Over the past four decades, China has experienced a nutritional transition and has developed the largest population of internet users. In this study, we evaluated the impacts of internet access on the nutritional intake in Chinese rural residents. An IV-Probit-based propensity score matching method was used to determine the impact of internet access on nutritional intake. The data were collected from 10042 rural households in six Chinese provinces. The results reveal that rural residents with internet access have significantly higher energy, protein, and fat intake than those without. Chinese rural residents with internet access consumed 1.35% (28.62 kcal), 5.02% (2.61 g), and 4.33% (3.30 g) more energy, protein, and fat, respectively. There was heterogeneity as regards the intake of energy, protein, and fat among those in different income groups. Moreover, non-staple food consumption is the main channel through which internet access affects nutritional intake. The results demonstrate that the local population should use the internet to improve their nutritional status. Further studies are required to investigate the impact of internet use on food consumed away from home and micronutrients intake.

This study utilized panel data from 31 Chinese provinces over a period of nine years to investigate the impact of green finance on the upgrading of the agricultural industrial structure. A fixed-effect model was employed, and the findings indicate that green financing has a positive effect on the growth of China's agricultural industry. However, regional disparities exist, particularly in the uneven distribution of green financing across the eastern, central, and western regions. Moreover, it emphasizes the need to consider regional differences and tailor development strategies accordingly. To promote further development and transformation of China's agricultural industrial structure, the study recommends innovative green financial products, improved regulations and policies, and the integration of digital technologies.

This study evaluates the agricultural carbon emission efficiency of Shandong Province from 2011 to 2020 using the DEA-SBM model. The nexus between endogenous and exogenous variables is estimated using the Tobit model. The findings reveal an overall increasing trend in agricultural carbon emissions, with significant variations in efficiency values among different cities, leading to a severe polarization. Spatial evaluation shows a high distribution trend in the central region and low in the eastern and western regions of Shandong Province. The empirical tests conducted for Shandong Province and its three regions indicate that urbanization plays a major role in sup-porting the growth of agricultural carbon emission efficiency, while the education level of the la-bor force has a suppressive impact. Economic development and crop cultivation structure, how-ever, have no significant influence. The impact of these variables varies across the eastern, central, and western regions. The proposed countermeasures include improving planting structure and reducing brain drain in the eastern region, strengthening agricultural and rural inputs and in-creasing the added value of agricultural products in the central region, and intensifying the link-age between urbanization and industrial layout in the western region to reduce agricultural car-bon emissions efficiency in Shandong Province.

The build-up of greenhouse gases (GHGs) is causing warmness in the Earth’s atmosphere, resulting in climate change. The transport sector is one of the active members of GHG emissions and it is imperative to use sustainable transport sources to control climate change. The measure aims to encourage citizens to stop using their private vehicles as their choice of transport and instead opt for joint sustainable mobility during traveling. In this study, a quantitative research method was used and data were collected from a sample of 410 respondents through questionnaire. On the other hand, study also took a simulation-based (N=10000) sample size of private vehicle data. The data were analyzed using structural equation modelling. The results revealed that sustainable transportation, climate change technologies and electric rail vehicles reduce climate change in the ecoregions of China. We conclude that sustainable transportation policies could be formulated and implemented to reduce climate change. In response to the research results, it is recommended that, since climate change is a multi-level governance issue and the outdated pyramidal transport industry models must be shifted to a sustainable transportation system model.