Emission Policies Research Articles

Research on carbon emission prediction and economic policy based on TCN-LSTM combined with attention mechanism

IntroductionIn the face of increasingly severe global climate change and environmental challenges, reducing carbon emissions has become a key global priority. Deep learning, as a powerful artificial intelligence technology, has demonstrated significant capabilities in time series analysis and pattern recognition, opening up new avenues for carbon emission prediction and policy development.MethodsIn this study, we carefully collected and pre-processed four datasets to ensure the reliability and consistency of the data. Our proposed TCN-LSTM combination architecture effectively leverages the parallel computing capabilities of TCN and the memory capacity of LSTM, more efficiently capturing long-term dependencies in time series data. Furthermore, the introduction of an attention mechanism allows us to weigh important factors in historical data, thereby improving the accuracy and robustness of predictions. ResultsOur research findings provide novel insights and methods for advancing carbon emission prediction. Additionally, our discoveries offer valuable references for decision-makers and government agencies in formulating scientifically effective carbon reduction policies. As the urgency of addressing climate change continues to grow, the progress made in this paper can contribute to a more sustainable and environmentally conscious future. DiscussionIn this paper, we emphasize the potential of deep learning techniques in carbon emission prediction and demonstrate the effectiveness of the TCN-LSTM combination architecture. The significant contribution of this research lies in providing a new approach to address the carbon emission prediction problem in time series data. Moreover, our study underscores the importance of data reliability and consistency for the successful application of models. We encourage further research and application of this method to facilitate the achievement of global carbon reduction goals.

Climatological assessment of the vertically resolved optical and microphysical aerosol properties by lidar measurements, sun photometer, and in situ observations over 17 years at Universitat Politècnica de Catalunya (UPC) Barcelona

Abstract. Aerosols are one of the most important pollutants in the atmosphere and have been monitored for the past few decades by remote sensing and in situ observation platforms to assess the effectiveness of government-managed reduction emission policies and assess their impact on the radiative budget of the Earth's atmosphere. In fact, aerosols can directly modulate incoming short-wave solar radiation and outgoing long-wave radiation and indirectly influence cloud formation, lifetime, and precipitation. In this study, we quantitatively evaluated long-term temporal trends and seasonal variability from a climatological point of view of the optical and microphysical properties of atmospheric particulate matter at the Universitat Politècnica de Catalunya (UPC), Barcelona, Spain, over the past 17 years, through a synergy of lidar, sun photometer, and in situ concentration measurements. Interannual temporal changes in aerosol optical and microphysical properties are evaluated through the seasonal Mann–Kendall test. Long-term trends in the optical depth of the recovered aerosol; the Ångström exponent (AE); and the concentrations of PM10, PM2.5, and PM1 reveal that emission reduction policies implemented in the past decades were effective in improving air quality, with consistent drops in PM concentrations and optical depth of aerosols. The seasonal analysis of the 17-year average vertically resolved aerosol profiles obtained from lidar observations shows that during summer the aerosol layer can be found up to an altitude of 5 km, after a sharp decay in the first kilometer. In contrast, during the other seasons, the backscatter profiles fit a pronounced exponential decay well with a well-defined scale height. Long-range transport, especially dust outbreaks from the Sahara, is likely to occur throughout the year. During winter, the dust aerosol layers are floating above the boundary layer, while during the other seasons they can penetrate the layer. The analysis also revealed that intense, short-duration pollution events during winter, associated with dust outbreaks, have become more frequent and intense since 2016. This study sheds some light on the meteorological processes and conditions that can lead to the formation of haze and helps decision makers adopt mitigation strategies to preserve large metropolitan areas in the Mediterranean basin.

China's Energy Consumption and Carbon Peak Path Under Different Scenarios

Accurately predicting energy consumption and carbon emission is important for China to make energy and carbon emission policy formulation more scientific and to achieve the goal of carbon peak before 2030 and carbon neutrality before 2060. Since energy demand is affected by numerous complex factors, it is hard to capture the dynamically developing rules of energy consumption comprehensively. Therefore, a novel two-layer decomposition-ensemble forecasting approach that was optimized by an improved particle swarm optimization algorithm based on simulation anneal and position disturbance strategy (IPSO) was proposed. Firstly, trend decomposition (TD) was utilized to break energy consumption time series down into a trend and a non-trend subseries. Then, empirical mode decomposition (EMD) was adopted to break the non-trend subseries down into several intrinsic mode functions (IMFs) and a residuum subseries. Subsequently, the aforementioned trend subseries, intrinsic mode functions, and residuum series were respectively modeled for prediction. The trend subseries was predicted using the multivariate linear regression model (MLR), which was optimized using IPSO. Both IMFs and residuum series were predicted using long short-term memory (LSTM). Finally, the final prediction of energy consumption was obtained by integrating the forecasting results of these subseries. According to China's energy consumption empirical analysis, the proposed IPSO-MLR-LSTM forecasting model based on the two-layer decomposition-ensemble approach using TD-EMD combined the advantages of TD, EMD, IPSO, and LSTM, which could comprehensively extract the developing rules of energy consumption by implementing a deeper decomposition strategy. Therefore, it is feasible and effective to apply the proposed forecasting model for energy consumption prediction. Finally, the energy consumption and carbon emissions of China under different energy consumption structure, economic growth, population, energy efficiency, and household energy consumption per capita scenarios in 2021-2035 were predicted. Then, some relevant policies and suggestions were put forward based on the forecasting results.

Financial constraints and carbon emissions: an empirical investigation

PurposeThis study aims to empirically examine the influence of financial constraints on firm carbon emissions. In addition to the role of financial constraints in firm-level carbon emissions, this study also examines this influence in the presence of governance, environmental orientation and firm-level attributes.Design/methodology/approachUsing pooled ordinary least square, this study examines the impact of financial constraints on firm-level carbon emissions using a panel of 1,536 US firm-year observations from 2008 to 2019. This study also used two-step generalized method of moment–based dynamic panel data and two-stage least square approaches to address potential endogeneity. The results are robust to endogeneity and collinearity issues.FindingsThe results suggest that financial constraints enhance the carbon emissions of the firms. The economic significance of financial constraints on carbon emissions is more pronounced for the firms that do not report environment-related expenditure investment and those that are highly leveraged. The authors further document that firms with a nondiverse gender board signify a statistically significant impact of financial constraints on carbon emissions. These results are also economically significant, as one standard deviation increase in financial constraints is associated with a 3.340% increase in carbon emissions at the firm level.Research limitations/implicationsSome implicit and explicit factors like corporate emissions policy and culture may condition the relationship of financial constraints with carbon emissions. Therefore, it would be worthwhile to consider these factors for future research. In addition, it is beneficial to identify the thresholds and/or quantiles at which financial constraints may significantly make a difference in enhancing carbon emissions.Practical implicationsThe findings offer policy implications for investment in stakeholder engagement for capital acquisitions, thereby effectively enforcing environmental innovation and leading to a reduction in carbon emissions.Originality/valueThis study integrated governance and environment-oriented variables in the model to empirically examine the role of financial constraints on the carbon emissions of the firms in the USA over and above what has already been documented in the earlier literature.

Carbon (CO2) emission and food availability convergence in the Niger Basin region: Insight from a club clustering algorithm

The study employed the Phillips and Sul log-t convergence test to analyse the degree of convergence for the Niger Basin region (NBR) countries in terms of per capita carbon emission and food availability. We found that, between the years 1986 and 2020, the Niger Basin region produced 13.5% less food per person than it did during the base period of 2004 to 2006. This study also found a strong convergence among the NBR countries on per capita food production. The result for the region’s convergence of per capita carbon emission was rejected. The non-convergence of the entire sample, and the presence of the different subgroup convergence clubs for per capita CO2 emission for the region, implies that individual factors characterise the NBR countries in terms of per capita CO2 emissions, which in turn determine an idiosyncratic course of their transition path for per capita CO2 emission policies. Considering that the transboundary river basin links nine countries, this study recommends that the NBR countries formulate and implement CO2 emission policies based on cluband country-specific policies to achieve convergence in relation to a concerted food security threat facing the region.

Changes in apparent temperature and PM2.5 around the Beijing–Tianjin megalopolis under greenhouse gas and stratospheric aerosol intervention scenarios

Abstract. Apparent temperature (AP) and ground-level aerosol pollution (PM2.5) are important factors in human health, particularly in rapidly growing urban centers in the developing world. We quantify how changes in apparent temperature – that is, a combination of 2 m air temperature, relative humidity, surface wind speed, and PM2.5 concentrations – that depend on the same meteorological factors along with future industrial emission policy may impact people in the greater Beijing region. Four Earth system model (ESM) simulations of the modest greenhouse emissions RCP4.5 (Representative Concentration Pathway), the “business-as-usual” RCP8.5, and the stratospheric aerosol intervention G4 geoengineering scenarios are downscaled using both a 10 km resolution dynamic model (Weather Research and Forecasting, WRF) and a statistical approach (Inter-Sectoral Impact Model Intercomparison Project – ISIMIP). We use multiple linear regression models to simulate changes in PM2.5 and the contributions meteorological factors make in controlling seasonal AP and PM2.5. WRF produces warmer winters and cooler summers than ISIMIP both now and in the future. These differences mean that estimates of numbers of days with extreme apparent temperatures vary systematically with downscaling method, as well as between climate models and scenarios. Air temperature changes dominate differences in apparent temperatures between future scenarios even more than they do at present because the reductions in humidity expected under solar geoengineering are overwhelmed by rising vapor pressure due to rising temperatures and the lower wind speeds expected in the region in all future scenarios. Compared with the 2010s, the PM2.5 concentration is projected to decrease by 5.4 µg m−3 in the Beijing–Tianjin province under the G4 scenario during the 2060s from the WRF downscaling but decrease by 7.6 µg m−3 using ISIMIP. The relative risk of five diseases decreases by 1.1 %–6.7 % in G4, RCP4.5, and RCP8.5 using ISIMIP but has a smaller decrease (0.7 %–5.2 %) using WRF. Temperature and humidity differences between scenarios change the relative risk of disease from PM2.5 such that G4 results in 1 %–3 % higher health risks than RCP4.5. Urban centers see larger rises in extreme apparent temperatures than rural surroundings due to differences in land surface type, and since these are also the most densely populated, health impacts will be dominated by the larger rises in apparent temperatures in these urban areas.

Comparison of oxidation absorption and reduction absorption process for sulfur recovery tail gas treatment of natural gas treatment plants in China Part Ⅰ: Technical section

BackgroundChina's newest SO2 emission policy for the natural gas industry forced natural gas treatment plant to add sulfur recovery tail gas treatment unit. In this context, the oxidation absorption process has been applied for the first time in Sichuan Basin. However, the advantages and disadvantages of this process compared with the traditional reduction absorption process have not been reported. MethodsThe two processes were compared from the technical angle in this paper. The data of one plant in Sichuan Basin was selected as the simulation condition. Significant findingsThe calculation results showed good agreement with plants data. The solution circulation amount of oxidation absorption process were 19 and 18.52 m3/h, which were just 20 %∼25 % of that for reduction absorption process. Meanwhile the acid gas returned amount was only about 14 % of reduction absorption process. However, the main process gas flow was 1.5 times of reduction absorption process. Regarding the utility consumptions, the oxidation absorption process had more advantages in electricity consumption, but it was inferior in fuel gas and circulating water consumption.

The anthropogenic cycles of palladium in China during 2001–2020

Palladium (Pd) is a strategic metal and can help reduce environmental pollution, especially from vehicle exhausts. China is the world's largest Pd consumer, but with very limited reserves. However, Pd anthropogenic cycles remain unclear in China. This study aims to uncover the dynamic Pd flows and stocks in China for the period of 2001–2020 by conducting dynamic material flow analysis. The results show that the demand for Pd had increased by 10 folds during the study period due to stricter vehicle emissions policies. Also, China mainly imported such resource from the United States, Western Europe, and East Asia, with a share of 88.8 %. However, due to insufficient end-of-life vehicle (ELV) recycling system, the total recycled Pd was only 12.3 tons although the end-of-life Pd flow increased from 3.7 tons in 2001 to 30.8 tons in 2020. This implies a great Pd recycling potential. Therefore, it is urgent to promote Pd recycling by establishing an effective Pd recycling system. In addition, other policy recommendations, such as diversifying Pd import partners, increasing Pd emergency reserves, and economic instruments, are raised by considering the Chinese realities so that the overall Pd resource efficiency can be improved.

Does Climate Change News Matter?

We explore the importance of climate change as a news topic and examine the relationship between climate change news and financial returns using a large news database that consists of more than 4 million news stories. We use multinomial inverse regression—a Bayesian approach capable of handling the multi-dimensionality of our data—to translate news into a quantifiable input. We also build a climate change dictionary from different sources to identify climate change related words. We find that climate change is a persistent topic in our news universe, which indicates that it is a relevant news topic. This relevance is supported by the non-zero contribution of climate change related trigrams (CCRTs) in the constructed news index. However, our sample does not show an increasing trend of the relative daily presence of CCRTs, which signals that the news are unlikely the source that furthers the perceived increasing awareness of climate change. Lastly, we determine the salient CCRTs present during good and bad days of the market. This result highlights the presence in the news of topics related to fuel and energy, emission, climate change, disaster, and fiscal policy.

China's Carbon Emission Policies and High-quality Economic Development: Stylized Facts and Prospect

Since 2006, China has become the worldwide largest emitter of carbon dioxide, and its annual emissions have been continuing to rise. China has always prioritized energy conservation and the reduction of pollution emissions as the long-term goal in its carbon emission reduction strategies, gradually shifting the focus from "Energy-saving Emission Reduction" to "Low-Carbon Development" and then into the current "Double Carbon" period. This paper mainly focuses on the progress of Chinese carbon policies and how it get to high-quality economic development, it aims to provide better policies to improve environmental problems for government and policymakers. Because China's carbon emissions regulations have a variety of effects on the market and country's military economy, which could encourage the R&D and innovative motivation of green technology, more trades in carbon trading market and growth in renewable-energy related industry from market aspect, while the development high-quality economic and promotion in the digital economy in economy perspective, the government should keep combining market mechanism with traditional carbon tax and seek for high-quality economic development.

Treatment of salt from hides curing stage by electrocoagulation for use in the pickling stage of the tanning industry

The raw materials for the tanning industry, namely hides and skins, are preserved (curing stage) and carried with common salt, i.e., sodium chloride (NaCl). Proceeding to conversion into leather, pickling is a key stage of the tannery process, which entails high demand of water and salt. In this work, the salt-derived brine (SdB) generated from the curing of hides was treated by iron-driven electrocoagulation (EC), aiming at its later application in the pickling stage of the tanning industry, promoting a transition to zero waste emission policy. Focusing on reducing the brine's total organic carbon (TOC), central composite rotational design and response surface methodology were adopted to study the effect of electrolysis time (6.2–14.2 min) and current density (74–431 A·m−2) on the treatment of the SdB (≅ 7.5 % wt. NaCl). The quality of the treated brines was then assessed in pickling trials and compared with virgin brine. 68–83 % removal of TOC from the SdB were achieved under electrolysis time ranging 6.2–14.2 min and current density ranging 126–252 A·m−2. Under these operating ranges the quality of the wet-blue leathers was guaranteed. Lowest power consumption (0.44 kWh·m−3) was achieved under electrolysis time of 6 min and current density of 126 A·m−2, yielding 68 % removal of TOC. Moreover, the shrinkage temperature of the hides was improved with treated brine (103.5 °C–110.5 °C) compared to virgin brine (103.0 °C). The present study provides strong evidence that contaminated salt from the curing stage can be valorised within the tanning industry through electrocoagulation treatment and then used in another production stage, instead of being landfilled.

Global carbon dioxide emissions analysis based on time series visualization

Carbon emissions and climate change is a significant challenge faced by the world today. The effects of climate change are felt globally, and many countries are making efforts to tackle this problem. The paper aims to analyze the carbon emissions data of 159 countries spanning from 1860 to 2016. By using the method of time-series visualization, the research aims to transform this data into complex networks to uncover any hidden information that might be useful in reducing emissions. By employing k-means, cluster analysis and other methods, we found that 1) While global carbon emissions continue to rise, there is a deceleration or reduction in carbon emissions in high-income countries. This deceleration or reduction may be attributed to factors such as policy measures and industrial shifts. 2) Additionally, our analysis highlights the significant increase in carbon emissions in certain economies that are not among the world’s leading nations in terms of overall economic size. This indicates the importance of these countries recognizing the relationship between carbon emissions and their economic development levels. 3) In addition, comparing the carbon emission levels of China and the United States, it can be found that even if the total amount of economic development is similar, their carbon emission patterns may be greatly different. Finally, we suggest that in the formulation of carbon emission policies, we should not only pay attention to the similar national models of economic development, but also take into account the actual development industry and stage of the country.

The Onus on Coal Consumption and the ‘Beautiful China Initiative’: Economic and Policy Implications

China’s need for rapid economic growth and its hunger for natural resources significantly challenge its economic and policy vision of sustainability, social stability and economic development. The ‘Beautiful China Initiative’ plans to put China on the path of sustainable development in line with the United Nations’ 2030 Agenda and its Sustainable Development GoaSls. The Chinese authorities are expected to reconsider traditional economic policy models to integrate environmental protection while ensuring that their economy proliferates. The shift from a traditional and heavy coal-dependent economy towards greener energy and a sustainable economic model brings additional challenges to China due to its historical dependence on coal as its energy engine. This research paper examines causality patterns between economic growth and fossil fuels energy consumption by analysing coal consumption and carbon dioxide emissions policies using Pesaran’s autoregressive distributed lag model. The research findings offer insights into China’s challenges to transition towards a more sustainable economic model, making the country’s ‘Beautiful China Initiative’ quite complex as it needs to navigate through high levels of environment-friendly economic growth whilst trying to avoid the middle-income trap.

Characterization of the sources and health risks of polycyclic aromatic hydrocarbons in PM2.5 and their relationship with black carbon: A case study in northern Taiwan

Polycyclic aromatic hydrocarbons (PAHs) and black carbon (BC) often coexist in PM2.5 because both form during the incomplete combustion of organic matter. These compounds are regarded as hazardous air pollutants with potential health effects, including respiratory and cardiovascular effects. In this study, to evaluate the health risks of PAHs and BC at an urban site in northern Taiwan, 16 priority PAHs and BC, identified by the United States Environmental Protection Agency, were analyzed and quantified in PM2.5 to determine their concentrations, their relationship with each other, and their likely sources. The results indicated that the mean concentrations of total PAHs and BC were 0.91 ng m−3 and 0.97 μg m−3, respectively, with a significant positive correlation between them, indicating the same emission sources. The results also indicated that fossil fuel combustion and traffic emissions were primary contributors to PAHs, with wood and biomass combustion playing a less prominent role. Among these 16 priority PAHs, benzo[a]pyrene, dibenz[a,h]anthracene, benzo[b]fluoranthene, and indeno[1,2,3-cd]pyrene served as major carcinogenic compounds, accounting for 89.0% of the total carcinogenic toxicity. Thus, the lifetime excess cancer risk resulting from PAH exposure was estimated as 8.03 × 10−6, indicating a potential carcinogenic risk to human health at the sampling site. Overall, this study highlights the need for future mitigation policies for traffic emissions and fossil fuel combustion for reducing the local emissions of BC and co-produced PAHs in northern Taiwan.

Forecasting China's energy consumption and carbon emission based on multiple decomposition strategy

Accurately predicting energy consumption (EC) and carbon emission is essential for China's achieving carbon peak by 2030 and carbon neutrality by 2060. In view of decomposition-ensemble (DE) strategy can effectively enhancing the prediction performance by decreasing the complexity and nonlinearity of the original EC forecasting problems. A novel three-layer DE forecasting approach is proposed, which combines the advantages of trend decomposition (TD), empirical mode decomposition (EMD) and wavelet decomposition (WD). Compared with traditional individual decomposition strategy or secondary decomposition strategy, the proposed three-layer DE forecasting method breaks EC dataset into more simpler trend subseries and non-trend subseries. Then the forecasting performance is improved by turning the original complex EC prediction task to some relatively simpler trend and non-trend subseries prediction tasks. The future carbon emission is solved out using IPCC carbon emission coefficient method and EC prediction results. Empirical analysis proves the validity of the proposed forecasting method. Finally, China's EC and carbon emission in 2021–2035 under different EC structure, economic growth, industrial structure, population, energy efficiency, household EC per capita Scenarios are predicted by the proposed three-layer DE forecasting model. And some relevant energy and carbon emission policies and suggestions are put forward.

Optimal production–inventory decision with shortage for deterioration item and effect of carbon emission policy combination with green technology

Optimal production–inventory decision with shortage for deterioration item and effect of carbon emission policy combination with green technology

Ammonia and methane emissions from small herd cattle buildings in a cold climate

Ammonia (NH3) and methane (CH4) emission measurements that reflect local production conditions are required to track progress in national emission policies and verify emission factors. The findings can also be used to better understand key factors influencing emissions. This is especially important in Norway, which has long cold winters, and small cattle herds in mechanically ventilated buildings. However, until now, NH3 and CH4 emissions from Norwegian cattle buildings have not been reported in literature. Moreover, in other cold climates, NH3 and CH4 emissions are often taken from large dairy herds in naturally ventilated buildings, with less focus on suckler cows. The objectives were to assess indoor climate, report NH3 and CH4 emissions and examine the impact of climatic factors on NH3 and CH4 emissions in three small herd dairy and suckler cow buildings over three seasons. Three of the buildings had mechanical ventilation, while one was naturally ventilated. The suckler building had higher relative humidity (RH > 90 %) and NH3 concentrations (> 25 ppm) due to lower minimum air change rate (ACH = 1.2 h−1). The suckler building also had the highest NH3 emissions (2.04 g Livestock Unit (LU)−1 h−1) followed by the mechanically ventilated dairy building (1.92 g LU−1 h−1) with the highest ACH. These two buildings had the lowest stocking densities and floor areas. In contrast, the suckler building had the lowest CH4 emissions (6.8–10.7 g LU−1 h−1). Methane emissions from the dairy building with the supply-exhaust air mixing system (16.4–19.3 g LU−1 h−1) was higher than the other dairy buildings (11.7–13.8 g LU−1 h−1). Temperature influenced NH3 emissions however, the direction of association between temperature and NH3 emissions differed among buildings. Relationship between RH and NH3 emissions was positive, but the correlation coefficient (R2 = 0.67) was strongest in the building with the highest RH.

From East to West: Lessons Learned from China and the UK's Approaches to Environmental Regulation of Multinational Enterprises

Environmental regulations play a crucial role in shaping the operations of multinational enterprises (MNEs), with different countries adopting diverse approaches to ensure sustainable development and reduce environmental degradation. This essay will provide an in-depth comparison of the environmental regulations in China and the UK, focusing on critical aspects of their regulatory frameworks, climate change and carbon emissions policies, corporate environmental reporting requirements, and enforcement and compliance systems. The central argument of this essay is that the differences in ecological regulations between China and the UK have significant implications for MNEs operating in these countries, affecting their compliance costs, operational risks, and opportunities for innovation. By comparing the regulatory landscapes in China and the UK, this essay provides valuable insights for policymakers, business leaders, and other stakeholders in understanding the complexities and implications of multinational operations in different regulatory environments.

Uncertainty of temperature rise under nationally determined contributions and carbon neutral policies

Nationally determined contributions raised by Paris Agreement aim to control the temperature rise below 2 °C or even 1.5 °C at the end of the 21st century, compared to pre-industrial levels. However, the climate response of the Nationally Determined Contributions (NDCs) remains uncertain due to unstable policies and their credibility. In this study, we calculated the uncertainty of global temperature rise caused by uncertain NDCs and carbon-neutral policies and discussed the difficulty of policy implementation. The results show that there will be 8 GtC uncertainty in emission at the end of the 21st century, responsible for the temperature rise of 0.37 °C (1.73–2.10 °C). A delayed policy in emission reduction by major emitters would result in a temperature rise of over 2 °C, while under non-delay policy, the 2 °C target will be possibly achieved. Besides, low-emission countries would introduce a 30 GtC cumulative emission uncertainty at the end of the 21st century if there are no restrictions, leading to a 0.3 °C global warming uncertainty. Developed countries need more substantial reductions in carbon intensity to achieve their climate policies while developing countries are under less pressure. The reduction of carbon intensity requires the strengthening of technical and economic methods. This study provides a reference for the realization of emission policies and temperature rise targets.

Company Valuation of PT Adaro Energy Indonesia Due to the Coal Price Volatility

This study examines the financial performance and valuation of PT Adaro Energy Indonesia, a major coal mining company in Indonesia, considering declining coal prices. The analysis reveals a downward trend in the forecast coal price index from 2023 to 2030, but the company’s coal production continues to grow due to global demand. Financial ratios indicate a strong performance compared to industry peers. Discounted cash flow analysis shows positive cash flow, assuming coal price growth ceases by 2030 due to zero carbon emission policies. The study concludes that PT Adaro Energy Indonesia is overvalued and suggests strategic measures such as diversification and exploring new business areas to mitigate risks and enhance long-term sustainability.