DOI: https://doi.org/10.14710/presipitasi.v18i2.329-337

Selecting Plant Types to Control Air Pollution and Developing Software to Plan Green Open Space in the Urban Area

*Yulfiah Yulfiah  -  Institut Teknologi Adhi Tama Surabaya, Indonesia
Fiona Azzahro  -  Institut Teknologi Adhi Tama Surabaya, Indonesia
Rosa Canina Pissera  -  Institut Teknologi Adhi Tama Surabaya, Indonesia

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Abstract

The decrease in air quality becomes one of the development impacts that must be controlled deliberately. Planting trees is crucial for reducing the total number of dust and gas pollutants as it can restrain air pollution through absorption and adsorption. This research aimed at (a) determining the most appropriate types of plants for controlling air pollution and (b) developing software to plan the need for Green Open Space (GOS) in the urban city. The criteria of assessment for measuring the ability of a plant to absorb pollutant gas consisted of: (a) the density level of tree-crown, (b) plant combination, (c) thickness level of leaf, (d) the total number of leaves, and (e) plant distance. Meanwhile, the criteria for assessing the ability of the plant to adsorb dust particles comprised: (a) the roughness of leaf surface structure, (b) leaf width, (c) density level of tree-crown, (d) texture of stem skin surface, and (e) density level of the twig. The results of the research demonstrated that plants of Angsana (Pterocarpus indicus), Kihujan (Samanea saman), and Acacia (Acacia auriculiformis) were very appropriate for absorbing pollutant gas. Meanwhile, the good plants for adsorbing dust particles involved Angsana, Kihujan, Acacia, Tanjung (Mimusops elengi), Kersen (Mutingia calabura), Ketapang (Terminalia cattapa), and red Dadap (Erythrina crista-galli) by the level of adsorption ability around 65-75%. The successfully developed software could present suitability between Green Open Space (GOS) calculated manually and the one counted by software.

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Keywords: air pollution, green open space, software

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Section: Regional Case Study
Language : EN
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Last update: 2024-04-24 20:20:40

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