Seasonal and inter-annual variability of atmosphere CO2 based on NOAA Carbon Tracker analysis and satellite observations

Krishnapriya, M.; Chandra, Ambika; Nayak, R. K.; Patel, N. R.; Rao, Preeti; Dadhwal, V. K.

doi:10.1007/s12524-017-0688-4

Cited by 7 publications

(4 citation statements)

References 27 publications

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“…The increasing atmospheric concentrations of greenhouse gases (GHG) are recognized as the main cause of climate change (Adame‐Castro et al, 2020; Villanueva‐López et al, 2019). GHG emissions have increased by more than 40% since preindustrial times, with CO 2 concentrations in the atmosphere increasing from 278 ppm in 1750 to 414 ppm in 2020 (Krishnapriya et al, 2019). This is attributable mainly to fossil fuel burning and land use change (Kopittke et al, 2017; Tubiello et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

Silvopastoral systems improve carbon stocks at livestock ranches in Tabasco, Mexico

Que

Villanueva‐López

Alcudia‐Aguilar

et al. 2022

Soil Use and Management

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Silvopastoral systems have great potential for storing carbon because of carbon assimilation in tree woody biomass, carbon input through litterfall and below‐ground carbon turnover. In this study, we quantified and compared the carbon stocks at livestock ranches in Tabasco, Mexico, containing either scattered trees in grazing pastures (STP) or grass monocultures. Sampling plots were randomly established at each ranch where the above‐ and below‐ground carbon stocks, carbon input from litterfall, grass production and arboreal biomass growth were measured. We found that silvopastoral systems stored an average of 257.45 Mg ha−1 of soil organic carbon (SOC) compared to 119.17 Mg SOC ha−1 at grass monoculture ranches (to 30 cm depth); silvopastoral systems also stored 44.64 Mg C ha−1 in wood biomass; and, grass monocultures had greater cumulative grass biomass production. Overall, it is concluded that livestock ranches in Tabasco, Mexico, with scattered trees in grazing pastures stored 58.8% more carbon than those grass monocultures, with carbon stocks of 327.01 Mg C ha−1and 134.47 Mg C ha−1, respectively. The results are useful for land management decision making for sustainable livestock systems framed in the Sustainable Development Goals (SDGs).

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Section: Introductionmentioning

confidence: 99%

Silvopastoral systems improve carbon stocks at livestock ranches in Tabasco, Mexico

Que

Villanueva‐López

Alcudia‐Aguilar

et al. 2022

Soil Use and Management

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“…Within this context, it is important to understand the radiative effects of CO 2 changes on atmospheric temperature retrieval and radiance assimilation in NWP models. Although atmospheric CO 2 is a trace gas, it has increased in the last decade and exhibits a significant seasonal variation [11,19]. Figure 1 shows the time series of CO 2 monthly mean measured at Waliguan (upper) and Key Biscayne (lower) between 2009 and 2018 [20,21].…”

Section: Introductionmentioning

confidence: 99%

“…Figure 1 shows the time series of CO 2 monthly mean measured at Waliguan (upper) and Key Biscayne (lower) between 2009 and 2018 [20,21]. The global mean CO 2 concentration in the atmosphere is increasing, with an accelerating growth rate of about 2 ppmv/year [19]. The seasonal pattern has also been demonstrated as the CO 2 concentrations reach a peak at the beginning of spring in the northern Hemisphere, and then decline to a minimum near the end of the growing season [19].…”

Section: Introductionmentioning

confidence: 99%

“…The global mean CO 2 concentration in the atmosphere is increasing, with an accelerating growth rate of about 2 ppmv/year [19]. The seasonal pattern has also been demonstrated as the CO 2 concentrations reach a peak at the beginning of spring in the northern Hemisphere, and then decline to a minimum near the end of the growing season [19]. CO 2 concentrations at both stations show an increasing trend with an annual fluctuation: the minimum usually occurs in the summer or early fall and the maximum in April-May.…”

Section: Introductionmentioning

confidence: 99%

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Effects of CO2 Changes on Hyperspectral Infrared Radiances and Its Implications on Atmospheric Temperature Profile Retrieval and Data Assimilation in NWP

Xue

et al. 2020

Remote Sensing

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Although atmospheric CO2 is a trace gas, it has seasonal variations and has increased over the last decade. Its seasonal variation and increase have substantial radiative effects on hyperspectral infrared (IR) radiance calculations in both longwave (LW) and shortwave (SW) CO2 absorption spectral regions that are widely used for weather and climate applications. The effects depend on the spectral coverage and spectral resolution. The radiative effect caused by the increase of CO2 has been calculated to be greater than 0.5 K within 5 years, whereas a radiative effect of 0.1–0.5 K is introduced by the seasonal variation in some CO2 absorption spectral regions. It is important to take into account the increasing trend and seasonal variation of CO2 in retrieving the atmospheric temperature profile from hyperspectral IR radiances and in the radiance assimilation in numerical weather prediction (NWP) models. The simulation further indicates that it is very difficult to separate atmospheric temperature and CO2 information from hyperspectral IR sounder radiances because the atmospheric temperature signal is much stronger than that of CO2 in the CO2 absorption IR spectral regions.

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Influence of dataset density on CO2 and CH4 trend calculation

Pérez

Sánchez

García

et al. 2019

Air Qual Atmos Health

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Seasonal and inter-annual variability of atmosphere CO2 based on NOAA Carbon Tracker analysis and satellite observations

Cited by 7 publications

References 27 publications

Silvopastoral systems improve carbon stocks at livestock ranches in Tabasco, Mexico

Silvopastoral systems improve carbon stocks at livestock ranches in Tabasco, Mexico

Effects of CO2 Changes on Hyperspectral Infrared Radiances and Its Implications on Atmospheric Temperature Profile Retrieval and Data Assimilation in NWP

Influence of dataset density on CO2 and CH4 trend calculation

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