Quantifying the potential impacts of China's power-sector policies on coal input and CO2 emissions through 2050: A bottom-up perspective

The concentration of atmospheric carbon dioxide (CO2) has increased rapidly worldwide, aggravating the global greenhouse effect, and coal-fired power plants are one of the biggest contributors of greenhouse gas emissions in China. However, efficient methods that can quantify CO2 emissions from individual coal-fired power plants with high accuracy are needed. In this study, we estimated the CO2 emissions of large-scale coal-fired power plants using Orbiting Carbon Observatory-2 (OCO-2) satellite data based on remote sensing inversions and bottom-up methods. First, we mapped the distribution of coal-fired power plants, displaying the total installed capacity, and identified two appropriate targets, the Waigaoqiao and Qinbei power plants in Shanghai and Henan, respectively. Then, an improved Gaussian plume model method was applied for CO2 emission estimations, with input parameters including the geographic coordinates of point sources, wind vectors from the atmospheric reanalysis of the global climate, and OCO-2 observations. The application of the Gaussian model was improved by using wind data with higher temporal and spatial resolutions, employing the physically based unit conversion method, and interpolating OCO-2 observations into different resolutions. Consequently, CO2 emissions were estimated to be 23.06 ± 2.82 (95% CI) Mt/yr using the Gaussian model and 16.28 Mt/yr using the bottom-up method for the Waigaoqiao Power Plant, and 14.58 ± 3.37 (95% CI) and 14.08 Mt/yr for the Qinbei Power Plant, respectively. These estimates were compared with three standard databases for validation: the Carbon Monitoring for Action database, the China coal-fired Power Plant Emissions Database, and the Carbon Brief database. The comparison found that previous emission inventories spanning different time frames might have overestimated the CO2 emissions of one of two Chinese power plants on the two days that the measurements were made. Our study contributes to quantifying CO2 emissions from point sources and helps in advancing satellite-based monitoring techniques of emission sources in the future; this helps in reducing errors due to human intervention in bottom-up statistical methods.

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Calculating Carma: Global Estimation of Co2 Emissions from the Power Sector

SSRN Electronic Journal ◽

10.2139/ssrn.1138690 ◽

2008 ◽

Cited By ~ 37

Author(s):

David Wheeler ◽

Kevin Ummel

Keyword(s):

Co2 Emissions ◽

Power Sector ◽

Global Estimation

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The synthesis of bottom-up and top-down approaches to climate policy modeling: Electric power technologies and the cost of limiting US CO2 emissions

Energy Policy ◽

10.1016/j.enpol.2005.08.027 ◽

2006 ◽

Vol 34 (18) ◽

pp. 3847-3869 ◽

Cited By ~ 80

Author(s):

Ian Sue Wing

Keyword(s):

Electric Power ◽

Climate Policy ◽

Co2 Emissions ◽

Top Down ◽

Bottom Up ◽

Policy Modeling ◽

The Cost

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CO2 emissions from cement industry in China: A bottom-up estimation from factory to regional and national levels

Journal of Geographical Sciences ◽

10.1007/s11442-017-1402-8 ◽

2017 ◽

Vol 27 (6) ◽

pp. 711-730 ◽

Cited By ~ 6

Author(s):

Yan Yang ◽

Limao Wang ◽

Zhi Cao ◽

Chufu Mou ◽

Lei Shen ◽

...

Keyword(s):

Co2 Emissions ◽

Cement Industry ◽

Bottom Up

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A global map of emission clumps for future monitoring of fossil fuel CO<sub>2</sub> emissions from space

Earth System Science Data ◽

10.5194/essd-11-687-2019 ◽

2019 ◽

Vol 11 (2) ◽

pp. 687-703 ◽

Cited By ~ 6

Author(s):

Yilong Wang ◽

Philippe Ciais ◽

Grégoire Broquet ◽

François-Marie Bréon ◽

Tomohiro Oda ◽

...

Keyword(s):

Co2 Emissions ◽

Land Surface ◽

Urban Areas ◽

Power Plants ◽

Fossil Fuel ◽

Large Fraction ◽

Point Sources ◽

Bottom Up ◽

Large Power ◽

Data Product

Abstract. A large fraction of fossil fuel CO2 emissions emanate from “hotspots”, such as cities (where direct CO2 emissions related to fossil fuel combustion in transport, residential, commercial sectors, etc., excluding emissions from electricity-producing power plants, occur), isolated power plants, and manufacturing facilities, which cover a small fraction of the land surface. The coverage of all high-emitting cities and point sources across the globe by bottom-up inventories is far from complete, and for most of those covered, the uncertainties in CO2 emission estimates in bottom-up inventories are too large to allow continuous and rigorous assessment of emission changes (Gurney et al., 2019). Space-borne imagery of atmospheric CO2 has the potential to provide independent estimates of CO2 emissions from hotspots. But first, what a hotspot is needs to be defined for the purpose of satellite observations. The proposed space-borne imagers with global coverage planned for the coming decade have a pixel size on the order of a few square kilometers and a XCO2 accuracy and precision of <1 ppm for individual measurements of vertically integrated columns of dry-air mole fractions of CO2 (XCO2). This resolution and precision is insufficient to provide a cartography of emissions for each individual pixel. Rather, the integrated emission of diffuse emitting areas and intense point sources is sought. In this study, we characterize area and point fossil fuel CO2 emitting sources which generate coherent XCO2 plumes that may be observed from space. We characterize these emitting sources around the globe and they are referred to as “emission clumps” hereafter. An algorithm is proposed to identify emission clumps worldwide, based on the ODIAC global high-resolution 1 km fossil fuel emission data product. The clump algorithm selects the major urban areas from a GIS (geographic information system) file and two emission thresholds. The selected urban areas and a high emission threshold are used to identify clump cores such as inner city areas or large power plants. A low threshold and a random walker (RW) scheme are then used to aggregate all grid cells contiguous to cores in order to define a single clump. With our definition of the thresholds, which are appropriate for a space imagery with 0.5 ppm precision for a single XCO2 measurement, a total of 11 314 individual clumps, with 5088 area clumps, and 6226 point-source clumps (power plants) are identified. These clumps contribute 72 % of the global fossil fuel CO2 emissions according to the ODIAC inventory. The emission clumps is a new tool for comparing fossil fuel CO2 emissions from different inventories and objectively identifying emitting areas that have a potential to be detected by future global satellite imagery of XCO2. The emission clump data product is distributed from https://doi.org/10.6084/m9.figshare.7217726.v1.

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Toward an Operational Anthropogenic CO2 Emissions Monitoring and Verification Support Capacity

Bulletin of the American Meteorological Society ◽

10.1175/bams-d-19-0017.1 ◽

2020 ◽

Vol 101 (8) ◽

pp. E1439-E1451 ◽

Cited By ~ 5

Author(s):

G. Janssens-Maenhout ◽

B. Pinty ◽

M. Dowell ◽

H. Zunker ◽

E. Andersson ◽

...

Keyword(s):

Co2 Emissions ◽

European Space Agency ◽

Green Light ◽

Atmospheric Measurements ◽

Top Down ◽

Bottom Up ◽

Holistic View ◽

Support Tool ◽

Anthropogenic Co2 ◽

Operational Capacity

Abstract Under the Paris Agreement (PA), progress of emission reduction efforts is tracked on the basis of regular updates to national greenhouse gas (GHG) inventories, referred to as bottom-up estimates. However, only top-down atmospheric measurements can provide observation-based evidence of emission trends. Today, there is no internationally agreed, operational capacity to monitor anthropogenic GHG emission trends using atmospheric measurements to complement national bottom-up inventories. The European Commission (EC), the European Space Agency, the European Centre for Medium-Range Weather Forecasts, the European Organisation for the Exploitation of Meteorological Satellites, and international experts are joining forces to develop such an operational capacity for monitoring anthropogenic CO2 emissions as a new CO2 service under the EC’s Copernicus program. Design studies have been used to translate identified needs into defined requirements and functionalities of this anthropogenic CO2 emissions Monitoring and Verification Support (CO2MVS) capacity. It adopts a holistic view and includes components such as atmospheric spaceborne and in situ measurements, bottom-up CO2 emission maps, improved modeling of the carbon cycle, an operational data-assimilation system integrating top-down and bottom-up information, and a policy-relevant decision support tool. The CO2MVS capacity with operational capabilities by 2026 is expected to visualize regular updates of global CO2 emissions, likely at 0.05° x 0.05°. This will complement the PA’s enhanced transparency framework, providing actionable information on anthropogenic CO2 emissions that are the main driver of climate change. This information will be available to all stakeholders, including governments and citizens, allowing them to reflect on trends and effectiveness of reduction measures. The new EC gave the green light to pass the CO2MVS from exploratory to implementing phase.

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