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The implementation of environmental regulation needs to consider not only pollution control but also its impact on economic growth. Using the provincial panel data in China from 2000 to 2017, this paper constructs dynamic spatial panel models and employs system GMM approach to evaluate the nonlinear and spatial effects of environmental regulation on economic growth and CO 2 emissions, respectively. The results suggest that, first, environmental regulation presents a significant "N"-shaped effect on economic growth and an inverted "N" effect on CO 2 emissions at the national level and in the eastern and central regions; while the effects are both"N"-shaped in the western region. Second, environmental regulation presents significant spatial effects on economic growth and CO 2 emissions. The enhancement of regional environmental regulation helps the economic growth and CO 2 emissions reduction in neighboring provinces at the national level and in the eastern and central regions, however, the spatial effects are opposite in the western provinces, proving the co-exists of "race to the top" and "race to the bottom" strategies of environmental regulation competition among China's regions. Third, the effects of environmental regulation on economic growth and CO 2 emissions are affected by FDI, and the moderating effect of FDI is regional heterogenous. • Building a dynamic spatial panel model based on the spatial spillover theory. • Proving an "N"-type effect of environmental regulation on economic growth. • The effect of environmental regulation on CO 2 emissions is regionally different. • Environmental regulation affects the role of FDI on economy and CO 2 emissions. • The spatial spillover effects of environmental regulation are proved. [ABSTRACT FROM AUTHOR]

Green development is the direction of China's agricultural sector. Investigating the main influencing factors of the agricultural sector's CO 2 emissions will help plan agricultural development and achieve low-carbon growth. This paper selects 2001–2016 panel data of China's 30 provinces, and uses the nonparametric additive regression models to investigate the agricultural sector's CO 2 emissions. The empirical results show that economic growth, financial capacity, and energy intensity all have a "pull first, then restrict" inverted U-shaped nonlinear effect on CO 2 emissions. However, the influencing mechanisms of these three influencing factors are different and need to be paid attention by relevant government departments. More complicated, the impact of urbanization on CO 2 emission shows a gentle "M-shaped" pattern. In addition, an inverse "N-shaped" nonlinear link exists between trade openness and CO 2 emissions. Therefore, government departments should formulate differentiated emission reduction policies at different stages. • The drivers of CO 2 emissions in China's agriculture sector are investigated. • Financial capacity has an inverse "U-shaped" effect on CO 2 emissions. • The impact of urbanization on CO 2 emission shows a gentle "M-shaped" pattern. [ABSTRACT FROM AUTHOR]