Scholarlink

<p>The rapid expansion of rice processing mills in agriculturally rich regions, such as Khajanagar, Kushtia, has resulted in elevated concentrations of particulate matter (PM), posing serious environmental and public health risks. The close proximity of rice mills to residential areas necessitates evaluating particulate matter dispersion to assess neighbourhood-level health risks. This study examines the spatial distribution, dispersion behaviour, and health impacts of PM₂.₅ and PM₁₀ across industrial and adjacent residential zones. A total of 69 sampling points were monitored using optical particle counters (OPCs) at 0–100&#xa0;m (industrial) and 101–300&#xa0;m (residential) distances, along with meteorological observations. PM₂.₅ concentrations in industrial areas exceeded all regulatory limits in Bangladesh, the WHO, and the U.S. EPA, while PM₁₀ exceeded WHO standards only within industrial zones; both fractions exceeded all benchmarks in residential areas. The Kruskal–Wallis test (<i>p</i> &lt; 0.05) confirmed significant interzonal variation. Spatial mapping identified PM hotspots in the western and eastern industrial belts and the western residential cluster, providing empirical evidence of localized emission intensity and downwind accumulation driven by mill density and prevailing wind patterns. PM₂.₅ and PM₁₀ were highly correlated, though their relationships with humidity and temperature were weak. Gaussian plume modelling indicated that PM₁₀ dispersed and deposited over greater distances than PM₂.₅ due to its size-dependent transport under prevailing winds, increasing exposure in residential zones. AirQ⁺ health risk analysis revealed that PM₂.₅ exposure contributed to 39.78% of ALRI-related mortality in children under five, while in adults (≥ 30&#xa0;years), it accounted for 48.01% of Chronic Obstructive Pulmonary Disease (COPD), 56.25% of Ischemic Heart Disease (IHD), and 65.05% of stroke deaths. PM₁₀ posed additional risks for IHD and lung cancer, with 34.16% of lung cancer mortality linked to PM₂.₅ exposure. By integrating spatial monitoring, dispersion modelling, and health risk assessment, this study identifies high-risk micro-environments and underscores the need for stricter emission control in rice-processing regions.</p> Graphical abstract <p></p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Integrated spatial analysis and Gaussian dispersion modelling of airborne particulate matter from rice processing mill hubs in rural Bangladesh and associated public health risks

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年7月22日

查看全文
  • Rubaiatul Islam Zerin,
  • Md. Kamrul Hossain,
  • Humaira Rashid,
  • Sababa Tasnim,
  • Md. Julfikar Ali,
  • Md. Mizanur Rahman,
  • Mohd. Maniruzzaman,
  • Rafiquel Islam

摘要

The rapid expansion of rice processing mills in agriculturally rich regions, such as Khajanagar, Kushtia, has resulted in elevated concentrations of particulate matter (PM), posing serious environmental and public health risks. The close proximity of rice mills to residential areas necessitates evaluating particulate matter dispersion to assess neighbourhood-level health risks. This study examines the spatial distribution, dispersion behaviour, and health impacts of PM₂.₅ and PM₁₀ across industrial and adjacent residential zones. A total of 69 sampling points were monitored using optical particle counters (OPCs) at 0–100 m (industrial) and 101–300 m (residential) distances, along with meteorological observations. PM₂.₅ concentrations in industrial areas exceeded all regulatory limits in Bangladesh, the WHO, and the U.S. EPA, while PM₁₀ exceeded WHO standards only within industrial zones; both fractions exceeded all benchmarks in residential areas. The Kruskal–Wallis test (p < 0.05) confirmed significant interzonal variation. Spatial mapping identified PM hotspots in the western and eastern industrial belts and the western residential cluster, providing empirical evidence of localized emission intensity and downwind accumulation driven by mill density and prevailing wind patterns. PM₂.₅ and PM₁₀ were highly correlated, though their relationships with humidity and temperature were weak. Gaussian plume modelling indicated that PM₁₀ dispersed and deposited over greater distances than PM₂.₅ due to its size-dependent transport under prevailing winds, increasing exposure in residential zones. AirQ⁺ health risk analysis revealed that PM₂.₅ exposure contributed to 39.78% of ALRI-related mortality in children under five, while in adults (≥ 30 years), it accounted for 48.01% of Chronic Obstructive Pulmonary Disease (COPD), 56.25% of Ischemic Heart Disease (IHD), and 65.05% of stroke deaths. PM₁₀ posed additional risks for IHD and lung cancer, with 34.16% of lung cancer mortality linked to PM₂.₅ exposure. By integrating spatial monitoring, dispersion modelling, and health risk assessment, this study identifies high-risk micro-environments and underscores the need for stricter emission control in rice-processing regions.

Graphical abstract