Hydrolyzed Al(Ⅲ) clusters: Speciation stability of nano-Al13

Pure nano-Al13 and aggregates at various concentrations were prepared to examine the particle size effect of coagulation with inorganic polymer fiocculant. The property and stability of various species formed were characterized using Infrared, 27Al-NMR,photo correlation spectroscopy (PCS), and Ferron assay. Results showed that concentration and temperature exhibited different roles on the stability of Al13. The quantity of Alb species analyzed by ferron assay in the initial aging period corresponded well with that of Al13, which has been confirmed in a dimension range of 1-2 nm by PCS. Al13 solutions at high concentrations (0.5-2.11 mol/L)were observed to undergo further aggregation with aging. The aggregates with a wide particle size distribution would contribute to the disappeared/decreased Al13 basis on the 27Al-NMR spectrum, whereas a part of Al13 would still remain as Alb. At low concentrations,Al13 solution was quite stable at normal temperature, but lost its stability quickly when heating to 90°C.     

基于鱼类保护目标的太子河环境流量研究

环境流量是流域水资源合理配置的基础.因此,本文借鉴FLOWS法,以太子河重要鱼类为保护目标,构建了流量组分与鱼类生态需求关系模型.同时,结合栖息地指标与流量关系曲线,计算了包含基流、脉冲流、平滩流和漫滩流4种组分在内的太子河环境流量.结果表明：太子河本溪、辽阳、唐马寨河段鱼类保护年基流量分别为2.93×108、3.12×108、2.88×108m3;现状径流总体可以满足年基流量的要求,但水文过程需要通过水库调度以匹配鱼类生态过程.推荐的各河段脉冲流、平滩流和漫滩流的量级、频率、历时、出现时间等水文参数,可以体现环境流量组分与自然径流过程的一致性要求.该研究可为太子河流域水库生态调度提供理论依据.     

Managing dependencies in forest offset projects: toward a more complete evaluation of reversal risk

Although forest carbon offsets can play an important role in the implementation of comprehensive climate policy, they also face an inherent risk of reversal. If such risks are positively correlated across projects, it can affect the integrity of larger project portfolios and potentially the entire offsets program. Here, we discuss three types of risks that could affect forest offsets—fat tails, micro-correlation, and tail dependence—and provide examples of how they could present themselves in a forest offset context. Given these potential dependencies, we suggest several new risk management approaches that take into account dependencies in reversal risk across projects and which could help guard the climate integrity of an offsets program. We also argue that data collection be included as an integral part of any offsets program so that disturbance-related dependencies may be identified and managed as early and to the greatest extent possible.     

A dominant coalition and policy change: an analysis of shale oil and gas politics in India

This paper identifies the coalitions involved in the topic of shale oil and gas development in India and identifies the circumstances surrounding a change in policy in 2013 by the Ministry of Petroleum and Natural Gas to promote shale exploration. Using the Advocacy Coalition Framework as the theoretical lens, the data are collected primarily from newspaper articles from 2010 to 2015 to identify coalitions, including actors’ positions, priorities, and interactions. The findings show the presence of a dominant advocacy coalition in favor of shale oil and gas development with priorities about energy security and a regulatory framework. The findings indicate some internal coalition disagreement, but stronger internal coalition agreement. Policy change was preceded by a spike in disagreement internal to the dominant coalition. This paper shows how a change in a dominant coalition can precede a change in policy, offers a replicable method of identifying and measuring coalitions via newspaper content analysis, provides a rare application of the Advocacy Coalition Framework outside of North America and Western Europe, and provides evidence of support for shale oil and gas development in India.     

Instream Restoration to Improve the Ecohydrologic Function of a Subalpine Meadow: Pre‐implementation Modeling with HEC‐RAS

Vegetation in subalpine meadows in the Sierra Nevada Mountains is particularly vulnerable to lowering of groundwater levels because wet meadow vegetation is reliant upon shallow groundwater during the dry summer growing season. These ecosystems are especially vulnerable to channel incision as meadow aquifers are hydrologically connected to tributaries, and many have not yet recovered from previous anthropogenic influences. While instream restoration projects have become a common approach, lack of postrestoration monitoring and communication often result in a trial‐and‐error approach. In this study we demonstrate that preimplementation modeling of possible instream restoration solutions, chosen to raise stream stage and subsequently groundwater levels, is a useful tool for evaluating and comparing potential channel modifications. Modeling allows us to identify strategic locations and specific methods. Results show additional sediment depth and roughness on tributaries along with introduced woody debris (simulated by high roughness) on the Tuolumne River are the most effective means of raising stream stage. Results demonstrate that restoration efforts are most efficient in tributary streams. Managers and planners can more efficiently direct resources while minimizing the potential for negative impacts or failed restoration projects by modeling the possible effects of multiple restoration scenarios before implementation.     

Efficient Markov chain Monte Carlo sampling for hierarchical hidden Markov models

Traditional Markov chain Monte Carlo (MCMC) sampling of hidden Markov models (HMMs) involves latent states underlying an imperfect observation process, and generates posterior samples for top-level parameters concurrently with nuisance latent variables. When potentially many HMMs are embedded within a hierarchical model, this can result in prohibitively long MCMC runtimes. We study combinations of existing methods, which are shown to vastly improve computational efficiency for these hierarchical models while maintaining the modeling flexibility provided by embedded HMMs. The methods include discrete filtering of the HMM likelihood to remove latent states, reduced data representations, and a novel procedure for dynamic block sampling of posterior dimensions. The first two methods have been used in isolation in existing application-specific software, but are not generally available for incorporation in arbitrary model structures. Using the NIMBLE package for R, we develop and test combined computational approaches using three examples from ecological capture–recapture, although our methods are generally applicable to any embedded discrete HMMs. These combinations provide several orders of magnitude improvement in MCMC sampling efficiency, defined as the rate of generating effectively independent posterior samples. In addition to being computationally significant for this class of hierarchical models, this result underscores the potential for vast improvements to MCMC sampling efficiency which can result from combinations of known algorithms.