Towards a clean production by exploring the nexus between agricultural ecosystem and environmental degradation using novel dynamic ARDL simulations approach

Agriculture, which serves as a lifeline for us, is unequivocally vital for an agriculture-dependent economy like Bangladesh, not only for its food supply but also because of its significant contribution towards achieving Sustainable Development Goals (SDGs) 1 and 2. However, in a third-world nation like Bangladesh, where farming practices largely circumvent the environmental consequences, raised our concern. In this milieu, this study is a novel attempt to explore the association between agricultural ecosystem and environmental degradation in Bangladesh using a long time spanning from 1972 to 2018. We observed a long-run association between the agroecosystem and CO 2 emission. Further, findings from the dynamic autoregressive distributed lag (DARDL) simulation model revealed that the environmental quality of Bangladesh is heavily distorted by total cereal production, total livestock head, enteric methane emissions, N 2 O emissions from manure application, and CO 2 equivalent N 2 O emissions from synthetic fertilizers in the short and long run, whereas agricultural technology, pesticide use in agriculture, and burned biomass crop residue deteriorated the environmental quality only in the long run. The counterfactual diagram entailed from the DARDL model projected the trend of CO 2 emission in response to positive and negative changes in the analyzed variables. Lastly, this study established a causal relationship between the agroecosystem and environmental degradation using frequency domain causality. Indeed, our study will aid in reshaping agricultural practices in an eco-friendly manner to mitigate environmental degradation and help formulate pragmatic policy actions so that agro-lead nations can thrive in the race of achieving SDGs 1, 2, and 13.