A city-level comparison of fossil-fuel and industry processes-induced CO2 emissions over the Beijing-Tianjin-Hebei region from eight emission inventories

Qixiang Cai,Rong Wang,Wenjun Meng,Tomohiro Oda,Guocheng Wang,Bo Zheng,Di Liu,Wen Zhang,Xiaolin Ma,Xiaohui Lin,Ning Zeng,Pengfei Han

doi:10.1186/s13021-020-00163-2

Abstract

BackgroundQuantifying CO2 emissions from cities is of great importance because cities contribute more than 70% of the global total CO2 emissions. As the largest urbanized megalopolis region in northern China, the Beijing-Tianjin-Hebei (Jing-Jin-Ji, JJJ) region (population: 112.7 million) is under considerable pressure to reduce carbon emissions. Despite the several emission inventories covering the JJJ region, a comprehensive evaluation of the CO2 emissions at the prefectural city scale in JJJ is still limited, and this information is crucial to implementing mitigation strategies.ResultsHere, we collected and analyzed 8 published emission inventories to assess the emissions and uncertainty at the JJJ city level. The results showed that a large discrepancy existed in the JJJ emissions among downscaled country-level emission inventories, with total emissions ranging from 657 to 1132 Mt CO2 (or 849 ± 214 for mean ± standard deviation (SD)) in 2012, while emission estimates based on provincial-level data estimated emissions to be 1038 and 1056 Mt. Compared to the mean emissions of city-data-based inventories (989 Mt), provincial-data-based inventories were 6% higher, and national-data-based inventories were 14% lower. Emissions from national-data-based inventories were 53–75% lower in the high-emitting industrial cities of Tangshan and Handan, while they were 47–160% higher in Beijing and Tianjin than those from city-data-based inventories. Spatially, the emissions pattern was consistent with the distribution of urban areas, and urban emissions in Beijing contributed 50–70% of the total emissions. Higher emissions from Beijing and Tianjin resulted in lower estimates of prefectural cities in Hebei for some national inventories.ConclusionsNational-level data-based emission inventories produce large differences in JJJ prefectural city-level emission estimates. The city-level statistics data-based inventories produced more consistent estimates. The consistent spatial distribution patterns recognized by these inventories (such as high emissions in southern Beijing, central Tianjin and Tangshan) potentially indicate areas with robust emission estimates. This result could be useful in the efficient deployment of monitoring instruments, and if proven by such measurements, it will increase our confidence in inventories and provide support for policy makers trying to reduce emissions in key regions.

Highlights

Quantifying CO2 emissions from cities is of great importance because cities contribute more than 70% of the global total CO2 emissions
The emissions from urban and non-urban areas were separated by using an urban mask from the European Space Agency (ESA) Climate Change Initiative (CCI) land cover maps with a 300 m resolution, and the urban area here mainly refers to impermeable surfaces, with high coherence and bright reflections, maintained in time and under varying angles detected by satellite
The total emissions estimated from provincial-data-based inventories (i.e., Multi-resolution Emission Inventory for China (MEIC) and Nanjing University CO2 emission inventory (NJU)) were 6% higher than those from city-data-based inventories (i.e., China High Resolution Emission Database (CHRED) and China Emission Accounts and Datasets (CEADs)) but were 14% lower from downscaled nationallevel emissions (i.e., Peking University CO2 emission inventory (PKU), Open-source Data Inventory for Anthropogenic CO2 (ODIAC), Emissions Database for Global Atmospheric Research (EDGAR), and Fossil Fuel Data Assimilation System (FFDAS)) in 2012

Summary

Introduction

Quantifying CO2 emissions from cities is of great importance because cities contribute more than 70% of the global total CO2 emissions. Despite the several emission inventories covering the JJJ region, a comprehensive evaluation of the C O2 emissions at the prefectural city scale in JJJ is still limited, and this information is crucial to implementing mitigation strategies. Cities have become the critical and basic units for implementing emissions mitigation policies [2,3,4,5]. City carbon emissions are influenced by the physical environment, economic development, urbanized density, industry structure, and energy use patterns specific to each city [1, 8]. City strategies that reduce carbon emissions are expected to achieve emissions mitigation and meet a city’s economic growth goals [12]. An accurate understanding of city-level C O2 emissions is of great importance in developing and implementing mitigation strategies

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Conclusion