东亚春季边界层臭氧的数值模拟研究

利用嵌套网格空气质量模式系统(NAQPMS)对2004年4月东亚边界层(距地面.km以下)臭氧进行了数值模拟.并评估了东亚边界层光化学反应的活性.结果表明.东亚春季臭氧呈带状分布,其高值.〔φ(O3)>55×10-9.主要集中在30°N～40°N.受东亚季风气候控制.沿蒙古、中国东北以及日本一线有一强臭氧输送通道.输送通量达3×10-.mol/(m2·s).通过计算边界层O3光化学净生成率可知.光化学影响主要集中在高污染源排放地区.其与水平输送对臭氧影响的分布具有负相关性.说明光化学生成的O3可被输送至下风地区,而不仅限于局地.      

Challenges of simulating complex environmental systems at the landscape scale: A controversial dialogue between two cups of espresso

With the advancement of computational systems and the development of model integration concepts, complexity of environmental model systems increased. In contrast to that, theory and knowledge about > environmental systems as well as the capability for environmental systems analyses remained, to a large extent, unchanged. As a consequence, model conceptualization, data gathering, and validation, have faced new challenges that hardly can be tackled by modellers alone. In this discourse-like review, we argue that modelling with reliable simulations of human-environmental interactions necessitate linking modelling and simulation research much stronger to science fields such as landscape ecology, community ecology, eco-hydrology, etc. It thus becomes more and more important to identify the adequate degree of complexity in environmental models (which is not only a technical or methodological question), to ensure data availability, and to test model performance. Even equally important, providing problem specific answers to environmental problems using simulation tools requires addressing end-user and stakeholder requirements during early stages of problem development. In doing so, we avoid modelling and simulation as an end of its own.     

Effects of experimental protocol on global vegetation model accuracy: A comparison of simulated and observed vegetation patterns for Asia

Prognostic vegetation models have been widely used to study the interactions between environmental change and biological systems. This study examines the sensitivity of vegetation model simulations to: (i) the selection of input climatologies representing different time periods and their associated atmospheric CO₂ concentrations, (ii) the choice of observed vegetation data for evaluating the model results, and (iii) the methods used to compare simulated and observed vegetation. We use vegetation simulated for Asia by the equilibrium vegetation model BIOME4 as a typical example of vegetation model output. BIOME4 was run using 19 different climatologies and their associated atmospheric CO₂ concentrations. The Kappa statistic, Fuzzy Kappa statistic and a newly developed map-comparison method, the Nomad index, were used to quantify the agreement between the biomes simulated under each scenario and the observed vegetation from three different global land- and tree-cover data sets: the global Potential Natural Vegetation data set (PNV), the Global Land Cover Characteristics data set (GLCC), and the Global Land Cover Facility data set (GLCF). The results indicate that the 30-year mean climatology (and its associated atmospheric CO₂ concentration) for the time period immediately preceding the collection date of the observed vegetation data produce the most accurate vegetation simulations when compared with all three observed vegetation data sets. The study also indicates that the BIOME4-simulated vegetation for Asia more closely matches the PNV data than the other two observed vegetation data sets. Given the same observed data, the accuracy assessments of the BIOME4 simulations made using the Kappa, Fuzzy Kappa and Nomad index map-comparison methods agree well when the compared vegetation types consist of a large number of spatially continuous grid cells. The results of this analysis can assist model users in designing experimental protocols for simulating vegetation.     

Multiple sources of predictive uncertainty in modeled estimates of net ecosystem CO2 exchange

Net ecosystem CO₂ exchange (NEE) is typically measured directly by eddy covariance towers or is estimated by ecosystem process models, yet comparisons between the data obtained by these two methods can show poor correspondence. There are three potential explanations for this discrepancy. First, estimates of NEE as measured by the eddy-covariance technique are laden with uncertainty and can potentially provide a poor baseline for models to be tested against. Second, there could be fundamental problems in model structure that prevent an accurate simulation of NEE. Third, ecosystem process models are dependent on ecophysiological parameter sets derived from field measurements in which a single parameter for a given species can vary considerably. The latter problem suggests that with such broad variation among multiple inputs, any ecosystem modeling scheme must account for the possibility that many combinations of apparently feasible parameter values might not allow the model to emulate the observed NEE dynamics of a terrestrial ecosystem, as well as the possibility that there may be many parameter sets within a particular model structure that can successfully reproduce the observed data. We examined the extent to which these three issues influence estimates of NEE in a widely used ecosystem process model, Biome-BGC, by adapting the generalized likelihood uncertainty estimation (GLUE) methodology. This procedure involved 400,000 model runs, each with randomly generated parameter values from a uniform distribution based on published parameter ranges, resulting in estimates of NEE that were compared to daily NEE data from young and mature Ponderosa pine stands at Metolius, Oregon. Of the 400,000 simulations run with different parameter sets for each age class (800,000 total), over 99% of the simulations underestimated the magnitude of net ecosystem CO₂ exchange, with only 4.07% and 0.045% of all simulations providing satisfactory simulations of the field data for the young and mature stands, even when uncertainties in eddy-covariance measurements are accounted for. Results indicate fundamental shortcomings in the ability of this model to produce realistic carbon flux data over the course of forest development, and we suspect that much of the mismatch derives from an inability to realistically model ecosystem respiration. However, difficulties in estimating historic climate data are also a cause for model-data mismatch, particularly in a highly ecotonal region such as central Oregon. This latter difficulty may be less prevalent in other ecosystems, but it nonetheless highlights a challenge in trying to develop a dynamic representation of the terrestrial biosphere.     

基于管理成熟度的大型水利水电工程环境绩效评价研究

借鉴项目管理成熟度模型的研究方法,构建了大型水利水电工程环境管理成熟度模型,对模型的组成、内容和评价方法进行了定义.结合大型水利水电工程施工过程中的生态环境影响因素分析,建立了大型水利水电工程的环境绩效评价体系,并采用数据包络分析(DEA)动态评估模型进行了环境管理成熟模型评价.案例研究表明,大型水利水电工程环境绩效评价结果能较好的反映出工程施工期间的环境管理成熟度水平,并能反映持续改进方面的环境贡献,研究成果对于改善我国大型水利水电工程建设对生态环境的影响及制定相关政策具有重要意义.     

Two stage fluid bed-plasma gasification process for solid waste valorisation: technical review and preliminary thermodynamic modelling of sulphur emissions

Gasification of solid waste for energy has significant potential given an abundant feed supply and strong policy drivers. Nonetheless, significant ambiguities in the knowledge base are apparent. Consequently this study investigates sulphur mechanisms within a novel two stage fluid bed-plasma gasification process. This paper includes a detailed review of gasification and plasma fundamentals in relation to the specific process, along with insight on MSW based feedstock properties and sulphur pollutant therein. As a first step to understanding sulphur partitioning and speciation within the process, thermodynamic modelling of the fluid bed stage has been performed. Preliminary findings, supported by plant experience, indicate the prominence of solid phase sulphur species (as opposed to H₂S) - Na and K based species in particular. Work is underway to further investigate and validate this.     

A COMPARISON OF DELTA CHANGE AND DOWNSCALED GCM SCENARIOS FOR THREE MOUNTAINOUS BASINS IN THE UNITED STATES1

ABSTRACT: Simulated daily precipitation, temperature, and runoff time series were compared in three mountainous basins in the United States: (1) the Animas River basin in Colorado, (2) the East Fork of the Carson River basin in Nevada and California, and (3) the Cle Elum River basin in Washington State. Two methods of climate scenario generation were compared: delta change and statistical downscaling. The delta change method uses differences between simulated current and future climate conditions from the Hadley Centre for Climate Prediction and Research (HadCM2) General Circulation Model (GCM) added to observed time series of climate variables. A statistical downscaling (SDS) model was developed for each basin using station data and output from the National Center for Environmental Prediction/National Center for Atmospheric Research (NCEPINCAR) reanalysis regridded to the scale of HadCM2. The SDS model was then used to simulate local climate variables using HadCM2 output for current and future conditions. Surface climate variables from each scenario were used in a precipitation‐runoff model. Results from this study show that, in the basins tested, a precipitation‐runoff model can simulate realistic runoff series for current conditions using statistically down‐scaled NCEP output. But, use of downscaled HadCM2 output for current or future climate assessments are questionable because the GCM does not produce accurate estimates of the surface variables needed for runoff in these regions. Given the uncertainties in the GCMs ability to simulate current conditions based on either the delta change or downscaling approaches, future climate assessments based on either of these approaches must be treated with caution.     

Evaluation of ecological network analysis: Validation of output

Ecological network analysis (ENA) is a modeling approach increasingly being used to evaluate food webs and provide an ecosystem-based approach to resource management. Unfortunately, validation of ENA output is rarely performed. This study represents part of a larger effort to critically evaluate ENA. Here we validate ENA output using stable isotope analysis (SIA), and where validation is not met, determine the effects of modifying trophic networks to reflect validation.     

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.     

多环芳烃室内土柱淋溶行为的CDE模型模拟

采用土柱淋溶实验方法对多环芳烃(PAHs)在人工污染士柱中表面活性剂淋溶下的运移进行了实验室研究,获得了示踪剂Br^-和PAHs的穿透曲线(BTCs);并通过室内批量平衡试验(PAHs和表面活性剂吸附试验和表面活性剂对PAHs吸附／解吸影响试验)获得了吸附系数,进而获得阻滞因子．基于这些实验室结果,通过CXTFIT2．1软件,用平衡CDE模型拟合了Br^-的BTCs,获得物理和水动力参数;并在此基础上应用CDE非平衡模型拟合PAHs在表面活性剂淋溶条件下土柱中的BTCs以及不同时刻、不同埋深处PAHs浓度的动态变化,预测了PAHs在土柱中的迁移趋势。