Large Chinese land carbon sink estimated from atmospheric carbon dioxide data

Wang, Jing; Feng, Liang; Palmer, Paul I.; Liu, Yi; Fang, Shuangxi; Bösch, H.; O’Dell, C.; Tang, Xiaoping; Yang, Dongxu; Liu, Lixin; Xia, Chang

doi:10.1038/s41586-020-2849-9

Cited by 421 publications

(240 citation statements)

References 46 publications

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“…12(c)), indicating another source of C10 OOMs, such as monoterpenes oxidation. These results underscore the formation of SOA precursors from a mixture of anthropogenic and biogenic emissions, under ongoing forest cover increases (Wang et al, 2020a) in highly urbanized eastern China.…”

Section: Ensemble Chemical Propertiesmentioning

confidence: 58%

“…Fine particulate matter, with an aerodynamic diameter smaller than 2.5 μm (PM2.5), has been significantly reduced in eastern China after the implementation of "Action Plan for Air Pollution Prevention and Control" since 2013 (Ding et al, 2019), while (secondary) organic aerosol are still much more abundant than in clean areas Sun et al, 2020). Here we investigated condensable oxygenated organic vapors observed by nitrate CI-APi-TOF in August-September 2019 at the Station for Observing Regional Processes and the Earth System (SORPES) in the western part of the YRD, an anthropogenic-emissions-dominated environment (Fu et al, 2013;Xu et al, 2017) mixed with enhanced biogenic emissions during summer (Wang et al, 2020a;Xu et al, 2021). A variety of oxidants (Liu et al, 2019;Li et al, 2020;Xia et al, 2020) with numerous precursors (VOCs) suggest very complicated atmospheric oxidation processes and thousands of products (OOMs).…”

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confidence: 99%

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Formation of condensable organic vapors from anthropogenic and biogenic VOCs is strongly perturbed by NO<sub>x</sub> in eastern China

Liu¹,

Nie²,

Li³

et al. 2021

Preprint

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Abstract. Oxygenated organic molecules (OOMs) are the crucial intermediates linking volatile organic compounds (VOCs) to secondary organic aerosol (SOA) in the atmosphere, but understandings on the characteristics of OOMs and their formations from VOCs are very limited. Ambient observations of OOMs using recently developed mass spectrometry techniques are still limited, especially in polluted urban atmosphere where VOCs and oxidants are extremely variable and complex. Here, we investigate OOMs, measured by a nitrate-ion-based chemical ionization mass spectrometer at Nanjing in eastern China, through performing positive matrix factorization on binned mass spectra (binPMF). The binPMF analysis reveals three factors about anthropogenic VOCs (AVOCs) daytime chemistry, three isoprene-related factors, three factors about biogenic VOCs (BVOCs) nighttime chemistry, and three factors about nitrated phenols. All factors are influenced by NOx in different ways and to different extents. Over 1000 non-nitro molecules have been identified and then reconstructed from the selected solution of binPMF, and about 72 % of the total signals are contributed by nitrogen-containing OOMs, mostly regarded as organic nitrates formed through peroxy radicals terminated by nitric oxide or nitrate-radical-initiated oxidations. Moreover, multi-nitrates account for about 24 % of the total signals, indicating the significant presence of multiple generations, especially for isoprene (e.g., C5H10O8N2 and C5H9O10N3). Additionally, the distribution of OOMs concentration on carbon number confirm their precursors driven by AVOCs mixed with enhanced BVOCs during summer. Our results highlight the decisive role of NOx on OOMs formation in densely populated areas, and encourage more studies on the dramatic interactions between anthropogenic and biogenic emissions.

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Section: Ensemble Chemical Propertiesmentioning

confidence: 58%

mentioning

confidence: 99%

Formation of condensable organic vapors from anthropogenic and biogenic VOCs is strongly perturbed by NO<sub>x</sub> in eastern China

Liu¹,

Nie²,

Li³

et al. 2021

Preprint

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“…Lake shrinkage caused by the reclamation and urban sprawl in such regions has triggered some problems concerning the water resource management and flood relief (Hou et al, 2020;Xie et al, 2017). In particular, Figure 13j demonstrated the conversion of the barren to grassland in the Mu Us Desert of Yulin City, where green area has increased significantly over the past few decades due to several ecological restoration projects implemented by the government (Wang et al, 2020;Xiu et al, 2018). Overall, the CLCD shows great potential to reveal the human impact on LC changes under the condition of climate change, and also demonstrates the promising applications in environment change studies.…”

Section: Lc Conversion Patternsmentioning

confidence: 99%

30 m annual land cover and its dynamics in China from 1990 to 2019

Yang¹,

Huang²

2021

Preprint

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Abstract. Land cover (LC) determines the energy exchange, water and carbon cycle between Earth's spheres. Accurate LC information is a fundamental parameter for the environment and climate studies. Considering that the LC in China has been altered dramatically with the economic development in the past few decades, sequential and fine-scale LC monitoring is in urgent need. However, currently, fine-resolution annual LC dataset produced by the observational images is generally unavailable for China due to the lack of sufficient training samples and computational capabilities. To deal with this issue, we produced the first Landsat-derived annual China Land Cover Dataset (CLCD) on the Google Earth Engine (GEE) platform, which contains 30 m annual LC and its dynamics of China from 1990 to 2019. We first collected the training samples by combining stable samples extracted from China’s Land-Use/Cover Datasets (CLUD), and visually-interpreted samples from satellite time-series data, Google Earth and Google Map. Using 335,709 Landsat images on the GEE, several temporal metrics were constructed and fed to the random forest classifier to obtain classification results. We then proposed a post-processing method incorporating spatial-temporal filtering and logical reasoning to further improve the spatial-temporal consistency of CLCD. Finally, the overall accuracy of CLCD reached 79.31 % based on 5,463 visually-interpreted samples. A further assessment based on 5,131 third-party test samples showed that the overall accuracy of CLCD outperforms that of MCD12Q1, ESACCI_LC, FROM_GLC, and GlobaLand30. Besides, we intercompared the CLCD with several Landsat-derived thematic products, which exhibited good consistencies with the Global Forest Change, the Global Surface Water, and three impervious surface products. Based on the CLCD, the trends and patterns of China’s LC changes during 1985 and 2019 were revealed, such as expansion of impervious surface (+148.71 %) and water (+18.39 %), decrease of cropland (−4.85 %) and grassland (−3.29 %), increase of forest (+4.34 %). In general, CLCD reflected the rapid urbanization and a series of ecological projects (e.g., Gain for Green) in China and revealed the anthropogenic implications on LC under the condition of climate change, signifying its potential application in the global change research. The CLCD dataset introduced in this article is freely available at http://doi.org/10.5281/zenodo.4417810 (Yang and Huang, 2021).

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“…The GOSAT sun glint observations are known to have additional retrieval bias relative to those over the land surfaces, and produces greater inconsistency when compared with transport model simulations (Patra et al, 2017;Schuh et al, 2019;Yoshida et al, 2013). Both our models systematically overestimated XCO 2 concentrations over Asia around the latitude 45 o N, which could either arise from high bias in FFC CO 2 emissions over China (Saeki and Patra 2017) or underestimation of sinks over the regions (Wang et al 2020). For both the simulations, XCO 2 over the tropical land regions, except over India, are underestimated (negative differences) while the XCO 2 over the ocean basins are systematically overestimated (positive differences) (Fig.…”

Section: Resultsmentioning

confidence: 78%

Evaluation of Earth System Model and Atmospheric Inversion using Total Column CO2 Observations from GOSAT and OCO-2

Patra¹,

Hajima²,

Saito

et al. 2021

Preprint

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The measurements of one of the major greenhouse gases, carbon dioxide (CO2), are being made using dedicated satellite remote sensing since the launch of the greenhouse gases observing satellite (GOSAT) by Japan Aerospace Exploration Agency (JAXA) in 2009 and National Aeronautics and Space Administration (NASA) Orbiting Carbon Observatory-2 (OCO-2). In the past 10 years, estimation of CO2 fluxes from land and ocean using the earth system models (ESMs) and inverse modelling of in situ atmospheric CO2 data have also made significant progress. We attempt, for the first time, to evaluate the CO2 fluxes simulated by an earth system model (MIROC-ES2L) and the fluxes estimated by an inverse model (MIROC4-Inv) using in situ data by comparing with GOSAT and OCO-2 observations. Both MIROC-ES2L and MIROC4-Inv fluxes are used in the MIROC4-atmospheric chemistry transport model (referred to as ACTM_ES2LF and ACTM_InvF, respectively) for calculating total column CO2 mole fraction (XCO2) that are sampled at the time and location of the satellite measurements. Both the ACTM simulations agreed well with the GOSAT and OCO-2 satellite observations, within 2 ppm for the spatial maps and time evolutions of the zonal mean distributions. Our results suggest that the inverse model using in situ data are more consistent with the OCO-2 retrievals, compared to those of the GOSAT XCO2 data due to the higher accuracy of the former. This suggests that the MIROC4-Inv fluxes are of sufficient quality to evaluate MIROC-ES2L simulated fluxes. The ACTM_ES2LF simulation shows a slightly weaker seasonal cycle for the meridional profiles of CO2 fluxes, compared to that from the ACTM_InvF. This difference is revealed by greater XCO2 differences for ACTM_ES2LF vs GOSAT, compared to those of ACTM_InvF vs GOSAT. Using remote sensing based global products of leaf area index (LAI) and gross primary productivity (GPP) over land, we show a weaker sensitivity of MIROC-ES2L biospheric activities to the weather and climate in the tropical regions. Our results clearly suggest the usefulness of XCO2 measurements by satellite remote sensing for evaluation of large-scale ESMs, which so far remained untested by the sparse in situ data.

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Large Chinese land carbon sink estimated from atmospheric carbon dioxide data

Cited by 421 publications

References 46 publications

Formation of condensable organic vapors from anthropogenic and biogenic VOCs is strongly perturbed by NO<sub>x</sub> in eastern China

Formation of condensable organic vapors from anthropogenic and biogenic VOCs is strongly perturbed by NO<sub>x</sub> in eastern China

30 m annual land cover and its dynamics in China from 1990 to 2019

Evaluation of Earth System Model and Atmospheric Inversion using Total Column CO2 Observations from GOSAT and OCO-2

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Large Chinese land carbon sink estimated from atmospheric carbon dioxide data

Cited by 421 publications

References 46 publications

Formation of condensable organic vapors from anthropogenic and biogenic VOCs is strongly perturbed by NO&lt;sub&gt;x&lt;/sub&gt; in eastern China

Formation of condensable organic vapors from anthropogenic and biogenic VOCs is strongly perturbed by NO&lt;sub&gt;x&lt;/sub&gt; in eastern China

30 m annual land cover and its dynamics in China from 1990 to 2019

Evaluation of Earth System Model and Atmospheric Inversion using Total Column CO2 Observations from GOSAT and OCO-2

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Product

Resources

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Formation of condensable organic vapors from anthropogenic and biogenic VOCs is strongly perturbed by NO<sub>x</sub> in eastern China

Formation of condensable organic vapors from anthropogenic and biogenic VOCs is strongly perturbed by NO<sub>x</sub> in eastern China