Spatial variation of carbon turnover time and carbon uptake in a Chinese desert steppe ecosystem
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This study presents a comprehensive pipeline network modeling framework to estimate the CO 2 delivery cost for CO 2 utilization and geologic CO 2 storage across the United States. We developed a Python-based CO 2 pipeline transportation cost model leveraging Argonne National Laboratory’s pipeline engineering expertise and detailed natural gas transmission pipeline cost data across U.S. regions. Using existing road corridors as practical routing guides, the model designs pipeline networks that aggregate CO 2 from one or multiple sources and deliver it to selected destinations. It then minimizes the total transportation cost by optimizing pipeline diameters and incorporating booster pumps. A key contribution is the incorporation of up-to-date, region-specific cost factors with itemized components for materials, labor, miscellaneous construction expenses, and right-of-way acquisition. Results emphasize that regional variation and economies of scale associated with CO 2 pipeline costs are significant and should be explicitly accounted for in screening and planning studies. By combining realistic routing constraints with regionalized cost inputs, the model provides transparent design methodology and location-specific insights into source–destination delivery costs, including the effects of routing complexity along existing road networks. We demonstrate the model with two illustrative case studies – one for CO 2 storage and one for CO 2 utilization – in which the model designs pipeline networks spanning hundreds of miles across the states, collecting CO 2 from multiple sources and delivering it to designated endpoints while minimizing levelized cost of delivery via diameter and compression optimization. The model offers a practical, scalable approach for alternative design option screening and early-stage CO 2 transportation planning.
Herein, this work explores the extent to which secondary gas-phase reactions (SGR) in pyrolysis can be used to modify coal tar chemistries from coals of different ranks in favor of improved anisotropy formation in their respective pitches. Pyrolysis was performed on four different coals of varying bituminous rank (Utah Sufco, Wyoming PRB Black Thunder, Illinois #6, and West Virginia Flying Eagle), with SGR temperatures ranging from 800 to 900° C and nominal SGR gas-phase residence times from 1 to 2.5 s. The oxygen content, aliphatic content, and molecular weight distributions of the coal tar samples were measured to indicate the changes with increasing levels of SGR, and microscopy was also used to measure changes in anisotropy formation in the resulting pitch samples. Generally, for all coals tested, increased levels of pyrolysis SGR led to decreased oxygen and aliphatic content, increased molecular weight sizes, and improved anisotropy formation. However, it was clear that the extent of these property changes depended on the chemistry and rank of the starting coal feedstock. Despite the relatively high rank of the Illinois #6 coal, its respective pitch samples performed poorly in improving anisotropy formation, due to its high sulfur content. The PRB, Sufco, and Flying Eagle coals performed better in their anisotropy formation than Illinois #6, depending on their respective coal ranks. Statistical analysis (analysis of variance, ANOVA) performed on the sample characterization data also suggests that SGR temperature is consistently the most dominant and significant effect on the resulting coal products.
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