Sholikin, Mohamad (2024) Analisis Ultrafine Particle (UFPs) dan Black Carbon (BC) di Indoor Microenvironment Universitas: Sumber Potensial, Faktor Infiltrasi, Exposure, dan Machine Learning Model. Undergraduate thesis, UPN Veteran Jawa Timur.
![[img]](https://repository.upnjatim.ac.id/style/images/fileicons/text.png) |
Text (COVER)
20034010013-cover.pdf Download (1MB) |
|
Text (BAB 1)
20034010013-bab1.pdf Download (292kB) |
|
Text (BAB 2)
20034010013-bab2.pdf Restricted to Repository staff only until 11 December 2027. Download (826kB) |
|
Text (BAB 3)
20034010013-bab3.pdf Restricted to Repository staff only until 11 December 2027. Download (669kB) |
|
Text (BAB 4)
20034010013-bab4.pdf Restricted to Repository staff only until 11 December 2027. Download (886kB) |
|
Text (BAB 5)
20034010013-bab5.pdf Download (282kB) |
|
Text (DAFTAR PUSTAKA)
20034010013-daftar pustaka.pdf Download (265kB) |
|
Text (LAMPIRAN)
20034010013-lampiran.pdf Restricted to Repository staff only Download (1MB) |
Abstract
Ambient ultrafine particles (UFPs; PM0.1; particles of diameter less than or equal to 0.1µm) and black carbon (BC) have a negative impact on human health. As students spend most of their time indoor and one third in school, the educatory environment deserve special attention; however, majority of past research focused on UFPs and BC assessment itself in classroom. Thus, this work aims to expand the the characterization of UFPs and BC in university by considering different indoor microenvironment, infiltration factor, and estimating exposure for healthy children and adult. Additionally, machine learning (ML) that could accurately predict the particle number of UFPs was developed and utilized in this investigation. This study measured UFPs and BC concentrations across four room types: cafeteria, gym, office room, and classroom. The observed average UFPs PNC and BC in the cafeteria (13,355 # cm⁻³ & 599 ng m⁻³ ), gym (8,811 # cm⁻³ & 987 ng m⁻³ ), office room (7,679 # cm⁻³ & 830 ng m⁻³ ), and classroom (6,420 # cm⁻³ & 548 ng m⁻³). The highest I/O ratio for UFPs was found in the cafeteria (0.80), indicating outdoor pollution influence, while BC had the highest I/O ratio in the gym (1.11), suggesting indoor BC sources. The majority of inhaled UFPs were found in the alveoli (ALV) fraction in children (68.3%) and the tracheobronchial (TB) respiratory fraction in adults (67.7%). The ML algorithm, artificial neural network (ANN) demonstrated the best performance for the office room and cafeteria, with R² values of 0.958 and 0.923, respectively, and low MAE and MSE values. Meanwhile, the random forest regressor (RFRegressor) performed optimally for the classroom and gym, with R² values of 0.915 and 0.865, respectively.
| Item Type: | Thesis (Undergraduate) | ||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Contributors: |
|
||||||||||||
| Subjects: | G Geography. Anthropology. Recreation > GE Environmental Sciences | ||||||||||||
| Divisions: | Faculty of Engineering > Departement of Environmental Engineering | ||||||||||||
| Depositing User: | Mohamad Sholikin | ||||||||||||
| Date Deposited: | 11 Dec 2024 04:47 | ||||||||||||
| Last Modified: | 11 Dec 2024 04:47 | ||||||||||||
| URI: | https://repository.upnjatim.ac.id/id/eprint/32731 |
Actions (login required)
 |
View Item |