碳监测城市2.0

CARBON MONITORCITIES 2.0: TRACKINGURBAN EMISSIONS INNEAR REAL TIME © 2024 International Bank for Reconstruction and Development / The World Bank1818 H Street NWWashington DC 20433Telephone: 202-473-1000Internet: www.worldbank.org This work is a product of the staff of The World Bank with external contributions. The findings, interpretations, andconclusions expressed in this work do not necessarily reflect the views of The World Bank, its Board of ExecutiveDirectors, or the governments they represent. The World Bank does not guarantee the accuracy, completeness, or currency of the data included in this work and doesnot assume responsibility for any errors, omissions, or discrepancies in the information, or liability with respectto theuse of or failure to use the information, methods, processes, or conclusions set forth. The boundaries, colors,denominations, and other information shown on any map in this work do not imply any judgment on the part of The WorldBank concerning the legal status of any territory or the endorsement or acceptance of such boundaries. Nothing herein shall constitute or be construed or considered to be a limitation upon or waiver of the privileges andimmunities of The World Bank, all of which are specifically reserved. Rights and Permissions The material in this work is subject to copyright. Because The World Bank encourages dissemination of its knowledge,this work may be reproduced, in whole or in part, for noncommercial purposes as long as full attribution to this work isgiven. Any queries on rights and licenses, including subsidiary rights, should be addressed to World Bank Publications, TheWorld Bank, 1818 H Street NW, Washington, DC 20433, USA; fax: 202-522-2625; e-mail: pubrights@worldbank.org. Carbon MonitorCities 2.0 Tracking Urban Emissions in NearRealTime1 Introduction This note describes Carbon MonitorCities 2.0, a new approach to near-real-time monitoring of city-level greenhouse gas emissions from various sectors without the need for local data collection. Withsupport from the City Climate Finance Gap Fund,the World Bankpilotedthis approachfor 11cities inthree middle-income countries: Egypt, South Africa, and Türkiye. The aim of the pilot was todemonstrate theability to generatenear-real-timedataon localgreenhouse gas emissions,whichcould allowabetter understanding ofthe spatial and temporalpatterns of urban carbon emissionsinspecificcities.Thisunderstandingcould inform local climatechange mitigation policies and investments, and also potentially be used as part of a monitoring,reporting andverification(MRV)system for carbon financein the future. As this approach does notrely on local data collection, it can be scaled up to a large number of cities relatively easily,particularly in low-and-middle-incomecountries thatlack data. Why isa better systemneededtomonitorurban greenhouse gas emissions? City-level greenhouse gas emissions data is necessary as an input into identifying, planning, andmonitoring urban climatechange mitigation actions. Near-real-time data with a high frequency,visualized in a clear and compelling manner,can aid decision-makersto analyzethe relationshipbetween urban activities and emissions and evaluatethe impacts of their actions. However,data onlocalgreenhouse gas (GHG)emissions is unavailable for most cities in low-andmiddle-income countries. While some cities have produced local GHG inventories, they areinconsistent in methodology and year, and not updated regularly. Some data sets, such as theEuropean Commission’sEmissions Database for Global Atmospheric Research (EDGAR), downscalenational emissions inventories using spatial proxy data to a global grid of 10x10km cells. However,there is a lag of a few years before this datais available. Satellites measure CO2concentrations butface significant data gaps due to cloud cover. It is also challenging to trace CO2concentrations fromsatellite data back to original emission locations, as CO2can travel great distances in the atmosphere.While each of these data sources can be used for certain types of analysis, none of them meets theneed for high-frequency, recent city-level emissions data. Building on recent innovations As an attempt to meet this need for high-frequency, low-latency city-level emissions data, aconsortium of researchers at universities in France, China, and the United States developed amonitoring system called Carbon Monitor Cities, the predecessor of thesystem discussed in thisnote.3The Carbon Monitor Cities model disaggregated national emissions data spatially to a 0.1degree (approximately 10x10 km) grid and temporally to a daily frequency, resulting in daily CO2estimates for approximately 1500 cities in 46 countries. To do this,it used EDGAR data and otherpointdata for spatial disaggregation,and satellite data on NO2 emissions for temporaldisaggregation. Annual estimates produced using this model were close (within 15percent) ofestimates using other methods. Emissions werea