Source Rock Classification and the Basic Structure of Coal and Kerogen

In accordance with the confusion on classification of source rocks, the authors raised a source rock classification for its enriched and dispersed organic matter types based on both Alpern’s idea and maceral genesis/composition. The determined rock type is roughly similar to palynofacies of Combaz , whereas it is "rock maceral facies (for coal viz. coal facies)" in strictly speaking. Therefore, it is necessary to use the organic ingredients classification proposed by the authors so that it can be used for both maceral analysis and environment research . This source rock classification not only shows sedimentology and diagenetic changes but also acquires organic matter type even if hydrocarbon potential derived from maceral’s geochemical parameters. So, it is considered as genetic classification. The "rock maceral facies" may be transformed to sedimentary organic facies , which is used as quantitative evaluation means if research being perfect.Now, there are many models in terms of structure either for coal or for kerogen. In our opinion, whatever coal or kerogen ought be polymer, then we follow Combaz’s thought and study structure of amorphous kerogens which are accordance with genetic mechanism showing biochemical and geochemical process perfectly. Here, we use the time of flight secondary ion mass spectrometry (TOFSIMS) to expand Combaz’s models from three to five. They are also models for coal.

An integrated fuzzy production inventory model for manufacturer–retailer coordination under simple carbon tax system

This paper develops twin models towards integrated production inventory planning for manufacturer–retailer ecosystem in a sustainable supply chain setup.Decision-making models are developed in fuzzy environment and under purview of carbon taxation system.Novel conception of Fermatean fuzzy numbers is introduced for handling parameters imprecision.The first model addresses planning problem without considering green investments,whereas the second one additionally identifies optimal green investments for each player of ecosystem.Models are formulated as nonlinear optimization problems with objective of maximizing profit.Comparison of results from both models enables decision-makers to figure out the profitability of green investment option.Numerical instance with data from the existing literature is solved using Mathematica 12.1.Computational results for studied case report profitability of green investments for supply chain partners and significant reduction in carbon emissions as well.Variation analysis demonstrates stability of the proposed model.Developed models equip small-scale retailer-manufacture tie-ups prevalent in developing economies for discussed decisions.