9 research outputs found

    Tangetal2023

    No full text
    <p>The updated dataset and code for TSECfire. </p&gt

    Assessing the Impacts of Urbanization on Albedo in Jing-Jin-Ji Region of China

    No full text
    As an indicative parameter that represents the ability of the Earth’s surface to reflect solar radiation, albedo determines the allocation of solar energy between the Earth’s surface and the atmosphere, which plays an important role in both global and local climate change. Urbanization is a complicated progress that greatly affects urban albedo via land cover change, human heat, aerosol, and other human activities. Although many studies have been conducted to identify the effects of these various factors on albedo separately, there are few studies that have quantitatively determined the combined effects of urbanization on albedo. In this study, based on a partial derivative method, vegetation index data and nighttime light data were used to quantitatively calculate the natural climate change and human activities’ contributions to albedo variations in the Jing-Jin-Ji region, during its highest population growth period from 2001 to 2011. The results show that (1) 2005 is the year when urbanization starts accelerating in the Jing-Jin-Ji region; (2) albedo trends are equal to 0.0065 year−1 before urbanization and 0.0012 year−1 after urbanization, which is a reduction of 4/5; and (3) the contribution rate of urbanization increases from 15% to 48.4%, which leads to a decrease in albedo of approximately 0.05. Understanding the contribution of urbanization to variations in urban albedo is significant for future studies on urban climate change via energy balance and can provide scientific data for energy conservation policymaking

    Decisions and Coordination in E-Commerce Supply Chain under Logistics Outsourcing and Altruistic Preferences

    No full text
    Considering the peculiarities of logistics in the electronic commerce (e-commerce) supply chain (ESC) and e-commerce platform’s altruistic preferences, a model including an e-commerce platform, third-party logistics service provider, and manufacturer is constructed. Based on this, three decision models are proposed and equilibrium solutions are obtained by the Stackelberg game. Then, an “altruistic preference joint fixed-cost” contract is proposed to maximize system efficiency. Finally, numerical analysis is used to validate the findings of the paper. The article not only analyzes and compares the optimal decisions under different ESC models, but also explores the intrinsic factors affecting the decisions. This paper finds that the conclusions of dual-channel supply chains or traditional supply chains do not necessarily apply to ESC, and that the effect of altruistic behavior under ESC is influenced by consumer preferences. Moreover, there is a multiparty win–win state for ESC, and this state can be achieved through the “altruistic preference joint fixed-cost” contract. Therefore, the findings of this paper contribute to the development of an e-commerce market and the cooperation of ESC members

    Decisions and Coordination in E-Commerce Supply Chain under Logistics Outsourcing and Altruistic Preferences

    No full text
    Considering the peculiarities of logistics in the electronic commerce (e-commerce) supply chain (ESC) and e-commerce platform’s altruistic preferences, a model including an e-commerce platform, third-party logistics service provider, and manufacturer is constructed. Based on this, three decision models are proposed and equilibrium solutions are obtained by the Stackelberg game. Then, an “altruistic preference joint fixed-cost” contract is proposed to maximize system efficiency. Finally, numerical analysis is used to validate the findings of the paper. The article not only analyzes and compares the optimal decisions under different ESC models, but also explores the intrinsic factors affecting the decisions. This paper finds that the conclusions of dual-channel supply chains or traditional supply chains do not necessarily apply to ESC, and that the effect of altruistic behavior under ESC is influenced by consumer preferences. Moreover, there is a multiparty win–win state for ESC, and this state can be achieved through the “altruistic preference joint fixed-cost” contract. Therefore, the findings of this paper contribute to the development of an e-commerce market and the cooperation of ESC members

    Impacts of Environmental Regulation on the Green Transformation and Upgrading of Manufacturing Enterprises

    No full text
    Since environmental problems are becoming increasingly prominent, macro policies and social development have placed higher requirements on manufacturing enterprises to promote green transformation and upgrading (GTU) in China. Considering that different manufacturing enterprises choose different green technology innovation levels for GTU under environmental regulation, a game model between manufacturing enterprises and the government is constructed. The relationship between the green technology innovation level (GTIL) and the environmental regulation intensity is analyzed. Through numerical examples, the influences of environmental regulation and consumer preference on system decisions are further examined. Moreover, an econometric model is constructed to explore the influence that the environmental regulation exerts on the GTIL using panel data from the Chinese manufacturing industry. Our results show that the increase in environmental regulation intensity contributes to improving GTIL and promoting the GTU of manufacturing enterprises. Furthermore, as the environmental regulation is enhanced, the sales price decreases, benefiting consumers. Consumers’ preference for high-GTIL products is conducive to GTU under environmental regulation. Empirical analysis shows that there is a U-shaped relationship between environmental regulation and the GTIL. Only when the intensity reaches a threshold can the environmental regulation be beneficial to improve the GTIL and promote the GTU of Chinese manufacturing enterprises

    Global fire modelling and control attributions based on the ensemble machine learning and satellite observations

    No full text
    Contemporary fire dynamics is one of the most complex and least understood land surface phenomena. Global fire controls related to climate, vegetation, and anthropogenic activity are usually intertwined, and difficult to disentangle in a quantitative way. Here, we leveraged an ensemble of five machine learning (ML) models and multiple satellite-based observations to conduct global fire modeling for three fire metrics (burned area, fire number, and fire size), and quantified driving mechanisms underlying annual fire changes in a spatially resolved manner for the period 2003–2019. Ensemble learning is a meta-approach that combines multiple ML predictions to improve accuracy, robustness, and generalization performance. We found that the optimized ensemble ML well reproduced annual dynamics of global burned area (R2 = 0.90, P < 0.001), total fire numbers (R2 = 0.86, P < 0.001), and averaged fire size (R2 = 0.70, P < 0.001). Additionally, the ensemble ML captured key spatial patterns of multi-year mean magnitudes, annual variabilities, anomalies, and trends for different fire metrics. Our ML-based fire attributions further highlighted the dominant role of enhanced anthropogenic activity in reducing global burned area (−1.9 Mha/yr, P < 0.01), followed by climate control (−1.3 Mha/yr, P < 0.01) and insignificant positive vegetation control (0.4 Mha/yr, P = 0.60). Spatially, climate dominated a much larger burned area (53.7%) than human (23.4%) or vegetation control (22.9%); however, the counteracting effects from regional wetting and drying trends weakened the net climate impacts on global burned area. The fire number and fire size exhibited similar spatial control patterns with burned area; globally, however, fire number tended to be more affected by climate while fire size more influenced by human activities. Overall, our study confirmed the feasibility and efficiency of ensemble ML in global fire modeling and subsequent control attributions, providing a better understanding of contemporary fire regimes and contributing to robust fire projections in a changing environment
    corecore