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The dataset presented in this article is related to the research article entitled “Towards improving emissions accounting methods in waste management: A proposed framework” (Maalouf and El-Fadel, 2019) [1] that examines the variability in aggregated and disaggregated emissions from waste management when using commonly adopted international methods (the UN IPCC 2006 Guidelines, the US EPA WARM, the EU EpE protocols, the Canadian IWM, and the UK IWM-2). The dataset presents the aggregated and disaggregated emission factors (EFs) used in existing accounting methods to estimate emissions from the waste sector. The EFs were retrieved from accounting methods to clarify their contribution to variability in estimating emissions across methods. The data contains three parts: aggregated EFs per tonne of waste category for individual waste management processes; disaggregated EFs per management process for a tonne of waste type; and emission flow diagrams of waste management systems for tested methods.

Nearly 40 % current global annual energy-related CO 2 emissions come from the fossil fuel-dominated power sector. Accurately accounting for carbon emissions in power systems from the consumption-based perspective is crucial for achieving the low-carbon power transition. Consumption-based carbon accounting has emerged as a major research focus, which aids in the implementation of targeted measures such as low-carbon demand response and dispatch. Choosing an appropriate method to account carbon emission needs thorough consideration of characteristics of various methods. There still lacks a systematic review that concludes the essence and application status of these methods, as well as comparing their advantages and disadvantages. To address this gap, a consumption-based carbon accounting framework for power systems is proposed. This framework groups four typical methods into two perspectives: Attributional methods and consequential methods. The principles, calculation approaches, and research application status of these methods are comprehensively summarized in a transparent, integrated and comparative manner, which makes progress in two critical limitations: (i) temporal and spatial granularity, and (ii) consideration of the actual topology and operational constraints of the power grid. As improvements in the transparency and quality of electricity data and expansion of application scenarios, the flexibility and applicability of the framework will continue to improve to achieve the unity of efficiency and fairness. The proposed framework can serve as a valuable guide to conducting research and exploration on low-carbon energy management, policy and regulatory decisions and to inform the development of effective strategies for the low-carbon transition of power systems. [Display omitted] • A consumption-based carbon accounting framework for power system is developed. • Typical carbon accounting methods are divided into attributional and consequential. • Principle and application status of indirect carbon accounting methods are analyzed. • Research in electricity-consuming carbon accounting is reviewed and compared. • Challenges and future directions are given to foster the framework's development. [ABSTRACT FROM AUTHOR]

Using model projections to study the emergence of observable climate signals presumes omniscient knowledge about the climate system. In reality, observational knowledge suffers from data quality and availability issues, for instance data gaps, changes in instrumentation, issues due to gridding and retrieval algorithms. Overlooking such deficiencies leads to misrepresentations of the time of emergence (ToE). We introduce a new definition of ToE that accounts for observational limitations, and show that significant corrections to the ToE may be necessary to achieve the same statistical confidence as would be afforded by omniscient knowledge. We also show how our method can inform future observational needs and observing systems design. Plain Language Summary: Long‐term planning for climate change adaptation requires accurate forecasts of climate impacts. Such forecasts are produced using computer models, which provide omniscient knowledge of the climate states they simulate. However, real‐world knowledge is based on incomplete and sometimes flawed observational data. Ignoring these flaws yields a distorted view of the timing of observable climate impacts. We propose a method to address this issue by accounting for observational limitations such as data gaps, changes in measuring equipment, data post‐processing, etc. We also show how to use the method to plan future data collection. Key Points: The degree of confidence placed in observed climate trends is misrepresented when overlooking observational limitationsWe provide a nonparametric method to account for such limitationsThe method can also inform the design of future observing platforms [ABSTRACT FROM AUTHOR]

The vulnerability in smart contracts (SCs) on the blockchain system may lead to severe security compromises. The SC can be invoked from an externally owned account (EOA) or a contract account (CA). The account a user creates to receive or send ether is an EOA. A CA contains codes that can interact with SCs. In Solidity SC, some vulnerabilities can only be exploited by the interactions between CAs and vulnerable SCs, which can be named external‐risky vulnerabilities. Most state‐of‐the‐art (SOTA) detectors detect external‐risky vulnerabilities by executing contract codes as an EOA user, thus reporting many unexploitable vulnerabilities. Therefore, we propose a CA‐triggering method to identify exploitable external‐risky vulnerabilities in Solidity SCs. We first designed agent contracts to simulate CAs' interactions with the target SCs in the real blockchain environment. We then detect vulnerability exploitation by analyzing transaction logs between agent contracts and target SCs and identifying successful exploits. We implemented the CA‐triggering method in a tool named SoliTester and evaluated it using three benchmark datasets, which contain three types of external‐risky vulnerabilities, namely, Reentancy (RE), Unchecked Call (UcC), and TxOrigin (TO). The results show that SoliTester can efficiently detect exploitable external‐risky vulnerabilities with significantly better precisions and recalls than SOTA detectors. We propose a contract account triggering method to detect exploitable external‐risky vulnerabilities in Solidity smart contracts. We designed agent contracts to simulate contract accounts' interactions with the target smart contract in the real blockchain environment. We then analyze transaction logs to identify successful vulnerability exploitation. A tool named SoliTester was implemented based on this method. [ABSTRACT FROM AUTHOR]

At present, it is increasingly necessary to process accounting information with greater speed, quality, reliability of the information and proper functioning of the system, guaranteeing correct decision making to achieve the fulfillment of the goals and objectives set in each entity. The characterization of the entity allowed to verify the organizational deficiencies presented with the accounting information that hinder the aspects related to the informative problems, the organization of the management processes and the realization of activities that have an impact on the decision-making process. The objective of this article is: to show a procedure for the management of accounting information, based on the Cascade Methodology. The proposed procedure is structured in five stages, and its implementation contributed to the improvement of the different processes and sub-processes of each subsystem in correspondence with the updating of the economic model, improving the decision-making process. Its application was developed in the Commerce Enterprise of Pinar del Río. Theoretical and empirical methods were applied, which allowed the collection and credibility of the information presented. [ABSTRACT FROM AUTHOR]

Motivation Colocalization analysis is commonly used to assess whether two or more traits share the same genetic signals identified in genome-wide association studies (GWAS), and is important for prioritizing targets for functional follow-up of GWAS results. Existing colocalization methods can have suboptimal performance when there are multiple causal variants in one genomic locus. Results We propose SharePro to extend the COLOC framework for colocalization analysis. SharePro integrates linkage disequilibrium (LD) modeling and colocalization assessment by grouping correlated variants into effect groups. With an efficient variational inference algorithm, posterior colocalization probabilities can be accurately estimated. In simulation studies, SharePro demonstrated increased power with a well-controlled false positive rate at a low computational cost. Compared to existing methods, SharePro provided stronger and more consistent colocalization evidence for known lipid-lowering drug target proteins and their corresponding lipid traits. Through an additional challenging case of the colocalization analysis of the circulating abundance of R-spondin 3 GWAS and estimated bone mineral density GWAS, we demonstrated the utility of SharePro in identifying biologically plausible colocalized signals. Availability and implementation SharePro for colocalization analysis is written in Python and openly available at https://github.com/zhwm/SharePro_coloc. [ABSTRACT FROM AUTHOR]

Copyright of China Population Resources & Environment is the property of Shandong Normal University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Under the dual constraints of China's carbon peaking and carbon neutrality goals, as well as ecological protection and high-quality development of the Yellow River Basin, clarifying the embodied carbon emissions and responsibility sharing of inter-provincial trade is crucial to the carbon reduction strategy of the Yellow River Basin. This paper uses the MRIO (multi-regional input–output) model to measure the production-side and consumption-side responsibility sharing of nine provinces in the Yellow River Basin in 2012 and 2017, revealing the amount and direction of the embodied carbon transfer between provinces, and finally introduces the share of provincial value added as the responsibility sharing factor to compare and analyze the differences between the three responsibility sharing methods. The results show the following: (1) The embodied carbon emissions on the production side in most provinces of the Yellow River Basin were larger than that on the consumption side, with the most significant differences in Shanxi, Inner Mongolia, and Shandong, among which local demand carbon emissions and intermediate product transfer out of carbon emissions were the main causes of production-side carbon emissions. (2) In general, all provinces except Shaanxi were net carbon transfer-in regions, and the embodied carbon was mainly transferred to Beijing, Jiangsu, Guangdong, Zhejiang, and Hebei. (3) Shared responsibility for carbon emissions was jointly determined by the volume of embodied carbon trade and the ability to obtain value added, which lay between production and consumption side responsibility shares. (4) The Yellow River Basin had a large responsibility-sharing factor and embodied carbon trade, and thus needs to take more responsibility for emission reduction. This study is expected to provide scientific support for the strategy of differentiated emission reduction in the Yellow River Basin and enrich the regional carbon accounting methods. [ABSTRACT FROM AUTHOR]

Copyright of Power Generation Technology is the property of Power Generation Technology Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Water resource asset (WRA) accounting holds great importance in ecological civilization construction. Existing WRA accounting methods heavily rely on statistical data, resulting in issues such as missing and inaccessible data. Moreover, they only consider the value brought by the physical resources, such as water quantity and quality, while neglecting the value brought by the ecological functions. Therefore, by fully exploiting the rapid, objective, and efficient advantages of remote sensing (RS) in monitoring surface objects, this article develops a surface WRA (SWRA) accounting method based on multisource RS data. First, a representation model is innovatively proposed, with full consideration of the ecological service functions offered by water resources. Specifically, the SWRAs are represented by two parts: tangible and intangible assets. The tangible asset refers to the quantifiable stock of water resources. Surface water volume is adopted as the indicator for tangible assets in this article. The intangible asset, which primarily embodies the ecological service functions provided by water resources, encompasses five major categories: flood regulation, carbon fixation, oxygen release, water purification, and water conservation. Furthermore, due to different units, the total amounts cannot be summed or compared directly. Therefore, this article utilizes price tools to convert SWRAs into price value, ultimately achieving SWRA accounting. The established method was tested in Miyun, Beijing, China, from 2013 to 2023. The findings demonstrate that the SWRA value reached its peak in 2023, amounting to 56,9368.6 × 104 yuan, while it had its lowest point in 2014, standing at 14,7402.7 × 104 yuan. The experimental results indicate that the proposed method can quickly provide the SWRA values for many years, offering a methodological foundation for SWRA asset auditing and enhancing the timeliness of the auditing work. [ABSTRACT FROM AUTHOR]

Nature-based solutions (NBS), in the form of active ecosystem conservation, restoration and improved land management, represent a pathway to accelerate net-zero emissions (NZE) strategies and support biodiversity. Meaningful implementation and successful accounting depend on the ability to differentiate between anthropogenic and natural carbon fluxes on land. The United Nations Framework Convention on Climate Change (UNFCCC) land carbon accounting methods currently incorporate all CO2 fluxes on managed land in country inventories without distinguishing between anthropogenic and natural components. Meanwhile, natural land carbon sinks are modelled by earth system models but are mostly reported at global level. Here we present a simple yet novel methodology to estimate the present and future progression of natural land sinks at the country and regional level. Forests dominate the uptake of CO2 on land and as such, our analysis is based on allocating global projections of the natural land carbon flux to individual countries using a compilation of forest land areas for a historic and scenario range spanning 1960-2100. Specifically, we use MIT's carbon cycle model simulations that are set in the context of emissions pathways from the Shell Energy Security Scenarios (2023). Our natural land carbon flux estimates for individual countries and regions such as the European Union (EU) show generally good agreement with independent estimates from recent land-use harmonisation studies for 2000-2020. Hence, our approach may also provide a simple, first-order exploration of future natural land fluxes at country level--a potential that other studies do not yet offer. In turn, this enables better understanding of the anthropogenic and natural components contributing to country NZE targets under different scenarios. Nevertheless, our findings also suggest that models such as the Shell World Energy Model (WEM) would benefit from further improvements in the apportionment of land carbon sources and sinks to evaluate detailed actions to meet country targets. More importantly, uncertainties remain regarding the resilience of land ecosystems and their capacity to store increasing amounts of carbon under progressive global warming. Therefore, we recommend that the carbon cycle modelling and energy modelling research communities continue to collaborate to develop a next generation of relevant data products to distinguish anthropogenic from natural impacts at local, regional and national levels. [ABSTRACT FROM AUTHOR]

The revised accounting rules applicable to business combinations in force on July1st 2009, are the result of several years efforts the convergence of U.S. and International Committee of the Financial Accounting Standards. Following the harmonization of global accounting procedures are revised and implemented also Czech accounting regulations. In our research we wanted to see how changes can affect the strategy and timing of business combinations. Comparative analysis is mainly focused on the differences between U.S. and international accounting policies and Czech accounting regulations. Key areas of analysis and synthesis are the identification of business combination, accounting methods for business combinations and goodwill recognition. The result is to assess the impact of the identified differences in the reported financial position and profit or loss of company.

The article covers the main operation peculiarities of public catering enterprises and their impact on accounting procedures. The author reviews the industry regulatory and legislative basis, identifies the issues in accounting for public catering enterprises, and comes up with proposals aimed at issues resolution. The article also describes the methods of calculating the cost of products and services, the sales prices of goods and outputs in the public catering sector, the advantages and disadvantages of each method. The given numerical examples show the accounting formulae used to calculate the cost of products and services in public catering enterprises, applying both the trade method and the production method

The overarching purpose of carbon accounting is to reduce carbon emissions to meet net-zero targets and minimize the impact of climate change. However, the plethora of methods and approaches used means that products and systems sometimes cannot easily be compared. The mix of regional and life cycle-based systems can mean that we lack global oversight of our emissions and impact. In some situations where a regional approach is used, industry/business/regions are incentivized to reduce their own/territorial emissions, which can mean that an optimal global solution is not adopted. Countries where grid emissions are higher can be selected for production because it reduces regional (not global) carbon levels. Furthermore, these can be areas where the climate impact may be felt the most: not the just transition we aspire to. Our work provides an analysis of the current system together with its challenges and limitations, paving the way towards a more unified framework to create climate justice together with transparent and comparable accounting methodology for industry and regions alike. This article is part of the discussion meeting issue 'Green carbon for the chemical industry of the future'. [ABSTRACT FROM AUTHOR]

Copyright of Zeszyty Teoretyczne Rachunkowości is the property of Stowarzyszenie Ksiegowych w Polsce Rada Naukowa and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)