sustainable can be achieved through different actions on poverty and environmental impact reduction without necessarily generating productive inefficiencies. This result can be considered of prominent importance for sustainable development in Brazil and can also serve as a reference in the definition of goals of the plan ‘Brazil without Misery’ and international commitments to reduce Greenhouse Gas – GHG – in Brazil, especially for the 17 inefficient Brazilian states.     

Renewable energy,non-renewable energy and sustainable development

The purpose of the present study is to analyse the effects of renewable energy and non-renewable energy on sustainable development. This study is pioneering in this respect because it analyses the effect of renewable energy on adjusted net savings, which is a good sustainable development variable. For this purpose, the data of 40 developed and 73 developing countries were included. According to the estimation results obtained in the study, renewable energy has a positive and statistically significant effect on sustainable development both in developed countries and in developing countries. The impact of renewable energy on sustainable development is greater than the impact of non-renewable energy. In this respect, as the renewable energy amount increases, the level of sustainable development increases. According to these results, the fact that countries use renewable energy more than non-renewable energy sources is extremely important in terms of making progress towards sustainability of development and the 2030 Sustainable Development Goals.     

基于多源数据的城市空间活力时空特征分析——以南京市河西、仙林新城为例

采用微信宜出行数据、传统规划数据,探索南京市河西和仙林新城的空间活力时空特征。结果发现:(1)在空间层面,河西呈"东高西低、北高南低"的集聚特征,仙林活力分布与高校区位高度匹配。(2)在时间层面,河西呈"降—升—降—升—降"的波动特征,仙林呈"降—升—平缓"的波动特征。(3)工作日的河西活力集中在居住区,休息日集中在商业区;仙林在工作日和休息日无差异,均分布在高校区及其周边的商业区。     

资源产业集聚对资源型城市经济增长的影响--基于夜间灯光数据的实证研究

在资源依赖背景下,发挥好资源产业集聚的正向作用,是资源型城市实现经济可持续增长的关键。基于2005—2017年山西省11个地级市面板数据,采用校正整合的夜间灯光数据度量城市经济增长,并运用系统广义矩估计法(SYS-GMM)检验了资源产业集聚对城市经济增长的影响。结果表明:资源产业集聚对资源型城市经济增长影响显著,呈“先上升,后下降”的倒“U”型关系,在资源产业集聚初期将推动城市经济增长,但过度集聚反而会抑制经济增长。     

我国环境规制强度测度及其对就业规模的影响——基于省际动态面板数据的实证分析

本文建立模型具体测算了我国30个省(区、市)自2003年至2016年的环境规制强度指标,发现全国环境规制强度整体呈上升趋势,其中东部省份强度最大,中部地区的环境规制强度低于东部而略高于西部地区。进一步构建动态面板计量模型进行实证分析,结果显示,环境规制对就业的影响具有明显的U形特征,即随着环境规制强度的提高,其对就业起着先抑制后促进的作用。而经济发展水平、人口规模、产业结构的优化升级以及平均工资水平的提高均能显著促进全样本的就业增长,但对外依存度对各样本而言都明显不利于就业规模的扩张。     

Automated conservation assessment of the orchid family with deep learning

International Union for Conservation of Nature (IUCN) Red List assessments are essential for prioritizing conservation needs but are resource intensive and therefore available only for a fraction of global species richness. Automated conservation assessments based on digitally available geographic occurrence records can be a rapid alternative, but it is unclear how reliable these assessments are. We conducted automated conservation assessments for 13,910 species (47.3% of the known species in the family) of the diverse and globally distributed orchid family (Orchidaceae), for which most species (13,049) were previously unassessed by IUCN. We used a novel method based on a deep neural network (IUC-NN). We identified 4,342 orchid species (31.2% of the evaluated species) as possibly threatened with extinction (equivalent to IUCN categories critically endangered [CR], endangered [EN], or vulnerable [VU]) and Madagascar, East Africa, Southeast Asia, and several oceanic islands as priority areas for orchid conservation. Orchidaceae provided a model with which to test the sensitivity of automated assessment methods to problems with data availability, data quality, and geographic sampling bias. The IUC-NN identified possibly threatened species with an accuracy of 84.3%, with significantly lower geographic evaluation bias relative to the IUCN Red List and was robust even when data availability was low and there were geographic errors in the input data. Overall, our results demonstrate that automated assessments have an important role to play in identifying species at the greatest risk of extinction.     

Ethics and governance for internet-based conservation science research

Internet-based research is increasingly important for conservation science and has wide-ranging applications and contexts, including culturomics, illegal wildlife trade, and citizen science. However, online research methods pose a range of ethical and legal challenges. Online data may be protected by copyright, database rights, or contract law. Privacy rights may also restrict the use and access of data, as well as ethical requirements from institutions. Online data have real-world meaning, and the ethical treatment of individuals and communities must not be marginalized when conducting internet-based research. As ethics frameworks originally developed for biomedical applications are inadequate for these methods, we propose that research activities involving the analysis of preexisting online data be treated analogous to offline social science methods, in particular, nondeceptive covert observation. By treating internet users and their data with respect and due consideration, conservationists can uphold the public trust needed to effectively address real-world issues.