A climate-change vulnerability and adaptation assessment for Brazil's protected areas

Brazil hosts the largest expanse of tropical ecosystems within protected areas (PAs), which shelter biodiversity and support traditional human populations. We assessed the vulnerability to climate change of 993 terrestrial and coastal-marine Brazilian PAs by combining indicators of climatic-change hazard with indicators of PA resilience (size, native vegetation cover, and probability of climate-driven vegetation transition). This combination of indicators allows the identification of broad climate-change adaptation pathways. Seventeen PAs (20,611 km²) were highly vulnerable and located mainly in the Atlantic Forest (7 PAs), Cerrado (6), and the Amazon (4). Two hundred fifty-eight PAs (756,569 km²), located primarily in Amazonia, had a medium vulnerability. In the Amazon and western Cerrado, the projected severe climatic change and probability of climate-driven vegetation transition drove vulnerability up, despite the generally good conservation status of PAs. Over 80% of PAs of high or moderate vulnerability are managed by indigenous populations. Hence, besides the potential risks to biodiversity, the traditional knowledge and livelihoods of the people inhabiting these PAs may be threatened. In at least 870 PAs, primarily in the Atlantic Forest and Amazon, adaptation could happen with little or no intervention due to low climate-change hazard, high resilience status, or both. At least 20 PAs in the Atlantic Forest, Cerrado, and Amazonia should be targeted for stronger interventions (e.g., improvement of ecological connectivity), given their low resilience status. Despite being a first attempt to link vulnerability and adaptation in Brazilian PAs, we suggest that some of the PAs identified as highly or moderately vulnerable should be prioritized for testing potential adaptation strategies in the near future.     

A hybrid model for human factor analysis in process accidents: FBN-HFACS

Human factors are the largest contributing factors to unsafe operation of the chemical process systems. Conventional methods of human factor assessment are often static, unable to deal with data and model uncertainty, and to consider independencies among failure modes. To overcome the above limitations, this paper presents a hybrid dynamic human factor model considering Human Factor Analysis and Classification System (HFACS), intuitionistic fuzzy set theory, and Bayesian network. The model is tested on accident scenarios which have occurred in a hot tapping operation of a natural gas pipeline. The results demonstrate that poor occupational safety training, failure to implement risk management principles, and ignoring reporting unsafe conditions were the factors that contributed most failures causing accident. The potential risk-based safety measures for preventing similar accidents are discussed. The application of the model confirms its robustness in estimating impact rate (degree) of human factor induced failures, consideration of the conditional dependency, and a dynamic and flexible modelling structure.     

Modeling of a sequencing batch reactor treating municipal wastewater using multi-layer perceptron and radial basis function artificial neural networks

A sequencing batch reactor was modeled using multi-layer perceptron and radial basis function artificial neural networks (MLPANN and RBFANN). Then, the effects of influent concentration (IC), filling time (FT), reaction time (RT), aeration intensity (AI), SRT and MLVSS concentration were examined on the effluent concentrations of TSS, TP, COD and NH₄⁺-N. The results showed that the optimal removal efficiencies would be obtained at FT of 1 h, RT of 6 h, aeration intensity of 0.88 m³/min and SRT of 30 days. In addition, COD and TSS removal efficiencies decreased and TP and NH₄⁺-N removal efficiencies did not change significantly with increases of influent concentration. The TSS, TP, COD and NH₄⁺-N removal efficiencies were 86%, 79%, 94% and 93%, respectively. The training procedures of all contaminants were highly collaborated for both RBFANN and MLPANN models. The results of training and testing data sets showed an almost perfect match between the experimental and the simulated effluent of TSS, TP, COD and NH₄⁺-N. The results indicated that with low experimental values of input data to train ANNs the MLPANN models compared to RBFANN models are more precise due to their higher coefficient of determination (R²) and lower root mean squared errors (RMSE) values.     

可持续旅游及其区域实现途径探讨—以井冈山风景名胜区为例

可持续旅游是 80年代中期以后提出的关于旅游业发展的新思想。经过十多年的不断拓展深化 ,已经得到世界各国的广泛认同 ,并作为跨世纪旅游业发展的战略指导思想。本文从可持续旅游的由来和对可持续旅游内涵实质的界定角度出发 ,结合可持续旅游实现途径的探讨 ,以井冈山风景名胜区为例 ,对风景区旅游业可持续发展进行了深入的探讨 ,为景区的发展规划提出了战略性构想 ,以期能对井冈山风景名胜区旅游资源的可持续利用和旅游业的可持续发展起到抛砖引玉的作用     

新时期区域公共管理创新

信息社会发展与全球化趋势，出现了区域集群、区域竞争、区域创新、学习区域等新特征，给区域管理者带来了新的挑战。区域发展需要创新，区域公共管理同样需要创新。本文从新公共管理、区域创新系统、区域核心竞争力、支持系统等方面对区域管理创新进行了探讨。     

长江三峡区间数字流域水系的构建

基于全球陆地一公里基础高程GLOBE数据 ,采用Martz和Garbrecht研制的数字高程流域水系模型自动提取长江三峡万县～宜昌区间的河网水系、各子流域分水线、河网与子流域编码及河网结构拓扑关系 ,从而构成该区域的数字流域和数字水系。结果表明该模型生成的水系是可以接受的 ,与 1:10万地形图上长江三峡万县～宜昌区间的水系一致 ,这为空间分布式模型的建立提供了必备的空间信息数据。最后 ,探讨了数字流域水系在流域生态学中的应用前景 ,构建的数字水系可为中尺度以上流域水体和水生生物的资源保护与合理利用提供决策平台 ,服务于社会经济的可持续发展。     

SUSTAINABILITY AT THE LOCAL LEVEL: MANAGEMENT TOOLS AND MUNICIPAL TAX INCENTIVE MODEL

The implementation of sustainable development may seem a simple concept when written on paper. However to carry-out long term actions put forward by the Agenda 21 (AG21) at the local level represents one of the main challenges as municipal governments in general do not have the capacity to effectively implement the process. Regional environmental assessment (REA) has shown to be effective in supporting decision-making not only to correct environmental problems due to past unsustainable social-economic developments but also help local governments to implement sustainable actions. However this requires long-term investments of AG21 plans and projects. The allocation of regular and consistent financial resources is one of the main ingredients for the sustainable development process. But traditional plans and projects financed by national and/or international funds may not be sustainable in the long-term because they become dependent on external funding. Research demonstrate that innovative economic instruments such as ecotaxes represent a feasible alternative to sponsor local sustainability because taxes are collected permanently by the government and could be invested in continuous actions. Ecotaxes experiences have provided important reference to structure a municipal incentive model (MIM) to sponsor AG21’s environmental plans and projects on a long-term (permanent) basis. However sustainable development cannot be solely through economic investments. A comprehensive municipal environmental management scheme (MEMS) has been established to support the incentive model. The scheme seeks not only to improve local institutional framework but also incentive continuous participation of local stakeholders at all levels of society. Participatory events and the provision of incentives (educational and financial) are key to motivate society to protect the environment and support actively the sustainable development process as emphasised in the RIO-92 Conference.     

区域性“减灾十年初步规划”的编制原则

本文简要介绍区域性“减灾十年初步规划”编制的一般原则，包括规划编制的意义、目的、编制顺序和规划应注意的几个方面，并提出规划成果的实施意见。可供各地编制规划时参考。     

外商投资的区位变动分析

文章利用1983—2000年的统计数据，通过比较分析方法，分析了我国外商投资区位的转移及其影响因素的变化，综合评价了我国中部5省、华东和西部的区位优势，提出了有利于吸引外商投资的建议。     

Phosphate recovery with granular acid-activated neutralized red mud: Fixed-bed column performance and breakthrough curve modelling

Granular acid-activated neutralized red mud (AaN-RM) has been successfully prepared with good chemical stability and physical strength. However, its potential for industrial application remains unknown. Therefore, the performance of granular AaN-RM for phosphate recovery in a fixed-bed column was investigated. The results demonstrated that the phosphate adsorption performance of granular AaN-RM in a fixed-bed column was affected by various operational parameters, such as the bed depth, flow rate, initial solution pH and initial phosphate concentration. With the optimal empty-bed contact time (EBCT) of 24.27 min, the number of processed bed volumes and the phosphate adsorption capacity reached 496.95 and 84.80 mg/g, respectively. Then, the saturated fixed-bed column could be effectively regenerated with a 0.5 mol/L HCl solution. The desorption efficiency remained as high as 83.45% with a low weight loss of 3.57% in the fifth regeneration cycle. In addition, breakthrough curve modelling showed that a 5-9-1 feed-forward artificial neural network (ANN) could be effectively applied for the optimization of the fixed-bed adsorption system; the coefficient of determination (R²) and the root mean square error (RMSE) evaluated on the validation-testing data were 0.9987 and 0.0183, respectively. Therefore, granular AaN-RM fixed-bed adsorption exhibits promising potential for phosphate removal and recovery from polluted water.