摘要
环境统计是环境保护的一项重要基础性工作。推动我国经济实现高质量绿色发展,更需要调整和建立新的环境统计指标体系,科学衡量中国经济增长的质量,评判中国经济增长的短板。本文在回顾国内外环境统计发展历程的基础上,针对当前高质量绿色发展形势,分析了环境统计工作中存在的统筹制度缺乏、统计指标不完善、统计数据质量不高、统计体系法律法规不健全等问题。最后从完善环境统计方法体系、建立监测统计数据收集和审核机制、建立和完善环境投资统计体系三方面提出有针对性的对策与建议。本文可为完善我国环境统计制度和政策、提高环境统计科学准确性提供决策支持,为推动我国经济向高质量绿色化发展奠定坚实基础。
Environmental statistics is animportant basic work of environmental protection.In order to achieve continuous high-quality and green development domestically,it's supposed to adjust or even establish new environmental statistical index system to assess the quality and to evaluate defects of China's economic growth scientifically.Based on the review of development history of international and domestic environmental statistics,and the situation of currenthigh-quality and green development,an analysis of defects of environmental statistics has been made,including the imperfect planning system,absence of necessary statistical index,lack of high-quality data and inadequate laws and regulations.To improve China's current environmental statistical system,to provide decision-making support in terms of environmental statistics and to ensure China's high-quality and green development,advices have been provided from following aspects:improving the method system of environmental statistics,establishing monitoring data collection and audit system,building environmental investment statistical system in this article.
作者
胡溪
张伟
李永源
刘洁
HU Xi;ZHANG Wei;LI Yongyuan;LIU Jie(State Environmental Protection Key Laboratory of Environmental Planning and Policy Simulation, Chinese Academy for Environmental Planning, Beijing 100012 China;The Center for Beijing-Tianjin-Hebei Regional Environment, Chinese Academy for Environmental Planning, Beijing 100012 China;College of Resource Environment and Tourism, Capital Normal Universily, Beijing 100048, China)
出处
《中国环境管理》
2018年第6期75-78,86,共5页
Chinese Journal of Environmental Management
基金
环保财政项目"普查清查与汇总数据校核技术支持"(2110399)
关键词
环境统计
高质量发展
绿色化
环境数据
environmental statistics
high-quality development
green revolution
environmental data
