What influences the performance of carbon emissions in China?-Research on the inter-provincial carbon emissions' conditional configuration impacts.

The severe global warming issue currently threatens humans' existence and development. Countries and international organizations have effectively implemented policies to reduce carbon emissions and investigate low-carbon growth strategies. Reducing carbon emissions is a hot topic that academics and government policy-making departments are concerned about.Through necessary condition analysis (NCA) and fuzzy set qualitative comparative analysis(fsQCA), this paper investigates local governments' configuration linkage effect and path choice to improve carbon emission performance from six dimensions: energy consumption, industrial structure, technological innovation, government support, economic development, and demographic factors. The research findings include the following: (1) Individual condition does not represent necessary conditions for the government's carbon performance. Among the two sets of second-order equivalence configurations(S and Q) (five high-level carbon performance configurations), those dominated by economic development or low energy consumption can produce high-level carbon performance. Therefore, the six antecedent conditions dimensions work together to explain how the government can create high levels of carbon performance. (2)According to the regional comparison, China's eastern, central, and western regions exhibit similarities and differences in the driving forces behind high carbon emission performance. All three regions can demonstrate carbon emission performance when all the factors are combined. However, when constrained by the conditions of each region's resource endowment, the eastern region emphasizes the advantage of economic and technological innovation, the central region favors government support and demographic factors, and the western region prefers upgrading industrial structure based on a specific level of economic development.

Designing a sustainable reverse logistics network for used cell phones based on offline and online trading systems.

Unsustainable production and consumption are driving a significant increase in global electronic waste, posing substantial environmental and human health risks. Even in more developed nations, there is the challenge of low collection rates. In response, we integrate offline and online trading systems and design a material efficiency strategy for used cell phones. We propose a new multi-objective optimization framework to maximize profit, carbon emissions reduction, and circularity in the process of recycling and treatment. Considering multi-period, multi-product, multi-echelon features, as well as price sensitive demand, incentives, and qualities, we established a new multi-objective mixed-integer nonlinear programming optimization model. An enhanced, Fast, Non-Dominated Solution Sorting Genetic Algorithm (ASDNSGA-II) is developed for the solution. We used operational data from a leading Chinese Internet platform to validate the proposed optimization framework. The results demonstrate that the reverse logistics network designed achieves a win-win situation regarding profit and carbon emission reduction. This significantly boosts confidence and motivation for engaging in recycling efforts. Online recycling shows robust profitability and carbon reduction capabilities. An effective coordination mechanism for pricing in both online and offline channels should be established, retaining offline methods while gradually transitioning towards online methods. To increase the collection rate, it is essential to jointly implement a transitional strategy, including recycling incentives and subsidy policies. Additionally, elevating customer environmental awareness should be viewed as a long-term strategy, mitigating the cost of increasing collection rates during the market maturity stage (high collection rates).

Evaluating the carbon total factor productivity of China: based on Cobb-Douglas production function.

This paper introduces a novel methodology for estimating carbon total factor productivity based on the Cobb-Douglas production function. The research method introduced in this article expands upon the framework for assessing total factor productivity through the Solow residual method. It unifies the conceptual and methodological aspects of carbon total factor productivity with those of single factor productivity. Utilizing panel data from various provinces between 2010 and 2021, we computed carbon total factor productivity to understand its implications for China in combating global climate change. We demonstrate that (i) we have introduced a method to handle negative coefficients in the Cobb-Douglas production function by incorporating productivity in lieu of input factors during calculations. (ii) Carbon total factor productivity, encapsulating the geometric weighted mean of labor, capital, and carbon productivity, holds notable economic relevance. Further, it serves as an integrative metric comprising carbon productivity intertwined with the mean labor and capital carbon factors. And (iii) the influence of carbon total factor productivity growth on economic progression remains relatively subdued, with escalating labor force growth posing detrimental effects on several provincial economies. Enhancing carbon total factor productivity emerges as an imperative to harmonize robust economic growth with strategic carbon curtailment. Our analytical framework provides nuanced perspectives on productivity determinants, accentuating the thrust towards sustainable evolution amidst climatic challenges. This investigation bears profound significance for policymakers endeavoring to sculpt a carbon-conscious economic paradigm in consonance with global climatic ambitions.

The impact of digital economy on carbon total factor productivity: A spatial analysis of major urban agglomerations in China.

Amid global climate imperatives and intensified economic competition, pivoting from China's conventional growth paradigms to innovative economic catalysts emerges as pivotal for its transformative agenda. Drawing on panel data from 141 principal urban conglomerates spanning 2011-2021, this investigation delves into the intricate nexus between the digital economy and carbon total factor productivity. Our empirical analysis unveils a U-shaped trajectory characterizing the digital economy - carbon total factor productivity interplay, accompanied by a congruent spatial spillover dynamic. While digital economy fortifies environmental governance mechanisms through amplified data and media channels, such regulatory frameworks, albeit efficacious in emission abatement, may inadvertently impede economic vitality, thus attenuating carbon total factor productivity. Progressing from digital economy's foundational phase to its comprehensive deployment, its reverberations on capital productivity manifest in a U-shaped curve, invigorating local carbon total factor productivity while potentially undermining adjacent regions. This digital economy - carbon total factor productivity interrelation is accentuated in advanced, non-resource-reliant metropolises with subdued innovation propensities. This discourse proffers nuanced policy implications for sculpting digital economy trajectories and bolstering carbon total factor productivity in a sustainable context.

What determines the performance of low-carbon cities in China? Analysis of the grouping based on the technology-Organization-Environment framework.

BACKGROUND AND OBJECTIVES: Addressing climate change and reducing greenhouse gas emissions have emerged as shared global objectives. Enhancing the development performance of low-carbon cities has become an urgent and widely acknowledged concern for both government policy-making departments and academics. Drawing upon the complex grouping perspective and resource allocation theory, this study investigates how varying conditions related to technology, organization, and environment in Chinese low-carbon pilot cities can effectively allocate resources to shape the governance performance of low-carbon cities. METHODS AND DATA: This paper employs a comprehensive grouping analysis perspective, treating the research object as a combination of various ways between condition variables. It integrates the advantages of case studies and variable studies, and investigates the collective relationships between elemental groupings and outcomes using the fsQCA analysis method. This approach facilitates the understanding of multiple concurrent causal relationships within the technology-organization-environment (TOE) framework, accounting for different performance levels in Chinese low-carbon pilot cities, as well as addressing complex causal issues such as asymmetry and multiple scenario equivalence. Data from 30 representative low-carbon pilot cities in China were employed to validate the TOE theoretical framework. CONCLUSION: No single element alone can be considered a necessary condition for low-carbon city governance performance. However, environmental enhancement plays a more prominent role in the governance performance of low-carbon cities. Additionally, the presence of "multiple concurrent" technical, organizational, and environmental conditions leads to a diverse range of governance performance in Chinese low-carbon pilot cities. In other words, the driving paths of low-carbon city performance exhibit distinct pathways. CONTRIBUTION: The findings of this study can assist low-carbon pilot city managers in generating effective governance ideas, facilitating the successful implementation of low-carbon city pilot projects, and drawing valuable lessons from the experience of low-carbon city development in China.

Research on Motivational Mechanisms and Pathways for Promoting Public Participation in Environmental Protection Behavior.

Public participation in environmental protection is an essential component of evaluating the effectiveness of ecological and environmental protection. General awareness, social dynamics, and cognitive preferences frequently impact the protection's impact. The aim of this study is to investigate the correlation research on the confluence of mainstream awareness, social factors, and cognitive preferences by building a theoretical model. First, this work employs partial least squares structural equation modelling (PLS-SEM). Second, using the mediation model, the research describes and examines the factors that motivate public involvement in ecological and environmental conservation. Third, the research summarizes the suggested path countermeasures to offer practical advice and helpful ecological and environmental protection solutions. The findings demonstrate that mainstream policy leadership substantially impacts environmental conservation. Leadership in policy matters restricts the group's natural awareness of social factors. The subjective quality and competence basis in cognitive preferences are significantly influenced by policy leadership. Policy leadership significantly influences the effectiveness of environmental protection through the mediating factor of cognitive preferences. The ability base has a considerable mediating effect on cognitive preferences.

The influencing factors and spillover effects of interprovincial agricultural carbon emissions in China.

Agricultural carbon emissions have become the constraints of agricultural low-carbon and circular economy development in China. China's agricultural production faces severe pressures and challenges in agricultural carbon reduction. In this paper, we take observation for the 31 provinces in china from 1997 to 2017, to explore the influencing factors and spatial spillover effects of agricultural by estimating spatial panel data models. The results show that China's agricultural carbon emissions will continue to increase in the future, because the growth of per capita gross domestic product (GDP) is the main driving force to accelerate the growth of agricultural carbon emissions, but the agricultural input factors will help to reduce the growth of carbon emissions. Moreover, it is proved that economic factors and agricultural input factors have direct effects and spatial spillover effects on agricultural carbon emissions except for agricultural environmental factors. In the short term, strengthening environmental protection may bring some pressure to the economic development of some places, but to achieve high-quality development, we must fundamentally solve the problem of environmental pollution. The conclusion provides important enlightenment and scientific basis for formulating effective policies to curb the growth of CO2 emissions in China.

Research on China's embodied carbon transfer network in 2012 from the perspective of provinces and sectors.

Resource endowment and economic development of different provinces in China vary greatly, resulting in large amount of CO2 transfers. We need further exploration to help decision makers allocate emission responsibilities reasonably. We construct China's embodied CO2 transfer network (CTN) in 2012 from the perspective of provinces and sectors based on multi-regional input-output (MRIO) model and complex network analysis. The key CO2 transfer nodes and paths, final demand decomposition, topological structure, clustering characteristics, and influencing factors are analyzed. The results show that the average CO2 transfer length from one province (sector) to another is only 1.323 (1.584). The top three net CO2 importers (45.39% of the total), located in developed eastern coastal area, mainly import CO2 from energy-rich but underdeveloped provinces such as Heilongjiang. It presents a CO2 transfer pattern from north to south and from west to east. CO2 transfer in energy industry is mainly driven by urban household consumption. Non-adjacent provinces with distance greater than 750 km have no significant spillover effect and difference in technology level has the greatest impact on CTN. This work is important for differentiating the roles of provinces and sectors in CTN, guiding the allocation of carbon credits and controlling total CO2 emissions.

Antibiotics in coastal water and sediments of the East China Sea: Distribution, ecological risk assessment and indicators screening.

The distribution of 77 antibiotics in the coastal water and sediment from 3 bays of the East China Sea was investigated. There were 43 and 25 antibiotics detected with total concentrations of 30.8-2106.1 ng/L and 2.2-99.9 ng/g in water and sediment, respectively. Approximately 83.0% and 85.4% of the individual antibiotic concentrations were lower than 5.0 ng/L in water and 1.0 ng/g in sediment. Clindamycin (1.2-1507.9 ng/L, mean 183.8 ng/L) and erythromycin (ND-45.2 ng/g, mean 3.4 ng/g) were the most abundant in water and sediment, respectively. Ecological risk assessment revealed that the joint toxicity was enhanced when multiple antibiotics were present simultaneously. A decrease in the total antibiotic concentration and the ecological risk in water was observed from nearshore to offshore. Three antibiotics (sulfamethoxypyridazine, sulfamethoxazole and cinoxacin) were selected to be prioritized based on ecological risks for antibiotics monitoring and management of the coastal water in the East China Sea.

[Study on sustainable development of Tibetan medicine resources on Qinghai-Tibet Plateau].

Through using the theoretical research results of traditional Chinese medicine resource management and sustainable utilization as references,this article systematically analyzes the relationship between economic subsystems for utilization of wild renewable resources in Tibetan medicine,resources,environment and social systems. It sorts out and designs the relationship diagram of the sustainable utilization system for Tibetan medicine resources,input and output relationship diagrams of economics subsystems for Tibetan medicine resources,development model diagram for Tibetan medical industrial chain,market development flow chart of wild herb resources of Tibetan medicine,causal circuit diagram of sustainable use mechanism for Tibetan medicine resources,cause tree of the stock and function for Tibetan medicine resources,cause tree of total income for Tibetan medicine resource utilization and tree diagram of compensation fund usage of Tibetan medicine resources. It provides an innovative research method for Tibetan medicine resources,and theoretical basis and relevant countermeasure for constructing sustainable approaches to development of wild renewable resources in Tibetan medicine.

Air pollution characteristics in China during 2015-2016: Spatiotemporal variations and key meteorological factors.

With rapid economic development and urbanization, China has suffered from severe and persistent air pollution during the past years. In the work, the hourly data of PM2.5, PM10, SO2, NO2, CO, and O3 in all of the prefecture-level cities (336 cities) during 2015-2016 were collected to uncover the spatiotemporal variations and influential factors of these pollutants in China. The average concentrations of PM2.5, PM10, SO2, NO2, and CO decreased by 19.32%, 15.34%, 29.30%, 9.39%, and 8.00% from 2015 to 2016, suggesting the effects of efficient control measurements during this period. On the contrary, the O3 concentration increased by 4.20% during the same period, which mainly owed to high volatile organic compounds (VOCs) loading. The concentrations of PM2.5, PM10, SO2, CO and NO2 showed the highest and the lowest ones in winter and summer, respectively. However, the O3 concentration peaked in summer, followed by ones in spring and autumn, and presented the lowest one in winter. All of the pollutants exhibited significantly weekly and diurnal cycle in China. PM2.5, PM10, SO2, CO and NO2 presented the higher concentrations on weekdays than those at weekends, all of which showed the bimodal pattern with two peaks at late night (21:00-22:00) and in morning (9:00-10:00), respectively. However, the O3 concentration exhibited the highest value around 15:00. The statistical analysis suggested that the PM2.5, PM10, and SO2 concentrations were significantly associated with precipitation (Prec), atmosphere temperature (T), and wind speed (WS). The CO and NO2 concentrations displayed the significant relationship with T, while the O3 concentration was closely linked to the sunshine duration (Tsun) and relative humidity (RH). T and WS were major factors affecting the accumulation of PM and gaseous pollutants at a national scale. At a spatial scale, Prec and T played the important roles on the PM distribution in Northeast China, and the effect of Prec on CO concentration decreased from Southeast China to Northwest China. The results shown herein provide a scientific insight into the meteorology impacts on air pollution over China.