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Carbon emissions (CE) have a profound impact on the natural environment of the surface, and the ecologic environment quality (EEQ) affects the conversion and absorption of CE. CE and EEQ have an interaction and mutual influence relationship. The connection between them includes not only local interactions but also the long-range distance of external systems. It is critical to measure CE and EEQ and coordinate their association in order to increase the effectiveness of CE and EEQ collaborative governance. However, the traditional remote sensing ecological index (RSEI) model ignores the importance of air quality. Furthermore, there is limited current research on the local and telecoupling relationship between CE and the EEQ. To fill these research gaps, this paper first used night light data to dynamically monitor CE. Then we proposed an upgraded RSEI model (RSEInew) to assess EEQ. Finally, the local and telecoupling coordination degree (LTCCD) model was suggested to further investigate their relationship in the Yangtze River Economic Belt (YREB) from 2000 to 2019. The results showed that: (1) Total CE in the YREB increased from 837.5738 million tons to 4757.3794 million tons between 2000 and 2019 but has not yet reached its peak. Jiangsu and Zhejiang are at the forefront in terms of CE and have huge emission reduction potential. (2) The YREB's overall EEQ has deteriorated over the last 20 years. The average RSEInew value ranged between 0.52 and 0.71, with "medium" and "good" EEQ levels dominating. (3) The LTCCD of CE and EEQ in the YREB has increased year by year. This study can deliver a reference for decision-makers to synergistically formulate carbon emission reduction plans and environmental protection schemes. • Ecologic environment quality should combine regional characteristics, our RSEInew model could evaluate it with introduces PM2.5. • Carbon emissions and the ecologic environment quality interact with each other, with near- and long-range interactions. • The LTCCD model enable to analysis the local and telecoupling relationships of CE and EEQ. [ABSTRACT FROM AUTHOR]

The upscaling of farming operations in China has been advancing rapidly in recent years. This trend is likely to increase the use of agricultural machinery inputs, and possibly also the use of chemical pesticides, which is already extremely high. The relationship between farm size and the intensity of chemical pesticide usage is a subject of debate, and little is known about the mechanisms that might underlie this relationship. In this paper, we apply an integrated framework of larger-scale farming, agricultural mechanization and the intensity of chemical pesticide usage to examine and quantify the mediating effect of agricultural mechanization on the relationship between larger-scale farming and the use of chemical pesticides. Results obtained by applying seemingly unrelated regression (SUR) considering two-way fixed-effects and mediation analysis to county-level data for Jiangsu Province (2002–2019) suggest that an increase of 1% in the ratio of scale of farming is related to a total decline of 0.070% in chemical pesticide usage per hectare of land. Mediation analysis subsequently identifies mechanical sowing/transplanting is the only mediating variable, through which an increase of 1% in the ratio of scale of farming reduces the unit consumption of chemical pesticides by 0.017%. [ABSTRACT FROM AUTHOR]

The upscaling of farming operations in China has been advancing rapidly in recent years. This trend is likely to increase the use of agricultural machinery inputs, and possibly also the use of chemical pesticides, which is already extremely high. The relationship between farm size and the intensity of chemical pesticide usage is a subject of debate, and little is known about the mechanisms that might underlie this relationship. In this paper, we apply an integrated framework of larger-scale farming, agricultural mechanization and the intensity of chemical pesticide usage to examine and quantify the mediating effect of agricultural mechanization on the relationship between larger-scale farming and the use of chemical pesticides. Results obtained by applying seemingly unrelated regression (SUR) considering two-way fixed-effects and mediation analysis to county-level data for Jiangsu Province (2002–2019) suggest that an increase of 1% in the ratio of scale of farming is related to a total decline of 0.070% in chemical pesticide usage per hectare of land. Mediation analysis subsequently identifies mechanical sowing/transplanting is the only mediating variable, through which an increase of 1% in the ratio of scale of farming reduces the unit consumption of chemical pesticides by 0.017%. [ABSTRACT FROM AUTHOR]