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The global population influx during the COVID-19 pandemic poses significant challenges to public health, making the prevention and control of infectious diseases a pressing concern. This paper aims to examine the impact of population influx on the spread of infectious diseases, with a specific emphasis on the mediating role of air pollution in this process. A theoretical analysis is conducted to explore the relationship between population influx, air pollution, and infectious diseases. Additionally, we establish a series of econometric models and employ various empirical tests and analytical techniques, including mediation effect test, threshold effect test, and systematic GMM test, to evaluate our hypotheses. The results indicate that: (1) Population influx directly and indirectly impacts infectious diseases. Specifically, population influx not only directly elevates the risk of infectious diseases, but also indirectly increases the incidence rate of infectious diseases by intensifying air pollution. (2) The impact of population inflow on infectious diseases exhibits regional heterogeneity. Compared to central and western China, the eastern regions exhibit a significantly higher risk of infectious diseases, exceeding the national average. (3) External factors influence the relationship between population influx and infectious diseases differently. Personal income and medical resources both help mitigate the risk of infectious diseases due to population influx, with medical resources having a more substantial effect. Contrary to expectations, abundant educational resources have not reduced the risk, instead, they have exacerbated the risk associated with population influx. This paper provides a scientific basis for formulating effective strategies for the prevention and control of infectious diseases.

Carbon emissions and air pollutant emissions in China share common sources. A thorough examination of carbon and pollutant emissions is imperative for a comprehensive understanding. This study aims to assess carbon-pollutant emissions efficiency (CPEE) in 30 Chinese provinces from 2006 to 2020, focusing on the integration of carbon and air pollutant emissions. Previous research on CPEE is limited, and this article addresses this gap by investigating its spatiotemporal characteristics and identifying potential influencing factors. Our study employs a super-efficiency data envelopment analysis model, social network analysis, and spatial econometric models. The results indicate that: (1) During the research period, provincial CPEE in China follows a “W-shaped” trend and exhibits a “bimodal” asymmetric distribution, indicating notable regional heterogeneity. (2) Although spatial correlations are unstable and do not adhere to a strict hierarchical structure, positive spatial spillover effects are evident in the CPEE. (3) The spatial correlation network of CPEE displays various characteristics, including the Matthew effect, external preference, siphoning effect, and altruistic tendency. (4) Apart from technical input, explanatory variables affecting CPEE exert a significantly negative direct impact. Furthermore, the indirect effect of energy intensity on CPEE contradicts its direct effect when economic distance is considered in the spatial weight setting. These findings provide valuable theoretical insights and practical guidance for improving CPEE and its synergistic effects.

Urban green spaces have long been cherished as the “lungs of the city”, it can not only improve air quality and enhance residents' health. The impact of urban green spaces on air pollution and residents' health has attracted great attention. In this paper, we select 31 provinces in China as research samples and use ArcGIS software to draw spatial distribution maps of urban green spaces, air pollution, and residents' health in China, characterizing their spatiotemporal changes in order to explore whether there is a correlation among the three. On this basis, this paper utilizes panel data of Chinese provincial-level from 2010 to 2020 and conducts empirical tests through a two-way fixed effect model and a threshold regression model. The research findings are as follows: (1) Urban green spaces not only bring environmental benefits, but also health benefits, and the health benefits are greater than the environmental benefits. (2) There is a health risk of air pollution in northern China, and the health benefits of urban green spaces are not significant. Conversely, there is no health risk of air pollution in southern China, and the health benefits of urban green spaces are significant. (3) Although environmental regulations can enhance the health benefits of urban green spaces, the role of environmental regulations in enhancing the health benefits of urban green spaces may be further weakened as the economy develops.

Global climate change could pose an additional threat to the already vulnerable Gentiana macrophylla. To reduce this emerging climate-related threat, we applied ArcGIS and the maximum entropy method (MaxEnt) to analyse the consequences of climate change on the distribution of G. macrophylla and the vulnerability of this species in China. The modelling results indicate the following: (1) the suitable range of G. macrophylla in China is mainly located in the Loess Plateau hinterland, including the provinces of Shaanxi, Gansu, Shanxi, Ningxia, Hebei and Inner Mongolia, under the current climate conditions; (2) the unsuitable habitats for G. macrophylla in China would increase by 11.92% under the moderate greenhouse gas emissions/climate scenario (RCP4.5) by the 2050s, while significant losses of suitable habitat are predicted to occur; (3) the current suitable habitat mainly located in the Loess Plateau, Great Xingan Mountains, Changbai Mountains and Hengduan Mountains (with a total area of 135.09×104 km2) is predicted to be vulnerable. Climate change will further accelerate the speed of the fragmentation of the vast majority of G. macrophylla suitable habitat, threatening the survival and reproduction of this species in this region. Therefore, some proactive conservation measures should be undertaken to mitigate the adverse effects of climate change. Our findings can be used to provide background information related to the long-term conservation of G. macrophylla.

Erigeron canadensis L., an alien invasive plant originating from North America, has already invaded Chongqing, Sichuan, Taiwan, and some other areas in China. It causes damage to the local ecosystems and has demonstrated great potential for invasion. With the use of occurrence points, this study combined the maximum entropy niche model with geographic information system to comprehensively analyse the influencing factors affecting the distribution of E. canadensis and to quantitatively and intuitively predict its potential distribution range in China. The prediction was verified by the receiver operating characteristic (ROC) curve analysis method, and the results showed that E. canadensis had a wide range of potential distribution regions in China, with the main suitable regions in Taiwan, Hainan, and Guangdong. The current actual distribution is far from the maximum potential distribution range, and it is still likely to continue to spread. The ROC curve results showed that the MaxEnt model had a high prediction accuracy and that the results were credible. Temperature and precipitation could be the main influencing factors affecting the potential distribution of E. canadensis. We should attach great importance to the dangers of E. canadensis, take measures to eliminate the current population in China, and strictly monitor the invasion and spread of E. canadensis. to its most suitable possible distribution region. Keywords: Invasive species, Erigeron canadensis L., MaxEnt model, Potential distribution

As an invasive alien species, Alternanthera philoxeroides has spread rapidly in China since its invasion, which has caused serious harm to the ecological environment and substantial economic losses. To better manage this invasive plant, we analysed the spatial and temporal distribution patterns and predicted the suitable areas for this species in China using the MaxEnt model and ArcGIS. The results showed that the suitable area for A. philoxeroides in the current climatic conditions was 91.8–122.7°E,18.2–39.8°N, which was mainly located in the tropical, subtropical and southeastern warm temperate regions of China. The high suitability region is mainly located in the provinces of Guangxi, Shanghai, Jiangsu, Chongqing and Sichuan. The total areas with low, medium, and high suitability are 90.13×104km2, 99.78×104km2, and 23.33×104km2, respectively. All of these suitable regions cover a total of 213.24×104km2, accounting for 22.2% of China’s land area. A. philoxeroides has a tendency to continue to invade. Precipitation and temperature are the primary variables shaping the distribution of A. philoxeroides. This species prefers a warm, stable and rainy climate. Measures should be taken to prevent it from spreading to these high suitability regions. Moreover, biological and ecological prevention and control technologies are necessary to block its spread, invasion, colonization and damage, especially in the potentially suitable regions with suitable climates. Keywords: Alternanthera philoxeroides, MaxEnt, Invasion, Spatial region distribution