嘉山台地电阻率各类变化的判定与分析

本文以嘉山台地电阻率数字化改造后的观测资料为基础,在台址条件、资料质量、干扰因素等方面进行了较为系统的整理,总结了地电阻率观测中的非震现象、典型干扰的变化及影响观测精度的因素,对干扰机制也进行了必要的判断,同时对嘉山台地电阻率的映震效能进行了尝试性的分析,为同类型地电台有效地识别和排除干扰提供参考和借鉴。     

温室气体对气候环境的影响预测及其不确定性

随着温室气体排放量的增加,联系温室气体特有的保温效应,大气平均气温将升高。在采用气候模式对未来近百年的气候变化做出一定预测的基础上,分析未来可能出现的气候变化所造成的对气候环境方面的影响。详细分析了现阶段预测未来气候环境变化存在的不确定性,正是这些不确定性影响了预测的可信度。     

西安市春季生物气溶胶的分布特征和健康影响

西安春季经常出现大量飞絮,易造成空气污染并引发居民哮喘等健康风险.采集西安市春季不同观测点(交通样点和校园样点)生物气溶胶、 PM_2.5和飞絮样品,通过恒温培养和高通量测序等方法研究可培养生物气溶胶的浓度变化、粒径分布,PM_2.5和飞絮携带的微生物的来源、群落结构和健康影响.结果表明,可培养细菌浓度在交通样点高于校园样点(P=0.027);交通样点可培养细菌浓度为真菌的2.7倍,而校园样点可培养真菌浓度高于细菌(1.4倍).可培养细菌和真菌日内最高浓度均出现在08:00;可培养细菌粒径呈双峰分布,真菌为单峰分布.土壤和植被是大气微生物的主要来源(占比85.9%),变形菌门(Proteobacteria)是飞絮和PM_2.5中共有的、丰度最高的菌门,在飞絮中占比达到91.3%(交通样点)和99.1%(校园样点);在PM_2.5样品中放线菌门(Actinobacteria)、厚壁菌门(Firmicutes)、拟杆菌门(Bacteroidetes)、蓝藻门(Cyanobacteria)和异常球菌-栖热菌门(D...     

马拉硫磷和百菌清胁迫下斑马鱼行为变化的研究

以马拉硫磷和百菌清为胁迫因子,本文研究了2种污染物暴露下斑马鱼行为强度的变化。首先通过急性毒性试验确定了2种农药对斑马鱼24 h、48 h、72 h、96 h的半致死浓度(LC50),其次以LC50-48 h为1个染毒单位(TU),在0.01 TU、0.1 TU、0.5 TU、1 TU、2 TU 5个条件下,本文开展了斑马鱼行为学研究。结果显示,48 h马拉硫磷暴露斑马鱼的LC50为5 mg·L~(-1),百菌清暴露斑马鱼的LC50为0.01 mg·L~(-1)。随着污染物浓度增大,综合行为强度变化幅度增大。在设置的暴露浓度下,斑马鱼的行为强度在急剧增大或减小后都出现了明显的调节适应过程,基本符合环境压力模型。通过比较在不同频率下的影响强度,马拉硫磷和百菌清暴露斑马鱼摆鳍所受影响最大。本研究提示,水质监测中可增加斑马鱼摆鳍观察指标。     

珠江三角洲土地利用变化对特征大气污染物扩散的影响

在珠江三角洲两种下垫面条件下,应用CALPUFF大气污染扩散模式,对特征污染物SO2、SO42-的扩散进行数值模拟,探讨大规模土地利用变化,尤其是城镇建设用地增加,对珠江三角洲地区大气污染物扩散的影响,并通过对4个典型区污染物月均质量浓度变化特征分析,揭示土地利用变化对不同地区的污染物分布的影响机制。模拟结果表明：土地利用变化,尤其是城镇建设用地增加,不利于污染物扩散,污染源下风方向地区受影响较大,污染物质量浓度明显升高,SO2和 SO42-年均质量浓度分别增加14.07%和3.31%;受影响范围、变化幅度与污染源排污强度呈正相关,变化幅度亦与污染源距离远近呈负相关。土地利用变化后,尤其是城镇建设用地增加,四个典型区 SO2月均质量浓度都表现为升高趋势,且冬季 SO2质量浓度升高幅度最大,夏季升高幅度最小,临近污染源密集区的两个典型区SO2月均质量浓度分别增加33.6%和26.3%。土地利用变化不仅改变局地的污染扩散,也会对区域的污染扩散有一定影响,尤其对污染源分布密集区的大气污染物扩散影响强度最大。因此,建议人类在城市化建设过程中尽可能保留自然斑块,消除人工下垫面对污染物扩散的负面影响。     

紫外光催化氧化在污水处理厂除臭工程中的应用

通过采用合适的构筑物加盖形式,设计合理的换气次数,采用自行研制的紫外光催化氧化设备处理广东某污水处理厂产生的恶臭气体,运行结果表明:该设备具有除臭效率高、操作简单、阻力小及不产生二次污染的优良性能;该工艺对产生恶臭的物质均能达标排放,且占地少,投资省,适合用于城镇污水处理厂除臭工程,具有良好的经济效益和广阔的发展前景。     

A multi-scale approach to modelling spatial and dynamic ecological patterns for reservoir's water quality management

With growing levels of urbanization and agriculture throughout the world, it is increasingly important that both research and management efforts take into account the effects of this widespread landscape alteration and its consequences for natural systems. Freshwater ecosystems, namely reservoirs, are particularly sensitive to land use changes. In this context, modelling can be very useful, for decision support, as an investigative tool to forecast the outcome of various scenarios, to guide current management in order to meet future targets and to develop integrated frameworks for management accordingly to the Water Framework Directive (WFD). The present paper examined the applicability of a holistic Stochastic-Dynamic Methodology (StDM), coupled with a Cellular Automata (CA) model, in capturing how expected changes at land use level will alter the ecological status of lentic ecosystems, namely at physicochemical and biological levels. The methodology was applied to Portuguese reservoirs located in the Douro's basin and illustrated with a series of stochastic-dynamic and spatial outputs taking into account expected scenarios regarding land use changes. Overall, the simulation results are encouraging since they seem to demonstrate the tool reliability in capturing the stochastic environmental dynamics of the selected metrics facing spatial explicit scenarios. The ultimate goal was to couple monitoring assessment and the described modelling techniques to ease management and decision making regarding the practical implementation of the WFD, both at the scale of the reservoir body and at the scale of the respective river watershed dynamics.     

Understanding the effects of rainfall on elephant-vegetation interactions around waterholes

The distribution of surface water affects herbivore-vegetation interactions in arid and semi-arid regions. Limited access to surface water typically results in the emergence of vegetation gradients around natural and artificial water sources. In particular, African elephants can create large-scale gradients of woody vegetation. Understanding the dynamics of these gradients is of particular importance for the conservation of other, less mobile herbivores that depend on woody vegetation in areas close to water. While rainfall is known to be a key determinant of herbivore-vegetation interactions in dry areas, we only have limited understanding on how it impacts woody vegetation gradients around waterholes. To address this problem, we developed a deterministic simulation model that describes the interplay of rainfall, elephants and woody vegetation in the vicinity of waterholes. The model is based on elephant telemetry data and the ecological conditions in Etosha National Park (ENP), Namibia. We found that decreasing amounts of rainfall led to an increased degradation of woody vegetation, which was particularly severe in areas close to water. Based on this result we conclude that low rainfall was an important driver of recently observed patterns of vegetation degradation in ENP. More generally, rainfall appears to be a key factor that determines elephant-vegetation interactions and thus dynamics of woody vegetation gradients around waterholes. Using long-term rainfall data from ENP, we also demonstrate that an increase in the number of water sources during periods of low rainfall can mitigate the destructive impact of elephants in areas close to water. However, more research is required to assess the sustainability and effectiveness of rainfall-adapted strategies of artificial water provisioning in more detail. In particular it is important to investigate potential effects on elephant population dynamics.     

Path forward: Emerging issues and challenges

The NIOSH Construction Program worked with industry stakeholders to develop a National Occupational Safety and Health Construction Agenda to target future research and activities. The Program and its partners are also cognizant that new developments can emerge over time and that research can play an important role in helping to understand and address these emerging issues. Examples of emerging issues relevant to construction safety and health are described. These include: (a) climate change and energy considerations; (b) green construction developments and opportunities; (c) new materials; (d) changes in industry structure and practice; (e) workforce developments and disparities; (f) injury underreporting and cost and risk shifting; and (g) increased interest in addressing root causes. Responding to emerging issues while maintaining a focus on fundamental longstanding issues represents an ongoing challenge for researchers and industry organizations. Additional research to understand the diffusion and adoption of research by the industry is also needed. Research accomplished to date provides a strong foundation for addressing future industry needs and trends.     

Spatial and temporal relationships between precipitation and ANPP of four types of grasslands in northern China

Precipitation is considered to be the primary resource limiting terrestrial biological activity in water-limited regions. Its overriding effect on the production of grassland is complex. In this paper, field data of 48 sites （including temperate meadow steppe, temperate steppe, temperate desert steppe and alpine meadow） were gathered from 31 published papers and monographs to analyze the relationship between above-ground net primary productivity （ANPP） and precipitation by the method of regression analysis. The results indicated that there was a great difference between spatial pattern and temporal pattern by which precipitation influenced grassland ANPP. Mean annual precipitation （MAP） was the main factor determining spatial distribution of grassland ANPP （r^2 = 0.61, P 〈 0.01）; while temporally, no significant relationship was found between the variance of AN PP and inter-annual precipitation for the four types of grassland. However, after dividing annual preeipitation into monthly value and taking time lag effect into account, the study found significant relationships between ANPP and precipitation. For the temperate meadow steppe, the key variable determining inter-annual change of ANPP was last August-May precipitation （r^2 = 0.47, P = 0.01）; for the temperate steppe, the key variable was July precipitation （r^2 = 0.36, P = 0.02）; for the temperate desert steppe, the key variable was April-June precipitation （r^2 = 0.51, P 〈 0.01）; for the alpine meadow, the key variable was last September-May precipitation （r^2 = 0.29, P 〈 0.05）. In comparison with analogous research, the study demonstrated that the key factor determining inter-annual changes of grassland ANPP was the cumulative precipitation in certain periods of that year or the previous year.