This study investigates the adsorption performance of biochar synthesized under varying pyrolysis and CO₂ activation conditions for the simultaneous removal of nitrogen monoxide (NO) and sulfur dioxide (SO₂), with an additional focus on its environmental impacts via life cycle assessment (LCA). Biochar was produced from Hinoki cypress using a two-stage process comprising initial pyrolysis followed by CO₂ activation, and its physicochemical properties were evaluated through pore structure analysis. Adsorption experiments were conducted under both single- and combined-gas conditions to assess the synergistic or competitive behaviors of NO and SO₂ adsorption. The results indicated that activation conditions significantly influenced the surface area and pore volume of biochar, leading to enhanced gas adsorption capacities. A trade-off between biochar yield and pollutant removal efficiency was observed, suggesting an optimal activation temperature balancing these two factors. Furthermore, the LCA approach, employing IPCC 2021 GWP 100 metrics, quantified the environmental impacts of biochar production under different thermal conditions. The findings revealed that although higher activation temperatures improved adsorption efficiency, they also resulted in increased energy consumption and associated greenhouse gas emissions. These outcomes demonstrate the necessity of optimizing activation parameters not only for functional performance but also for environmental sustainability. This work provides insight into designing efficient biochar-based gas treatment systems and supports their potential application as eco-friendly alternatives in industrial emission control strategies.

A flue gas condenser (FGC) system recovers heat from exhaust flue gases in energy production and chemical plants, reducing air pollution due to dust, SOx, and HCl. An FGC system is divided into indirect contact condenser (ICC) and direct contact condenser (DCC) types. In an ICC, the exhaust gases do not mix with the working fluid, and a water film is formed during flue gas condensation for partial SOx removal. In a DCC, direct mixing of the exhaust flue gas with the cooling fluid (mainly water) occurs, with simultaneous absorption of SOx. In this study, we investigated the SO₂ removal efficiency and heat recovery of an ICC, a DCC, and a DCC–ICC hybrid system, and compared the results of the hybrid system with those obtained for a single DCC type at the same liquid-to-gas (L/G) ratio. The SO₂ removal characteristics of the hybrid system were examined based on the L/G ratio and absorbent-to-SO₂ molar ratio. In the reference ICC-type FGC system, the exit temperature of the mixed gas was 28 °C, with the condensed water ratio and heat recovery efficiency being 80.9% and 93.4%, respectively. At an L/G ratio of 1.5–3.5, the SO₂ removal efficiency of a single DCC was 31.5–65.9%, whereas that of the hybrid FGC system (with packing material) increased from 47.1% to 72.3%, which further increased to ~90% upon the addition of NaOH at a molar ratio of 0.7 and an L/G ratio of 1.5.

Biochar has a carbon-based porous structure that is advantageous for adsorbing air pollutants. The pore structure of biochar ranges from several tens to hundreds of m²/g depending on the production temperature. We compared the pore characteristics of biochar with its NOx and SOx adsorption performances to evaluate its adsorbing potential. Biochar was produced from cypress biomass via slow pyrolysis in a fixed-bed reactor and CO2 partial gasification. Slow pyrolysis experiments at 500–700°C were conducted to produce biochar, followed by yield, proximate, elemental, and surface area analyses. CO2 partial gasification activated the biochar produced by slow pyrolysis at the same temperature, and similar analyses were performed. NO and SO2 adsorption experiments were conducted separately and together for biochar produced under each condition. Biochar produced at 600°C showed the highest specific surface area. CO2 partial gasification increased the surface area at each temperature, reaching 680.3 m²/g at 700°C. In single adsorption experiments, N2 carbonized biochar showed NO and SO2 adsorption efficiencies of 84–90% and 88.2–91.4%, respectively, with similar trends in simultaneous adsorption experiments. CO2 activated biochar exhibited higher adsorption efficiencies due to its increased surface area, with NO and SO2 adsorption at 89.8–93.9% and 92–98.9%, respectively. Biochar activated at 700°C simultaneously adsorbed approximately 99% NO and SO2. The NO adsorption efficiency increased with increasing surface area of the small pores, whereas the SO2 adsorption efficiency improved with the development of both small and large pores.

Aluminium cold rolling is an energy-intensive process that has a substantial impact on CO2 emissions and production cost, yet plant-level optimization remains challenging due to strong process nonlinearities and various operational constraints. This study develops a physics-consistent hybrid model that combines a Stone–Hitchcock–Ludwik analytical rolling-energy formulation with a residual deep neural network to predict the daily electricity consumption of three single-stand cold rolling mills. Using plant raw data, the hybrid model achieves lower prediction errors than conventional data driven model and yields line-specific physical parameters that agree well with the observed behaviour of each mill. On this basis, an NSGA-II-based tri-objective optimization is carried out to minimise daily energy use, CO2 emissions, and specific production cost (SPC) by adjusting pass-wise reduction and tension schedules and line-wise production allocation. Case studies on a representative operating day and additional plant data show that the optimised operating strategy shifts production load from less efficient to more efficient lines and smooths pass-wise operating conditions, thereby consistently reducing daily energy consumption and unit cost while moderately decreasing CO2 emissions without any hardware modifications. The proposed hybrid prediction–optimization framework thus provides a practical decision-support tool for integrated energy–environment–economic optimization in multi-line aluminium cold rolling operations.