China's Fossil Fuel CO Emissions Estimated Using Surface Observations of Coemitted NO.

Environ Sci Technol

Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, International Institute for Earth System Science, Nanjing University, Nanjing 210023, China.

Published: May 2024

Accurate estimates of fossil fuel CO (FFCO) emissions are of great importance for climate prediction and mitigation regulations but remain a significant challenge for accounting methods relying on economic statistics and emission factors. In this study, we employed a regional data assimilation framework to assimilate NO observations, allowing us to combine observation-constrained NO emissions coemitted with FFCO and grid-specific CO-to-NO emission ratios to infer the daily FFCO emissions over China. The estimated national total for 2016 was 11.4 PgCO·yr, with an uncertainty (1σ) of 1.5 PgCO·yr that accounted for errors associated with atmospheric transport, inversion framework parameters, and CO-to-NO emission ratios. Our findings indicated that widely used "bottom-up" emission inventories generally ignore numerous activity level statistics of FFCO related to energy industries and power plants in western China, whereas the inventories are significantly overestimated in developed regions and key urban areas owing to exaggerated emission factors and inexact spatial disaggregation. The optimized FFCO estimate exhibited more distinct seasonality with a significant increase in emissions in winter. These findings advance our understanding of the spatiotemporal regime of FFCO emissions in China.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11097393PMC
http://dx.doi.org/10.1021/acs.est.3c07756DOI Listing

Publication Analysis

Top Keywords

ffco emissions
12
fossil fuel
8
emission factors
8
co-to-no emission
8
emission ratios
8
emissions china
8
emissions
6
ffco
6
emission
5
china's fossil
4

Similar Publications

Top-down estimates of fossil fuel CO (FFCO) emissions are crucial for tracking emissions and evaluating mitigation strategies. However, their practical application is hindered by limited data coverage and overreliance on NOx-to-CO emission ratios from emission inventories. We developed the Machine Learning-Driven Mapping Satellite-based XCO (ML-MSXE) model using the column-averaged dry-air mole fraction of CO enhancement (XCO) derived from OCO-2 and OCO-3 measurements to reconstruct the XCO distribution for monitoring FFCO emissions.

View Article and Find Full Text PDF

Fossil fuel (FF) CO emissions account for the largest portion of human-related CO emissions. It is essential to accurately understand the spatial distribution of high-resolution FFCO emissions to formulate different carbon emission reduction policies in different regions. Therefore, a sectoral allocation approach was proposed to estimate FFCO emissions in China from 2000 to 2021 based on multi-source data.

View Article and Find Full Text PDF

China's Fossil Fuel CO Emissions Estimated Using Surface Observations of Coemitted NO.

Environ Sci Technol

May 2024

Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, International Institute for Earth System Science, Nanjing University, Nanjing 210023, China.

Accurate estimates of fossil fuel CO (FFCO) emissions are of great importance for climate prediction and mitigation regulations but remain a significant challenge for accounting methods relying on economic statistics and emission factors. In this study, we employed a regional data assimilation framework to assimilate NO observations, allowing us to combine observation-constrained NO emissions coemitted with FFCO and grid-specific CO-to-NO emission ratios to infer the daily FFCO emissions over China. The estimated national total for 2016 was 11.

View Article and Find Full Text PDF

The direct way to estimate the regional fossil fuel CO surplus (ΔffCO) at a station is by measuring the ΔCO depletion compared with a respective background. However, this approach has several challenges, which are (i) the choice of an appropriate ΔCO background, (ii) potential contaminations through nuclear CO emissions and (iii) masking of ΔffCO by C-enriched biosphere respiration. Here we evaluate these challenges and estimate potential biases and typical uncertainties of C-based ΔffCO estimates in Europe.

View Article and Find Full Text PDF

Quantifying the coevolution of greenhouse gases and air quality pollutants can provide insight into underlying anthropogenic processes enabling predictions of their emission trajectories. Here, we classify the dynamics of historic emissions in terms of a modified Environmental Kuznets Curve (MEKC), which postulates the coevolution of fossil fuel CO (FFCO) and NOx emissions as a function of macroeconomic development. The MEKC broadly captures the historic FFCO-NO dynamical regimes for countries including the US, China, and India as well as IPCC scenarios.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!