scholarly journals Measuring Regional Atmospheric CO2 Concentrations in the Lower Troposphere with a Non-Dispersive Infrared Analyzer Mounted on a UAV, Ogata Village, Akita, Japan

Atmosphere ◽  
2019 ◽  
Vol 10 (9) ◽  
pp. 487 ◽  
Author(s):  
Takashi Chiba ◽  
Yumi Haga ◽  
Makoto Inoue ◽  
Osamu Kiguchi ◽  
Takeshi Nagayoshi ◽  
...  
Keyword(s):  
Transport Model ◽  
Atmospheric Transport ◽  
Lower Troposphere ◽  
Co2 Concentration ◽  
Measuring System ◽  
Japan Meteorological Agency ◽  
Co2 Concentrations ◽  
Monthly Pattern ◽  
Carbon Dioxide Co2 ◽  
Atmospheric Co2 Concentrations

We have developed a simple measuring system prototype that uses an unmanned aerial vehicle (UAV) and a non-dispersive infrared (NDIR) analyzer to detect regional carbon dioxide (CO2) concentrations and obtain vertical CO2 distributions. Here, we report CO2 measurement results for the lower troposphere above Ogata Village, Akita Prefecture, Japan (about 40° N, 140° E, approximately −1 m amsl), obtained with this UAV system. The actual flight observations were conducted at 500, 400, 300, 200, 100, and 10 m above the ground, at least once a month during the daytime from February 2018 to February 2019. The raw CO2 values from the NDIR were calibrated by two different CO2 standard gases and high-purity nitrogen (N2) gas (as a CO2 zero gas; 0 ppm). During the observation period, the maximum CO2 concentration was measured in February 2019 and the minimum in August 2018. In all seasons, CO2 concentrations became higher as the flight altitude was increased. The monthly pattern of observed CO2 changes is similar to that generally observed in the Northern Hemisphere as well as to surface CO2 changes simulated by an atmospheric transport model of the Japan Meteorological Agency. It is highly probable that these changes reflect the vegetation distribution around the study area.

scholarly journals Sensitivity of simulated CO<sub>2</sub> concentration to sub-annual variations in fossil fuel CO<sub>2</sub> emissions

2016 ◽  
Vol 16 (4) ◽  
pp. 1907-1918 ◽  
Author(s):  
Xia Zhang ◽  
Kevin R. Gurney ◽  
Peter Rayner ◽  
David Baker ◽  
Yu-ping Liu
Keyword(s):  
Fossil Fuel ◽  
Transport Model ◽  
Atmospheric Transport ◽  
Vertical Mixing ◽  
Grid Cell ◽  
Co2 Concentration ◽  
Tracer Transport ◽  
Annual Variations ◽  
Atmospheric Co2 Concentrations ◽  
The Impact

Abstract. Recent advances in fossil fuel CO2 (FFCO2) emission inventories enable sensitivity tests of simulated atmospheric CO2 concentrations to sub-annual variations in FFCO2 emissions and what this implies for the interpretation of observed CO2. Six experiments are conducted to investigate the potential impact of three cycles of FFCO2 emission variability (diurnal, weekly and monthly) using a global tracer transport model. Results show an annual FFCO2 rectification varying from −1.35 to +0.13 ppm from the combination of all three cycles. This rectification is driven by a large negative diurnal FFCO2 rectification due to the covariation of diurnal FFCO2 emissions and diurnal vertical mixing, as well as a smaller positive seasonal FFCO2 rectification driven by the covariation of monthly FFCO2 emissions and monthly atmospheric transport. The diurnal FFCO2 emissions are responsible for a diurnal FFCO2 concentration amplitude of up to 9.12 ppm at the grid cell scale. Similarly, the monthly FFCO2 emissions are responsible for a simulated seasonal CO2 amplitude of up to 6.11 ppm at the grid cell scale. The impact of the diurnal FFCO2 emissions, when only sampled in the local afternoon, is also important, causing an increase of +1.13 ppmv at the grid cell scale. The simulated CO2 concentration impacts from the diurnally and seasonally varying FFCO2 emissions are centered over large source regions in the Northern Hemisphere, extending to downwind regions. This study demonstrates the influence of sub-annual variations in FFCO2 emissions on simulated CO2 concentration and suggests that inversion studies must take account of these variations in the affected regions.

scholarly journals A regional carbon data assimilation system and its preliminary evaluation in East Asia

2015 ◽  
Vol 15 (2) ◽  
pp. 1087-1104 ◽  
Author(s):  
Z. Peng ◽  
M. Zhang ◽  
X. Kou ◽  
X. Tian ◽  
X. Ma
Keyword(s):  
Transport Model ◽  
Atmospheric Transport ◽  
Co2 Flux ◽  
Co2 Concentration ◽  
Preliminary Evaluation ◽  
Co2 Fluxes ◽  
Scaling Factors ◽  
Multi Scale ◽  
Co2 Concentrations ◽  
Inflation Factor

Abstract. In order to optimize surface CO2 fluxes at grid scales, a regional surface CO2 flux inversion system (Carbon Flux Inversion system and Community Multi-scale Air Quality, CFI-CMAQ) has been developed by applying the ensemble Kalman filter (EnKF) to constrain the CO2 concentrations and applying the ensemble Kalman smoother (EnKS) to optimize the surface CO2 fluxes. The smoothing operator is associated with the atmospheric transport model to constitute a persistence dynamical model to forecast the surface CO2 flux scaling factors. In this implementation, the "signal-to-noise" problem can be avoided; plus, any useful observed information achieved by the current assimilation cycle can be transferred into the next assimilation cycle. Thus, the surface CO2 fluxes can be optimized as a whole at the grid scale in CFI-CMAQ. The performance of CFI-CMAQ was quantitatively evaluated through a set of Observing System Simulation Experiments (OSSEs) by assimilating CO2 retrievals from GOSAT (Greenhouse Gases Observing Satellite). The results showed that the CO2 concentration assimilation using EnKF could constrain the CO2 concentration effectively, illustrating that the simultaneous assimilation of CO2 concentrations can provide convincing CO2 initial analysis fields for CO2 flux inversion. In addition, the CO2 flux optimization using EnKS demonstrated that CFI-CMAQ could, in general, reproduce true fluxes at grid scales with acceptable bias. Two further sets of numerical experiments were conducted to investigate the sensitivities of the inflation factor of scaling factors and the smoother window. The results showed that the ability of CFI-CMAQ to optimize CO2 fluxes greatly relied on the choice of the inflation factor. However, the smoother window had a slight influence on the optimized results. CFI-CMAQ performed very well even with a short lag-window (e.g. 3 days).

scholarly journals Sensitivity of simulated CO2 concentration to sub-annual variations in fossil fuel CO2 emissions

2015 ◽  
Vol 15 (14) ◽  
pp. 20679-20708 ◽  
Author(s):  
X. Zhang ◽  
K. R. Gurney ◽  
P. Rayner ◽  
D. Baker ◽  
Y.-P. Liu
Keyword(s):  
Fossil Fuel ◽  
Transport Model ◽  
Atmospheric Transport ◽  
Vertical Mixing ◽  
Grid Cell ◽  
Co2 Concentration ◽  
Tracer Transport ◽  
Annual Variations ◽  
Atmospheric Co2 Concentrations ◽  
The Impact

Abstract. Recent advances in fossil fuel CO2 (FFCO2) emission inventories enable sensitivity tests of simulated atmospheric CO2 concentrations to sub-annual variations in FFCO2 emissions and what this implies for the interpretation of observed CO2. Six experiments are conducted to investigate the potential impact of three cycles of FFCO2 emission variability (diurnal, weekly and monthly) using a global tracer transport model. Results show an annual FFCO2 rectification varying from −1.35 to +0.13 ppm from the combination of all three cycles. This rectification is driven by a large negative diurnal FFCO2 rectification due to the covariation of diurnal FFCO2 emissions and diurnal vertical mixing, and a smaller positive seasonal FFCO2 rectification driven by the covariation of monthly FFCO2 emissions and monthly atmospheric transport. The diurnal FFCO2 emissions are responsible for a diurnal FFCO2 concentration amplitude of up to 9.12 ppm at the grid cell scale. Similarly, the monthly FFCO2 emissions are responsible for a simulated seasonal CO2 amplitude of up to 6.11 ppm at the grid cell scale. The impact of the diurnal FFCO2 emissions, when only sampled in the local afternoon is also important, causing an increase of +1.13 ppmv at the grid cell scale. The simulated CO2 concentration impacts from the diurnally and seasonally-varying FFCO2 emissions are centered over large source regions in the Northern Hemisphere, extending to downwind regions. This study demonstrates the influence of sub-annual variations in FFCO2 emissions on simulated CO2 concentration and suggests that inversion studies must take account of these variations in the affected regions.

scholarly journals Elevated field atmospheric CO2 concentrations affect the characteristics of winter wheat (cv. Bologna) grains

2017 ◽  
Vol 68 (8) ◽  
pp. 713 ◽  
Author(s):  
Francesca Verrillo ◽  
Franz-Werner Badeck ◽  
Valeria Terzi ◽  
Fulvia Rizza ◽  
Letizia Bernardo ◽  
...  
Keyword(s):  
Co2 Enrichment ◽  
Co2 Concentration ◽  
Triticum Aestivum L ◽  
Interactive Effects ◽  
Elevated Concentration ◽  
Co2 Concentrations ◽  
Co2 Levels ◽  
Carbon Dioxide Co2 ◽  
Atmospheric Co2 Concentrations ◽  
The Impact

The aim of this study was to investigate the impact of elevated concentration of carbon dioxide (CO2), as expected over coming decades, on yield and quality of winter bread wheat (Triticum aestivum L.). Plants (cv. Bologna) were grown by using the free-air CO2 enrichment (FACE) system at Fiorenzuola d’Arda under ambient (control) and elevated (570 ppm, e[CO2]) CO2 concentrations for two growing seasons. We addressed whether there would be a response of wheat grains to elevated CO2 concentration in terms of the contents of nitrogen (N), micro- and macronutrients, proteins and free amino acids. Under e[CO2], total wheat biomass and grain yield increased in both years of the study. Grain N percentage was reduced under e[CO2], but grain N yield (kg ha–1) was increased. Among macro- and micronutrients, a decrease in zinc concentration was observed. The proteome pattern was significantly different in grains grown at the two different CO2 levels, but the observed changes were highly dependent on interactions with prevailing environmental conditions. Finally, a negative trend was observed in the early germination rates of seeds from plants grown under e[CO2] compared with the controls. The results suggest that the expected increase in CO2 levels and their interactive effects with environmental variables may influence agronomic performance by increasing yield and negatively affecting quality.

scholarly journals A regional carbon flux data assimilation system and its preliminary evaluation in East Asia

2014 ◽  
Vol 14 (14) ◽  
pp. 20345-20381
Author(s):  
Z. Peng ◽  
M. Zhang ◽  
X. Kou ◽  
X. Tian ◽  
X. Ma
Keyword(s):  
Carbon Flux ◽  
Transport Model ◽  
Atmospheric Transport ◽  
Co2 Flux ◽  
Co2 Concentration ◽  
Preliminary Evaluation ◽  
Co2 Fluxes ◽  
Scaling Factors ◽  
Co2 Concentrations ◽  
Inflation Factor

Abstract. In order to optimize surface CO2 fluxes at finer scales, a regional surface CO2 flux inversion system (Carbon Flux Inversion system and Community Multi-scale Air Quality, CFI-CMAQ) has been developed by simultaneously assimilating CO2 concentrations and surface CO2 fluxes into the regional modeling system, CMAQ. The smoothing operator is associated with the atmospheric transport model to constitute a persistence dynamical model to forecast the surface CO2 flux scaling factors. In this implementation, the "signal-to-noise" problem can be avoided; plus, any useful observed information achieved by the current assimilation cycle can be transferred into the next assimilation cycle. Thus, the surface CO2 fluxes can be optimized as a whole at the grid scale in CFI-CMAQ. The performance of CFI-CMAQ was quantitatively evaluated through a set of Observing System Simulation Experiments (OSSEs) by assimilating CO2 retrievals from GOSAT (Greenhouse Gases Observing Satellite). The results showed that the CO2 concentration assimilation using the ensemble Kalman filter (EnKF) could constrain the CO2 concentrations effectively, illustrating that the simultaneous assimilation of CO2 concentrations can provide convincing CO2 initial analysis fields for CO2 flux inversion. In addition, the CO2 flux optimization using the ensemble Kalman smoother (EnKS) demonstrated that CFI-CMAQ could in general reproduce true fluxes at finer scales with acceptable bias. Two further sets of numerical experiments were conducted to investigate the sensitivities of the inflation factor of scaling factors and the smoother window. The results showed that the ability of CFI-CMAQ to optimize CO2 fluxes greatly relied on the choice of the inflation factor. However, the smoother window had a slight influence on the optimized results. CFI-CMAQ performed very well even with a short lag-window (e.g. 3 days).

scholarly journals Study of the main processes driving atmospheric CH<sub>4</sub> variability in a rural Spanish region

2017 ◽  
Author(s):  
Claudia Grossi ◽  
Felix R. Vogel ◽  
Roger Curcoll ◽  
Alba Àgueda ◽  
Arturo Vargas ◽  
...  
Keyword(s):  
Transport Model ◽  
Atmospheric Transport ◽  
Daily Basis ◽  
Atmospheric Variability ◽  
Absolute Deviation ◽  
Monthly Basis ◽  
Bottom Up ◽  
Methane Fluxes ◽  
Carbon Dioxide Co2 ◽  
Atmospheric Concentrations

Abstract. Atmospheric concentrations of the two main greenhouse gases (GHGs), carbon dioxide (CO2) and methane (CH4), are continuously measured since November 2012 at the Spanish rural station of Gredos (GIC3), within the climate network ClimaDat, together with atmospheric radon (222Rn) tracer and meteorological parameters. The atmospheric variability of CH4 concentrations measured from 2013 to 2015 at GIC3 has been analyzed in this study. It is interpreted in relation to the variability of measured 222Rn concentrations, modelled 222Rn fluxes and modelled heights of the planetary boundary layer (PBLH) in the same period. In addition, nocturnal fluxes of CH4 were estimated using two methods: the Radon Tracer Method (RTM) and one based on the EDGARv4.2 bottom-up emission inventory. Both previous methods have been applied using the same footprints, calculated with the atmospheric transport model FLEXPARTv6.2. Results show that daily and seasonal changes in atmospheric concentrations of 222Rn (and the corresponding fluxes) can help to understand the atmospheric CH4 variability. On daily basis, the variation in the PBLH mainly drives changes in 222Rn and CH4 concentrations while, on monthly basis, their atmospheric variability seems to depend on changes in their emissions. The median value of RTM based methane fluxes (FR_CH4) is 0.17 mg CH4 m−2 h−1 with an absolute deviation of 0.08 mg CH4 m−2 h−1. Median methane fluxes based on bottom-up inventory (FE_CH4) is of 0.32 mg CH4 m−2 h−1 with an absolute deviation of 0.06 mg CH4 m−2 h−1. Monthly FR_CH4 flux shows a seasonality which is not observed in the monthly FE_CH4 flux. During January–May FR_CH4 fluxes present a median value of 0.08 mg CH4 m−2 h−1 with an absolute deviation of 0.05 mg CH4 m−2 h−1 and a median value of 0.19 mg CH4 m−2 h−1 with an absolute deviation of 0.06 mg CH4 m−2 h−1 during June–December. This seasonal doubling of the median methane fluxes calculated by RTM at the GIC3 area seems to be mainly related to the alternate presence of transhumant livestock in the GIC3 area. The results obtained in this study highlight the benefit of applying independent RTM to improve the seasonality of the emission factors from bottom-up inventories.

scholarly journals Global to local impacts on atmospheric CO2 caused by COVID-19 lockdown

2021 ◽  
Author(s):  
Ning Zeng
Keyword(s):  
Fossil Fuel ◽  
Transport Model ◽  
Atmospheric Transport ◽  
Carbon Sink ◽  
Co2 Concentration ◽  
Atmospheric Co2 ◽  
Monitoring Systems ◽  
Carbon Cycle Model ◽  
Safe Level ◽  
Small Change

&lt;p&gt;&lt;span&gt;The world-wide lockdown in response to the COVID-19 pandemic in year 2020 led to economic slowdown and large reduction of fossil fuel CO2 emissions 1,2, but it is unclear how much it would reduce atmospheric CO2 concentration, the main driver of climate change, and whether it can be observed. We estimated that a 7.9% reduction in emissions for 4 months would result in a 0.25 ppm decrease in the Northern Hemisphere CO2, an increment that is within the capability of current CO2 analyzers, but is a few times smaller than natural CO2 variabilities caused by weather and the biosphere such as El Nino. We used a state-of-the-art atmospheric transport model to simulate CO2, driven by a new daily fossil fuel emissions dataset and hourly biospheric fluxes from a carbon cycle model forced with observed climate variability. Our results show a 0.13 ppm decrease in atmospheric column CO2 anomaly averaged over 50S-50N for the period February-April 2020 relative to a 10-year climatology. A similar decrease was observed by the carbon satellite GOSAT3. Using model sensitivity experiments, we further found that COVID, the biosphere and weather contributed 54%, 23%, and 23% respectively. In May 2020, the CO2 anomaly continued to decrease and was 0.36 ppm below climatology, mostly due to the COVID reduction and a biosphere that turned from a relative carbon source to carbon sink, while weather impact fluctuated. This seemingly small change stands out as the largest sub-annual anomaly in the last 10 years. Measurements from global ground stations were analyzed. At city scale, on-road CO2 enhancement measured in Beijing shows reduction of 20-30 ppm, consistent with drastically reduced traffic during the lockdown, while station data suggest that the expected COVID signal of 5-10 ppm was swamped by weather-driven variability on multi-day time scales. The ability of our current carbon monitoring systems in detecting the small and short-lasting COVID signal on the background of fossil fuel CO2 accumulated over the last two centuries is encouraging. The COVID-19 pandemic is an unintended experiment whose impact suggests that to keep atmospheric CO2 at a climate-safe level will require sustained effort of similar magnitude and improved accuracy and expanded spatiotemporal coverage of our monitoring systems.&lt;/span&gt;&lt;/p&gt;

scholarly journals Can seasonal and interannual variation in landscape CO<sub>2</sub> fluxes be detected by atmospheric observations of CO<sub>2</sub> concentrations made at a tall tower?

2014 ◽  
Vol 11 (3) ◽  
pp. 735-747 ◽  
Author(s):  
T. L. Smallman ◽  
M. Williams ◽  
J. B. Moncrieff
Keyword(s):  
Interannual Variation ◽  
Atmospheric Transport ◽  
Co2 Exchange ◽  
Atmospheric Co2 ◽  
Co2 Uptake ◽  
Post Harvest ◽  
Co2 Concentrations ◽  
Prevailing Wind Direction ◽  
Atmospheric Co2 Concentrations ◽  
Tall Tower

Abstract. The coupled numerical weather model WRF-SPA (Weather Research and Forecasting model and Soil-Plant-Atmosphere model) has been used to investigate a 3 yr time series of observed atmospheric CO2 concentrations from a tall tower in Scotland, UK. Ecosystem-specific tracers of net CO2 uptake and net CO2 release were used to investigate the contributions to the tower signal of key land covers within its footprint, and how contributions varied at seasonal and interannual timescales. In addition, WRF-SPA simulated atmospheric CO2 concentrations were compared with two coarse global inversion models, CarbonTrackerEurope and the National Oceanic and Atmospheric Administration's CarbonTracker (CTE-CT). WRF-SPA realistically modelled both seasonal (except post harvest) and daily cycles seen in observed atmospheric CO2 at the tall tower (R2 = 0.67, rmse = 3.5 ppm, bias = 0.58 ppm). Atmospheric CO2 concentrations from the tall tower were well simulated by CTE-CT, but the inverse model showed a poorer representation of diurnal variation and simulated a larger bias from observations (up to 1.9 ppm) at seasonal timescales, compared to the forward modelling of WRF-SPA. However, we have highlighted a consistent post-harvest increase in the seasonal bias between WRF-SPA and observations. Ecosystem-specific tracers of CO2 exchange indicate that the increased bias is potentially due to the representation of agricultural processes within SPA and/or biases in land cover maps. The ecosystem-specific tracers also indicate that the majority of seasonal variation in CO2 uptake for Scotland's dominant ecosystems (forests, cropland and managed grassland) is detectable in observations within the footprint of the tall tower; however, the amount of variation explained varies between years. The between years variation in detectability of Scotland's ecosystems is potentially due to seasonal and interannual variation in the simulated prevailing wind direction. This result highlights the importance of accurately representing atmospheric transport used within atmospheric inversion models used to estimate terrestrial source/sink distribution and magnitude.

Sources and Sinks of Atmospheric CO2

1992 ◽  
Vol 40 (5) ◽  
pp. 407 ◽  
Author(s):  
JA Taylor ◽  
J Lloyd
Keyword(s):  
Climate Change ◽  
Biomass Burning ◽  
Transport Model ◽  
Atmospheric Co2 ◽  
Tropical Rainforests ◽  
Co2 Uptake ◽  
Tracer Transport ◽  
Intergovernmental Panel ◽  
Co2 Concentrations ◽  
Atmospheric Co2 Concentrations

The biosphere plays an important role in determining the sources, sinks, levels and rates of change of atmospheric CO2 concentrations. Significant uncertainties remain in estimates of the fluxes of CO2 from biomass burning and deforestation, and uptake and storage of CO2 by the biosphere arising from increased atmospheric CO2 concentrations. Calculation of probable rates of carbon sequestration for the major ecosystem complexes and global 3-D tracer transport model runs indicate the possibility that a significant net CO2 uptake (> 1 Pg C yr-1), a CO2 'fertilisation effect', may be occurring in tropical rainforests, effectively accounting for much of the 'missing sink'. This sink may currently balance much of the CO2 added to the atmosphere from deforestation and biomass burning. Interestingly, CO2 released from biomass burning may itself be playing an important role in enhanced carbon storage by tropical rainforests. This has important implications for predicting future CO2 concentrations. If tropical rainforest destruction continues then much of the CO2 stored as a result of the CO2 'fertilisation effect' will be rereleased to the atmosphere and much of the 'missing sink' will disappear. These effects have not been considered in the IPCC (Intergovernmental Panel on Climate Change) projections of future atmospheric CO2 concentrations. Predictions which take account of the combined effects of deforestation, the return of carbon previously stored through the CO2 'fertilisation effect' and the loss of a large proportion of the 'missing sink' as a result of deforestation, would result in much higher predicted concentrations and rates of increase of atmospheric CO2 and, as a consequence, accelerated rates of climate change.

scholarly journals Global emissions of HFC-143a (CH<sub>3</sub>CF<sub>3</sub>) and HFC-32 (CH<sub>2</sub>F<sub>2</sub>) from in situ and air archive atmospheric observations

2014 ◽  
Vol 14 (17) ◽  
pp. 9249-9258 ◽  
Author(s):  
S. O'Doherty ◽  
M. Rigby ◽  
J. Mühle ◽  
D. J. Ivy ◽  
B. R. Miller ◽  
...  
Keyword(s):  
Growth Rate ◽  
Mole Fraction ◽  
Radiative Forcing ◽  
Transport Model ◽  
Atmospheric Transport ◽  
Lower Troposphere ◽  
Emission Rates ◽  
Global Emission ◽  
Atmospheric Observations

Abstract. High-frequency, in situ observations from the Advanced Global Atmospheric Gases Experiment (AGAGE), for the period 2003 to 2012, combined with archive flask measurements dating back to 1977, have been used to capture the rapid growth of HFC-143a (CH3CF3) and HFC-32 (CH2F2) mole fractions and emissions into the atmosphere. Here we report the first in situ global measurements of these two gases. HFC-143a and HFC-32 are the third and sixth most abundant hydrofluorocarbons (HFCs) respectively and they currently make an appreciable contribution to the HFCs in terms of atmospheric radiative forcing (1.7 ± 0.04 and 0.7 ± 0.02 mW m−2 in 2012 respectively). In 2012 the global average mole fraction of HFC-143a was 13.4 ± 0.3 ppt (1σ) in the lower troposphere and its growth rate was 1.4 ± 0.04 ppt yr−1; HFC-32 had a global mean mole fraction of 6.2 ± 0.2 ppt and a growth rate of 1.1 ± 0.04 ppt yr−1 in 2012. The extensive observations presented in this work have been combined with an atmospheric transport model to simulate global atmospheric abundances and derive global emission estimates. It is estimated that 23 ± 3 Gg yr−1 of HFC-143a and 21 ± 11 Gg yr−1 of HFC-32 were emitted globally in 2012, and the emission rates are estimated to be increasing by 7 ± 5% yr−1 for HFC-143a and 14 ± 11% yr−1 for HFC-32.

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