Siyuan Shao

In response to climate change, the reduction of carbon emissions during agricultural production has garnered increasing global focus. This study takes high-standard farmland construction (HSFC) implemented in 2011 as the standard natural experiment and adopts the continuous differences-in-differences (DID) model to explore the impact and internal mechanism of HSFC on agricultural carbon emissions based on a panel data of 31 provinces, municipalities, and autonomous regions in China from 2003 to 2021. The results show that HSFC can effectively reduce the carbon emissions in agricultural production, and the average annual reduction can reach 53.8%. The effects of HSFC on agriculture carbon emissions could be associated with reducing agricultural fossil energy consumption and reducing agricultural chemical use. Further, the heterogeneity study shows that the carbon reduction effect of HSFC was mainly reflected in non-major grain-producing areas, while there was no significant impact in major grain-producing areas. Policymakers should unswervingly continue to promote HSFC, considering their own economic and geographical conditions. This study can provide valuable information and references for developing countries similar to China to formulate policies on agricultural carbon reduction.

To reduce traffic congestion and pollution, urban rail transit in China has been in a stage of rapid development in recent years. As a result, rail transit service interruption events are becoming more common, seriously affecting the resilience of the transportation system and user satisfaction. Therefore, determining the changing mechanism of the passenger waiting tolerance, which helps establish a scientific and effective emergency plan, is urgent. First, the variables and levels of the urban rail service interruption scenarios were screened and determined, and the stated preference questionnaire was designed using the orthogonal design method. Further, the data of the waiting tolerance of passengers during service interruptions were obtained through questionnaires. Second, combined with the questionnaire data, an accelerated failure time model that obeys the exponential distribution was constructed. The results indicate that factors such as the service interruption duration, travel distance, bus bridging, information accuracy, attention to operation information, travel frequency and interruption experience affect the waiting tolerance of passengers during service interruptions. Finally, combined with the sensitivity analysis of the key influencing factors, the policy analysis and suggestions are summarized to provide theoretical support for the urban rail operation and management department to capture the passenger waiting tolerance accurately during service interruptions and formulate an efficient, high-quality emergency organization plan.