基于住房价格的通勤碳排放空间分异——以济南市为例

住房价格能够影响居民的居住决策,进而影响其通勤碳排放。为研究住房价格与通勤碳排放的内在关系,构建住房价格影响个体通勤碳排放的理论模型,并利用“个体—街道”两水平线性模型,对济南市居民出行调查数据进行实证检验。研究发现：（1）通勤碳排放呈现出“中心低碳化、外围高碳化”,且外围趋于分化的空间格局。（2）住房价格通过虹吸效应影响居民的碳排放。具体表现为住房价格与碳排放负相关,外围低房价吸引居住者,而居住者的远程机动通勤导致外围高值碳排放;但住房价格的边际增碳程度随着远离市中心而先缓（距市中心 5 km）后增（距市中心5 km及以上）。（3）外围工资收入对虹吸效应起调节作用。工资水平较高的外围区域有利于实现职住平衡,抑制了虹吸效应,进而分化为碳排放的冷点区,工资水平较低的外围区域则分化为碳排放的热点区。研究认为,应通过多中心空间发展战略、提高居民的就业可达性、优化针对公租房的公共交通供给等措施,引导居民低碳通勤。     

明渠中有机质微粒沉降过程的随机游走模拟

基于明渠流动的主要特点,考虑紊动强度的垂向非均匀性,及颗粒运动的游荡效应（loitering effect）影响,对微粒运动基本方程进行改进,建立了明渠非均匀紊流中考虑游荡效应的随机游走模型,对明渠中微粒的沉降损失进行了模拟分析.模拟结果显示,不考虑游荡效应影响时,明渠中微粒的沉降损失率可用微粒沉速与水深之比计算;而在游荡效应影响下,微粒沉降损失率会发生约18%~27%的下降,下降百分比与均匀紊流中微粒沉速在游荡效应影响下的折减百分比渐近值（19~25%）基本一致.本文结论基于不考虑微粒重悬浮、游荡效应为紊流对微粒沉降的主导影响机理等前提,主要适用于对明渠中细小有机质微粒沉降至床底过程更准确的计算分析.     

建立在生命周期分析之上的城市机动车能源结构优化

针对我国城市能源供需矛盾日益恶化、环境污染日益严重的现状,优化城市机动车能源结构,缓解城市机动车对传统能源的使用压力,减少尾气排放,具有十分重要的意义.因此,本文以成都市为例,采用线性优化技术,通过确定各种车用能源生命周期内的能源消耗及排放、各种能源车辆的经济成本等,分析得到成都市整个城区范围内能耗最低、排放最小的各种能源机动车数量比例.结果表明,成都市各种能源机动车的数量比例随所选目标函数的不同而有所变化.为实现总能耗最小,各种能源机动车的比例按汽油、柴油、纯电动、电力/汽油混合动力、CNG单燃料、CNG/汽油双燃料、LPG单燃料、及LPG/汽油双燃料等划分应分别68.6%、11.4%、3.7%、6.1%、5.0%、5.0%、0.1%、0.1%.与机动车数量比例优化前相比,优化后总能源消耗量、石油消耗量分别平均减少了11.5%、13.8%.除PM₁₀及SO_x排放量有所增加外,其他气体的排放均有所减少,如CO₂、VOC、CO及NO_x的平均排放量分别减少了10.6%、13.5%、13.5%及16.5%.这是因为机动车能源结构优化后,纯电动汽车及混合燃油汽车的比例有所增加,由于这两类汽车都需要经常充电从而增加了电网的压力.而我国发电技术主要采用火力发电,发电过程将会产生大量的PM₁₀及SO_x.本研究的成果可用于环境决策者制定有效的交通能源政策,达到城市可持续发展的目的.     

Addressing onsite sampling in recreation site choice models

Independent experts and politicians have criticized statistical analyses of recreation behavior, which rely upon onsite samples due to their potential for biased inference. The use of onsite sampling usually reflects data or budgetary constraints, but can lead to two primary forms of bias in site choice models. First, the strategy entails sampling site choices rather than sampling individuals—a form of bias called endogenous stratification. Under these conditions, sample choices may not reflect the site choices of the true population. Second, exogenous attributes of the individuals sampled onsite may differ from the attributes of individuals in the population—the most common form in recreation demand is avidity bias. We propose addressing these biases by combining two the existing methods: Weighted Exogenous Stratification Maximum Likelihood estimation and propensity score estimation. We use the National Marine Fisheries Service's Marine Recreational Fishing Statistics Survey to illustrate methods of bias reduction, employing both simulated and empirical applications. We find that propensity score based weights can significantly reduce bias in estimation. Our results indicate that failure to account for these biases can overstate anglers' willingness to pay for improvements in fishing catch, but weighted models exhibit higher variance of parameter estimates and willingness to pay.     

Assessing the effects of disease and bleaching on Florida Keys corals by fitting population models to data

Coral diseases have increased in frequency over the past few decades and have important influences on the structure and composition of coral reef communities. However, there is limited information on the etiologies of many coral diseases, and pathways through which coral diseases are acquired and transmitted are still in question. Furthermore, it is difficult to assess the impacts of disease on coral populations because outbreaks often co-occur with temperature-induced bleaching and anthropogenic stressors. We developed spatially explicit population models of coral disease and bleaching dynamics to quantify the impact of six common diseases on Florida Keys corals, including aspergillosis, dark spots, white band, white plague, white patch, and Caribbean yellow band. Models were fit to an 8-year data set of coral abundance, disease prevalence, and bleaching prevalence. Model selection was used to assess alternative pathways for disease transmission, and the influence of environmental stressors, including sea temperature and human population density, on disease prevalence and coral mortality. Classic disease transmission from contagious to susceptible colonies provided the best-fit model only for aspergillosis. For other diseases, external disease forcing, such as through a vector or directly from pathogens in the environment, provided the best fit to observed data. Estimates of disease reproductive ratio values (R₀) were less than one for each disease, indicating coral colonies were below densities required for diseases to become established through contagious spread alone. Incidences of white band and white patch disease were associated with greater susceptibility or slower recovery of bleached colonies, and no disease outbreaks were associated with periods of elevated sea temperatures alone. Projections of best-fit models indicated that, atleast during the period of this study, disease and bleaching did not have substantial impacts on populations and impaired rates of population growth appeared to be attributable to other stressors. By applying epidemiological models to field data, our study gives qualitative insights into the dynamics of coral diseases, relative stressor impacts, and directions for future research.     

Modeling an exploited rocky coastal ecosystem: Bahia Tortugas, Mexico

A trophic structure model of the rocky coastal ecosystem in Bahia Tortugas, Mexico was constructed using Ecopath software to represent the main biomass flows in the system. Data for the model came from field observations (biomass estimates, stomach contents, and ecological observations for sea snails, abalones, lobster, some demersal finfishes, and macroalgae) carried out through ten field trips from 2006 to 2008. The results provide a snapshot of how the ecosystem operates. The model considers 23 functional groups. The total system throughput was 553 t/km²/year, 57% corresponds to internal consumption, 28% to respiration, 14% becomes detritus, and only 1% is removed through commercial fishing. The model suggests that even for exploited populations, predation and competition are heavier stresses than current fishing effort; however, because spiny lobster showed the second highest keystoneness’ index value, increasing fishing pressure on this group could strongly impact the entire ecosystem. We believe that this model has the potential to support management by allowing the exploration of the potential impacts of different fishing decisions at ecosystem level.     

Combining state and transition models with dynamic Bayesian networks

Bashari et al. (2009) propose combining state and transition models (STMs) with Bayesian networks for decision support tools where the focus is on modelling the system dynamics. There is already an extension of Bayesian networks - so-called dynamic Bayesian networks (DBNs) - for explicitly modelling systems that change over time, that has also been applied in ecological modelling. In this paper we propose a combination of STMs and DBNs that overcome some of the limitations of Bashari et al.’s approach including providing an explicit representation of the next state, while retaining its advantages, such an the explicit representation of transitions. We then show that the new model can be applied iteratively to predict into the future consistently with different time frames. We use Bashari et al.’s rangeland management problem as an illustrative case study. We present a comparative complexity analysis of the different approaches, based on the structure inherent in the problem being modelled. This analysis showed that any models that explicitly represent all the transitions only remain tractable when there are natural constraints in the domain. Thus we recommend modellers should analyse these aspects of their problem before deciding whether to use the framework.     

宁波市农村生活污水处理模式研究

对现有农村污水治理方式进行了总结和效果评价。提出了适合宁波地区农村污水治理的4类模式。分别是污废合流的集中模式、分散模式,污废分流的分散模式、过渡模式。分析了模式选择的影响因素,分别是人口规模、集聚模式、地形、地质条件、功能区域,并对目标村庄进行亍相应分类,建立数学模型探讨了集中与分散模式的经济距离以及集中模式下户均投资的控制距离,最后根据研究成果对首批实施的14个行政村25个自然村的生活污水治理模式进行了选择。     

River environmental decision support system development for Suzhou Creek in Shanghai

The Suzhou Creek Rehabilitation Project (SCRP) is one of the largest water-related environmental rehabilitation schemes ever undertaken in the vicinity of Shanghai, China. This paper details the development and application of a River Environmental Decision Support System (REDSS) for scientific planning and decision-making on the Suzhou Creek project, and illustrates the flexibility of the REDSS framework. We developed the following components: (1) a GIS-based analysis employing Component technology; (2) a "data mart" for multi-dimensional, multi-level, integrated, dynamic, and flexible data querying; and (3) a set of hydrodynamic and water quality models which can simulate complex tidal river networks. In addition, we detail how a water quality assessment model is embedded into the REDSS by employing an Identification Index Method. With the REDSS, all GIS and non-GIS components are integrated seamlessly and data from different sources can be queried simultaneously. This allows for various scenarios to be simulated and analyzed in advance to predict and assess the effects of proposed engineering and management measures. Generated information can thus support effective decisions. All operations of the REDSS can be implemented conveniently through user-friendly interfaces. The function of the REDSS framework is demonstrated through an application to Suzhou Creek. Because the REDSS characteristics are quite general, it may be applied in different geographic regions.     

Herbicide Transport in Goodwater Creek Experimental Watershed: II. Long‐Term Research on Acetochlor,Alachlor, Metolachlor,and Metribuzin1

Lerch, R.N., E.J. Sadler, C. Baffaut, N.R. Kitchen, and K.A. Sudduth, 2010. Herbicide Transport in Goodwater Creek Experimental Watershed: II. Long‐Term Research on Acetochlor, Alachlor, Metolachlor, and Metribuzin. Journal of the American Water Resources Association (JAWRA) 1‐15. DOI: 10.1111/j.1752‐1688.2010.00504.x Abstract: Farmers in the Midwestern United States continue to be reliant on soil‐applied herbicides for weed control in crop production, and herbicide contamination of streams remains an environmental problem. The main objective of this study was to analyze trends in concentration and load of acetochlor, alachlor, metolachlor, and metribuzin in Goodwater Creek Experimental Watershed (GCEW) from 1992 to 2006. A secondary objective was to document the effects of best management practices (BMPs) implemented within GCEW on herbicide transport trends. Median relative herbicide loads, as a percent of applied, were 3.7% for metolachlor, 1.3% for metribuzin, 0.36% for acetochlor, and 0.18% for alachlor. The major decrease in alachlor use and increase in acetochlor use caused shifts in flow‐weighted concentrations that were observed over the entire concentration range. The smaller decrease in metolachlor use led to a consistent decreasing time trend only for the upper end of the concentration distribution. Metribuzin also showed moderate decreases in concentration with time since 1998. Annual loads were generally correlated to second quarter discharge. Despite extensive education efforts in the watershed, conservation BMPs within GCEW were mainly implemented to control erosion, and therefore had no discernable impact on reducing herbicide transport. Overall, changes in herbicide use and second quarter discharge had the greatest effect on trends in flow‐weighted concentration and annual load.