Production of Benzene, Toluene, and the Xylenes from Natural Gas via Methanol

Techno-Economic Analysis of a Process to Convert Methane to Olefins, Featuring a Combined Reformer via the Methanol Intermediate Product

The substantial growth in shale-derived natural gas production in the US has caused significant changes in the chemical and petrochemical markets. Ethylene production of ethane and naphtha via steam cracking is one of the most energy- and emission-intensive activities in chemical manufacturing. High operating temperatures, high reaction endothermicity, and complex separation create high energy demands as well as considerable CO2 emissions. In this study, a demonstration of a transformational methane-to-ethylene process that offers lower emissions using energy optimization and a CO2 minimum-emission approach is presented. The comparisons of different reforming processes suggest that the dry reforming of methane has a negative carbon footprint at low syngas ratios of 1 and below, and that additional carbon emissions can be reduced using integrated heating and cooling utilities, resulting in a 99.24 percent decrease in CO2. A process design implemented to convert methane into value-added chemicals with minimum CO2 emissions is developed.

A framework to predict the price of energy for the end-users with applications to monetary and energy policies

Energy affects every single individual and entity in the world. Therefore, it is crucial to precisely quantify the “price of energy” and study how it evolves through time, through major political and social events, and through changes in energy and monetary policies. Here, we develop a predictive framework, an index to calculate the average price of energy in the United States. The complex energy landscape is thoroughly analysed to accurately determine the two key factors of this framework: the total demand of the energy products directed to the end-use sectors, and the corresponding price of each product. A rolling horizon predictive methodology is introduced to estimate future energy demands, with excellent predictive capability, shown over a period of 174 months. The effectiveness of the framework is demonstrated by addressing two policy questions of significant public interest.

Global energy transformation requires quantifying the "price of energy" and studying its evolution. Here the authors present a predictive framework that calculates the average US price of energy, estimating future energy demands for up to four years with excellent accuracy, designing and optimizing energy and monetary policies.