Partial dissolution of ACQ-treated wood in lithium chloride/N-methyl-2-pyrrolidinone: separation of copper from potential lignocellulosic feedstocks

A cellulose solvent system based on lithium chloride (LiCl) in N-methyl-2-pyrrolidinone (NMP) was used to assess the merits of partial dissolutions of coarsely ground wood samples. Alkaline Copper Quaternary (ACQ)-treated pine wood was of particular interest for treatment given the potential to generate a copper-rich stream apart from solid and/or liquid lignocellulosic feedstocks. Treatment with NMP alone gave yields of soluble materials that were higher than typical extractives contents thereby suggesting a limited degree of wood dissolution. Inclusion of LiCl, which disrupts hydrogen bonding, gave lower wood residue recoveries (i.e., higher dissolution) with higher LiCl concentration. Lower wood residue recoveries coincided with lower Klason lignin and hemicellulose-derived sugar contents in the wood residues. After treatment with 8% LiCl in NMP, subsequent filtration afforded 34% of the ACQ-treated sapwood as a wood residue retaining only 2% of the original copper. Pouring the filtrate over an excess of water resulted in the recovery of 30% of the solids and 50% of the copper together as a copper-enriched lignocellulosic precipitate. Results demonstrate a solvent system showing potential as a means to separate heavy metals from preservative-treated wood and to recover lignocellulosic feedstocks that may be suitable for use in a biorefinery.     

Self healing databases for predictive risk analytics in safety-critical systems

Assuring the quality, consistency and accuracy of safety data repositories is essential in safety-critical systems. In many systems, however, significant effort is required to identify, address, clean and repair data errors and inconsistencies, and to integrate safety data sets and repositories, particularly for risk analyses. Although some self healing and self repairing capabilities leveraging machine learning and predictive analyses have been employed to identify anomalies and monitor quality in structured safety-critical data sets, little attention has been focused on addressing shortcomings in heterogeneous—structured and unstructured—safety data sets, the focus of this work. The text mining and classification analysis employed in this research indicates that machine learning techniques can be employed to improve the accuracy and robustness of large-scale structured and unstructured database repositories, and to improve the effectiveness and efficiency of safety data repository maintenance. Hybrid machine learning approaches, leveraging machine learning, text mining and natural language processing, offer additional promise in future work.     

基于GIS天津市燃气管网预警系统的构建研究

基于GIS的原理,结合燃气事故的致因及其后果,对燃气泄漏模型、扩散模型、火灾及爆炸后果模型进行完善和改进,建立了燃气事故预警模型;通过Visual C++编程,借助ARCGIS平台将燃气事故预警模型与天津市燃气管网GIS相结合,构建了基于GIS的天津市燃气管网预警系统。该系统应用结果显示:由燃气事故预警模型计算得出的事故后果,通过GIS地理空间数据库和模型库的链接,实现了燃气泄漏点的可视化预警分析;并根据分析结果启动相应应急预案,实现了事故预警实时分析与应急预案启动的联动功能,为相关决策者提供了可靠决策依据。     

Evaluation of methods for the physical characterization of the fine particle emissions from two residential wood combustion appliances

The fine particle emissions from a U. S. certified non-catalytic wood stove and a zero-clearance fireplace burning Quercus rubra L. (northern red oak) and Pseudotsuga menziesii (Douglas fir) cordwood each at two different moisture levels were determined. Emission testing was performed using both time-integrated and continuous instrumentation for total particle mass, particle number, particle size distribution, and fixed combustion gases using an atmospheric wind tunnel, full-flow laboratory dilution tunnel, and dilution stack sampler with a comparison made between the three dilution systems and two sampling filter types. The total mass emission factors (EFs) for all dilution systems and filter media are extremely variable ranging from <1 to 55 g kg⁻¹ of dry wood depending on the combination of appliance type, wood species and moisture content, filter medium, and dilution system. For Teflon filter sampling of stove emissions in the wind tunnel, the total mass EFs varied from 2 to 8 g kg⁻¹ of dry fuel depending on wood type whereas the equivalent fireplace emissions burning wet oak averaged 11 g kg⁻¹. A substantial number of ultrafine particles in the accumulation size range were also observed during all tests as determined by an Electrical Low Pressure Impactor (ELPI) and Scanning Mobility Particle Sizer. The PM-2.5 (particles ≤2.5 μm in aerodynamic diameter) fractions determined from the ELPI electrometer data ranged from 93 to 98% (mass) depending on appliance type as reported previously by Hays et al. (Aerosol Science, 34, 1061, 2003).     

A prediction-based approach to modelling temporal and spatial variability of traffic-related air pollution in Montreal, Canada

Concentrations of traffic-related air pollution can be highly variable at the local scale and can have substantial seasonal variability. This study was designed to provide estimates of intra-urban concentrations of ambient nitrogen dioxide (NO₂) in Montreal, Canada, that would be used subsequently in health studies of chronic diseases and long-term exposures to traffic-related air pollution. We measured concentrations of NO₂ at 133 locations in Montreal with passive diffusion samplers in three seasons during 2005 and 2006. We then used land use regression, a proven statistical prediction method for describing spatial patterns of air pollution, to develop separate estimates of spatial variability across the city by regressing NO₂ against available land-use variables in each of these three periods. We also developed a “pooled” model across these sampling periods to provide an estimate of an annual average. Our modelling strategy was to develop a predictive model that maximized the model R². This strategy is different from other strategies whose goal is to identify causal relationships between predictors and concentrations of NO₂.Observed concentrations of NO₂ ranged from 2.6 ppb to 31.5 ppb, with mean values of 12.6 ppb in December 2005, 14.0 ppb in May 2006, and 8.9 ppb in August 2006. The greatest variability was observed during May. Concentrations of NO₂ were highest downtown and near major highways, and they were lowest in the western part of the city. Our pooled model explained approximately 80% of the variability in concentrations of NO₂. Although there were differences in concentrations of NO₂ between the three sampling periods, we found that the spatial variability did not vary significantly across the three sampling periods and that the pooled model was representative of mean annual spatial patterns.     

The relationship of place to substance use and perceptions of risk and safety in urban adolescents

Geographic and substance use data were collected from 301 urban adolescents to compare the perceived and observed risk and safety associated with their home and activity space locations (routine locations). The geographic characteristics of the neighborhood surrounding each location was summarized according to features theorized to be risky, such as criminal activity and alcohol sales, and features theorized to be safe, such as recreation centers and churches. Data on socioeconomic status, derived from U.S. Bureau of the Census data, were also used to characterize locations. Adolescents' homes were typically perceived as safe despite observed measures of risk such as density of crimes and proximity to alcohol outlets. This held for both substance users and non-users. Differences in geographic characteristics for safe and risky activity spaces were observed for both substance users and non-users, with non-users appearing to be more sensitive to the presence of risky characteristics in the environment than substance users. Results highlight the need and provide a methodology to collect fine-grained activity space data instead of relying only on home residence when attempting to represent place and health behaviors with urban youth.     

Consideration of User Needs and Spatial Accuracy in Drought Mapping1

Abstract: The increasing availability of web mapping tools creates new opportunities to bridge decision‐makers’ climate information needs with technical capabilities. These new tools, however, raise familiar, unresolved issues related to cartographic representation. Using an on‐line drought mapping tool, this study seeks to understand which spatial unit best meets the desire drought managers have for “local” information, their comprehension of uncertainties introduced in mapping information at local scales, and their willingness to trade off accuracy for information at a desired unit. We found that the most useful local map information includes regional context and boundaries which present their local area of interest. Even among this experienced, well‐educated, professional group, those who had not taken a GIS or cartography class did not fully recognize the role of interpolation in creating and introducing uncertainty to some drought maps. Those who did recognize the uncertainty introduced by interpolation still strongly favored maps that provided estimated values for all areas vs. station point accuracy. Mapping poses a unique set of challenges to communicating risk and uncertainty. As more decision‐support efforts incorporate web mapping, greater attention is needed to assure that users understand the tradeoffs between accuracy and precision in creating local information, the imprecision of boundaries, as well as the limits of forecasts. Clearly conveying spatial accuracy and uncertainty is a challenge that merits greater attention in using maps to communicate drought and other environmental risk information.     

A Conceptual Model for Defining and Assessing Land Management Units Using a Fuzzy Modeling Approach in GIS Environment

Appropriate land management decisions are important for current and future use of the land to ensure its sustainability. This requires that land management units (LMUs) be specified to enable the identification of specific parameters employed in decision making processes. This paper presents the development of a conceptual model, within geographic information systems (GIS), for defining and assessing LMUs from available biophysical information. The model consists of two main components (sub-models): land quality-based suitability analysis and soil erosion estimation. Using a fuzzy set methodology, the first sub-model was constructed to derive a land suitability index (LSI) for a cropping land utilization type. The LSI thus highlights the suitability grades of every pixel in the study area on a continuous basis. A sub-model of soil erosion was established based on the Revised Universal Soil Loss Equation (RUSLE) utilising the same spatial data bases employed for structuring the LSI. Using a soil loss tolerance principle, a fuzzy membership function of average annual soil loss (called soil loss index, SLI) was established, leading to compatibility between LSI and SLI for data integration. LMUs were then derived from various combinations of LSI and SLI. The methodology developed shows the significance of the model for refining available land suitability evaluation systems, which take no account of expected land degradation (from erosion) due to a nominated land use. It also provides a valuable guideline for cost-effective GIS applications in the identification and assessment of homogeneous land units, using available spatial information sets, at a finer scale.     

耕作方式对紫色水稻土农田生态系统CH4和N2O排放的影响

以位于西南大学农业部重庆紫色土生态环境重点野外科学观测试验站内1990年设立的长期免耕试验田为研究对象,采用静态暗箱/气相色谱法,对传统的冬水田平作（CT）及由其改良而成的水旱轮作（CTR）、厢作免耕（NTP）和垄作免耕（NTR）等农田生态系统CH4和N2O的排放进行了连续1 a的田间原位观测研究.结果表明,传统的CT处理中,CH4和N2O主要排放时期为水稻种植季,该时期的持续时间仅占全年的27.1%,但2种温室气体的总排放量分别占全年的77.6%和55.0%;耕作制度改良后,CH4排放降低而N2O排放增加.不同耕作方式下CH4的年平均排放通量[以CH4计,mg.（m2.h）-1]为CT（2.96±0.04）〉NTR（1.83±0.21）〉NTP（1.42±0.01）〉CTR（0.96±0.09）,CT处理的CH4排放极显著高于CTR和NTP处理（P〈0.01）,显著高于NTR处理（P〈0.05）;N2O的年平均排放通量[以N2O计,μg.（m2.h）-1]依次为CTR（123.6±47.1）〉NTR（115.2±22.1）〉NTP（100.5±25.8）〉CT（81.3±13.5）,CTR处理N2O的排放显著高于CT（P〈0.05）.通过对不同时间尺度（20、100及500 a）2种温室气体综合全球增温潜势（global warming potential,GWP）的计算,可以发现,改良后的3种耕作方式对CH4和N2O的综合GWP有一定的减排作用,无论时间尺度长短,4种耕作处理全年所排放的CH4和N2O所产生的综合GWP均为CT〉NTR〉NTP〉CTR.因此,耕作方式的改良对紫色水稻土农田生态系统中CH4和N2O综合GWP减排有着明显的效果.     

A geostatistical approach for mapping thematic classification accuracy and evaluating the impact of inaccurate spatial data on ecological model predictions

Spatial information in the form of geographical information system coverages and remotely sensed imagery is increasingly used in ecological modeling. Examples include maps of land cover type from which ecologically relevant properties, such as biomass or leaf area index, are derived. Spatial information, however, is not error-free: acquisition and processing errors, as well as the complexity of the physical processes involved, make remotely sensed data imperfect measurements of ecological attributes. It is therefore important to first assess the accuracy of the spatial information being used and then evaluate the impact of such inaccurate information on ecological model predictions. In this paper, the role of geostatistics for mapping thematic classification accuracy through integration of abundant image-derived (soft) and sparse higher accuracy (hard) class labels is presented. Such assessment leads to local indices of map quality, which can be used for guiding additional ground surveys. Stochastic simulation is proposed for generating multiple alternative realizations (maps) of the spatial distribution of the higher accuracy class labels over the study area. All simulated realizations are consistent with the available pieces of information (hard and soft labels) up to their validated level of accuracy. The simulated alternative class label representations can be used for assessing joint spatial accuracy, i.e., classification accuracy regarding entire spatial features read from the thematic map. Such realizations can also serve as input parameters to spatially explicit ecological models; the resulting distribution of ecological responses provides a model of uncertainty regarding the ecological model prediction. A case study illustrates the generation of alternative land cover maps for a Landsat Thematic Mapper (TM) subscene, and the subsequent construction of local map quality indices. Simulated land cover maps are then input into a biogeochemical model for assessing uncertainty regarding net primary production (NPP).