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Technological innovation in the new energy vehicle industry is conducive to the achievement of China’s major strategic goal of ‘carbon peak and carbon neutrality’. This research involved an empirical study on the relevant data of 14 listed new energy vehicle companies from 2012 to 2019. It used the entropy weight method to obtain the technological innovation index through the four indicators of research and development (R&D) investment, fixed asset investment, intangible assets, and patent application volume. Taking fiscal subsidies and tax burdens as independent variables, a fixed effect model was used to analyze the impact of fiscal and taxation policies on technological innovation in the new energy vehicle industry. The research results show that financial subsidies will encourage new energy vehicle companies to carry out technological innovation, the tax burden has no significant impact on the technological innovation of new energy vehicle enterprises, the scale and age of enterprises, as well as the proportion of R&D personnel to the total number of employees, will all encourage new energy vehicle companies to carry out technological innovation. Based on this, we put forward specific suggestions on further improving the fiscal subsidy and tax incentive policies.

One of the goals of developing a transport corridor is to promote socio-economic development by improving connectivity and sustainable transport operations, which largely depends on the operational strategy. Trade-off policies can be important tools for gaining the competitive advantage of road transport corridors, and thus, help facilitate sustainable growth and welfare. This article uses a case-based approach to observe the trade-offs in the first phase of transport infrastructure development, and then, in the second stage, further explores the trade-off variables in the transport operations strategy under the China-Pakistan Economic Corridor (CPEC). The results from the three cases of the parallel route system of the CPEC indicate that trade-off is an easily understandable and applicable method, which can foresee the operational gains or compromises for significant welfare of the regions. The implications of the trade-off are two fold, first is the “importance” of the trade-off, which is related to its impact on operational competitiveness. The other is the “sensitivity” of the trade-off, in terms of the change that will be caused to one variable when changing the other. The trade-off concept can be used for several landlocked transport corridors to achieve a competitive edge in transit trade.

Abstract The rapid urbanization in the Belt and Road Initiative (BRI) area has aggravated the cross-regional pollution of PM2.5 and aroused concern about the conflicts between urban development and air quality. This study aims to examine the spatial-temporal PM2.5 variations in the BRI region, in which area many countries are undergoing rapid urbanization and the main field of future urbanization, to delineate the driving mechanism of PM2.5 accumulation or dissipation. Previous studies have analyzed the PM2.5 distribution at the national level, providing limited information regarding regional heterogeneity in urbanization and PM2.5 concentrations within each country. Additionally, the regional differences in the driving mechanisms of urbanization factors on PM2.5 concentrations have not been thoroughly investigated within the BRI areas. In this study, remote sensing raster data was combined with geographic grid units to examine variations in urbanization and PM2.5 within the BRI region, identifying “typical regions” where urbanization could enhance PM2.5 accumulation. The main results are as follows: i) The spatial autocorrelation of urbanization and PM2.5 concentrations has gradually strengthened, showing consistent high-value distributions in the North China Plain, Ganges Plain and indicating a synergistic growth among emerging developing regions such as China, India, and the Persian Gulf Coast. ii) The correlation between urbanization and PM2.5 concentrations exhibited a distinct trend of differentiation within the BRI regions. The influence of urbanization on PM2.5 changed from agglomeration to dispersion, forming a “typical region” category composed of ten countries, including China, India, and Morocco. iii) The three main urbanization-related factors for PM2.5 accumulation in the “typical regions” for 2005–2016 were energy pollution emission, economic activities, and human activities. By 2023, the effects of energy pollution and economic activities are expected to converge in some “typical region” countries. Targeted urban strategies and governance actions based on the different driving-types of “typical regions” in BRI have been proposed to coordinate relationship between urban construction and atmospheric environmental protection.

In open innovation platforms, users learn external knowledge through network interaction, and their position in the interactive network has an impact on the user’s sustainable knowledge contribution. Due to the gap in knowledge level, users’ absorption and utilization efficiency of external knowledge is not consistent. We studied the differences in user sustainable knowledge contribution behavior from the perspective of knowledge absorption. We crawled the data of a typical open innovation platform, used LDA to identify the level of user knowledge diversity and social network technology to analyze the user’s network location, and used the negative binomial regression model for empirical analysis. Our results show that knowledge diversity positively affects user knowledge contribution, and network breadth and network depth have positive and negative effects on user knowledge contribution behavior, respectively. In addition, the level of user knowledge diversity moderates the influence of network location on knowledge contribution. In summary, this research not only provides a comprehensive perspective on our current understanding of the contribution behavior of open innovation platforms, but also provides an in-depth understanding of how open innovation platforms can be properly designed to promote continuous contributions.

Under Smart Grid circumstance, the problem that the large grid system is difficult to schedule can be solved by the micro-grid. Meanwhile, the shortage of traditional energy makes the demand-supply gap enlarge and renewable energy will become the primary energy supply in the future. Therefore, the study on how to expand renewable energy in the co-generation system in micro-grid is of great significant and valuable. In this paper, the minimum total cost of the expansion plan and the improvement of micro-grid reliability are taken as the optimal goal. The expansion planning model of the wind-thermal co-generation system is established, which uses the Harmony Search (HS) and the Genetic Algorithm (GA) to simulate a micro-grid with five nodes in a decade respectively. The comparison results of the simulation results show that the expansion planning model of the co-generation system with the HS method is more feasible and effective than that with GA. Through the research on the expansion planning of wind-thermal co-generation system, it can provide the decision support and reference for the long-term expansion planning of co-generation system in micro-grid under the Smart Grid.

The construction industry consumes a tremendous amount of energy and resources each year in China. It is imperative to implement sustainable management in this industry in order to reduce the depletion of energy and resources. To conduct a sustainable development, this paper firstly describes the current energy consumption situation in China. The urgency for conducting sustainable management is emphasized. Afterward, evaluation standard for a green building in China is described. By using a life cycle method, specific measures which can be implemented to construct a green building are issued. It is concluded that as more and more attentions are being paid on this topic, sustainable building in China will get a rapid development in the coming years.

In the era of sustainable development, glass-fiber reinforced polymer (GFRP) composites have made their way into modern engineering, construction, and building sectors due to their exponential characteristics. While considering the rapid growth and development in this sector, this research has assessed the relative environmental and techno-economic sustainability of two sorts of GFRP composite technologies: (a) filament winding and (b) pultrusion to effectively appraise their application, merits, and demerits. This study will help low-middle-income countries like Pakistan toward cleaner production, environmental management, and sustainable industrial development. The techno-economic sustainability is determined by using life cycle costing and techno-economic indicators, i.e., benefit-cost (B/C) ratio, net present value (NVP), internal rate of return (IRR), and payback period. The B/C ratio depicts the relationship between the relative cost and benefits of a technology, and NVP expresses the calculated present value of the future payback stream of a technological investment, while the IRR is an effective techno-economic indicators which can predict the efficacy of an investment, and the payback period is the time forecast for a technology to recover its investments. These techno-economic analytics showed that the net life-cycle cost performance, B/C ratio, and IRR are 5%, 7%, and 15% higher respectively for filament winding-based GFRP technology than the pultrusion-based manufacturing technology, whereas overall net life cycle benefits are about 80% greater for filament winding. Similarly, the payback time is shorter for filament winding compared to pultrusion. The environmental sustainability is determined, by employing a relative life cycle analysis (LCA) for both technologies. The system boundary for the study is "gate to gate," i.e., manufacturing phase, where these technologies are assessed for their environmental externalities. The functional unit of "1 kg finished product," i.e., manufactured by pultrusion and filament winding technology, and eight life cycle impact assessment (LCIA) categories; climate change potential (CCP), terrestrial eco-toxicity potential (TETP), ozone depletion potential (ODP), fossil resource depletion potential (FDP), acidification potential (AP), eutrophication potential (EP), particulate matter (PM) formation, and water consumption potential (WCP) have been selected. The significant ecological impact scores are determined in the categories of CCP (kg CO2 eq.) as 10.8E + 00 and 5.01E + 00 and ETP (kg. 2,4-D eq.) as 1.26E-02 and 9.47E-03 and FDP (kg Oil eq.) as 3.96E + 00 and 2.59E + 00 for filament winding and pultrusion-based GFRP technologies, respectively. These LCIA results depicted that the ecological performance of filament winding technology is specifically better than pultrusion technology in the categories of EP, PM, and WCP, while, for all other life cycle impact categories, the pultrusion technology has depicted significantly lower impact potential and is environmentally more sustainable. The outcomes of this research will be greatly assistive for researchers, developers, manufacturers, and policymakers to effectively appraise the externalities and selection of a more sustainable GFRP technology.

This paper focuses on energy efficiency that is a key performance metric in heterogeneous cellular networks to two key areas. First, based on the Poisson point process distributions of small-cell base stations (SBSs) and macrocell base stations (MBSs), the energy-efficiency model is formulated, and the effect of base stations’ distribution on energy efficiency is analyzed. For maximizing energy efficiency, the joint optimal densities of SBSs and MBSs are deduced under the constraint of quality of service. Second, according to this, we propose a joint sleep strategy of MBSs and that of SBSs. We deduce the optimal threshold of traffic load according to the joint optimal densities. If the traffic load of SBSs (or MBSs) is less than the optimal threshold of traffic load, these SBSs (or MBSs) go to sleep; otherwise, it is activated. This makes the SBSs and MBSs adaptively and distributively sleep according to their own traffic loads. The simulation results verify that the deduced joint optimal densities of the SBS and the MBS are accurate, and energy efficiency is improved when SBSs and MBSs adaptively sleep.