Development of a regional carbon assimilation system and its application for estimating fossil fuel carbon emissions in the Yangtze River Delta, China.

Urban areas are the largest contributors to global fossil fuel carbon emissions, and controlling urban carbon emissions is critical to addressing climate change and reducing greenhouse gas emissions. However, estimates of urban emissions remain large uncertainties, making it difficult to accurately understand changes in urban carbon emissions and to assess the effectiveness of emission controls. Atmospheric CO observations, through data assimilation, can objectively invert changes in urban carbon emissions.

Influence of extreme 2022 heatwave on megacities' anthropogenic CO emissions in lower-middle reaches of the Yangtze River.

An unprecedented heatwave hit the Yangtze River Basin (YRB) in August 2022. We analyzed changes of anthropogenic CO emissions in 8 megacities over lower-middle reaches of the YRB, using a near-real-time gridded daily CO emissions dataset. We suggest that the predominant sources of CO emissions in these 8 megacities are from the power and industrial sectors.

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

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.

Improved estimation of CO emissions from thermal power plants based on OCO-2 XCO retrieval using inline plume simulation.

CO emissions from power plants are the dominant source of global CO emissions, thus in the context of global warming, accurate estimation of CO emissions from power plants is essential for the effective control of carbon emissions. Based on the XCO retrievals from the Orbiting Carbon Observatory 2 (OCO-2) and the Gaussian Plume Model (GPM), a series of studies have been carried out to estimate CO emission from power plants. However, the GPM is an ideal model, and there are a number of assumptions that need to be made when using this model, resulting in large uncertainties in the inverted emissions.

The Nord Stream pipeline gas leaks released approximately 220,000 tonnes of methane into the atmosphere.

Sudden mega natural gas leaks of two Nord Stream pipelines in the Baltic Sea (Denmark) occurred from late September to early October 2022, releasing large amounts of methane into the atmosphere. We inferred the methane emissions of this event based on surface in situ observations using two inversion methods and two meteorological reanalysis datasets, supplemented with satellite-based observations. We conclude that approximately 220 ± 30 Gg of methane was released from September 26 to October 1, 2022.

Anthropogenic emissions estimated using surface observations and their impacts on PM source apportionment over the Yangtze River Delta, China.

Source-tagged source apportionment (SA) has advantages for quantifying the contribution of various source regions and categories to PM; however, it is highly affected by uncertainty in the emission inventory. In this study, we used a Regional multi-Air Pollutant Assimilation System (RAPAS) to optimize daily SO, NO and primary PM (PPM) emissions in the Yangtze River Delta (YRD) in December 2016 by assimilating hourly in-situ measurements. The CMAQ-ISAM model was implemented with prior and posterior emissions respectively to investigate the impacts of optimizing emissions on PM SA in the YRD megalopolis (YRDM) and three megacities of Shanghai, Nanjing, and Hangzhou in the YRDM.

The status of carbon neutrality of the world's top 5 CO emitters as seen by carbon satellites.

China, the Unite States (US), the European Union (EU), India, and Russia are the world's top 5 fossil fuel and cement CO (FFC) emitting countries or regions (CRs). It is very important to understand their status of carbon neutrality, and to monitor their future changes of net carbon fluxes (NCFs). In this study, we implemented a well-established global carbon assimilation system (GCAS, Version 2) to infer global surface carbon fluxes from May 2009 to December 2019 using both GOSAT and OCO-2 XCO retrievals.

NO Emission Changes Over China During the COVID-19 Epidemic Inferred From Surface NO Observations.

The COVID-19 epidemic has substantially limited human activities and affected anthropogenic emissions. In this work, daily NO emissions are inferred using a regional data assimilation system and hourly surface NO measurement over China. The results show that because of the coronavirus outbreak, NO emissions across the whole mainland China dropped sharply after 31 January, began to rise slightly in certain areas after 10 February, and gradually recover across the country after 20 February.

A comprehensive estimate of recent carbon sinks in China using both top-down and bottom-up approaches.

Atmospheric inversions use measurements of atmospheric CO2 gradients to constrain regional surface fluxes. Current inversions indicate a net terrestrial CO2 sink in China between 0.16 and 0.