ABSTRACT
The county is the basic administrative unit of China, and the spatialization of carbon budget at the county scale plays an irreplaceable role in deepening the understanding of the carbon emission mechanism and spatial pattern. Yueqing County, an economically developed county in the Yangtze River Delta of China, was selected as the study area, the spatial pattern of the carbon budget and the optimal resolution of the spatialization at the county level were dissected on the basis of accurate accounting, and driving factors of carbon emissions were further identified using the geographically weighted regression model. The results indicated that (1) the carbon emissions were mainly generated from fossil fuel combustion related to energy, accounting for 98.8% of the total carbon budget in the study area; (2) the optimal resolution of spatialization was 200 m and carbon emissions were concentrated in the southeast of the study area; (3) energy intensity, energy structure, per capita GDP, and urbanization rate were positively correlated with carbon emissions, while population played a bidirectional role in carbon emissions. This study not only strengthens the understanding of the patterns and drivers of the carbon budget but also establishes a theoretical framework and operational tools for policymakers to formulate solutions to mitigate the carbon crisis.
ABSTRACT
Heavy metal pollution is a notable threat to agricultural production. Soil heavy metal pollution can cause potential ecological risk (ERI), and crop heavy metal pollution can cause human health risk (HRI). However, most previous studies partially focused on heavy metal pollution in soil or crop but often neglected the relationship between them. Actually, soil heavy metal can pollute crops to some extent, while not all heavy metal pollution in crops comes from soil. The inner relationship of pollution risk in soil-crop system is worth attention. In this study, we selected Ningbo as the study region and used sample data to assess both soil and crop heavy metal risks, in order to explore the differences between heavy metal contamination risks in soil and crops as well as the relationships between heavy metal contents in soil and crops. Our results showed that Hg was the most polluted heavy metal in soil, which led to the highest ecological risk in Jiangbei (Comprehensive ERI = 567) with the maximum ERI of Hg (430). However, As in crops contributed the most to health risk and caused the highest health risk in Fenghua (HRI = 10) with the largest contribution of 64.5%. Such differences of pollution risk assessment indicated that the contents of the same heavy metal were inconsistent in soil and crops. Our results further showed that the heavy metals in soil had the greatest influence on Zn in crops. Pb and Cr in soil had synergistic effects on the crop absorption of Zn, whereas As, Hg and Cu played antagonistic roles in the crop absorption of Zn. Our study confirms that heavy metals in soil would variously influence heavy metals in crops and the interaction of heavy metals is very important for pollution risk control, which have been largely ignored yet.
