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be indicated that the ratio of N:D did not affect the degradation of COD by mixed culture bacteria but affect
the degradation time. The higher initial SCOD concentration required more degradation time to degrade
SCOD.
Table 1 Percent SCOD removal and degradation time
Initial SCOD Minimum SCOD % SCOD Time (hr)
removal
Batch (N:D) (mg/L) (mg/L) 96.0% 24
97.4% 24
A (100:0) 247 10 100% 24
96.7% 24
B (80:20) 312 8 97.4% 48
100% 72
C (60:40) 344 0
D (40:60) 390 13
E (20:80) 464 12
F (0:100) 509 0
The results of pH are shown in Figure 1. It was found that pH values in all conditions was in the range of 7.0
- 8.41 except in batch F which lower than 7. The pH of batch F was decreasing along the experiment period
because the stationary phase of batch F was reached earlier than the others batch.
PH A (n100, d0) pH C (n60, d40)
D (n40, d60) F (n0, d100)
9 B (n80, d20)
8 E (n20, d80)
7
6 DAY 1 DAY 2 DAY 3 DAY 4
5
4
3
2
1
0
DAY 0
Figure 1 The results of pH in each condition
MLVSS was measured to identity the increasing of biomass and determine the growth up efficiency. The
results are shown in Figure 2. Thus, the results showed MLVSS of all batch was increase in same trend. At
start of experiment, the initial bacteria 30 ml was added to reactor. The initial MLVSS in all batch was in the
range of 30-47.5 mg/L. After 24 hours, the MLVSS of all batch was increasing. The highest increasing of
MLVSS was found in batch E (N:D = 20:80). On the other hands, the lowest increasing of MLVSS was
found in batch F (N:D = 0:100). As the increasing of MLVSS represented the growth of bacteria. It can be
indicated that the bacteria growth of batch F was lowest. The results were the same with batch A (N:D =
100:0) which found the low growth of bacteria. Thus, it can be concluded that only diesel and only synthetic
solution has low ability to growth up bacteria. The growth up of bacteria need both diesel and nutrient in
synthetic solution. The optimal ratio of N:D was 20:80 as in batch E that provided the highest increasing of
bacteria resulted in high growth rate of bacteria.
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mg/L MLVSS
600
Batch B Batch C Batch D Batch E Batch F
500 Day 0 Day 4
400
300
200
100
0
Batch A
Day 1 Day 2 Day 3
Figure 2 MLVSS in each condition
The biomass yield was calculated as shown in Table 2. This study was focus on the volume of the microbial
community because it was necessary for startup the system. The highest biomass yield was found in batch E.
The result was same trends as MLVSS results. It indicated that the carbon source in batch E was
highly rated to degrade and promote growth up of mix culture. It can be indicated that the synthetic solution
added to reactor was affected the biomass growth and the ratio 20:80 of synthetic solution: diesel is the
optimum for growth up mix culture to degraded diesel. Thus, the growth of biomass depended not only
diesel but also glucose in synthetic solution. Glucose play role in a cometabolism or substrate as was found
in the study.
Table 2 Biomass yield in each batch
Yield (mg of MLVSS/mg of SCOD) A B Batch (N:D) E F
(10:0) (80:20) CD (20:80) (0:10)
0.2637 0.3026 (60:40) (40:60) 0.4535 0.0540
0.3197 0.3315
Effect of initial concentration naphthalene on degradation efficiency
The results showed that pH of all batch was found in the range of 6.52-7.99 at all batch conditions. The
MLVSS in every batch was increase in the same trend. That was indicated varied naphthalene concentration
was not affect to growth up the mix culture of bacteria. The biomass yield was calculated to indicate the
biomass growth in each batch by normalized the COD concentration in each batch. The results of biomass
yield are shown in Table 3, it can be indicated that the concentration of naphthalene affects biomass yield.
Thus, the optimal initial concentration of naphthalene was 20 mg/L which provided the high growth rate of
microbe.
Table 3 Biomass Yield of each batch A B Batch D E
20 mg/L 40 mg/L 80 mg/L 100 mg/L
Initial Naphthalene concentration C
Yield (mg of MLVSS/mg of SCOD) 1.6 0.5 60 mg/L 0.275 0.195
0.325
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The degradation of naphthalene in each batch was investigated. Figure 3 showed naphthalene concentration
in each batch. The results of degradation of naphthalene was the same trend in all batch. The naphthalene
was rapidly degraded in 2 hours and continuous degraded slowly. The highest naphthalene degradation was
found in batch A (99.8%) and followed by batch B (87.4%). The naphthalene degradation in batch C to E
was the nearly the same (75%). The efficiency and time to degrade naphthalene was affected by the initial
naphthalene concentration. The higher decrease naphthalene concentration provided the lower efficiency and
required more time to degrade. This resulted can imply that the suitable of initial napthalene concentration
was 20 mg/L.
48
mg/L
Figure 3 Naphthalene concentration in each batch during operating periods
As the government gazette of Thailand, naphthalene does not over 48 mg/L in underground water [10].
Microbe can degrade naphthalene of every batch to lower than 48 mg/L after 2 hours operation periods.
CONCLUSION
The mixed culture bacteria was high efficiency to remove organic compound from wastewater. The ratio of
N:D did not affect the degradation of COD by mixed culture bacteria but affect the degradation time. The
result of MLSS and MLVSS showed that the mix cultured was low degradable when degrade pure diesel or
pure synthetic solution. Thus, the ratio of synthetic solution and diesel added was affected the biomass
growth. The highest biomass yield (0.4535 mg of MLVSS/mg of SCOD) was found at N:D ratio of 20:80.
From the obtained results, the optimal ratio of N:D was 20:80 with the high SCOD removal efficiency and
biomass yield.
The mixed cultures of diesel degradation bacteria can degrade naphthalene 100% with varied concentration
in varied duration time. The highest efficiency of naphthalene degraded was found in lowest initial
concentration of naphthalene (20 mg/L). The suitable initial concentration of naphthalene was 20 mg/L
which provided the highest growth rate of microbes and the group of cultures can degrade the others
chemical that similar diesel structure as naphthalene.
ACKNOWLEDGEMENT
This research work was partially supported by Graduate School of Chiang Mai University and Chia Nan
University
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REFERENCE
[1] United States Environmental Protection Agency. Polycyclic Aromatic Hydrocarbons (PAHs).
Guidance for Reporting Toxic Chemicals: Polycyclic Aromatic Compounds Category, EPA 260-B-01-
03, 2008
[2] Wattayakorn, G. 2012. Petroleum pollution in the Gulf of Thailand: A historical review. Coastal
Marine Science, 35(1)
[3] Paul, J. T., Michael, M. R., Robin, D. P., Jim, B. 1996. Diesel combustion of an alkylated polycyclic
aromatic hydrocarbon. Fuel, 75(6).
[4] Hawai’i Department of Health, Office of Hazard Evaluation and Emergency Response. 2018.
Petroleum Fuels. http://www.hawaiidoh.org/tgm-content/0903a.aspx?f=T (accessed 3 March 2018).
[5] Singhyakaew, S. 2015. Phosphorus Recovery from Aerobic Membrane Bioreactor Effluent Using
Purolite A500 Resin and Chemical Precipitation. Master Thesis of Chia Nan University of Pharmacy
and Science.
[6] Britton, L. N. 1984. Microbial Degradation of Aliphatic Hydrocarbons. Microbial Degradation of
Organic Compounds.
[7] Shallu, S., Hardik, P. and Jaroli, D. P. 2014. Factors Affecting the Rate of Biodegradation of
Polyaromatic Hydrocarbons. International Journal of Pure&Applied Bioscience. 2(3).
[8] Zhong, Y., Luan, T., Wang, X., Lan, C., Tam, N. F. 2007. Influence of growth medium on
cometabolic degradation of polycyclic aromatic hydrocarbons by sphingomonas sp. strain PheB4.
Microbial Biotechnology. 75
[9] Banu, R. J., Uan, D. K. and Yoem, I. T. 2009. Nutrient removal in an A20-MBR reactor with sludge
reduction. Bioresource Technology. 100(16). 3820-3824.
[10] Thai government gazette. 2018. Notification of the Ministry of Industry the Government Gazette.
www.ratchakitcha.soc.go.th › DATA › PDF › 4.PDF (accessed 16 May 2018).
9th International Conference on Environmental Engineering, Science and Management
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Application of Geo-informatics Technology to Study Land Use
Changes for Agriculture at Wang Wiset District, Trang Province
Dungjai Sirirak1 and Tidarat Kumlom1*
1*Lecturer; 1Undergraduate, Environmental science Program, Faculty of Science and Technology,
Phuket Rajabhat University 83000
*Phone : 076-240-474 ext. 4000, Fax : 076-218-806, E-mail : [email protected]
ABSTRACT
The research aimed to study of land use for agricultural purposes in Wang Wiset District of Trang
Province occurred in 1993 and 2019 using satellite images acquired from LANDSAT 5 in 1993 and
LANDSAT 8 in 2019. The satellite images were interpreted and analyzed with a computer. The method of
supervised classification and normalized difference vegetation index (NDVI) and to study the land use
changes for agriculture by the information on land uses from both time periods was compared to identify
changes in land uses by union overlay function.
The study of land use for agriculture in 1993 indicated that the majority of land use was for the
cultivation of perennial with the area coverage of 314.12 km2 (65.84%), followed by 73.27 km2 (15.34%) of
forests land, and 53.96 km2 (11.31%) of miscellaneous lands. Meanwhile, in 2019, the majority of land use
was for the cultivation of perennial with the area coverage of 383.54 km2 (80.37%) followed by 50.99 km2
(10.69%) of forests land, and 15.62 km2 (3.27%) of urban and built-up land, respectively. In 2019, The
Kappa statistic was used in the analysis of data obtained from field survey in 2019 with the result of 0.75 and
overall accuracy at 80%, which considered the moderate level. The analysis of changes in land uses for
agricultural purposes which occurred during the last 26 years from 1993 to 2019 exhibited the alteration
from previous paddy field, forests, and miscellaneous lands in 1993 to the additional 69.42 km2 of perennial
cultivation areas, additional 0.97 km2 of orchard cultivation areas, additional 6.55 km2 of urban and built-up
land, and additional 0.01 km2 of poultry farm house. Meanwhile, there were the diminishing in the following
areas: 22.28 km2 of forests land. Forest lands have the most reduced areas. In which the forest land has been
changed to an agricultural land of 13.26 km2. (9.41%), 41.89 km2 of miscellaneous lands, and 10.62 km2 of
paddy field lands. This was due to the emerged para rubber and oil palms as the primary industrial crops of
Trang Province and these crops yielded the higher value products which yielded the highest value among the
southern provinces along the Andaman coast. Thus provoked the locals to alter their land use from the
previous paddy field and trespassed and clear cut the forests to seize the prohibited lands for unauthorized
para rubber and oil palms cultivations steadily increasing.
Keywords: Agriculture, Geo-informatics, Land use Change
INTRODUCTION
Land use is essential for agricultural occupations. The increase in population along with economic and
social growth and various aspects of the country's development has resulted in diminishing natural resources.
This is especially true in the rural regions where agricultural areas are insufficient and eventually caused the
intrusions into forests to utilize the lands for agricultural purposes and deterioration of natural resources and
environments as a result [1]. The Royal Decree in 1993 regulated the forests in Khao Pra - Bang Kram of
Khlong Thom District in Krabi Province, Wang Wiset and Sikao District of Trang Province as Wildlife
Sanctuary. Furthermore, the Decree revoked forest concessions and discontinued land reform operations for
farmers in Wang Wiset District of Trang Province. Two main industrial crops of Trang Province, Para
Rubber (Hevea brasiliensis) and Oil Palm (Elaeis guineensis) which yielded the highest value among the
southern provinces along the Andaman coast were cultivated in the regulated areas. Para Rubber became the
province’s primary industrial crop since 2005 to present [2] and thus provoked the locals to trespass and
clear cut the forests to seize the prohibited lands for unauthorized farming and the locals have since
increasingly cultivated para rubber and oil palms. The deterioration of natural resources and environments
may occur anywhere. The modern geo-informatics technology has been applied to survey, monitor, and
inspect geographical changes due to its decent advanced abilities and accuracy of the provided results. Geo-
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informatics is the fast and affordable approach in addressing geographical problems. Providing such various
benefits, the author thus adopted geo-informatics technology for the survey and classification of land uses for
agricultural purposes and the monitoring of changes that occurred in the alterations of lands from previous
paddy field to the cultivation of para rubber and oil palms. It was an interest of the author to apply geo-
informatics technology in the observation of changes occurred in land uses for agricultural purposes at Wang
Wiset District of Trang Province and to make a comparison of such changes between the year 1993 and 2019
to provide the insights regarding changes in land uses for associated authorities to apply in the land
management and stipulate the strict actions for the supervision and protection of forests against the
unauthorized intrusions and exploitations.
METHODOLOGY
The data and instruments used in the study were satellite images in the territory of Wang Wiset
District of Trang Province acquired from LANDSAT 5 (as of April 10, 1993) and LANDSAT 8 (as of March
11, 2019), computer, printer, GPS, digital camera, and geo-informatics software.
Methodologies: the author studied land uses for agricultural purposes in Wang Wiset District of Trang
Province that occurred in 1993 and 2019 using satellite images acquired from LANDSAT 5 in 1993 and
LANDSAT 8 in 2019. The satellite images were interpreted and analyzed with a computer. The method of
supervised classification and normalized difference vegetation index (NDVI) were applied in the
examination of alterations that occurred from land uses for agricultural purposes in Wang Wiset District of
Trang Province during 1993 and 2019. The information on land use from both time periods was compared to
identify changes in land uses by Union Overlay Function in Figures 1 and 2.
Satellite Image (Landsat 5, 8)
Pre-Processing
Supervised Classification/NDVI
Ground Survey
Post Classification
Land use Map in 1993 and 2019
Overlay by Union
Land use Change
Figure 1 Chart showing the process of Figure 2 Study Area
study the Land Use Changes for
Agriculture at Wang Wiset District,
Trang Province in 1993 and 2019
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RESULTS AND DISCUSSIONS
1. Result of land uses for agricultural purposes in Wang Wiset District of Trang Province in 1993 and
2019
According to the modification of the satellite imagery interpretation using the supervised classification
and the vegetation index analysis, the lowest and the highest normalized difference vegetation index (NDVI)
were reported as -1 and 0.4 in 1993, and -0.1 and 0.6 in 2019. The difference of NVDI between time points
is in good agreement with the previous report Parinya Sakkanayok et al., (2008) [3] which revealed the
lowest and the highest NDVI as -1 and 0.2 in 2006, and -0.4 and 0.4 in 2008. The NDVI of the identical type
of land cover is different. The NDVI of -1 – 0.29 indicates an absence of the land cover e.g. water body and
agricultural area. The NDVI of 0.3 – 0.59 represents the low vegetation land cover because of the difference
between the environment and air humidity due to the regular changes in the land utilization for agriculture.
Data classification of agricultural areas. The research results can be classified into 8 types of land use
which are perennial, paddy field, orchard, poultry farm house, forest land, miscellaneous land, urban and
built-up land and water body. In corresponding with the previous report [3], the land use classification is
divided into 8 types which are paddy field, grassland, mixed horticulture, para rubber, perennial, forest land,
mangrove forest and shrimp farm. In 1993, it was found that the most use of land for perennial areas,
followed by paddy field and orchard and in 2019, it was found that land use for agriculture, perennials areas
at the most followed by the orchard, paddy field and Poultry farm house respectively
The study of land use for agricultural purposes in Wang Wiset District of Trang Provinceoccurred in
1993 indicated that the majority of land uses was for the cultivation of perennial with the area coverage of
314.12 km2 (65.84%), followed by 73.27 km2 (15.34%) of forests land, and 53.96 km2 (11.31%) of
miscellaneous lands. Meanwhile, in 2019, the majority of land uses was for the cultivation of perennial with
the area coverage of 383.54 km2 (80.37%) followed by 50.99 km2 (10.69%) of forests land, and 15.62 km2
(3.27%) of urban and built-up land, respectively. The Kappa statistic was used in the analysis of data
obtained from field research in 2019 with the result of 0.75 and overall accuracy at 80%, which considered
the moderate level which corresponds with the previous report Khampeera, T et al., (2007) [4] found that the
overall accuracy of the classification is 94.90% and kappa statistics is 0.93 and has been checked with the
land use data of the Land Development Department shows that this classification of land use is at a moderate
level. Follow in Tables 1, 2 and 3.
Table 1 Data of Land use in 1993 and 2019
Types of land use 1993 (km2) Percentage 2019 (km2) Percentage
Perennial 314.12 65.84 383.54 80.37
Paddy field 11.56 2.42 0.94 0.20
Orchard 3.51 0.74 4.48 0.94
0.00 0.00 0.01 0.002
Poultry farm house 73.27 15.34 50.99 10.69
Forest land 53.96 11.31 11.87 2.49
9.07 1.90 15.62 3.27
Miscellaneous land 11.68 2.45 9.72 2.03
Urban and Built-up land 477.17 100 477.17 100
Water Body
Total
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Field survey data checking by going to the area on December 9-10, 2019 as in Table 2
Table 2 Field survey data collection
Coordinates Types of land Field Survey Sattlelite image
use
X : 546121 Para Rubber
Y : 848140
X : 534571 Oil Palms
Y : 864869
X : 549915 Paddy field
Y : 848264
X : 539571 Orchard
Y : 855777
X : 552555 Water Body
Y : 844817
X : 551825 Forest land
Y : 844650
X : 550665 Urban and Built-
Y : 847384 up land
X : 542726
Y : 855405
Miscellaneous
land
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The examination and the analysis of field survey data with the data collected from the satellite
imagery interpretation demonstrated the similar area characteristics. The information of the changes in land
utilization is shown in Table 3.
Table 3 Field survey data for land use in Wang Wiset District, Trang Province.
Land use Ground Survey
Classification A3 A1 A4 F U M W Total
A3 4 0 100 0 05
1 03
A1 0 2 000 0 02
1 0 10
A4 0 0 200 0 0 10
7 0 10
F 10 080 2 7 10
11 7 50
U 00 0 0 10
M 10 110
W 10 000
Total 72 3 9 10
Overall Accuracy from field survey = 80 %
Kappa Coefficient = 0.75
Note:
Urban and Built-up land: U, Forest land: F, Miscellaneous land: M, Water Body: W
Paddy field: A1, Perennial: A3, Orchard: A4, Poultry farm house: A7
2. Land use change for agriculture at Wang Wiset District, Trang Province, 1993 and 2019
The analysis of change in land use for agricultural purposes in Wang Wiset District of Trang Province
ccurred during the last 26 years from 1993 to 2019 exhibited the alteration from the previous paddy field, forests,
and miscellaneous land in 1993 to the additional 69.42 km2 of perennial cultivation areas in accordance with Geo-
Informatics and Space Technology Center (Southern) (2012) [5], revealing that the Songkhla Lake Basin area
has reduced the area of 25.30 % by changing to para rubber, orchard and oil palm. Additional 0.97 km2 of orchard
cultivation area, additional 6.55 km2 of urban and built-up land, and additional 0.01 km2 of poultry farm house.
Meanwhile, the diminishing of 22.28 km2 of forests land. This is in accordance with Natthapong Puangkaew et
al., (2016) [6] stating that the forest area has the most reduced area, at where the forest area has been changed to
an agricultural area of 13.26 km2 (9.41%), 42.09 km2 of miscellaneous areas, 10.62 km2 of paddy field area. There
was a 91.87 % decrease in paddy field area and 30.41 % decrease in forest area. It indicated that such mentioned
areas had changed to be the most perennial area such as rubber, oil palm. In accordance with Khamphee,T et al.
(2007) [4], revealing that the change of paddy field area to rubber plantation area was 31.66 % followed by
changing to an area of 1.21% fruit plantation. At Phatthalung District, paddy field area changed to rubber planting
area of 23.68%, and 1.96 km2 of water body area.
Such change was due to the emerged para rubber and oil palms as the primary industrial crops of Trang
Province and these crops yielded the higher value products among the southern provinces along the Andaman
coast. Thus provoked the locals to altered their land uses from the previous paddy field and trespassed and clear
cut the forests to seize the prohibited lands for unauthorized para rubber and oil palms cultivations steadily
increasing as presented in Table 4 and Figure 3.
Table 4 The analysis of changes in land uses for agricultural
Types of land use Land use change Percentage
22.10
Perennial + 69.42 91.87
27.64
Paddy field - 10.62 0.002
30.41
Orchard + 0.97 78.00
72.22
Poultry farm house + 0.01 16.78
Forest land - 22.28
Miscellaneous land - 42.09
Urban and Built-up land + 6.55
Water Body - 1.96
Note: + Increase / - Decrease
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Figure 3 Land use in 1993 and 2019
Information of changes in land use Wang Wiset District, Trang Province, between 1993 to 2019,
obtained from the study in a tabular form as shown in Table 5.
Table 5 Comparative data of land use change Wang Wiset District, Trang Province, in 1993 and 2019
Land Use 2019 (km2)
1993 (km2)
Agricultural Land F M U W Total
A3 A1 A4 A7
Agricultural A3 313.27 0.00 0.67 0.01 0.00 0.01 0.16 0.00 314.12
Land
A1 9.33 0.93 0.11 0.00 0.00 0.33 0.78 0.08 11.56
A4 0.00 0.00 3.51 0.00 0.00 0.00 0.00 0.00 3.51
A7 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
F 20.73 0.00 0.01 0.00 50.90 0.00 1.61 0.02 73.27
M 40.20 0.01 0.15 0.00 0.09 9.45 4.00 0.06 53.96
U 0.00 0.00 0.01 0.00 0.00 0.00 9.06 0.00 9.07
W 0.01 0.00 0.02 0.00 0.00 2.08 0.01 9.56 11.68
Total 383.54 0.94 4.48 0.01 50.99 11.87 15.62 9.72 477.17
Note:
Urban and Built-up land: U, Forest land: F, Miscellaneous land: M, Water Body: W
Paddy field: A1, Perennial: A3, Orchard: A4, Poultry farm house: A7
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Perennial
The perennial area is still a perennial area of 313.27 km2 and changed to other areas as follows, 0.67
km2 of orchard, a poultry farm house area of 0.01 km2, forest area of 0.40 km2 , a miscellaneous area of 0.01
km2, urban and built-up land of 0.16 km2, water body of 0.01 km2.
Paddy field
The paddy field is still a paddy field of 0.93 km2 and changed to other areas as follows: perennial
area of 9.33 km2. area of orchard of 0.11 km2, miscellaneous area of 0.33 km2ม urban and built-up land of
0.78 km2, and water area of 0.08 km2.
Orchard
The orchard area is still 3.51 km2. No change to other areas
Poultry farm house
No changes in poultry farm house areas
Forest land
The forest land is still a forest land of 50.90 km2 and changed to other areas as follows: perennial
area of 20.73 km2, orchard of 0.01 km2. Urban and built-up land of 1.16 km2, and water body of 0.02 km2.
Miscellaneous land
Miscellaneous land is still 9.45 km2 and changed to other areas as follows, 40.20 km2 perennial area,
paddy field area of 0.01 km2, orchard of 0.15 km2, forest area of 0.09 km2, urban and built-up land of 4.00
km2 and water body of 0.06 km2.
Urban and built-up land
Urban and built-up lands are still urban and built-up lands of 9.06 km2, and changed to orchard area
of 0.01 km2.
Water body
The water body is still 9.56 km2, and changed to other areas as follows; perennial area of 0.01 km2.
0.02 km2 of orchard, miscellaneous area of 2.08 km2 and urban and built-up land of 0.01 km2.
Noting that there are various organizations deal with the same land use type. For example; for forest
protection e.g. the Royal Forest Department and Department of National Parks, Wildlife and Plant
Conservation. Moreover, the integration of the central departments and the local organizations area is
needed. Furthermore, people living in the local area should cooperate and monitor to protect the forest.
Nevertheless, the strict preventive measure of protected areas with the penalty for the offender is also
important. Regarding the Forest Act, B.E. 2484 (1941) of section 54 and 54, no person shall construct,
reclaim, burn forest, or do any manner whatsoever to destroy forest, or hold, or possess forest for himself or
other person without the permission. In the National Reserved Forest Act, B.E. 2507 (1964) of section 14, no
person shall hold or possess land, live, make a construction, reclaim, burn forest, or do any matter
whatsoever with purport to harm or decay a condition of national reserved forest without the permission. For
the Wildlife Reservation and Protection Act, B.E. 2535 (1992) of section 37, no person shall enter a wildlife
sanctuary without the permission; while section 38, no person shall possess, occupy the land, or build up, or
any other means whatsoever to construct, or cut, fell, reclaim, burn, or destroy trees or any other flora
without the permission from the authorities [7]. Furthermore, the consecutive monitoring of change should
be performed to protect and manage the forest. Also, the preventive measure is strongly required for further
management of land utilization.
The study on the land utilization for agriculture revealed that the agricultural area is increasing while
the forest area is decreasing. To prevent an increase of agricultural area in the protected area and further
decrease of forest area, the cooperation among many line agencies both central and local sectors as well as
with the communities are strongly required.
CONCLUSION
The adoption of geo-informatics technology to study the changes that occurred in land uses for agricultural
purposes at Wang Wiset District of Trang Province indicated that the majority of land uses was for the cultivation
of perennial plants: para rubber and oil palms. The alteration of agricultural land uses also resulted in the
diminishing of paddy field areas (at 91.87%) and forests (at 30.41%). The altered areas have been dominated by the
cultivation of perennial plants.
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ACKNOWLEDGEMENT
Thank you, Environmental Science Program, Faculty of Science and Technology, Phuket Rajabhat
University that has provided various information and suggestions that are very useful for this research and
make the research work well accomplished.
REFERENCE
[1] Thirakan Srithairak, Tuenjai Noochdamrong, Komon Pragtong and Rachanee Photitan. 2007.
Agriculture Land Use Change of Local Communities in Westurn Forest Complex. Kasetsart
University Academic Conference 45th: Architecture and Engineering Program Natural Resources
and Environment Branch, Page 633-642 Cooperatives, 20 16 Retrieved from
[2] Ministry of Agriculture and
https://www2.moac.go.th/download/moac_report/2016/moac_report_aug2016.pdf
[3] Parinya Sakkanayok and Terdsak Laksanahut. 2008. The use of geographic information technology
and remote sensing data to monitor changes in watershed conditions Pak Phanang. Retrieved
February 2, 2018 from http://kmcenter.rid.go.th/kmc15/KMC15%202551-2553/H1-1-2.php
[4] Khampeera, .T, Yongsatitsak, .T, Suphavilai, .R , Yongchalermchai, .C. 2007. Applications of
SPOT–5 Satellite Images to Study the Landuse Changes from Paddy Fields into others Cash
Crops such as Para rubber, Oil Palm or Mixed-Orchard Plantations. The Case-study: Phattalung
Muang District, Khao Chaison District and Bang Kaeo District, Phattalung Province.
[5] Geo-Informatics and Space Technology Center (Southern) Faculty of Environmental
Management Prince of Songkla University. 2012. Application of Geo-informatics for Paddy
Field Zoning in Songkhla Lake Basin. Complete report Regional Center for Geo-Informatics and
Space Technology, Prince of Songkla University Geo-Informatics and Space Technology
[6] Nattapong Puangkaew and Russana Salae. 2016. Forest Area Changes in Tonenga Chang Wildlife
Sanctuary. The 7th National and International Academic Conference on Hat Yai, 23 June 2016
(Page 1377-1387), Hat Yai University.
Development Agency (Public organization).
[7] Thailand Development Research Institute (TDRI). 2015. Forest resources. Retrieved January 11,
2018, from http://forestinfo.forest.go.th/
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Effects of Vinasse Concentration and Aeration Rate on Fungal Protein
Production in Bubble Column Bioreactor
Akethakorn Thaworn1 and Saoharit Nitayavardhana2*
1Graduate student, Department of Environmental Engineering, Faculty of Engineering/Graduate School,
Chiang Mai University, Chiang Mai 50200, Thailand;
2*Assistant Professor, Department of Environmental Engineering, Faculty of Engineering,
Chiang Mai University, Chiang Mai, Thailand;
*Phone : 097-238-8313, E-mail : [email protected]
ABSTRACT
This study examined the potential of producing fungal biomass, Rhizopus oligosporus, as an
aquaculture feed ingredient on vinasse generated during sugar-to-ethanol production. A bubble column
bioreactor (2.5-L working volume) was used for fungal cultivation under various organic concentrations
measured as COD (25, 50, 75, and 100 g/L) and aeration rates (1.0, 1.5, and 2.0 vvm
(volumeair/volumeliq/min)) at 37 ºC and pH 5.0 for 5 days. The fungal biomass yield depended on COD
concentration and aeration rate, the suitable condition was COD concentration of 50 g/L and aeration rate of
2.0 vvm, which resulted in a maximum fungal biomass yield of 12.29±1.09 gdry weight and COD removal of
39%. The fungal biomass was found to have 23.37% protein with essential amino acids. The produced fungal
biomass was nutritious and possibly suitable for use as a protein source in aquaculture feed.
Keywords: Aquaculture feed; Fungal fermentation; Rhizopus oligosporus; Vinasse
INTRODUCTION
Aquaculture industry is facing problem regarding high production cost due to the expensive fish
meal ingredient used to produce aquaculture feed [1, 2]. The use of alternative low-cost protein ingredient
could possibly lower the overall production cost. Microbial protein would be a promising option for
commercial scale application as the process can be easily controlled and high yield could be obtained. The
food grade fungus, Rhizopus oligosporus (R. oligosporus), commonly used to produce tempeh, a local food
in Indonesia, has been certified as safe, edible and rich in protein [3]. This fungus can use a variety of
substrates for growth. R. oligosporus produces cells biomass which is rich in protein, approximately 50% of
dry weight, and various amino acids that are necessary for use as aquaculture feed protein supplement [4, 5].
The fungus has been proven to grow well in vinasse, a liquid residue leftover from ethanol production of
sugar-based feedstock with a great potential for wastewater treatment [4, 5]. The production of fungal protein
from vinasse could mitigate environmental concern over vinasse/ethanol effluent disposal as it contains
significantly high in organic content (50-150 g/l measured as chemical oxygen demand (COD)), low pH of
3.0-5.0 with dark brown color and unpleasant smell [6]. Direct vinasse discharge can cause soil salification,
metal and nutrient leaching into surface and groundwater, and alterations in soil quality (such as nutrients
imbalance and reduction of alkalinity) [7, 8].
Although fungal protein has been successfully produced from vinasse, 3 days for fungal seed culture
preparation is needed which resulted in a total of 6 days requirement for the process [4]. Elimination of the
seed culture preparation state not only could lower the time for fungal protein production but also the
production cost as no nutrient and less process requirement. Therefore, this research aimed at using vinasse
as a substrate for culturing R. oligosporus using fungal spore inoculation directly into vinasse. Our specific
objective was to investigate the effects of organic concentrations and aeration rates on fungal growth. The
nutritional characteristics of the produced fungal biomass was also determined.
METHODOLOGY
Vinasse samples
The vinasse sample obtained from Tanapakdi Co., Ltd., Chiang Mai was used as a substrate for
fungal cultivation. Vinasse sample was kept at 4 ºC until use. After dilution of the vinasse as required COD
concentration Will be sterilized with autoclave at 121 ºC for 15 minutes before culturing the fungus. The
characteristics of vinasse sample are presented in Table 1.
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Table 1 Characteristics of vinasse sample.
Parameter Values
pH 4.26±0.02
Chemical Oxygen Demand (COD) (g/L) 150±0.47
Soluble COD (SCOD) (g/L) 140±2.18
Total Kjeldahl Nitrogen (TKN) (g/L) 4.77±0.23
Total phosphorus (TP) (mg/L) 55.77±5.33
Potassium (K) (mg/L)
Total solids (TS) (g/L) 15,300
Volatile solids (VS) (g/L) 136±0.24
Total suspended solids (TSS) (g/L) 102±0.31
Volatile suspended solids (VSS) (g/L) 20±3.13
COD: N: P 17±2.63
100:3.18:0.04
Fungal culture
The fungus used in this research was Rhizopus oligosporus TISTR 3616 derived from TISTR:
Biodiversity Research Centre. The fungus was grown on PDA (Potato dextrose agar) and incubated at 30 ºC
for 5-7 days. To prepare fungal spore suspension. A mixed solution of 0.1% (w/v) peptone and 0.2% (v/v)
Tween 80 in sterile deionized water was used to harvest fungal spores. Harvested fungal spore suspensions
(106-107 cells/ml) were kept in glycerol (20% v/v) at -18 ºC prior to use as a spore inoculum.
Fungal cultivation
The fungus was cultured in a bubble column bioreactor (2.5-L working) (Fig.1) under various
organic concentrations measured as COD (25, 50, 75, and 100 g/L) and aeration rates (1.0, 1.5, and 2.0 vvm
(volumeair/volumeliq/min)). The pH and temperature were controlled at 5.0 and 37 ºC, respectively. Fungal
cultivation was conducted for 5 days. Organic removal efficiency and fungal biomass yield were evaluated to
obtain suitable fungal growth condition.
Fungal biomass characterization
To study the suitability of the fungal protein used as a protein substitute in aquaculture feed, crushed
dry fungal biomass (at 65 ºC) was analyzed for nutritional values (ash, carbohydrates, energy, fat, moisture,
protein, minerals, and essential amino acids).
Figure 1 Schematic diagram of a bubble bioreactor system.
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RESULTS AND DISCUSSIONS
The effect of the organic matter concentration of vinasse and the aeration rate on the growth of fungal
biomass.
Figure 2 Fungal biomass production and COD removal for various COD concentrations of vinasse and
aeration rates. The bar graph represents fungal biomass and the scatter plot graph represents COD
removal.
The fungal biomass production and COD removal are summarized in Fig 2. It was found that the
best evaluated condition for fungal cultivation was at COD concentration of 50 g/L and aeration rate of 2.0
vvm which resulted in a maximum fungal biomass yield of 12.29±1.09 gdry weight with COD removal of 38.73
± 0.80 %. When compared within the same COD concentration value, it was found that increasing the
aeration rate resulted in increased fungal biomass yield. Increasing in aeration rate would enhance gas mass
transfer in the bioreactor resulted in high fungal biomass production. However, the fungal biomass yield
decreased to 3.95±0.24 gdry weight at an aeration rate of 2.5 vvm (data not shown here) presumably because the
intensive turbulent flow in the liquid phase caused a shear force that impacted the fungal growth [4].
COD concentration of vinasse also affects the fungal growth. The higher organic substance in
feedstock, the higher amount of fungal biomass could be obtained. Considering fungal cultivation at the best
aeration rate of 2.0 vvm, fungal biomass yield obtained from sample containing COD concentrations of 25
and 50 g/L were 6.81 ± 0.36 and 12.29 ± 1.09 with COD removals of 73.18 ± 7.59% and 38.73 ± 0.80%,
respectively. The high COD concentration of 75 g/L had an adverse effect on fungal biomass production
resulted in only 1.14 ± 0.47 gdry weight of fungal biomass and 48.71 ± 1.86 % of COD removal were obtained.
The R. oligosporus was unable to grow on the substrate containing 100 g/L of COD (data not shown here).
This would be due to a large amount of fungal growth inhibitors, such as yeast residues in vinasse [9]. The
organic removal measured as COD from sample with little amount of fungal biomass production could be
due to other undesired microorganism growth during cultivation process.
Interestingly, this research shows the possibility of fungal cultivation using direct spore inoculum,
which could make the fungal fermentation process simpler as the fungal mycelia preparation step could be
eliminated. This could lower the production cost as no Yeast Mold (YM) broth needed to prepare fungal
mycelia inoculum and time for inoculum preparation. When compared to other researches using fungal
mycelia inoculum, fungal cultivation using spore inoculum could be done at higher aeration rate (2.0 vvm)
compared to the aeration rate of fungal cultivation using fungal mycelia inoculum (1.5 vvm), resulted in
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higher fungal biomass production by 29% [4]. Moreover, nutrient supplementation which was not done in
this research could possibly enhance the biomass production significantly as shown in previous research [4].
Fungal biomass characterization.
Fungal biomass could be a source of protein substitution in aquaculture feeds. Table 2 shows that the
produced fungal had lower protein content than the requirements in aquaculture feeds with high amounts of
fat. The low protein would be due to washing step after harvest the fungal biomass to minimize dry weight
error from solids attached on the fungal product (other research 40-50 % protein content) [4, 5], which could
be easily mitigated by direct use of the fungal protein with no washing applied. High fat content in the fungal
biomass resulted from vegetable oil added into the process as an antifoaming. The use of other antifoaming
agent can lower the fat content of the fungal protein.
Table 2 The nutritional value of the fungal biomass and nutritional requirement in aquaculture feeds.
Parameter unit Fungi biomass Needs in aquaculture feeds*
Protein % 23.37 25-50
dry 23.64 20-50
proximate Carbohydrate weight 41.11
3.08 10
Fat % 0.46 0.3-0.5
protein 2.97
Minerals Calcium 2.35 0.60
Phosphorus 0.09 5.30
1.15 3.10
Lysine 0.23 0.70
1.12 3.50
Threonine 2.03 3.60
2.18 2.80
Tryptophan 1.53 4.00
1.90
Essential Valine 6.30
Amino Methionine
Acid Isoleucine
Leucine
Histidine
Phenylalanine
Source: * [10]
CONCLUSION
The vinasse concentration and aeration rate affected the growth of the fungus. The suitable condition
was COD concentration of 50 g/L and aeration rate of 2.0 vvm. Fungal cultivation using direct fungal spore
inoculation resulted in fungal biomass yields similar to that of the system using fungal seed culture [4, 5].
This can reduce process, time and the cost of fungal culture. The produced fungal biomass was nutritious,
suitable for use as a protein source in aquaculture feeds, which can possibly be used to replace some other
protein sources. And vinasse after fungal culture had lower organic content by 39%.
ACKNOWLEDGEMENT
This research was supported through CMU Junior Research Fellowship Program (Grant No.
R000017092). The authors would like to express our gratitude to Thanapakdi Co., Ltd., Chiang Mai for
supplying vinasse sample. We also gratefully acknowledge laboratory staffs at Energy Research and
Development Institute - Nakornping and the Department of Environmental Engineering, Faculty of
Engineering, Chiang Mai University for their supports.
REFERENCE
[1] Prachom, N., Y. Haga, and S. Satoh, Impact of dietary high protein distillers dried grains on amino
acid utilization, growth response, nutritional health status and waste output in juvenile rainbow trout
(Oncorhynchus mykiss). Aquaculture Nutrition, 2013. 19: p. 62-71.
[2] Tacon, A.G.J. and M. Metian, Global overview on the use of fish meal and fish oil in industrially
compounded aquafeeds: Trends and future prospects. Aquaculture, 2008. 285(1-4): p. 146-158.
[3] Schauer, F. and R. Borriss, Biocatalysis and biotransformation, in Advances in Fungal
Biotechnology for Industry, Agriculture, and Medicine, J.S. Tkacz and L. Lange, Editors.
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[4] Nitayavardhana, S., et al., Production of protein-rich fungal biomass in an airlift bioreactor using
vinasse as substrate. Bioresour Technol, 2013. 133: p. 301-6.
[5] Nitayavardhana, S. and S.K. Khanal, Innovative biorefinery concept for sugar-based ethanol
industries: production of protein-rich fungal biomass on vinasse as an aquaculture feed ingredient.
Bioresour Technol, 2010. 101(23): p. 9078-85.
[6] Christofoletti, C.A., et al., Sugarcane vinasse: environmental implications of its use. Waste Manag,
2013. 33(12): p. 2752-61.
[7] Smeets, E., Junginger, M., Faaij, A., Walter, A., Dolzan, P., Turkenburga, W., The sustainability of
Brazilian ethanol an assessment of the possibilities of certified production. Biomass and Bioenergy
32, 2008: p. 781–813.
[8] Navarro, A.R., Sepúlveda, M.del C., Rubio, M.C., Bio-concentration of vinasse from the alcoholic
fermentation of sugar cane molasses. Waste Management 20, 2000: p. 581–585.
[9] Niraphai, K. and E. Chukeatirote, Biology of Lasiodiplodia spp. Srinakharinwirot Science Journal,
2009. 25: p. 119-134.
[10] Tanaporn Chittapalapong, Creating aquaculture and economic aquaculture formulas. 2014, Central
Administrative Office Department of Fisheries.
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Occupational Hazard Identification in Plastic Recycling Plants in
Thailand: Case studies of Polyethylene and Polypropylene
Ayaj Ansar1 Mongkolchai Assawadithalerd2 Danai Tipmanee3 Laksana Laokiat4
Pummarin Khamdahsag5 and Suthirat Kittipongvises5*
1Graduate student, International Postgraduate Programs in Hazardous Substance and Environmental
Management, Graduate School, Chulalongkorn University, Bangkok, Thailand;
2Researcher, Center of Excellence for Environmental and Hazardous Waste Management (EHWM),
Chulalongkorn University, Bangkok, Thailand;
3Lecturer, Faculty of Technology and Environment, Prince of Songkla University Phuket Campus, Thailand;
4Associate Professor, Faculty of Public Health, Thammasat University, Thailand;
5 Environmental Research Institute, Chulalongkorn University (ERIC), Bangkok 10330, Thailand
E-mail* : [email protected]
ABSTRACT
The recycling of plastic solid waste (PSW) is the highly desirable way for resource, energy conservation and
reduction in pollution emissions compared to other alternatives to minimize the global exponential growth of
PSW. The mechanical recycling approach is the commonly adopted recycling approach in small scale
recycling plants in Thailand. This recycling process includes a series of mechanical and thermal driven
stages that may lead to various occupational hazards. Accordingly, every industry has to identify the hazards,
assess associated risks, and reduce those risks to acceptable levels to improve occupational safety and health.
In this research, hazard identification and risk assessment were performed for four selected small-scale
plastic recycling plants of polypropylene (PP) and polyethylene (PE) in Thailand. Physical hazards (heat and
noise) and chemical hazards from volatile organic compounds (VOCs) were the main two groups of hazards
identified in the initial step. Exposure assessment and risk evaluation were carried out for all three main
identified hazards to determine the group of workers at risk and risk levels for further management actions.
Most of the determined values of heat and noise exposure assessments were exceed the standards. The high
noise level above 90 dBA was found at shredding areas of all plants. Also, heat stress values at extrusion
were shown a considerable increment within 4.5oC to 5.5oC than standard heat stress values. Besides,
breathing difficulty and odor nuisance observed at the premise’s inspection step, due to VOC emission from
the extrusion process. In conclusion, machine operators of shredding machine and extruder are the group of
workers at higher risk, and risk control strategies are highly recommended to minimize these identified risks.
Keywords: Plastic recycling, Small-scale industries, Occupational hazards, Risk evaluation
INTRODUCTION
The global production of plastic and the associated plastic solid waste (PSW) generated by households and
industries have grown exponentially in recent decades. This growing amount of PSW can lead to various
environmental problems [1]. Dealing with these enormous PSW remains a challenging task in many
countries including Thailand. Over the past decade in Thailand, plastic waste has increased by 12% or ~ 2
million tons every year, and the concerns have also increased due to the non-degradability of plastic and
toxic gas that is generated from plastic waste incineration. Out of all types of plastics, polyethylene (PP) and
polypropylene (PE) contributed approximately 90% of total plastic waste in Thailand [2]. To manage PSW,
the recycling of PSW is a highly desirable way for resource, energy conservation and reduction in waste gas
emissions compared to other alternatives [1]. Accordingly, waste recyclers play an important role in the
plastic waste management network in Thailand. In 2013, the amount of PSW that was recycled by
manufacturers in Thailand was approximately 0.77 Mt or 22% of post consumed waste and 0.8 Mt of
recyclable PSW (10% from entire production) [2].
The mechanical recycling approach is the commonly adopted recycling approach in small scale recycling
plants in Thailand. In the process of mechanical recycling, raw materials subjected to mechanical processes
(shredding, pelletizing) and thermal processes (melting/extrusion) to produce pellets as raw material for
plastic manufacturing industries. However, these mechanically and thermally driven stages may lead to
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various occupational hazards including physical, chemical, etc.[3]. Moreover, small scale enterprises (SSEs)
have a worse safety record than large ones. It seems that the rate of fatal and serious injuries in SSEs
(defined as those with fewer than 50 employees) is twice that in larger workshops. Economically weakness
of SSEs without adequate management conditions and less preparation with minimal assets and the ability
for working environment improvements compared to larger enterprises might be the main reasons for this
difference [4]. On the other hand, occupational safety and health (OSH) legislation in most countries
including Thailand have exempted small scale enterprises (SSEs) and are generally applicable only to
manufacturing industries. Accordingly, small businesses with fewer than 50 employees are not obligated to
perform health management or appoint a health manager under the current Thai ministerial regulations for
OSH [5]. Similarly, in Thailand, most small scale PSW recycling plants are also not implementing good
manufacturing practices and safety protocols due to the unavailability of proper OSH management systems
(OHSMS), which may create a pathway to high-risk situations in the working environment. On this basis,
every industry must identify hazards, assess associated risks, and minimize those risks to acceptable levels
continuously to improve occupational safety and health. As a result of these, most countries have basic
requirements that employers must meet as OSH standards. Occupational hazard identification and risk
assessment help to identify risks and provide information for decision making at these types of industries to
implementing risk control and management strategies [6]. Moreover, occupational hazard identification and
risk evaluation are considered as an initial implementation of OSHMS for SSEs [7]. By considering all the
mentioned factors, this research aims at identifying occupational hazards and assessing the associated risk.
3.0 METHODOLOGY
3.1 Study Scope and Goal
Four PSW recycling plants (Plants A, B, C & D) located in Thailand were selected as case studies. These
plants perform palletization from both PE and PP resins. Plants A (PP), B (PE+PP) C (PE), and D (PE)
categorized as a small scale based on the employees‘ number [3]. An exposure assessment was implemented to
measure or estimate the magnitude, frequency, and duration of exposure from identified hazards. Risk
assessment was implemented to manage and control potential risks. Therefore, relevant risk evaluations and
estimation were carried out to determine potential risks from identified hazards. The checklist method was
implemented for all plants to search for hazards according to Thai regulations and certain global
standards [8]. A checklist consisted of question-related for implementation to determine whether it has been
done according to design standard, operating standard, or the law to bring the inspection result to identify the
hazard and evaluate the risk.
Figure 1 Overall research procedure
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3.2 Hazard Identification
Step 1: Aspects was set for safety in implementation.
Step 2: Detail description of such aspects to be inspected was outlined by considering the operating
procedure, legal matters concerning safety and occupational health, and safety standard.
Specific areas of the worksite premises and activities carried on in those premises were examined for the first
two steps. The process outline is given below:
Worksite plan was accessed.
A chart was formulated to show the process of production or workflow.
The worksite was divided into identifiable areas and number them. This division was based on the
production process or the physical layout of a site.
Staff in all areas was interviewed to list other potential hazards in the working station and
consultation of owners for the required information.
Also, other sources of hazard information were utilized to identify hazards.
Step 3: The information in step 2 was used to constitute a checklist for a safety inspection.
Step 4: Accuracy and completeness of the checklist were checked, and it was rechecked. by expertise to
assure that the checklist covers all aspects concerning existing safety problems.
Step 5: The checklist was used to inspect safety in the implementation of a factory.
Step 6: Result from inspection in assessing risk was used to prioritize risk associated with a potential hazard.
Step 7: Risk management plan was established according to the risk level determined from the assessment
and fill into form.
3.3 Exposure Assessment
3.3.1 Heat stress
The indoor Wet Bulb Globe Temperature (WBGTin) index was used to represent the heat stress to which an
an individual is exposed. The WBGT readings were taken by using Quest temp WBGT meter by placing it
close as possible to employees who had the potential to subject heat stress at the extrusion process and main
workstation, where many workers were performing their tasks. The first reading was taken after 20 min from
a point of inspection. After that, 10 reading was taken from the same point for each one-minute interval to
determine the average value. Finally, WBGT measurements were made based on the standards (ISO, 1989,
BS EN, 1994) at 3 regions of the head, abdomen and ankle. Then values were averaged from the equation
(1). In all workplaces, all activities were conducted in the standing posture and so all the measurements were
performed at 0.1, 1.1 and 1.7 m above the floor corresponding to the height of the head, abdomen and
ankles [9].
WBGT= (WBGT head + (2 x WBGT abdomen) + WBGT ankle) / 4 (1)
Clothing Adjustment Factor (CAF) was added to determine WBGT Effective. Identified the CAF based on the
clothing wear inside premises by workers [10]. Selected the work rate category according to the Thai and
American Conference of Industrial Hygienists (ACGIH) regulations to determine the maximum allowable
heat stress levels [11].
3.3.2 Noise level
Detailed noise survey was performed when data from the preliminary survey performed at hazard
identification indicated the need for more specific monitoring, the detailed survey [12]:
Used a SoundPro noise dosimeter to provide specific information about the noise levels at individual
workstations and closer to machinery including manual sorting, shredding, extrusion, and
palletization.
Measured the noise levels at a distance from machinery, where machine operators and employees
were usually operating the machinery and performing their tasks.
Evaluated employee exposure averaged out over an 8-hour workday.
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Defined areas that should be designated as a noise hazard area and require the use of hearing
protection
3.2.3 Volatile Organic Compounds (VOC’s) sampling, extraction and analysis
Qualitative analysis was carried out as a preliminary analysis to detect VOCs in the indoor environment.
Sampling and sample preparation was performed according to the procedure of the National Institute for
Occupational Safety and Health (NIOSH) 1500. GC/MS (Agilent model 7890A coupled with 5977B MSD)
method was used to analyze the prepared samples. Quantitative analysis was carried out to detect the selected
group of VOCs. All the procedures were performed under the procedure of NIOSH 1500, 1501, 1300 and
2541 methods. All the samples were taken at a specified area where the machine operators placed while
operating the extrusion machinery. A sampling pump with a sorbent tube was placed on the selected position
based on requirements.
3.3 Risk Evaluation and Estimation
3.3.1 Risk matrix method
Risk evaluation was performed as a combination and modification of criteria approved by the Department of
Industrial works, Thailand and similar case study findings[8, 13]. The risk level was set by considering the
multiplication product between probability level and severity level of the event affecting workers. The
following levels were used to assess the probability and severity levels (Table 1 & 2).
Table 1 Probability levels
Level Probability Description
4 Almost certain Constant exposure to hazard. Very high probability of damage.
3 Likely Frequent exposure to hazard. High probability of damage.
2 Possible Regular or occasional exposure to hazard. Moderate probability of damage.
1 Unlikely Infrequent exposure to hazard. Low probability of damage.
Table 2 Severity levels
Rating Noise Heat
Frequent perspiration at work
1 75 to 84 dBA Heat stroke (Mental or psychological strain or transient Heat Fatigue)
Heat exhaustion (Unconsciousness or Fainting, Eye disorder, Nausea), Heat
2 85 to 94 dBA cramps, Throbbing, Headache
3 95 to 104 dBA Heat stroke/ Exhaustion lead to death or permanent damage
4 >=105dBA
3.3.2 Heat stress – Alternative method
At first, Threshold Limit Value (TLV) or Action Limit (AL) values were determined according to the
ACGIH standards. After that risk was evaluated based on the WBGT, TLV, and AL values (Table 3).
Table 3 Risk decision for heat-related stress [14]
WBGT value Decision
WBGT < AL Low Risk
AL < WBGT < TLV Medium Risk
WBGT > TLV High Risk
3.3.3 Occupational exposure limits for VOCs (OEL) and Hazard Quotient (HQ) of VOCs emission
The OEL and HQ were calculated for every group or species of Chemical compounds separately. OEL
calculated under ISO and ACGIH guidelines. Hazard Quotient (HQ) of workers for non-cancer risk, which is
defined as the ratio of chronic daily intake to the reference dose (RfD) [1].
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4.0 RESULTS AND DISCUSSIONS
4.1 Hazard identification
Each plant comprises different working conditions due to many factors such as production capacity, number of
employees, infrastructure facilities, machinery, process variations, product variation &, etc. Figure 2 shows the
schematic floor diagrams of the main stations of all plants with process flow and hazard identification steps.
Physical and chemical hazards were the main two groups of hazards identified in this step. The unavailability of
any detailed health and safety audits and records in all plants was highlighted as any of these establishments were
not eligible for the implementation of relevant Thai laws and regulations [15]. The machine operators at all the
plants were the potential group of workers subjected to the highest risks compared to others due to direct exposure
to hazards from machinery.
Figure 2 Schematic floor diagram of plastic recycling plants (only main working stations)
4.2 Exposure Assessment
4.2.1 Heat stress
The heat stress at the extrusion process was higher than the other working areas. Different heat stress values
obtained in each plant due to differences in recycling capacity, extrusion temperature, ventilation systems &, etc.
Also, the heat stress at PP recycling plant was higher than PE, because of the higher extrusion temperature in PP
[16]. The heavy workload category was selected for workers at the extrusion section of all plants based on
observations. All the employees dressed in standard cotton or light polyester material cloths without any
protective wear. The CAF value for standard cotton shirt/pants is zero. Final WBGT values were calculated
and compared with standard allowable limits. This result indicated that all workers in all four plastic plants were
experiencing a degree of heat stress due to exceeding Thai and ACGIH standards. This outcome is higher than
28% of workers employed in multiple processes were at risk of heat stress-related health impairment in
automotive industries [17]. Machine operators of plant B and C were experiencing the highest increment in heat
around 5.5 oC compared to standard.
Table 4 Comparison of calculated WBGT values (oC) at extrusion with Thai and ACGIH standards
At Extrusion At the main station
Calculated Thai ACGIH Work-Rest Measured Thai ACGIH Work-Rest
Std* std Std* std
Plant A 34.48 30 30 25%-75% 30.83 30 26 continuous
Plant B 35 30 28.5 50%-50% 30.77 30 26 continuous
Plant C 33.97 30 27.5 75%-25%
Plant D 31.92 30 27.5 75%-25%
*Heavy workload
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4.2.1 Noise level
Noise levels at shredding, extrusion, and palletization of all plants were exceeded the Thai standard limit of
90 dBA (TWA) (figure 3) [11]. All the noise levels were ranged between 90 dBA to 98 dBA. The highest
noise levels were determined near to shredding machinery and shredding machine operators were greatly
exposed to that noise level as they were very close to those machines. The noise levels at Plant A and B are
greater due to larger machines, multiple production lines and harder raw material compared to other plants.
Figure 3 Noise levels at different stages of plastic recycling plant
4.2.3 Volatile Organic Compounds (VOC’s)
Preliminary quantitative studies have detected the presence of VOCs such as propane, pentane, hexane,
cyclohexane and styrene. In the quantitative analysis of samples, the low quantities of VOC groups were
detected. Only hexane concentration was highlighted among all groups of VOCs at Plant A and B within a
range of around 1.2 mg/m3. All other measured values were very below 0.001 mg/m3. These results are very
low compare to existing literature, where researchers have observed a high level of VOC concentrations
from extrusion of similar types of plastics [1]. Advanced analysis procedures were used in that research to
increase the sensitivity of results.
4.3 Risk Evaluation and Estimation
4.3.1 Risk matrix method
The risk due to exposure of noise from shredding at plant A & B was higher among all other hazards (Table
1). The unacceptable risk was resulted because of noise levels from shredding machinery above 95 dB at
plant A and B. Both the plants were operating comparatively higher quantities of industrial waste plastic in
the form of harder materials (PP), which required intense shredding procedure. Moreover, the noise levels
from extrusion and palletization ware led to higher risk. Evaluated risk level from heat stress at the extrusion
process was also rated as higher risk. Furthermore, lack of records for the heat-related illnesses for the
extrusion machine operators was crucial in risk evaluation, though the exposure values were high. Also, the
unavailability of records about occupational accidents and hazards were common in small scale industries.
Regardless, the risk from VOC exposure was unable to estimate according to the analytical results due to the
certain uncertainty in the outcome.
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Table 5 Evaluated Risk levels Risk Evaluation
Hazard Probability Severity Multiplication Risk
product level
Heat stress at extrusion 42 8
Noise level at all plants at 42 8 3
palletization, extrusion and 3
shredding (except plan A 43 12
& B) 4
Noise from shredding at
plant A & B only
Table 6 Risk level guideline [6]
Risk Multiplication
Level product Meaning
1 1-2 Small risk
2 3-6 Acceptable risk, requiring revision of control measure
3 7-11 High risk, requiring action to reduce risk
Unacceptable risk, requiring a cease in operation and immediate corrective
4 12-16 action to reduce risk
4.3.2 Heat stress-Alternative method
Risk decision was obtained based on screening criteria of TLV and AL. All the machine operators at extrusion
were at higher risk, where other workers at Plant A and B are subjected to medium risk. Further analysis may be
required to assess other health-related problems arise from this risk. This may include monitoring heat strain
(physiological responses to heat stress), signs and symptoms of heat-related disorders. Besides, job-specific
control should be implemented. These results were almost identical to risk matrix results.
4.3.3 Volatile Organic Compounds (VOC’s)
The results of OEL for all detected chemical substances were not exceeded allowable limits. These results were
similar to the existing literature, but these values are very low compared to values in previous studies [1]. HQ
values of all VOC species were below 1, due to the very low values of VOC concentrations determined. The
necessity of more sensitive and accurate analysis may be required for the significant outcomes for risk assessment
of VOC exposure.
4.4 Risk Control and Management
Factory owners should reduce workplace heat stress by implementing engineering and work practice controls.
Engineering controls such as reduce workers’ activity by providing mechanical aids and adequate ventilation.
Provide and encourage regular intake of fluid/oral rehydration salt drinks, and train supervisors/workers about
heat stress are considered as the most suitable administrative controls.
Also, factory owners should aim to reduce hazardous exposure to the point where the risk to hearing is eliminated
or minimized. With the reduction of even a few decibels, the hazard to hearing is reduced, communication is
improved, and noise-related annoyance is reduced. Engineering controls including place a barrier between the
noise source and employee (e.g., sound walls or curtains), enclose or isolate the noise source from other
workstations. Otherwise, work practice recommendations such as limiting the amount of time, a person spends at
a noise source, restricting worker presence to a suitable distance away from noisy equipment and provide hearing
protection devices (HPDs), such as earmuffs and plugs, are considered an acceptable but less desirable option to
control exposures to noise.
CONCLUSION
Most of the determined values of heat and noise exposure assessments did not meet the standards. The high
noise level above 90 dBA was detected at shredding, extrusion and palletization processes. The highest noise
levels above 95 dBA were found in shredding areas of plant A and B. Heat stress values at extrusion were
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shown a considerable increment within 4.5oC to 5.5oC from standard heat stress values. It was an indication
that the occupational safety and health condition of small-scale plants was not compatible with the industrial
laws and regulations. Risk evaluation results indicated that machine operators at shredding and extrusion are
at higher risk than the rest of the workers. Besides, breathing difficulty and odor nuisance were observed at
premises inspection, though OEL and HQ results were below allowable limits. It is highly required to carry
out further advanced analysis for the reassurance of the above fact. The implementation of proper
engineering and administrative controls such as improved ventilation systems and adequate safety training
was highly recommended for these plants to minimize the potential risks.
Acknowledgment
The authors would like to express their sincere gratitude to IP-HSM, Graduate School, Chulalongkorn
University for providing 'full scholarship of H.M. the King Bhumibhol Adulyadej’s 72nd Birthday
Anniversary Scholarship and Scholarship for graduate studets to support this study.
REFERENCE
[1] He, Z., et al., Pollution characteristics and health risk assessment of volatile organic compounds
emitted from different plastic solid waste recycling workshops. Environment International, 2015. 77:
p. 85-94.
[2] Wichai-utcha, N. and O. Chavalparit, 3Rs Policy and plastic waste management in Thailand. Journal
of Material Cycles and Waste Management, 2019. 21(1): p. 10-22.
[3] Cioca, L.I., et al., Risk Assessment in a Materials Recycling Facility: Perspectives for Reducing
Operational Issues. Resources, 2018. 7: p. 85.
[4 Park, J., et al., Effects of health and safety problem recognition on small business facility investment.
Annals of occupational and environmental medicine, 2013. 25(1): p. 26-26.
[5] MINISTERIAL REGULATION ON THE PRESCRIBING OF STANDARD FOR ADMINISTRATION
AND MANAGEMENT OF OCCUPATIONAL SAFETY, HEALTH AND ENVIRONMENT B.E. 2549
M.o. industry, Editor. 2006.
[6] Asean guidelines for occupational safety and health. 2013, Jakarta: The Association of Southeast
Asian Nations (ASEAN).
[7] Organization, I.L., OSH Management Systems: A tool for continual improvement. 2011.
[8] Regulation of Department of Industrial Works. Re: Criteria for hazard identification, risk
assessment, and establishment of risk management plan B.E. 2543 2000.
[9] Pourmahabadian, M., M. Adelkhah, and K. Azam, Heat exporure assessment in the working
environment of glass manufacturing unit. Iranian Journal of Environmental Health Science &
Engineering, 2008. 5.
[10] Heat Stress and Strain: TLV® Physical Agents 7th Edition Documentation 7th ed. TLVs and BEIs
with 7th Edition Documentation. 2017: American Conference of Governmental Industrial Hygienists
(ACGIH).
[11] Summary Ministerial Regulation on the Prescribing of Standard for Administration and
Management of Occupational Safety, Health and Work Environment in Relation to Heat Light and
Noise, M.o.L. Thailand, Editor. B.E. 2549 (2006).
[12] Denisov, E., Noise at a workplace: Permissible noise levels, risk assessment and hearing loss
prediction. Health Risk Analysis, 2018: p. 13-23.
[13] Ramesh, R., M. S, and P. Senthilkumar, Hazard Identification and Risk Assessment in Automotive
Industry. International Journal of ChemTech Research, 2017. 10: p. 352-358.
[14] Guidelines On Heat Stress Management At Workplace 2016: Department of Occupational Safety and
Health, Ministry of Human Resource, Malaysia.
[15] Phan, R.W. and S. Santiponwut. Factors influencing the manufacturers' acceptation to implement
the occupational health and safety management systems. in The 42th Kasetsart University Academic
Conference. 2004. Bangkok.
[16] Yamashita, K., et al., Compositions of Volatile Organic Compounds Emitted from Melted Virgin and
Waste Plastic Pellets. Journal of the Air & Waste Management Association, 2009. 59(3): p. 273-278.
[17] Ayyappan, R., et al., Work-related heat stress concerns in automotive industries: A case study from
Chennai, India. Global health action, 2009. 2.
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Long-term Trend of Visibility and PM2.5 in Southern Taiwan
Chayanis Wongrat 1*, Khajornsak Sopajaree2 and Ying I. Tsai3
1* Graduate student, Department of Environmental Engineering, Faculty of Engineering,
Chiang Mai University, Thailand;
2Associate Professor, Department of Environmental Engineering, Faculty of Engineering,
Chiang Mai University, Chiang Mai 50000, Thailand;
3 Professor, Department of Environmental Engineering and Science,
Chia Nan University of Pharmacy and Science, Taiwan
*Phone : 0947578811, E-mail :[email protected]
ABSTRACT
Airborne particulate matters are an important component of ambient air because of its significant effects on air
quality, human health, regional visibility, and global climate change. High particulate matters are an important
factor that causes low visibility. In this study, we investigated the relationships between visibility and PM2.5
concentration in the Tainan metropolitan area, southern Taiwan, from 2010 to 2018. The annual average PM2.5
concentration decreased from 37.0±19.4 µg/m3 in 2010 to 22.4±11.8 µg/m3 in 2018, while the annual average
visibility increased from 8.53±4.56 km to 15.8±10.3 km in 2018. The 9-year annual average visibility was
exponentially increased with the decreased annual average PM2.5 mass concentrations, expressing as
Vis=587.2PM2.5-1.21 (where the unit in Vis is km and in PM2.5 is μg/m3, r value=-0.860). From 2010 to 2018,
the visibility of the four seasons was the best in summer, with an average of 15.1±7.54 km, while the PM2.5
concentration in summer was the lowest, averaging only 15.5±7.88 µg/m3. The worst visibility was in the
winter, with an average of only 6.62±6.18 km, while winter PM2.5 was the highest concentration, with an
average of 40.5±16.9 µg/m3. Season visibility was also negatively correlated with PM2.5 concentration,
expressing as Vis=157.9PM2.5-0.860 (r value=-0.866). The increasing trend in visibility is significantly related
to the decreased concentration in PM2.5. In Chemical composition reveals that ammonium sulfate,
ammonium nitrate and carbon particles in the submicron particle size of 0.32~0.56 μm should be the main
aerosol composition that affects visibility.
Keywords : Long-term trend; PM2.5; Visibility impairment; Chemical composition
INTRODUCTION
Air pollution levels remain dangerously high in many parts of the world. New data from World Health
Organization (WHO) shows that 9 out of 10 people breathe air containing high levels of pollutants.
Estimations reveal an alarming death toll of 7 million people every year caused by ambient (outdoor) and
household air pollution. Ambient air pollution alone caused some 4.2 million deaths in 2016, while
household air pollution from cooking with polluting fuels and technologies caused an estimated 3.8 million
deaths in the same period. WHO estimates that around 7 million people die every year from exposure to fine
particles in polluted air that penetrate deep into the lungs and cardiovascular system, causing diseases
including stroke, heart disease, lung cancer, chronic obstructive pulmonary diseases and respiratory
infections, including pneumonia (WHO, 2018).
Airborne particulate matters are an important component of ambient air because of its significant effects on
air quality, human health, regional visibility, and global climate change. It is impacting on public health and
visibilities have become Taiwan’s most pressing air quality problem in recent years. High particulate matters
are an important factor that causes low visibility.
Visibility is a measure of the distance at which a matter or light can be not clear. In addition, it is an indicator
of air quality reflecting the atmospheric turbidity. Since particulate matters and their interaction with light
are known to be the most important factors in visibility impairment (Koschmieder, 1924). Poor visibility is
an important air quality issue. Previous investigations have demonstrated that visibility is markedly
influenced by the size, chemical composition, and concentration of airborne particles. Reduced visibility is
attributed mainly to high concentrations of secondary aerosol sulfate and nitrate, with sizes ranging from 0.1
to 2 µm (Sloane et al., 1991). In cities like Denver, fine nitrate particulates cause the most reduction in
visibility during winter (Groblicki et al., 1981), but in most areas it is sulfate particulates that cause most of
the loss of visibility. Meteorological factors, particularly humidity, also contribute to reduce visibility (Tang
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et al., 1981). Many studies have conferred that sulfate is formed at a significantly faster rate in water droplets
under high humidity conditions (Mangelson et al., 1997). When relative humidity is less than 70%,
prevailing visibility has been used to estimate the atmospheric sulfate concentrations in urban areas
(Leaderer et al., 1981). However, the relationship between prevailing visibility and sulfate concentration is
not valid in conditions of high humidity
Thus, in this study the size distributions of particulate matters were measured over a wide range of diameters
and determined the relationships of visibilities and ambient air concentrations in the Tainan metropolitan
area, southern Taiwan, from 2010 to 2018. The effects of size distribution changes of particulate matters on
the visibility were also investigated
METHODOLOGY
Sampling site was located at the Department of Environmental Engineering and Science of Chia Nan
University of Pharmacy and Science, Taiwan. The samples of size fractional in the range of 0.18-1.8 µm
collected by Micro Orifice Uniform Deposit Impactors (MSP, model 100, MOUDI) from the ambient air in
urban area of Tainan city. All the collected samples were collected during the Moon Festival in the autumn
(September 2018 - October 2018) and analyzed for the chemical compositions including water soluble ions,
carboxylic acid, saccharides, sugar and sugar alcohol by ion chromatograph (IC).
RESULTS AND DISCUSSIONS
Comparison PM2.5 average and visibility average from 2010 to 2018
Results from the Environmental Protection Administration are shown in table 1and figure 1 which indicated
that, average of PM2.5 in 2010 to 2018 gradually decreases. Meanwhile, average of visibility is increase.
Visibility reduction, as a result, when PM2.5 increases. Because of particulate pollutants can cause visibility
impairment by light absorbing and light scattering. Likewise, in figure 2 reveal that seasonal trend in the
summer (June, July, and August), due to decreasing PM 2.5, visibility is increase. Compared to the Air
Quality Index refer to the concentration of PM2.5 in the good. That means the air quality in the summer is
better than any others. Furthermore, the particulates matter was collected during Moon Festival (Sep 22- Oct
1, 2018). Chemical compositions (the water-soluble ionic species: F-, SO42-, NO3−, Cl−, and NH4+,
carboxylate species: oxalate, saccharides species: levoglucosan in figure 3 among the ions, sulfate has been
found to be the maximum during Moon Festival, followed by ammonium and oxalate.
Table 1 Yearly variation of PM 2.5 averages and visibility averages from 2010 to 2018 from
the Environmental Protection Administration.
Year PM2.5 Vis
(µg/m3) (km)
2010
2011 37.0±19.4 8.53±4.56
2012 37.2±17.6 6.76±4.09
2013 34.4±14.6 6.78±3.71
2014 39.3±18.5 7.43±4.41
2015 28.2±17.4 9.17±6.02
2016 23.9±15.2 9.77±6.30
2017 27.1±16.6 12.4±8.58
2018 25.1±13.9 12.9±9.54
23.3±12.0 15.4±10.4
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Figure 1 Relationships between average PM2.5 concentrations (μg/m3)
and average visibilities (km) from 2010 to 2018.
Figure 2 Seasonal trend of PM2.5 average and visibility average
from 2010 to 2018 in Taiwan
Figure 3 Summation of Chemical compositions During Moon Festival
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Chemical compositions during Moon Festival
Water-soluble ions During Moon Festival in figures 4-8 indicated that SO42- , NO3- , and NH4+ were the
dominant ions in PM2.5 in Tainan. The concentrations of an organic acid such as oxalic acid exhibited a
similar trend, which is high in PM2.5. Hence, we may assume that secondary formation is the main source of
oxalic acid. Similarly, size distribution of major chemical components in figures 9-12 shown that most
abundant chemical components size distribution in Southern Taiwan was the submicron particle size of
0.32~0.56 µm should be the main aerosol composition that affects visibility.
Figures 4-8 The concentrations of major chemical components during Moon Festival in PM2.5.
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Figures 9-12 Size distribution of major chemical components during Moon Festival in PM2.5.
CONCLUSION
Results from the Environmental Protection Administration reveal that the annual average PM2.5 concentration
decreased from 37.0±19.4 µg/m3 in 2010 to 22.4±11.8 µg/m3 in 2018, while the annual average visibility
increased from 8.53±4.56 km to 15.8±10.3 km in 2018. The 9-year annual average visibility was
exponentially increased with the decreased annual average PM2.5 mass concentrations, expressing as
Vis=587.2×PM2.5-1.21
(where the unit in Vis is km and in PM2.5 is µg/m3, r value=-0.860).
From 2010 to 2018, the visibility in summer was the best in all of the four seasons, with an average of
15.1±7.54 km, while the PM2.5 concentration in summer was the lowest with an averaging of 15.5±7.88
µg/m3. In the winter, visibility was the worst, with an average of only 6.62±6.18 km, while winter PM2.5 was
the highest concentration, with an average of 40.5±16.9 µg/m3. Season visibility was also negatively
correlated with PM2.5 concentration, expressing as
Vis=157.9×PM2.5-0.860
(r value=-0.866).
The increasing trend in visibility is significantly related to the decreasing concentration of PM2.5. Most
abundant chemical in Southern Taiwan were SO42- , NO3- , and NH4+ and Carbonaceous contents. Similarly,
size distribution of major chemical components in figures 9-12 shown that most abundant chemical
components size distribution in Southern Taiwan was the submicron particle size of 0.32~0.56 µm. In
addition, ammonium sulfate, ammonium nitrate and carbon particles in the submicron particle should be the
main aerosol composition that affects visibility.
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Electronic Database
[1] 9 out of 10 people worldwide breathe polluted air, but more countries are taking action.
Retrieved from https://www.who.int/news-room/detail/02-05-2018-9-out-of-10-people-worldwide-
breathe-polluted-air-but-more-countries-are-taking-action.
REFERENCE
[1] Bert Brunekreef and Stephen T Holgate. (2002). Air pollution and health. The Lancet. 360 (9341),
1233-1242.
[2] Brain P. Leaderer, Roger L. Tanner, Paul J. Lioy, Jan A. J. Stolwijk. (1981). Seasonal variations in
light scattering in the New York region and their relation to sources. Atmospheric Environment.15
(12), 2407-2420.
[3] Christine S. Sloane, John Watson, Judith Chow, Lyle Pritchett, L. Willard Richards. (1991). Size-
segregated fine particle measurements by chemical species and their impact on visibility impairment
in Denver. Atmospheric Environment. Part A. General Topics, 25, 5–6, 1013-1024.
[4] N. TANG, W. T. WONG and H. R. MUNKELWITZ. 1981. THE RELATIVE IMPORTANCE OF
ATMOSPHERIC SULFATES AND NITRATES IN VISIBILITY REDUCTION. Atmospheric
Environment, 15(12), 2463-2471.
[5] Peter J. Groblicki, George T. Wolff, Richard J. Countess. (1981). Visibility-reducing species in the
denver ―brown cloud‖—I. Relationships between extinction and chemical composition.
Atmospheric Environment, 15, (12), 2473-2484.
[6] Roy M.Harrison and JianxinYin. (2000). Particulate matter in the atmosphere: which particle
properties are important for its effects on health. Science of The Total Environment. 249 (1–3),
85-101.
[7] LingxiaoYang, Xuehua Zhou, Zhe Wang, Yang Zhou, Shuhui Cheng, Pengju Xu, Xiaomei Gao, Wei
Nie Xinfeng Wang, Wenxing Wang. (2012). Airborne fine particulate pollution in Jinan, China:
Concentrations, chemical compositions and influence on visibility impairment. Atmospheric
Environment. 55, 506-514.
[8] Xingna Yu, Jia Ma, Junlin An, Liang Yuan, Bin Zhu, Duanyang Liu, Jing Wang, Yang Yang,
Huxiong Cui. Impacts of meteorological condition and aerosol chemical compositions on visibility
impairment in Nanjing, China. (2016). Journal of Cleaner Production. 131, 112-120.
9th International Conference on Environmental Engineering, Science and Management
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Detection and Preliminary Assessment of Human Exposure to
Organophosphate Flame Retardants (OPFRs) From House Dust
1*Benjawan Nilyok, 2Sun Olapiriyakul, 3Supachai Songngam and 4Premrudee Kanchanapiya
1,2Sirindhon International Institute of Technology, 99 Moo 18,
Paholyothin Rd., Khlong Luang, Pathum Thani, Thailand.
3,4National Metal and Materials Technology Center, 114 Thailand Science Park
(TSP), Paholyothin Rd., Khlong Luang, Pathum Thani, Thailand.
*Phone : 062-3280966, E-mail : [email protected]
ABSTRACT
In numerous consumer products, flame retardants and plasticizers contain additives using
organophosphorus flame retardants (OPFRs). Indoor environments also use OPFRs in varying amounts. In
many nations globally, OPFRs have been shown to exist in house dust, making it a significant concern for
human health. In this research, 38 houses in Thailand were selected for collection of house dust which was
analyzed the amount of 7 types of OPFRs including Tris(2-butoxyethyl)phosphate (TBEP), Tris(chloroiso-
propyl)phosphate (TCPP), Tris(1,3-dichloro-2-propyl) phosphate (TDCPP), Triphenyl phosphate
(TPP),Tri(2-chloroethyl) phosphate (TCEP), Tris(2-ethylhexyl)phosphate (TEHP), Tri-cresyl phosphate
(TCP). The results demonstrate that not all of the target compounds were found in every sample. Only
TBEP, TCPP, and TEHP were identified in the samples, with detection rates of 71.0%, 31.6%, and 15.8%,
respectively. While the highest OPFRs dust average concentration was TBEP (9.45 μgg−1 TEHP 0.96
μgg−1and TCPP 0.51 μgg−1), respectively. Estimated exposures of toddlers to TBEP (19.18 μgg-1 bw day-1)
for the worst-case scenario via dust ingestion estimated at a maximum was found to surpass the suggested
reference doses (RfD).This indicates the population in Thailand faces significant health risks due to
exposure.
.
Keywords : Organophosphorus flame retardants (OPFRs) , Indoor dust, Human exposure
INTRODUCTION
In order to make combustible materials more able to resist ignition and address fire safety concerns,
flame retardants (FRs) are extensively used. Used for plasticizers in construction materials and consumer
products such as furniture, electronic equipment, and textiles. FRs are the most commonly used
polybrominated flame retardants (BFRs). Even so, research has suggested that BFRs are toxic. For instance,
there is evidence that polybrominated diphenyl ethers (PBDEs) and hexabromocyclododecane (HBCD) can
contaminate air, water, and soils [1]. These findings have resulted in global restrictions and bans have been
levied on the use of PBDEs [2, 3]. For example, Penta-BDE, Octa-BDE, and HBCD were named by the
UNEP Stockholm Convention on Persistent Organic Pollutants [4]. Due to production limitations and the use
of BFRs, FRs, organophosphorus (OPFRs) use for flame retardation has amplified [5]. For instance,
functions in the production of furniture, aircraft, and trains have switched to tris ( 2-chloroethyl) -phosphate
(TCEP), tris (1-chloro-2-propyl) -phosphate (TCPP) and tris (1,3-dichloro-2-propyl) phosphate (TDCPP) in
rigid and flexible polyurethane foams as flame retardants instead of penta-BDE [2, 5]. Additionally, non-
chlorinated organophosphates as Tris (2-ethylhexyl) phosphate (TEHP), tricresyl phosphate (TCP), and
triphenyl phosphate (TPP) are extensively used in polyvinylchloride (PVC), polyurethane foam, artificial
leather, electrical cables, and electronic equipment. Furthermore, tris (2-butoxyethyl) phosphate (TBEP) is
being used commonly as a plasticizer and also as a chemical stabilizer for synthetic rubber and floor wax.
Due to OPFRs does not have covalent bonds with polymer matrix, they were released from products
into the environment with ease through abrasion and evaporation. OPFRs can be detected indoors and
outdoors. Indoor environments typically have higher levels of OPFRs than outdoor environments [6, 7].
OPFRs have also been reported to be found in house dust in various countries, including Germany [8],
Greece [9], Japan [10], the Netherlands, Saudi Arabia [11], Sweden [6], and the UK [12].
OPFRs have been found negative health effects to human and animal. Several studies show that these
compounds are toxic including neurotoxic, suspected carcinogens, and skin irritation[13-16]. TCEP and TPP
have been recorded to be neurotoxic effects. while TDCPP is associated with male hormone level and
reduced semen quality [17]. Human exposure to these chemicals can occur through three main pathways:
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inhaling air and airborne particles; dermal adsorption; and ingestion. However, the ingestion is a significant
pathway of OPFRs exposure for humans that should be troubling, particularly for toddlers exposed when
they ingest the dust such as playing toys and playing on the floor (hand to mouth activity).
Knowledge concerning toxicity of OPFRs is abundant in Thailand, so the usage of OPFRs in Thailand
is not closely regulated. In fact numerous consumer products contain these compounds. Consequently,
human exposure to OPFRs may occurs at home, at work, and even while driving through ingestion path way.
This study estimated OPFRs concentrations in house dust in Thailand, which aimed to (i) To determine
OPFRs concentrations in dust collected from Thai homes; and (ii) To preliminarily estimate human exposure
to OPFRs via dust ingestion.
METHODOLOGY
Target compound
Tris(2-butoxyethyl)phosphate (TBEP), Tris(chloroiso-propyl)phosphate (TCPP), Tris(1,3-dichloro-2-
propyl) phosphate (TDCPP), Triphenyl phosphate (TPP),Tri(2-chloroethyl) phosphate (TCEP), Tris(2-
ethylhexyl)phosphate (TEHP), Tri-cresyl phosphate (TCP) and TPP D-15 (as internal standard).
House dust sample collection and preparation
Dust samples (n=38) were collected from the filters in air conditioners and stored in an aluminum foil
bag to prevent moisture and kept at -20°C. The dust samples were collected from March to June 2019 from
residences in Bangkok and Pathum Thani Province. The physical properties of dust samples such as
moisture and particle size were measured.
Exaction by Accelerated Solvent Extraction (ASE)
ASE cells (ASE 300, Dionex Inc.) was filled up with dust sample (~0.2 g), florisil (2 g), alumina (2g)
,and diatomaceous earth (5 g). Then, the ASE cells were extracted by hexane:acetone (1:1, v/v) with 1500 psi
and 150 °C . A static time of 8 minutes, purge time of 120 seconds, and 100% flush volume was used with
three static cycles and then evaporated to 5mL.
Analysis by GC/MS
Analysis of OPFRs was conducted byGCMS-QP 2010 Shimadzu with a DB-5MS capillary column (15
m, 0.25 mm, 0.1 μm film thickness). Helium was used as a carrier gas with a flow of 1ml/min. The samples
were injected in splitless mode. The injector temperature were 340 °C for TBEP and 280 °C for OPFRs. The
temperatures of ion and inlet source were maintained at 330°C and 200°C for TBEP, and 280°C and 200°C
for other OPFRs, respectively. The initial temperature of the GC was set to 40 °C with hold time of 1 min.
Then, the temperature was raised in 3 steps: (1) ramp rate of 2 °C/min to 60 °C, (2) ramp rate of 30 °C/min
to 210 °C, and (3) ramp rate of 5 °C/min to final temperature of 300 °C with hold time of 2 min. The MS
has performed on the electron impact ionization (EI) mode with selective ion monitoring (SIM) mode. Ions
monitored for identification and quantification shown in table 1.
Table 1 Ions monitored (m/z) for OPFRs.
Target Quantification Ion Identification Ion
57 45 85 56
TBEP 63
125
TCEP 326 249 143 251
75
TCPP 99 99 201 279
368
TPP 77 325 -
341
TDCPP 99 191 379
TEHP 113 71 -
TCP 368 367 91
TPP D-15 82 339 70
(internal standard)
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Quality control
TPP D-5 was used as an internal standard for all sample analysis. Recovery rates were examined using
field blank sample (ASE cells filled with florisil, alumina and diatomaceous earth) spikes with OPFRs
standard and then extracted the same method used for dust samples before analyzed by GC-MS. The range of
recovery percentage was between 81 and 97 % for OPFRs extraction by ASE method. The limit of
quantification (LOQ) were calculated based on the standard deviation of the response and the slope as ten
times the standard deviation of blank values and divided by the slope of the calibration curve.
At least 2 field blanks (ASE cells filled with florisil, alumina and diatomaceous earth) were extracted in
parallel with the extraction of each sample batch (5 dust samples per batch) by ASE.. The extract solution of
field blanks were analyzed by GC-MS alongside the dust samples. Blank concentrations were periodically
check and should be lower than LOD (limit of detection), which were deemed as acceptable. If blank
concentrations were more than LOD, all samples in the same batch were discarded and reanalyzed. In
addition, to checking repeatability of GC-MS analysis one sample per batch should be run repeatedly. If the
percent of repeatability value exceeds 20%, all samples in that batch were reanalyzed. To avoid OPFRs
contaminatation in the equipments for sample collection, extraction and analysis, all equipments such as
glass and stainless steel were ultrasonicated for 20 min in acetone, rinsed with acetone and then dried by
heating with hot air oven before using.
Exposure assessment
The human exposure for OPFRs in toddlers and adults was assessed using the average (for normal-
case) and the maximum (for worst-case) values of OPFRs concentration in dust to calculate the intake rates
of OPFRs. All values are in μg/kg body weight (BW) per day.
In order to assess human exposure by ingestion pathway, the values were calculated using the following
equation 1:
) (µg/kg/day) (1)
where ING is the daily human exposure via ingestion (μg/kg BW per day), C is the OPFRs
concentration in sample dust (µg/g), IR is ingestion rate of 0.002 and 0.00008 g/hr [18]. Meanwhile, the
average Thai adult and toddler BW used in calculation were 57.7 [19] and 12 kg [20]. The average spent
time in house was assumed to be 16 hr /day and 100 % absorption intake of OPFRs was assumed.
RESULTS AND DISCUSSIONS
Concentrations of OPFRs in house dust samples
Analysis of OPFRs in all dust samples (n = 38) was shown in Table 2. The results demonstrated that
not all of the target compounds were found in every sample. Only TBEP, TCPP, and TEHP were identified
in the samples, with detection rates of 71.0%, 31.6%, and 15.8%, respectively. TEHP and TCPP are widely
used in polyurethane foam therefore can be found in furniture, upholstery, and mattresses. However, the
highest OPFRs dust concentration was TBEP (9.45 μgg−1). This may be caused by the commonly using of
TBEP as a plasticizer in plastics and also as a chemical stabilizer in artificial rubber and polisher in floors.
These results are similar to previous studies that measure the concentration of OPFRs in house dust. [10, 20,
24-26].
Table 2 Statistical summary of OPFRs concentrations (μg g-1) measured in house dust of Thailand
Concentration (μg g-1 dust)
Target LOQ* House (N=38) DF%***
Mean** STDEV** Min-Max
TBEP 0.225 9.45 21.95 <LOQ-71.95 15.8
TCEP 0.028 <LOQ <LOQ <LOQ 0.0
TEHP 0.013 0.96 0.83 <LOQ-2.3 71.0
TPP 0.027 <LOQ <LOQ 0.0
TDCPP 0.065 <LOQ <LOQ <LOQ 0.0
TCPP 0.105 0.51 1.01 <LOQ 31.6
TCP 0.014 <LOQ <LOQ <LOQ-5.3 0.0
<LOQ
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*LOQ :Limit of quantitation**Mean and STDEV: if the value is less than LOQ, LOQ/2 was used in
calculation
***DF (%): Detection frequency is percentage of sample found in concentration above the quantitation limit
(LOQ)
The Comparison of OPFRs with other countries
Table 3 The minimum and maximum range of OPFRs concentrations (μgg-1) in house dust of Thailand
and other countries (previously reported).
Country N Year TBEP TCEP TCPP TDCPP TPP TEHP TCP References
<0.013-
Thailand 38 2019 <0.225- <0.028- <0.105- <0.065- <0.027 <0.014- [27]
(this 71.95 5.3 2.3 <0.04– [25]
study) <0.08– 0.04– -*
0.19– 6.64 29.8 5.07 [25]
Belgium 33 2012 0.36– <0.08– 73.7 0.044 -* 0.075 – [8]
67.6 2.65 0.06 – 10.99 [22]
0.120 – 1.555 – -* <0.002 [28]
Kuwait 15 2012 0.031 – 0.275 – 7.065 6.890 – 0.36 [30]
140.450 1.800 <0.005 -* [31]
<0.02 – – 0.255 <0.002 -* [29]
Pakistan 15 2012 <0.015 <0.01 – 0.085 – 0.33 -* [26]
– 0.145 0.175 0.080- 0.200- -*
0.370- 0.110 0.180-
Germany 6 2012 <60 – 0.140- 0.960 1.300 3.7 -*
2.8 0.280 0.020 – 0.020 -*
0.020 – 16.550 -* -*
New 34 2012 0.050 – 0.020 – 7.620 – 1.340-
Zealand 27.300 7.650 0.920 – 7.500 51 -*
0.490 – 44 0.790 -*
USA 16 2012 0.790 – 0.330 – 140 – 36 -*
170 110 0.009- 0.008-
0.010- 560 300 -*
Egypt 20 2012 <0.003- 0.008- 120 0.020-
0.305 130 0.020- 2.260
0.020- 0.460 1.600-
Romania 47 2012 <0.050 0.020- 16.400 1.180- 245
– 21 1.160 1.120- 864 0.290-
nd- 9.500
Japan 148 2014 6.200- 1.300- 430 1.100
Spain 5,890 338 0.350-
10.300
8 2016 1.180 – 0.250-
18.5 9.800
*(-) not available or investigated
Table 3 shows the range of OPFRs in house dust studied in other countries. The most frequently
detected and the most concentrated OPFRs was TBEP. The levels of TBEP reported in Thai house exceeded
those detected in Pakistan, Germany, Spain, Belgium, New Zealand Egypt and Romania may be due to the
use of high TBEP materials such as wall coverings as well as leveling agents for paints and coatings. In
addition, PVC floor is frequently used in Thai residences but the level of TBEP in Thai house was lower
than those reported in US [28]and Japan house dust [30]. The use of TBEP in floor wax and PVC floor
coverings, such as carpeting, tile, stone, or tatami[10] [29] [32] could be the reason of its significantly high
concentrations in Japan[30]and America commonly used carpet cover the floor.
TCPP level detected in this study exceeded the concentration reported in Pakistan [25] and Germany
[8] but was much lower than those measured in USA [28] Kuwait [25], Spain[26], Belgium[27], New
Zealand [22], Egypt [30] ,Romania [31] and Japan [30]. The level of TCPP and TDCPP from house dust in
this study might be due to potential release of TCPP and TDCPP from upholstered furniture present in the
Thai resident houses.
The different concentration ranges of OPFRs in each dust samples in this study could possibly be
ascribed to the differences in the application of OPFRs containing in products, pattern cleaning, interior
decoration, human and pet activities as well as the sampling location. [23][33] [34]
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Human exposure to OPFRs via indoor dust ingestion
In both scenarios, TBEP was the highest daily intake rate. The results demonstrated that all exposure
estimated for adults were much lower than the RfD, as show in table 4. In contrast, for Thai toddlers, the
worst case scenario dust ingestion estimated at maximum of TBEP (19.18 μg g-1 bw day-1) exceeded RfD (15
μg g-1 bw day-1). This indicates the toddlers are exposed to significant health risks due to TBEP exposure,
which may be released from electronic equipment, furniture, floor polisher, and carpet.
Table 4 Ingestion exposure assessment for OPFRs in toddlers and adults using average and high dust
intake rates (μg/kg bw per day)
Target Normal-case Worst-case RfD*
adult toddler adult toddler 15
80
TBEP 0.02 2.5 0.16 19.18 35
TCPP 0.001 0.14 0.01 1.39
TEHP 0.002 0.25 0.005 0.63
*The value of the Reference doses (RfD) was proposed by NOAEL value. [11], [25], [27], [35]
Currently, OPFRs are still being used throughout the world. There are some countries that have
restricted use of the substances, such as in USA. A new section of the Children's Safe Products Act restricts
[36] the use of flame retardant chemicals in children's products and residential upholstered furniture. After
July 1, 2017, children's products and residential upholstered furniture sold in Washington cannot contain
more than 1,000 parts per million of these flame retardant chemicals: such as TCEP and TDCPP. In
Thailand, there are still no regulations regarding the use of OPFRs. However, many studies have suggested
ways to reduce exposure to OPFRs. Chenyang [23] found that although frequent vacuuming of carpet, tile or
laminate helped to decrease the concentrations of compounds in settled dust, but cleaning to remove dust
from electronic device and furniture actually increased the levels of compounds in HVAC filter dust.
Additionally, washing hands often can reduce hand-to-mouth contact exposure to flame retardants.
CONCLUSION
This study investigated the concentration of OPFRS in dust samples from 38 households in Thailand and
conducted the preliminary assessment of human exposure to OPFRs in house via ingestion pathway. The highest
average concentration of OPFRs in dust collected from the filter in air conditioner was TBEP (9.45 μgg−1),
followed by TEHP (0.96μgg−1) and TCPP (0.51μgg−1). In addition, the exposure assessment of these substances
in dust implied that toddlers are exposed to these chemicals, through dust ingestion pathways, more than adults.
Especially, in the worse-case the TBEP exposure by dust ingestion pathway in toddlers (19.18 μgg-1 bw day-1)
exceeded the RfD value (15 μgg-1 bw day-1). With sample size limit, these results may not be a representative
information of indoor air in all environments of Thailand. Generally, the concentration of OPFRs in indoor dust
depends on many factors, such as, pattern cleaning, interior decoration human and pet activities as well as the
sampling location.
ACKNOWLEDGEMENT
This study was financially supported by National Metal and Materials Technology Center (MTEC)
and Sirindhorn International Institute of Technology (SIIT). The author would like to thank all the professors
and research staff for giving suggestions to this research and also gratefully all the donors of the house dust
samples for their cooperation.
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I 023
Ammonium-Nitrogen Removal in Wastewater Through Adsorption
Utilizing Bio-Sorbent Matrix
Chalisa Jantaraksa1 and Nawatch Surinkul2*
1Graduate student, International Master’s Program in Environmental Water Resources Engineering;
2Assistant Professor, Department of Civil and Environmental Engineering, Faculty of Engineering,
Mahidol University, Nakhonpathom 73710, Thailand.
*Phone : (662) 889-2138 Ext. 6290, Fax : (662) 889-2138 Ext. 6388, E-mail : [email protected]
ABSTRACT
Adsorption is one of the effective methods in removing nutrient from effluent. Due to variation in nutrient
adsorption efficiency ranging from 40 to 100 percent ammonium-nitrogen removal, adsorbent such as
chitosan and various formed of activated carbon such as granulated, maize cob, and bamboo were used in
nitrogen-rich wastewater treatment. An alternative to the aforementioned adsorbent is bio-sorbent, a
biological material that could the adsorb desired substances from aqueous solution. Eggshell, with calcium
carbonate as the main composition, is a waste and readily available biological material for the adsorbent
matrix development. This study aimed to develop an effective and economical alternative adsorbents matrix
with eggshell incorporated for the adsorption of nitrogen for the treatment of effluent from aquaculture and
high nutrient effluent. Eggshell was collected and washed with distilled water several times and dried in
oven at 105oC overnight, then, grinded into different sizes of 250-151, 150-75, and less than 75 µm using
sieve number 50, 100, 200 respectively. The 150-75 µm, and less than 75 µm sieved eggshell were formed
into matrix with diameter of 10 mm. Batch experiments were performed with 250-151, 150-75, less than 75
µm, and matrixes under simulated influent condition with ammonium sulfate concentration of 1 to 10 gL-1 at
room temperature and pressure for 24 hours. The ammonium-nitrogen adsorption efficiency of the sieved
eggshell was approximately ranging from 20 percent to 44 percent. The formed eggshell matrix underwent
tablet hardness test and also underwent batch experiment with the ammonium-nitrogen adsorption efficiency
of the sieved eggshell was approximately ranging from 20 percent to 41 percent. In conclusion, eggshell can
be used as bio-sorbent for nitrogen removal in aquaculture and nutrient-rich wastewater.
Keywords : eggshell; bio-sorbent; nitrogen removal; ammonium-nitrogen; adsorption
INTRODUCTION
Wastewater, especially wastewater from aquaculture, can contain high level of nutrient such as nitrogen (N).
Especially, in many aquaculture system, ammonium-nitrogen, a by-product from the digestion of high
protein feeds and density, poses threats towards the cultured system [1]. In agriculture, nitrogen fertilizer
such as ammonium sulfate, and potassium nitrate are used to increase the output of crops such as rice, cotton,
wheat, and soybean [2, 3, 4, 5]. Industry factories, landfilled, and piggery farms usually contain excess
ammonium-nitrogen of up to 2.8 gL-1 [6, 7]. The runoff and the wastewater leakage can also contribute to
excess nutrients in water-body nearby. High level of nutrients in aquatic system adversely affected water
quality, leading to the deterioration of water quality, and eutrophication [8]. Nutrients removal is essential to
aquaculture industry as this process protects receiving water bodies from excess nutrient, and eutrophication
as well as allowing the treated water to be recirculated in the aquaculture system [9]. The current processes
of ammonium-nitrogen removal from wastewater are nitrification–denitrification, air stripping, chemical
precipitation, and adsorption and ion-exchange. Among these, adsorption and ion-exchange offer many
advantages such as economically feasible and environmentally friendly treatment alternatives, and simple-to-
operate basis [6].
Due to variation in nutrient removal efficiency ranging from 40 to 100 percent nitrogen removal, adsorbent
such as chitosan and various formed of activated carbon such as granulated, maize cob, and bamboo were
used in aquaculture wastewater treatment [10, 11, 12]. An alternative to the aforementioned adsorbent is bio-
sorbent. A bio-sorbent matrix is defined as biological material that could the adsorb desired substances from
aqueous solution [13, 14]. Eggshell consists of biomineralized calcite crystals embedded in an organic
framework of protein fibers with macropore structure contains open voids with a total volume of 0.006
cm3g−1 and specific surface area that ranges between 0.84 to 1.3 m2g−1 [15, 16, 17]. Eggshell, with calcium
carbonate as the main composition, is a cheap and readily available biological material for the adsorbent
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matrix development [18]. Global egg production is expected to increase by more than 90 tons by 2030, and
so would the eggshell waste generate from consumption [19]. In order to develop the matrix, bentonite was
selected as a binding material. Bentonite is a clay rock, generally consisting mostly of hydrated aluminum
silicate in a calcium montmorillonite, with permanent negative charges on its interlamellar sites. The
advantageous of bentonite includes high ion exchange capacity, ion selectivity and ability to regenerate,
make bentonite uses as adsorbent in many applications for wastewater treatment [20]. The bentonite
structure enables the material to be intercalated by inorganic and organic cations such as cadmium, and
ammonium, with high specific-surface-area relative to its size [20, 21]. Bentonite macropore structure
contains open voids with a total volume of 0.11 cm3g−1 and specific surface area of approximately 97 m2g−1
with ammonium-nitrogen adsorption capacity of 46.90 mgg-1[22].
The aim of this study was to evaluate the potential of eggshell as effective adsorbents in removing high
concentration of ammonium-nitrogen from wastewater. In addition, the objective was to examine the
potential of bentonite and eggshell matrix as adsorbent for ammonium-nitrogen removal from simulated
solution. The adsorption of ammonium-nitrogen by different bentonites was evaluated by adsorption
isotherms.
METHODOLOGY
Preparation of the eggshell as adsorbents
Eggshells were collected from the Faculty of Social Sciences and Humanities Canteen, Mahidol University,
Nakhonpathom, Thailand. The eggshells were washed with tap water multiple times to remove eggshell
membrane, then rinsed with deionized water thrice to remove other contaminants and impurities. The
eggshells were then dried at 105°C overnight in an electric oven. The dried eggshells were grinded and
sieved through three different sieve size: number 50, number 100, and number 200. The eggshells were
categorized according to sieve size into 250-151 µm sieved eggshell (EGGPOW >150), 150-75 µm sieved
eggshell (EGGPOW 150-75), and less than 75 µm sieved eggshell (EGGPOW <75) before use as adsorbents.
Preparation of the matrix as adsorbents
Different types of eggshell matrixes were formed with the combination of three different categories of sieved
eggshell and bentonite. The ratio of sieved eggshell to bentonite were determined using trial and error
method with the goal of maximizing the eggshell component and minimizing bentonite. The ratio of eggshell
to bentonite mixture were 95:5, 90:10, 85:15, 80:20, 75:25, 70:30, and 65:35. Deionized water was slowly
added to the combination of eggshell and bentonite until spherical matrix with diameter of 10 millimeter
could be formed using handheld tablet press. The formed matrixes were dried in oven at 155-160°C for 3
hours, then, tempered in electric furnace at 450°C for 1 hour and at 950°C for 1 hour. The matrixes were left
to cool in the furnace overnight. The matrix would be categorized based on sieved eggshell size into sieved
eggshells of 250-151 µm with bentonite (MATRIX >150), 150-75 µm sieved eggshell with bentonite
(MATRIX 150-75), and less than 75 µm sieved eggshell with bentonite (MATRIX <75). The matrixes
underwent tablet hardness test (Diligent HP-500N Hand screw type max 500N Res 0.1 N., China). The
matrixes with highest ratio of the eggshell and withstanding 30 Newtons, which is average the force from
hand-crushing, were selected to be use as adsorbents.
Characteristic of adsorbents
The pH of adsorbents provides information about the acidity and basicity of the surface. Approximately 1.0 g
of the initial and exhausted adsorbents was added to 75 mL of deionized water. The solution was stirred
using magnetic stirrer overnight, then pH was recorded.
Surface area and total pore volume of the particle distribution of the developed matrix adsorbent were
analyzed with Brunauer- Emmett-Teller (BET) (BELSORP-max series, Japan).
Preparation of adsorbate
Ammonium sulfate was dried in oven at 105°C for 6 hours and left in desiccator to cool. The stock solution
of (NH4)2SO4 (10 gL-1) was prepared by dissolving 10.0 g dried (NH4)2SO4 in deionized water. The
experimental solutions being used to simulate effluent condition were prepared by diluting the stock solution
with deionized water.
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Batch experiments
The adsorption experiments were performed using the batch equilibrium method. Experiments were
performed in triplicates and the averages were reported. In this experiment, 100 mL of different
concentration of (NH4)2SO4 solution was added in a 250 mL conical flask inside a shaking incubator
operating at 125 rpm and room temperature and pressure. The adsorbents, namely, EGGPOW >150,
EGGPOW 150-75, EGGPOW <75, MATRIX >150, MATRIX 150-75, and MATRIX <75 were added at
approximately 5 g with variation of less than 5 percent in the experiments. To assess the effects of initial
ammonium-nitrogen concentration, a (NH4)2SO4 concentration range of 1 to 10 gL-1 was at equilibrium time.
To assess the effects of contact time, kinetic studies were carried out where the samples were shaken from 1
h to 72 h, and the initial (NH4)2SO4 concentrations were 2.5 gL-1. The concentration of ammonium ions in
this experiment was analyzed using the titrimetric method with the determination limit of ammonium-
nitrogen of 50–100 mgL-1 [23]. Serial dilution was performed when the concentration of sample exceeded
the determination limit using equation (1)
C1V1 = C2V2 (1)
where C1 (mgL-1) is the initial concentration, V1 (L) is the initial volume, C2 (mgL-1) is the final concentration,
and V2 (L) is the final volume. The ammonium-nitrogen adsorption rate was calculated using equation (2),
and the ammonium-nitrogen adsorption capacity was calculated using equation (3) below
Adsorption percentage = (C0 – C)/C0 × 100 (2)
q = (C0 − Ce) ×V M-1 (3)
where q (mgg-1) is the ammonium-nitrogen adsorption capacity, C0 (mgL-1) and Ce (mgL-1) are the initial and
equilibrium ammonium-nitrogen concentrations in the solution respectively, V (L) is the solution volume,
and M (g) is the mass of adsorbent.
Langmuir and Freundlich models are used to describe the equilibrium isotherm. Langmuir model usually
describes monolayer adsorption. The linearized form of Langmuir model can be expressed as shown in
equation (4) and (5) below
qe-1 = (Ce KL qmax)-1 + qmax-1 (4)
RL = (1 + KL qmax)-1 (5)
where qmax (mgg-1) is the maximum adsorption capacity of adsorbent, KL (Lmg-1) is the Langmuir constant,
and RL is the adsorption energy coefficient. The Freundlich model usually describes multilayer adsorption
and the adsorption on heterogeneous surfaces. Its linearized form is as equation (6)
log qe = log KF + n-1 log Ce (6)
where KF (Lmg-1) is the Freundlich constant, and n is the heterogeneity factor, and a constant related to
adsorption intensity or surface heterogeneity.
RESULTS AND DISCUSSIONS
Effect of eggshell powder sizes on matrix formation
Different types of eggshell matrixes were formed with the combination of three different categories of sieved
eggshell; EGGPOW >150, EGGPOW 150-75, and EGGPOW <75 with bentonite at different ratio. The
effect of powdered sizes and ratio of sieved eggshell powder to bentonite were shown in Figure 1. The ratio
65 to 35 of sieved eggshell to bentonite was selected from results of hardness test. The sizes of eggshell
powder also contributed to the hardness factor of the matrix formation. EGGPOW >150 with bentonite,
regardless of ratio, could not be formed into functional matrix as the combination would break apart at less
than 5 N of force (Figure 1). EGGPOW 150-75 with bentonite (MATRIX 150-75), and EGGPOW <75 with
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bentonite (MATRIX <75) withstood the force of more than 30, demonstrated that particle size affects the
hardness of the matrix and, thus, affects the viability of matrix formation. MATRIX 150-75, and MATRIX
<75 were selected for further study.
35
30
25 >150 µm
20 150-75 µm
15 <75 µm
10 30 Newton
5
0
95:5 90:10 85:15 80:20 75:25 70:30 65:35
Ratio of eggshell powder to bentonite
Figure 1 Effect of different ratio of eggshell powder to bentonite on hardness of matrix adsorbent
Characteristic of matrix adsorbents
In this study, the initial pH of MATRIX 150-75, and MATRIX <75 adsorbents were found to be
approximately 7.8 to 8.1 and the pH of exhausted MATRIX 150-75, and MATRIX <75 adsorbents were 9.6
to 10.8 respectively. The pH of MATRIX 150-75, and MATRIX <75 showed that the surface is basic. The
initial condition of experiment was adjusted to the initial pH of the matrixes using sodium hydroxide and
sulfuric acid, which was also the pH range for optimal ammonium adsorption capacities [20].
Surface area and total pore volume of MATRIX 150-75, and MATRIX <75 were investigated. Results
showed that the MATRIX <75 had the highest surface area and total pore volume of 8.17 m2g-1 and 0.0443
cm3g-1 respectively. Similarly, MATRIX 150-75 had the surface area and total pore volume of 8.05 m2g-1 and
0.0416 cm3g-1 respectively. The surface area and total pore volume of adsorbents affects the performance of
adsorbents, the higher the surface area and total pore volume, the higher the adsorption sites and
effectiveness of the adsorbents.
Effect of contact time
The effect of contact time on the adsorption of ammonium nitrogen was studied with initial concentration of
(NH4)2SO4 at 2.5 gL-1. The ammonium adsorption by the sieved eggshell powder and matrixes with contact
times from 2 to 72 hours. The results showed that the adsorption rate of ammonium nitrogen by all type of
adsorbents rose sharply from 2 hours to 6 hours due to the availability of adsorption sites (Figure 2).
After the contact time of 6 hours, there is decrease in ammonium-nitrogen adsorption rate in experiments
with EGGPOW >150, EGGPOW 150-75, EGGPOW <75, and MATRIX 150-75 adsorbents. The decrease in
ammonium-nitrogen adsorption rate could be attributed to desorption of ammonium from adsorbents as well
as pseudo-second-order kinetics biosorption [24]. The decreased rate of ammonium-nitrogen adsorption with
increasing contact time was due to the filling of adsorption site by ammonium ions. As seen in Figure 2 the
higher the contact time, the higher the adsorption of ammonium-nitrogen percentage. From experiment, the
adsorption equilibrium was reached at 24 hours.
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35
Ammonium-nitrogen adsorption (%) 30
25
20 EGGPOW > 150
15 EGGPOW 150-75
EGGPOW < 75
10 Matrix 150-75
Matrix < 75
5
0 10 20 30 40 50 60 70 80
Time in hours
Figure 2 Effect of contact time in hours on the adsorption of ammonium-nitrogen
Adsorption isotherms
As ammonium-nitrogen adsorption rate increased with the decrease of concentration between EGGPOW
>150, EGGPOW 150-75, EGGPOW <75, MATRIX >150, MATRIX 150-75, and MATRIX <75 and
simulated wastewater, the isotherm of the adsorbents was studied. Langmuir and Freundlich models were
used to fit the experimental data. Based on the experiment, two isotherm parameters of Langmuir model and
Freundlich model were determined as shown in Table 1. The correlation for Langmuir model (R2) was
within acceptable range of more than 0.972 for all types of adsorbents. This implied that the adsorption
reaction occurs as a monolayer on the matrixes surface with a finite number of adsorption sites. RL of
EGGPOW >150, EGGPOW 150-75, EGGPOW <75, MATRIX 150-75, and MATRIX <75 were between
0.98 to 0.99, which is less than 1 and more than 0. Therefore, there are four probabilities for the RL value, for
favorable adsorption, 0 < RL < 1; for unfavorable adsorption, RL > 1; for linear adsorption, RL = 1; for
irreversible adsorption, RL = 0 [14]. In this case, RL obtained from experiment showed that adsorption of
ammonium ions on the adsorbents was favorable.
From correlation comparison, it was concluded that the Freundlich model provided a more consistent fit to
the data comparing with the Langmuir model. Freundlich model based on the sorption onto a heterogeneous
surface was applicable with R2 of 0.99. The empirical parameter value of n-1 which was smaller than 1 was
implied favorable adsorption conditions [14]. From the results, both Langmuir and Freundlich model are
applicable, should be considered for further application.
Table 1 Langmuir and Freundlich isotherm parameters for ammonium-nitrogen adsorption onto
different types of eggshell and matrixes
Langmuir Isotherm Freundlich Isotherm
Adsorbents qmax KL RL R2 n-1 KF R2
(mgg-1) (Lmg-1) (Lmg-1)
EGGPOW > 150 0.999
EGGPOW 150-75 19.0 0.0005 0.99 0.975 0.9588 0.0251 0.998
EGGPOW < 75 25.0 0.984
MATRIX 150-75 36.2 0.0003 0.99 0.990 0.9909 0.0214 0.996
MATRIX < 75 20.1 0.972
16.4 0.0002 0.99 0.9627 0.0245 0.999
0.0007 0.98 0.9989 0.0197 0.998
0.0009 0.98 0.9986 0.0201 0.999
Effect of initial concentrations
In order to analyze the effect of the initial ammonium-nitrogen concentrations, experiment was performed
using (NH4)2SO4 concentration range of 1 to 10 gL-1 was at equilibrium time of 24 hours as determined in the
earlier experiment with adsorbents at 5 g. The results showed that the initial ammonium-nitrogen
concentration had a significant influence on the ammonium-nitrogen adsorption by the adsorbents. There
was also a significant different in adsorption percentage between sieved eggshell powder and matrixes form
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from sieved eggshell, and bentonite. It was observed, at 1 gL-1, that the ammonium-nitrogen adsorption
percentage is highest at 41% for MATRIX 150-75 and slightly less than 40% for MATRIX <75 in
comparison to ammonium-nitrogen adsorption percentage of EGGPOW >150, EGGPOW 150-75, and
EGGPOW <75 at 29%, 26%, and 30% respectively (Figure 3).
Overall, the increases in initial concentration of ammonium-nitrogen inversely affected the adsorption
percentage of the adsorbents. With the increase in initial ammonium-nitrogen concentration, the ammonium-
nitrogen adsorption percentage of MATRIX 150-75, and MATRIX <75 decreased sharply (Figure 3). The
decreases in adsorption percentage could be attributed to the decreasing sorption site on the adsorbents.
However, due to high concentration of initial ammonium-nitrogen concentration, it was expected that with
the same surface area and total pore volume of adsorbents, a higher initial ammonium-nitrogen concentration
would result in a stronger driving force generating from the higher concentration gradient on the adsorbent.
As a result of the concentration gradient, there was a drive on adsorption percentage for higher concentration
of initial condition as seen in Figure 3 at the (NH4)2SO4 concentration of 2.5 to 7.5 gL-1[25]. The decreases
in adsorption percentage at the 10 gL-1 (NH4)2SO4 could be attributed to the filling up of sorption site on the
adsorbents.
Ammonium-nitrogen adsoption (%) 45
EGGPOW > 150
EGGPOW 150-75
40 EGGPOW < 75
Matrix 150-75
35 Matrix < 75
30
25
20 2.5 5 7.5 10
0 (NH4)2SO4 concentration (gL-1)
Figure 3 Effect of initial (NH4)2SO4 concentration on the percent of ammonium-nitrogen adsorption
CONCLUSION
The experimental results showed both eggshell and eggshell matrix could potentially be utilized as a bio-sorbent
for ammonium-nitrogen adsorption. The MATRIX 150-75 also showed potential of ammonium-nitrogen with
maximum ammonium-nitrogen adsorption of 41%, which was higher than EGGPOW >150, EGGPOW 150-75,
and EGGPOW <75. The surface area and total pore volume of adsorbents affects the performance of adsorbents.
The higher the surface area and total pore volume gave the higher the adsorption sites and effectiveness of the
adsorbents. The results showed that the initial ammonium-nitrogen concentration and contact time had a
significant influence on the ammonium-nitrogen adsorption by the adsorbents. The experimental data were
fitted to both the Langmuir and Freundlich model to characterized the adsorption model, of which the
Freundlich model is more applicable. However, there are other forms of nitrogen such as nitrite and nitrate
presence in wastewater that adversely affect the environment. Further research is required to understand the
efficiency of eggshell to remove other form of nitrogen from the wastewater. Other factors such as ion-exchange
and chemical precipitation could be considered in future experiment.
ACKNOWLEDGEMENT
This study was conducted as part of thesis activities of the Mahidol University. We also express
sincere gratitude to the Department of Civil and Environmental Engineering, Faculty of Engineering,
Mahidol University for the financial support in Academic Presentation.
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I 024
Adsorption of bromoacetonitriles by using activated carbon produced
from calico fabric
Kanlayanee Yimyam1, 2 and Pharkphum Rakruam2*
1Graduate School, Chiang Mai University, Chiang Mai 50200, Thailand; 2Department of Environmental
Engineering, Faculty of Engineering, Chiang Mai University, Chiang Mai 50200
*Phone : 053 – 944 192, E-mail : [email protected].
ABSTRACT
Activated carbon (AC) can be widely used in adsorption process both for water and wastewater treatment,
but it remains challenging to find a low-cost material and activation technique to prepare AC. Calico fabric
has been reported that contains a cellulose as the main component. Thus, it can be utilized as raw material for
produce AC. The objective of this research was synthesized the activated carbon from calico fabric as calico
fabric-derived activated carbon (CF-C) by chemical and physical activations with ferric nitrate (Fe(NO3)3)
and nitrogen gas (N2), respectively. The surface characteristics of CF-C was investigated. Properties of AC
were characterized by N2 adsorption/desorption isotherms, SEM, BET and pHPZC. The bromoacetonitriles
(MBAN) removal efficiency by CF-C was investigated. The results showed that the morphology of CF-C
was porous in both micro pores and mesopores. BET surface area, porous volume, and average pore radius
of CF-C were 437.86 m2/g adsorbent, 0.3021 m3/g adsorbent, and 1.380 nm, respectively. In addition, the
value of the pHPZC was 8. CF-C was provided high efficiency for MBAN removal and all of MBAN was
removed by using CF-C at 3.0 g/L.
Keywords : activated carbon; adsorption; bromoacetonitriles; calico fabric
INTRODUCTION
Activated carbon (AC) is a popular absorbent material in environmental engineering aspects. The advantages
of AC have been reported such as highly effective in eliminating natural organic substances, can be used
with a variety of contaminants and easy to operate the treatment system [1]. In addition, activated carbon can
absorb chemicals in both gas and liquid state and can also be used as a catalyst. Nowadays, many low-cost
materials are utilized to produce activated carbon, such as corncobs, mango seeds, bamboo, cotton, etc.
Calico fabric is one of the interesting materials. Because the calico fabric contains cellulose as the main
component, it is suitable to produce of activated carbon [2]. Recently, there are a lot of fabric waste and
residue fabric product was found. The destination for these wastes is landfill. However, its widely known
that landfill is a source of many environmental pollution. Furthermore, the fabric wastes have been applied
as precursors to produce ACs, which transform these wastes into functional materials [3-4]. Calico is an
interesting type of fabric waste due to a lot of calico fabric bags production. Therefore, the amount of waste
from the production process increases accordingly.
Activation is the process by which carbon or charcoal has been activated to produce higher absorption
capacity. There are two types of stimulation: chemical stimulation and physical stimulation. Chemical
activation method is widely used to prepare AC with high specific surface area. Generally, the chemicals
used in the activation process are phosphoric acid (H3PO4), potassium hydroxide (KOH), zinc chloride
(ZnCl2), ferric chloride (FeCl3) and ferric nitrate (Fe(NO3)3). Because their high performance in pore-
forming process [5-9]. The previous research found that chemical activation with Fe(NO3)3 cause the
increasing of surface area in carbon material surface [9]. Rufford et al. [10] compared effect of tree activated
chemical and found that treatment with ZnCl2 and FeCl3 produced coffee grounds-derived activated carbon
was higher surface areas (977 and 846 m2/g, respectively) than treatment with MgCl2 (123 m2/g). Xu et al.
[8] investigate the effects of Fe3+ and Fe2+ on pore size of AC. Fe2+ was more conductive to forming
mesopores, whereas Fe3+ was more beneficial to the formation of micropores.
The specific surface area of a porous material is determined from physical gas adsorption. Nitrogen
adsorption-desorption isotherm is a technique used to characterize the pore structure. Classification of
isotherms are divided into six types. The different types of physisorption isotherms are indicative for
different adsorbent materials: type I: microporous, type II: non-porous or macroporous, type III: non-porous
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or macroporous with weak interaction, type IV: mesoporous, type V: mesoporous with weak interaction, and
type VI: layer-by-layer adsorption [11].
Bromine is a microelement present in waters, though at lower concentrations. Bromide presence in treated
water gives rise to formation of potentially mutagenic disinfection by-products (DBPs) [12-13].
Bromoacetonitrile (MBAN), one class of disinfection DBPs, have been detected in water supply process. It
can react with natural organic matter (NOM) to produce activated carbon. The cytotoxicity and genotoxicity
of MBAN have been demonstrated in mammalian cells [14]. Therefore, it is crucial to control MBAN
formation in a water treatment system.
This research aims to study the surface characteristics of calico fabric-derived activated carbon (CF-C)
which synthesized by chemical and physical activations with ferric nitrate and nitrogen gas, respectively. In
addition, MBAN removal efficiency by CF-C was also investigated.
METHODOLOGY
Materials and chemicals
The calico fabric was obtained from market. Ferric (Ⅲ) nitrate (Fe(NO3)3 chemical was purchased from RCI-
Labscan. Bromoacetonitrile solution was purchased from Sigma-Aldrich, Germany.
Synthesis of the AC
Calicos fabric were used as raw materials for preparation of CF-C. The calico fabric samples were cut into
small size and washed with deionized water (DI water). Next, the calico fabric samples were dried in the
oven at 80 °C for 48 hours. Subsequently, pieces of the calico fabric were soaked in 0.05 M of ferric nitrate
solution for 48 hours and dried at 80 °C. Finally, dried sample was carbonized at 830 °C under N2 ambient
for 2 hours to produce calico fabric-derived activated carbon (CF-C).
Characterization of mesoporous carbon
Nitrogen adsorption-desorption isotherms were performed by nitrogen adsorption apparatus (Autosorb-1-
MP, QuantaChrome). The Brunauer Emmett-Teller (BET) method was used to determine the specific surface
area (SBET). The Barrett-JoynerHalenda (BJH) method was applied to calculate the mesopore width
distribution, and mesopore volume (Vmeso). Micropore volume (Vmic) was determined by the Dubinin-
Radushkevich (D-R) model. The morphology of both samples was verified through scanning electron
microscopy (FE-SEM, JSM-6335F, JEOL). Point of zero charge (pHpzc) was investigated to describe the
surface charges of CF-C.
Removal of MBAN by CF-C
MBAN solution was prepared at an initial concentration of 10 µg/L, and then was added into the volumetric
flask containing CF-C sample in the range of 0.25 to 3.00 mg. Then, it was shaken at 200 rpm under room
temperature. After that, the samples were filtered by 0.22 μm nylon filter. MBAN concentrations were
analyzed by GC. The percentage removal (%R) of MBAN was calculated by Eq. (1)
%R = (Ci-Cf)×100/Ci (1)
where Ci and Cf were initial concentration (mg/L) and final concentration (mg/L) of MBAN, respectively.
RESULTS AND DISCUSSIONS
Characterization of CF-C
Figure 1 showed N2 adsorption-desorption isotherm of CF-C (a.) indicated that CF-C exhibited a combination of
the characteristic type Ⅰ and type Ⅳ shapes. It can be explained that the existence of both mesopores and
micropores in the wall macropores [15]. The distribution of porous width shown in Figure 1 (b.). The result
showed that most mesoporous widths were 2 nm.
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(a.) (b.)
Figure 1 N2 adsorption-desorption isotherm (a.) and porous width distribution of CF-C (b.)
The morphology and surface texture were revealed by SEM images as depicted in Figure 2 and the results of
elemental analysis of CF-C by SEM are presented in Table 1.
(a.) (b.)
Figure 2 SEM micrographs of the CF-C: ×3,000(a.) and ×50,000 (b.)
Table 1 Elemental analysis of CF-C Weight% Atomic%
73.89 83.52
Element 16.72 14.19
C 9.39 2.28
O
Fe
BET surface area, porous volume, and average pore radius were 437.86 m2/g adsorbent, 0.3021 m3/g
adsorbent, and 1.380 nm, respectively. When comparing the analyzed values with Xu et al. [8] which
produce AC from fabric, it is found that the surface area of CF-C was lower than previous study (1,400
m2/g). The different of surface area might be depending on the production process and the structure of the
different fabric.
The surface charges of CF-C were studied through point of zero charge (PZC) by varied pH of solution. The
results are shown in Figure 3.
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Figure 3 The results of PZC of CF-C
The pHPZC is the pH value in which the net exchange of protons between the solution and the carbon surface
equals zero [16]. From the study of PZC, it was found that the point at which the total charge is equal to zero
was approximately 8. If the pH is lower than the PZC point, the final pH value shows more base, indicating
that the amount of Hydrogen ion (H3O+) in the solution was reduced. Thus, the surface of CF-C was negative
charges. On the other hand, if the pH is higher than the PZC point, the final pH was more acidity, indicating
that the surface of CF-C was a positive charge.
The MBAN removal efficiency by CF-C
The removal efficiency of CF-C for MBAN was investigated. The CF-C dosage was varied in the range of
0.25 to 3.0 g/L and adsorption for 24 hours. The results are shown in Figure 4.
Figure 4 Removal efficiency of MBAN in AC
From the results, it was found that the highest percentage removal was 100% under dosage of CF-C 3.0 g/L.
Due to the CF-C produced from biomass which usually hydrophobic surface, resulting in the MBAN can
approach the pores of CF-C more efficiently.
CONCLUSION
The calico fabric-derived activated carbon was synthesized by chemical and physical activations with ferric
nitrate (Fe(NO3)3) and nitrogen gas (N2), respectively. The results showed that the synthesized activated
carbon was porous in both micro pores and mesopores. BET surface area, porous volume, and average pore
radius were 437.86 m2/g adsorbent, 1.380 nm., and 0.3021 m3/g adsorbent, respectively. From the obtained
result, it can be concluded that CF-C was high efficiency for MBAN removal. The highest percent MBAN
removal was obtained when using CF-C at 3.0 g/L.
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full papers proceeding The 9th International Conference on Environmental Engineering, Science and Management_Final
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full papers proceeding The 9th International Conference on Environmental Engineering, Science and Management_Final
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