Global energy-related carbon dioxide (CO₂) emissions reached approximately 37.4 Gt in 2023, reflecting continued dependence on fossil fuels. In the Philippines, coal accounted for about 62% of total electricity generation in 2023, highlighting the need for renewable and lower-carbon fuel alternatives. At the same time, increasing urbanization has intensified municipal solid waste generation, which now exceeds 35,000 tons per day, with fruit and vegetable residues (FVR) comprising a substantial biodegradable fraction. This study investigated the effects of torrefaction temperature and residence time on the physicochemical properties, fuel quality, and structural transformation of FVR to assess its suitability as a torrefied solid fuel.

Torrefaction experiments were conducted using a full factorial 2² design under an inert nitrogen atmosphere at two temperatures (200°C and 300°C) and two residence times (30 and 90 min), with three replicates per condition. Prior to treatment, the feedstock was air-dried, oven-dried, and milled to particle sizes ranging from 0.25 to 2.00 mm. Product performance was evaluated through mass yield determination, proximate analysis, higher heating value (HHV), fuel ratio, visual colorimetric analysis, Fourier Transform Infrared (FTIR) spectroscopy, and Analysis of Variance (ANOVA).

ANOVA identified temperature as the dominant factor affecting torrefaction behavior and product quality. Samples treated at 200°C exhibited high mass yields of 94.92%–96.83%, indicating limited devolatilization, whereas torrefaction at 300°C reduced mass yield to 46.40%–52.74%. Despite lower product recovery, higher torrefaction severity improved fuel characteristics. HHV increased from 9060–9246 Btu/lb at 200°C and 30 min to 10,918–11,560 Btu/lb at 300°C and 90 min. Volatile matter decreased from 73.90%–76.50% to 39.70%–44.30%, while fixed carbon increased from 17.10%–20.40% to 41.60%–48.00%. Ash content increased from 5.70%–6.32% to 12.30%–14.20%, and fuel ratio rose from 0.2235–0.2760 to 0.9391–1.2091, indicating enhanced carbonization and improved solid fuel behavior. FTIR analysis further showed a reduction in hydroxyl and aliphatic C–H functional groups and a stronger aromatic C=C band near 1600 cm⁻¹, confirming the formation of a more aromatic and chemically stable carbonaceous structure. These changes were accompanied by progressive darkening from light brown feedstock to nearly black torrefied solids.

The results show that lower torrefaction severity favors mass retention, whereas higher severity improves fuel quality and structural stability, supporting the potential use of market waste-derived torrefied solids for renewable energy applications.

Despite Nigeria’s vast and diverse untapped potential in solar, wind, biomass, and small-scale hydropower, a significant and persistent gap remains between national policy ambition and the practical implementation of renewable energy projects. This study investigates the underlying structural reasons why existing sustainable energy strategies have failed to significantly reduce fossil-fuel dependency or resolve chronic electricity shortages, particularly within underserved semi-urban and rural communities where energy poverty remains a major barrier to development. Through a comprehensive thematic analysis of current regulatory frameworks, international development reports, and peer-reviewed academic literature, the research identifies critical bottlenecks in the energy transition process, with a specific focus on the deployment of solar mini-grids and decentralized energy systems as viable alternatives to the struggling national grid. The findings reveal that progress is hindered not by a lack of natural resources or high-level policy intent, but by fragmented institutional coordination, weak regulatory enforcement, and a lack of robust de-risking mechanisms necessary to attract essential private sector investment. The study highlights that the current reliance on thermal power plants fueled by gas and oil continues to cause significant environmental degradation and economic instability. To bridge this implementation gap, the paper proposes a multi-dimensional strategic framework centered on fostering inter-agency synergy, implementing specialized capacity-building programs for both policy-makers and technical personnel, and the stabilization of financial foundations for renewable infrastructure through targeted incentives. The study concludes that strengthening these institutional, financial, and technical pillars is the vital prerequisite for translating high-level policy commitments into measurable, sustainable development outcomes in addition to good and revised government policies to engage more stakeholders in the energy sector. Furthermore, the lessons derived from the Nigerian context offer a scalable roadmap for low-carbon growth and socioeconomic transformation that is highly relevant for other West African nations pursuing similar sustainable energy goals in the face of global climate challenges and the urgent need for a regional energy transition.

Direct air capture (DAC) is increasingly recognized as a critical component of net-zero emission strategies, as it enables the direct removal of CO₂ from ambient air. While carbon capture, utilization, and storage technologies are relatively mature for point sources, the ultra-low concentration of atmospheric CO₂ presents fundamental challenges for DAC, leading to high energy demand and elevated costs that currently constrain large-scale deployment. Recent advances in nanotechnology have enabled the development of nanostructured adsorbents with high surface areas, tunable pore architectures, and tailored surface chemistries capable of enhancing CO₂ capture under ultra-dilute conditions. In this study, a unified comparative evaluation framework is established to assess the performance of key classes of nanostructured adsorbents under DAC-relevant conditions. The analysis focuses on critical performance metrics, including CO₂ adsorption capacity, regeneration energy requirements, moisture tolerance, and cyclic stability. Representative material classes examined include MOFs, LDHs, porous carbons, graphene-based materials, and bio-derived nanostructures. Comparative assessment indicates that amine-functionalized LDH nanosheets exhibit rapid CO₂ uptake and stable performance over repeated adsorption–desorption cycles. At the same time, polyamidoamine-dendrimer-functionalized nanosilica demonstrates enhanced capture efficiency under both dry and humid conditions with relatively low-temperature regeneration. In parallel, charged-sorbent systems incorporating ions within activated carbon pores have emerged as a promising strategy, enabling fast CO₂ capture and electrically driven regeneration. Despite advances, substantial challenges remain. Reported techno-economic assessments frequently estimate capture costs in the approximate range of USD 300–1000 per ton of CO₂, depending on system configuration and scale, with associated energy penalties. Additional limitations include sensitivity to moisture, structural degradation during long-term cycling, and challenges related to scalable synthesis and deployment. No single adsorbent class currently satisfies all performance, cost, and scalability requirements. The comparative framework presented here highlights key trade-offs among material classes and underscores the need for integrated material- and system-level optimization to advance scalable, low-carbon DAC technologies.

Introduction

Coal mining continues to play a central role in South Africa’s energy system, contributing significantly to national electricity generation. However, coal-based energy extraction is also associated with substantial environmental pressures, particularly land degradation, ecosystem disruption, and water resource stress. Understanding the spatiotemporal impacts of mining-induced land-use and land-cover (LULC) change is therefore essential for informing sustainable energy planning and environmental governance. Advances in satellite remote sensing, cloud computing, and artificial intelligence provide new opportunities for continuous, large-scale monitoring of energy-related environmental impacts. This study investigates LULC dynamics associated with coal mining activities around the Tendele Coal Mine in Somkhele, KwaZulu-Natal, South Africa, within the broader context of the energy–environment nexus.

Methods

Multi-temporal Landsat satellite imagery spanning the period 2008–2023 was processed using the Google Earth Engine (GEE) cloud-based geospatial analysis platform. Five primary LULC classes—forests, grasslands, built-up areas, water bodies, and mines and quarries—were mapped using a supervised machine-learning approach based on the Random Forest (RF) algorithm. Classification accuracy was evaluated using overall accuracy and Kappa statistics to ensure robust model performance. Post-classification change detection techniques were applied to quantify spatial and temporal transitions among LULC classes. To support future-oriented energy and environmental planning, a Cellular Automata–Markov (CA-Markov) model was implemented to project LULC changes to 2028 based on historical transition probabilities.

Results

The RF-based classification achieved reliable performance, with overall accuracies ranging from 73.62% in 2008 to 93.33% in 2020 and Kappa coefficients indicating substantial to near-perfect agreement, peaking at 0.9123. Change detection analysis revealed that coal mining activities significantly influenced regional land dynamics. The mining footprint expanded markedly between 2008 and 2014, stabilized during the 2017–2020 period, and exhibited a slight decline by 2023, suggesting the influence of regulatory controls and environmental management measures. Forest cover demonstrated an overall net increase by 2023, while grasslands showed an initial expansion followed by subsequent decline. Built-up areas expanded rapidly during periods of intensified mining activity before contracting after 2017. CA-Markov projections indicate continued growth in forest and built-up areas by 2028, alongside a modest expansion of mining and quarrying areas to approximately 7.19 km².

Conclusions

The findings highlight the complex and evolving environmental impacts of coal-based energy extraction on land systems. By integrating remote sensing, cloud computing, machine learning, and spatial modelling, this study demonstrates the effectiveness of AI-enabled geospatial frameworks for monitoring energy-related environmental change. The results provide decision-support insights for policymakers, environmental managers, and energy-sector stakeholders seeking to balance energy security with sustainable land management. Such approaches are essential for supporting environmentally responsible energy transitions in mining-dependent regions.

Decarbonizing industry and accelerating the deployment of clean energy technologies are increasingly important priorities across Central Asia as countries pursue long-term strategies to reduce emissions and enhance energy security. Uzbekistan, with its high solar potential and rising energy demand, provides a relevant case for evaluating the role of low-carbon hydrogen in supporting this transition. In this study, green hydrogen is produced using an alkaline water electrolyser enhanced with metal–organic framework (MOF) materials (MOF–WAE) and powered entirely by solar photovoltaic (PV) electricity. The MOFs are integrated into the electrolyser electrode structure to improve electrochemical performance and hydrogen production efficiency. The system is modeled at an industrially relevant scale, consisting of a 40 MW alkaline electrolysis plant operating at 85% annual capacity factor, resulting in an annual hydrogen production of approximately 5,100 tonnes. The environmental performance of the proposed system is evaluated using a life-cycle assessment (LCA) implemented in SimaPro, covering the full hydrogen pathway from solar electricity generation to hydrogen utilization. Results show that the MOF–WAE configuration achieves a life-cycle global warming potential of approximately 1.97 kg CO₂ per kg of hydrogen produced. When compared with a conventional steam methane reforming (SMR) reference pathway, this corresponds to an annual reduction of about 13,340 tonnes of CO₂, representing an overall reduction of nearly 80% in global warming potential. The remaining impacts are largely driven by electricity-related processes, underlining the importance of clean and reliable renewable power supply for large-scale hydrogen deployment. The advantages of renewable hydrogen are also evident in transport applications. Fuel-cell vehicles powered by solar-based hydrogen can emit up to 89% less CO₂ per 100 km than diesel vehicles, and approximately 83% less CO₂ than vehicles using SMR-derived hydrogen. Overall, the findings indicate that solar-powered, MOF-enhanced alkaline electrolysis is technically feasible and capable of delivering substantial environmental benefits, making it a promising pathway for Uzbekistan and other Central Asian countries pursuing resilient, low-carbon energy systems.

Introduction

The United Nations has emphasised the urgent need to transition towards a more sustainable and resource-efficient global economy, with improved waste management identified as a key enabler. One major challenge is the disposal and valorisation of end-of-life tyres. The global tyre industry produces approximately 3.66 billion tyres annually, creating significant environmental and energy concerns. Conventional disposal routes, such as landfilling and incineration, are associated with toxic emissions, environmental risks, and poor energy recovery. In this context, gasification offers a promising route for converting waste into valuable energy carriers.

This paper investigates microwave-induced plasma gasification as a sustainable alternative for tyre waste treatment. Experimental studies are conducted using a novel microwave plasma furnace equipped with a mode converter that maintains the plasma core away from reactor walls, improving thermal efficiency and eliminating the need for ceramic linings. Tyre crumb is used as a representative feedstock. Although tyres are generally safe to handle, their combustion can release 10-100 times more polycyclic aromatic hydrocarbons than coal, whereas gasification enables cleaner conversion into synthesis gas.

Microwave plasma gasification achieves efficient destruction of complex organics, producing inert ash with negligible fixed carbon and significantly reduced VOC emissions. Independent control of temperature and oxidant supply enables optimisation of syngas quality and process economics. Ongoing research at Lancaster University focuses on improving applicator efficiency and advancing scalable, energy-efficient waste-to-energy technologies.

Methods

Previous gasification research at Lancaster University employed a 2.45 GHz, 6 kW microwave-induced plasma torch (Sairem SAS, France). Atmospheric-pressure microwave plasmas are most readily sustained within electrically insulating, microwave-transparent ceramic vessels, which reduce electron losses and enable operation at lower power. In this system, the plasma torch comprised a fused silica tube (25.4 mm internal diameter) passing through a WR340 rectangular waveguide operating in the TE₁₀ mode. Microwave leakage was suppressed using concentric metallic chokes, while plasma ignition was achieved via a transient tungsten arc. Although effective, the fused silica tube required intensive cooling to prevent thermal damage, significantly reducing system efficiency.

To address these limitations, a new applicator was developed to increase plasma volume, enable scale-up, and eliminate the need for a cooled ceramic tube. The design operates in the TE₀₁ mode of a cylindrical waveguide, where the azimuthal electric field and low wall field strength minimise electron and heat losses, improving thermal efficiency. For 2.45 GHz operation, a cylindrical diameter of 182 mm was selected and a dedicated mode converter fabricated. While stable operation requires specific gas flow and power thresholds, the design is readily scalable to 915 MHz, where magnetron efficiencies exceed 90%, enabling industrial-scale processing. Independent control of gas flow and power can be achieved through hot-gas recirculation, further optimising gasification performance.

Results

The current test bed comprises three main components: a microwave plasma chamber, a gasification furnace, and a gas recirculation system. The gasification stage of the process is modelled using ASPEN Plus, enabling heat and enthalpy balancing under assumed constant pressure and enthalpy conditions. Although the overall system operates as a single reactor experimentally, a hybrid modelling approach is adopted, dividing the gasification process into three stages: drying at 105 °C, pyrolysis at 500 °C (modelled using an RYield block), and gasification (modelled using an RGibbs block). Heat for drying and pyrolysis is supplied by the plasma exhaust stream, while the final gasifier temperature depends on reaction heat and available exhaust energy. Two operating cases are examined: without syngas recirculation and with recirculation. In the non-recirculation case, air is heated by microwave input in the plasma chamber and fully directed to the gasifier. In the recirculation case, the plasma is modelled using three temperature zones to reflect realistic plasma–gas interactions, followed by heat exchange and partial syngas extraction. ASPEN Plus simulations indicate that an optimal airflow of 16.5 kmol h⁻¹ eliminates fixed carbon while minimising undesirable by-products. Importantly, incorporating up to 80% gas recirculation significantly reduces exhaust temperatures and microwave power demand by a factor of approximately 2.8 without adversely affecting syngas composition or calorific value, thereby improving overall process efficiency and economics.

Conclusions

A stable atmospheric-pressure microwave-induced plasma was successfully generated within a steel vessel, demonstrating robust and controllable operation. The high-temperature plasma exhaust exhibited the thermal intensity and chemical reactivity required to effectively gasify a range of waste feedstocks, including tyre crumb. Key operational parameters governing efficient plasma formation and stability were identified, providing essential baseline data for the evaluation of tyre-derived materials as viable feedstocks in plasma-assisted gasification processes.

These results highlight the strong potential of microwave-induced plasma technology as a cleaner and more efficient alternative to conventional thermal treatment methods, offering enhanced destruction of organic compounds with the prospect of reduced harmful emissions. Importantly, stable operation at atmospheric pressure significantly improves the practicality of this approach, supporting the development of compact and modular waste-to-energy systems. Such systems could be deployed closer to waste generation sites, thereby reducing transportation requirements, lowering environmental impact, and advancing sustainable waste management strategies.

The accelerated deployment of wind and solar energy is a cornerstone of global decarbonization strategies, yet it has intensified challenges related to the transparency, credibility, and governance of environmental and social impact assessments, particularly in emerging and Global South contexts. Life Cycle Assessment (LCA) is widely established as a robust methodological framework for evaluating environmental impacts across the full life cycle of energy systems; however, practical applications often rely on fragmented datasets, static evaluations, and limited verification mechanisms, which can undermine trust among regulators, communities, and project developers. These limitations are especially critical in renewable energy projects, where cumulative effects, social impacts, and governance considerations are central to enabling a just energy transition. In this context, this study proposes a blockchain-supported LCA framework that enhances data integrity, traceability, and accountability while preserving the scientific foundations of life cycle thinking.

Methodologically, the framework positions LCA as the analytical backbone, aligned with ISO-compliant life cycle principles, and integrates blockchain strictly as a technological enabler for data governance rather than as an end in itself. The approach combines a structured environmental LCA with a selected set of social indicators inspired by Social Life Cycle Assessment (S-LCA) practice, focusing on dimensions particularly relevant to renewable energy projects in emerging contexts, such as community engagement, labor conditions, land-use interactions, grievance mechanisms, and compliance with social commitments across project phases. These indicators are operationalized through a digital architecture capable of capturing, structuring, and processing heterogeneous data streams derived from monitoring systems, project documentation, and stakeholder inputs. A permissioned blockchain layer records cryptographic hashes and metadata associated with datasets, indicators, and assessment outputs, enabling immutability, version control, and verifiability while maintaining data privacy and operational flexibility. Within this setup, authorized stakeholders—such as project developers, regulators, and academic partners—can write and validate records, while broader audiences can access verified information through read-only interfaces, supporting transparency and accountability. The framework is operationalized through a functional digital platform developed under the IMPACT Energy.CO initiative, designed to interlink LCA workflows, data management modules, and blockchain services in a coherent and scalable manner.

The results demonstrate both conceptual and applied contributions. Conceptually, the framework clarifies how blockchain can be systematically embedded within LCA workflows to address long-standing issues of transparency, accountability, and trust without compromising methodological rigor or comparability. Functionally, the platform implementation shows that life cycle indicators, monitoring records, and governance-related events can be registered in a tamper-resistant manner, enabling independent verification of assessment outputs across project phases. The integration of blockchain enhances data integrity and traceability, while the LCA engine ensures analytical consistency and supports evidence-based decision-making, regulatory review, and multi-stakeholder oversight in renewable energy projects.

Overall, this work advances a novel, blockchain-supported LCA framework that strengthens the environmental and social governance of renewable energy systems and contributes to the operationalization of a just energy transition. While the approach is broadly applicable to emerging and Global South contexts, its practical feasibility is illustrated through a case study in Colombia, where wind and solar projects face complex environmental, social, and institutional challenges. The proposed framework offers a scalable and replicable pathway for bridging science, policy, and practice by embedding trustworthy, life-cycle-based evidence into renewable energy planning and governance worldwide.

This research was made possible through the support of the Agencia Nacional de Hidrocarburos (ANH), Vicepresidencia Técnica, within the framework of Contracts 478 and 515 of 2025 executed between the ANH and the Universidad del Magdalena. The authors gratefully acknowledge this institutional cooperation, which enabled the development of the IMPACT Energy.CO platform and the advancement of applied research aimed at improving the assessment, transparency, and governance of environmental and social impacts in renewable energy projects in Colombia.

The rapid expansion of solar energy systems is a cornerstone of the global energy transition; however, their environmental assessment still relies predominantly on static Life Cycle Assessment (LCA) approaches based on aggregated, time-invariant datasets, which limit the ability to capture operational variability, context-specific dynamics, and data quality challenges—particularly in emerging economies where public institutions, private developers, and local communities interact. To address these limitations, this study proposes an Internet of Things (IoT)-enhanced dynamic Life Cycle Assessment (dLCA) framework aimed at enabling continuous environmental impact monitoring of solar energy systems in support of a sustainable and just energy transition. The proposed approach integrates real-time data streams from IoT devices into a dLCA methodological structure, allowing life cycle inventory parameters to be updated dynamically throughout key project phases. The framework is implemented through an edge/cloud IoT architecture, in which edge devices capture and pre-process environmental and operational data, while cloud-based services aggregate, harmonize, and feed these data into the dLCA workflow. Particular emphasis is placed on data provenance, temporal consistency, interoperability, and transparent documentation of assumptions. The framework has been operationalized within a functional digital platform developed under the IMPACT Energy.CO project and applied to a Latin American—specifically Colombian—solar energy case study characterized by regulatory oversight, public-sector involvement, and community engagement. The results demonstrate that integrating IoT-enabled data collection with dLCA significantly enhances the capacity to track environmental performance over time and across system boundaries, improving traceability, data quality control, and transparency in environmental assessments. Although the results are qualitative and functional rather than quantitative, they show how the proposed framework overcomes key limitations of conventional static LCA, particularly regarding temporal resolution and stakeholder trust. Overall, this work advances LCA practice from retrospective analysis toward dynamic, platform-based environmental monitoring, providing a transferable methodological foundation for evidence-based decision-making in solar energy projects and establishing the basis for future quantitative assessments and full-scale journal publication on the transition from static to dynamic LCA. This research was funded by the Agencia Nacional de Hidrocarburos, through its Vicepresidencia Técnica, under Contract No. 515 of 2025 executed with the Universidad del Magdalena.

Decarbonising the automotive sector requires powertrains capable of delivering cleaner and more efficient energy conversion processes. Low‑carbon gaseous fuels such as natural gas and hydrogen represent promising alternatives for spark‑ignition engines, as they facilitate more sustainable combustion while maintaining operational feasibility. Hydrogen, in particular, enables CO₂‑free combustion and can achieve net‑zero lifecycle emissions when produced from renewable sources. However, its inherently high reactivity and flame speed pose operational challenges, including an increased risk of backfiring, difficulties in controlling the combustion rate, and a higher propensity for engine knock, especially in stoichiometric mixtures. Blending hydrogen with natural gas can mitigate these limitations by reducing mixture reactivity and improving combustion stability, while preserving the low‑carbon characteristics of both fuels.

Despite their potential to lower CO₂ emissions, the combustion of natural‑gas–hydrogen mixtures may still generate pollutants such as CO, NOₓ and unburned hydrocarbons. Controlling these emissions requires a detailed understanding of how the combustion process governs pollutant formation, especially under varying fuel compositions and operating conditions. Furthermore, cleaner in‑cylinder conversion processes can simplify the design and improve the performance of after‑treatment systems, which must be tailored to the specific characteristics of hydrogen‑assisted combustion. However, the literature still lacks comprehensive studies describing the interplay between combustion dynamics and pollutant formation when using hydrogen–natural‑gas blends.

The main objective of this work is to characterise the combustion process in relation to the formation of CO and NOₓ emissions in a spark‑ignition engine operating with various hydrogen–natural‑gas mixtures. Experimental tests were carried out at three engine speeds (1000, 1750 and 2000 rpm), varying both the fuel–air equivalence ratio and the hydrogen fraction in the mixture. The engine was evaluated under three fuelling strategies: pure natural gas (ϕ = 0.7–1.0), pure hydrogen (ϕ = 0.3–0.7) and binary mixtures of natural gas and hydrogen. The experimental data were processed using a two‑zone thermodynamic diagnostic model and a kinetic diagnostic model, enabling a detailed analysis of both the combustion process and the formation of pollutant emissions.

The results show that, although adding hydrogen reduces overall carbon emissions, CO formation persists under stoichiometric conditions when the engine operates on natural gas. Increasing the hydrogen fraction leads to higher NO formation, primarily due to the faster energy release associated with hydrogen’s high laminar flame speed. Conversely, when the engine runs on 100% hydrogen, the use of lean mixtures with equivalence ratios below 0.5 almost completely suppresses NO emissions while maintaining stable engine operation. These findings provide valuable insight into the relationship between combustion evolution and pollutant formation, supporting the development of cleaner, more efficient energy‑conversion systems based on hydrogen‑enriched gaseous fuels.

The construction sector all over the world is one of the great consumers of land and natural resources, which ultimately contribute to pollution globally. The conventional and traditional construction materials like fire clay bricks (7000 BC) and Ordinary Portland cement concrete are energy-intensive and environmentally detrimental. Nowadays, bio-based or agro-based construction materials have been introduced as comparable alternatives due to their renewable properties, lower embodied energy, and improved thermal efficiency. Hempcrete is basically a bio-composite material consisting of hemp shiv, mineral binders, and water; it is a sustainable and thermally efficient building construction material that is used in farm structures, poultry sheds, farm workshops and other agriculture-based buildings where low temperatures are required in summer. The main objective and theme of the proposed research is the development and evaluation of a thermally efficient sustainable hempcrete structure utilizing hemp, which is a wild herb or weed naturally occurring in Pakistan, especially in mid-Punjab areas, where there is moderate temperature and locally available agro-residues like rice crop residue, wheat residue, sugarcane residue, rice husk and waste fodder. The research will focus on optimizing material composition, evaluating thermal, physical, and mechanical properties, and assessing the environmental benefits of hempcrete for its practical application in Pakistan’s climatic conditions. Experimental and practical investigations of the research will be carried out to determine thermal conductivity, density, compressive strength, water absorption, and hygrothermal performance. The results are expected to demonstrate that hempcrete and agro-residues would offer exceptional thermal insulation and enhanced sustainability as compared to conventional masonry materials like clay bricks, etc. This research aims to contribute to sustainable construction practices and promote the utilization of agricultural waste in eco-friendly building systems to utilize the waste residues and hemp, resulting in decreased carbon footprints in the environment and reducing the contribution of the agriculture sector to indirect smog formation caused by stubble burning of different crop residues.