Generally, the average distribution of Irgarol and Diuron in seawater, collected at the major ports of Peninsular Malaysia is shown in Fig. 2. Throughout November 2011, January 2012, and April 2012; the distribution of Irgarol shows similar increasing pattern at all ports, where the concentration of Irgarol was the lowest in November 2011 and highest in April 2012. However, the distribution of Diuron was undistinguishable, where each port has recorded different period with high and low concentration of Diuron.
The distribution pattern of Irgarol is proclaimed by the consistently usage of Irgarol as the antifouling biocides at the selected major ports in Peninsular Malaysia, with no additional source. Irgarol is a notable alternative tributyltin-free vessel coating paint which has been used widely since the usage of tributyltin coating was banned due to its severe impact towards the ecosystem (Konstantinou and Albanis 2004; Ali et al. 2015; Gallucci et al. 2015). Additionally, the continuing pattern of Irgarol in the seawater samples indicated the accumulation of Irgarol compound correlated with its’ half-life cycle. According to Dafforn et al. (2011) and Galucci et al. (2015), since the half-life for Irgarol in the seawater is in between 100 to 350 days, it is not simply degraded in a short period of time. In the present study, the gap left between the sampling periods was approximately two months apart, i.e., 60 days. Ideally, the Irgarol compound which has been introduced during November 2011 did not completely degraded in the seawater; however, the continuous usage of Irgarol by the boats and vessel coating activities are introducing additional Irgarol into the water column. Therefore, the concentration of Irgarol constantly accumulates in time which explains the increasing trend of Irgarol in the collected seawater at the major ports in Peninsular Malaysia.
In the meantime, the existent of Diuron in the seawater is less persistent than Irgarol (Thomas et al. 2002) which may justify the vague distribution of Diuron recorded throughout the study period. Based on Fig. 2, the average concentration of Diuron recorded in Kemaman Port and Pasir Gudang Port were slightly lower than recorded in Klang ports (Klang North Port, Klang South Port and Klang West Port). The random distribution of Diuron in the collected seawater samples is deemed to be affected by the usage of antifouling paint contains biocides booster at the ports as well as continuous usage of Diuron in agricultural activities. A similar finding was found by Omar et al. (2018) as the possible source of organic pollutants found within Klang ports region were derived by high industrial and agricultural activities surround.
On-site observation during sampling activities found that Kemaman Port is largely surrounded by urbanisation and industrial activities; Pasir Gudang Port is located within the vicinity of high industrial and urban activities, whereas Klang ports are predominantly enclosed by high industrial, agricultural and urbanisation activities. According to Rameli and Jaafar (2014), large area of southwest Selangor which include Carey Island, Morib and Tanjong Sepat are dominantly being occupied by palm oil plantation. Therefore, this activity is counted as a non-point source of Diuron which has been contaminating the water column of Klang ports since Diuron is being actively used as herbicides in agricultural activies (Ali et al. 2014); besides the continuous usage of Diuron as antifouling biocides paints in shipping sector (Ansanelli et al. 2017; Hanapiah et al. 2017).
The variation of Irgarol and Diuron throughout the present study was further investigated using discriminant analysis (DA). DA was applied on the raw dataset for both biocides using standard, stepwise forward and stepwise backward methods. The spatial variation of Irgarol using standard mode DFA (Table 1) shows an accuracy of 50% with 1 discriminant variable whereas the accuracy of Irgarol spatial variation using stepwise forward and stepwise backward mode DFA is similar which is 42.86% with 1 discriminant variable. The only significant discriminant variable for all DA modes is sampling period of November 2011 which explain the variation of Irgarol was significant between sampling area during November 2011. The spatial distribution of Irgarol during November 2011 sampling period shows a significant variation compared to January 2012 and April 2012 sampling period (Fig. 3).
Table 1
Classification matrix for Irgarol spatial distribution using DA.
Standard DA Mode (1 variable)
|
Sampling Area
|
Kemaman
|
Klang North Port
|
Klang South Port
|
Klang West Port
|
Pasir Gudang Johor Port
|
Total
|
% correct
|
Kemaman
|
3
|
1
|
0
|
0
|
1
|
5
|
60.00
|
Klang North Port
|
2
|
1
|
0
|
0
|
2
|
5
|
20.00
|
Klang South Port
|
1
|
0
|
0
|
0
|
4
|
5
|
0.00
|
Klang West Port
|
0
|
0
|
0
|
3
|
2
|
5
|
60.00
|
Pasir Gudang Johor Port
|
0
|
0
|
0
|
1
|
7
|
8
|
87.50
|
Total
|
6
|
2
|
0
|
4
|
16
|
28
|
50.00
|
Stepwise Forward DA and Stepwise Backward DA Mode (1 variable)
|
Kemaman
|
4
|
0
|
0
|
0
|
1
|
5
|
80.00
|
Klang North Port
|
2
|
0
|
0
|
0
|
3
|
5
|
0.00
|
Klang South Port
|
1
|
0
|
0
|
0
|
4
|
5
|
0.00
|
Klang West Port
|
0
|
1
|
0
|
0
|
4
|
5
|
0.00
|
Pasir Gudang Johor Port
|
0
|
0
|
0
|
0
|
8
|
8
|
100.00
|
Total
|
7
|
1
|
0
|
0
|
20
|
28
|
42.86
|
Based on Table 2, the accuracy of Irgarol temporal classification using standard mode DFA is 93.33% (5 discriminant variables) whereas similar accuracy of temporal classification for stepwise forward and stepwise backward modes DFA is 80% (3 discriminant variables). Klang North Port (KNP), Klang South Port (KSP) and Pasir Gudang (PGJP) Johor Port were found to be the discriminant variables using the stepwise forward and stepwise backward DA methods. According to DA temporal variation, KNP, KSP and PGJP shows high variation of Irgarol compared to Kemaman and Klang West Port (Fig. 4).
Table 2
Classification matrix for Irgarol temporal distribution using DA.
Standard DA Mode (5 variables)
|
Sampling Period
|
April, 2012
|
January, 2012
|
November, 2011
|
Total
|
% correct
|
April, 2012
|
5
|
0
|
0
|
5
|
100.00
|
January, 2012
|
0
|
4
|
1
|
5
|
80.00
|
November, 2011
|
0
|
0
|
5
|
5
|
100.00
|
Total
|
5
|
4
|
6
|
15
|
93.33
|
Stepwise Forward DA and Stepwise Backward DA Mode (3 variables)
|
April, 2012
|
5
|
0
|
0
|
5
|
100.00
|
January, 2012
|
0
|
3
|
2
|
5
|
60.00
|
November, 2011
|
0
|
1
|
4
|
5
|
80.00
|
Total
|
5
|
4
|
6
|
15
|
80.00
|
The spatial variation of Diuron using standard mode DFA (Table 3) shows an accuracy of 50% with no discriminant variable, where there is no significant spatial distribution of Diuron throughout the present sampling period.
Table 3
Classification matrix for Diuron spatial distribution using DA.
Standard DA Mode (No discriminant variable)
|
Sampling Area
|
Kemaman
|
Klang North Port
|
Klang South Port
|
Klang West Port
|
Pasir Gudang Johor Port
|
Total
|
% correct
|
Kemaman
|
4
|
0
|
0
|
0
|
1
|
5
|
80.00
|
Klang North Port
|
0
|
3
|
0
|
1
|
1
|
5
|
60.00
|
Klang South Port
|
0
|
1
|
1
|
1
|
2
|
5
|
20.00
|
Klang West Port
|
2
|
0
|
2
|
0
|
1
|
5
|
0.00
|
Pasir Gudang Johor Port
|
2
|
0
|
0
|
0
|
6
|
8
|
75.00
|
Total
|
8
|
4
|
3
|
2
|
11
|
28
|
50.00
|
Based on Table 4, the accuracy of Diuron temporal classification using standard mode DFA is 58.33% (1 discriminant variable) whereas similar accuracy of Diuron temporal classification for stepwise forward and stepwise backward modes DFA is 54.17% (1 discriminant variable). DA temporal variation of Diuron shows that Kemaman sampling area is the only discriminant variable where the Diuron distribution was varied highly during the present sampling periods (Fig. 5).
Table 4
Classification matrix for Diuron temporal distribution using DA.
Standard Mode DA (1 variable)
|
Sampling Period
|
April, 2012
|
January, 2012
|
November, 2011
|
Total
|
% correct
|
April, 2012
|
5
|
0
|
3
|
8
|
62.50
|
January, 2012
|
1
|
5
|
2
|
8
|
62.50
|
November, 2011
|
1
|
3
|
4
|
8
|
50.00
|
Total
|
7
|
8
|
9
|
24
|
58.33
|
Stepwise Forward and Stepwise Backward DA (1 variable)
|
April, 2012
|
8
|
0
|
0
|
8
|
100.00
|
January, 2012
|
3
|
4
|
1
|
8
|
50.00
|
November, 2011
|
5
|
2
|
1
|
8
|
12.50
|
Total
|
16
|
6
|
2
|
24
|
54.17
|
Risk assessment of pollutants in the environment have been widely applied to indicate the extent of contamination of various type of organic pollutants in the ecosystem, particularly in the aquatic compartment. The estimation of ecological risks for pesticides and other type of organic pollutants in Malaysian coastal water have been described by several studies, and it was observed that the risks are being categorized from negligible to high risk. For the record, in Klang estuary, pesticide such as chlorpyrifos has been classified as having a high risk (Wee and Aris 2017) while other organic pollutants such as pharmaceutically active compounds (PhACs) are classified as low risk (Omar et al. 2019). However, there were no previous studies have been reported on the ecological risk of Irgarol and Diuron in the aquatic environment of Malaysian coastal water, and thus the present assessment will be the first account of study reported on the risk of these biocides. As a chemical that are widely being used for marine application as well as agriculture sector, these biocides should be given specific attention due to toxicity of these chemical towards marine organisms in the aquatic food web.
Several toxicological studies have indicated that both biocides are the major threat to non-target organisms, such as coral reef and fishes, as well as other aquatic life. A study by Ali et al. (2015) reported toxicological evaluation of Irgarol on Asian seabass, Lates calcarifer, and found that this substance was toxic and reduced the fatty acid composition of the fish at the low level of concentration. Both compounds also showed toxic effects in marine microalgae species such as, Tisochrysis lutea, Skeletonema marinoi and Tetraselmis suecica (Dupraz et al. 2017). Another study by Park et al. (2016a) reported that exposure to Irgarol and Diuron have potential hazardous effect on Pacific oyster, Crassostrea gigas, while Park et al. (2016b) observed changes in the exoskeleton, molting, and proteolysis metabolism of mud crab, Macrophthalmus japonicus, when exposed to Irgarol.
Table 5 shows the ecotoxicity endpoint and risk quotient (RQ) of algae, daphnids and fish for Irgarol and Diuron in the surface water of selected ports in peninsular Malaysia. The calculated RQ for the three test species showed that algae posed high risk for both of Irgarol and Diuron during the present study, particularly during April 2012 sampling. Based on the maximum concentration from three sampling period, the value of RQ is 1.61 and 77.73 for Diuron and Irgarol, respectively. Irgarol was observed to exhibit higher risk as compared to Diuron at the ports of peninsular Malaysia. Throughout the sampling campaigns that were carried out for 2–3-month interval, the risk of Irgarol was significantly increased during April 2012 sampling.
Table 5
Ecotoxicity endpoints for algae, daphnids and fish and risk quotient (RQ) assessment for Diuron and Irgarol in surface water of selected ports in Peninsular Malaysia.
Compounds
|
EC50/LC50 (µg L− 1)
|
Assessment
factor
|
PNEC (µg L− 1)
|
Concentration
(µg L− 1)
|
RQ
|
Fish
|
Daphnids
|
Algae
|
Fish
|
Daphnids
|
Algae
|
Maximum
|
Fish
|
Daphnids
|
Algae
|
Diuron
|
18100
|
5220
|
177
|
1000
|
2.13
|
3.12
|
0.26
|
0.285
|
0.015
|
0.052
|
1.61
|
Irgarol
|
2130
|
3120
|
26
|
1000
|
18.1
|
5.22
|
0.177
|
2.021
|
0.95
|
0.65
|
77.73
|
EC50 = effective concentration; LC50 = lethal concentration; PNEC = predicted no effect concentration, RQ = risk quotient |
Table 6
Comparison of biocides (Irgarol and Diuron) in the surface water of selected ports in peninsular Malaysia relatives to other countries
Location/
Country
|
Method
|
Diuron
|
Irgarol
|
References
|
|
LOD (ng L− 1)
|
Concentrationmax (µg L− 1)
|
RQ
|
LOD
(ng L− 1)
|
Concentrationmax (µg L− 1)
|
RQ
|
|
São Marcos Bay / Brazil
|
SPE-LC MS/MS
|
0.8
|
0.022
|
14.7
|
1.4
|
0.089
|
37
|
Viana et al., 2020
|
Bay of Vilaine / Britanny, France
|
SPE-LCMS/MS
|
50
|
0.268
|
5
|
20
|
0.186
|
100
|
Caquet et al., 2013
|
River in southern Poland / Poland
|
SPE-GC MS/MS
|
2.5
|
0.077
|
0.39
|
-
|
-
|
-
|
Durak et al., 2021
|
Kemaman, Klang and Pasir Gudang ports / Malaysia
|
SPE-GC MS/MS
|
0.5
|
0.285
|
1.61
|
1.0
|
2.021
|
77.73
|
This study
|
Referring to Fig. 6, the RQ for Irgarol particularly for algae were categorised as high for all sampling points during the April 2012 sampling. As comparison with January 2012 and November 2011 sampling, only several sampling points indicated high risk of Irgarol, notably in Klang and Kemaman port. Meanwhile for Diuron, only two sampling points indicated high risk as shown in Pasir Gudang and Klang port during April 2012 and January 2012 sampling, respectively. It was noted that the concentration of Diuron at both sampling points during those sampling period exceeded the maximum level as stipulated in the Malaysian Marine Water Quality Standards (MMWQs) which is regulated at 0.2 µg/L. However, the similar comparison cannot be made for Irgarol because there is no regulation yet for the allowable level of this biocide in the MMWQs. Thus, due to high risk, the need for guideline value for Irgarol to be included in the MMWQs should be taking into consideration as an effort to protect the aquatic and marine life.
Comparison of worldwide studies on the ecological risk assessment of Irgarol and Diuron showed similar trend of risk classification. As summarized in Table 6, most of studies reported high risk for Irgarol and Diuron in the aquatic ecosystem. High risk of Irgarol and Diuron was reported in the São Marcos Bay of Brazil (Viana et al. 2021), while similar risk trend was also reported in the Bay of Vilaine, France. Both locations exhibited the RQ more than 1 with the highest RQ of 100 was reported at Bay of Vilaine. Only a study in several river system in Poland showed the RQ for Diuron less than 1, which reported at 0.39 indicating moderate risk to the aquatic ecosystem. This trend of ecological risk suggested that most of the countries having a serious threat with the Irgarol and Diuron contamination, and therefore it should be considered as priority pollutants that must be continuously monitored.