Mass-based depth and velocity scales for gravity currents and related flows

Gravity driven flows on inclines can be caused by cold, saline or turbid inflows into water bodies. Another example are cold downslope winds, which are caused by cooling of the atmosphere at the lower boundary. In a well-known contribution, Ellison and Turner (ET) investigated such flows by making use of earlier work on free shear flows by Morton, Taylor and Turner (MTT). Their entrainment relation is compared here with a spread relation based on a diffusion model for jets by Prandtl. This diffusion approach is suitable for forced plumes on an incline, but only when the channel topography is uniform, and the flow remains supercritical. A second aspect considered here is that the structure of ET’s entrainment relation, and their shallow water equations, agrees with the one for open channel flows, but their depth and velocity scales are those for free shear flows, and derived from the velocity field. Conversely, the depth of an open channel flow is the vertical extent of the excess mass of the liquid phase, and the average velocity is the (known) discharge divided by the depth. As an alternative to ET’s parameterization, two sets of flow scales similar to those of open channel flows are outlined for gravity currents in unstratified environments. The common feature of the two sets is that the velocity scale is derived by dividing the buoyancy flux by the excess pressure at the bottom. The difference between them is the way the volume flux is accounted for, which—unlike in open channel flows—generally increases in the streamwise direction. The relations between the three sets of scales are established here for gravity currents by allowing for a constant co-flow in the upper layer. The actual ratios of the three width, velocity, and buoyancy scales are evaluated from available experimental data on gravity currents, and from field data on katabatic winds. A corresponding study for free shear flows is referred to. Finally, a comparison of mass-based scales with a number of other flow scales is carried out for available data on a two-layer flow over an obstacle. Mass-based flow scales can also be used for other types of flows, such as self-aerated flows on spillways, water jets in air, or bubble plumes.     

区域及全球尺度的NPP过程模型和NPP对全球变化的响应

植被净第一性生产力（NPP）不仅是表征植被活动和生态过程的关键参数,而且是判定生态系统碳汇和反映生态系统对全球变化响应的主要因子。当前,模型模拟成为大尺度NPP研究的主要手段,而在众多NPP估算模型中,过程模型逐渐趋于主导地位。虽然目前有关NPP的研究有很多,但还没有关注于大尺度上应用的过程模型及其模拟的NPP对全球变化的响应。因此本文主要侧重于 NPP 过程模型在区域及全球尺度上的应用,具体包含以下内容,①进一步将区域及全球尺度的NPP过程模型分为静态植被模型和动态植被模型。②阐明这些模型间存在的区别与联系。③归纳出NPP过程模型在区域及全球尺度上应用的3大挑战：时空尺度转换、多源数据的获取与融合以及模型模拟结果的验证与评价,并根据其解决方案总结出通用的模型应用框架。④从气候变化、大气成分变化和土地利用/土地覆盖变化3个方面探讨NPP对全球变化的响应机制,以期找到NPP变化的规律与模式。最后根据NPP模型的发展对未来区域及全球尺度的NPP过程模型进行展望,认为未来模型的综合性将更高,机理性也将更强,同时与全球变化研究结合得更加紧密,且基于多个已有模型的混合模型也是未来NPP模型发展的一个重要方向。此外,本文认为对NPP模拟结果的尺度效应研究也是未来NPP研究的热点之一。     

Distribution of phytoplankton community and its influence factors in an urban river network,East China

To reveal the distribution characteristics of phytoplankton and the main influence factors under different conditions in the urban rivers, the investigations were conducted during autumn and winter 2014 in Changzhou City, East China. 178 taxa of phytoplankton belonging to 28 functional assemblages were identified. In autumn, the phytoplankton community compositions have high similarity for enhanced hydrological connectivity. The chlorophytes and diatoms (prevailing functional groups C, F, J, P), together with euglenoids (W1), showed high proportions of biomass in the main rivers and connected rivers. It was related to the well mixed eutrophic conditions. The phytoplankton community exhibited spatiotemporal heterogeneity in winter. Affected by the low water level and temperature, the free-living phytoflagellates (X2) replaced groups F and J in the main rivers. Phytoplankton productivity was the highest in the Tongji River. Chlorophytes Dictyosphaerium ehrenbergianum and Chlamydobotrys stellata had an overwhelming superiority during the winter bloom. They were significantly correlated with ammonium, total phosphorus and biochemical oxygen demand. Affected by tail water supply, the diatoms (MP) and euglenoids (W1) dominated in a beheaded river. The multivariate analyses based on the phytoplankton functional groups helped to evaluate the relationships and variations between the urban rivers. The redundancy analysis (RDA) results showed that nitrate nitrogen, water temperature, total nitrogen and total suspended solids were the main influence factors on the phytoplankton community. Except MP, the prevailing groups all showed significant negative correlations with nitrate nitrogen. Availability and utilization of dissolved inorganic nitrogen and hydrodynamic conditions affected the phytoplankton distribution.

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Imposed and inherent scales in cellular automata models of habitat

Both observational and modelling studies of the natural environment are characterised by their ‘grain’ and ‘extent’, the smallest and largest scales represented in time and space. These are imposed scales that should be chosen to ensure that the natural scales of the system are captured in the study. A simple cellular automata model of habitat represents only the presence or absence of vegetation, with global and local interactions described by four empirical parameters. Such a model can be formulated as a nonlinear Markov equation for the habitat probability. The equation produces inherent space and time scales that may be considered as transition scales or the scales for recovery from disturbance. However, if the resolution of the model is changed, the empirical parameters must be changed to preserve the properties of the system. Further, changes in the spatial resolution lead to different interpretations of the spatial structure. In particular, as the resolution is reduced, the apparent dominance of one habitat type over the other increases. The model provides an ability to compare both field and model investigations conducted at different resolutions in time and space.     

多时间尺度上研究中国近代气温变化规律

应用MODIS数据反演了过去10年中国气温及气温的空间分布特征,并基于气象数据重建了过去60年中国城市、郊区、农村及气象台周边地区冬季气温距平的时间序列,从多时间尺度上,详细分析了20世纪中国气温变化规律。结果发现：气象台气温记录可能受城市热岛效应影响;60年来我国气温呈震荡波动,波动小周期约为7a;从10年尺度上看,近60年来,年代际气温增加幅度最大的是20世纪90年代,21世纪初气温虽然仍处于暖期,但已经出现下降趋势。     

Binational school-based monitoring of traffic-related air pollutants in El Paso, Texas (USA) and Ciudad Juárez, Chihuahua (México)

Paired indoor and outdoor concentrations of fine and coarse particulate matter (PM), PM2.5 reflectance [black carbon(BC)], and nitrogen dioxide (NO₂) were determined for sixteen weeks in 2008 at four elementary schools (two in high and two in low traffic density zones) in a U.S.-Mexico border community to aid a binational health effects study. Strong spatial heterogeneity was observed for all outdoor pollutant concentrations. Concentrations of all pollutants, except coarse PM, were higher in high traffic zones than in the respective low traffic zones. Black carbon and NO₂ appear to be better traffic indicators than fine PM. Indoor air pollution was found to be well associated with outdoor air pollution, although differences existed due to uncontrollable factors involving student activities and building/ventilation configurations. Results of this study indicate substantial spatial variability of pollutants in the region, suggesting that children’s exposures to these pollutants vary based on the location of their school.     

Spatial variations in CO2 fluxes in a subtropical coastal reservoir of Southeast China were related to urbanization and land-use types

Carbon dioxide (CO2) emissions from aquatic ecosystems are important components of the global carbon cycle, yet the CO2 emissions from coastal reservoirs, especially in developing countries where urbanization and rapid land use change occur, are still poorly understood. In this study, the spatiotemporal variations in CO2 concentrations and fluxes were investigated in Wenwusha Reservoir located in the southeast coast of China. Overall, the mean CO2 concentration and flux across the whole reservoir were 41.85 ± 2.03 µmol/L and 2.87 ± 0.29 mmol/m2/h, respectively, and the reservoir was a consistent net CO2 source over the entire year. The land use types and urbanization levels in the reservoir catchment significantly affected the input of exogenous carbon to water. The mean CO2 flux was much higher from waters adjacent to the urban land (5.05 ± 0.87 mmol/m2/hr) than other land use types. Sites with larger input of exogenous substance via sewage discharge and upstream runoff were often the hotspots of CO2 emission in the reservoir. Our results suggested that urbanization process, agricultural activities, and large input of exogenous carbon could result in large spatial heterogeneity of CO2 emissions and alter the CO2 biogeochemical cycling in coastal reservoirs. Further studies should characterize the diurnal variations, microbial mechanisms, and impact of meteorological conditions on reservoir CO2 emissions to expand our understanding of the carbon cycle in aquatic ecosystems.     

Influence of indoor transport and mixing time scales on the performance of sensor systems for characterizing contaminant releases

Optimizing real-time sensor systems to detect and identify relevant characteristics of an indoor contaminant event is a challenging task. The interpretation of incoming sensor data is confounded by uncertainties in building operation, in the forces driving contaminant transport, and in the physical parameters governing transport. In addition, simulation tools used by the sensor interpretation algorithm introduce modeling uncertainties. This paper explores how the time scales inherent in contaminant transport influence the information that can be extracted from real-time sensor data. In particular, we identify three time scales (within room mixing, room-to-room transport, and removal from the building) and study how they affect the ability of a Bayesian Monte Carlo (BMC) sensor interpretation algorithm to identify the release location and release mass from a set of experimental data, recorded in a multi-floor building. The research shows that some limitations in the BMC approach do not depend on details of the models or the algorithmic implementation, but rather on the physics of contaminant transport. These inherent constraints have implications for the design of sensor systems.     

Pheromone-based aggregation behaviour of the firebrat, <Emphasis Type="Italic">Thermobia domestica</Emphasis> (Packard) (Thysanura: Lepismatidae)

Summary. We tested the hypothesis that aggregation behaviour of the firebrat, Thermobia domestica (Packard) (Thysanura: Lepismatidae), an inhabitant of enclosed microhabitats, is mediated, at least in part, by a pheromone. Individual insects were released into the central chamber of a 3-chambered olfactometer and test stimuli were placed in lateral chambers. Paper discs previously exposed for 3 days to 10 female, male, or juvenile T. domestica were all preferred by female, male, or juvenile T. domestica over unexposed paper discs, indicating the presence of an aggregation/arrestment pheromone. In additional experiments, frass and scales from female T. domestica, tested singly and in combination, proved not to be the source of the pheromone. Physical contact was required for pheromone recognition, indicating that the pheromone arrests rather than attracts conspecifics. Arrestment by the long-tailed silverfish, Ctenolepisma longicaudata Escherich (Thysanura: Lepismatidae), but not by the common silverfish, Lepisma saccharina L. (Thysanura: Lepismatidae), to T. domestica exposed paper discs suggests closer phylogenetic relatedness between C. longicaudata and T. domestica, than between C. longicaudata and L. saccharina. Whether C. longicaudata or L. saccharina produce an aggregation signal, and whether T. domestica respond to this signal is unknown. Received 10 June 2002; accepted 30 September 2002.     

Exploring pedestrian injury severities at pedestrian-vehicle crash hotspots with an annual upward trend: A spatiotemporal analysis with latent class random parameter approach

Introduction: With the increasing trend of pedestrian deaths among all traffic fatalities in the past decade, there is an urgent need for identifying and investigating hotspots of pedestrian-vehicle crashes with an upward trend. Method: To identify pedestrian-vehicle crash locations with aggregated spatial pattern and upward temporal pattern (i.e., hotspots with an upward trend), this paper first uses the average nearest neighbor and the spatial autocorrelation tests to determine the grid distance and the neighborhood distance for hotspots, respectively. Then, the spatiotemporal analyses with the Getis-Ord Gi* index and the Mann-Kendall trend test are utilized to identify the pedestrian-vehicle crash hotspots with an annual upward trend in North Carolina from 2007 to 2018. Considering the unobserved heterogeneity of the crash data, a latent class model with random parameters within class is proposed to identify specific contributing factors for each class and explore the heterogeneity within classes. Significant factors of the pedestrian, vehicle, crash type, locality, roadway, environment, time, and traffic control characteristics are detected and analyzed based on the marginal effects. Results: The heterogeneous results between classes and the random parameter variables detected within classes further indicate the superiority of latent class random parameter model. Practical Applications: This paper provides a framework for researchers and engineers to identify crash hotspots considering spatiotemporal patterns and contribution factors to crashes considering unobserved heterogeneity. Also, the result provides specific guidance to developing countermeasures for mitigating pedestrian-injury at pedestrian-vehicle crash hotspots with an upward trend.