The costs and benefits of packaging waste management systems in Europe: the perspective of local authorities

Local authorities are generally in charge of household packaging waste management operations, particularly in countries with Green Dot schemes or similar extended producer responsibility systems. This leads to the need of establishing a system of financial transfers between the packaging industry and the local authorities (regarding the costs involved in selective collection and sorting). In the present study, the costs and benefits of recycling, from the perspective of local authorities, are compared for Portugal, Belgium and Italy (in Lombardia region), adopting the same economic–financial methodology. The results show that the industry is not paying the net cost of packaging waste management. If the savings attained by diverting packaging waste from other treatment operations are not considered, it seems that the industry should increase the financial support to local authorities. However, if the avoided costs with other treatments are considered as a benefit for local authorities, the costs are generally outweighed by the benefits, and the financial support could, therefore, be reduced.     

Impacts of Human Behavioral Heterogeneity on the Benefits of Probabilistic Flood Warnings: An Agent‐Based Modeling Framework

Flood forecasts and warnings are intended to reduce flood‐related property damages and loss of human life. Considerable research has improved flood forecasting accuracy (e.g., more accurate prediction of the occurrence of flood events) and lead time. However, the delivery of improved forecast information alone is not necessarily sufficient to reduce flood damage and loss of life, as people have varying responses and reactions to flood warnings. This study develops an agent‐based modeling framework that evaluates the impacts of heterogeneity in human behaviors (i.e., variation in behaviors in response to flood warnings), as well as residential density, on the benefits of flood warnings. The framework is coupled with a traffic model to simulate evacuation processes within a road network under various flood warning scenarios. The results show the marginal benefit associated with providing better flood warnings is significantly constrained if people behave in a more risk‐tolerant manner, especially in high‐density residential areas. The results also show significant impacts of human behavioral heterogeneity on the benefits of flood warnings, and thus stress the importance of considering human behavioral heterogeneity in simulating flood warning‐response systems. Further study is suggested to more accurately model human responses and behavioral heterogeneity, as well as to include more attributes of residential areas to estimate and improve the benefits of flood warnings.     

水土环境介质中阿特拉津修复过程研究进展

除草剂阿特拉津农用后的残留物会随地表径流或地下渗漏作用进入江河湖泊等自然水体,由于阿特拉津的环境内分泌干扰作用,其会造成水资源污染和水生态失衡。根据阿特拉津的生产和使用状况,将阿特拉津的污染对象分为土壤、市政污水、河流湖泊等地表水和地下水系统模块,分别阐述了这几种环境介质中阿特拉津的物理、化学和生物修复技术以及阿特拉津在修复过程中的变化特点,介绍了土壤在淋溶过程中阿特拉津的固定手段和今后污染水体中阿特拉津修复的研究重点。     

Social Demand for Ecosystem Services and Implications for Watershed Management

We performed a sociocultural preference assessment for a suite of ecosystem services provided by the Kiamichi River watershed in the south‐central United States, a region with intense water conflict. The goal was to examine how a social assessment of services could be used to weigh tradeoffs among water resource uses for future watershed management and planning. We identified the ecosystem services beneficiaries groups, analyzed perception for maintaining services, assessed differences in the importance and perceived trends for ecosystem services, and explored the perceived impact on ecosystem services arising from different watershed management scenarios. Results show habitat for species and water regulation were two ecosystem services all beneficiaries agreed were important. The main discrepancies among stakeholder groups were found for water‐related services. The identification of potential tradeoffs between services under different flow scenarios promotes a dynamic management strategy for allocating water resources, one that mitigates potential conflicts. While it is widely accepted the needs of all beneficiaries should be considered for the successful incorporation of ecosystem services into watershed management, the number of studies actually using the sociocultural perspective in ecosystem service assessment is limited. Our study demonstrates it is both possible and useful to quantify social demand of ecosystem services in watershed management.     

Two-stage vertex analysis method for planning electric power systems with greenhouse gas abatement consideration

This study presents a two-stage vertex analysis (TSVA) method for the planning of electric power systems (EPS) under uncertainty. TSVA has advantages in comparison to other optimization techniques. Firstly, TSVA can incorporate greenhouse gas (GHG) abatement policies directly into its optimization process, and, secondly, it can readily integrate inherent system uncertainties expressed as fuzzy sets and probability distributions directly into its modeling formulation and solution procedure. The TSVA method is applied to a case study of planning EPS and it is demonstrated how the TSVA efficiently identify optimal electricity-generation schemes that could help to minimize system cost under different GHG-abatement considerations. Different combinative considerations on the uncertain inputs lead to varied system costs and GHG emissions. Results reveal that the total electricity supply will rise up along with the time period due to the increasing demand and, at the same time, more non-fossil fuels should be used to satisfy the increasing requirement for GHG mitigation. Moreover, uncertainties in connection with complexities in terms of information quality (e.g., capacity, efficiency, and demand) result in changed electricity-generation patterns, GHG-abatement amounts, as well as system costs. Minimax regret (MMR) analysis technique is employed to identify desired alternative that reflects compromises between system cost and system-failure risk.     

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.