Abstract The Climate Change Advisory Opinion (AO) by the International Court of Justice (ICJ) demonstrates the growing prominence of general principles of law in international law. The Climate Change AO was handed down at the end of the International Law Commission's project on general principles of law with the adoption of its Draft Conclusions. In the Climate Change AO, the ICJ accords general principles of law particular importance in environmental protection. This article documents how States identified general principles of law as the bedrock of the international climate change regime, and how the ICJ employed a systematic approach to ‘thicken’ climate change law, both in terms of normative content, obligations and consequences of breach. It then examines the general principles of law affirmed by the ICJ, in particular, the principles of common but differentiated responsibilities and intergenerational equity, both extracted from the broader general principle of equity. These principles guide the interpretation of ‘how far’ or ‘how much’, operating as balancing tools in relation to other obligations. The broader significance of this development lies in the ICJ's growing recognition of general principles of law as a means of supporting and structuring its legal reasoning. The article further argues that the normative development of these principles has been reinforced by reports of the Intergovernmental Panel on Climate Change (IPCC), and that Article 38(1)(c) of the ICJ Statute provides a broader gateway for taking account of normative contributions by actors such as the IPCC. The identification of customary law and peremptory norms ( jus cogens ) is more narrowly defined than general principles of law. The article concludes by examining the IPCC's role in underpinning the normative character of certain general principles of law, building on the interaction of law and science, and suggests that strengthening these principles may facilitate their more robust incorporation into future treaty‐design mechanisms.

Fluorinated greenhouse gases (F-GHGs) from the semiconductor industry represent a rapidly growing climate driver, yet localized accounting and abatement analyses remain scarce. To improve estimation accuracy and assess mitigation potential, we developed an improved accounting model by incorporating previously neglected sources, experimentally measuring destruction and removal efficiencies (DREs) for major process gases, and establishing gas usage coefficients by wafer size and process type. Applied to Shanghai's semiconductor sector in 2022, the model estimated 3.35 Mt CO2e emissions, dominated by process gases (47.93%) and electricity consumption (43.88%). Emissions based on measured DREs were 7.4-23.0 times higher than those from the Intergovernmental Panel on Climate Change (IPCC) 2019 default DREs, revealing overestimation in defaults. The share of indirect emissions increased markedly with wafer size, from 20.68% to 55.46%, driven by higher power intensity in advanced nodes and greater abatement efficiency. Plasma-based abatement achieved the highest DREs, yet their NOx byproducts warrant further attention. Without additional controls, emissions could increase to 4.20 Mt CO2e by 2035, whereas defined mitigation scenarios could achieve 37.49-77.69% reductions, primarily through enhanced gas abatement and low-carbon electricity adoption. The study emphasizes localized methodology and scenario analysis as essential for developing effective climate strategies in emerging industries.

The study conducted a detailed carbon footprint assessment of the Gandhi Krishi Vignana Kendra (GKVK) campus, University of Agricultural Sciences, Bangalore, using internationally recognised standards such as the Intergovernmental Panel on Climate Change (IPCC) Guidelines and the greenhouse gas (GHG) Protocol. As institutions are increasingly recognised for their contribution to GHG emissions through energy use, transport, waste and food services, this research quantified emissions across scope 1 (direct), scope 2 (indirect from purchased electricity) and scope 3 (other indirect emissions). Activity data were collected from institutional records, surveys and field assessments, while emission factors were sourced from IPCC (6th assessment report) AR6, the united nations framework convention on climate change (UNFCCC) GHG calculator v2.6 and Central Electricity Authority (CEA) guidelines. The total GHG emissions from the GKVK campus were estimated at 7606.545 tonnes CO₂e/yr, with scope 1 contributing 42.08 %, scope 2 contributing 20.46 % and scope 3 contributing 37.46 %. Major sources included liquefied petroleum gas (LPG) usage (1334884 kg CO₂e), grid electricity (1556180 kg CO₂e), food waste (1622855 kg CO₂e), refrigerant leakage (982430 kg CO₂e) and student commuting (879466 kg CO₂e). While the study provides a comprehensive institutional GHG baseline, it is limited to one academic year and excludes embodied emissions from infrastructure. The findings establish a replicable framework for Indian educational institutions to measure, manage and mitigate emissions. Future research should extend this model to multi-campus assessments and long-term carbon management planning, strengthening the roadmap toward carbon-neutral academic ecosystems and supporting India’s broader net-zero commitments.

In order to analyze the characteristics of fossil source CO2 emissions in the AAO process of municipal wastewater treatment, in-situ monitoring in a typical AAO process of a municipal wastewater treatment plant in North China was conducted in this work. The CO2 emission flux of each main process unit (selection tank, anaerobic tank, anoxic tank, aerobic tank, sludge return gallery, and secondary sedimentation tank) from September 2023 to August 2024 was obtained, and the 24 h day and night continuous change pattern and the emission contribution of fossil source CO2 was analyzed. Through 12 months of continuous monitoring, the direct CO2 emission fluxes of major process units such as selection tank, anaerobic tank, anoxic tank, aerobic tank, sludge return gallery, and secondary sedimentation tank were (30.20±2.85), (43.50±5.81), (44.41±4.69), (2 736.82±213.26), (82.68±7.21), and (11.59±1.15) g·(m2·d)-1, respectively. In summer, the AAO process showed "double peaks" of direct CO2 emission flux in 24 h, with peak periods at 06:00-09:00 [average 12 443.14 μg·(m2·s)-1] and 21:00-24:00 [average 12 395.38 μg·(m2·s)-1], both of which were 20% higher than the average value of direct CO2 emission flux in summer for 24 h. In winter, the AAO process showed a "single peak" of direct CO2 emission flux in 24 h, with peak periods at 09:00-12:00 [average 16 705.90 μg·(m2·s)-1], which was 21% higher than the average value of direct CO2 emission flux in winter for 24 h. The direct CO2 emission flux in winter [24 h average 13 811.81 μg·(m2·s)-1, CV=9.0%] was higher than that in summer [24 h average 10 388.41 μg·(m2·s)-1, CV=14.4%] but with smaller fluctuations. The monthly direct CO2 emission monitoring results showed that the average direct CO2 emission flux of the AAO process for 12 months was (1 094.86±80.97) g·(m2·d)-1 with large-size monthly fluctuations (CV=35.6%); the peak occurred in March 2024 [1 737.74 g·(m2·d)-1], which was 59% higher than the average value of 12 months. The direct CO2 emission intensity of the AAO process varied significantly with the seasons. The average direct CO2 emission intensities in spring, winter, summer, and autumn were (3 546.76±616.24), (3 089.66±363.98), (2 738.55±120.38), and (2 267.45±229.33) kg·d-1, respectively. The direct CO2 emissions of different process units were obviously different, and the aerobic tank was the main source of CO2 emissions in the AAO process, with an average annual emission flux, average annual daily emission intensity, and average annual emission factor (measured in CO2/COD) of (2 736.82±213.26) g·(m2·d)-1, (2 859.14±214.32) kg·d-1, and (3.83±0.75) kg·kg-1, respectively, which were significantly (P < 0.001) higher than those of other treatment units. The direct CO2 emission flux was significantly positively correlated with oxidation-reduction potential (ORP; P < 0.000 1), DO (P < 0.05), NO3--N (P < 0.05), and NO2--N (P < 0.05) and was significantly negatively correlated with TP (P < 0.01), NH4+-N (P < 0.01), and pH (P < 0.05). The direct CO2 emissions from fossil sources in the municipal wastewater treatment process were estimated based on the measured values of direct CO2 emissions, and the overall fossil source direct CO2 emission range of the AAO process was (38.05±5.31)-(148.41±20.72) g·m-3 (converted into fossil source CO2 emissions per m3 of wastewater treated). Direct CO2 emissions from fossil sources accounted for approximately 28.7%-67.1% of the greenhouse gas emissions of the whole plant calculated by the Intergovernmental Panel on Climate Change (IPCC) method. The direct CO2 emissions from fossil sources in municipal wastewater treatment plants are underestimated by the IPCC carbon emission accounting system, and it is recommended to include direct CO2 emissions from fossil sources in the carbon emission accounting system of wastewater treatment plants.

ABSTRACT Under the Paris Agreement, Parties committed to curbing greenhouse gas (GHG) emissions to limit global warming. The Enhanced Transparency Framework (ETF) has introduced new reporting standards for all Parties, including Biennial Transparency Reports (BTRs), starting in December 2024. These reports require the submission of national GHG inventories (NGHGIs) following the Intergovernmental Panel on Climate Change (IPCC) guidelines. Reporting in the Land Use, Land-Use Change and Forestry (LULUCF) sector is challenging due to complex land dynamics and data requirements. Earth Observation (EO) has emerged as a crucial tool to improve the accessibility, accuracy, and consistency of land representation in NGHGIs. Yet, its current use in official submissions has not been systematically evaluated. The first BTRs provide a timely opportunity to analyse the global status of EO integration by all Parties. This study presents the first global assessment of EO’s application in LULUCF reporting submissions, including the first BTRs, by cataloguing countries that use EO for land representation, assessing the types of EO data, products, and tools currently employed in LULUCF reporting, and analysing their adherence to IPCC-compliant requirements. Despite progress in EO, LULUCF reporting remains heterogeneous, with only 75 of 195 Parties explicitly reporting the use of EO. Global EO products (i.e. datasets derived from satellite remote sensing, such as land cover maps) are particularly underused, featuring in only 14% of the assessed submissions. The results highlight the inadequacy and poor usability of existing products, emphasizing the need for global solutions and harmonized, scalable methodological frameworks. The study identifies key gaps in current EO-based reporting methodologies and discusses opportunities to improve reporting, focusing on compliance with ETF and IPCC requirements. Greater collaboration between EO communities and inventory compilers is recommended to align targets, improve the compliance of EO datasets, and contribute to the achievement of the Paris Agreement's mitigation goals.

This study presents a methodological refinement of calculating greenhouse gas emissions from agricultural land management in the Czech Republic according to IPCC requirements. The authors utilize the SoilClim model providing input data in a 500 × 500 m grid for finer division of the Czech territory into climate zones according to IPCC. The research analyses the application of nitrogen fertilizers at the district level for the period 2015–2023 instead of national data. Results show significant dynamics of climate zones, where the extent of “dry” areas fluctuated in individual years from 40% to more than 80%. Implementation of the refined model led to a reduction in reported nitrous oxide emissions by an average of more than 9% in the reported period 1990–2023, representing savings of 20 Mt CO2 equivalent. The model-based use of district-level data on fertilizer application led to an additional reduction of 1.2 Mt CO₂ equivalent for the years 2015–2023. The study demonstrates that methodological refinement and the use of region-specific activity data can significantly influence the national greenhouse gas inventory. It highlights the need for continuous updates of calculation methods and activity data to improve the quality of national reporting and provides essential insights for a more effective emission reduction strategy in the agricultural sector of the Czech Republic.

Abstract Integrated assessment models produce large ensembles of socioeconomic scenarios that are used profusely in climate change research. The Intergovernmental Panel on Climate Change (IPCC), non-governmental organizations or national climate committees often rely on ensemble statistics to identify mitigation strategies and set climate targets. A limitation of such evidence is the opportunistic nature of scenario ensembles: they are an unstructured, serendipitous collection of evidence. Drawing on concepts from physical climate science and ensemble analysis, we present an approach for the flexible, multidimensional weighting of emission scenario data that accounts for relevance, quality and diversity. Our illustrative application to the latest IPCC scenario database demonstrates a reduction in dominance of highly represented models and studies, and sees net-zero emission milestones differ to those originally reported. Our framework formalizes decisions otherwise made in an ad hoc manner, providing a tool contributing to the broader challenge of assessing ensembles of opportunity.

Recently, international judicial forums have issued landmark advisory opinions on the subject of the ocean–climate nexus. The opinions are based on the recognition of the interconnection between the United Nations Framework Convention on Climate Change (UNFCCC) and the United Nations Convention on the Law of the Sea (UNCLOS). All judicial forums stated that Small Island Developing States (SIDS) are a distinct focus due to their disproportionate vulnerability to climate change, as reported by the Intergovernmental Panel on Climate Change (IPCC). According to the opinions, SIDS could become uninhabitable in the coming years, necessitating urgent global climate action. The United Nations (UN) has acknowledged the unique challenges of SIDS through various resolutions, which emphasise the need for climate justice and adherence to the 1.5 C climate target. Sustainable Development Goal 14 (SDG 14) brought attention to the direct impacts of climate change on oceans and the issues faced by SIDS. This paper reviews the historical and legal developments necessary for the sustainable development of SIDS, emphasising the nexus between climate change, ocean governance, and human rights. It highlights the potential for further advocacy and the interconnected nature of SDG 14 with judicial opinions.

Measuring the resilience of historic areas is challenging due to their heterogeneity in scale, heritage type, multi-hazard exposure, and socio-cultural context, creating the need for a flexible framework aligned with the latest Intergovernmental Panel on Climate Change (IPCC) approaches. This study introduces the SHELTER framework, which takes the historic area as its primary unit of analysis while enabling a cross-scalar assessment, from artefact/building scale to urban and transregional contexts. Developed through a co-creation strategy and an extensive literature review, the framework integrates indicators for multidimensional, cross-scale, and systemic resilience assessment and monitoring. The indicators span hazards such as heatwaves, earthquakes, floods, subsidence, and wildfires and capture exposure and vulnerability, the latter being understood as the sensitivity and coping, adaptive, and transformative capacities of communities. Refinement using the RACER methodology yielded a concise yet comprehensive shortlist of indicators, providing both general overviews and specific insights tailored to historic environments. The framework’s efficacy was tested across five case studies, demonstrating adaptability and suitability in diverse historic areas. Overall, SHELTER moves beyond a traditional focus on physical vulnerability and risk management, offering a replicable, holistic set of resilience indicators that supports consistent assessment and monitoring while respecting the singularities of historic settings.

Most models for international environmental governance acknowledge that the participation of non-state actors is critical; however, this participation is limited to a pre-political level in which scientific communities have a predominant role and indigenous ontologies are often marginalized. This article contextualizes these discussions by examining how ontological differences are incorporated or excluded in the international environmental governance of the Amazon rainforest. By exploring the interactions between Indigenous peoples and scientific communities, it examines the prospects of institutionalizing these interactions within the Amazonian Cooperation Treaty Organization (ACTO). The article relies on research during the years 2021-2024 involving semi-structured interviews and the comparative analysis of the the Science Panel for the Amazon (SPA) procedures and reports with the main international scientific platforms dedicated to the environment: the Intergovernmental Panel on Climate Change (IPCC) and the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES). The article argues that the inclusion of Indigenous peoples in these panels is not about knowledge co-production. Scientists conceive these panels through their Western universalist ontology as apolitical sites to collect, systematize, and diffuse scientific knowledge. In contrast, for Indigenous peoples, these are spaces for political exchanges on which they seek to formulate their political ontology and the proper ways to protect their world. Based on these findings, the article proposes reimagining scientist platforms and international decision-making forums as spaces for ‘pluriversal governance’.

Antimicrobial resistance (AMR) has been extensively studied in clinical settings; however, research on the environmental aspects of AMR is relatively new. Recently, there has been growing interest in the relationship between climate change and AMR, yet evidence linking AMR to climate change and potential environmental transmission is very limited. Even less is understood about how vulnerabilities may exacerbate exposure and associated health risks. This study aims to compile literature on recent research on how climate change exacerbates risks associated with AMR. The study builds a framework based on this review that connects the amplifying effects of climate change to AMR risk using the modified DPSEEA (mDPSEEA) model. Additionally, the framework complements the mDPSEEA context by incorporating the vulnerability concept of the Intergovernmental Panel on Climate Change (IPCC) risk framework, which encompasses susceptibility and limited coping capacity to face exposure and potential health impacts of AMR. The integrated framework facilitates systemic analysis of the combined risk of climate change and AMR in its early stages, particularly within the driver-pressure-state interface. It also helps to identify vulnerable groups most likely to experience severe effects from AMR, such as the older adult(s), children, individuals with pre-existing chronic conditions, those at higher occupational risk of being colonised by antibiotic-resistant bacteria (ARB), and populations living in highly contaminated environments. The framework analysis emphasises that addressing AMR requires more than just isolated interventions; it demands a fundamental rethinking of public health planning and agendas. There is a need to develop strategies that coordinate various policy frameworks, including those about infectious diseases, chronic diseases and environmental hazards. Tackling climate change, pollution, and social inequalities is essential for combating AMR, as their interconnectedness cannot be overlooked.

N2O emissions fueled by eutrophication in a shallow lake.

The Intergovernmental Panel on Climate Change (IPCC) acknowledges the existing robust data that show that climate change substantially and negatively affects human health both directly and indirectly, with Indigenous people facing heightened vulnerability. The health impacts of climate change make litigation an important means of pursuing justice and strategically challenging legal systems that are not taking sufficient steps to reduce the impacts of climate change. This article invites medical professionals to learn from recent climate litigation cases and calls on professionals to listen deeply, act in allyship, and embrace legal and cultural literacy as core to delivering health equity in a changing climate.

Refining regional estimates of N2O emissions from agricultural soils: A modelling study from Austria.

The protection and restoration of seagrass meadows are recognised contributions to address the combined biodiversity-climate crises because the meadows are hotspots of biodiversity, sediment organic carbon (OC) stocks and carbon accumulation rate (CAR) and have experienced major global declines in response to pressures. However, OC storage varies among seagrass species. Here we assess carbon storage and CAR in meadows of Zostera marina (eelgrass), the most widely distributed seagrass species, thereby evaluating their potential for inclusion in carbon markets. We review sediment OC stocks, CAR, sources and stability (mineral associated organic matter - MAOM) of the organic matter. We compare our findings for eelgrass, which is a fast-growing colonizing-opportunistic seagrass species, with those for Posidonia oceanica, typifying slow-growing, persistent seagrass species. Eelgrass sediment OC stocks and CAR display median stocks 40% and 50% lower, respectively, than those of P. oceanica and median eelgrass CAR is only 21% of the Tier 1 emission factor for seagrass used in the Intergovernmental Panel on Climate Change (IPCC) greenhouse gas accounting guidelines. The OC stocks in most (60%) vegetated areas were not significantly different from stocks of nearby unvegetated sediments and only 27% of the eelgrass sediment samples in this compilation would return positive OC values after subtracting the MAOM fraction, a requirement of some carbon market methodologies. These features may partly be due to the strong spatial heterogeneity and temporal dynamics of eelgrass meadows, eelgrass traits as well as export of eelgrass carbon beyond the meadows. We discuss implications for carbon market restoration projects and encourage considering all the ecosystem services the meadows provide.

Introduction The agricultural sector faces increasing pressure to contribute to the Sustainable Development Goals (SDGs) while simultaneously acting as a driver of global climate change. In response, agroecology amongst other approaches is gaining recognition as a holistic framework to transform food systems towards greater sustainability and resilience. Methods To facilitate standardized assessment of agroecological performance, the Tool for Agroecology Performance Evaluation (TAPE) was developed by the UN Food and Agriculture Organization (FAO). While a greenhouse gas (GHG) emission score was originally envisioned within the TAPE framework, to date, no standardized implementation exists. Results This study presents a first step toward operationalizing such a score by estimating livestock GHG emissions, specifically from enteric fermentation and manure management, using TAPE data collected from smallholder farms in Kenya's Nandi and Bomet counties. Emission factors (EFs) derived from local studies were applied to improve accuracy of the GHG emission score, achieving a level of specificity comparable to Intergovernmental Panel on Climate Change (IPCC) Tier II methods. TAPE results showed correlations between total livestock emissions as well as milk-based emission intensity (EI) of cattle and the agroecological indicators: Efficiency, Recycling, and Resilience. Discussion The correlations varied in direction and magnitude, with the strongest relation found for Recycling and EI. Our findings demonstrate (1) the feasibility of integrating a GHG emission estimation into TAPE, and (2) highlight its potential as a tool for identifying synergies and tradeoffs between agroecological performance, emissions and emission intensities.

Tourism-related waste generation poses a significant environmental challenge, particularly in ecologically sensitive areas. This study investigates the quantity, composition and associated carbon emissions of solid waste generated by tourists over four weekends at Lata Sempeneh, Batu Kurau, Perak, Malaysia. The waste characterization was conducted following the Malaysian Standard MS 2505:2012 for household solid waste composition, whereas greenhouse gas emissions (methane (CH4) and carbon dioxide (CO2)) were estimated using the Intergovernmental Panel on Climate Change (IPCC) 1996 mass balance methodology. The average waste generation rate was found to be 0.174 kg per capita per day, with an estimated 259 tourists visiting the site each weekend day. Food waste constituted the majority (63.92%) of the total waste, indicating a significant potential for CH4 generation if landfilled. The average carbon emission attributable to tourist-generated waste was estimated at 0.138 kg CO2-eq per capita per day. Scenario analysis demonstrated that diverting 50% of food waste through composting could reduce this number by nearly half, to 0.069 kg CO2-eq capita per day. This study highlights the practical sustainable waste management strategy for tourist-generated waste in natural recreational areas like Lata Sempeneh. Unlike conventional disposal methods, this approach not only diverts organic waste from landfills, thereby significantly reducing carbon emissions but also promotes resource recovery by transforming food waste into compost, which can benefit local agriculture or landscaping efforts. Such a localized, circular intervention tailored to tourist hotspots in Malaysia remains underexplored and adds a practical dimension to sustainable tourism management.

The rapid spread of climate change misinformation across digital platforms undermines scientific literacy, public trust, and evidence-based policy action. Advances in Natural Language Processing (NLP) and Large Language Models (LLMs) create new opportunities for automating the detection and correction of misleading climate-related narratives. This study presents a multi-stage system that employs state-of-the-art large language models such as Generative Pre-trained Transformer 4 (GPT-4), Large Language Model Meta AI (LLaMA) version 3 (LLaMA-3), and RoBERTa-large (Robustly optimized BERT pretraining approach large) to identify, classify, and generate scientifically grounded corrections for climate misinformation. The system integrates several complementary techniques, including transformer-based text classification, semantic similarity scoring using Sentence-BERT, stance detection, and retrieval-augmented generation (RAG) for evidence-grounded debunking. Misinformation instances are detected through a fine-tuned RoBERTa–Multi-Genre Natural Language Inference (MNLI) classifier (RoBERTa-MNLI), grouped using BERTopic, and verified against curated climate-science knowledge sources using BM25 and dense retrieval via FAISS (Facebook AI Similarity Search). The debunking component employs RAG-enhanced GPT-4 to produce accurate and persuasive counter-messages aligned with authoritative scientific reports such as those from the Intergovernmental Panel on Climate Change (IPCC). A diverse dataset of climate misinformation categories covering denialism, cherry-picking of data, false causation narratives, and misleading comparisons is compiled for evaluation. Benchmarking experiments demonstrate that LLM-based models substantially outperform traditional machine-learning baselines such as Support Vector Machines, Logistic Regression, and Random Forests in precision, contextual understanding, and robustness to linguistic variation. Expert assessment further shows that generated debunking messages exhibit higher clarity, scientific accuracy, and persuasive effectiveness compared to conventional fact-checking text. These results highlight the potential of advanced LLM-driven pipelines to provide scalable, real-time mitigation of climate misinformation while offering guidelines for responsible deployment of AI-assisted debunking systems.

Abstract Peppermint ( Mentha piperita ) is a perennial herb valued for its menthol‐rich oil and requires high nitrogen (N) inputs for its irrigated production. Optimizing N management can reduce nitrous oxide (N 2 O) emissions, a potent greenhouse gas associated with fertilizer N input. A 2‐year experiment (2022–2023) was conducted in western Nebraska to evaluate the effects of N fertilizer sources (urea and polymer‐coated urea; PCU) applied at different rates on peppermint yield and N 2 O emissions. Application rates were lower in 2022 than in 2023 due to transplanting and herbicide injury issues. Therefore, dry matter yield was lower in 2022 (3.38–3.84 Mg ha −1 ) than in 2023 (7.56–14.11 Mg ha −1 ). In 2023, PCU at the highest rate (332 kg N ha −1 ) had a greater peppermint dry matter yield than all other treatment combinations except for urea at the same rate. In 2023, yield did not vary with N source, except at the low rate, where PCU had a greater yield (12.14 Mg ha −1 ) than urea (9.31 Mg ha −1 ). In both years, urea had greater N 2 O emissions than PCU, except for the lowest N rate (34 kg N ha −1 ) in 2022. Nitrous oxide emissions varied by N rates for urea but not for PCU. Fertilizer‐induced emission factors (FIEF) were within the range of the Intergovernmental Panel on Climate Change (IPCC) disaggregated emission factor of 0.5% (0.0%–1.1%) for dry climates. Nitrogen source‐specific FIEF disaggregation might narrow the current IPCC uncertainty range.

Abstract The oil and gas industry produces diverse hazardous and toxic wastes (HTW) classified into dominant wastes, including chemicals residues, while non‐dominant wastes, such as contaminated materials, which pose greenhouse gas (GHG) emissions risks. Therefore, this study provides a detailed estimation of its total GHG emissions on the period from 2020 to 2024 and its transportation in the oil and gas industry. The Tier 1 approach of the 2006 Intergovernmental Panel on Climate Change (IPCC) Guidelines was applied for estimating, covering three major GHG: carbon dioxide (CO 2 ), methane (CH 4 ), and nitrous oxide (N 2 O). Results indicate a substantial 83.99% reduction in total emissions from hazardous waste from 705,093 tCO 2 eq in 2020 to 112,888 tCO 2 eq in 2024 reflecting improved waste handling practices. Emissions from dominant waste types declined by 42.46%, while non‐dominant waste types showed a 99.67% reduction. Its transportation‐related emissions of marine transport were 14,292 tCO 2 eq, while land transport of 0.001742069 tCO 2 eq from CH 4 and N 2 O conversion value which due to avoid double counting, CO 2 emissions were treated as part of the energy sector. The study contributes to policy formulation by highlighting the importance of incorporating both treatment and transportation emissions in waste management strategies to achieve low‐carbon and sustainable development goals.