考虑区域特点和车型差异的氢燃料电池汽车全生命周期减碳预测分析

发展氢燃料电池汽车是我国实现“双碳”战略的重要路径之一,目前我国多个区域正在推广应用包括乘用车、客车以及重卡在内的氢燃料电池汽车,如何量化研究未来不同车型和不同区域的氢燃料电池汽车减碳潜力成为如今的研究热点之一.基于全生命周期的评价方法,考虑了未来的汽车燃油经济性、电力碳排放因子、氢能碳排放因子和氢燃料电池汽车推广规模及制氢方式的区域差异,量化评价了不同类型的氢燃料电池汽车（FCV）、传统燃油汽车（ICEV）和纯电动汽车（BEV）的全生命周期碳排放量（以CO₂当量计）,对比分析了氢燃料电池汽车在不同时间及不同区域的减碳潜力,并对百公里氢耗量进行了不确定性分析.结果发现,到2025年氢燃料电池客车的全生命周期碳排放比传统燃油客车降低36.0%,而氢燃料电池重卡相较于传统燃油重卡并没有减碳效益.随着未来我国氢能来源结构的不断优化,到2035年氢燃料电池重卡的全生命周期碳排放比传统燃油重卡降低36.5%,相较于乘用车和客车两种车型,其减碳效益是最明显的.以2035年京津冀示范群为例,随着百公里氢耗量降低20%,FCV乘用车、客车和重卡的减碳规模分别增加了7.29%、9.93%和19.57%.因此建议氢燃料电池汽车推广应短期以客车为主,长期以重卡为主,乘用车推广作为补充.分区域和分阶段推广氢燃料电池汽车更有助于推进我国汽车领域的低碳化进程.     

GLOBAL CLIMATE CHANGE AND PUBLIC PERCEPTION: THE CHALLENGE OF TRANSLATION1

ABSTRACT: Global climate change is examined from the perspective of its relevancy and urgency as a public policy issue. Interpreting from literature specific to investigations into public awareness and concern, climate change is seen as a legitimate though less than urgent issue. The literature reveals that the general public holds surprising misconceptions about the processes contributing to climate change, including failure to grasp the fundamental connection to CO₂. General ambivalence is also suggested from the results of two surveys conducted by The Groundwater Foundation. They first asked participants in a recent Groundwater Guardian Conference to rate levels of discussion and concern for water resources implications in the participants' communities. A second survey polled national water resource organizations about the extent climate change has been a focus of their educational, investigative, or advocacy efforts. The paper concludes by describing basic barriers to stimulating public response to climate change, which education about the issue should address, and by offering a model to educate and involve citizens based on the Groundwater Guardian program developed by the The Groundwater Foundation.     

Choice of stakeholder groups and members in multicriteria decision models

Simplistic economic objectives such as maximisation of producer profits are of little relevance in generating information to assist in the management of natural resources beyond the individual firm level. To provide data and information to support decision-making in natural resource management, it is necessary to take into account the views of various stakeholder groups and the multiple objectives of each group, through the use of some form of multicriteria analysis (MCA). Important decisions arise in the choice of stakeholder, since this will influence the management advice generated. Many groups and individuals can be affected by resource management decisions, but it would be impractical to attempt to identify the objectives and estimate their importance for each group. Also, questions arise concerning whether or not to include government agencies (which represent the broader community) and researchers as stakeholders. A further issue concerns choosing representative samples of stakeholder groups, from which to obtain preference data. Discussions with modellers and a reading of the literature would suggest that the choice of stakeholder groups and representatives is conducted haphazardly and is perhaps biased, and that a more systematic approach is needed. This article explores the above issues with reference to a number of multicriteria analyses, including local studies.     

Incorporating multidimensional behavior into a risk management tool for a critically endangered and migratory species

Conservation of migratory species exhibiting wide-ranging and multidimensional behaviors is challenged by management efforts that only utilize horizontal movements or produce static spatial–temporal products. For the deep-diving, critically endangered eastern Pacific leatherback turtle, tools that predict where turtles have high risks of fisheries interactions are urgently needed to prevent further population decline. We incorporated horizontal–vertical movement model results with spatial–temporal kernel density estimates and threat data (gear-specific fishing) to develop monthly maps of spatial risk. Specifically, we applied multistate hidden Markov models to a biotelemetry data set (n = 28 leatherback tracks, 2004–2007). Tracks with dive information were used to characterize turtle behavior as belonging to 1 of 3 states (transiting, residential with mixed diving, and residential with deep diving). Recent fishing effort data from Global Fishing Watch were integrated with predicted behaviors and monthly space-use estimates to create maps of relative risk of turtle–fisheries interactions. Drifting (pelagic) longline fishing gear had the highest average monthly fishing effort in the study region, and risk indices showed this gear to also have the greatest potential for high-risk interactions with turtles in a residential, deep-diving behavioral state. Monthly relative risk surfaces for all gears and behaviors were added to South Pacific TurtleWatch (SPTW) ( https://www.upwell.org/sptw ), a dynamic management tool for this leatherback population. These modifications will refine SPTW's capability to provide important predictions of potential high-risk bycatch areas for turtles undertaking specific behaviors. Our results demonstrate how multidimensional movement data, spatial–temporal density estimates, and threat data can be used to create a unique conservation tool. These methods serve as a framework for incorporating behavior into similar tools for other aquatic, aerial, and terrestrial taxa with multidimensional movement behaviors.     

Assigning trend-based conservation status despite high uncertainty

Estimates of temporal trends in species’ occupancy are essential for conservation policy and planning, but limitations to the data and models often result in very high trend uncertainty. A critical source of uncertainty that degrades scientific credibility is that caused by disagreement among studies or models. Modelers are aware of this uncertainty but usually only partially estimate it and communicate it to decision makers. At the same time, there is growing awareness that full disclosure of uncertainty is critical for effective translation of science into policies and plans. But what are the most effective approaches to estimating uncertainty and communicating uncertainty to decision makers? We explored how alternative approaches to estimating and communicating uncertainty of species trends could affect decisions concerning conservation status of freshwater fishes. We used ensemble models to propagate trend uncertainty within and among models and communicated this uncertainty with categorical distributions of trend direction and magnitude. All approaches were designed to fit an established decision-making system used to assign species conservation status by the New Zealand government. Our results showed how approaches that failed to fully disclose uncertainty, while simplifying the information presented, could hamper species conservation or lead to ineffective decisions. We recommend an approach that was recently used effectively to communicate trend uncertainty to a panel responsible for setting the conservation status of New Zealand's freshwater fishes.     

Understanding Managers’ Views of Global Environmental Risk

This research investigated managers’ views of two global environmental risks: climate change and loss of biodiversity. The intent was to understand why different managers place varying levels of attention and priority on these issues. The data came from in-depth interviews with 28 senior corporate managers across Canada and a range of sectors, although most were employed in the energy sector. Approximately half had direct environmental responsibilities and half had other management duties. Grounded theory was used to collect and analyze the data. From the results, a theoretical framework was constructed to explain important factors that can influence managers’ mental models of environmental risk. Four factors relevant to managers’ appraisal of the threat of environmental risk include: (1) salience, (2) intrinsic value of nature, (3) knowledge, and (4) perceived resilience of nature. In addition, four factors relevant to managers’ view of the appeal of a particular response strategy were: (1) avoidability, (2) perceived costs and benefits, (3) fairness and equity, and (4) effectiveness. The time horizon for decision making was seen as being important in both portions of the mental model.     

Modelling the conversion of Colombian lowland ecosystems since 1940: drivers, patterns and rates

In biologically mega-diverse countries that are undergoing rapid human landscape transformation, it is important to understand and model the patterns of land cover change. This problem is particularly acute in Colombia, where lowland forests are being rapidly cleared for cropping and ranching. We apply a conceptual model with a nested set of a priori predictions to analyse the spatial and temporal patterns of land cover change for six 50-100 km(2) case study areas in lowland ecosystems of Colombia. Our analysis included soil fertility, a cost-distance function, and neighbourhood of forest and secondary vegetation cover as independent variables. Deforestation and forest regrowth are tested using logistic regression analysis and an information criterion approach to rank the models and predictor variables. The results show that: (a) overall the process of deforestation is better predicted by the full model containing all variables, while for regrowth the model containing only the auto-correlated neighbourhood terms is a better predictor; (b) overall consistent patterns emerge, although there are variations across regions and time; and (c) during the transformation process, both the order of importance and significance of the drivers change. Forest cover follows a consistent logistic decline pattern across regions, with introduced pastures being the major replacement land cover type. Forest stabilizes at 2-10% of the original cover, with an average patch size of 15.4 (+/-9.2)ha. We discuss the implications of the observed patterns and rates of land cover change for conservation planning in countries with high rates of deforestation.     

不同类型有机化合物理论化学耗氧量的数学计算模型

根据有机物与氧反应的化学平衡,建立了计算不同类型有机物理论化学耗氧量的通用数学模型,计有三种表式：有机物摩尔理论COD;单位质量有机物理论COD;体积为V升、理论COD浓度为Cmg/L的有机化合物溶液所含该有机化合物的量（x,g）。对大多数模型进行了实验验证,模型计算值与实测值间的最大相对误差在4％左右,说明这些模型推导合理。     

Development of models for predicting toxicity from sediment chemistry by partial least squares-discriminant analysis and counter-propagation artificial neural networks

There is strong interest in developing tools to link chemical concentrations of contaminants to the potential for observing sediment toxicity that can be used in initial screening-level sediment quality assessments. This paper presents new approaches for predicting toxicity in sediments, based on 10-day survival tests with marine amphipods, from sediment chemistry, by means of the application of Partial Least Squares-Discriminant Analysis (PLS-DA) and Counter-propagation Artificial Neural Networks (CP-ANNs) to large historical databases of chemical and toxicity data. The exploration of the internal structure of the developed models revealed inherent limitations of predicting toxicity from common chemical analyses of bulk contaminant concentrations. However, the results obtained in the validation of these models combined relevant values of non-error classification rate, sensitivity and specificity of, respectively, 76, 87 and 73% with PLS-DA and 92, 75 and 97% with CP-ANNs, outperforming the results reported for previous approaches.     

Linking desorption kinetics to phenanthrene biodegradation in soil

The desorption of polycyclic aromatic hydrocarbons (PAHs) often exhibits a biphasic profile similar to that observed for biodegradation whereby an initial rapid phase of degradation or desorption is followed by a phase of much slower transformation or release. Most investigations to-date have utilised a polymeric sorbent, such as Tenax, to characterise desorption, which is methodologically unsuitable for the analysis of soil. In this study, desorption kinetics of ¹⁴C-phenanthrene were measured by consecutive extraction using aqueous solutions of hydroxypropyl-β-cyclodextrin (HPCD). The data indicate that the fraction extracted after 24 h generally approximated the linearly sorbed, rapidly desorbing fraction (F_rap), calculated using a three-compartment model. A good linear correlation between phenanthrene mineralised and F_rap was observed (r² = 0.89; gradient = 0.85; intercept = 8.20). Hence HPCD extraction (24 h) and first-order three-compartment modelling appear to provide an operationally straightforward tool for estimating mass-transfer limited biodegradation in soil.