No abstract

Xinjiang’s agricultural carbon emissions showed three stages of change, i.e., continued to rise, declined and continued to rise, during 1991–2014. The agriculture belonged to the “low emissions and high efficiency” agriculture category, with a lower agricultural carbon emission intensity. By using the logarithmic mean divisia index decomposition method, agricultural carbon emissions were decomposed into an efficiency factor, a structure factor, an economy factor, and a labour factor. We divided the study period into five stages based on the changes in efficiency factor and economy factor. Xinjiang showed different agricultural carbon emission characteristics at different stages. The degree of impact on agricultural carbon emissions at these stages depended on the combined effect of planting-animal husbandry carbon intensity and agricultural labour productivity. The economy factor was the critical factor to promote the increase in agricultural carbon emissions, while the main inhibiting factor for agricultural carbon emissions was the efficiency factor. The labour factor became more and more obvious in increasing agricultural carbon emissions. Finally, we discuss policy recommendations in terms of the main factors, including the development of agricultural science and technology (S&T), the establishment of three major mechanisms and transfer of rural labour in ethnic areas.

Abstract:Regional economic inequality is a persistent problem for all nations. Meanwhile, satellite-derived night-time light (NTL) data have been extensively used as an efficient proxy measure for economic activity. This study firstly proposes a new method for correction of the NTL data derived from the Visible Infrared Imaging Radiometer Suite (VIIRS) aboard the Suomi National Polar-orbiting Partnership (Suomi-NPP) satellite and then applies the corrected NTL data to estimate gross domestic product (GDP) at a multi-scale level in China from 2014 to 2017. Secondly, incorporating the two-stage nested Theil decomposition method, multi-scale level regional inequalities are investigated. Finally, by using scatter plots, this paper identifies the relationship between the regional inequality and the level of economic development. The results indicate that: (1) after correction, the NPP-VIIRS NTL data show a statistically positive correlation with GDP, which proves that our correction method is scientifically effective; (2) from 2014 to 2017, overall inequality, within-province inequality, and between-region inequality all declined, However, between-province inequality increased slightly. As for the contributions to overall regional inequality, the within-province inequality was the highest, while the between-province inequality was the lowest; (3) further analysis of within-province inequality reveals that economic inequalities in coastal provinces in China are smaller than in inland provinces; (4) China's economic development plays an important role in affecting regional inequality, and the extent of influence of economic development on regional inequality is varied across provinces.