Journal of Energy Research and Reviews

Asymmetric Effects of Energy Efficiency on Manufacturing Output in Nigeria: A Nonlinear ARDL Approach

2026-05-27T09:47:21+00:00

The relationship between energy efficiency and manufacturing productivity is often assumed to be linear. Yet theoretical and empirical evidence suggest significant asymmetries: firms may respond differently to efficiency gains than to efficiency losses. This study investigates the asymmetric impact of energy efficiency on manufacturing output in Nigeria using annual time-series data from 1981 to 2023. Estimating a Nonlinear Autoregressive Distributed Lag (NARDL) model, we decompose energy efficiency into positive (EE⁺) and negative (EE⁻) partial sums. The bounds test confirms cointegration (F = 9.036 > upper bound at 1%). Results reveal a striking asymmetry: in the long run, a 1% increase in energy efficiency raises output by 0.93%, while a 1% decrease reduces output by 2.24% — a loss aversion ratio of approximately 2.4:1. While short-run effects appear symmetric (F = 1.52, p = 0.229), long-run asymmetry is statistically significant (F = 11.61, p = 0.002). Capital positively affects output (elasticity 0.98), while labour exhibits a negative coefficient (-0.96), reflecting structural inefficiencies. The error correction term (-0.194, p < 0.01) indicates a 19% annual convergence to equilibrium. Diagnostic tests confirm the absence of serial correlation, heteroscedasticity, or specification error, and the CUSUM test indicates structural stability. These findings suggest that preventing declines in energy efficiency is more critical than promoting improvements — a fundamental departure from conventional policy wisdom.

Correlation Analysis between Meteorological Parameters and Solar Radiation for Utility-scale Photovoltaic Farm Development in Imo State, South-Eastern Nigeria

2026-05-27T12:54:49+00:00

Solar photovoltaic (PV) technology has become a technically feasible and economically viable option for addressing electricity supply deficits in Imo State and Nigeria. This research paper presents a correlation analysis between some major meteorological variables, including maximum temperature, minimum temperature, rainfall rate (the intensity of rainfall at a given time measured in mm/hr), relative humidity, rainfall amount, and sunshine duration in Imo State, South-Eastern Nigeria, over a period of six years (2015-2020). The study describes the solar energy potential and evaluates the technical potential to develop utility-scale photovoltaic (PV) solar farms. Data were sourced from the Nigerian Meteorological Agency (NiMet) and Tropospheric Data Acquisition Network (TRODAN). Statistical findings from one-way ANOVA, Tukey HSD pairwise comparisons, linear regression trend analysis, and Pearson correlation are employed in this analysis. Findings showed that the sunshine hours registered a mean of 8.9hours/day, and were strongly and positively correlated with maximum temperature (r = +0.6912), strongly negatively correlated with relative humidity (r = -0.9372) and rainfall amount (r = -0.6923). A capacity factor of 17.58% during the dry season, 16.47% during the early period of the rainy season, 15.42% during the peak rainfall and 14.92% during the rainfall retreat resulted in an annual average capacity factor of 16.1%. This shows that Imo State has a very good economic potential to develop utility-scale solar Photovoltaic projects. The peak generation potential expected is about 68.02 MW during the dry season (November-March) with a capacity factor of 17.58%, and the lowest capacity factor of 14.92% is observed during the late rainfall/transition period, which indicates a manageable seasonal variability of about 7.92%. Although the results demonstrate strong solar potential in Imo State for utility-scale PV development, the study highlights the need for further investigation using long-term multi-decadal meteorological datasets to improve the reliability of solar resource estimation, reduce uncertainty in interannual climate variability and enhance the accuracy of long-term PV performance prediction. The study is significant as it provides a local empirical basis for assessing solar potential in Imo State, supports the planning and design of utility-scale PV systems, improves energy forecasting, and helps fill the gap in state-level solar resource studies in South-Eastern Nigeria.

Energy Optimization and Heat Integration in Amine-based CO₂ Capture from Natural Gas: An Aspen HYSYS Simulation Study

2026-05-27T13:04:03+00:00

The high energy demand associated with solvent regeneration remains a major limitation in amine-based carbon dioxide (CO₂) capture from natural gas, significantly affecting process efficiency and operational cost. Despite the widespread use of chemical absorption technologies, limited attention has been given to integrated energy optimization and heat recovery under region-specific conditions. This study addresses this gap by investigating energy optimization and heat integration strategies using Aspen HYSYS simulation, based on Niger Delta gas compositions. A steady-state absorber–stripper model was developed using the Electrolyte Non-Random Two-Liquid (e-NRTL) thermodynamic framework to simulate CO₂ absorption with Monoethanolamine (MEA), Diethanolamine (DEA), and Methyldiethanolamine (MDEA). Key energy indicators, including reboiler duty, condenser load, heat exchanger efficiency, and specific energy consumption, were evaluated under varying operating conditions. Heat integration strategies, particularly lean–rich heat exchange, were analyzed to minimize thermal energy requirements. Results show that regeneration energy follows the trend MEA > DEA > MDEA, with MEA exhibiting the highest energy demand. Optimized heat integration reduced overall energy consumption by 25–35%, with the greatest improvements observed in MDEA systems. Sensitivity analysis identified absorber temperature and solvent circulation rate as critical factors influencing energy demand, while efficient heat exchange enhanced thermal performance. The findings highlight the importance of balancing CO₂ removal efficiency and energy consumption. Overall, optimized MDEA systems with effective heat recovery offer a promising solution for energy-efficient and sustainable natural gas processing.