A Global Review of Blue and Green Hydrogen Fuel Production Technologies, Trends and Future Outlook to 2050
Abstract
1. Introduction
Properties of Hydrogen
| Properties | Normal Hydrogen | Deuterium |
|---|---|---|
| Atomic number | 1 | 1 [34] |
| Atomic weight | 1.0080 | 2.0141 |
| Electron affinity | 0.7542 electron volts | 0.754 electron volts |
| Nuclear spin | ½ | 1 |
| Properties | Molecular Hydrogen | Deuterium |
|---|---|---|
| Bond distance | 0.7416 Angstrom | 0.7416 Angstrom |
| Dissociation energy (25 °C) | 104.19 kilocalories/mol | 105.97 kilocalories/mol |
| Ionisation potential | 15.427 electron volts | 15.457 electron volts |
| Density of solid | 0.08671 g/cm3 | 0.1967 g/cm3 |
| Melting point | −259.20 °C | −254.43 °C |
| Heat of fusion | 28 calories/mol | 47 calories/mol |
| Density of liquid | 0.07099 g/cm3 (−252.78 °C) | 0.1630 g/cm3 (−249.75 °C) |
| Boiling point | −252.77 °C [33] | −249.49 °C |
| Heat of vaporisation | 216 calories/mol | 293 calories/mol |
| Critical temperature | −240.0 °C | −243.8 °C |
| Critical pressure | 13.0 atmospheres | 16.4 atmospheres |
| Critical density | 0.0310 g/cm3 | 0.0668 g/cm3 |
2. Technologies of Blue and Green Hydrogen Fuel Production
2.1. Blue Hydrogen
2.1.1. Production of Blue Hydrogen by Steam Reforming of Methane and Light Hydrocarbons
2.1.2. Blue Hydrogen Production by Gasification of Coal and Biomass
2.2. Green Hydrogen
2.2.1. Green Hydrogen Production by Water Electrolysis
2.2.2. Thermochemical Conversion Method of Producing Green Hydrogen
2.2.3. Photochemical Conversion Method of Green Hydrogen Production
2.2.4. Photoelectrochemical Conversion
2.3. Comparison of Green and Blue Hydrogen Emissions
3. Global Production of Hydrogen
3.1. Global Production of Green and Blue Hydrogen
3.2. Blue and Green Hydrogen Production in Europe
4. Future Scope of Blue and Green Hydrogen Production and Demand
4.1. Future Scope for Blue and Green Hydrogen as a Fuel
4.2. Comparative Analysis for Both Blue and Green Hydrogen
4.3. Reduction in CO2 Emissions Using Hydrogen Energy
4.4. Long Short-Term Memory (LSTM) Prediction Model for Blue and Green Hydrogen Production Until 2050
5. Conclusions
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
Appendix A
| import numpy as np import pandas as pd import matplotlib.pyplot as plt from sklearn.preprocessing import MinMaxScaler from tensorflow.keras.models import Sequential from tensorflow.keras.layers import LSTM, Dense # Data years = np.arange(2010, 2023) blue_h2 = [1.2, 1.3, 1.4, 1.6, 1.7, 1.9, 2.0, 2.1, 2.3, 2.5, 2.6, 2.8, 3.0] green_h2 = [0.2, 0.25, 0.3, 0.35, 0.45, 0.5, 0.55, 0.6, 0.7, 0.8, 0.9, 1.1, 1.3] data = pd.DataFrame({“Blue”: blue_h2, “Green”: green_h2}) # Normalize scaler = MinMaxScaler() scaled = scaler.fit_transform(data) # Sequences seq_len = 3 X, y = [], [] for i in range(len(scaled) - seq_len): X.append(scaled[i:i+seq_len]) y.append(scaled[i+seq_len]) X, y = np.array(X), np.array(y) # Model model = Sequential([ LSTM(50, activation=‘relu’, input_shape=(seq_len, 2)), Dense(2) ]) model.compile(optimizer=‘adam’, loss=‘mse’) model.fit(X, y, epochs=300, verbose=0) # Forecast future_years = np.arange(2023, 2051) last_seq = scaled[-seq_len:] preds = [] for _ in future_years: pred = model.predict(last_seq[np.newaxis, :, :], verbose=0)[0] preds.append(pred) last_seq = np.vstack([last_seq [1:], pred]) forecast = scaler.inverse_transform(preds) # Combine forecast_df = pd.DataFrame(forecast, columns=[“Blue”, “Green”]) forecast_df[“Year”] = future_years all_df = pd.concat([data.assign(Year=years), forecast_df], ignore_index=True) # Plot plt.figure(figsize=(10,5)) plt.plot(all_df[“Year”], all_df[“Blue”], label=“Blue H2 (LSTM)”) plt.plot(all_df[“Year”], all_df[“Green”], label=“Green H2 (LSTM)”) plt.xlabel(“Year”); plt.ylabel(“Million Tonnes”); plt.title(“LSTM Forecast of Hydrogen”) plt.legend(); plt.grid(); plt.tight_layout() plt.show() # Save if needed all_df.to_excel(“Hydrogen_Production_LSTM_Forecast_2023_2050.xlsx”, index=False) |
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| Parameter | Blue Hydrogen | Green Hydrogen |
|---|---|---|
| Feedstock | Natural gas | Water and renewable electricity |
| Emission profile | Low (10–30 gCO2/MJ) | Very low (<5 gCO2/MJ) |
| CAPEX | USD 800–$1400/Kw | USD 1100–1800/kW |
| Levelised cost | USD 2.0–$3.5/kg H2 | USD 3.5–6.0/kg H2 |
| Maturity | High (commercial) | Emerging (pilot-scale to low-scale) |
| Key barrier | CH4 leakage, CCS cost | High electricity demand/cost |
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© 2025 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
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Ammar, M.; Oyewale, B.O.; Elseragy, A.; Albayati, I.M.; Aliyu, A.M. A Global Review of Blue and Green Hydrogen Fuel Production Technologies, Trends and Future Outlook to 2050. Fuels 2025, 6, 88. https://doi.org/10.3390/fuels6040088
Ammar M, Oyewale BO, Elseragy A, Albayati IM, Aliyu AM. A Global Review of Blue and Green Hydrogen Fuel Production Technologies, Trends and Future Outlook to 2050. Fuels. 2025; 6(4):88. https://doi.org/10.3390/fuels6040088
Chicago/Turabian StyleAmmar, Muhammad, Babatunde Oyeleke Oyewale, Ahmed Elseragy, Ibrahim M. Albayati, and Aliyu M. Aliyu. 2025. "A Global Review of Blue and Green Hydrogen Fuel Production Technologies, Trends and Future Outlook to 2050" Fuels 6, no. 4: 88. https://doi.org/10.3390/fuels6040088
APA StyleAmmar, M., Oyewale, B. O., Elseragy, A., Albayati, I. M., & Aliyu, A. M. (2025). A Global Review of Blue and Green Hydrogen Fuel Production Technologies, Trends and Future Outlook to 2050. Fuels, 6(4), 88. https://doi.org/10.3390/fuels6040088

