Toward a harmonized approach for evaluating GHG emissions in high-end hotels with implications for China

Literature search and screening

A structured literature review was conducted to identify the methodological approaches, benchmarking systems, and certification frameworks employed to evaluate GHG emissions in the hotel sector. Searches were conducted using the Scopus database (Elsevier; https://www.scopus.com) and the Web of Science Core Collection (Clarivate; https://www.webofscience.com) with Boolean combinations of keywords related to hotels or hospitality, LCA, carbon footprint, GHG emissions, benchmarking, sustainability assessment, and certification. Database searches were conducted in November and December 2025. The Scopus database was searched on 10 November 2025, and the Web of Science Core Collection was searched on 13 November 2025. Screening, refinement, and the selection of eligible studies continued until the literature review was finalized on 15 December 2025. The Scopus search covered publications from January 2010 to 10 November 2025, while the Web of Science search covered publications from January 2015 to 13 November 2025. The search strategy involved an iterative refinement process applied independently to each database. In Scopus, an initial broad query produced 102 records, which were progressively refined by narrowing the subject areas, restricting the results to English-language peer-reviewed publications, and applying a publication-year filter of 2010-2025. This refinement reduced the working set to 82 records, which were then screened by title and abstract for relevance; 36 records were excluded at this stage, yielding 46 records retained for comparative analysis. A parallel but independently conducted protocol was applied in the Web of Science, where an initial set of 183 records was similarly refined; a narrower publication-year filter of 2015-2025 was applied at this stage, as searches for records before 2015 in this database consistently returned results that were off-topic or lacked sufficient methodological relevance. This refinement reduced the working set to 68 records, which were screened by title and abstract for relevance; 43 records were excluded at this stage, yielding 25 records retained for comparative analysis. The two database searches were conducted and screened independently rather than pooled, and no deduplication step was applied between them, consistent with the structured comparative, rather than fully systematic, nature of this review. The titles and abstracts of the combined records were reviewed to exclude studies that addressed generic building assessments without specific applicability to hotels, research on tourism sustainability that lacked quantitative environmental evaluation, and publications that did not provide methodological transparency regarding emissions accounting or life-cycle system boundaries. Full-text screening was then conducted to confirm the final eligibility for inclusion in the comparative analysis of hotel-specific GHG and environmental assessment methodologies. Across both databases, this screening process yielded a combined total of 71 records (46 from Scopus and 25 from Web of Science) retained for the comparative framework analysis presented in this study.

In addition to peer-reviewed sources, widely used hotel sustainability frameworks are often documented in industry methodologies, technical manuals, and organizational reports rather than in peer-reviewed literature. Consequently, a targeted screening of the grey literature was conducted. This approach allowed for the inclusion of globally applied tools, such as operational carbon-accounting methodologies, benchmarking indices, and certification schemes, that influence real-world sustainability practices in the hospitality sector^[12,13]. While benchmarking and certification documentation were reviewed for contextual understanding, they were not treated as peer-reviewed analytical sources within the literature dataset but were incorporated into the framework comparison stage.

Grey-literature sources were included when they were issued by recognized hospitality, tourism, sustainability, benchmarking, or certification organizations and provided methodological information relevant to hotel carbon, water, resource-use, benchmarking, or certification assessment. Sources were excluded when they were primarily promotional, lacked methodological or indicator-level detail, were not specific to hotels or accommodation services, or did not address emissions, resource use, benchmarking, or certification logic. Grey-literature documents were therefore used to characterize applied industry frameworks and their practical role in hotel sustainability assessment, rather than to replace peer-reviewed evidence.

After screening and integrating sources, the unit of analysis was established as assessment frameworks and methodological approaches rather than individual empirical hotel case studies. This aligns with the study’s aim of elucidating the methodological landscape of hotel GHG assessments rather than synthesizing emissions results across properties. In line with this aim, this review is framed as a structured comparative methodological review rather than a fully systematic literature review (SLR). Although transparent database searching and screening procedures were applied, the review was designed to support framework comparison rather than exhaustive bibliometric mapping. The inclusion of grey literature was necessary because several widely used hotel assessment tools are defined primarily through industry guidance, technical manuals, and certification documentation rather than peer-reviewed publications.

From this combined pool of 71 retained peer-reviewed and grey-literature sources, specific assessment frameworks were shortlisted for detailed comparative mapping [Table 1] according to three explicit, traceable inclusion criteria: (1) explicit status as a primary operational standard or reference framework within the 71 retained documents, rather than an incidental citation; (2) active, documented application in real-world hospitality carbon reporting as of 2023-2024; and (3) distinct categorization across the three identified functional sectors (methodological accounting, benchmarking, and certification) to ensure a balanced structural overview. Applying these criteria to the 71 sources directly isolated eight primary frameworks for comparison (HCMI, HWMI, Greenview HFT, Academic LCA, CHSB, EarthCheck, GSTC, and Ecostars). Frameworks that were mentioned only contextually in the literature pool or lacked sufficient public methodological documentation to analyze system boundaries and functional units were systematically excluded [Table 2].

Analytical classification of frameworks

In the analytical phase of this study, we focused on characterizing and comparing hotel-specific sustainability assessment frameworks identified through the database search and grey literature screening detailed in Section Literature search and screening Instead of aggregating quantitative emission outcomes from individual hotel case studies, the analysis delves into the methodological structure, functional purpose, and operational applicability of each framework. This approach aligns with the study’s primary goal of elucidating the conceptual and methodological landscape of GHG assessments in the hospitality sector, particularly in high-end hotel operations. The classification was therefore intended to distinguish the role each framework plays in assessment practice, rather than to rank frameworks according to methodological quality.

To facilitate a structured comparison of various assessment approaches, frameworks were categorized based on their primary functional role in evaluating GHG and carbon footprints. This classification process combined deductive reasoning, guided by established distinctions in the environmental assessment and sustainability accounting literature^[22], with an inductive interpretation of recurring patterns observed in the reviewed academic methodologies and industry tools. Through this mixed interpretive approach, three analytically distinct yet conceptually related functional categories were identified: methodological calculation frameworks that outline procedures for quantifying emissions or environmental impacts; benchmarking systems that aggregate and normalize performance metrics to enable comparisons between hotels; and certification frameworks that focus on auditing, standardization, and communication of sustainability performance rather than on primary emissions quantification. This functional differentiation offers a coherent analytical structure for comparing tools that would otherwise remain methodologically non-equivalent to each other.

After classification, each framework was scrutinized using a consistent comparative structure aimed at capturing the essential methodological attributes pertinent to carbon footprint assessment in hotel settings. The determining factors were drawn from LCA standards and environmental accounting principles^[23] but remained flexible enough to accommodate the unique characteristics of each framework identified during the review. Special attention was paid to defining system boundaries, selecting functional units, determining the scope of the included emission sources, and ensuring data requirements and transparency. Additionally, the degree of methodological standardization and practical applicability to various hotel types were considered in this study. The focus on high-end hotels highlights their unique blend of intensive service provision, extensive infrastructure, and diverse indirect emission sources, which can challenge the simplified accounting assumptions embedded in standardized tools.

In this study, LCA serves as a conceptual foundation for interpreting and harmonizing the various frameworks examined. LCA is a structured methodology designed to quantify environmental impacts throughout the entire life cycle of a product, service, or system, from resource extraction through operation to end-of-life management^[23]. This approach enables consistent evaluation of energy use, emissions, and resource consumption within complex systems. In the hospitality sector, previous LCA applications have demonstrated their ability to identify environmental hotspots across hotel construction, operation, and waste management stages, while highlighting persistent challenges related to data availability, regional variability, and methodological inconsistency. Building on these insights, the present research does not conduct new case-study LCAs but instead applies LCA methodological principles as an analytical reference for evaluating boundary completeness, functional unit consistency, and emission scope coverage across existing hotel carbon footprint assessment frameworks. The Beijing case study presented in Section 3.5 is not a newly conducted LCA but a reuse of a previously completed thesis-based inventory analysis, presented here to illustrate boundary and methodological effects rather than to report original primary data collection.

The analytical procedure outlined above facilitated a structured comparison of how existing hotel assessment frameworks define system boundaries, functional units, emission scopes, data requirements, and governance roles for sustainability evaluation. Instead of merely aggregating numerical emissions results, the analysis aimed to clarify the conceptual and methodological differences between the framework types and identify areas of overlap or inconsistency. This comparative interpretation lays the groundwork for the framework-specific review presented in Section COMPARATIVE OVERVIEW OF HOTEL SUSTAINABILITY FRAMEWORKS, where methodological calculation approaches, benchmarking systems, and certification schemes are examined in detail and assessed for their applicability to high-end hotel contexts. This classification provides the structure used to examine the frameworks in the following section.

Methodological frameworks

Methodological frameworks serve as the analytical backbone of GHG assessments in the hospitality sector, as they dictate how emissions are calculated, which processes fall within the system boundaries, and what types of data are necessary for quantification. Unlike benchmarking systems or certification schemes that depend on aggregated indicators or governance criteria, methodological approaches offer core computational logic for measuring hotel-related emissions^[12,13]. A review of the literature and industry documentation identified four key methodological approaches pertinent to hotel GHG assessments: the Hotel Carbon Measurement Initiative (HCMI), Hotel Water Measurement Initiative (HWMI), Greenview Hotel Footprinting Tool (HFT), and academic LCA models developed for hotel case studies. These approaches exhibit methodological variations primarily through four structural dimensions: system boundary definition, functional unit selection, data requirements, and the included GHG scope. Collectively, these factors determine the level of analytical completeness, comparability across hotels, and practical feasibility of implementation in the study’s operational contexts.

Benchmarking frameworks

Benchmarking frameworks consolidate environmental performance data from various hotels to facilitate comparisons across properties, brands, and geographic regions. In contrast to methodological accounting tools, benchmarking systems generally do not establish emission calculation methods. Instead, they compile standardized indicators derived from foundational reporting systems and operational datasets. Consequently, benchmarking primarily serves as an interpretive layer within broader sustainability assessments. Within the hospitality sector, the Cornell Hotel Sustainability Benchmarking Index represents one of the most prominent examples of this framework type^[12]. In this study, benchmarking frameworks are therefore treated as contextual comparison tools rather than primary calculation methodologies. This distinction is important because benchmark values can support interpretation of hotel performance, but they should not be used as direct substitutes for transparent inventory-based assessment.

Certification frameworks

Certification frameworks constitute a third and distinct category of sustainability tools in the hospitality sector. While methodological accounting approaches concentrate on quantifying environmental impacts and using benchmarking systems to compare performance across properties, certification programs prioritize governance, verification, and communication of sustainability performance^[13]. These frameworks set criteria that hotels must meet to demonstrate environmental responsibility and ongoing improvement. Although certification programs often require the reporting of environmental data, the underlying calculation methods are usually derived from external accounting tools or internal proprietary systems rather than publicly standardized methodologies. Unlike methodological accounting frameworks, certification programs typically do not define how emissions are calculated. Instead, they rely on externally generated environmental indicators and translate them into governance standards that can be audited and communicated across the hospitality industry.

Comparative analysis and harmonization

Toward a harmonized GHG assessment

The comparative analysis reveals that current hotel sustainability frameworks function at varying analytical levels and are crafted to support diverse decision-making contexts. Industry methodologies often focus on standardized operational accounting, whereas academic studies tend to adopt broader life-cycle perspectives to capture additional environmental impact sources. Previous research has consistently demonstrated that methodological choices significantly affect both the magnitude of reported emissions and the comparability of results across hotels and regions^[2,6,14].

Several methodological patterns have consistently emerged in the literature reviewed in this study. Most assessments rely on activity-based functional units linked to hotel service provision, typically expressed per guest-night, per occupied room, or per unit of floor area^[14,17]. Operational energy consumption related to heating, cooling, and electricity use is widely recognized as the primary contributor to hotel emissions^[4,6]. Consequently, operational energy data form the basis of most existing accounting methods.

Previous studies have highlighted significant limitations in the narrowly defined operational frameworks. Life cycle analyses have shown that substantial environmental impacts may arise from indirect sources such as construction materials, infrastructure, and supply chains^[15,14,17]. However, incorporating these processes significantly increases data requirements and methodological complexity, which can limit their applicability in routine hotel operations. As a result, many industry tools deliberately restrict system boundaries to maintain consistency and feasibility across large hotel portfolios. These observations suggest that hotel GHG assessments can be more clearly interpreted through a layered analytical structure that reconciles the strengths of existing approaches. Therefore, the conceptual framework proposed in this study distinguishes three progressively broader levels of assessment [Figure 2]. These three levels reflect the progression from standardized reporting to comprehensive environmental analysis.

Figure 2. The tiered conceptual structure of hotel assessment approaches emerged from the comparative framework analysis conducted in this study, with each level expanding outward and increasing in complexity. LCA: Life-cycle assessment.

• Level 1 - Core Operational Accounting: This level defines the essential system boundary required for a standardized comparison among hotels and aligns closely with current operational accounting practices. It emphasizes emissions linked to direct on-site fuel use and electricity purchased for key hotel services, including heating, cooling, lighting, and hot water. Functional units are generally activity-based, such as emissions per guest-night or per occupied room, facilitating consistent benchmarking across different properties.

• Level 2 - Extended Operational Boundary: The second level broadens the operational perspective by incorporating additional resource flows that impact hotel emissions, all of which can still be measured using management data systems. These typically encompass water supply and wastewater treatment, waste management processes, and certain service-related supply chains, such as outsourced laundry or food services. By including these elements, the environmental representation is enhanced without adding undue complexity.

• Level 3 - Comprehensive LCA: The third level involves a comprehensive life-cycle analysis, which broadens the system boundary to encompass modeling, construction materials, maintenance activities, and upstream supply chains. This method allows for the identification of environmental hotspots and wider system impacts, but it demands significantly more detailed data and modeling efforts, making it more commonly applied in academic research.

Examining existing frameworks through this tiered lens elucidates how operational accounting tools, industry reporting systems, and academic life-cycle models each play a complementary role in sustainability assessments. This is particularly relevant for high-end hotels, where diverse facilities and service-intensive operations result in complex resource flows. By integrating insights from these various analytical levels, a more comprehensive understanding of environmental performance can be achieved. The proposed harmonized structure does not seek to replace existing methodologies but rather offers a conceptual foundation for interpreting their interrelationships and appropriate applications. By clarifying how different approaches are interconnected, the framework can enhance the transparency, comparability, and practical utility of GHG assessments in the hospitality sector.

Case study: high-end hotel in China

To demonstrate the practical application of various carbon footprint assessment frameworks, this study focused on a large international luxury hotel in Beijing, China. This property, part of a globally renowned hotel chain, caters to both domestic and international guests, blending European-style luxury with local hospitality expectations. The hotel includes approximately 480 guest rooms over about 46,000 m², six restaurants, ten conference rooms, wellness facilities, a heated rooftop pool, and centralized HVAC systems. Because the operational records were provided at hotel level, energy and water demand could not be attributed to individual compartments; this limitation is reflected in the inventory treatment summarized in Table 4. Such large-scale properties operate continuously and demand significant energy and resource inputs, making them ideal for exploring the practical implications of different sustainability assessments.

The hotel’s environmental performance was assessed by drawing on the 2023 operational dataset and inventory-based calculation originally compiled for the first author’s master’s thesis^[33], which is summarized and reframed here to illustrate the practical implications of the harmonized structure proposed in this study. The dataset included 2023 hotel-level operational records for electricity consumption, heating gas, kitchen gas, water consumption, waste generation where available, and monthly occupancy rates. These data were treated at the whole-building level because facility-level disaggregation by restaurants, conference rooms, wellness areas, or laundry operations was not available. Activity-based functional units commonly employed in hospitality sustainability studies were utilized, including emissions per guest-night and per floor area^[14,17]. Reliance on operational records ensured that the analysis accurately reflected the actual performance of the building rather than generalized assumptions. To improve transparency regarding the case-study application, Table 4 summarizes the main inventory categories, data sources, treatment, and limitations considered in the Beijing hotel assessment. Electricity emissions were calculated using a China/Beijing grid-based factor where available, while water and gas-related factors were derived from LCA databases and literature sources when region-specific values were not available.

Data processing for the baseline case study began with a rigorous data audit to eliminate gaps and verify the accuracy of the available records. Although the hotel’s original commercial billing file contained incomplete data for March 2023, with only the opening day’s entry recorded, the primary facility-level daily meter logs were successfully recovered. These logs allowed the complete reconstruction of electricity consumption for the entire month, removing the need for statistical interpolation or averaging. The audit also revealed that electricity consumption had been overstated in the preliminary billing summaries. After integrating the verified daily meter data, the annual electricity consumption was corrected to 13,791,000 kWh. The corresponding greenhouse gas emissions were then calculated by applying an electricity emission factor of 0.5580 kg CO₂-eq/kWh, representing the official 2022 Beijing provincial grid emission factor published by the Ministry of Ecology and Environment and the National Bureau of Statistics in December 2024^[34]. A Beijing-specific factor was selected instead of the national average because China’s provincial electricity grids differ considerably in their energy mixes, and the hotel is located in Beijing. Emission factors for stationary combustion were set at 2.1622 kg CO₂-eq/m³ for both heating gas and kitchen gas, based on Meng et al.(2025)^[35]. Domestic water consumption was assigned a combined emission factor of 0.301 kg CO₂-eq/m³, derived by multiplying the energy intensities reported for urban water supply (0.29 kWh/m³) and wastewater treatment (0.25 kWh/m³) by the same 2022 Beijing grid factor [(0.29 + 0.25) × 0.5580 = 0.301 kg CO₂-eq/m³], following the energy-intensity data reported by Smith and Liu (2017)^[31]. As shown in the calculation matrix provided in Supplementary Materials, multiplying the annual activity data by their respective emission factors resulted in a total annual carbon footprint of 11,161,062.7 kg CO₂-eq. When divided by the hotel’s recorded 116,376 guest-nights, this corresponds to a carbon intensity of approximately 95.9 kg CO₂-eq per guest-night.

For contextual reference, the Greenview Hotel Footprinting Tool reports an operational carbon-footprint benchmark of approximately 36.7 kg CO₂-eq per guest-night^[26,27] for five-star hotels in Beijing. The tool calculates hotel carbon-footprint estimates using market-level benchmark data from the Cornell Hotel Sustainability Benchmarking Index, with user-selected parameters including location, hotel type, rooms occupied, meeting-space area, and meeting duration^[26,27]. In the present study, this value is used as an operational benchmark reference^[26,27] rather than as a case-study result calculated from the Beijing hotel inventory. Consistent with common hotel-industry practice (including the HCMI and Greenview HFT methodologies described in Section Methodological frameworks), “guest-night” throughout this case study denotes an occupied room-night (one occupied room for one night), rather than an individual guest headcount; the hotel's reported 116,376 guest-nights therefore represents an occupied-room-night total (approximately 480 rooms × 365 days at the property's 2023 average occupancy rate), placing it on the same basis as the Greenview HFT benchmark. By contrast, the thesis-derived emissions estimate for the Beijing case-study hotel was calculated to be approximately 95.9 kg CO₂-eq per guest-night for 2023. This estimate reflects a broader analytical boundary based on the inventory categories summarized in Table 4. The contrast between these two values, shown in Figure 3, is therefore not intended to rank the case-study hotel against the benchmark sample, but to illustrate how different system boundaries, data sources, and methodological assumptions produce different types of carbon information. Previous hotel life-cycle studies have similarly shown that incorporating indirect processes and more detailed activity data can reveal environmental impacts not captured by simplified operational accounting approaches^[15,14,17].

Figure 3. Methodological contrast between selected hotel carbon-intensity values expressed as kg CO₂-eq per guest-night. The Beijing case-study hotel value reflects the extended operational emissions estimate derived from local property data, whereas the Beijing five-star value represents the baseline operational benchmark reference obtained from the Greenview HFT. HFT: Hotel Footprinting Tool.

The hotel reports its sustainability performance through the EarthCheck certification program, currently holding a Silver certification level. However, the detailed emissions inventory underlying this certification is not publicly disclosed, limiting direct methodological comparisons with the analytical approaches examined in this study. Therefore, this case illustrates the complex relationship between operational accounting tools, benchmarking datasets, and certification systems discussed in Section Benchmarking frameworks. A comparison of the case study results across the assessment approaches is presented in Table 5. This comparison highlights how the choice of framework fundamentally shapes both the reported emissions values and the interpretation of sustainability performance.

Key insights from the framework comparison

The comparison in this study shows that differences between hotel GHG assessment frameworks arise primarily from their intended analytical functions rather than from simple inconsistencies in measurement. Methodological tools such as HCMI and Greenview HFT are designed to quantify operational emissions in a standardized manner^[24,27], while academic life-cycle approaches extend the assessment boundary to include broader infrastructure, supply chain, and service-related processes. Certification programs operate at a different level, emphasizing governance, verification, and communication rather than primary emissions calculation.

This distinction helps explain why hotel carbon results can vary substantially across frameworks. Operational accounting frameworks prioritize comparability and routine reporting, whereas life-cycle approaches prioritize boundary completeness and hotspot identification. The harmonized structure proposed in this study therefore provides a way to interpret existing tools according to their purpose, data requirements, and boundary depth, rather than treating them as competing or directly interchangeable methods.

Comparison with previous studies

Previous studies on hotel sustainability have commonly focused on either individual case studies or the application of a single assessment method. Much of this literature identifies operational energy demand, particularly heating, cooling, lighting, and electricity use, as a major contributor to hotel emissions^[2,4]. The Beijing case is consistent with this pattern, as building energy demand represented a central component of the case-study inventory.

However, LCA-based studies show that the interpretation of hotel environmental performance changes when system boundaries extend beyond core operational energy use^[14,15,17]. Studies incorporating construction materials, supply chains, waste treatment, and supporting services have shown that broader inventories can reveal emission sources that remain outside simplified operational accounting frameworks^[15,17]. This supports the need to distinguish between operational benchmarking results and life-cycle-informed assessments.

The contribution of the present study is to connect these methodological differences to the functional roles of existing hotel assessment frameworks. Rather than comparing individual carbon footprint values in isolation, the proposed harmonized structure clarifies why different tools produce different types of information and how these outputs should be interpreted in relation to their boundaries, data requirements, and intended use.

Implications for high-end hotels in China

High-end hotels provide a useful setting for examining the limits of existing GHG assessment frameworks because their operations combine accommodation, food service, events, wellness facilities, and intensive building services within a single property. These functions generate resource flows that are not always visible in simplified operational accounting, particularly when data are aggregated at the whole-building level. The Beijing case illustrates this challenge by showing that framework selection affects not only the magnitude of reported emissions, but also the type of operational information made visible to hotel managers.

For hotels operating in China, this issue is further shaped by regional energy systems, infrastructure conditions, and evolving policy requirements. Carbon intensity, district energy systems, building age, and waste-management practices can all influence the interpretation of hotel emissions^[20,21]. As a result, international benchmarking values should not be applied without considering the local conditions under which hotel operations take place. This is particularly important for high-end properties, where large, fixed energy loads and service-intensive activities may amplify the influence of regional emission factors and infrastructure assumptions.

The implication is not that operational benchmarks are unsuitable, but that their role should be clearly defined. Benchmarking indicators are useful for portfolio comparison and routine performance tracking, whereas extended operational inventories and life-cycle-informed assessments are better suited to identifying the drivers of emissions in complex properties. For high-end hotels in China, a harmonized assessment logic can therefore support more transparent interpretation of carbon results by linking each type of framework to its appropriate decision-making context.

Implications for framework development and policy

The findings suggest that future development of hotel GHG assessment frameworks should focus on clearer alignment between methodological purpose, data requirements, and reporting use. Rather than focusing only on additional tools, the priority should be to improve transparency around what each framework measures, which emissions sources are included, and how results should be interpreted. This is especially important when operational accounting, benchmarking, and certification outputs are used together in sustainability reporting. This gap is compounded by the fact that governance-oriented frameworks such as EarthCheck and GSTC are documented primarily through grey literature, industry manuals, certification handbooks, and organizational presentations, rather than peer-reviewed, publicly auditable methodologies, underscoring the need for a more harmonized, consistent, and scientifically validated public method for assessing hotel carbon footprints, particularly for luxury properties.

For framework users, the proposed harmonized structure provides a practical basis for selecting the appropriate level of assessment. Core operational accounting can support routine monitoring and cross-property comparison, while extended operational inventories and life-cycle-informed approaches can support deeper diagnosis of emission drivers and long-term mitigation planning. Making these distinctions explicit would reduce the risk of overinterpreting benchmark values or certification outcomes as complete carbon assessments.

In the Chinese context, this alignment is also relevant to policy and compliance. National initiatives such as the 14th Five-Year Plan, China’s 2060 carbon-neutrality commitment, and green building policies increasingly emphasize energy efficiency, emissions monitoring, and improved environmental performance in commercial buildings. Hotel assessment frameworks that incorporate local emission factors, infrastructure characteristics, and operational data can therefore better support both international comparability and regionally meaningful carbon management.

Conclusions

This study examined how hotel GHG assessment frameworks differ in their methodological assumptions, analytical functions, and practical applications. The comparison shows that operational accounting tools, benchmarking systems, certification programs, and life-cycle-based approaches should not be interpreted as interchangeable measures of environmental performance. Rather, they provide different types of information depending on their system boundaries, data requirements, and intended use.

The harmonized structure proposed in this study offers a way to organize these approaches into complementary assessment levels. Core operational accounting supports standardized reporting and benchmarking; extended operational assessment incorporates additional resource flows relevant to hotel service provision; and life-cycle-informed analysis enables broader identification of structural and indirect emission drivers. This tiered interpretation helps clarify why carbon results may differ across frameworks and how each type of assessment can be used appropriately.

The Beijing high-end hotel case illustrates the practical importance of this distinction. By making the case-study inventory, assumptions, and boundary levels more explicit, the analysis demonstrates how different assessment approaches can generate different but complementary insights. The case should therefore be understood as an illustrative application of the harmonized framework rather than as a representative estimate of the Chinese hotel sector as a whole.

For practitioners and framework users, the findings highlight the importance of aligning assessment methods with decision-making needs. Benchmarking and certification can support communication, monitoring, and comparison, while broader inventories and life-cycle approaches are more suitable for diagnosing emission drivers and identifying mitigation opportunities in complex hotel systems.

This study is subject to several limitations. The review focused on selected hotel-specific and sector-relevant frameworks rather than all environmental assessment tools used in buildings or tourism. In addition, the case study relied on available hotel-level data and was constrained by confidentiality and limited disaggregation of some inventory categories. Future research could apply the harmonized structure across multiple hotel types, regions, and data conditions to further test its usefulness and refine guidance for hotel carbon assessment.

Overall, improving transparency around framework purpose, boundary definition, and data requirements can strengthen the interpretation of hotel carbon footprints and support more consistent sustainability assessment across the hospitality sector.