RESUMEN
Yellow River Basin (YRB) is a pivotal region for energy consumption and carbon emissions (CEs) in China, with cities emerging as the main sources of regional CEs. This highlights their critical role in achieving regional sustainable development and China's carbon neutrality. Consequently, there is a pressing need for a detailed exploration of the urban spillover effects and an in-depth analysis of the complex determinants influencing CEs within the YRB. Remote sensing data provide optimal conditions for conducting extensive studies across large geographical areas and extended time periods. This study integrates DMSP/OLS and NPP/VIIRS nighttime light datasets for a longitudinal analysis of urban CEs in the YRB. Using a harmonized dataset from DMSP/OLS and NPP/VIIRS nighttime light from 2007 to 2021, this study quantifies CEs of 58 prefecture-level cities in the YRB. By combining ESDA, STIRPAT model and spatial econometric model, this investigation further clarifies empirically the spatial spillover effects and driving factors of urban CEs. The analysis delineates a phase-wise augmentation in urban CEs, converging towards a distinct spatial distribution characterized by "lower reach > middle reach > upper reach". The spatial autocorrelation tests unravel a complex interplay between agglomeration and differentiation patterns within urban CEs, underscored by pronounced spatial lock-in phenomena. Significantly, this study demonstrates that urbanization, economic development, energy consumption structure, green coverage rate, industrial structure, population, technological progress, and FDI each exhibit varied direct and indirect effect on urban CEs. Furthermore, it elaborates on potential policy implications and future research directions, offering crucial insights for formulating CEs mitigation strategies to advance sustainable development.
RESUMEN
Industrial organizations play a crucial role in transforming the production and management practices of smallholder farmers, encouraging the adoption of environmentally friendly production methods. However, limited studies have conducted comprehensive research examining how these industrial organizations effectively encourage farmers to adopt green production technologies. To address this research gap, this study examines the influence of organizational support on the adoption of agricultural green production technologies among 645 kiwifruit farmers in Shaanxi Province, northwestern China, using cross-sectional survey data from 2022. In addition, this research explores the mechanisms and heterogeneity in this impact. In our analysis, we estimated Probit models and mediation effect models, which show a positive influence of organizational support on farmers' adoption of these technologies. Notably, both institutional support and tool support have a more pronounced positive effect on this adoption. The mechanism analysis shows that organizational support facilitates farmers' adoption of these agricultural green production technologies by expanding their access to high-value markets. Furthermore, when considering heterogeneity among farmers, the study finds that organizational support has the most significant impact on the adoption of these technologies among farmers operating at a moderate scale. Moreover, our research highlights a technology linkage effect in the adoption process. Specifically, organizational support has a positive and significant effect on the adoption of technologies like bagging, physical control, and soil testing formulas, while also having a positive but statistically insignificant impact on technologies such as pollution-free pesticides and organic fertilizer substitution. In conclusion, the study proposes to increase assistance to industrial organizations, to play an influential role in guiding and driving farmers.