China's Fossil Fuel CO2 Emissions Estimated Using Surface Observations of Coemitted NO2.

Accurate estimates of fossil fuel CO2 (FFCO2) 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 in situ NO2 observations, allowing us to combine observation-constrained NOx emissions coemitted with FFCO2 and grid-specific CO2-to-NOx emission ratios to infer the daily FFCO2 emissions over China. The estimated national total for 2016 was 11.4 PgCO2·yr-1, with an uncertainty (1σ) of 1.5 PgCO2·yr-1 that accounted for errors associated with atmospheric transport, inversion framework parameters, and CO2-to-NOx emission ratios. Our findings indicated that widely used "bottom-up" emission inventories generally ignore numerous activity level statistics of FFCO2 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 FFCO2 estimate exhibited more distinct seasonality with a significant increase in emissions in winter. These findings advance our understanding of the spatiotemporal regime of FFCO2 emissions in China.

NO x Emission Changes Over China During the COVID-19 Epidemic Inferred From Surface NO2 Observations.

The COVID-19 epidemic has substantially limited human activities and affected anthropogenic emissions. In this work, daily NO x emissions are inferred using a regional data assimilation system and hourly surface NO2 measurement over China. The results show that because of the coronavirus outbreak, NO x 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. Compared with the emissions before the outbreak, NO x emissions fell by more than 60% and ~30% in many large cities and most small to medium cities, respectively. Overall, NO x emissions were reduced by 36% over China, which were mainly contributed by transportation. Evaluations show that the inverted changes over eastern China are credible, whereas those in western China might be underestimated. These findings are of great significance for exploring the reduction potential of NO x emissions in China.

Improved estimation of CO2 emissions from thermal power plants based on OCO-2 XCO2 retrieval using inline plume simulation.

CO2 emissions from power plants are the dominant source of global CO2 emissions, thus in the context of global warming, accurate estimation of CO2 emissions from power plants is essential for the effective control of carbon emissions. Based on the XCO2 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 CO2 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. Here, based on 6 cases of power plant plumes observed by the OCO-2 satellite over the Yangtze River Delta, China, we use an inline plume rise module coupled in the Community Multi-scale Air Quality model (CMAQ) to simulate the plumes and invert the emissions, and compare the simulated plumes and inverted emissions using the GPM model. We found that CO2 emissions can be significantly overestimated or underestimated based on the GPM simulations, and that the CMAQ inline plume simulation could significantly improve the estimates. However, the simulation bias in wind speed can significantly affect the inversion results. These results indicate that accurate meteorological field and plume simulations are critical for future inversion of point source emissions.

Increased diurnal difference of NO2 concentrations and its impact on recent ozone pollution in eastern China in summer.

Nitrogen dioxide (NO2) is a key tropospheric O3 precursor. Since 2013, efforts to decrease air pollution in China have driven substantial declines in annual NO2 concentrations, whereas ozone (O3) concentrations have increased. Based on nationwide NO2 observations and a regional air quality model (WRF-CMAQ), we analyzed trends in the diurnal difference (DD, the difference between nighttime and daytime concentrations) of NO2 concentrations across eastern China and in five national urban agglomerations (UAs) from 2014 to 2021, and explored the factors underlying such changes and the potential impacts on O3 pollution. We found that the observed DD of NO2 has increased in most cities and UAs, and that this trend can be primarily attributed to changes in anthropogenic emissions, based on comparison with DDs simulated with fixed anthropogenic emissions, which generally showed much weaker trends and little interannual variation. A sensitivity analysis using the WRF-CMAQ model was conducted to investigate the impact of a modified diurnal cycle of nitrogen oxides (NOx) emissions on O3 concentrations. The result revealed that enhancing the DD of NO2 would increase O3 concentrations in the morning and the daily maximum 8-h O3 concentrations in the cities with high NOx concentrations, as well as downwind areas of cities, indicating that greater DDs in NO2 is one of the reasons that have led to the enhanced China's O3 pollution in recent years.

Modeling the biogenic isoprene emission and its impact on ozone pollution in Zhejiang province, China.

Isoprene is the most abundantly emitted biogenic volatile organic compound (BVOC), which plays an essential role in producing tropospheric ozone (O3). However, the simulations of isoprene emissions have not been sufficiently verified over Yangtze River Delta (YRD), and few studies have specifically addressed its impact on O3 formation. In this study, we simulated the isoprene emissions in Zhejiang Province (ZJ), a region with the largest BVOC emission in YRD, in August 2020 using the Model of Emissions of Gases and Aerosols from Nature (MEGAN) and the latest Moderate Resolution Imaging Spectroradiometer (MODIS) products, and investigated its contributions to O3 using the Weather Research and Forecasting (WRF)-Community Multiscale Air Quality (CMAQ) model. The model has a good performance on isoprene simulations over urban and suburban areas, with mean biases of -0.16-0.12 ppb, but underestimated the concentrations at forest sites (mainly due to bamboo). Regionally, the simulated formaldehyde concentrations over forests agree well with the satellite observations. In August 2020, the total isoprene emission in ZJ was 125.1 GgC, with higher emissions in western ZJ and relatively lower emissions in eastern coastal regions. The spatial pattern of isoprene concentrations is similar to its emissions, and the maximum daytime average concentrations are above 3.5 ppb. The spatial pattern of its contribution to daily maximum 8 h average O3 concentrations is significantly different from the emissions and concentrations, which shows a higher impact in northern ZJ (>6 ppb) and relatively lower impact in southern ZJ (1-3 ppb). The mean contribution over ZJ is 8.9 %, with daily variation in the range of 3.1 % to 13.4 %. For different cities, the monthly mean contribution is in the range of 4.6 % to 14.3 %, and the maximum daily contribution reaches about 25 %. These findings help understand the summertime O3 pollution in ZJ and the YRD region of China.

Anthropogenic emissions estimated using surface observations and their impacts on PM2.5 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 PM2.5; 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 SO2, NOx and primary PM2.5 (PPM2.5) 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 PM2.5 SA in the YRD megalopolis (YRDM) and three megacities of Shanghai, Nanjing, and Hangzhou in the YRDM. The results showed that RAPAS significantly improved the simulations and reduced the emission uncertainties of the different pollutants. Compared with prior emissions, the posterior emissions in the YRD decreased by 13% and 11% for SO2 and NOx respectively, and increased by 24% for PPM2.5. Compared with SA using prior emissions, the contributions from Hangzhou, northern Zhejiang, and areas outside of the YRD to the YRDM increased. The local contributions from the YRDM, Nanjing and Shanghai decreased by 1.8%, 9.7%, and 2.3%, respectively, whereas that of Hangzhou increased by 5.6%. The changes in the daily local contributions caused by optimizing emissions ranged from -18.0% to 23.6%. Generally, under stable weather conditions, the local contribution changed the most, whereas under unstable weather conditions, the contribution from upwind areas changed significantly. Overall, with optimized emissions, we found in Nanjing, Shanghai, and Hangzhou, local emissions contributed 18.2%, 39.6% and 36.8% of their PM2.5 concentrations, respectively; long-range transport from outside the YRDM contributed 59.2%, 48.1%, and 48.2%, respectively. This study emphasizes the importance of improving emission estimations for source-tagged SA and provides more reliable SA results for the main cities in the YRD, which will contribute to pollution control in these regions.

The status of carbon neutrality of the world's top 5 CO2 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 CO2 (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 XCO2 retrievals. The reductions of flux uncertainty and XCO2 bias, and the evaluation of posterior flux show that GCAS has comparable and good performance in the 5 CRs. The results suggest that Russia has achieved carbon neutrality, but the other 4 are still far from being carbon neutral, especially China. The mean annual NCFs in China, the US, the EU, India, and Russia are 2.33 ± 0.29, 0.82 ± 0.20, 0.42 ± 0.16, 0.50 ± 0.12, and -0.33 ± 0.23 PgC yr-1, respectively. From 2010 to 2019, the NCFs showed an increasing trend in the US and India, a slight downward trend after 2013 in China, and were stable in the EU. The changes of land sinks in China and the US might be the main reason for their trends. India's trend was mainly due to the increase of FFC emission. The relative contributions of NCFs to the global land net carbon emission of China and the EU have decreased, while those of the US and India have increased, implying the US and India must take more active measures to control carbon emissions or increase their sinks. This study indicates that satellite XCO2 could be successfully used to monitor the changes of regional NCFs, which is of great significance for major countries to achieve greenhouse gas control goals.

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.

Impact of weather and emission changes on NO2 concentrations in China during 2014-2019.

Nitrogen dioxide (NO2) is one of the most important air pollutants that highly affect the formation of secondary fine particles and tropospheric ozone. In this study based on hourly NO2 observations from June 2014 to May 2019 and a regional air quality model (WRF-CMAQ), we comprehensively analyzed the spatiotemporal variations of NO2 concentrations throughout China and in 12 urban agglomerations (UAs) and quantitatively showed the anthropogenic and meteorological factors controlling the interannual variations (IAVs). The ground observations and tropospheric columns show that high NO2 concentrations are predominantly concentrated in UAs such as Beijing-Tianjin-Hebei (BTH), the Shandong Peninsula (SP), the Central Plain (CP), Central Shaanxi (CS), and the Yangtze River Delta (YRD). For different UAs, the NO2 IAVs are different. The NO2 increased first and then decreased in 2016 or 2017 in BTH, YRD, CS, and Cheng-Yu, and decreased from 2014 to 2019 in Harbin-Changchun, CP, SP, Northern Slope of Tianshan Mountain, and Beibu-Gulf, while increased slightly in the Pearl River Delta (PRD) and Hohhot-Baotou-Erdos-Yulin (HBEY). The NO2 IAVs were primarily dominated by emission changes. The net wintertime decreases of NO2 in BTH, Yangtze River Middle-Reach, and PRD were mostly contributed by emission reductions from 2014 to 2018, and the significant increase in the wintertime in HBEY was also dominated by emission changes (93%). Weather conditions also have an important effect on the NO2 IAVS. In BTH and HBEY, the increases of NO2 in winter of 2016 are mainly attributed to the unfavorable weather conditions and for the significant decreases in the winter of 2017, the favorable weather conditions also play a very important role. This study provides a basic understanding on the current situation of NO2 pollution and are helpful for policymakers as well as those interested in the study of tropospheric ozone changes in China and downwind areas.