Penggunaan Model Land Use Regression untuk Memprediksi Distribusi Spasiotemporal Materi Partikulat di Udara Ambien

Mila Dirgawati, Rina Dwi Riyanti, Didin Agustian Permadi, Mohamad Rangga Sururi

Abstract


Penggunaan Model Land Use Regression untuk Memprediksi Distribusi  Spasiotemporal Materi Partikulat. Polusi udara ambien di wilayah perkotaan merupakan salah satu isu lingkungan dan  kesehatan yang penting. Polutan udara, terutama materi partikulat (PM) mampu mempengaruhi kesehatan manusia bahkan ketika terpapar dengan konsentrasi rendah. Model Land use regression (LUR) telah banyak digunakan untuk menggambarkan distribusi spasial dan temporal partikulat berukuran <2,5µm (PM2.5) dan <10µm (PM10) dengan berbagai variabel prediktornya. Studi ini mengkaji kemampuan model LUR yang digunakan untuk memprediksi distribusi spasial dan temporal PM10 dan PM2,5 di wilayah perkotaan dengan cara memodelkan konsentrasi polutan dengan variabel prediktornya berdasarkan prinsip regresi linier.  Berbagai studi terdahulu mengenai model LUR yang telah dipublikasikan pada tahun 2016 – 2023 dikaji untuk mengetahui variabel prediktor penting yang menentukan konsentrasi partikulat, kemampuan model LUR, serta faktor-faktor yang mempengaruhi kemampuan model LUR dalam memprediksi distribusi spasial-temporal dari konsentrasi PM10 dan PM2,5. Database yang digunakan berasal dari beberapa studi terdahulu yang relevan dengan tujuan studi ini. Data diperoleh melalui kajian literatur pada sumber data elektronik, yaitu Google Scholar. Model LUR mampu menjelaskan variasi spasial–temporal dari konsentrasi PM2.5 sebesar 26%-84% dan PM10 sebesar 45%-70%. Model LUR menunjukkan faktor yang berkontribusi terhadap PM2,5 adalah lalu lintas (volume lalu lintas, jarak ke jalan besar, panjang semua tipe jalan, dan intensitas lalu lintas), kepadatan penduduk, penggunaan lahan (industri, residensial, ruang terbuka hijau, dan area komersil), geografi dan meteorologi. Sedangkan PM10 sangat dipengaruhi oleh  kegiatan transportasi. Faktor yang memperngaruhi kemampuan model LUR untuk memprediksi PM adalah jumlah titik pantau PM10 dan PM2,5 yang menjadi input data dalam pemodelan LUR. Kemampuan prediksi model LUR untuk PM10 dan PM2.5 akan meningkat ketika jumlah titik pemantauan 40-80 titik. Pemodelan LUR mampu menggambarkan distribusi spasial-temporal materi partikulat dan memprediksi konsentrasi PM10 dan PM2,5 di area yang tidak dilakukan pemantauan.


Keywords


Land Use Regression Models, Materi Partikulat; Distribusi Spasial-Temporal; Variabel prediktor; PM10; PM2.5

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References


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DOI: https://doi.org/10.59495/jklh.2024.18.1.25-34

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