Kinetika Formaldehida (HCHO) Dan Ozon (O3) Di Daerah Urban (Studi Kasus Jakarta): (CASE STUDY: JAKARTA) - Nadiyatur Rahmatikal Wasiah; Driejana Driejana (JURNAL RISET KESEHATAN POLTEKKES DEPKES BANDUNG, Online ISSN 2579-8103, 2020)
Formaldehyde (HCHO) is a toxic compound and plays an important role in atmospheric chemical reactions as a source of radicals and precursor of oxidants (mainly ozone). HCHO generates from primary sources (motor vehicles) and secondary sources (photochemical reactions). However, carbonyl compounds monitoring and research on their roles in chemical reaction (ozone production) in Indonesia is still limited. This research investigated the contribution and relationship of hydrocarbons (formaldehyde) and ozone in urban areas. Formaldehyde measurements were carried out for two weeks using absorption method and samples were analyzed by spectrophotometric. Two empirical methods were used to predict ozone production, namely MIR (maximum incremental reactivity) method and propane equivalent method. MIR is a method to calculate organic compounds reactivity in ozone formation. Meanwhile, propane-equivalent method aims to determine ozone estimate using the rate of hydrocarbons oxidation (formaldehyde and propane). Based on ozone diurnal variation, the MIR method provided overestimation, while the propane equivalent method show underestimate predictions. The mean value ​​of ozone concentrations as the reference data in µg/m3) was 34.39 , while estimates resulted in 83.93 (MIR method) and 9.92 (propane equivalent method), respectively. RMSE (Root Mean Squared Error) calculated the error range of the two methods found the values of 81.23 µg/m3 (MIR) and 31.90 µg/ m3 (propane equivalent). It is found that these methods did not predict ozone well. However, both method were easy to applied and could estimated ozone concentration although the information of hydrocarbons data were limited. it is suggested that alternative method were applied by adding meteorological data and other hydrocarbons concentrations to produce better prediction ozone model