Emission Reduction Plan Research Articles

Boosting Electric Vehicle Adoption with PCT Policy: Insights from China's Private Transportation

Personal Carbon Trading (PCT) motivates low-carbon consumption and travel by rewarding sustainable behaviors. This study examines the impact of PCT policies on electric vehicle (EV) adoption in China's private transportation sector. Using a Stackelberg game model involving the government, EV manufacturers, and consumers, it finds that PCT policies can boost EV adoption rates by 2.29% to 14.3%. Each addition of 100,000 new EVs could reduce carbon emissions by 30,000 tons. Effective PCT policies require an independent carbon pricing system and should be implemented where infrastructure and public willingness to pay are high. Both allocation methods are conducive to the promotion of EVs: one facilitates the government in setting regional emission reduction plans, while the other ensures that the government does not incur policy-related expenditures, and different allocation methods should be chosen according to the time and circumstances in different periods of EV market development.

Emission reduction planning for carbon footprint in rural residential life cycle under the low-carbon background

In the context of global low-carbon development, reducing rural residential carbon emissions is the key to implementing emission reduction policies. In order to reduce carbon emissions from rural housing, a carbon emission classification method based on residential life cycle assessment is proposed based on the characteristics of rural housing in China. Its innovation lies in achieving precise analysis of carbon emissions from multiple stages of residential design, construction, and use. Secondly, introducing a lifecycle based emission reduction planning strategy to achieve a new pattern of low-carbon emission reduction in rural residential areas. Taking a rural residential building as a case study, in the early stage of implementing emission reduction, the mean values of the initial carbon emissions corresponding to building energy consumption, energy consumption, and resident living habits were 689, 691, and 683, with standard deviations of 81, 79, and 84. After implementing emission reduction plans, the values decreased to 686, 674, and 631, respectively, with standard deviations reduced to 28, 32, and 13. It was evident that emission reduction planning not only significantly reduced the mean carbon emissions but also substantially decreases their variability, enhancing the stability of carbon emissions. This research contributed to a deeper understanding of the carbon emissions from rural residential life cycles and provides theoretical support and data references for the formulation and implementation of more scientific and effective emission reduction planning. Simultaneously, it promoted low-carbon development in rural areas of China, achieving a harmonious coexistence of economic and social development with environmental protection and contributing to global low-carbon development.

Spatio-temporal distribution and peak prediction of energy consumption and carbon emissions of residential buildings in China

With the acceleration of urbanization and the improvement of people's living standards, the carbon emissions of residential buildings (BCE) in China have been increasing, hindering the achievement of carbon peaking and carbon neutrality goals. It has become increasingly urgent and important to analyze and grasp the dynamic trends of BCE. Given the notable regional variations in carbon emissions, it is necessary to delve into the distribution characteristics of BCE and the underlying factors influencing them. First, based on the emission factor method, the energy consumption and carbon emissions calculation models are established. Next, the main influencing factors are obtained by improving Kaya's constant equation. Meanwhile, the GA-PPC-Kmeans model is established to divide BCE into different regions. Then, the STIRPAT-Ridge model is built to predict the peak carbon emissions. Finally, a combination of static and dynamic methods is used to forecast peaks under three scenarios, which are low-carbon (LC) scenario, baseline (BA) scenario, and high-carbon (HC) scenario. The results show that five pivotal factors significantly impact BCE in China, which are energy carbon emission intensity (ECEI), energy intensity (EI), economic density (ED), residential housing level (RHL) and population size(P). Furthermore, BCE is categorized into five distinct regions: low-carbon demonstration area, energy efficiency improvement area, carbon concentration and innovation area, high-carbon optimization area, and carbon poverty development area. Under BA scenario, the peaks for BCE in these regions converge primarily around 2040 and 2045. This study provides a regional research perspective for China's residential buildings to reach the peak of carbon emissions, and serves as a reference for formulating carbon emission reduction plans in different regions.

A New Methodology for High Spatiotemporal Resolution Measurements of Air Volatile Organic Compounds: From Sampling to Data Deconvolution.

Monitoring of volatile organic compounds (VOCs) in air is crucial for understanding their atmospheric impacts and advancing their emission reduction plans. This study presents an innovative integrated methodology suitable for achieving semireal-time high spatiotemporal resolution three-dimensional measurements of VOCs from ground to hundreds of meters above ground. The methodology integrates an active AirCore sampler, custom-designed for deployment from unmanned aerial vehicles (UAV), a proton-transfer-reaction mass spectrometry (PTR-MS) for sample analysis, and a data deconvolution algorithm for improved time resolution for measurements of multiple VOCs in air. The application of the deconvolution technique significantly improves the signal strength of data from PTR-MS analysis of AirCore samples and enhances their temporal resolution by 4 to 8 times to 4-11 s. A case study demonstrates that the methodology can achieve sample collection and analysis of VOCs within 45 min, resulting in >120-360 spatially resolved data points for each VOC measured and achieving a horizontal resolution of 20-55 m at a UAV flight speed of 5 m/s and a vertical resolution of 5 m. This methodology presents new possibilities for acquiring 3-dimensional spatial distributions of VOC concentrations, effectively tackling the longstanding challenge of characterizing three-dimensional VOC distributions in the lowest portion of the atmospheric boundary layer.

Forecasting urban passenger transportation emissions: a green and new energy approach

ABSTRACT Passenger transportation significantly contributes to urban carbon dioxide emission. Decreasing these emissions is essential to achieving low-carbon development. This research focused on Xi’an City to enhance previous research works by considering factors such as road greening, online ride-hailing, and use of vehicles with new energy sources. Using system dynamics method, a carbon dioxide emission prediction model was developed for urban passenger transportation in Xi’an. The developed model estimated total emissions from 2012 to 2021 and projected carbon dioxide emission reduction plans through six different scenarios for the time period of 2023 to 2032. The analysis identified private cars as the main contributors to carbon emission in urban passenger transportation. Single scenario simulations indicated that passenger traffic in Xi’an would not achieve carbon emission peak by 2030, but multi-scenario simulations showed it would. Specific recommendations for carbon emission reduction in urban passenger transportation were provided, focusing on travel patterns, energy sources, and promotion of green initiatives.

Carbon emission efficiency of China’s construction industry based on super-efficiency SBM and Tobit model

Global warming is one of the key issues attracting international concern. The carbon dioxide emission produced by energy combustion is the main cause of the greenhouse effect, and reducing carbon emissions is considered the most effective way to deal with the greenhouse effect. The extensive production mode characterized by high energy consumption, high emission, and low efficiency in China’s construction industry intensifies the contradiction between economic development and resources and the environment, and the growth under this mode is at the expense of consuming a lot of resources and energy. The improvement of carbon emission efficiency is an effective means of achieving the goal of economic growth and carbon emission reduction simultaneously, making it necessary to accurately measure the carbon emission efficiency of the construction industry in each province, determine the influencing factors, and formulate reasonable emission reduction policies for this industry. In this study, an input-output index system of carbon emission efficiency of China’s construction industry was constructed, the carbon emission efficiency of the construction industry in each province was evaluated using the super-efficiency SBM model, and the factors affecting the carbon emission efficiency of this industry were analyzed via the Tobit model. The results showed that the average value of carbon emission efficiency of the construction industry generally showed a rising trend in a fluctuating way during the study period. From 2014 to 2022, the average carbon emission efficiency of the national construction industry presented an upward trend, from 1.122 in 2014 to 1.148 in 2022; the regional economic level (p= 0.020 < 0.05) and human capital level (p= 0.000 < 0.01) exerted obvious promoting effects on the carbon emission efficiency of China’s construction industry, while the urbanization development (p= 0.049 < 0.05) generated evident negative effects on carbon emission efficiency of this industry. The research results have important reference values for making cross-provincial emission reduction plans for the construction industry, promoting its carbon emission efficiency, and driving the research and development of green building materials and clean energy.

Trend Changes and the Driving Forces of Environmental Indicators in Countries Worldwide: A Structural Change Analysis of Variations in CO2 Emissions and Eco-Efficiency

Many authors state that climate change is driven by increasing CO2 emissions worldwide. An understanding of the major driving forces affecting emissions over time in both developed and developing countries is important. Thus, in this study, structural break analysis is used to identify when the trends of environmental indicators—CO2 emissions and environmental efficiency (EE)—across countries worldwide change. Our findings revealed notable structural breaks occurring in countries in 1994, coinciding with ballooning fossil energy prices. Regarding CO2, 55 of 143 countries experienced a structural break. Furthermore, another wave of structural breaks emerged in 2014, corresponding to the implementation of CO2 emission reduction plans by certain nations. For CO2, 64 of 143 countries experienced a structural break. Upon detecting breakpoints and their trends, we utilized LMDI factor decomposition analysis to discern their driving factors, thereby elucidating the underlying dynamics. In Latin America and the Caribbean, most breakpoints were undesirable shifts, but recently, desirable shifts have increased in North America, Oceania, and Europe, which include many countries with high economic levels, improving energy-related factors. Sub-Saharan Africa can also be said to have undergone an undesirable shift regarding energy-related factors. This study clarifies the precise influences on the trend of CO2 emissions at the global level by identifying the point in time when there is a significant statistical, rather than a subjective, breakpoint.

Is South Korea's 2050 Carbon-Neutral scenario sufficient for meeting greenhouse gas emissions reduction goal?

In line with Global Climate Change Alliance initiated in 2007 by the European Commission, the South Korean government announced the “2050 Carbon-Neutral Strategy” in October 2020. The 2050 Carbon-Neutral Scenario was announced in October 2021, with the aim of reducing the country's greenhouse gas (GHG) emissions by 40 % by 2030 compared to those in 2018. The primary objective of this study is to conduct a scenario-based comparative analysis focusing on the forecast of greenhouse gas emissions and the potential for reduction within the building sector. The methodology employed in this study utilizes the greenhouse gas emission calculation methods outlined in the IPCC Guidelines of 1996 and 2006. Based on the national building energy and statistics database for the years 2015 to 2019, the study analyzes building types, building energy intensity, and floor areas to calculate emissions and energy consumption within the sector. The results indicate that the emissions will increase continuously from 2020 (156.9 million tons of CO2 equivalent) to 2050 (217.8 million tons of CO2 equivalent). We have considered the four scenarios outlined in the ‘2050 Carbon Neutrality Scenario’ as the most effective strategies for reducing greenhouse gas emissions in the building sector. These include: (1) Mandatory implementation of Zero-Energy Buildings (ZEB) for new buildings by 2050, (2) 100 % execution of green remodeling for existing buildings, (3) Promotion of high-efficiency devices to achieve a 25–30 % improvement in energy consumption efficiency compared to 2018 and an enhancement of device energy use per unit, and (4) Expansion of clean heat utilization such as fuel cells and waste heat utilization in district heating. Thus, the possibility of South Korea achieving the 2050 carbon-neutrality target in the building sector is low. Therefore, it is important to develop effective emissions reduction policies and plans for the building sector.

Towards low-carbon steel: System dynamics simulation of policies impact on green hydrogen steelmaking in China and the European Union

Green hydrogen (GH) has been included in the steel emission reduction plans of many countries. This study evaluates the status quo of GH and steel industry and the related subsidy and regulatory policies in two major steelmaking countries/regions: China and the European Union. A system dynamics model coupling GH and steel industry is established to conduct simulation analysis of the low-carbon transition path of GH replacing fossil fuels in these two countries/regions' steel industry under several carbon emission reduction scenarios. Results verify the feasibility of using GH in the steelmaking and GH's contribution to the steel industry's carbon emission reduction. And this study assesses the policy impacts on the development of green hydrogen steel and gives specific policy implications on the timing and measures. The methodology and policy tools in this study also provide the reference for other countries who are still in wait-and-see attitude towards the development of GH steel.

Emissions Reduction Target Plan and Export Product Quality: Evidence from China’s 11th Five-Year Plan

Determining how environmental policy affects export competitiveness is essential for achieving win–win objectives in environmental governance and trade development. We examine whether and how China’s emissions reduction policy declines the firm’s export product quality during the 11th five-year plan via the difference-in-difference-in-difference method. The main findings of this paper are as follows: (i) Compared with less polluting industries, the export production quality declines 5.74% and 3.31%, respectively, as the pollution reduction targets of SO2 and chemical oxygen demand (COD) are set 1 unit higher in more polluting industries. (ii) The negative effect is greater in Western regions as well as state-owned firms. (iii) Local officials facing promotion pressure are more incentivized to raise emissions reduction goals, as well as greater increasing emissions abatement costs, thus leading to greater declines in export quality. However, the innovation compensation effect still remains. (iv) The negative effects can be mitigated through product switching that contributes to resource allocation within firms towards their core products, or executing the first-mover advantage in response to the emissions reduction plan.

Simulation of emission reduction path under the path of differentiated energy transformation in China's industrial cities: a case study of Shanghai.

The formulation of long-term step-by-step emission reduction plan is an important step for effective scientific emission reduction. This paper takes Shanghai as the research object, constructs PSO-LSTM model on the basis of STIRPAT model, and further constructs three dynamic policy scenarios combined with China's actual situation and makes short-, medium-, and long-term multivariate predictions for them. The study finds that only the improvement of energy consumption structure has a promotion effect on carbon emission reduction, and urbanization, industrial structure, technology level, population, and economic level all have an increasing effect, and secondly, the carbon emission reduction path of Shanghai basically achieves the core objective of steady decrease under the three scenarios. Secondly, under the three scenarios, Shanghai's carbon emission reduction path basically achieves the core objective of steady decline, but the decline in the GU scenario is more significant. It is recommended that Shanghai further adjusts its industrial structure, optimizes its energy consumption structure, promotes technological innovation and progress, and promotes the development of the circular economy model.

An integrated zero-sum game and data envelopment analysis model for efficiency analysis and regional carbon emission allocation

As the global economic environment changes, the concept of green and sustainable development has become the international community’s consensus. As a participant in the worldwide emission reduction plan, China is also under great pressure to reduce carbon emissions. As an example, this study constructs an optimal scheme for regional carbon emission allowance allocation in Hunan Province, China. We first forecast the total carbon emissions in 2030 for each city, state, and major industry in Hunan Province through a scenario and then innovatively use the mass function allocation theory in marketing to sort out the logical ideas of the optimization model. More importantly, we combine the zero-sum game theory to build the zero-sum game-data envelopment analysis model to continuously reallocate the carbon emission allowances of each city and state and major industries in Hunan Province until the optimal allocation scheme is reached. From the perspective of each city and state, the initial carbon emission efficiency level of fourteen cities in Hunan is high, but there are still some differences. From the perspective of industries, the initial efficiency of carbon emission of six major industries in Hunan is lower, and the difference in efficiency values is evident.

Analysis of carbon emission equity degrees based on regional heterogeneity in China.

Carbon emission reduction is an environmental and development issue that needs to consider various factors, such as the economy and people's livelihood. Supporting the achievement of emission reduction targets has become an important planning goal for provincial governments; however, there are differences in provincial industrial structure and economic development, which cannot be ignored in goal setting. This study measures the equity degrees of carbon emissions based on economic output by using provincial panel data from 2000 to 2019 and evaluates the spatial distribution characteristics of the carbon emission inequity index (CII). Then, analysis of the influencing factors to CII is employed by spatial econometric methods. Furthermore, multi-index panel data factor analysis and cluster analysis are used to divide regions. The empirical results show that nearly half of the provinces have the problem of carbon emissions inequity with significant spatial correlation. For local development, economic growth and population expansion will significantly improve the equity degrees of carbon emissions. In contrast, the growth of urbanization level, the percentage of secondary industry, and increased energy intensity will significantly improve the equity degrees of carbon emissions in neighboring regions. Policymakers should consider the factors influencing CII and formulate emission reduction plans according to regional characteristics.

Managing Carbon Efficiency and Carbon Equity

China has committed to achieving carbon neutrality by 2060, primarily focusing on reducing carbon intensity. Understanding the regional embodied carbon emissions is critical for managing carbon efficiency and carbon equity in this process. Using the input-output and SBM-DEA models, this article first calculates China's regional embodied carbon emissions. The results reveal substantial carbon transfers between China's different regions. Therefore, designing reduction pathways solely based on production-based carbon emissions raises fairness concerns. To address this, this article employs the SBM-DEA model to calculate the regional reduction potential and marginal abatement costs using the regional embodied carbon emissions and optimize China's pathways of regional carbon emission reduction. The new pathways consider consumption-based reduction potential, marginal abatement cost, and reduction equity, and are all in line with China's carbon reduction target. These schemes are of practical significance for China to develop a more efficient and equitable regional emission reduction plan.

Climate targets by major steel companies: An assessment of collective ambition and planned emission reduction measures

This article systematically assesses the status, robustness, and potential impact of greenhouse gas emission reduction targets set by the largest steel producer companies as of mid-2022. The assessment covers the 60 largest steel companies by volume, accounting for more than 60 % of global steel production. Data on company-level greenhouse gas emission reduction targets and emission reduction measures were collected from publicly available documents.We found that only 30 companies have their own greenhouse gas emission reduction targets of varying timeframes between 2025 and 2060. Even when excluding the 15 Chinese state-owned companies that are under the national 2060 net zero target, 15 companies had no emission reduction targets. Twenty-one companies had long-term targets (2040 or after), of which 18 were net zero emission targets; all but one also had interim targets. If all climate targets identified among the 60 companies are achieved, annual CO2 emissions for the 60 companies could be reduced by up to 12 % by 2030 and up to 39 % by 2050 in comparison to a baseline scenario. Assuming a gradual increase in global crude steel demand from 1.9 Gt in 2019 to 2.5 Gt in 2050 and assuming similar trends for the rest of the global iron and steel sector as observed for the 60 companies, we estimate that the current ambition of the global iron and steel sector on emission reductions would lead to a reduction of 38 % to 53 % by 2050 from 2019 levels (3.4 GtCO2 to 1.6–2.1 GtCO2), or compared to a 32 % to 43 % reduction in a baseline scenario in 2050.Steel companies are also lagging in setting clear emission reduction plans to achieve their targets. We found that 14 out of the 30 steel producers with targets did not provide an emission reduction plan. The most popular measures amongst the 16 companies that identified at least one measure to achieve their target in their emission reduction plans were hydrogen-based DRI (n = 14), enhanced use of renewable electricity (n = 13) and Carbon Capture Utilisation and Storage (CCU/S) for blast furnaces (n = 9). While it is encouraging that the steel companies have started acting toward long-term deep decarbonisation, our findings suggest that there is a long way ahead and the action needs to be accelerated considerably.

Is ICT innovation a recipe for carbon efficiency gains? Evidence from patent retrieval

In recent years, information and communication technology (ICT) innovation has been an essential part of China's strategy for achieving low carbon and improving carbon emission efficiency (CEE). This research innovatively calculates ICT innovation indexes for 30 Chinese regions and 12 ICT innovation indexes from 2007 to 2019 across 30 regions in China. Based on this, this study investigates how ICT innovation affects CEE from a digital technology innovation perspective by applying the system-generalized method of moments (SYS-GMM) dynamic technique. This study also explores the mediating effect of industrial structure upgrading and R&D intensity and the threshold effect of human capital. The results show that ICT innovation facilitates CEE improvement, with High-speed network and Large-capacity and high-speed storage technologies being the main contributors to green technology. ICT innovation indirectly improves the CEE level by enhancing the industrial structure and R&D intensity. Additionally, the impact of ICT innovation on CEE tends to grow when human capital quality rises. The results of this paper will benefit policymakers in developing emission reduction plans from an ICT innovation perspective.

An integrated perspective on the spatial–temporal characteristics of China’s manufacturing carbon emissions at the regional and industry levels

Given that manufacturing industry is the second-largest source of carbon emissions in China, effective carbon emission reduction plans require a comprehensive examination of the spatial–temporal characteristics (STC) of manufacturing carbon emissions (MCE) from both regional and industrial perspectives. However, most studies on the STC of MCE focus solely on regional perspectives, overlooking the importance of integrating both regional and industrial perspectives to fully understand the STC of China’s MCE. Moreover, there is limited research on the spatial disparities in China’s MCE. Building on a detailed carbon emissions inventory of 27 manufacturing industries across 30 provinces in China from 2001 to 2020, this study employed descriptive statistics, natural breakpoint classification, spatial–temporal transition, and the Dagum Gini ratio with its cluster decomposition method to analyze the STC of MCE from regional and industrial perspectives. The assessment of STC of MCE includes an examination of both spatial–temporal changes and disparities. Results show that the MCE of the three regions in China follow the order of east > central > west, with most of the super-heavy-duty MCE and heavy-duty MCE provinces located in the eastern and central regions. China’s three-tier manufacturing industries exhibit a pattern of “low-end high-end industries with small carbon emissions, while mid-end industries have large carbon emissions”. The regional differences show that the gap in the high-end MCE among the three regions is gradually narrowing, while the gap between mid-end MCE in the east and those in the central and western regions is widening. The overall disparities of MCE exhibited a continuous widening trend. In terms of sources, inter-regional disparities had the highest contribution rate, followed by intra-regional disparities, and super-dense disparities had the least contribution. Based on the research findings, this paper proposes targeted policy suggestions for carbon emission reduction in the manufacturing industry.

The driving force of carbon emissions reduction in China: Does green finance work

Under the goal of “carbon peaking” and “carbon neutrality” in China, it is significant to explore whether green finance contributes to carbon emission reduction. Therefore, based on the panel data of 30 provinces in China from 2005 to 2020, this paper empirically examines the impact of green finance on carbon emissions and its mechanism using the FE model, GMM model, DID, and the mediating effect model. Results find that green finance can significantly promote carbon emissions reduction, and this promotion remains still after robustness tests. The heterogeneity analysis shows that green finance's carbon emission reduction effect is more significant in developed and western regions. Moreover, the results of policy intervention effects confirm that green finance reform and innovation pilot zones (GFRIs) for carbon emission reduction are more pronounced than in other regions. Finally, the mediating effects reveal that industrial structure and green innovation are the core transmission channels through which green finance influences carbon emission reduction. These findings offer meaningful implications for formulating reasonable carbon emission reduction plans and determining the future development direction of green finance.

What determines climate ambition? Analysing NDC enhancement with a mixed-method design

The 2015 Paris Agreement relies on Nationally Determined Contributions (NDCs) to outline each country’s policies and plans for reducing greenhouse gas (GHG) emissions. To strengthen global climate action and achieve the Agreement’s temperature goal, it is crucial to enhance the ambition level of NDCs every 5 years. While previous studies have explored the ambition of initial NDCs, limited research has delved into the factors driving the enhancement or lack thereof in NDCs’ emission reduction plans. This study employs a mixed-method design to investigate the determinants of NDC enhancement. First, we analyse the updated or revised NDCs of 111 countries using quantitative methods. Second, we conduct qualitative case studies focusing on Brazil and South Africa. Our findings reveal that countries that engaged in stakeholder consultations with civil society, business, and labour groups prior to developing their updated or revised NDCs were more likely to enhance their greenhouse gas reduction targets. These results are further supported by the case studies. South Africa conducted comprehensive consultations and submitted an enhanced GHG target, while Brazil, which did not arrange open consultations, did not improve its target. This study underscores the significance of comprehensive and transparent stakeholder engagement processes, highlighting their potential to drive enhanced NDCs. By involving diverse stakeholders, including civil society, business, and labour groups, countries can foster greater ambition and effectiveness in their climate action, ultimately contributing to the global effort to combat climate change.

Innovative Thinking Drives Emissions Mitigation

_ The oil and gas industry walks a fine line between providing the energy supplies demanded by a growing global population and addressing the challenge of reducing greenhouse gas emissions, mainly methane. While the industry has made gains in many areas, critics have flagged concerns that the current pace of emissions mitigation needs to be faster and called for acceleration of the process. According to the International Energy Agency (IEA), methane is responsible for approximately 30% of the rise in global temperatures since the Industrial Revolution, making it the second-largest contributor to climate change behind carbon dioxide. Methane is released during oil and gas production processes, and the industry accounts for about a quarter of the global anthropogenic methane emitted into the atmosphere. With increasing recognition of their negative environmental impacts, these emissions are now under greater scrutiny by governments worldwide as they strive toward cleaner power generation sources. As a result, energy companies continue to find ways to effectively manage and reduce their methane emissions to remain compliant with new regulations. According to nonprofit organizations Clean Air Task Force and Ceres, industry efforts are delivering results. An analysis assessed the production-based emissions of more than 300 US producers, finding that the methane emissions intensity of natural gas production and the greenhouse-gas emissions intensity of oil and gas production vary dramatically across companies. The intensity of methane and greenhouse-gas emissions from the oil and gas sector declined 28% and 30%, respectively, between 2019 and 2021 among the largest producers in the country, the report said. However, according to the IEA, overall progress could have been faster. In a special report, the agency looked at the investment required to deliver a sharp reduction in emissions by 2030, finding that if the industry spent $75 billion—about 2% of its 2022 net income—to curb methane emissions through 2030, it would keep the sector on a pathway to achieve net-zero emissions by 2050. The agency also reported that methane abatement is one of the most cost-effective measures to cut emissions and would generate about $45 billion from the sale of captured methane (Fig. 1). Leak Detection Comparisons Promising advances in technology have improved methane measurement and leak detection. Traditionally a laborious and error-prone task, leak-detection technologies are undergoing a revolution. Drone technology, satellite surveillance, and infrared cameras are emerging as powerful tools in the industry’s arsenal to pinpoint leaks and fix them swiftly. Companies like Shell and BP have committed to routine checks via drones and cameras to spot leaks more accurately and promptly. By employing these technologies, the industry can reduce its environmental footprint and save valuable natural resources, transforming “waste” methane into a valuable energy source. ExxonMobil deployed new technology to expand measurement and mitigation of methane emissions and reduced methane emissions intensity from operated assets by more than 40% as of year-end 2021 vs. 2016 levels in line with greenhouse gas emission reduction plans. In its 2023 Advancing Climate Solutions Progress Report, the supermajor also said that it increased the amount it intends to invest through 2027 on lower-emission initiatives to approximately $17 billion, up by nearly 15%.