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We researched China's climate and sustainable development goal with relevant and susceptible instruments capable of inducing and mitigating carbon emissions. Amidst the contributor to the global carbon emissions, China is caught in between mitigating its carbon emission and aiming towards placing its national contribution of emissions to the acceptable levels of 1.5 °C and below 2 °C. Following the intricacies surrounding China's sustainable development as it contains its economic and environmental performance, we adopt China's data of 1980 and 2018 with different scientific approaches (nonlinear autoregressive distributed lag (NARDL), dynamic ordinary least square test, and bootstrap Granger causality) with different instruments (such as economic growth, financial development, renewable energy, and innovation policies) to research China's sustainable development. For clear exposition and insight into our findings with policies attached, we draw a conclusion from the outcomes of the mentioned approaches. From NARDL and dynamic ordinary least squares (DOLS), we find that economic growth through economic activities is statistically significant in determining the trend (increase) of carbon emissions in China in both periods (short run and long run). However, other selected instruments (financial, renewable, and innovation policies) tend towards controlling and moderating the carbon emissions in China. Thus, China has good prospects to mitigate its carbon emissions if considered tailoring its policies towards favorable instruments. From bootstrap Granger causality, we find similar inferential results that support previous findings thereby confirming the positive implication of the selected instruments to China's sustainable development. Hence, the nexus that is established among the selected instruments clearly show the importance of technological innovation and renewable energy in mitigating carbon emissions.

Biodiversity analysis underlies macroevolutionary studies and allows to identify mass extinctions. Numerous studies of mass extinctions show that geological factors play a central role in determining the diversity dynamics. The late Cretaceous extinction is of interest to science as the closest to us extinction of the five mass extinctions that occurred in the Phanerozoic. There is currently no scientific consensus on the scenario in which the extinction occurred on land. In order to assess the features of superorderDinosauriadevelopment during the Cretaceous-Paleogene, the authors have analysed the diversity of terrestrial taxa of Mesozoic dinosaurs. Based on data from the paleobiodb paleontological database using the Python programming language and its libraries, the features of the species diversity ofDinosauriahave been studied. An attempt was made to quantify the species diversity of this group based on the ratio of predators to herbivores using data on dinosaur food types. The simulated diversity data were compared with observed patterns and existing estimates. It is likely that less than one-third of the dinosaurs that existed are currently known, as indicated by the geography of the fossils, and the proportions of dinosaurs by type of diet.

Closed-loop supply chain networks are gaining research popularity due to environmental, economic and social concerns. Such networks are primarily designed to overcome carbon footprints and to retrieve end of life products from customers. This study considers a multi echelon closed-loop supply chain in the presence of machine disruption. A multi-objective model is presented to optimize the total cost, the total time and emissions in a closed-loop supply chain network. The aim is to analyze the trade-off between the objectives of cost, time, and emissions and how these decisions are impacted by the selection of different available machines. A number of solution approaches are tested on a case study from the tire industry. The results suggest the improved performance of the hybrid heuristic and the importance of controlling disruption in a closed-loop supply chain network. Furthermore, there is a trade-off between the different objective functions which can help the decision maker to choose a particular solution according to the preference of an organization. Finally, conclusion and future research avenues are provided.

Abstract Mitigating the effects of environmental deterioration requires a focus on not just CO2 emissions from energy consumption, but also environmental pollution from industry sectors. To reach this goal, recent studies have extended ecological footprint (EF) analysis to identify the ecological drivers of various key industry sectors. The role of the phosphorus (P) industry on the EF within the environmental Kuznets curve (EKC) framework for China is the emphasis of this study. Autoregressive distributive lag (ARDL) as well as the impulse response function and robustness analysis were used to consider a time from 1985 to 2018. The study verifies the EKC hypothesis for China in both the long and the short run, and indispensable determinants are proposed to be included to assure the model’s fitness and robustness when conducting EF analysis of industry sectors. Energy consumption–based carbon emissions have been verified as the dominant contributor to EF, but P use and urbanization have a significant lagged positive influence on EF in the short run. P exports, in particular, have been highlighted as a critical driver of the EF of China’s P industry. The conducted frequency domain causality test reinforced the above findings and demonstrated bidirectional causality at different frequencies. This work suggests that formulating plausible P export policies to alleviate the conflict between the output of China’s P industry and the environmental sustainability of this industry are necessary. In this context, “multidisciplinary, multidimensional, and practical solutions” are most desirable for sustainable P management.

The concept of the “Energy strategy of Russia for the period up to 2035” implies a comprehensive structural transformation of the energy sector and its transition to a qualitatively new level through the use of digital technologies. One of the first steps in building a model of the Internet of energy in Russia may be the introduction of a mechanism for creating industrial microgrids, for which a draft resolution of the government of the Russian Federation has already been developed. The article considers the features of functioning of a new subject of electric power industry - active energy complexes, their conceptual, economic and legal features, and also developed a method for evaluating the system effects of their implementation.

The purpose of the article is to study the dynamics of volumes and stability of the structure of energy resource consumption at manufacturing enterprises, the analysis of the technical readiness of energy systems to implement the ideas of digital transformation. As the main research methods used in this article there are the method of dipole energy analysis to determine the priority of types of energy carriers, the method of graphical visualization of data to find the release points of values from the zone of relative stability, the method of classifying objects to assign products to a group of objects on the level of energy sustainability. The article analyzes the current trends in energy consumption with the determination of the vector of sustainable energy consumption and the parameters of reserves for improving energy efficiency; prioritized separate types of energy production of petrochemical plants; the types of products were classified according to the level of sustainability of energy consumption with the establishment of control points having emissions of values from the zone of relative stability and unproductive consumption of energy resources; the high technical readiness of energy systems of manufacturing industries to automate production processes with the subsequent development of digital technologies has been proved.

The construction industry is considered as one of the least productive, highest energy consuming, and least digitized industries. The Lean Management (LM) philosophy became a significant way for eliminating non-value-added activities and wastes during a building’s lifecycle. However, studies have shown that philosophies are not efficient by themselves to solve the issues of the construction industry. They need to be supported with the appropriate technologies and tools. Therefore, the integrated use of Building Information Modelling (BIM) with LM or Value Engineering (VE) were proposed in the literature. Nonetheless, it was also seen that BIM can provide more insights and improvements when BIM is integrated with data analysis tools to analyze BIM data. In the literature, the synergies between these concepts are generally addressed pairwise, and there is no comprehensive framework which identifies their relationships. Therefore, this study aims to develop a maturity framework that facilitates the adoption of LM, VE, BIM, and Big Data Analytic (BDA) concepts to address long-standing productivity and digitalization issues in the Architecture, Engineering, and Construction (AEC) industry. Design Science Research (DSR) methodology and its three-cycle view (relevance, rigor, and design cycle) were applied to build the proposed maturity framework. Two interviews were performed to identify and observe research problem in relevance cycle. In the rigor cycle, a comprehensive literature review was performed to create a base for the development of the maturity framework. In addition to the developed base of the framework, lean processes were added to this cycle. In the design cycle, the developed framework was evaluated and validated by five experts through face-to-face interviews. The importance of employer’s requirements to adopt the proposed methodologies, the negative impact of change orders, the importance of pre-construction phases to facilitate value creation and waste elimination, and the usage of common data environment with BIM were identified as the prominent application and adaptation issues.

The occurrence and development of reefal carbonates depend on biological activity and depositional conditions. Besides of fossil assemblages, it is also critical to determine depositional parameters of environment such as sea level change, substratum or clastic input.  This study is realised on an important reefal carbonate units as known the Kaplankaya and Karaisalı formations in the Değirmençay locality of Mersin Province, Mediterranean. In this study, the ostracod and foraminifer assemblages were determined in the samples collected from reefal carbonate units of the Early-Middle Miocene age.  The base of the investigated area consists of Upper Cretaceous ophiolite and Upper Cretaceous-Palaeocene ophiolitic mélange. These units are unconformably overlain by Miocene sediments. This study determine ostracod and foraminifera assemblages of the Early-Middle Miocene reefal carbonate system. While abundance ostracod species were observed at the reefal carbonate levels, also a few planktonic foraminifer species. As a result of paleontological studies, 12 genera and 15 species from Ostracoda, 3 genera and 3 species from planktonic foraminifera have been determined. The Ostracoda species (Aurila soummamensis, Hemicyprideis villandarutensis), and planktonic foraminifer species (Globigerinoides trilobus, Globoquadrina dehiscens and Orbulina universa) point out that these reefal carbonates deposited at the Early-Middle Miocene time interval.