The environmental impacts of different organic rice management in Italy considering different productive scenarios

Chinese organic rice transition spatial econometrics empirical analysis

Based on the integrated model of Super-SBM model, spatial Durbin model (SDM) and Grey neural network model, this paper analyzes the panel data of various provinces in China from multiple angles and dimensions. It was found that there were significant differences in eco-efficiency between organic rice production and conventional rice production. The response of organic rice to climate change, the spatial distribution of ecological and economic benefits and the impact on carbon emission were analyzed. The results showed that organic rice planting not only had higher economic benefits, but also showed a rising trend of ecological benefits and a positive feedback effect. This finding highlights the importance of organic rice farming in reducing carbon emissions. Organic rice farming effectively reduces greenhouse gas emissions, especially carbon dioxide and methane, by improving soil management and reducing the use of fertilizers and pesticides. This has important implications for mitigating climate change and promoting soil health and biodiversity. With the acceleration of urbanization, the increase of organic rice planting area shows the trend of organic rice gradually replacing traditional rice cultivation, further highlighting the potential of organic agriculture in emission reduction, environmental protection and sustainable agricultural production. To this end, it is recommended that the Government implement a diversified support strategy to encourage technological innovation, provide guidance and training, and raise public awareness and demand for organic products. At the same time, private sector participation is stimulated to support the development of organic rice cultivation through a public-private partnership model. Through these measures, further promote organic rice cultivation, achieve the dual goals of economic benefits and environmental benefits, and effectively promote the realization of double carbon emission reduction targets.

Sustainable crop production: Highlights on economic, environmental and social life cycle thinking

Seeking multi-dimensional inclusion is one of the most global concerns of the crop production sector worldwide. Socio-eco-effectiveness or socio-eco-efficiency optimization plays a crucial role in future strategy establishment. Life cycle is a widely used approach examining economic, environmental, and social impacts. Recently, life cycle thinking approaches have been increasingly utilized to bring to light useful perceptions of the crop production processes. This study aims to apply a systematic review and prescriptive analytics to critically investigate the life cycle thinking approaches application according to sustainability pyramid aspects, life cycle thinking unicity, goal and scope variability, functional units' causality, system boundary' diversity, involved aspect' concentration, indicators, impacts categories and influencing variables distribution, as well as to define a first datasheet model and directive axis to apply per aspect and family for socio-eco-effectiveness or socio-eco-efficiency evaluation. Over 295 peer-reviewed studies from 2019 to the middle of 2023, 52 reviews and articles gathered from Web of Science and Scopus meet the criteria to be analyzed. Our inspection revealed that related reviews are few, approximately 2 %. Moving from the traditional life cycle perspective to the sustainability pyramid approach, the indicators applied by researchers were classified per aspect and family belonging. A deductive analysis was carried out to narrow the impact categories, and the influencing factors to the population's main interests: four economic (input status, resources consumption, waste, and Costs of Life Cycle), eight environmental (Climate Change, Global Warming, Ozone, Acidification, Eutrophication, Photochemical Oxidation, Abiotic Depletion, and Toxicity), and three social families (Human Toxicity, employment, and Ionizing Radiation). The results combination highlights the construction need for a directive datasheet model to address the optimizing problem under the identified families and aspects constraints, as well as to envisage the units and methods worldwide standardization's necessity for spatial-temporal studies comparison in the present, the past, and the future.