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Big data: New tend to sustainable consumption research

机译:大数据:新趋势倾向于可持续消费研究

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摘要

Growing consumption has brought a series of environmental problems. Sustainable consumption patterns which could meet human needs, improve the quality of lives, and reduce pollutants in the product life cycle emerge and develop. With the development and application of information and network technology, the scale and variety of data are increasing rapidly; advances in data analytics have made the economy, and consumption, quantifiable and visible. At present, many scholars rely on a big-data background and carry out research on sustainable consumption. Therefore, we called for sustainable and consumption papers for special volume of Journal of Cleaner Production (JCLPRO). We received submissions from all over the world and eventually accepted 45. This Special Issue forming a study on sustainable energy consumption, low-carbon transportation, waste recovery and recycling, climate change cost assessment, application and policy modelling for big data and sustainable consumption to promote sustainable development in the fields of energy consumption, low-carbon transportation, waste recovery, and so on. The authors have analysed the problems of pollution and carbon emission in different regions and product production cycles, according to the background of specific regions and enterprises, through data mining, measurement models, and an evaluation index system. Some suggestions are provided for urban construction and enterprise development according to the results. (C) 2019 Elsevier Ltd. All rights reserved.
机译:消费的增长带来了一系列环境问题。可以满足人类需求,改善生活质量并减少产品生命周期中污染物的可持续消费模式应运而生。随着信息和网络技术的发展和应用,数据的规模和种类正在迅速增加。数据分析的进步使经济性和消耗变得可量化且可见。当前,许多学者依靠大数据背景进行可持续消费研究。因此,我们呼吁为可持续发展和消费性论文提供特别数量的《清洁生产杂志》(JCLPRO)。我们收到了来自世界各地的意见书,并最终接受了45条。该期特刊构成了一项关于可持续能源消耗,低碳运输,废物回收和再循环,气候变化成本评估,大数据和可持续消费的应用和政策模型的研究。在能源消耗,低碳运输,废物回收等领域促进可持续发展。作者根据特定地区和企业的背景,通过数据挖掘,度量模型和评估指标体系,分析了不同地区和产品生产周期中的污染和碳排放问题。研究结果为城​​市建设和企业发展提供了一些建议。 (C)2019 Elsevier Ltd.保留所有权利。

著录项

  • 来源
    《Journal of Cleaner Production》 |2019年第1期|117499.1-117499.9|共9页
  • 作者单位

    Beijing Inst Technol Sch Management & Econ Beijing 100081 Peoples R China|Beijing Inst Technol Ctr Energy & Environm Policy Res Beijing 100081 Peoples R China|Cornell Univ Civil & Environm Engn 305 Hollister Hall Ithaca NY 14853 USA;

    Fudan Univ Dept Environm Engn Sci Shanghai Key Lab Atmospher Particle Pollut & Prev Shanghai 200433 Peoples R China|Cornell Univ Civil & Environm Engn 305 Hollister Hall Ithaca NY 14853 USA;

    Anhui Univ Finance & Econ Collaborat Innovat Ctr Ecol Econ & Management Bengbu 233030 Anhui Peoples R China|Cornell Univ Civil & Environm Engn 305 Hollister Hall Ithaca NY 14853 USA;

    Cornell Univ Dyson Sch Appl Econ & Management 405 Warren Hall Ithaca NY 14853 USA|Cornell Univ Civil & Environm Engn 305 Hollister Hall Ithaca NY 14853 USA;

    Beijing Inst Technol Sch Management & Econ Beijing 100081 Peoples R China|Cornell Univ Civil & Environm Engn 305 Hollister Hall Ithaca NY 14853 USA;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Big data; Sustainable consumption; Low carbon; Climate change;

    机译:大数据;可持续消费;低碳;气候变化;

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