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<p>Agricultural activities have recently contributed to air pollution, highlighting the need to understand their impact on air quality is very important. This study used the WRF-CMAQ model to assess agricultural emissions in Lahore, refining the 2021 emissions inventory and creating a spatiotemporal distribution with ISAT. The evaluation focused on agricultural contributions to air pollution during peak months, April and October. Data from 2021 was used to conduct an emission inventory for agricultural sources in Lahore using the emission factor method to assess pollutants from straw burning, machinery emissions, crop harvesting, soil tillage, and grain treatment. The result showed that agricultural sources emitted 5.0, 47.3, 4.5, 437.8, 75.0, 118.1, and 70.1 kt of SO<sub>2</sub>, NOx, NH<sub>3</sub>, CO, VOCs, PM<sub>10</sub>, and PM<sub>2.5</sub>, respectively. The uncertainty of agricultural source emission inventory was assessed using the IPCC error transfer formula, showing an average uncertainty of 80% for seven pollutants. The WRF model performance of correlation coefficients between temperature, wind speed, and atmospheric pressure were 0.50 and 0.96, with NMB ranging from − 0.02 to 0.32 and NME from 0.02 to 0.51. CMAQ simulations showed PM<sub>2.5</sub> and NOx correlation coefficients of 0.40 to 0.48, with MFB between − 60 and 60% and MFE under 75%, indicating acceptable accuracy. Enhancing the agricultural inventory revealed that in April and October, agricultural sources contributed 6.01&#xa0;µg/m<sup>3</sup> (20% of PM<sub>2.5</sub>) and 4.32&#xa0;µg/m<sup>3</sup> (19%) respectively, demonstrating their significant impact on air quality.</p>

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Effects of agricultural sources on air quality in Lahore, Pakistan, based on CMAQ simulation

  • 期刊论文

  • 发表日期：

    2025年8月1日

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  • Arshad Abbasi,
  • Chunsheng Fang,
  • Ju Wang,
  • Usman Basharat,
  • Anees Akhtar

摘要

Agricultural activities have recently contributed to air pollution, highlighting the need to understand their impact on air quality is very important. This study used the WRF-CMAQ model to assess agricultural emissions in Lahore, refining the 2021 emissions inventory and creating a spatiotemporal distribution with ISAT. The evaluation focused on agricultural contributions to air pollution during peak months, April and October. Data from 2021 was used to conduct an emission inventory for agricultural sources in Lahore using the emission factor method to assess pollutants from straw burning, machinery emissions, crop harvesting, soil tillage, and grain treatment. The result showed that agricultural sources emitted 5.0, 47.3, 4.5, 437.8, 75.0, 118.1, and 70.1 kt of SO2, NOx, NH3, CO, VOCs, PM10, and PM2.5, respectively. The uncertainty of agricultural source emission inventory was assessed using the IPCC error transfer formula, showing an average uncertainty of 80% for seven pollutants. The WRF model performance of correlation coefficients between temperature, wind speed, and atmospheric pressure were 0.50 and 0.96, with NMB ranging from − 0.02 to 0.32 and NME from 0.02 to 0.51. CMAQ simulations showed PM2.5 and NOx correlation coefficients of 0.40 to 0.48, with MFB between − 60 and 60% and MFE under 75%, indicating acceptable accuracy. Enhancing the agricultural inventory revealed that in April and October, agricultural sources contributed 6.01 µg/m3 (20% of PM2.5) and 4.32 µg/m3 (19%) respectively, demonstrating their significant impact on air quality.