Spatiotemporal characteristics analysis of multi-factorial air pollution in the Jing-Jin-Ji region based on improved sequential ICI method and novel grey spatiotemporal incidence models.

Air pollution shares the attributes of multi-factorial influence and spatiotemporal complexity, leading to air pollution control assistance models easily falling into a state of failure. To address this issue, we design a framework containing improved data fusion method, novel grey incidence models and air pollution spatiotemporal analysis to analyze the complex characteristics of air pollution under the fusion of multiple factors. Firstly, we improve the existing data fusion method for multi-factor fusion. Subsequently, we construct two grey spatiotemporal incidence models to examine the spatiotemporal characteristics of multi-factorial air pollution in network relationships and changing trends. Furthermore, we propose two new properties that can manifest the performance of grey incidence analysis, and we provide detailed proof of the properties of the new models. Finally, in the Jing-Jin-Ji region, the novel models are used to study the network relationships and trend changes of air pollution. The findings are as follows: (1) Two highly polluted belts in the region require attention. (2) Although the air pollution network under multi-factorial fusion obeys the first law of geography, the network density and node density exhibit significant variations. (3) From 2013 to 2021, all pollutants except O3 show improvement. (4) Recommendations for responses are presented based on the above-mentioned results. (5) The parameter analyses, model comparisons, Monte Carlo experiments and model feature summaries illustrate that the proposed models are practical, interpretable and considerably outperform various prevailing competitors with remarkable universality.

A novel grey projection incidence model for assessing the relationships between cardiovascular diseases and air pollutants.

The accurate assessment of the relationships between cardiovascular diseases and various air pollutants is essential for population health protection, especially in low- and middle-income countries or regions with poor air quality and dense populations. In view of this situation, we propose a novel grey incidence model, namely, the grey projection incidence model based on Gaussian function, by integrating the advantages of geometric projection and Gaussian function. Firstly, the basic principles of the proposed model are elaborated. Then, a framework including six steps to evaluate the relationships between CVDs and air pollutants is illustrated. Finally, a case study is utilized to validate the effectiveness of the proposed model. Experimental results show that the proposed model outperforms other grey incidence models in terms of reliability and stability of the relational rank.

What inhibits regional inclusive green growth? Empirical evidence from China.

The diversity of locations, environment, and resource elements among different regions leads to the regional imbalance of inclusive green growth (IGG), especially in those developing countries like China. A core issue for achieving the coordination of regional IGG is to identify what influence factors with what extent to inhibit IGG levels of different regions. In this paper, a comprehensive IGG indicator system is designed based on the IGG connotation from four dimensions of economic development, social opportunity equity, green production and consumption, and ecological environment protection. An improved TODIM method is proposed to measure the regional IGG level and further reveal the inhibition effects of various influence factors on regional IGG. The results exemplified by China's 30 provinces during 2008-2018 show that China's eastern provinces possess more superior IGG levels, while the catch-up effect of IGG in central and western provinces is significant. The lower economic output, larger income gap, and weaker green production and consumption restrict the IGG of most western provinces. The higher economic and population agglomerations in eastern and central provinces challenge the ecological resource endowment and environment governance, which inhibits their IGG development. The inhibition effects of social opportunity equity involving employment, education, medical treatment, social security, and infrastructure on IGG levels do not reflect obvious regional agglomeration.

Optimal path for overcoming barriers in developing China's wind energy industry.

Developing the wind energy industry (WEI) has been a long-term strategy in China for responding to the energy crisis and greenhouse gas emissions. However, China's WEI faces various barriers despite its favorable prospects. This paper aims to propose a path analysis approach for exploring the best methods and timing for overcoming diverse barriers in developing WEI systematically, especially in terms of revealing in which phases these barriers should take priority. A multidimensional barrier set categorized by institutional, economic and financial, social, technical, and market factors is identified via the integration of a literature review and empirical interviews. A path analysis approach based on the grey group DEMATEL-NK model is constructed, where the causalities and intensities among barriers are extracted to design a path simulation algorithm with heuristics. The optimal path for overcoming barriers in developing the WEI is generated through a simulation of the search and optimization process used to climb to the fitness landscape peak. The results show that the different barriers to completing the legal and regulatory framework should be prioritized to reach adequate financial incentives and coordination among stakeholders, and that an efficient talent cultivation system should be developed and industry-academic cooperation should be strengthened to increase technical and R&D capabilities in the short term. The optimal path presents a strategic instrument for managers to use to better develop sustainable and clean wind energy systems from the novel insights of prioritizing to overcome barriers.

A grey spatiotemporal incidence model with application to factors causing air pollution.

The factors causing air pollution in China has caused extensive concern, but there are still many problems in the grey incidence model of identifying air pollution factors. The results produced by the existing grey incidence models are not stable when the order of objects in a given panel data is changed. In order to improve the reliability and uniformity of the grey incidence model, a new grey incidence model, called the grey spatiotemporal incidence model, abbreviated as the GSTI model, is designed in this paper. In the proposed model, the spatiotemporal data which can represent the spatial relationship among different objects rather than the three-dimensional panel data are defined. In addition, the new model includes two procedures. Firstly, the trend coefficient is used to measure the positive and negative connections between two data sequences. Secondly, the measurement coefficient is utilized to calculate the size of grey incidence degree. Subsequently, five properties of the GSTI model are discussed. To demonstrate its practicability and compatibility, the novel model is utilized to identify south Jiangsu province's main factors causing air pollution according to monthly data for 2018. The abundant comparison shows the applicability and superiority of the model in the identification of air pollution factors and the construction of grey incidence model.

A Decision-Making Method with Grey Multi-Source Heterogeneous Data and Its Application in Green Supplier Selection.

In view of the multi-attribute decision-making problem that the attribute values are grey multi-source heterogeneous data, a decision-making method based on kernel and greyness degree is proposed. The definitions of kernel and greyness degree of an extended grey number in a grey multi-source heterogeneous data sequence are given. On this basis, we construct the kernel vector and greyness degree vector of the sequence to whiten the multi-source heterogeneous information, then a grey relational bi-directional projection ranking method is presented. Considering the multi-attribute multi-level decision structure and the causalities between attributes in decision-making problem, the HG-DEMATEL method is proposed to determine the hierarchical attribute weights. A green supplier selection example is provided to demonstrate the rationality and validity of the proposed method.