Influence of monsoons on atmospheric CO2 spatial variability and ground-based monitoring over India

Tiwari, Yogesh K.; Vellore, Ramesh; Kumar, K. Ravi; Schoot, Marcel van der; Cho, Chun-Ho

doi:10.1016/j.scitotenv.2014.05.045

Cited by 47 publications

(39 citation statements)

References 28 publications

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“…(1) the interannually varying anthropogenic emissions obtained from the Emission Database for Global Atmospheric Research (EDGAR) v4.2 FT2010 product (http://edgar.jrc. ec.europa.eu, last access: 21 October 2016), including emissions from rice cultivation with the seasonal variations based on Matthews et al (1991) imposed to the original yearly data; (2) climatological wetland emissions based on the scheme developed by Kaplan et al (2006); (3) interannually and seasonally varying biomass burning emissions from Global Fire Emissions Database (GFED) v4.1 product (Randerson et al, 2012;Van Der Werf et al, 2017; http://www. globalfiredata.org/, last access: 3 May 2017); (4) climatological termite emissions (Sanderson, 1996); (5) climatological ocean emissions (Lambert and Schmidt, 1993); and (6) climatological soil uptake (Ridgwell et al, 1999).…”

Section: Prescribed Ch 4 and Co 2 Surface Fluxesmentioning

confidence: 99%

“…The prescribed CO 2 fluxes used to simulate the concentration fields are based on the following datasets: (1) three variants (hourly, daily and monthly means) of interannually varying fossil fuel emissions produced by the Institut für Energiewirtschaft und Rationelle Energieanwendung (IER), Universität Stuttgart, on the basis of EDGARv4.2 product (hereafter IER-EDGAR, http://carbones.ier.uni-stuttgart. de/wms/index.html, last access: 14 December 2014) (Pregger et al, 2007); (2) interannually and seasonally varying biomass burning emission from GFEDv4.1 (Randerson et al, 2012;Van Der Werf et al, 2017; http://www. globalfiredata.org/, last access: 3 March 2017); (3) interannually and hourly varying terrestrial biospheric fluxes produced from outputs of the Organizing Carbon and Hydrology in Dynamic EcosystEms (ORCHIDEE) model; and (4) interannually and seasonally varying air-sea CO 2 gas exchange maps developed by NOAA's Pacific Marine Environmental Laboratory (PMEL) and Atlantic Oceanographic and Meteorological Laboratory (AOML) groups (Park et al, 2010).…”

Section: Prescribed Ch 4 and Co 2 Surface Fluxesmentioning

confidence: 99%

“…tion; see also Tiwari et al, 2014) and stations from the Indo-French cooperative research program (the HLE, PON and PBL stations, Lin et al, 2015;Swathi et al, 2013). All the CH 4 (CO 2 ) flask measurements are reported on or linked to the NOAA2004 (WMOX2007) calibration scale, which guarantees comparability between stations in terms of annual means.…”

Section: Atmospheric Ch 4 and Co 2 Observationsmentioning

confidence: 99%

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Simulating CH4 and CO2 over South and East Asia using the zoomed chemistry transport model LMDz-INCA

et al. 2018

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Abstract. The increasing availability of atmospheric measurements of greenhouse gases (GHGs) from surface stations can improve the retrieval of their fluxes at higher spatial and temporal resolutions by inversions, provided that transport models are able to properly represent the variability of concentrations observed at different stations. South and East Asia (SEA; the study area in this paper including the regions of South Asia and East Asia) is a region with large and very uncertain emissions of carbon dioxide (CO2) and methane (CH4), the most potent anthropogenic GHGs. Monitoring networks have expanded greatly during the past decade in this region, which should contribute to reducing uncertainties in estimates of regional GHG budgets. In this study, we simulate concentrations of CH4 and CO2 using zoomed versions (abbreviated as “ZAs”) of the global chemistry transport model LMDz-INCA, which have fine horizontal resolutions of ∼0.66∘ in longitude and ∼0.51∘ in latitude over SEA and coarser resolutions elsewhere. The concentrations of CH4 and CO2 simulated from ZAs are compared to those from the same model but with standard model grids of 2.50∘ in longitude and 1.27∘ in latitude (abbreviated as “STs”), both prescribed with the same natural and anthropogenic fluxes. Model performance is evaluated for each model version at multi-annual, seasonal, synoptic and diurnal scales, against a unique observation dataset including 39 global and regional stations over SEA and around the world. Results show that ZAs improve the overall representation of CH4 annual gradients between stations in SEA, with reduction of RMSE by 16–20 % compared to STs. The model improvement mainly results from reduction in representation error at finer horizontal resolutions and thus better characterization of the CH4 concentration gradients related to scattered distributed emission sources. However, the performance of ZAs at a specific station as compared to STs is more sensitive to errors in meteorological forcings and surface fluxes, especially when short-term variabilities or stations close to source regions are examined. This highlights the importance of accurate a priori CH4 surface fluxes in high-resolution transport modeling and inverse studies, particularly regarding locations and magnitudes of emission hotspots. Model performance for CO2 suggests that the CO2 surface fluxes have not been prescribed with sufficient accuracy and resolution, especially the spatiotemporally varying carbon exchange between land surface and atmosphere. In addition, the representation of the CH4 and CO2 short-term variabilities is also limited by model's ability to simulate boundary layer mixing and mesoscale transport in complex terrains, emphasizing the need to improve sub-grid physical parameterizations in addition to refinement of model resolutions.

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Section: Prescribed Ch 4 and Co 2 Surface Fluxesmentioning

confidence: 99%

Section: Prescribed Ch 4 and Co 2 Surface Fluxesmentioning

confidence: 99%

Section: Atmospheric Ch 4 and Co 2 Observationsmentioning

confidence: 99%

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Simulating CH4 and CO2 over South and East Asia using the zoomed chemistry transport model LMDz-INCA

et al. 2018

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“…Cape Rama (CRI), a costal site on the south-west coast of India shows seasonal maxima one month before our observations in March with an annual amplitude of about 9 ppm (Bhattacharya et al, 2009). The Sinhagad (SNG) site located over the Western Ghats mountain range, show much larger seasonal cycles with annual amplitude at about 20 ppm (Tiwari et al, 2014). The amplitude of the mean annual cycle at the free tropospheric site, Hanle, at an altitude of 4500 m is observed to be 8.2 ± 0.4 ppm, with maxima in early May and minima in mid-September (Lin et al, 2015).…”

Section: N Chandra Et Al: Co 2 Over An Urban Regionmentioning

confidence: 99%

“…The first observations of CO 2 , CO and other greenhouse gases started in February 1993 from Cape Rama (CRI: a clean site) on the south-west coast of India using flask samples (Bhattacharya et al, 2009). Since then, several other groups have initiated the measurements of surface-level greenhouse gases Sharma et al, 2014;Tiwari et al, 2014;Lin et al, 2015). Most of these measurements are made at weekly or fortnightly time intervals.…”

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confidence: 99%

Temporal variations of atmospheric CO2 and CO at Ahmedabad in western India

et al. 2016

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Abstract. About 70 % of the anthropogenic carbon dioxide (CO 2 ) is emitted from the megacities and urban areas of the world. In order to draw effective emission mitigation policies for combating future climate change as well as independently validating the emission inventories for constraining their large range of uncertainties, especially over major metropolitan areas of developing countries, there is an urgent need for greenhouse gas measurements over representative urban regions. India is a fast developing country, where fossil fuel emissions have increased dramatically in the last three decades and are predicted to continue to grow further by at least 6 % per year through to 2025. The CO 2 measurements over urban regions in India are lacking. To overcome this limitation, simultaneous measurements of CO 2 and carbon monoxide (CO) have been made at Ahmedabad, a major urban site in western India, using a state-of-the-art laser-based cavity ring down spectroscopy technique from November 2013 to May 2015. These measurements enable us to understand the diurnal and seasonal variations in atmospheric CO 2 with respect to its sources (both anthropogenic and biospheric) and biospheric sinks. The observed annual average concentrations of CO 2 and CO are 413.0 ± 13.7 and 0.50 ± 0.37 ppm respectively. Both CO 2 and CO show strong seasonality with lower concentrations (400.3 ± 6.8 and 0.19 ± 0.13 ppm) during the south-west monsoon and higher concentrations (419.6 ± 22.8 and 0.72 ± 0.68 ppm) during the autumn (SON) season. Strong diurnal variations are also observed for both the species. The common factors for the diurnal cycles of CO 2 and CO are vertical mixing and rush hour traffic, while the influence of biospheric fluxes is also seen in the CO 2 diurnal cycle. Using CO and CO 2 covariation, we differentiate the anthropogenic and biospheric components of CO 2 and found significant contributions of biospheric respiration and anthropogenic emissions in the late night (00:00-05:00 h, IST) and evening rush hours (18:00-22:00 h) respectively. We compute total yearly emissions of CO to be 69.2 ± 0.07 Gg for the study region using the observed CO : CO 2 correlation slope and bottom-up CO 2 emission inventory. This calculated emission of CO is 52 % larger than the estimated emission of CO by the emissions database for global atmospheric research (EDGAR) inventory. The observations of CO 2 have been compared with an atmospheric chemistry-transport model (ACTM), which incorporates various components of CO 2 fluxes. ACTM is able to capture the basic variabilities, but both diurnal and seasonal amplitudes are largely underestimated compared to the observations. We attribute this underestimation by the model to uncertainties in terrestrial biosphere fluxes and coarse model resolution. The fossil fuel signal from the model shows fairly good correlation with observed CO 2 variations, which supports the overall dominance of fossil fuel emissions over the biospheric fluxes in this urban region.

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Observations and Modeling of GHG Concentrations and Fluxes Over India

Chakraborty

Burman

Roy

et al. 2020

Assessment of Climate Change Over the Indian Region

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Influence of monsoons on atmospheric CO2 spatial variability and ground-based monitoring over India

Cited by 47 publications

References 28 publications

Simulating CH<sub>4</sub> and CO<sub>2</sub> over South and East Asia using the zoomed chemistry transport model LMDz-INCA

Simulating CH<sub>4</sub> and CO<sub>2</sub> over South and East Asia using the zoomed chemistry transport model LMDz-INCA

Temporal variations of atmospheric CO<sub>2</sub> and CO at Ahmedabad in western India

Observations and Modeling of GHG Concentrations and Fluxes Over India

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Influence of monsoons on atmospheric CO2 spatial variability and ground-based monitoring over India

Cited by 47 publications

References 28 publications

Simulating CH&lt;sub&gt;4&lt;/sub&gt; and CO&lt;sub&gt;2&lt;/sub&gt; over South and East Asia using the zoomed chemistry transport model LMDz-INCA

Simulating CH&lt;sub&gt;4&lt;/sub&gt; and CO&lt;sub&gt;2&lt;/sub&gt; over South and East Asia using the zoomed chemistry transport model LMDz-INCA

Temporal variations of atmospheric CO&lt;sub&gt;2&lt;/sub&gt; and CO at Ahmedabad in western India

Observations and Modeling of GHG Concentrations and Fluxes Over India

Contact Info

Product

Resources

About

Simulating CH<sub>4</sub> and CO<sub>2</sub> over South and East Asia using the zoomed chemistry transport model LMDz-INCA

Simulating CH<sub>4</sub> and CO<sub>2</sub> over South and East Asia using the zoomed chemistry transport model LMDz-INCA

Temporal variations of atmospheric CO<sub>2</sub> and CO at Ahmedabad in western India