Low Carbon Intensity Research Articles

Carbon Emissions and Its Relationship with Foreign Trade Openness and Foreign Direct Investment

Previous research has investigated the connections between foreign direct investment (FDI), carbon emissions (CO2), and foreign trade openness. However, these past studies did not specifically focus on industrial sectors in China and their carbon emissions, thus leaving a gap in understanding this relationship. In our study, we aim to contribute to the existing body of knowledge by employing a threshold regression model with a threshold variable. This model calculates how strongly carbon emissions are produced to assess the impact of the industrial sector on carbon emissions. Our findings reveal that foreign trade openness and FDI have a threefold threshold impact on industrial carbon emissions. The effect of FDI on carbon emissions in the industrial sector shows a pattern of initially lowering and then increasing the emissions, indicating potential harm. Conversely, the impact of foreign trade openness on carbon emissions exhibits both positive and negative effects. While foreign trade openness exacerbates carbon emissions in economic sectors with lower carbon intensity, it helps mitigate emissions in sectors with high- carbon emission levels. Furthermore, our study identifies that the intensity of economic activity, per capita GDP, and the number of employees all significantly influence the industrial sector’s carbon emissions. By employing the latest cutting-edge methodology, our research opens the door for extrapolating these findings to other nations for a comprehensive analysis.

Reducing Carbon Emissions of EV Charging via User Behavior and Carbon Intensity Analysis

The increased adoption of electric vehicles (EVs) has the potential to significantly reduce carbon emissions by decreasing reliance on fossil fuels. However, as more EVs populate our roads, there will be a heightened demand for electricity from the grid, leading to increased carbon emissions due to EV charging. Currently, most EV owners do not align their charging behavior with periods of low carbon intensity in the power grid. To reduce the carbon emissions resulting from EV charging, it is essential to alter the charging behavior of EV users. To tackle this problem, we propose a solution that leverages user charging behavior data with carbon intensity data to identify optimal charging times for EVs, resulting in reduced carbon emissions. Our simulation results using 10,000 EVs demonstrate that the proposed carbon-aware EV charging algorithm can reduce 9.3% of carbon emissions by optimizing EV charging times.

Route-to-market strategy for low-carbon hydrogen from natural gas in the Permian Basin

This paper investigates the untapped potential of the Permian Basin, a multifaceted energy axis in Texas and adjoining states, in the emerging era of decarbonization. Aligned with current policy directives on regional hydrogen hubs, this study explores the viability of developing a hydrogen energy hub in the Permian Basin, thereby producing low-carbon intensity hydrogen from natural gas in the Basin and transporting it to the Greater Houston area. Diverging from existing literature, this study provides an integrated techno-economic evaluation of the entire hydrogen value chain in the Permian Basin, encompassing production, storage, and transportation. Furthermore, it comparatively analyzes the scenario of interest against an optimized base scenario, thereby underlining comparative advantages and disadvantages. The paper concludes that the delivered cost of Permian-based low-carbon intensity hydrogen to the Greater Houston area is $1.85/kg, benchmarked to the scenario, with hydrogen produced close to the Greater Houston area and delivered at $1.42/kg. Our findings reveal that Permian-based low-carbon intensity hydrogen production can achieve cost savings in feedstock ($0.25/kg) and potentially accrue a higher production tax credit due to a shorter gas supply chain to production ($0.33/kg). Nevertheless, a significant cost barrier is the expense of long-haul pipeline transport ($0.90/kg) from the Permian Basin to Houston as opposed to local production. Despite the obstacles, the study identifies a potential breakeven solution where increasing the production scale to at least 412,000 metric ton per year (about 3 steam-reforming plants) in the Permian Basin can effectively lower costs in the transport sector. Hence a scaled-up production can mitigate the cost difference and establish the Permian Basin as a competitive player in the hydrogen market. In conclusion, a SWOT analysis presents Strengths, Weaknesses, Opportunities, and Threats associated with Permian-based hydrogen production.

Assessment of M15 Fuel on BS IV 2 and 3-Wheeler

Across the world, methanol is evolving as a clean, sustainable transportation fuel for the future. Methanol fuel is an alternative biofuel for internal combustion and other engines, either in combination with gasoline or independently. Methanol's high octane and oxygen content produces a cleaner burning gasoline which significantly reduces vehicle exhaust emissions. A lower boiling temperature for better fuel vaporization in cold engines, the highest H-C ratio for a lower carbon intensity fuel, and no Sulphur contamination which improves catalytic converter operation. In the paper, a study is carried out for the blend of 15% methanol (M15) with Gasoline on BS-IV vehicles and a comparison is done for the tailpipe emissions. A gap analysis of vehicles with E0 and M15 fuel is done with baseline emission testing along with full throttle performance of the vehicle to check the effect of oxygenated fuel (M15). The main purpose of this study is to analyze the impact of M-15 fuel on 2 and 3-wheeler vehicles in the as-is condition without any engine tuning and retaining the base gasoline (E0) settings.
 Keywords: M15 fuel, methanol, BS IV, blended fuel, tailpipe emission, hygroscopic, 2 and 3-wheelers, mass emission, fuel economy, NOx

The characteristics and drivers of China’s city-level urban-rural activity sectors’ carbon intensity gap during urban land expansion

Identifying cities’ characteristics of urban-rural overall carbon intensity imbalance is significant for the formulation and implementation of emission mitigation policies. However, existing literature focused more attention on residential sectors, ignoring other important activity sectors’ emissions. Thus, this paper estimated China’s city-level urban and rural overall carbon intensities based on all activity sectors defined by EDGAR. Subsequently, we discussed the drivers from the perspective of urban expansion. The results show that (1) China’s activity sectors in rural areas presented higher carbon intensity than those in urban areas during urban land expansion, which was mainly caused by higher rural carbon emissions density and worse rural technological level; (2) Among cities, rural areas in some developed mega cities (e.g., Shanghai and Beijing) achieved lower carbon intensity than urban areas, while those in many developing cities still suffered from worse low-carbon economy. Carbon emissions density and technological gap were typically responsible for the worse situations of those developing cities’ rural areas; (3) based on impulse responses, an increase in urban-rural technology gap significantly reduced rural areas’ carbon intensity and urban-rural carbon intensity gap in lagged periods. Especially, China’s eastern region’s urban-rural technology gap made significant contributions to improving rural technological level.

Spatial compactness and carbon emission: Nighttime light satellite‐based exposure assessment

AbstractScholars of urban sustainability are increasingly interested in the influence of spatial configuration on local environmental performance, with a focus on urban compactness. Spatial compactness with urban density boosts energy‐efficient construction and infrastructure, subsequently encouraging lower carbon emissions. In this study, we first documented the distributional pattern of spatial compactness in the prefectures of Japan using refined measurement and nighttime light satellite data, which is a more consistent indicator of economic activities. Further, we investigate the underlying impact of this compactness on the local carbon emission intensity with quantitative evidence. The regression results indicate that higher compactness in a prefecture corresponds to lower carbon intensity even in different settings. Moreover, robustness checks verify the consistency of the abatement effects. Additionally, the mitigating role of compactness presents a heterogeneous pattern across sectors. The effect is statistically significant only in the manufacturing and household sectors. These findings add to the value of urban compactness and offer important policy implications for addressing sustainable societies in the long term.

Energy regulation, energy innovation, and carbon intensity nexus in China: A nonlinear perspective

Considering the role of energy regulations and innovations in reducing energy-driven emissions, our main objective is to scrutinize the influence of energy regulations and innovations on carbon intensity in China over the period 1991–2020. In contrast to the previous studies, the analysis also focuses on the asymmetry assumption. The scientific value added to this study lies in its innovative methods and empirical evidence. The autoregressive distributed lag model, both linear and nonlinear, is utilized in the research to examine the short- and long-run estimates. The linear model highlights that energy regulations, energy innovations, and human capital reduce carbon intensity in the long run, while per capita income and financial development escalate it. However, only energy regulations and human capital help reduce carbon intensity in the short term. In the nonlinear models, the positive shock in environmental regulations reduces carbon intensity in short and long run. Conversely, the positive shock in energy innovations reduces carbon intensity in the long run. Negative shocks in energy regulations and innovations have a statistically insignificant impact on carbon intensity in both the short and long term. In addition, per capita income and financial development only increase carbon intensity in the long run, while human capital reduces carbon intensity in the short run. These findings advocate for implementing heavy energy taxes on firms and industries that rely heavily on fossil fuels. Increasing investment in green energy innovations is the need of the hour in lowering carbon intensity in China.

Probabilistic modelling of seasonal energy demand patterns in the transition from natural gas to hydrogen for an urban energy district

The transition to a low-carbon energy system can be depicted as a “great reconfiguration” from a socio-technical perspective that carries the risk of impact shifts. Electrification with the objective of achieving rapidly deep decarbonisation must be accompanied by effective efficiency and flexibility measures. Hydrogen can be a preferred option in the decarbonisation process where electrification of end-uses is difficult or impractical as well as for long-term storage in energy infrastructure characterised by a large penetration of renewable energy sources. Notwithstanding the current uncertainties regarding costs, environmental impact and the inherent difficulties of increasing rapidly supply capacity, hydrogen can represent a solution to be used in multi-energy systems with combined heat and power (CHP), in particular in urban energy districts. In fact, while achieving carbon savings with natural gas fuelled CHP is not possible when low grid carbon intensity factors are present, it may still be possible to use it to provide flexibility services and to reduce emissions further with switch from natural gas to hydrogen. In this paper, a commercially established urban district energy scheme located in Southampton (United Kingdom) is analysed with the goal of exploring potential variations in its energy demand. The study proposes the use of scalable data-driven methods and probabilistic simulation to generate seasonal energy demand patterns representing the potential short-term and long-term evolution of the energy district.

Evaluation on key technologies for the construction of low-carbon index of electric power based on “double carbon”

Abstract At a time when global climate change poses a major challenge to human survival and development, all countries believe that people must actively deal with green and low-carbon (LC) development. As one of the hot topics in recent years, the concepts of “carbon neutral” and “carbon peak” have a significant impact on the construction of New Energy (NE) systems. The construction of NE systems with NE as the main component is an important way to achieve the “double carbon” goal. Affected by the “double carbon” goal, the energy system has shifted to a low carbon and high intensity system, reducing the dependence on fossil fuel power generation, accelerating the use of clean energy, and promoting the supply system of low carbon and clean energy. In order to improve the LC construction of electric power, this article studied the key technologies of LC index construction of electric power under the background of “double carbon”. This article first introduced the LC construction of urban electric power, including the connotation of LC electric power, the current situation of NE development and the difficulties of LC construction of electric power in the context of “double carbon”. Then this article constructed a new type of LC Power System (PS) on the basis of double carbon, and introduced the framework of the system and the key technologies included in the system. Finally, this article verified the effectiveness of the new LC PS in LC construction through experiments, and put forward suggestions for the realization of LC power construction. The experiment showed that the new LC PS can greatly promote the construction of the LC index of power, and is conducive to the development of urban power. The proportion of urban non-fossil energy and the new installed capacity of non-fossil energy power generation have been significantly increased. Among the four cities studied in this article, the proportion of non-fossil energy in two cities has increased from less than 50 % to more than 50 %, which has greatly promoted the construction of LC index of electricity.

Temperature-vacuum swing adsorption for direct air capture by using low-grade heat

Direct air capture (DAC) is a promising carbon mitigation technology and will likely be part of extensive carbon removal portfolio. Adsorptive DAC is an appropriate option for carbon capture to utilize low-grade heat because of its desirable regeneration temperature and adaptability to be integrated with renewables. Building indoor environment with CO2 concentrations above 1000 ppm provides another suitable scenario for DAC. Herein, DAC using temperature-vacuum swing adsorption (TVSA) is presented and analyzed by integrating various low-grade heat sources in buildings. An amine-functionalized metal organic framework is selected for process simulation, and the performance is compared with those using other sorbents. It indicates that amine-functionalized material has advantages in CO2 productivity and purity. A techno-economic analysis is carried out to explore the benefit of the proposed DAC in buildings. The results show that regeneration by heat pumps at 373 K is the most competitive solution and has 176.7 $·tCO2−1 of the levelized cost of DAC (LCOD). Compared with conventional energy supply, solutions with low-grade heat utilization in buildings could achieve lower carbon intensity and increase by 5.2–25.0% in net LCOD. These results will provide practical guidelines for DAC application with lower energy penalties and costs.

Carbon dioxide-enhanced oil recovery in Australia – techno-economic evaluation, carbon dioxide source/sink networks and current policy landscape

This paper presents the results of a techno-economics analysis to quantify the potential for storing CO2 and producing lower carbon intensity oil from mature, onshore Australian oil fields located in the Cooper/Eromanga and Surat/Bowen Basins. The work explores the impact of incentivisation, identifies possible sources of CO2 to support CO2-EOR (enhanced oil recovery) deployment, and discusses global CO2-EOR policy. The hypothetical ‘carbon incentive’ assessed in this study resulted in unlocking an additional 40 million metric tons (Mt) of CO2 storage and 73 million barrels (MMBO) of domestic oil production compared to the base case scenario that most closely represent Australia’s current policy and economic settings. Further, the results of this study indicated that, with incentivisation, net-negative carbon dioxide emissions could be achieved by deploying CO2-EOR practices in certain mature oil fields. The study found that there are currently sufficient industrial sources of CO2, particularly from black coal-fired power generation and hard-to-abate industries such as cement and steel production, to support this deployment. An opportunity to explore the co-development of ‘stacked storage’ using both CO2-EOR and concurrent geologic storage of CO2 in adjacent, unconnected reservoirs is proposed. This may significantly reduce development costs compared to stand-alone geologic storage projects, providing more favourable techno-economics, and accelerating the physical connection of CO2 sources and sinks.

Techno-economic analysis and life cycle analysis of e-fuel production using nuclear energy

Electrofuels, or e-fuels, are synthetic liquid hydrocarbon fuels which may be produced using carbon dioxide (CO2) and low carbon hydrogen (H2) as feedstock. They are of great interest because they have much lower carbon intensity compared to the conventional petroleum fuels and can utilize the existing fuel infrastructure owing to their ability to blend with or replace existing fuels. We modeled an e-fuel production process to produce low carbon jet, diesel, and naphtha using a reverse water gas shift process to produce synthesis gas, followed by a Fischer-Tropsch (FT) synthesis process. Nuclear energy is considered for e-fuel production due to its steady energy supply, near-zero carbon emissions, capability to produce hydrogen with high efficiency via high temperature electrolysis, and proximity to biogenic CO2 sources from nearby corn-ethanol plants in the United States. The modeled FT process achieved a high carbon conversion ratio of 99% by recycling CO2 and the use of oxy-combustion, and a process energy efficiency of approximately 70%. The life cycle greenhouse gases emissions are estimated to be 7 and −25 gCO2e/MJ, without and with steam coproduct credit, respectively, by using the Greenhouse gases, Regulated Emissions, and Energy use in Technologies (GREET®) model. Additionally, the process economics were evaluated for three scales corresponding to nuclear power plant capacities of 100, 400, and 1000 MWe, estimating a minimum fuel selling price (MFSP) of $3.61/gal ($0.95/L), $2.82/gal ($0.74/L), and $2.66/gal ($0.70/L) of FT fuel mix, respectively, by considering $3/kg of H2 tax credit prescribed in the recent Inflation Reduction Act.

Locus lands biosurfactant loan and collaboration

The specialty chemical firm Locus Fermentation Solutions has secured $117 million to expand its biosurfactant business . The money comes in the form of an unusual loan that uses Locus’s intellectual property (IP), including more than 1,300 patents, as collateral. Locus uses custom microbial fermentation to produce specialty surfactants. Most of the firm’s products are based on sophorolipids, biosurfactants with hydrophilic sophorose sugar heads and various hydrophobic fatty acid tails. CEO Andy Lefkowitz says the loan will help pay for a capacity expansion underway that will triple overall factory space to 14,000 m 3 at Locus’s headquarters site in Solon, Ohio, and other locations. Locus is organized as a holding company with operating companies focused on different markets. Lefkowitz says the firm’s fastest-growing market is oil drilling and mining, where its surfactants can increase yields and lower carbon intensity. One of the companies, Locus Performance Ingredients, recently signed a pact

CarbonMonitor-Power near-real-time monitoring of global power generation on hourly to daily scales

We constructed a frequently updated, near-real-time global power generation dataset: CarbonMonitor-Power since January, 2016 at national levels with near-global coverage and hourly-to-daily time resolution. The data presented here are collected from 37 countries across all continents for eight source groups, including three types of fossil sources (coal, gas, and oil), nuclear energy and four groups of renewable energy sources (solar energy, wind energy, hydro energy and other renewables including biomass, geothermal, etc.). The global near-real-time power dataset shows the dynamics of the global power system, including its hourly, daily, weekly and seasonal patterns as influenced by daily periodical activities, weekends, seasonal cycles, regular and irregular events (i.e., holidays) and extreme events (i.e., the COVID-19 pandemic). The CarbonMonitor-Power dataset reveals that the COVID-19 pandemic caused strong disruptions in some countries (i.e., China and India), leading to a temporary or long-lasting shift to low carbon intensity, while it had only little impact in some other countries (i.e., Australia). This dataset offers a large range of opportunities for power-related scientific research and policy-making.

Disruptive Displacement: The Impacts of Industrial Robots on the Energy Industry’s International Division of Labor from a Technological Complexity View

In light of the growing economic uncertainties worldwide, the use of industrial robots has emerged as a significant opportunity for improving the production efficiency and the international division of labor in China’s energy industry. This study employed a two-way fixed-effect model utilizing data from 31 Chinese provinces between 2011 and 2019 to investigate the impact of industrial robots on the energy industry’s participation in the international division of labor. The results of the study indicated that the widespread application of industrial robots can boost the international division of labor status of China’s energy sector. This conclusion remains robust even after addressing the potential endogeneity issues and conducting a range of sensitivity tests. Furthermore, our findings suggest that the regions that possess abundant energy resources or exhibit a lower carbon intensity are more likely to leverage the use of industrial robots to increase the technological sophistication and enhance their participation in the international division of labor. The application of industrial robots in the energy industry can enhance the international division of labor through two distinct channels: optimizing the factor structure and reducing the export costs. Our findings have important policy implications for ensuring energy security and improving the energy industry’s participation in the international division of labor.

Comparative analysis of associated cost of nuclear hydrogen production using IAEA hydrogen cost estimation program

The interest in non-electric applications of nuclear energy is rising ranging from hydrogen production, district heating, seawater desalination, and various industrial applications to provide long-term answers for a variety of energy issues that both present and future generations will confront. Hydrogen is a dynamic fuel that can be used across all industrial sectors to lower carbon intensity. This study, therefore, aims at estimating the cost of nuclear hydrogen production from some light water reactors using International Atomic Energy Agency (IAEA) Hydrogen Calculator (HydCalc) program and comparing the result with similar existing studies conducted by other scholars using the Hydrogen Economic Evaluation Program (HEEP) program. The study employs six existing Light Water Reactors (LWRs) comprised of Korea Advanced Power Reactor 1400 MW electricity (APR1400), Russian VVER-1200, Davis-Besse Nuclear Power Plant in Ohio, Prairie Island NPP in Minnesota, Nine Mile Point NPP in New York, and Arizona Public Service's Palo Verde NPP to evaluate the Levelized cost of nuclear hydrogen production. Estimation of hydrogen demand was performed without carbon dioxide (CO2) tax since nuclear power has zero CO2 emission. The Levelized costs obtained using IAEA HydCalc and HEEP Programme were compared as follows; APR1400 cost are 2.6$/kg and 3.18$/kg, VVER1200 cost are 3.8$/kg and 3.44$/kg; Exelon cost are 1.7$/kg and 4.85$/kg; Davis Besse cost are 3.9$/kg and 3.09$/kg; Parlo Verde cost are 3.5$/kg and 4.77$/kg; Xcel Energy cost are 3.63$/kg and 0.69$/kg. The cost of hydrogen production using HEEP for Xcel Energy's Prairie Island NPP is 0.69 $/kg. This is because the reactor utilizes High Temperature Steam Electrolysis, method of hydrogen production, while the other methods employs Low Temperature Electrolysis. The results shows that the final price of the hydrogen for each reactor technology depends not only on the production method but also on the cost of the nuclear power plant and the production rate of the hydrogen plant.

Developing guidelines for waste designation of biofuel feedstocks in carbon footprints and life cycle assessment

Biofuels continue to play a role in strategies for decarbonization, especially for transportation. However, to determine whether a particular biofuel pathway can achieve decarbonization, its life cycle greenhouse gases (i.e., carbon intensity) must be calculated. The two most important steps in the biofuel life cycle are feedstock production and conversion. When a feedstock is derived from a waste or residue, it can lead to very low carbon intensity for the resulting fuel. Consistency in how waste or residue designations are made is critical, especially when carbon intensities are used in a regulatory context. We develop a taxonomy for feedstock classification, supported by a decision tree for the designation of feedstocks, which may be classified as primary products, co-products, by-products, or wastes. These designations are critical for determining the allocation method by which carbon intensity estimates for feedstocks are calculated under policies such as California's Low Carbon Fuel Standard. The decision tree is designed to include two possible questions as the fifth step, differentiated by the inclusion or exclusion of an economic threshold. An economic threshold is common for distinguishing between co-products and byproducts in biofuel policies. Based on the resulting decision tree, several feedstock candidates are tested, and the results analyzed through a SWOT (Strengths, Weaknesses, Opportunities, Threats) analysis to determine if there are specific benefits or drawbacks of the proposed decision tree. The results from the feedstock tests show that the choice of the fifth question does not affect carbon intensity estimates for the selected test cases. However, depending on the economic value of a feedstock, a feedstock could be deemed a byproduct instead of a co-product based on an economic threshold. Choosing to include an economic threshold in the decision process will result in more feedstocks designated as by-products, rather than primary products, thus attributing them a lower carbon intensity.

Simulation of Sorption-Enhanced Steam Methane Reforming over Ni-Based Catalyst in a Pressurized Dual Fluidized Bed Reactor

Steam methane reforming is a major method of hydrogen production. However, this method usually suffers from low energy efficiency and high carbon-emission intensity. To solve this issue, a novel steam-methane-reforming process over a Ni-based catalyst in a pressurized dual fluidized bed reactor is proposed in this work. A three-dimensional computational fluid dynamics (CFD) model for the complex physicochemical process was built to study the reforming characteristics. The model was first validated against the reported data in terms of hydrodynamics and reaction kinetics. Next, the performance of the proposed methane-steam-reforming process was predicted. It was found that the methane-conversion ratio was close to 100%. The mole fraction of H2 in the dry-yield syngas reached 98.8%, the cold gas efficiency reached 98.5%, and the carbon-capture rate reached 96.4%. It is believed that the proposed method can be used for methane reforming with high efficiency and low carbon intensity.

Oriented immobilization of Thermomyces lanuginosus lipase by SBPs on silica-containing carriers for efficient bioproduction of biodiesel from Jatropha curcas oil

Biodiesel is recognized as green and renewable energy with low carbon intensity and less environmental impacts. The preparation of an economical immobilized lipase becomes much urgent challenge in the enzymatic production of biodiesel. In this study, recombinant Thermomyces lanuginosus lipase (TLL) was immobilized on the surface of silica-containing materials mediated by solid-binding peptides (SBPs). The obtained immobilized biocatalysts were effective in converting the oil from Jatropha curcas into biodiesel. The appropriate attachment mode of SBPs and TLL was investigated firstly, and the results showed that the activity of TLL was not negatively affected only when SBPs were fused at the C-terminus of TLL. Secondly, the immobilization efficiency of different SBPs (CecA, EctP1, VKT) on different silica-containing materials (SiO2, zeolite ZSM-5, SAR-100, MCM-41 and Na-Y) was systematically studied and it was concluded that the best immobilization efficiency was achieved for TLL-EctP1 immobilized on zeolite ZSM-5 (TLL- EctP1 @ZSM-5). TLL-EctP1 @ZSM-5 was found great performance in stability of pH, temperature, elution and storage. Eventually, biodiesel yield of 93 wt% was achieved using TLL-EctP1 @ZSM-5 as a biocatalyst to catalyze J. curcas oil for 48 h, and 81% of its initial yield was retained after 7 cycles of reuse. These results highlight the application of solid-binding peptides in enzyme immobilization for biocatalysts used in preparation of biodiesel or other chemicals.

The Environmental Kuznets Curve Hypothesis for Colombia: Impact of Economic Development on Greenhouse Gas Emissions and Ecological Footprint

Climate change has become a significant concern for developing countries given the risk that it poses to energy and food independence, and to general productivity. Despite having an energy system with low carbon intensity when compared to other Latin American countries, Colombia is already facing climate change impacts and requires urgent efforts to mitigate them. As a developing country, the challenge is bigger as policies for economic growth should be in line with the global commitment of reducing greenhouse gas emissions. With the aim of contributing to the design of climate policies by using data driven methodologies and scientific evidence, this study assesses the impact of economic development on the environment by examining the validity of the environmental Kuznets curve hypothesis for Colombia. Statistically validated and stable autoregressive distributed lag models are estimated for three different environmental indicators: carbon dioxide emissions, methane emissions, and the ecological footprint. Moreover, the effects of other variables such as urbanization, foreign direct investment, the value added by the agricultural and industrial sectors, and energy use are analyzed with dynamic simulations. To the best of our knowledge, there are no reports of EKC estimation using these variables in statistically validated models for Colombia; thus, this paper adds to the scientific evidence of the EKC hypothesis in developing countries. Empirical evidence supports a long-run equilibrium relationship among investigated variables and the existence of an inverted U-shaped EKC relationship between gross domestic product (GDP) and methane emissions, and GDP and the ecological footprint. The results of this paper show that shifting to renewable energy sources and leveraging the use of cleaner technologies in agricultural and industrial sectors are key factors for economic growth without harming the environment, which has important scientific value because of its evidence-based approach for public policy making in developing countries, particularly Colombia.