Shuzhuang Feng

• PhD
• Nanjing University

China has been actively reducing anthropogenic air pollutant emissions over the past decade and is about to embark on the next phase of air quality management. Carbon monoxide (CO) is an ideal indicator of primary pollutants from combustion sources. A comprehensive assessment of the current situation of anthropogenic CO emissions can inform the imp...

Wildfire carbon emissions are critical in the global carbon cycle, but their estimates remain highly uncertain. Here, we developed an inversion framework to jointly constrain wildfire carbon emissions and net ecosystem exchange using OCO-2 XCO 2 retrievals. The observing system simulation experiment shows that this approach significantly improves w...

The accurate quantification of anthropogenic carbon dioxide (CO2) emissions in urban areas is hindered by high uncertainties in emission inventories. We assessed the spatial distributions of three anthropogenic CO2 emission inventories in Shanghai, China—MEIC (0.25° × 0.25°), ODIAC (1 km × 1 km), and a local inventory (LOCAL) (4 km × 4 km)—and comp...

The outbreak of the Russia–Ukraine war in 2022 brought a huge impact on the Ukrainian economic production. To quantify this effect, we invert the anthropogenic Nitrogen oxides (NOx) emissions in Ukraine from 2019 to 2022, a key indicator of human activities, to reflect the disruption of activities in different economic sectors due to war. We found...

Satellite XCO2 retrievals have been widely used in estimating fossil fuel carbon (FFC) emissions at point and urban scales. However, at the regional scale, it remains a significant challenge. Furthermore, current global and regional atmospheric inversions often overlook the uncertainties associated with FFC emissions. To meet the needs of the globa...

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 t...

As China's land‐based anthropogenic emissions are decreasing, the impact of marine shipping emissions (MSEs) on the atmosphere, especially in coastal areas, deserves further attention. This study investigates the impact of MSEs on MDA8 ozone (O3) levels during the warm seasons of 2017 in China, considering different seasons and synoptic patterns. T...

Non-methane volatile organic compounds (NMVOC), serving as crucial precursors of O3, have a significant impact on atmospheric oxidative capacity and O3 formation. However, both anthropogenic and biogenic NMVOC emissions remain subject to considerable uncertainty. Here, we extended the Regional multi-Air Pollutant Assimilation System (RAPAS) using t...

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, all...

Anthropogenic nitrogen oxide (NO x ) emissions are closely associated with human activities. In recent years, global human activity patterns have changed significantly owing to the COVID‐19 epidemic and international energy crisis. However, their effects on NO x emissions are not yet fully understood. In this study, we developed a two-step inversio...

Non-methane volatile organic compounds (NMVOC), serving as crucial precursors of O3, have a significant impact on atmospheric oxidative capacity and O3 formation. However, both anthropogenic and biogenic NMVOC emissions remain subject to considerable uncertainty. Here, we extended the Regional multi-Air Pollutant Assimilation System (RAPAS) with th...

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 s...

Top-down atmospheric inversion infers surface–atmosphere fluxes from spatially distributed observations of atmospheric composition in order to quantify anthropogenic and natural emissions. In this study, we developed a Regional multi-Air Pollutant Assimilation System (RAPAS v1.0) based on the Weather Research and Forecasting–Community Multiscale Ai...

Land-sea atmosphere interaction (LSAI) is one of the important processes affecting ozone (O3) pollution in coastal areas. The effects of small-scale LSAIs like sea-land breezes have been widely studied. However, it is not fully clear how and to what extent the large-scale LSAIs affect O3 pollution. Here we explored an O3 episode to illuminate the r...

The magnitude and spatial pattern of anomalous net biome exchange (NBE) induced by the 2015/16 El Niño over Amazonian rainforests remain uncertain. We here investigated them using multi‐model posterior NBE products in the Orbiting Carbon Observatory‐2 (OCO‐2) version 10 modeling intercomparison project. Results suggest that relative to the annual N...

Plain Language Summary Remotesensing‐based CO2 measurement can improve the estimates of surface carbon fluxes due to its relatively well global coverage, but it remains unknown on what spatial scales the satellite observation could provide a robust estimate. Here, net ecosystem exchanges (NEEs) from 12 terrestrial biosphere models (TBMs) of 51 land...

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 stud...

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 dataset...

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 differe...

A global gridded net ecosystem exchange (NEE) of CO2 dataset is vital in global and regional carbon cycle studies. Top-down atmospheric inversion is one of the major methods to estimate the global NEE; however, the existing global NEE datasets generated through inversion from conventional CO2 observations have large uncertainties in places where ob...

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) em...

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 g...

Top-down atmospheric inversion infers surface-atmosphere fluxes from spatially distributed observations of atmospheric compositions, which is a vital means for quantifying large-scale anthropogenic and natural emissions. In this study, we developed a Regional multi-Air Pollutant Assimilation System (RAPAS v1.0) based on the Weather Research and For...

Satellite retrievals of the column-averaged dry air mole fractions of CO2 (XCO2) could help to improve carbon flux estimation due to their good spatial coverage. In this study, in order to assimilate the GOSAT (Greenhouse Gases Observing Satellite) XCO2 retrievals, the Global Carbon Assimilation System (GCAS) is upgraded with new assimilation algor...

Tropospheric ozone (O3) can be transported influenced by large-scale circulation. In this study, an ozone pollution episode in 6 cities of southeastern coastal area of China (SCA) in autumn 2017 was investigated. Compared with the typical local ozone pollution, there was no significant diurnal variations in this pollution episode, the O3 concentrat...

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...

The COVID‐19 epidemic has substantially limited human activities and affected anthropogenic emissions. In this work, daily NOx 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, NOx emissions across the whole mainland China droppe...

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 dr...

China has implemented active clean air policies in recent years, and the spatiotemporal patterns of major pollutant emissions have changed substantially. In this study, we construct a regional air pollution data assimilation system based on the WRF/CMAQ model and ensemble Kalman filter algorithm to quantitatively optimize gridded CO emissions using...

Data assimilation is one of the effective ways to improve model predictions. In this study, surface fine particulate matter (PM2.5) observations during 16 December 2015 to 15 January 2016 over China are assimilated in a regional air quality forecasting system using the three-dimensional variational (3DVAR) method. Two parallel experiments with and...