scholarly journals Large Volume of CO2 Injection at the Cranfield, Early Field Test of the SECARB Phase III: Near-Surface Monitoring

2012 ◽  
Author(s):  
Changbing Yang ◽  
Katherine D. Romanak ◽  
Robert M. Holt ◽  
Jeff Lindner ◽  
Laura Smith ◽  
...  
Keyword(s):  
Field Test ◽  
Large Volume ◽  
Phase Iii ◽  
Co2 Injection ◽  
Near Surface ◽  
Surface Monitoring

Near-Surface Monitoring of Large-Volume CO2 Injection at Cranfield: Early Field Test of SECARB Phase III

SPE Journal ◽  
2013 ◽  
Vol 18 (03) ◽  
pp. 486-494 ◽  
Author(s):  
Changbing Yang ◽  
Katherine Romanak ◽  
Susan Hovorka ◽  
Robert M. Holt ◽  
Jeff Lindner ◽  
...  
Keyword(s):  
Carbon Sequestration ◽  
Shallow Groundwater ◽  
Soil Gas ◽  
Phase Iii ◽  
Co2 Injection ◽  
Co2 Leakage ◽  
Gas Monitoring ◽  
Near Surface ◽  
Surface Monitoring ◽  
Gas Component

Summary An early field project of the Southeast Regional Carbon Sequestration Partnership (SECARB) was conducted in Cranfield oil field, western Mississippi. Carbon dioxide (CO2) was injected into coarse-grained fluvial deposits of the Cretaceous lower Tuscaloosa formation, forming a gentle anticline at depths of 3300 m. CO2 injection started in July 2008, increasing to 23 wells (as of May 2011), with total injection rates greater than 1 million tons/yr. Focused monitoring programs of the deep subsurface and near surface have been implemented in different study areas. Here we present results of the near-surface monitoring program over a 3-year period, including shallow groundwater monitoring and soil-gas monitoring. A general methodology of detecting CO2 leakage into shallow groundwater chemistry is proposed. A set of geochemical indicator parameters was identified on the basis of the characterization of groundwater geochemistry, and these were further tested and validated using numerical modeling approaches, laboratory experiments, and field experiments. For soil-gas monitoring, a site (P-site) containing a plugged and abandoned well, a nearby open pit, and an engineered pad (representing a typical industrial near-surface environment for soil-gas monitoring) was selected for detailed study. The site was heavily instrumented with various sensors for measuring soil-gas concentrations at different depths, soil-water content, matric potential, and weather information. Three monitoring technologies were assessed: soil CO2 concentration measurements, CO2 flux measurements on the land surface, and multiple soil-gas component measurements. Results indicate that soil-gas-component measurements provide reliable information for gas-leakage detection. Methodologies of near-surface monitoring developed in this study can be used to improve CO2-leakage monitoring at other CO2 sequestration projects. This early field project was funded by the US Department of Energy, National Energy Technology Laboratory, as part of the Regional Carbon Sequestration Partnerships (RCSP) program. SECARB is led by the Southern States Energy Board (SSEB).

Near-surface monitoring for the ZERT shallow CO2 injection project

2009 ◽  
Vol 3 (6) ◽  
pp. 736-744 ◽  
Author(s):  
Brian R. Strazisar ◽  
Arthur W. Wells ◽  
J. Rodney Diehl ◽  
Richard W. Hammack ◽  
Garret A. Veloski
Keyword(s):  
Co2 Injection ◽  
Near Surface ◽  
Surface Monitoring

scholarly journals Air Quality and Climate Change, Topic 3 of the Model Inter-Comparison Study for Asia Phase III (MICS-Asia III), Part I: overview and model evaluation

2017 ◽  
Author(s):  
Meng Gao ◽  
Zhiwei Han ◽  
Zirui Liu ◽  
Meng Li ◽  
Jinyuan Xin ◽  
...  
Keyword(s):  
Air Quality ◽  
Model Evaluation ◽  
Air Pollutants ◽  
North China ◽  
Correlation Coefficients ◽  
Phase Iii ◽  
Comparison Study ◽  
Model Ensemble ◽  
Near Surface ◽  
Ensemble Mean

Abstract. Topic 3 of the Model Inter-Comparison Study for Asia (MICS-Asia) Phase III examines how online coupled air quality models perform in simulating high aerosol pollution in the North China Plain region during wintertime haze events and evaluates the importance of aerosol radiative and microphysical feedbacks. A comprehensive overview of the MICS-ASIA III Topic 3 study design, including descriptions of participating models and model inputs, the experimental designs, and results of model evaluation, are presented. Two winter months (January 2010 and January 2013) were selected as study periods, when severe haze occurred in North China. Simulations were designed to evaluate radiative and microphysical feedbacks, together and separately, relative to simulations without feedbacks. Six modeling groups from China, Korea and the United States submitted results from seven applications of online coupled chemistry-meteorology models. Results are compared to meteorology and air quality measurements, including the Campaign on Atmospheric Aerosol Research Network of China (CARE-China) network, and the Acid Deposition Monitoring Network in East Asia (EANET). The analysis focuses on model evaluations and aerosol effects on meteorology and air quality, and potentially other interesting topics, such as the impacts of model resolutions on aerosol-radiation-weather interactions. The model evaluations for January 2010 show that current online-coupled meteorology-chemistry model can generally well reproduced meteorological features and variations of major air pollutants, including aerosol concentrations. The correlation coefficients between multi-model ensemble mean and observed near-surface temperature, water vapor mixing ratio and wind speeds can reach as high as 0.99, 0.99 and 0.98. The correlation coefficients between multi-model ensemble mean and the CARE-China observed near-surface air pollutants range from 0.51 to 0.94 (0.51 for ozone and 0.94 for PM2.5). However, large discrepancies exist between simulated aerosol chemical compositions from different models, which is due to different parameterizations of chemical reactions. The coefficient of variation (standard deviation divided by average) can reach above 1.3 for sulfate in Beijing, and above 1.6 for nitrate and organic aerosol in coastal regions, indicating these compositions are less consistent from different models. During clean periods, simulated Aerosol Optical Depths (AOD) from different models are consistent, but peak values differ during severe haze event, which can be explained by the differences in simulated inorganic aerosol concentrations and the hygroscopic growth efficiency (affected by varied RH). These results provide some brief senses of how current online-coupled meteorology-chemistry models reproduce severe haze events, and some directions for future model improvements.

Multi-model evaluation of aerosol optical properties in the AeroCom phase III Control experiment, using ground and space based observations from AERONET, MODIS, AATSR and a merged satellite product as well as surface in-situ observations from GAW sites

2020 ◽  
Author(s):  
Jonas Gliß ◽  
Augustin Mortier ◽  
Michael Schulz ◽  
Keyword(s):  
Optical Properties ◽  
Relative Humidity ◽  
Control Experiment ◽  
Phase Iii ◽  
Aerosol Optical Properties ◽  
Absorption Coefficients ◽  
Data Set ◽  
Near Surface ◽  
Extinction Coefficients

<p>Within the framework of the AeroCom (Aerosol Comparisons between Observations and Models) initiative, the present day modelling of aerosol optical properties has been assessed using simulated data representative for the year 2010, from 14 global aerosol models participating in the Phase III Control experiment. The model versions are close or equal to those used for CMIP6 and AerChemMIP and inform also on bias in state of the art Earth-System-Models (ESMs).<br>Modelled column optical depths (total, fine and coarse mode AOD) and Angstrom Exponents (AE) were compared both with ground based observations from the Aerosol Robotic Network (AERONET, version 3) and space based observations from the AATSR instrument. In addition, the modelled AODs were compared with MODIS (Aqua and Terra) data and a satellite AOD data-set (MERGED-FMI) merged from 12 different individual AOD products. Furthermore, for the first time, the modelled near surface scattering (under dry conditions) and absorption coefficients were evaluated against measurements made at low relative humidity at surface in-situ GAW sites. <br>The AeroCom MEDIAN and most of the participating models underestimate the optical properties investigated, relative to remote sensing observations. AERONET AOD is underestimated by 21%+/-17%. Against satellite data, the model AOD biases range from -38% (MODIS-terra) to -17% (MERGED-FMI). Correlation coefficients of model AODs with AERONET, MERGED-FMI and AATSR-SU are high (0.8-0.9) and slightly lower against the two MODIS data-sets (0.6-0.8). Investigation of fine and coarse AODs from the MEDIAN model reveals biases of -10%+/-20% and -41%+/-29% against AERONET and -13% and -24% against AATSR-SU, respectively. The differences in model bias against AERONET and AATSR-SU are in agreement with the established bias of AATSR against AERONET. These results indicate that most of the AOD bias is due to missing coarse AOD in the regions covered by these observations. Underestimates are also found when comparing the models against the surface GAW observations, showing AeroCom MEDIAN mean bias and inter-model variation of -44%+/-22% and -32%+/-34% for scattering and absorption coefficients, respectively. Dry scattering shows higher underestimation than AOD at ambient relative humidity and is in agreement with recent findings that suggest that models tend to overestimate scattering enhancement due to hygroscopic growth. <br>Considerable diversity is found among the models in the simulated near surface absorption coefficients, particularly in regions associated with dust (e.g. Sahara, Tibet), biomass burning (e.g. Amazonia, Central Australia) and biogenic emissions (e.g. Amazonia). Regions associated with high anthropogenic BC emissions such as China and India exhibit comparatively good agreement for all models. Evaluation of modelled column AEs shows an underestimation of 9%+/-24% against AERONET and -21% against AATSR-SU. This suggests that models tend to overestimate particle size, with implications for lifetime and radiative transfer calculations. An investigation of modelled emissions, burdens and lifetimes, mass-specific-extinction coefficients (MECs) and optical depths (ODs) for each species and model reveals considerable diversity in most of these parameters. Inter-model spread of aerosol species lifetime appears to be similar to that of mass extinction coefficients, suggesting that AOD uncertainties are still associated to a broad spectrum of parameterised aerosol processes.</p>

scholarly journals Air quality and climate change, Topic 3 of the Model Inter-Comparison Study for Asia Phase III (MICS-Asia III) – Part 1: Overview and model evaluation

2018 ◽  
Vol 18 (7) ◽  
pp. 4859-4884 ◽  
Author(s):  
Meng Gao ◽  
Zhiwei Han ◽  
Zirui Liu ◽  
Meng Li ◽  
Jinyuan Xin ◽  
...  
Keyword(s):  
Air Quality ◽  
Model Evaluation ◽  
The United States ◽  
Chemical Mechanism ◽  
Research Network ◽  
Phase Iii ◽  
Chemical Compositions ◽  
Comparison Study ◽  
Near Surface ◽  
Ensemble Mean

Abstract. Topic 3 of the Model Inter-Comparison Study for Asia (MICS-Asia) Phase III examines how online coupled air quality models perform in simulating high aerosol pollution in the North China Plain region during wintertime haze events and evaluates the importance of aerosol radiative and microphysical feedbacks. A comprehensive overview of the MICS-Asia III Topic 3 study design, including descriptions of participating models and model inputs, the experimental designs, and results of model evaluation, are presented. Six modeling groups from China, Korea and the United States submitted results from seven applications of online coupled chemistry–meteorology models. Results are compared to meteorology and air quality measurements, including data from the Campaign on Atmospheric Aerosol Research Network of China (CARE-China) and the Acid Deposition Monitoring Network in East Asia (EANET). The correlation coefficients between the multi-model ensemble mean and the CARE-China observed near-surface air pollutants range from 0.51 to 0.94 (0.51 for ozone and 0.94 for PM2.5) for January 2010. However, large discrepancies exist between simulated aerosol chemical compositions from different models. The coefficient of variation (SD divided by the mean) can reach above 1.3 for sulfate in Beijing and above 1.6 for nitrate and organic aerosols in coastal regions, indicating that these compositions are less consistent from different models. During clean periods, simulated aerosol optical depths (AODs) from different models are similar, but peak values differ during severe haze events, which can be explained by the differences in simulated inorganic aerosol concentrations and the hygroscopic growth efficiency (affected by varied relative humidity). These differences in composition and AOD suggest that future models can be improved by including new heterogeneous or aqueous pathways for sulfate and nitrate formation under hazy conditions, a secondary organic aerosol (SOA) formation chemical mechanism with new volatile organic compound (VOCs) precursors, yield data and approaches, and a more detailed evaluation of the dependence of aerosol optical properties on size distribution and mixing state. It was also found that using the ensemble mean of the models produced the best prediction skill. While this has been shown for other conditions (for example, the prediction of high-ozone events in the US (McKeen et al., 2005)), this is to our knowledge the first time it has been shown for heavy haze events.

scholarly journals A model comparison initiative for a CO2 injection field test: an introduction to Sim-SEQ

2012 ◽  
Vol 67 (2) ◽  
pp. 601-611 ◽  
Author(s):  
Sumit Mukhopadhyay ◽  
Jens T. Birkholzer ◽  
Jean-Philippe Nicot ◽  
Seyyed A. Hosseini
Keyword(s):  
Field Test ◽  
Model Comparison ◽  
Co2 Injection

Design of a two-well field test to determine in situ residual and dissolution trapping of CO2 applied to the Heletz CO2 injection site

2013 ◽  
Vol 19 ◽  
pp. 642-651 ◽  
Author(s):  
Fritjof Fagerlund ◽  
Auli Niemi ◽  
Jacob Bensabat ◽  
Vladimir Shtivelman
Keyword(s):  
Injection Site ◽  
Field Test ◽  
Co2 Injection ◽  
Well Field
Sign in / Sign up

Export Citation Format

Share Document