Combustion Of Fossil Fuels Research Articles

Protein biochemistry and engineering drive the development of a carbonic anhydrase-based carbon dioxide sequestration strategy.

The sequestration of carbon dioxide using carbonic anhydrase (CA) is one of the most effective methods for mitigating global warming. The burning of fossil fuels releases large quantities of flue gas; because of its high temperature and of the alkaline conditions required for CaCO3 precipitation in the mineralization process, thermo-alkali-stable CAs are needed. In this context, Manyumwa etal. conducted a biochemical characterization of three CAs derived from thermophilic bacteria. They then employed a rational design approach to enhance the specific activity and stability of the enzyme from the hydrothermal vent species Persephonella sp. KM09-Lau-8.

CO2 Capture: A Comprehensive Review and Bibliometric Analysis of Scalable Materials and Sustainable Solutions

The greenhouse effect and global warming, driven by the accumulation of pollutants, such as sulfur oxides (SOx), nitrogen oxides (NOx), and CO2, are primarily caused by the combustion of fossil fuels and volcanic eruptions. These phenomena represent an international crisis that negatively impacts human health and the environment. Several studies have reported novel carbon capture, utilization, and storage (CCUS) technologies, promising solutions. Notable methods include chemical absorption using solvents, and the development of functionalized porous materials, such as MCM-41, impregnated with amines like polyethyleneimine. These technologies have demonstrated high capture capacity and thermal stability; however, they face challenges related to recyclability and high operating costs. In parallel, biodegradable polymers and hydrogels present sustainable alternatives with a lower environmental impact, although their industrial scalability remains limited. This review comprehensively analyzes CO2 capture methods, focusing on silica-based porous supports, polymers, hydrogels, and emerging techniques, like CCUS and MOFs, while including traditional methods and a bibliometric analysis to update the field’s scientific dynamics. With increasing investigations focused on developing new CCUS technologies, this study highlights a growing interest in eco-friendly alternatives. A bibliometric analysis of 903 articles published between 2010 and 2024 provides an overview of current research on environmentally friendly carbon capture technologies. Countries such as the United States, the United Kingdom, and India are leading research efforts in this field, emphasizing the importance of scientific collaboration. Despite these advancements, implementing these technologies in industrial sectors with high greenhouse gas emissions remains scarce. This underscores the need for public policies and financing to promote their development and application in these sectors. Future research should prioritize materials with high capture capacity, efficient transformation, and valorization of CO2 while promoting circular economy approaches and decarbonizing challenging sectors, such as energy and transportation. Integrating environmentally friendly materials, energy optimization, and sustainable strategies is essential to position these technologies as key tools in the fight against climate change.

Atmospheric-level carbon dioxide gas sensing using low-loss mid-IR silicon waveguides.

Interest in carbon dioxide (CO2) sensors is growing rapidly due to the increasing awareness of the link between air quality and health. Indoor, high CO2 levels signal poor ventilation, and outdoor the burning of fossil fuels and its associated pollution. CO2 gas sensors based on integrated optical waveguides are a promising solution due to their excellent gas sensing selectivity, compact size, and potential for mass manufacturing large volumes at low cost. However, previous demonstrations have not shown adequate performance for atmospheric-level sensing on a scalable platform. Here, we report the clearly resolved detection of 500 ppm CO2 gas at 1 s integration time and an extrapolated 1σ detection limit of 73 ppm at 61 s integration time using an integrated suspended silicon waveguide at a wavelength of 4.2 µm. Our waveguide design enables suspended strip waveguides with bottom anchors while maintaining a constant waveguide core cross-sectional geometry. This unique design results in a low propagation loss of 2.20 dB/cm. The waveguides were implemented in a 150 mm silicon on insulator (SOI) platform using standard optical lithography, providing a clear path to low-cost mass manufacturing. The low CO2 detection limit of our proposed waveguide, combined with its compatibility for high-volume production, creates substantial opportunities for waveguide sensing technology in CO2 sensing applications such as fossil fuel combustion monitoring and indoor air quality monitoring for ventilation and air conditioning systems.

Evaluation of bromelia karatas as a bioindicator of lead contamination

Abstract: metals toxic contamination is a problem that has increased mainly due to anthropogenic activities. Lead (Pb) is a hightly toxic metal present in the environment due to industrial activities, such as mining, smelting, manufacturing, and burning of fossil fuels. This work studied Bromelia karatas as a bioindicator of the quality of the environment in the presence of lead. Forty 200-day-old plants (Bromelia karatas) were used, of which 30 were transplanted in a substrate (Peat moss) contaminated with Pb, using Pb(NO3)2 as a contaminating agent, at different concentrations, T1= 1000, T2=2000 and T3=3000 mg/kg (milligram of Pb/Kilogram of substrate), and 10 were used as control (Tc). At the end of the experiment, the presence of Pb was analyzed and found in the plant tissues (leaves and roots), using the ICP-OES equipment. This research revealed the potential of Bromelia karatas as a bioindicator of Pb contamination in soil, causing visible symptoms of foliar damage on its leaves with high doses of the contaminant. The low cost, easy reproduction and portability of bromeliad compared to other bioindicators make it a better option to be used as a bioindicator and/or biomonitor.

Proton Exchange Membrane Fuel Cell Catalyst Layer Degradation Mechanisms: A Succinct Review

Increasing demand for clean energy power generation is a direct result of the rapid depletion of fossil fuel reserves, the volatility of fossil commodity prices, and the environmental damage caused by burning fossil fuels. Fuel cell vehicles, portable power supplies, stationary power stations, and submarines are just some of the applications where proton exchange membrane (PEM) fuel cells are a prominent technology for power generation. PEM fuel cells have several advantages over conventional power sources, including a higher power density, lower emissions, a lower operating temperature, higher efficiency, noiseless operation, ease of design, and operation. The catalyst layer of the membrane electrode assembly is discussed in this paper as a vital part of the proton exchange membrane fuel cell. Along with that, the platinum (Pt)-based catalyst, carbon support, and nafion ionomer found in the catalyst layer often degrade. Catalyst growth, agglomeration, Pt loss, migration, active site contamination, and other microscopic processes are all considered in the degradation process. Employing experimental and numerical research with a focus on enhancing the material properties was suggested as a possible solution to understanding the problem of catalyst layer degradation. Ultimately, this review aims to prevent catalyst layer degradation and lower the high costs associated with replacing catalysts in proton exchange membrane fuel cells through the recommendations provided in this study.

A Comprehensive Review on Advancements in Modification Strategies of Polymer Blends for Enhanced Carbon Dioxide Capture and Reuse

ABSTRACTCarbon dioxide (CO2) is emitted into the atmosphere through the combustion of fossil fuels and various industrial processes, and it is presently regarded as a significant factor in global warming. Carbon capture and storage (CCS) stands out as a prominent strategy put forward to address CO2 emissions. This study aims to provide a comprehensive overview of recent developments in CO2‐based polymers, focusing on sustainable biopolymers, including copolymers and polymer blends. A thorough analysis of CO2 co‐polymers as components in polymer blends is conducted, focusing on the capture of CO2. In recent years, carbon capture technology has attracted considerable focus as a strategy to mitigate the negative effects of increasing CO2 levels in the environment. The process of developing polymer blends entails merging two or more polymeric substances to harness their distinct advantages. This investigation assessed polyethylene glycol (PEG), polyether sulfone (PES), polyurethane (PU), and polyimide (PI) based on their chemical properties as promising polymer blends for the efficient separation of CO2. Advances in polymer blend modifications for improved CO2 capture and reuse are highlighted in this review, with a focus on strategies such as chemical functionalization (e.g., amine or hydroxyl groups), the utilization of porous materials, and the integration of hybrid systems, delving into CO2 adsorption efficiency, selectivity, and reusability. The paper also examines novel materials' potential for CO2‐to‐product conversion, such as bio‐based polymers and nano‐engineered blends. The main obstacles and potential paths for applications that are sustainable and scalable are described.

What has the petroleum industry ever done for us? On the positive legacies from the petroleum industry and the role of carbonate and evaporite studies in the energy transition

The burning of fossil fuels over the last 150 years has been the main driver of rising atmospheric CO 2 levels and global warming. The petroleum industry as an entity is often blamed for a significant share of these emissions, even those far downstream in the value chain. As counterpoint to the prevailing narrative that the petroleum industry has caused nothing but global harm, this contribution argues for a more nuanced view by examining the industry's role in global warming within an historical and societal context, highlighting its positive contributions to society and the geosciences and, finally, showing how industry expertise in carbonate and evaporite geoscience is aiding the energy transition.

Molecular Dynamics Simulations of Supercritical Carbon Dioxide and Water using TraPPE and SWM4-NDP Force Fields.

The increased levels of carbon dioxide (CO2) emissions due to the combustion of fossil fuels and the consequential impact on global climate change have made CO2 capture, storage, and utilization a significant area of focus for current research. In most electrochemical CO2 applications, water is used as a proton donor due to its high availability and mobility and use as a polar solvent. Additionally, supercritical CO2 is a promising avenue for electrochemical applications due to its unique chemical and physical properties. Consequently, understanding the interactions between water and supercritical CO2 is of great importance for future electrochemical applications. Molecular dynamics (MD) simulation is a powerful tool that enables atomistic-resolution dynamics of molecular systems, which can complement and guide future experimental investigations. This study employed atomistic MD to study the cosolubilities, codiffusivities, and structure of supercritical CO2 and water systems, with a polarizable water model (SWM4-NDP) and a nonpolarizable CO2 model (TraPPE). Additionally, ab initio MD simulations were used to better understand how atomistic polarizable/nonpolarizable models compare to explicit modeling of electron densities. The polarizable water model exhibited substantial improvement in water-associated properties. We anticipate the development of a compatible polarizable CO2 model to yield similar improvement, providing a pathway for realizing novel high-pressure electrochemical systems.

Highly selective ethanol gas sensor based on CdS/Ti3C2T x MXene composites.

Sensing of hazardous gases has an important role in ensuring safety in a variety of industries as well as environments. Mainly produced by the combustion of fossil fuels and other organic matter, ethanol is a dangerous gas that endangers human health and the environment. Stability and sensing sensitivity are major considerations when designing gas sensors. Here, a superior ethanol sensor with a high response and fast recovery was synthesized by "wrapping" CdS nanoparticles on metallic Ti3C2T x MXene using a simple method. CdS nanoparticles were uniformly covered on the Ti3C2T x MXene surface, forming a "rice crust"-like heterostructure. The sensor displayed good detection of ethanol gas at room temperature. Response signals up to 31% were obtained for ethanol molecules (20 ppm) with quick recovery (41 s). The performance of the ethanol sensor was evaluated across a range of concentrations (5-100 ppm) and relative humidity (60% and 90% RH) at room temperature. Our method could open up a new strategy for the development of ethanol sensors.

Artificial Intelligence-Enhanced Green Building Design for Environmental Sustainability

Green buildings are those that use sustainable methods of construction to either maintain or improve the local quality of life. Decisions affecting a project's quality, safety, profitability, and timetable are made using Artificial Intelligence (AI) in Green Construction by analyzing data gathered from monitoring the construction site and using predictive analytics. For instance, increased accuracy in weather predictions might lead to more production, less waste, lower costs, and less greenhouse gas emissions. Green building construction is a significant source of carbon dioxide released through the breakdown of carbonates. Researchers have concluded that integrating industrial wastes is crucial in green concrete making due to its benefits, such as reducing the requirement for cement. When planning with concrete, its compressive strength must be considered. Due to their high predictive power, AI algorithms may be used to determine the compressive strength of concrete mixtures. Existing artificial intelligence (AI) models may be evaluated for their modeling process and accuracy to inform the creation of new models that more accurately represent the comprehensive evaluation of setting parameters on model performance and boost accuracy. Potential sources of conflict in this anthropocentric future include climate change and the availability of renewable energy sources. Scientists think there is a connection between the increased emission of greenhouse gases like carbon dioxide (Co2) from the combustion of fossil fuels and the acceleration of climate change and global warming. Research has demonstrated that the building sector is a significant source of atmospheric carbon dioxide (Co2). Construction, building activities, and subpar energy sources have all significantly increased atmospheric CO2. The proposed research set out to measure how well AI in Green Building Construction (AI-GBC) might reduce carbon emissions and utility bills. Artificial intelligence uses SVM and GA to reduce energy use and carbon dioxide emissions. Several statistical metrics, such as Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and Root Mean Squared Log Error (RMSLE), are used to evaluate the AI-GBC's precision. Both Machine Learning (ML) models yielded positive results, with prediction accuracies above 95%. Regarding predicting Co_2, GA models were close to the mark, with an R2 of 0.95. Ninety-six percent will complete a performance analysis, and 97% will conduct a k-fold cross-validation analysis. Cross-validation is used to ensure that the findings of the extended modeling technique are accurate and prevent overfitting.

DETERMINAÇÃO DE BIODIESEL METÍLICO DE DENDÊ EM MISTURAS COM DIESEL UTILIZANDO A RESOLUÇÃO MULTIVARIADA DE CURVAS COM MÍNIMOS QUADRADOS ALTERNADOS

DETERMINATION OF PALM METHYL BIODIESEL IN DIESEL BLENDS USING MULTIVARIATE CURVE RESOLUTION WITH ALTERNATING LEAST SQUARES. The increase in the average temperature of the Earth due to excess CO2 and other greenhouse gases has caused glaciers to melt and sea levels to rise. The burning of fossil fuels is one of the main causes of this problem, so the use of biofuels is important for mitigating this environmental impact. In Brazil, biodiesel is mixed with mineral; however, irregularities have been detected, reducing the expected positive effects. Therefore, this study proposes the use of multivariate curve resolution with alternating least squares (MCR-ALS) to quantify the content of methyl palm oil biodiesel in diesel blends and determine the concentration of the adulterant automotive lubricating oil in the blend. The model for quantifying biodiesel in diesel obtained R2 = 0.9997, root mean square error of calibration (RMSEC) = 0.56% (v v-1) and prediction (RMSEP) = 0.65% (v v-1), while the determination of adulteration in the biodiesel-diesel blend showed RMSEC = 0.67% (v v-1), RMSEP = 0.81% (v v-1) and R2 = 0.9992. These results demonstrate the ability of the models developed to predict both the content and quantity of possible adulterants in blends of palm oil biodiesel and mineral diesel, contributing to the quality control of this fuel.

Source-resolved black carbon and PM2.5 exposures during wildfires and prescribed burns.

Changes in climate and land-use have significantly increased both the frequency and intensity of wildland fires globally, exacerbating the potential for hazardous impacts on human health. A better understanding of particle exposure concentrations and scenarios is crucial for developing mitigation strategies to reduce the health risks. Here, PM2.5 and black carbon (BC) concentrations were monitored during wildland fires between 2022-2024, in fire-prone areas in Catalonia (NE Spain), by means of personal monitors (AirBeam2 and Micro-aethalometers AE51 and MA200). Results revealed that exposures to combustion aerosols (PM2.5 and BC) were significant and comparable during wildfires and prescribed burns (mean PM2.5 during wildfires = 152 μg/m3 vs. 110-145 μg/m3 for prescribed burns). Overall, BC/PM2.5 ratios showed a large variability as a function of the monitoring scenario, indicating varying contributions from mineral aerosols to the emissions mix originating from fire management and extinction tasks. Specifically, mop-up tasks (final extinction tasks involving stirring top soil using handheld tools) were identified as a significant contributor to PM2.5 exposures, with 1-minute PM2.5 peak concentrations reaching up to 1,190 μg/m3. These results may be especially valuable for emissions modelling. Source apportionment of multi-wavelength BC datasets provided deeper insights into emissions and their impact on exposure profiles: line operators (who control the fire perimeter) were predominantly exposed to biomass burning smoke (61%) when compared to BC from fossil-fuel combustion ( = 39%), while torchers (in charge of initiating technical fires using fossil-fuel drip-torches) were predominantly exposed to (77% vs. 23% ). These findings highlight the value of portable monitors in the assessment of wildfire emissions and impacts on human exposure and environment. The combination of these tools, reporting data in real-time and with high time-resolution, is key to the design and implementation of effective mitigation strategies for environmental and health concerns related to wildland fires.

Evaluation of solar thermal pretreatment of carbonate-rich manganese ores in high-carbon ferromanganese production through dynamic process modelling

The necessity of reducing greenhouse gas emissions to limit the impact of anthropogenic climate change means that all industrial processes should investigate their options towards decarbonization. Iron, steelmaking, aluminium, and cement production produce the most industrial emissions. Although most research focuses on decarbonizing these industries, minerals processing industries must be decarbonized to achieve net zero emissions goals by 2050. Incorporating renewable energy sources and avoiding the combustion of fossil fuels are two ways to reduce greenhouse gas emissions. This paper reports on the results from a dynamic process model developed to investigate the feasibility of concentrating solar thermal pretreatment of manganese ores to pretreat carbonate-rich manganese ores for increased ferromanganese smelter productivity and reduced greenhouse gas emissions. The results indicate that pretreated ores reduce the energy requirement for smelting significantly for some ores and lowers total carbon dioxide emissions by 13 to 19% compared to the traditional smelting route. A high-level economic evaluation shows that solar thermal treatment is financially viable for low cryptomelane, high braunite ore that is common in the Kalahari Manganese Field.

Procrastination on production of energy using renewable sources retard settlement of congenial society: Evidence of Bangladesh

A better flow of resources to total package of energy production can ensure sustainable development of a nation. Bangladesh is a country which cannot yet make available all resources of energy required for sustainable development. Production of energy from renewable sources are not yet been accounted nationally. Sustainable Development Goals (Goal–7) demands creation of energy through resources like: water, air, sunlight and joint effect of another environmental resources. The task of production of energy through renewable sources has already been started but in a discrete manner. As a result, energy from conventional resources are used heavily for completing the production cycles in Bangladesh. The sources of energy at persisting process are mentioned as: natural gas (54.67%), fossil fuel (21.72%), coal (6.97%) wind, solar etc. (0.085%) and hydro (0.12%) and bio-fuels (15.90%). It can be pointed that the sources of energy through renewable resources is observing very negligible picture even after nine years of adopting UN convention and ratification for SDG (Goal 7). The absent of energy through renewable sources and burning of coal, fossil fuels, and natural gas for energy warming the atmosphere and affecting human health and environment. Considering this, the study attempts to find relationship of per capita generation of electricity with economic growth and other energy resources. Besides this, the study attempts to know how the changes of resources quantity influence the per capita generation of energy. Moreover, the research required to find out the turning point of the individual series contributing to the amount final product. The values of the parameters and the analysis are shown significant results, which support that the atmosphere getting more heat, polluting the environment and affecting the human health. As a result, more strong steps are to be taken to get rid of many unacceptable issues which is degrading atmospheric environment, human health and retarding the development of congenial process of living. On this situation, the study suggests that the generation of electricity observing renewal process should be started in full swing reducing the persisting long traditional process. This may lead to achieving targeted indicators for sustainable development goals (SDG 7) and help creating a pleasant and congenial society.

Determination and Removal of Potentially Toxic Elements by Phragmites australis (Cav.) Trin. ex Steud. (Poaceae) in the Valles River, San Luis Potosí (Central Mexico)

The contamination of rivers by potentially toxic elements (PTEs) is a problem of global importance. The Valles River is Ciudad Valles’ (Central Mexico) main source of drinking water. During the four seasons of the year, water samples (n = 6), sediment samples (n = 6), and Phragmites australis plants (n = 10) were taken from three study sites selected based on the presence of anthropogenic activities in the Valles River. A graphite atomic absorption spectrophotometer estimated elements in the water, and an energy-dispersive X-ray fluorescence spectrometer quantified elements in sediments and plant samples. Phragmites australis accumulated metal(loid)s mainly in the roots during all seasons of the year. Water samples from all sites recorded PTEs (As, Pb, Cd, and Hg), with primary sources identified as the sugar industry, urban and industrial wastewater, and the combustion of fossil fuels. Sediment samples showed concentrations of Hg, Mn, Ni, Zn, Pb, V, Cu, Cr, and Cd, attributed to agricultural practices, industrial activity, and urbanization. P. australis is an alternative for in situ phytoremediation because this macrophyte can bioaccumulate different elements in its roots, such as Mn, Rb, V, Sr, Cu, Zn, Pb, Ni, and As.

A mid-20th century stratigraphical Anthropocene is recognisable in the birth-area of the industrial revolution

The formalisation of the Anthropocene as a subdivision of the Geological Time Scale has been under debate. Its stratigraphic boundary has been proposed as a precise Global boundary Stratotype Section and Point (GSSP) in the mid-20th century, but it is part of an episode of human-induced changes to the Earth System that have unfolded over millennia. Here we attempt to identify stratigraphical patterns of the Anthropocene from a previously well studied lake sedimentary archive from the English Midlands, located in one of the most heavily human-modified landscapes in the UK, and the birthplace of the Industrial Revolution. Our analysis is predicated on the sedimentary succession of Groby Pool, a small lake situated to the immediate northwest of Leicester. We have found that whilst proxy signals for biotic change are indicative of significant landscape and consequent ecological changes prior to the 20th century, the signal from radiogenic fallout and rapid increase in spheroidal carbonaceous particles indicative of fossil-fuel combustion yield a clear mid and later 20th century stratigraphical signature that corresponds with the Great Acceleration of the post-WWII period. We therefore demonstrate clear stratigraphical signatures in the oldest Industrial Revolution landscape on Earth that are consistent with a mid-20th century start point for the Anthropocene.

Forecasting CO₂ Emissions with Machine Learning Methods: Türkiye Example and Future Trends

Climate change is a critical problem that causes global environmental and social issues due to increased greenhouse gas emissions caused by human activities. Carbon dioxide (CO₂) emissions, in particular, are one of the main elements of global warming and have devastating effects on ecosystems. Keeping track of carbon dioxide emissions resulting from human activities like burning fossil fuels, clearing forests, and farming, as well as forecasting their future patterns, is essential for creating effective sustainable environmental strategies. The study utilized machine-learning models to evaluate CO₂ emissions per individual, using the dataset from the Global Carbon Atlas that has released in 2023. In the study, the traditional ARIMA model and deep learning-based LSTM networks were comparatively discussed. The models were trained with the aim of predicting Türkiye's future CO₂ emission levels by learning from past data, and their performances were evaluated with MAE, MSE, RMSE, and R² metrics. The LSTM model achieved an R² score of 90.4%, while the ARIMA model achieved an R² score of 94.3%. The findings show that machine learning techniques are a powerful tool in the fight against climate change and provide valuable insights for policymakers. The findings of the study guide more effective monitoring of CO₂ emissions and determination of strategies for sustainable development goals.

An overview of climate changes and its effects on health - from mechanisms to One Health.

Human activities, primarily the burning of fossil fuels, widespread deforestation, soil erosion or machine-intensive farming methods, manufacturing, food processing, mining, and construction iron, cement, steel, and chemicals industry, have been the main drivers of the observed increase in Earth's average surface temperature and climate change. Rising global temperatures, extreme weather events, ecosystems disruption, agricultural impacts, water scarcity, problems in access to good quality water, food and housing, and profound environmental disruptions such as biodiversity loss and extreme pollution are expected to steeply increase the prevalence and severity of acute and chronic diseases. Its long-term effects cannot be adequately predicted or mitigated without a comprehensive understanding of the adaptive ecosystems. Studying the complex interaction between environmental aggressors and the resilient adaptive responses requires the exposomic and the One Health approaches. The problem is broad and affects the whole ecosystem, plants, pets and animals in addition to humans. The central role of the epithelial barrier, microbiome, and diet as key pillars for an adaptive tolerogenic immune response should be explored for increasing resilience at the individual level. A radical change in mindset worldwide, with sustainable solutions and adaptive strategies and climate-resilience and health equity policies at their center, should be achieved quickly through increased awareness based on solid scientific data.

INTRODUCTION: CLIMATE SUSTAINABILITY – EVIDENCE AND POLICY

Last year saw yet another year of weather extremes. The Copernicus Climate Change Service run by the European Centre for Medium-Range Weather Forecasts on behalf of the European Commission (Copernicus, 2024) measured 2023 as being globally the warmest year since records began in 1850. This was by a large margin (0.17 per cent) over the previous record in 2016, with global surface air temperature at nearly 1.5°C above pre-industrial levels. While last year’s observations embodied an El Niño effect, which every few years sees temperatures affected by warmer waters coming to the surface of the tropical eastern Pacific Ocean, changes and anomalies consistently observed over the last few years across the globe are becoming more pronounced. What is commonly labelled “climate change” is turning into a global climate emergency. No economy or society are immune to its effects. Today, we see the global average temperature at over 1.1°C above pre-industrial levels, a rise that has been extraordinarily rapid on a planetary timescale, and one that has been primarily caused through our (humans) burning fossil fuels. Nearly a decade has passed since the United Nations’ Climate Change Conference in 2015, COP21, where 196 nations adopted The Paris Agreement – a legally binding international treaty on climate change. Its goal was to hold “the increase in the global average temperature to well below 2°C above pre-industrial levels” and to pursue efforts “to limit the increase to 1.5°C”.

The Impact of Energy Consumption, Economic Growth, and Non-Renewable Energy on Carbon Dioxide Emission in Malaysia

Human activities such as burning fossil fuels, deforestation, and economic growth are increasingly affecting the climate and temperature of the earth. Large amounts of greenhouse gases in the atmosphere have increased the greenhouse effect and global warming. By 2020, the concentration of greenhouse gases in the atmosphere has increased to 48% above its pre-industrial level. The main objectives of this study are to determine the level and the pattern of the relationship between dependent and independent variables. Also, this study examines the long-term and short-term impacts of energy consumption, economic growth, and non-renewable energy on carbon dioxide (CO2) emissions in Malaysia. Due to increased industrialization, Malaysia faces significant problems, such as environmental pollution. This study uses annual time series data from 1986 to 2021 and is analyzed using the Autoregressive Distributed Lag approach. The study suggests that energy consumption, economic growth, and non-renewable energy positively impact carbon dioxide (CO2) emissions. The results through dynamic ARDL indicate that energy consumption, economic growth, and non-renewable energy positively impact Malaysia’s carbon dioxide (CO2) emissions in the short-run and long run. The error correction model (ECM) provides short- run shocks in these variables and establishes equilibrium relations in the long run. Therefore, policymakers should consider implementing a carbon tax to be enforced on polluters to prevent ecological pollution at a minimum for the short-term regulation of carbon dioxide (CO2) emissions.