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BOTTOM-UP VERSUS TOP-DOWN HANDS-ON OPTIONS FOR MEASURING GHG AND POLLUTANTS IN SMART CITIES

机译:自下而上与自上而下的动手选择,用于测量智能城市的温室气体和污染物

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Urbanized areas account for more than 70% of the carbon dioxide equivalent emissions. Their current greenhouse gas (GHG) emission is based on a bottom-up approach that adds the different sources of emissions (activity data multiplied by emission factors). Those current estimated inventories, based on statistics, are expensive and take months for data collection. Moreover, they raised scepticism for municipal decision-makers who are not certain how to understand and use them in urban policies planning support. Indeed, cities are lacking reliable, accessible information of a high standard on which to base GHG emission reduction decisions. To help smart cities measure and lower their emissions, another approach is currently under investigation: the top-down approach, based on real GHG measurements. In this paper, we present the current and potential hands-on options for measuring GHG: network of sensors, network of sensors coupled with atmospheric inversion modelling, and the laser beam system. We conclude by making recommendations for municipal decision makers to help them take ownership of in order to tackle climate change issues.
机译:城市化区域占二氧化碳等效排放量的70%以上。他们目前的温室气体(GHG)排放基于自下而上的方法,该方法增加了不同的排放来源(活动数据乘以排放因子)。这些基于统计数据的当前估计的库存都是昂贵的并且需要数月的数据收集。此外,他们对市政决策者提出了怀疑,他们不确定如何理解和在城市政策规划支持中使用它们。实际上,城市缺乏高标准的可靠性,可访问的信息,从而归因于基于GHG减排决定。为了帮助智能城市衡量和降低排放,目前正在调查另一种方法:基于真正的温室气体测量,自上而下的方法。在本文中,我们介绍了测量温室气体的当前和潜在的动手选择:传感器网络,传感器网络,耦合大气反转建模和激光束系统。我们通过向市政决策者提出建议,帮助他们获取所有权以解决气候变化问题。

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