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Evaluation of respiratory deposition doses in the presence of green infrastructure

Air Quality Atmosphere and Health


Green infrastructure (GI) is effective in reducing PM concentrations in near-road environments, but how such reductions in concentration compared with relative respiratory deposition doses (RDDs) is rarely discussed. We quantified variations in RDD in the presence of three GI types (trees, hedges and tree-hedge combinations), and compared them with PM reduced by the GI under different wind directions and seasons through the assessment of data collected during multiple field campaigns. We also studied three scenarios (sitting, walking, running) to investigate RDD in adults and children during different possible activities in the presence of GI at public parks or gardens or in front of houses. Finally, we illustrated particle mass distribution before and after different GI configurations to explore the reasons for variations in RDD. Changes in RDD displayed a trend of %Delta RDDPM10 > %Delta RDDPM2.5 = %Delta RDDPM1, compared to the changes in PM concentrations of %Delta PM1 > %Delta PM10 > %Delta PM2.5. A maximum reduction (25%) in RDD was observed for PM10 in the presence of the tree-hedge combination, and this combination emerged as the most effective GI type in lowering the RDD. The changes in ratios of mass median diameter and deposition fraction of roughly +/- 0.2 before and after the GI led to differences between % increment PM and % increment RDD. Cross-winds (perpendicular to road direction) led to greater variations between % increment PM and % increment RDD, whereas parallel winds (along the road) led to similar variations in % increment RDD and % increment PM. Particle mass distributions revealed the absence of a peak around particle diameter 2.5 mu m in the presence of GI. The highest difference in RDD behind GI was observed in the presence of a hedge-tree combination during different physical activities.

Author(s): Abhijith, KV; Kumar, P

Journal: Air Quality Atmosphere and Health

Year: 2021


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