利用卫星遥感数据估算PM2.5浓度的应用研究进展

近年来,PM_(2.5)已成为中国大气污染的首要污染物,危害人体健康。为弥补地基监测站点在空间分布上的局限性,借助卫星遥感技术估算PM_(2.5)浓度已成为研究热点。文章总结了利用卫星估算PM_(2.5)浓度的各种研究方法,探讨了不同方法的优势和不足,指出不同方法对不同应用目的的选择性差异较大。提出,应针对不同应用目的选择相应的方法,从而取得满足各方面需求的研究成果,为未来PM_(2.5)浓度估算应用工作提供参考。     

An innovative computer design for modeling forest landscape change in very large spatial extents with fine resolutions

Although forest landscape models (FLMs) have benefited greatly from ongoing advances of computer technology and software engineering, computing capacity remains a bottleneck in the design and development of FLMs. Computer memory overhead and run time efficiency are primary limiting factors when applying forest landscape models to simulate large landscapes with fine spatial resolutions and great vegetation detail. We introduce LANDIS PRO 6.0, a landscape model that simulates forest succession and disturbances on a wide range of spatial and temporal scales. LANDIS PRO 6.0 improves on existing forest landscape models with two new data structures and algorithms (hash table and run-length compression). The innovative computer design enables LANDIS PRO 6.0 to simulate very large (>10⁸ ha) landscapes with a 30-m spatial resolution, which to our knowledge no other raster forest landscape models can do. We demonstrate model behavior and performance through application to five nested forest landscapes with varying sizes (from 1 million to 100 million 0.09-ha cells) in the southern Missouri Ozarks. The simulation results showed significant and variable effects of changing spatial extent on simulated forest succession patterns. Results highlighted the utility of a model like LANDIS PRO 6.0 that is capable of efficiently simulating large landscapes and scaling up forest landscape processes to a common regional scale of analysis. The programming methodology presented here may significantly advance the development of next generation of forest landscape models.     

Forecasting population trend from the scaling pattern of occupancy

Forecasting the temporal trend of a focal species, its range expansion or retraction, provides crucial information regarding population viability. To this end, we require the accumulation of temporal records which is evidently time consuming. Progress in spatial data capturing has enabled rapid and accurate assessment of species distribution across large scales. Therefore, it would be appealing to infer the temporal trends of populations from the spatial structure of their distributions. Based on a combination of models from the fields of range dynamics, occupancy scaling and spatial autocorrelation, here I present a model for forecasting the population trend solely from its spatial distribution. Numerical tests using cellular automata confirm a positive correlation, as inferred from the model, between the temporal change in species range sizes and the exponent of the power-law scaling pattern of occupancy. The model is thus recommended for rapid estimation of species range dynamics from a single snapshot of its current distribution. Further applications in biodiversity conservation could provide a swift risk assessment, especially, for endangered and invasive species.     

Evaluation of limits for effective flame acceleration in hydrogen mixtures

Results of experiments and data analysis on turbulent flame propagation in obstructed channels are presented. The data cover a wide range of mixtures: H₂/air, H₂/air/steam (from lean to rich) at normal and elevated initial temperatures (from 298 to 650 K) and pressures (from 1 to 3 bar); and stoichiometric H₂/O₂ mixtures diluted with N₂, Ar, He and CO₂ at normal initial conditions. The dataset chosen also covers a wide range of scales exceeding two orders of magnitude. It is shown that basic flame parameters, such as mixture expansion ratio σ, Zeldovich number β and Lewis number Le, can be used to estimate a priori a potential for effective flame acceleration for a given mixture. Critical conditions for effective flame acceleration are suggested in the form of correlations of critical expansion ratio σ^* versus dimensionless effective activation energy. On this basis, limits for effective flame acceleration for hydrogen combustibles can be estimated. Uncertainties in determination of critical σ^* values are discussed.     

Estimates of species- and ecosystem-level respiration of woody stems along an elevational gradient in the Luquillo Mountains, Puerto Rico

We measured CO₂ efflux from stems of seven subtropical tree species situated along an elevational gradient in the Luquillo Mountains, Puerto Rico and scaled these measurements up to the landscape level based on modeled and empirical relations. The most important determinants of ecosystem stem respiration were species composition and stem temperature. At a species scale, measured CO₂ efflux per unit bole surface area at a given temperature was highest in the early successional species Cecropia schreberiana and lowest in species that inhabit high elevations such as Micropholis garciniifolia and Tabebuia rigida. Carbon dioxide efflux rates followed a diel pattern that lagged approximately 6 h behind changes in sapwood temperatures. At an ecosystem scale, our simulation model indicates a decreasing trend of stem respiration rates with increasing elevation due to shifts in species composition, lower temperatures and reductions in branch surface area. The highest estimated stem respiration rates were present in the lowland tabonuco forest type and the lowest rates were present in the elfin forest type (mean 7.4 and 2.1 Mg C ha⁻¹ yr⁻¹, respectively). There was slight temperature-induced seasonal variation in simulated stem respiration rates at low elevations, with a maximum difference of 19% between the months of February and July. Our results coincide well with those of Odum and Jordan [Odum, H.T., Jordan, C.F., 1970. Metabolism and evapotranspiration of the lower forest in a giant plastic cylinder. In: Odum, H.T., Pigeon, R.F. (Eds.), A Tropical Rain Forest: A Study of Irradiation and Ecology at El Verde, Puerto Rico. U.S. Atomic Energy Commission, Oak Ridge, TN, pp. I165–I189] for the tabonuco forest type and extend their work by presenting estimates and spatial patterns of woody tissue respiration for the entire mountain rather than for a single forested plot.     

四川旱涝灾害时间分布序列的分形特征研究

本文采用分形理论计算了四川旱涝灾害时间分布序列的分数维，其结果初步证实了四川旱涝灾害时间分布在一定区间范围内的无标度性。无标度区的跨度及相应的分形维数可作为四川旱涝灾害自组织程度的量度。     

Individual changes in human EEG caused by 450 MHz microwave modulated at 40 and 70 Hz

This study was aimed to investigate the changes in the human electroencephalographic (EEG) signal caused by modulated low-level microwaves. The 450 MHz microwave exposure modulated at 40 Hz and 70 Hz frequencies was applied to a group of 15 volunteers. The field power density at the scalp was 0.16 mW/cm². Ten cycles of the exposure (1 min on and 1 min off) at both modulation frequencies were applied. Analysis of the EEG signal was performed using three different methods: nonlinear method of scaling analysis for length distribution of low variability periods (LDLVP), relative changes in EEG energy (S-parameter) and beta ratio (H-parameter). The analysis revealed significant changes caused by microwave for the whole group (H-parameter method). The exposure caused increase of the EEG beta power (S-parameter method). Statistically significant changes in EEG were detected for four subjects (26.7%) at 40 Hz modulation frequency (LDLVP method).     

Scaling-up spatially-explicit ecological models using graphics processors

How the properties of ecosystems relate to spatial scale is a prominent topic in current ecosystem research. Despite this, spatially explicit models typically include only a limited range of spatial scales, mostly because of computing limitations. Here, we describe the use of graphics processors to efficiently solve spatially explicit ecological models at large spatial scale using the CUDA language extension. We explain this technique by implementing three classical models of spatial self-organization in ecology: a spiral-wave forming predator-prey model, a model of pattern formation in arid vegetation, and a model of disturbance in mussel beds on rocky shores. Using these models, we show that the solutions of models on large spatial grids can be obtained on graphics processors with up to two orders of magnitude reduction in simulation time relative to normal pc processors. This allows for efficient simulation of very large spatial grids, which is crucial for, for instance, the study of the effect of spatial heterogeneity on the formation of self-organized spatial patterns, thereby facilitating the comparison between theoretical results and empirical data. Finally, we show that large-scale spatial simulations are preferable over repetitions at smaller spatial scales in identifying the presence of scaling relations in spatially self-organized ecosystems. Hence, the study of scaling laws in ecology may benefit significantly from implementation of ecological models on graphics processors.     

Scale-dependent relations in land cover biophysical dynamics

The exploration of the relationships between plant biotic dynamics and scale can reveal important information on ecosystem spatial organization by addressing preservation of information integrity in upscaling/downscaling procedures of land-surface parameterization for environmental modeling applications. Scale-dependent relations of vegetation dynamics are investigated in this study by using emergent biophysical characteristics obtained through a predictive multidimensional model of vegetation anomalies derived from remote-sensing observations. In particular, the analysis is focused on the spatial organization of some phenological parameters including deterministic variations (seasonal range, interannual variability, jump discontinuities) and stochastic components (plant memory, spatial correlations). The analysis is performed using MODIS-based Normalized Difference Vegetation Index (NDVI) 16-day composites for the period from March 2000 to December 2006 over Italy at different levels of spatial aggregation (1-8 km). Scale-dependences of the statistical moments of the phenological parameters are quantified through simple power laws for five distinct vegetated land covers. Results suggest that some biophysical characteristics, especially deterministic components, show no preferential spatial scale for important coverage. In particular, broad-leaved forests and natural grasslands are characterized by deterministic and low-distance spatial components well explained by scale relationships, which are modulated by possible spatiotemporal dynamics of climatic drivers. Agricultural lands show high scale-dependent relations on short-term biophysical memory sources and low-distance spatial components of phenology likely related to hierarchical interactions of anthropogenic and ecological processes; whereas mixed patterns of croplands and natural areas generally present no consistent scaling relations.     

Temporal scaling behavior of human-caused fires and their connection to relative humidity of the atmosphere

It has been found that many natural systems are characterized by scaling behavior. In such systems natural factors dominate the event dynamics. But in countries with high population density such as China and Japan, more than 95% of the forest fire disasters are caused by human activities. Furthermore, with the development of society, the wildland-urban interface (WUI) area is becoming more and more populated, and the forest fire is much connected with urban fire. Therefore exploring the scaling behavior of fires dominated by human-related factors is very challenging. The present paper explores the temporal scaling behavior of forest fires and urban fires in Japan. Our findings point out that although the human factors are the main cause, both the forest fires and urban fires exhibit time-scaling behavior. Similar distribution law characterizes the relative humidity.