Assessing environmental interference in northern China using a spatial distance model: From the perspective of geographic detection

Co-benefits and influencing factors exploration of air pollution and carbon reduction in China: Based on marginal abatement costs

This study addresses the pressing need for cost-effective emission reduction strategies that maximize co-benefits in terms of air pollution and carbon emissions. Our research contributes to the literature by accurately measuring these co-benefits, thereby facilitating their prompt realization in different regions. We employ an input-output framework that integrates carbon emissions and air pollution, allowing us to calculate marginal abatement costs using the shadow price of undesired output. Through this approach, we quantify the co-benefits and analyze the factors influencing them at both spatiotemporal and factor levels using spatial kernel density and geographical detectors. Our findings reveal several key insights: (1) under joint emission reduction efforts, we observe average annual reduction rates of 6.46% for marginal pollution and 6.10% for carbon reduction costs. Importantly, we document an increase in co-benefits from 0.50 to 0.86, characterized by an initial fluctuation followed by a linear increase. (2) the marginal cost difference for carbon emission and pollution reduction in western China was 179.45 and 155.08 respectively, compared to 321.51 and 124.70 in the Northeast, highlighting the crucial role of regional differences in shaping co-benefit outcomes. (3) we identify a negative spatial spillover effect between provinces, which diminishes over time, leading to heterogeneous effects when local provincial co-benefits exceed a threshold of 0.9. (4) during the adjustment period, we find that the industrial structure exerts significant single and interactive effects on co-benefits. Additionally, we highlight the critical role of environmental governance investment and government intervention as drivers of co-benefits in the current era. By offering the quantification of co-benefits under the marginal abatement costs, our study provides valuable scientific insights for planning and implementing effective synergy strategies.

Spatial variation of soil seed banks along a gradient of anthropogenic disturbances in tropical forests on coral islands

Poor regeneration of natural vegetation is a major factor contributing to the degradation of tropical coral islands. Soil seed banks (SSB) are important for maintaining the resilience of plant communities. However, the community characteristics and spatial distribution of SSBs and the controlling factors along human disturbance on coral islands are unclear. To fill this gap, we measured the community structure and spatial distributions of forest SSBs on three coral islands in the South China Sea, with varying degrees of human disturbance. The results showed that strong human disturbance increased the diversity, richness, and density of SSBs, as well as increased the richness of invasive species. With increased human disturbance, the heterogeneity pattern of SSBs spatial distribution changed from difference between forest east and west to forest center and edge. The similarity between the SSBs and above-ground vegetation also increased, and the distribution of invasive species extended from the edge to the central area of the forests, demonstrating that human disturbance limited the outward dispersal of seeds of resident species but increased the inward dispersal of seeds of invasive species. Interaction between soil properties, plant characteristics, and human disturbance explained 23-45% of the spatial variation of forest SSBs on the coral islands. However, human disturbance reduced the correlations of plant communities and spatial distribution of SSBs with soil factors (i.e., available phosphorus and total nitrogen) and increased the correlations of the community characteristics of SSB with landscape heterogeneity index, road distance, and shrub and litter cover. Resident seed dispersal on tropical coral islands might be enhanced by reducing building height, constructing buildings in down-wind locations, and preserving corridors that support animal movement among forest fragments.

The resilience of ecosystems to drought

In this commentary, we summarize the contributions of Yao et al. in the study of resilience of ecosystems to drought and point out future research directions that need further attention.

Assessing Snow Phenology and Its Environmental Driving Factors in Northeast China

Snow cover is an important water source and even an Essential Climate Variable (ECV) as defined by the World Meteorological Organization (WMO). Assessing snow phenology and its driving factors in Northeast China will help with comprehensively understanding the role of snow cover in regional water cycle and climate change. This study presents spatiotemporal variations in snow phenology and the relative importance of potential drivers, including climate, geography, and the normalized difference vegetation index (NDVI), based on the MODIS snow products across Northeast China from 2001 to 2018. The results indicated that the snow cover days (SCD), snow cover onset dates (SCOD) and snow cover end dates (SCED) all showed obvious latitudinal distribution characteristics. As the latitude gradually increases, SCD becomes longer, SCOD advances and SCED delays. Overall, there is a growing tendency in SCD and a delayed trend in SCED across time. The variations in snow phenology were driven by mean temperature, followed by latitude, while precipitation, aspect and slope all had little effect on the SCD, SCOD and SCED. With decreasing temperature, the SCD and SCED showed upward trends. The mean temperature has negatively correlation with SCD and SCED and positively correlation with SCOD. With increasing latitude, the change rate of the SCD, SCOD and SCED in the whole Northeast China were 10.20 d/degree, −3.82 d/degree and 5.41 d/degree, respectively, and the change rate of snow phenology in forested areas was lower than that in nonforested areas. At the same latitude, the snow phenology for different underlying surfaces varied greatly. The correlations between the snow phenology and NDVI were mainly positive, but weak correlations accounted for a large proportion.

Spatial distribution, risk assessment and influence factors of terrestrial gamma radiation dose in China

The current spatial distribution of the risk of terrestrial gamma radiation in China were investigated by using spatial interpolation. And the driving factors influence on the terrestrial gamma radiation dose (TGRD) distribution were identified using the geographic detector, a new statistical method based on the nonlinear hypothesis. The results showed that the values of TGRD were range from 60 to 195 nGy h^-1 with the average of 86.5 nGy h^-1, and the higher values were recorded in Qingahi-Tibet Plateau, which were all within the range of background value in China. In addition, the radiological indices, ELCR (Excess Lifetime Cancer Risk), TGRD and AEDE (Annual Effective Dose Equivalent) were also within the acceptable range of values by risk assessment. The results by use of the geographic detector showed that sunshine duration, atmosphere pressure, altitude, and rainfall condition have closely related to the TGRD distribution. In addition, these meteorological factors and altitude had more impact on TGRD than the air pollution-related factors. Our study can provide useful information on studying the influence mechanism of the TGRD distribution, the variability of the natural terrestrial gamma radiation in China, and exposure data for risk assessment from low dose chronic exposures.