Abstract

The majority of anthropogenic carbon dioxide emissions originate from cities, nonetheless, it is common to have inaccuracies and uncertainties in urban carbon emission measurement. Many countries have devoted much effort to improve the accuracy and consistency of urban emission data through improving measurement tools and inversion models. The paper presents achievements of research in the U.S and Europe, as well as discusses their technical impacts and obstacles. The paper provides an overwiew of the technical impacts and research gaps of CO2-USA network and the Carbosense CO2 sensor network in Switzerland, we discuss the spatial and temporal distribution characteristics of greenhouse gas concentrations and explain the principles of carbon emission inversion method. The CO2-USA network applies an interdisciplinary approach to estimate urban carbon emission to simulate the transport process of CO2 molecules in the atmosphere. The Carbosense network employs dense networks to observe the changing process of carbon dioxide emissions via enhancing data quality of low-cost carbon dioxide sensors. The purpose of this paper is to propose a novel framework of GHG observing network which combines carbon emission estimation method and real-time greenhouse gas monitoring network. The framework applies in-situ sites and mobile observations to build high-resolution emissions inventories and gain greenhouse gas concentration mappings in the urban regions. It provides governments with reliable measurement results for planning research directions for carbon emission management in China over the next few years.

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