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<p>Agriculture is vital to sustaining human life and is a major contributor to greenhouse gas emissions, posing serious risks to crop productivity. This study investigated the effects of CO<sub>2</sub>, methane (CH<sub>4</sub>), nitrous oxide (N<sub>2</sub>O) emissions, and renewable energy consumption on agricultural productivity in Bangladesh using the ARDL approach. Time series data from the World Development Indicators (1960–2023) were used to perform correlation analysis, unit root tests, ARDL, and dynamic ARDL estimation. Long-run estimation indicated that agricultural output is positively influenced by fertilizer consumption and CH<sub>4</sub> emissions from agriculture, whereas per capita CO<sub>2</sub> emissions (CO<sub>2</sub>EMPC), renewable energy use, and agricultural land exhibit negative associations. In the short run, renewable energy consumption, agricultural land, and N<sub>2</sub>O emissions had a significant positive impact on agricultural output. The findings also revealed that fertilizer consumption and CH<sub>4</sub> emission have a negative effect. However, the dynamic ARDL model confirmed the output persistence and mixed short-run emissions effects. These findings highlight the need for a policy framework that prioritizes climate-smart agricultural intensification through emission-efficient input management, balanced fertilization, and decentralized adoption of renewable energy to ensure sustainable productivity growth.</p>

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Analyzing the impact of climate change and renewable energy on agricultural productivity in Bangladesh using an ARDL model

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年5月30日

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  • Sharif Ahammad,
  • Tanmay Datta,
  • Nasif Bin Mosharof,
  • Muhammad Fakhrul Islam,
  • Md Ismile Hossain Bhuiyan,
  • Md Jisan Ahmed,
  • Kazi Estieque Alam

摘要

Agriculture is vital to sustaining human life and is a major contributor to greenhouse gas emissions, posing serious risks to crop productivity. This study investigated the effects of CO2, methane (CH4), nitrous oxide (N2O) emissions, and renewable energy consumption on agricultural productivity in Bangladesh using the ARDL approach. Time series data from the World Development Indicators (1960–2023) were used to perform correlation analysis, unit root tests, ARDL, and dynamic ARDL estimation. Long-run estimation indicated that agricultural output is positively influenced by fertilizer consumption and CH4 emissions from agriculture, whereas per capita CO2 emissions (CO2EMPC), renewable energy use, and agricultural land exhibit negative associations. In the short run, renewable energy consumption, agricultural land, and N2O emissions had a significant positive impact on agricultural output. The findings also revealed that fertilizer consumption and CH4 emission have a negative effect. However, the dynamic ARDL model confirmed the output persistence and mixed short-run emissions effects. These findings highlight the need for a policy framework that prioritizes climate-smart agricultural intensification through emission-efficient input management, balanced fertilization, and decentralized adoption of renewable energy to ensure sustainable productivity growth.