The demand for carbon capture is increasing over time due to rising CO${}_2$ levels in the atmosphere. Even though fossil emission could be decreased or even eliminated, there is a need to start removing CO${}_2$ from the atmosphere. The removed CO${}_2$ could be either stored permanently to a reservoir (CCS, Carbon Capture and Storage) or utilized as a raw material in a long-lasting product (CCU, Carbon Capture and Utilization). The capture of CO${}_2$ could be done by direct air capture, or capturing CO${}_2$ from biogenic sources. Amine absorption is the state-of-the-art method to capture CO${}_2$, but it has some drawbacks: toxicity, high heat demand, and sorbent sensitivity towards impurities such as sulfur compounds and degradation in cyclic operation. Another potential solvent for CO${}_2$ could be water, which is easily available and safe to use in many applications. The problem with water is the poorer solubility of CO${}_2$, compared with amines, which leads to larger required flow rates. This study analyzed the technical feasibility of water absorption in a counterflow bubble column reactor. A dynamic, one-dimensional multiphase model was developed. The gas phase was modeled with plug flow assumption, and the liquid phase was treated as axially dispersed plug flow. CO${}_2$ capture efficiency, produced CO${}_2$ mass flow rate, and the product gas CO${}_2$ content were estimated as a function of inlet gas and liquid flow rate. In addition, the energy consumption per produced CO${}_2$-tonne was calculated. The CO${}_2$ capture efficiency was improved by increasing the liquid flow rate, while the CO${}_2$ content in product gas was decreased. For some of the studied liquid flow rates, an optimum gas flow rate was found to minimize the specific energy consumption. Further research is required to study the integration and dynamical operation of the system in a realistic operation environment.

This study is a systematic analysis of selected research articles about power-to-X (P2X)-related processes. The relevance of this resides in the fact that most of the world’s energy is produced using fossil fuels, which has led to a huge amount of greenhouse gas emissions that are the source of global warming. One of the most supported actions against such a phenomenon is to employ renewable energy resources, some of which are intermittent, such as solar and wind. This brings the need for large-scale, longer-period energy storage solutions. In this sense, the P2X process chain could play this role: renewable energy can be converted into storable hydrogen, chemicals, and fuels via electrolysis and subsequent synthesis with CO₂. The main contribution of this study is to provide a systematic articulation of advanced data-driven methods and latest technologies such as the Internet of Things (IoT), big data analytics, and machine learning for the efficient operation of P2X-related processes. We summarize our findings into different working architectures and illustrate them with a numerical result that employs a machine learning model using historic data to define operational parameters for a given P2X process.

Hydrogen is a versatile feedstock for various chemical and industrial processes, as well as an energy carrier. Dedicated hydrogen infrastructure is envisioned to conceptualize in hydrogen valleys, which link together the suppliers and consumers of hydrogen, heat, oxygen, and electricity. One potential hydrogen valley is the Bay of Bothnia, located in the northern part of the Baltic Sea between Finland and Sweden. The region is characterized as having excellent wind power potential, a strong forest cluster with numerous pulp and paper mills, and significant iron ore and steel production. The study investigates the hydrogen-related opportunities in the region, focusing on infrastructural requirements, flexibility, and co-operation of different sectors. The study found that local wind power capacity is rapidly increasing and will eventually enable the decarbonization of the steel sector in the area, along with moderate Power-to-X implementation. In such case, the heat obtained as a by-product from the electrolysis of hydrogen would greatly exceed the combined district heat demand of the major cities in the area. To completely fulfil its district heat demand, the city of Oulu was simulated to require 0.5–1.2 GW of electrolyser capacity, supported by heat pumps and optionally with heat storages.