scholarly journals Analisis Risiko Kesehatan Lingkungan Pajanan Debu Kayu pada Pekerja Mebel Informal di Kelurahan Antang Kecamatan Manggala Kota Makassar

2021 ◽  
pp. 743-756
Author(s):  
Andi Dyan Rezki Devi Chaeruddin ◽  
Hasriwiani Habo Abbas ◽  
Abd. Gafur
Keyword(s):  
Total Suspended Particulate ◽  
Suspended Particulate

Mebel Informal di Kelurahan Antang Kecamatan Manggala Kota Makassar adalah industri berskala rumah tangga (home industry) yang mengolah kayu menjadi produk furniture. Proses pengolahannya cenderung menghasilkan debu kayu yang dicurigai berpotensi menimbulkan kontaminasi polusi udara termasuk debu atau Total Suspended Particulate (TSP) di tempat kerja serta gangguan kesehatan pada pekerja mebel. Penelitian ini bertujuan untuk mengkaji risiko kesehatan lingkungan dari pajanan debu kayu pada pekerja di Mebel Informal Kelurahan Antang. Jenis penelitian yang digunakan adalah kuantitatif dengan desain studi Analisis Risiko Kesehatan Lingkungan (ARKL). Populasi dalam penelitian ini adalah seluruh pekerja di Mebel Informal UD. Haming dan UD. Pondok Mekar yang berjumlah 30 orang dengan menggunakan teknik total sampling. Teknik pengambilan data dengan menggunakan kuesioner dan wawancara serta melakukan pengukuran dengan alat. Data dianalisis dengan menggunakan analisis univariat dan Analisis Risiko Kesehatan Lingkungan (ARKL). Hasil penelitian menunjukkan bahwa rata-rata konsentrasi TSP di lokasi Mebel Informal telah melebihi Nilai Ambang Batas (NAB), serta berdasarkan perhitungan ARKL menunjukkan seluruh asupan (intake) pekerja baik realtime maupun lifetime masih berada di bawah dosis referensi dan estimasi besaran risiko pekerja terpajan TSP adalah RQ<1 yang artinya belum terjadi risiko pajanan TSP pada pekerja saat ini hingga beberapa tahun mendatang.   Kata kunci : Konsentrasi TSP; ARKL; pekerja mebel informal Mebel Informal di Kelurahan Antang Kecamatan Manggala Kota Makassar adalah industri berskala rumah tangga (home industry) yang mengolah kayu menjadi produk furniture. Proses pengolahannya cenderung menghasilkan debu kayu yang dicurigai berpotensi menimbulkan kontaminasi polusi udara termasuk debu atau Total Suspended Particulate (TSP) di tempat kerja serta gangguan kesehatan pada pekerja mebel. Penelitian ini bertujuan untuk mengkaji risiko kesehatan lingkungan dari pajanan debu kayu pada pekerja di Mebel Informal Kelurahan Antang. Jenis penelitian yang digunakan adalah kuantitatif dengan desain studi Analisis Risiko Kesehatan Lingkungan (ARKL). Populasi dalam penelitian ini adalah seluruh pekerja di Mebel Informal UD. Haming dan UD. Pondok Mekar yang berjumlah 30 orang dengan menggunakan teknik total sampling. Teknik pengambilan data dengan menggunakan kuesioner dan wawancara serta melakukan pengukuran dengan alat. Data dianalisis dengan menggunakan analisis univariat dan Analisis Risiko Kesehatan Lingkungan (ARKL). Hasil penelitian menunjukkan bahwa rata-rata konsentrasi TSP di lokasi Mebel Informal telah melebihi Nilai Ambang Batas (NAB), serta berdasarkan perhitungan ARKL menunjukkan seluruh asupan (intake) pekerja baik realtime maupun lifetime masih berada di bawah dosis referensi dan estimasi besaran risiko pekerja terpajan TSP adalah RQ<1 yang artinya belum terjadi risiko pajanan TSP pada pekerja saat ini hingga beberapa tahun mendatang.

scholarly journals Trace metal concentration in atmospheric aerosols in some city areas of Bangladesh

2015 ◽  
Vol 49 (4) ◽  
pp. 263-270 ◽  
Author(s):  
MN Mondol ◽  
M Khaled ◽  
AS Chamon ◽  
SM Ullah
Keyword(s):  
Particulate Matter ◽  
Trace Metal ◽  
Suspended Particulate Matter ◽  
Ambient Air ◽  
Motor Vehicles ◽  
Trace Metal Concentration ◽  
Total Suspended Particulate ◽  
Total Suspended Particulate Matter ◽  
Suspended Particulate ◽  
The City

Aerosol particulate matter and trace gases were sampled at five locations in the city areas of Bangladesh. The sampling sites were selected in the city areas near motor vehicles run with heavy traffic. The average concentrations of total suspended particulate matter in city ambient air were 413.02, 292.63, 671.65, 184.09 and 301.13 ?g m-³ in Dhaka, Noakhali, Chittagong, Faridpur and Kustia, respectively, which were higher than the daily average value, given by WHO and US EPA standard. The highest SPM concentration is in Chittagong (671.65 ?g m-³) and the lowest in Faridpur (184.09 ?g m-³). The city areas studied fall in the ‘Unhealthy” to “Extremely Unhealthy’ class according to the Air Quality Index, 2003. Trace metal concentrations of total suspended particulate matter in city ambient air were analyzed. The reported previous Pb concentration in farmgate, Dhaka was 1238 ng m-3 by Biswas et al., (2003) and now shows a decreasing tendency, presumably due to the ban on the use of leaded fuel. The average results of trace metals have been compared to national and international standards. The Cu and Zn concentration of current study is found very high in comparison with other previously reported results. The air of Chittagong city is highly polluted. Motor vehicles, especially two stroke engine vehicles are increasingly major sources of air pollution in Chittagong. DOI: http://dx.doi.org/10.3329/bjsir.v49i4.22630 Bangladesh J. Sci. Ind. Res. 49(4), 263-270, 2014

scholarly journals Correction of Light Scattering-Based Total Suspended Particulate Measurements through Machine Learning

Atmosphere ◽  
2020 ◽  
Vol 11 (2) ◽  
pp. 139 ◽  
Author(s):  
Qiaofeng Guo ◽  
Zhu Zhu ◽  
Zhen Cheng ◽  
Shuhong Xu ◽  
Xiaoliang Wang ◽  
...  
Keyword(s):  
Machine Learning ◽  
Light Scattering ◽  
Support Vector ◽  
Total Suspended Particulate ◽  
Hygroscopic Growth ◽  
Learning Models ◽  
Suspended Particulate ◽  
Scattering Measurements ◽  
Machine Learning Models ◽  
Mass Concentrations

Instruments based on light scattering used to measure total suspended particulate (TSP) concentrations have the advantages of fast response, small size, and low cost compared to the gravimetric reference method. However, the relationship between scattering intensity and TSP mass concentration varies nonlinearly with both environmental conditions and particle properties, making it difficult to make corrections. This study applied four machine learning models (support vector machines, random forest, gradient boosting regression trees, and an artificial neural network) to correct scattering measurements for TSP mass concentrations. A total of 1141 hourly records of collocated gravimetric and light scattering measurements taken at 17 urban sites in Shanghai, China were used for model training and validation. All four machine learning models improved the linear regressions between scattering and gravimetric mass by increasing slopes from 0.4 to 0.9–1.1 and coefficients of determination from 0.1 to 0.8–0.9. Partial dependence plots indicate that TSP concentrations determined by light scattering instruments increased continuously in the PM2.5 concentration range of ~0–80 µg/m3; however, they leveled off above PM10 and TSP concentrations of ~60 and 200 µg/m3, respectively. The TSP mass concentrations determined by scattering showed an exponential growth after relative humidity exceeded 70%, in agreement with previous studies on the hygroscopic growth of fine particles. This study demonstrates that machine learning models can effectively improve the correlation between light scattering measurements and TSP mass concentrations with filter-based methods. Interpretation analysis further provides scientific insights into the major factors (e.g., hygroscopic growth) that cause scattering measurements to deviate from TSP mass concentrations besides other factors like fluctuation of mass density and refractive index.

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