Targeting for optimal grid-wide deployment of carbon capture and storage (CCS) technology

Carbon capture and storage (CCS) techniques are considered as one of the promising approaches to reduce carbon dioxide (CO₂) emissions from fossil fuel based power generation, which still accounts for a significant portion of greenhouse gas emissions in the world. CCS technology can be used to mitigate greenhouse gas emissions, with the additional advantage that it allows continuing use reliable and inexpensive fossil fuels. However, CCS retrofit entails major capital costs as well as a reduction of overall thermal efficiency and power output. Thus, it is essential for planning purposes to implement the minimal extent of CCS retrofit while meeting the specified carbon emission limits for the power sector. At the same time, it is necessary to plan for compensatory power generation capacity to offset energy losses resulting from CCS retrofit. In this paper, an algebraic targeting technique is presented for planning of grid-wide CCS retrofits in the power generation sector with compensatory power. The targeting technique is developed based on pinch analysis. In addition, the proposed methodologies are illustrated through case studies based on grid data in India and the Philippines. Sensitivity analysis is carried out to determine the suitable CCS technology and compensatory power source which satisfy emission limits.     

Corrosion behavior of steels for CO2 injection

The process chain for Carbon Capture and Sequestration (CCS) includes tubing for injection of CO₂ into saline aquifers. The compressed CO₂ is likely to contain specific impurities; small concentrations of SO₂ and NO₂ in combination with oxygen and humidity are most harmful. In addition, CO₂ saturated brine is supposed to rise in the well when the injection process is interrupted. The material selection has to ensure that neither CO₂ nor brine or a combination of both will leak out of the inner tubing. In this comprehensive paper the investigated materials range from low-alloy steels and 13% Cr steels up to high-alloy materials. Electrochemical tests as well as long term exposure tests were performed in CO₂, in brine and combination of both; pressure was up to 100 bar, temperature up to 60 °C. Whereas the CO₂ stream itself can be handled using low alloy steels, combinations of CO₂ and brine require more resistant materials to control the strong tendency to pitting corrosion. The corrosion behavior of heat-treated steels depends on factors such as microstructure and carbon content. For different sections of the injection tube, appropriate materials should be used to guarantee safety and consider cost effectiveness.     

Thermodynamic method for the prediction of solid CO2 formation from multicomponent mixtures

The increase in GHG concentration has a direct effect on global climate conditions. Among the possible technologies to mitigate GHG emissions, CCS is being accepted to gain emission reduction. Such technology also involves cryogenic CO₂ capture processes based on CO₂ freeze-out or where the formation of solid CO₂ must be avoided. Captured CO₂ is usually transported in pipelines for the reinjection.The risk associated to the release of CO₂ is due to the changing temperatures and pressures the system may experience, which can lead to the deposition of solid CO₂ where it must be avoided. Prolonged exposure to dry ice can cause severe skin damage and its resublimation could pose a danger of hypercapnia. It is, thus, necessary to build up a tool able to predict the conditions in which CO₂ can freeze-out.A thermodynamic methodology based on cubic EoSs has been developed which is able to predict solid–liquid–vapor equilibrium of CO₂ mixtures with n-alkanes or H₂S which are usually found in equipment for acidic gas, mainly natural gas, treatment.The focus is a detailed analysis of the method performances when more than two components are present since, for such a case, literature does not provide significant modeling results.     

Fuzzy optimization of multi-period carbon capture and storage systems with parametric uncertainties

Carbon capture and storage (CCS) is an important technology option for reducing industrial greenhouse gas emissions. In practice, CO₂ sources are easy to characterize, while the estimation of relevant properties of storage sites, such as capacity and injection rate limit (i.e., injectivity), is subject to considerable uncertainty. Such uncertainties need to be accounted for in planning CCS deployment on a large scale for effective use of available storage sites. In particular, the uncertainty introduces technical risks that may result from overestimating the limits of given storage sites. In this work, a fuzzy mixed integer linear program (FMILP) is developed for multi-period CCS systems, accounting for the technical risk arising from uncertainties in estimates of sink parameters, while still attaining satisfactory CO₂ emissions reduction. In the model, sources are assumed to have precisely known CO₂ flow rates and operating lives, while geological sinks are characterized with imprecise fuzzy capacity and injectivity data. Three case studies are then presented to illustrate the model. Results of these examples illustrate the tradeoff inherent in planning CCS systems under parametric uncertainty.     

Gas Transfer Coefficient Evaluation in the Mediterranean Sea Using Bomb Produced Radiocarbon

A study on the carbon dioxide exchange at the water-air interface in the Western Mediterranean Sea was carried out. the attention was focused on the mean air-sea flux estimations by radiocarbon profiles and bomb ¹⁴C concentration atmospheric data. Sampling techniques and analytical methods are reported; mass balance evaluations on data recorded during the MED'92 cruise are presented and discussed briefly.     

Unintended consequences of price controls: An application to allowance markets

Price controls established in a cap-and-trade allowance market are intended to reduce cost uncertainty by constraining allowance prices between a ceiling and floor; however, they could provide opportunities for strategic actions by firms that would lower government revenue and increase emissions. In particular, when the ceiling price is supported by introducing new allowances into the market, firms could choose to buy allowances at the ceiling price, regardless of the prevailing market price, in order to lower the equilibrium price of all allowances. Those purchases could either be transacted by firms intending to manipulate the market price or be induced through the introduction of inaccurate information about the cost of emissions abatement. Theory and simulations using allowance elasticity estimates for U.S. firms suggest that the manipulation could be profitable under the stylized setting and assumptions evaluated in the paper, although in practice many other conditions will determine its use.     

Changes in CO2 flux for different recovery processes of desertification in the alpine meadows of Northwest Sichuan北大核心CSCD

Desertification has emerged as a serious threat to the alpine meadows of Northwest Sichuan in recent decades. Artificial vegetation had certain effects on desertification recovery, while how the CO2 flux changed and its reasons are still unclear. During the growing season in 2016 (i.e., from July to September), we selected the desertified alpine meadows with different recovery degrees, including the early stage of restoration, the middle stage of restoration, the late stage of restoration, and control (the unrecovered desertification meadow) as four transects. CO2 flux was measured by the instrument LI-8100, and the microenvironment factors that affected CO2 flux changes were analyzed. The results showed that the carbon sequestration function of desertified alpine meadows gradually increased with the degree of recovery. Net ecosystem exchange (NEE) were -1.61, -3.55, and -4.38 μmol m-2 s-1 in the early, mid-term, and late transects, respectively, and the most dramatic changes occurred from the early stage to mid-term stage, increasing by 120.50%. Both ecosystem respiration (ER) and soil respiration (SR) were enhanced significantly with restoration (P < 0.05). In mid or late July, NEE, ER, and SR reached their maximum values, and thereafter, the indicators varied to near zero (P < 0.05). During the whole growing season, the daily dynamic in CO2 flux for the control alpine meadow was mild and retained the trend of continuous release all day, but that in the desertified alpine meadow was a single peak pattern. Moreover, with restoration process, the peak of CO2 flux increased and reached a peak in the late stage of the recovery process. The regression analysis showed that there was a significant positive correlation between CO2 flux and vegetation coverage, aboveground biomass, and soil moisture (0-5 cm) (P < 0.01), and a weak correlation with 0-5-cm soil temperature (P < 0.01). This indicates that topsoil moisture (5 cm) is a more significant factor for CO2 flux than topsoil temperature during the growing season in the restoration of desertified alpine meadows in Northwest Sichuan. In general, the vegetation recovery significantly improved the carbon-sequestration ability of the desertified alpine meadows during the growing season in Northwest Sichuan, and at the middle stage of restoration, the carbon-sequestration ability improved significantly due to vegetation restoration and increase in topsoil (0-5 cm) moisture. © 2018 Science Press. All rights reserved.     

碳中和——中国发展转型的机遇与挑战

碳中和是《巴黎协定》提出的到21世纪末在全球范围内实现人为活动排放的温室气体排放总量与大自然吸收总量相平衡,这是《联合国气候变化框架公约》应对气候变化问题的终极目标。本文从碳中和的目的、本质和进展分析入手,提出了在实现碳中和问题上中国的机遇与挑战。     

Development and optimization of an Agro-BGC ecosystem model for C4 perennial grasses

Extrapolating simulations of bioenergy crop agro-ecosystems beyond data-rich sites requires biophysically accurate ecosystem models and careful estimation of model parameters not available in the literature. To increase biophysical accuracy we added C₄ perennial grass functionality and agricultural practices to the Biome-BGC (BioGeochemical Cycles) ecosystem model. This new model, Agro-BGC, includes enzyme-driven C₄ photosynthesis, individual live and dead leaf, stem, and root carbon and nitrogen pools, separate senescence and litter fall processes, fruit growth, optional annual seeding, flood irrigation, a growing degree day phenology with a killing frost option, and a disturbance handler that simulates nitrogen fertilization, harvest, fire, and incremental irrigation. To obtain spatially generalizable vegetation parameters we used a numerical method to optimize five unavailable parameters for Panicum virgatum (switchgrass) using biomass yield data from three sites: Mead, Nebraska, Rockspring, Pennsylvania, and Mandan, North Dakota. We then verified simulated switchgrass yields at three independent sites in Illinois (IL). Agro-BGC is more accurate than Biome-BGC in representing the physiology and dynamics of C₄ grass and management practices associated with agro-ecosystems. The simulated two-year average mature yields with single-site Rockspring optimization have Root Mean Square Errors (RMSE) of 70, 152, and 162 and biases of 43, −87, 156 g carbon m⁻² for Shabbona, Urbana, and Simpson IL, respectively. The simulated annual yields in June, August, October, December, and February have RMSEs of 114, 390, and 185 and biases of −19, −258, and 147 g carbon m⁻² for Shabbona, Urbana, and Simpson IL, respectively. These RMSE and bias values are all within the largest 90% confidence interval around respective IL site measurements. Twenty-four of twenty-six simulated annual yields with Rockspring optimization are within 95% confidence intervals of Illinois site measurements during the mature fourth and fifth years of growth. Ten of eleven simulated two-year average mature yields with Rockspring optimization are within 65% confidence intervals of Illinois site measurements and the eleventh is within the 95% confidence interval. Rockspring optimized Agro-BGC achieves accuracies comparable to those of two previously published models: Agricultural Land Management Alternatives with Numerical Assessment Criteria (ALMANAC) and Integrated Farm System Model (IFSM). Agro-BGC suffers from static vegetation parameters that can change seasonally and as plants age. Using mature plant data for optimization mitigates this deficiency. Our results suggest that a multi-site optimization scheme using mature plant data from more sites would be adequate for generating spatially generalizable vegetation parameters for simulating mature bioenergy crop agro-ecosystems with Agro-BGC.     

Modelling forest management within a global vegetation model—Part 1: Model structure and general behaviour

This article describes a new forest management module (FMM) that explicitly simulates forest stand growth and management within a process-based global vegetation model (GVM) called ORCHIDEE. The net primary productivity simulated by ORCHIDEE is used as an input to the FMM. The FMM then calculates stand and management characteristics such as stand density, tree size distribution, tree growth, the timing and intensity of thinnings and clear-cuts, wood extraction and litter generated after thinning. Some of these variables are then fed back to ORCHIDEE. These computations are made possible with a distribution-based modelling of individual tree size. The model derives natural mortality from the relative density index (rdi), a competition index based on tree size and stand density. Based on the common forestry management principle of avoiding natural mortality, a set of rules is defined to calculate the recurrent intensity and frequency of forestry operations during the stand lifetime. The new-coupled model is called ORCHIDEE-FM (forest management).The general behaviour of ORCHIDEE-FM is analysed for a broadleaf forest in north-eastern France. Flux simulation throughout a forest rotation compare well with the literature values, both in absolute values and dynamics.Results from ORCHIDEE-FM highlight the impact of forest management on ecosystem C-cycling, both in terms of carbon fluxes and stocks. In particular, the average net ecosystem productivity (NEP) of 225 gC m⁻² year⁻¹ is close to the biome average of 311 gC m⁻² year⁻¹. The NEP of the “unmanaged” case is 40% lower, leading us to conclude that management explains 40% of the cumulated carbon sink over 150 years. A sensitivity analysis reveals 4 major avenues for improvement: a better determination of initial conditions, an improved allocation scheme to explain age-related decline in productivity, and an increased specificity of both the self-thinning curve and the biomass-diameter allometry.