遥感在生态与环境监测中的主要应用领域

遥感是一种以物理手段、数学方法和地学分析为基础的综合应用技术 ,具有宏观、综合、动态和快速的特点。在解决宏观尺度的环境问题时 ,卫星遥感可重复获取多种空间、不同时相和不同波谱分辨率的地球信息 ,是适宜于调查和研究这些主题的唯一的、最有效的工具。本文通过对遥感在环境与生态监测的主要应用领域进行概要阐述 ,旨在抛砖引玉 ,推动遥感在环境与生态监测中的广泛应用。     

Decision‐Making Triggers in Adaptive Management

We analyzed whether decision‐making triggers increase accountability of adaptive‐management plans. Triggers are prenegotiated commitments in an adaptive‐management plan that specify what actions are to be taken and when on the basis of information obtained from monitoring. Triggers improve certainty that particular actions will be taken by agencies in the future. We conducted an in‐depth, qualitative review of the political and legal contexts of adaptive management and its application by U.S. federal agencies. Agencies must satisfy the judiciary that adaptive‐management plans meet substantive legal standards and comply with the U.S. National Environmental Policy Act. We examined 3 cases in which triggers were used in adaptive‐management plans: salmon (Oncorhynchus spp.) in the Columbia River, oil and gas development by the Bureau of Land Management, and a habitat conservation plan under the U.S. Endangered Species Act. In all the cases, key aspects of adaptive management, including controls and preidentified feedback loops, were not incorporated in the plans. Monitoring and triggered mitigation actions were limited in their enforceability, which was contingent on several factors, including which laws applied in each case and the degree of specificity in how triggers were written into plans. Other controversial aspects of these plans revolved around who designed, conducted, interpreted, and funded monitoring programs. Additional contentious issues were the level of precaution associated with trigger mechanisms and the definition of ecological baselines used as points of comparison. Despite these challenges, triggers can be used to increase accountability, by predefining points at which an adaptive management plan will be revisited and reevaluated, and thus improve the application of adaptive management in its complicated political and legal context. Detonadores de la Toma de Decisiones en el Manejo Adaptativo     

Aortic isthmus Doppler velocimetry: role in assessment of preterm fetal growth restriction

Intrauterine fetal growth restriction (IUGR) is an important pregnancy complication associated with significant adverse clinical outcome, stillbirth, perinatal morbidity and cerebral palsy. To date, no uniformly accepted management protocol of Doppler surveillance that reduces mortality and cognitive morbidity has emerged. Aortic isthmus (AoI) evaluation has been proposed as a potential monitoring tool for IUGR fetuses. In this review, the current knowledge of the relationship between AoI Doppler velocimetry and preterm fetal growth restriction is reviewed. Relevant technical aspects and reproducibility data are reviewed as we discuss AoI Doppler and its place within the existing repertoire of Doppler assessments in placental insufficiency. The AoI is a link between the right and left ventricles which perfuse the lower and upper body, respectively. The clinical use of AoI waveforms for monitoring fetal deterioration in IUGR has been limited, but preliminary work suggests that abnormal AoI impedance indices are an intermediate step between placental insufficiency-hypoxemia and cardiac decompensation. Further prospective studies correlating AoI indices with arterial and venous Doppler indices and perinatal outcome are required before encorporating this index into clinical practice. Copyright © 2010 John Wiley & Sons, Ltd.     

A methodological framework for improving air quality monitoring network layout. Applications to environment management

This work aims to provide a methodology framework which allows to improve the performance and efficiency of an air quality monitoring network (AQMN). It requires to be constituted by a minimum and reliable number of measurement sites. Nevertheless, the AQMN efficiency should be assessed over time, as a consequence of the possible emergence of new emission sources of air pollutants, which could lead to variations on their spatial distribution within the target area. PM₁₀ particles data monitored by the Community of Madrid's (Spain) AQMN between 2008 and 2017 were used to develop a methodology to optimize the AQMN performance. The annual spatial distribution of average PM₁₀ levels over the studied period monitored by all current stations vs those more representative was provided by a geographic information system (GIS), and the percentage of similarity between both postulates was quantified using simple linear regression (> 95%). As one innovative tool of this study, the practical application of the proposed methodology was validated using PM₁₀ particles data measured by AQMN during 2007 and 2018, reaching a similitude degree higher than 95%. The influence of temporal variation on the proposed methodological framework was around 20%.The proposed methodology sets criteria for identifying non-redundant stations within AQMN, it is also able to appropriately assess the representativeness of fixed monitoring sites within an AQMN and it complements the guidelines set by European legislation on air pollutants monitoring at fixed stations, which could help to tackle efforts to improve the air quality management.     

Estimated Injury Risk for Specific Injuries and Body Regions in Frontal Motor Vehicle Crashes

Objective: Injury risk curves estimate motor vehicle crash (MVC) occupant injury risk from vehicle, crash, and/or occupant factors. Many vehicles are equipped with event data recorders (EDRs) that collect data including the crash speed and restraint status during a MVC. This study's goal was to use regulation-required data elements for EDRs to compute occupant injury risk for (1) specific injuries and (2) specific body regions in frontal MVCs from weighted NASS-CDS data.

Methods: Logistic regression analysis of NASS-CDS single-impact frontal MVCs involving front seat occupants with frontal airbag deployment was used to produce 23 risk curves for specific injuries and 17 risk curves for Abbreviated Injury Scale (AIS) 2+ to 5+ body region injuries. Risk curves were produced for the following body regions: head and thorax (AIS 2+, 3+, 4+, 5+), face (AIS 2+), abdomen, spine, upper extremity, and lower extremity (AIS 2+, 3+). Injury risk with 95% confidence intervals was estimated for 15–105 km/h longitudinal delta-Vs and belt status was adjusted for as a covariate.

Results: Overall, belted occupants had lower estimated risks compared to unbelted occupants and the risk of injury increased as longitudinal delta-V increased. Belt status was a significant predictor for 13 specific injuries and all body region injuries with the exception of AIS 2+ and 3+ spine injuries. Specific injuries and body region injuries that occurred more frequently in NASS-CDS also tended to carry higher risks when evaluated at a 56 km/h longitudinal delta-V. In the belted population, injury risks that ranked in the top 33% included 4 upper extremity fractures (ulna, radius, clavicle, carpus/metacarpus), 2 lower extremity fractures (fibula, metatarsal/tarsal), and a knee sprain (2.4–4.6% risk). Unbelted injury risks ranked in the top 33% included 4 lower extremity fractures (femur, fibula, metatarsal/tarsal, patella), 2 head injuries with less than one hour or unspecified prior unconsciousness, and a lung contusion (4.6–9.9% risk). The 6 body region curves with the highest risks were for AIS 2+ lower extremity, upper extremity, thorax, and head injury and AIS 3+ lower extremity and thorax injury (15.9–43.8% risk).

Conclusions: These injury risk curves can be implemented into advanced automatic crash notification (AACN) algorithms that utilize vehicle EDR measurements to predict occupant injury immediately following a MVC. Through integration with AACN, these injury risk curves can provide emergency medical services (EMS) and other patient care providers with information on suspected occupant injuries to improve injury detection and patient triage.     

阜新市空气监测点位优化的聚类分析

基于聚类分析法利用数据之间距离系数进行分类的原理,建立空气监测点位聚类分析优化模型,结合阜新市地形、气象及历史监测数据,进行阜新市空气监测点位布设优化应用,优化结果表明:距离相似水平取d=0.3时,环保局(B点)与人民公园(C点)监测点空气污染物浓度分布相似性最高,合并为1点,增设气象台监测点位作为清洁背景点,4个点位构成阜新市空气监测新网络;利用CALPUFF模型模拟对优化后监测点位进行相关性检验。检验结果表明:监测点位优化后SO2浓度与实测值相关系数为0.984,PM10相关系数为0.968,NO2相关系数为0.973。CALPUFF模型模拟值与实际监测值之间相关系数均大于0.75,表明优化后的阜新市空气监测点位具有客观环境代表性;监测点位优化与检验方法具有一定应用价值。     

大气颗粒物PM_(2.5)监测技术研究进展及展望

大气颗粒物已经成为中国的首要大气污染物,其中PM2.5污染越来越受到政府和相关部门关注,本文综述了国内外对大气颗粒物PM2.5的几种监测方法的研究进展,重点比较了各种监测方法的优缺点,并通过实例对比说明了β-射线法的可靠性及用膜片反演方法提高精确度的可行性,同时就加强国内PM2.5监测技术研究提出相关建议及展望。     

总氮自动分析仪在地表水监测中的优势与局限研究

文章分析了总氮自动分析仪在地表水监测中的优势与局限。通过对检出限、精密度、准确度等一系列实验室质量要求进行测定发现,该法的空白较低,准确度和精密度均能达到国标要求,分析效率高,但检出限偏高,适合总氮含量较高的地表水监测,对于含量较低的地表水,还应使用传统的国标方法检测。