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81.
低碳城市是一种实现低碳经济、进行低碳生产与消费、形成低碳生活、建设良性与可持续发展的能源生态体系的城市模式。通过调控城市绿地系统、优化城市开放空间,有利于低碳城市理念下的生态城市建设,实现城市的可持续发展。首先对低碳城市建设与城市绿地系统优化的关系进行了分析;其次对郑州城市绿地系统建设存在的主要问题进行了探讨,借助AreGIS9.3软件分析了郑州市绿地服务区的影响范围;最后基于城市绿地系统优化原则提出四方面的优化建议——注重城市的生态设计;优化绿地系统的空间布局;实现“点”、“线”、“面”的有机结合;实施适度的绿地容量限制;发展立体绿化与推广绿色建筑材料的使用。 相似文献
82.
马贺 《中国环境管理干部学院学报》2008,18(1):26-28,35
建设绿色企业文化是秦皇岛港实现绿色发展的前提,对港口的发展有深远的意义和重要作用.秦皇岛港应从强化领导意识、提高职工素质、完善绿色制度体系、构建绿色企业形象等方面入手建设港口绿色企业文化. 相似文献
83.
《组织行为杂志》2017,38(7):996-1015
How do employees' perceptions and interpretations of organizational policies, practices, and procedures affect the enactment of their behavioral intentions? In a daily diary study, we examined the between‐persons relationship of corporate environmental strategy and pro‐environmental or “green” psychological climate; and whether green psychological climate moderates the within‐person relationship of employees' daily green behavioral intentions and their green behavior on the following day. To test our hypotheses, we collected survey data from 74 employees across 10 workdays. Results showed that corporate environmental strategy is positively related to green psychological climate that, in turn, moderates the relationship between green behavioral intentions and next‐day employee green behavior. Specifically, we found the relationship to be positive only when employees perceive a positive green psychological climate. We discuss implications of our findings for future research on employee green behavior and for organizations interested in encouraging employee green behavior. Copyright © 2017 John Wiley & Sons, Ltd. 相似文献
84.
绿色大学的建设是贯彻环境保护基本国策和实施可持续发展战略的重要举措之一。建立一套系统全面且便于操作的指标体系对绿色大学建设具有指导意叉。“绿色大学”建设围绕教育的核心,将可持续发展和环境保护的指导思想落实到大学的各项活动中、融入到大学教育的全过程。按目标层、准则层和指标层的思路构建绿色大学的评价指标体系。准则层由绿色教育、绿色校园、绿色科研、绿色实践和绿色办学构成,反映的是绿色校园建设所应包括的5大部分。指标层包括指标和主要参数,反映准则层的具体内容。 相似文献
85.
中国生态农业与绿色食品 总被引:8,自引:0,他引:8
本文从农业环境问题和食品安全性出发,阐述了中国生态农业的兴起及特点,绿色食品生产的要求,生态农业与绿色食品的关系。介绍了几种可用于开发绿色食品的优化生态模式。 相似文献
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R. M. Patel S. O. Prasher P. K. God R. Bassi 《Journal of the American Water Resources Association》2002,38(1):91-100
ABSTRACT: This study explores the applicability of Artificial Neural Networks (ANNs) for predicting salt build‐up in the crop root zone. ANN models were developed with salinity data from field lysimeters subirrigated with brackish water. Different ANN architectures were explored by varying the number of processing elements (PEs) (from 1 to 30) for replicate data from a 0.4 m water table, 0.8 m water table, and both 0.4 and 0.8 m water table lysimeters. Different ANN models were developed by using individual replicate treatment values as well as the mean value for each treatment. For replicate data, the models with twenty, seven, and six PEs were found to be the best for the water tables at 0.4 m, 0.8 m and both water tables combined, respectively. The correlation coefficients between observed salinity and ANN predicted salinity of the test data with these models were 0.89, 0.91, and 0.89, respectively. The performance of the ANNs developed using mean salinity values of the replicates was found to be similar to those with replicate data. Not only was there agreement between observed and ANN predicted salinity values, the results clearly indicated the potential use of ANN models for predicting salt build‐up in soil profile at a specific site. 相似文献
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Aslı Aksoy 《International Journal of Green Energy》2019,16(1):34-48
All economic sectors are associated with energy use; therefore, government organizations aim to supply sustainable energy for human needs and economic growth. In particular, increased environmental concerns of the public in Turkey have impacted policymaking for renewable energy (RE) management in Turkey. The primary objective for RE sources of the Turkish Ministry of Energy is to ensure that 30% of the share of electricity production is from RE resources in 2023. In this paper, the integrated multi-objective, multi-period linear programming model is presented to determine effective allocation of RE supply for seven different geographical regions in Turkey for the period of 2017 to 2024. The integrated model consists of two different stages. The first stage involves qualitative evaluations of RE sources for seven geographical regions. Analytical Hierarchy Process (AHP) is applied to determine criteria priorities and overall ratings of geographical regions across determined criteria for RE sources are computed. The second stage of the integrated model consists of a multi-objective, multi-period linear programming model. The proposed multi-objective linear programming model is coded in MPL (Mathematical Programming Language) and solved using the GUROBI 5.1.0 solver. The output of the integrated model presents the total supply amount of RE sources for geographical regions in planning period. The ε-constraints method is applied to compute the total supply amount of RE from geographical regions for the period of 2017 to 2024. In this study, a systematic decision-making model is generated to allocate renewable energy sources to the geographical regions. The presented model integrates qualitative evaluations and quantitative parameters of different geographical regions to determine the optimal supply amount of RE. The obtained results are consistent with the potential quantities of RE alternatives in geographical regions, regional specifications, and social requirements. 相似文献