ABSTRACT

This research comprehensively assessed the water quality in three urban canals within Ho Chi Minh City (HCMC), Vietnam, representing waterways affected by various pollutants. In Vietnam, the rapid pace of urbanization and industrialization has exerted significant pressure on urban water bodies, turning many canals into repositories for untreated domestic sewage, industrial discharge, and urban runoff. Ho Chi Minh City, as the nation's largest economic hub, has been particularly affected, with urban canals serving both as drainage systems and informal waste disposal sites. These issues have led to severe water quality degradation, impacting aquatic ecosystems and posing health risks to local communities. The study focused on three representative canals:

1. Tham Luong–Ben Cat–Vam Thuat (Vam Thuat), impacted by industrial and domestic wastewater,
2. Kenh Doi–Kenh Te (Kenh Te), influenced by domestic wastewater and waterborne transportation, and
3. Nhieu Loc–Thi Nghe (Nhieu Loc), renovated and has been receiving domestic wastewater.

The study employed the extensive water pollution index (WPI) and heavy metal evaluation index (HEI) using fourteen physicochemical parameters and sixteen heavy metals, respectively. Five heavy metals, including manganese (Mn), iron (Fe), arsenic (As), cadmium (Cd), and barium (Ba), exceeded the allowable limits of the National technical regulation on surface water quality (QCVN 08:2023/BTNMT, level A). The WPI values for Vam Thuat, Kenh Te, and Nhieu Loc canals were 4.68–5.56, 1.85–4.48, and 1.87–2.45, respectively, indicating severe pollution. HEI values ranged from 25.59–49.83 (Vam Thuat), 33.62–54.32 (Kenh Te), and 6.05–16.54 (Nhieu Loc), with Vam Thuat and Kenh Te exhibiting high heavy metal pollution, while Nhieu Loc had moderate pollution levels. The study demonstrated that renovation efforts can significantly reduce pollution levels in megacity canals. However, further remediation is necessary to improve water quality in highly impacted canals and ensure compliance with standards for sustainable urban development and public health.

1. INTRODUCTION

Urban canals play a vital role in managing urban surface-runoff drainage, combined sewer overflow, flood control, and treated municipal wastewater receiving, forming an essential part of a city's hydraulic infrastructure. However, intensifying urbanization and expanding industrial activities have significantly increased pollutant loads in these waterways, posing substantial challenges to water quality and environmental health (Caracciolo et al. 2023).

Ho Chi Minh City, the economic hub of Vietnam, has been grappling with significant challenges related to water pollution and inadequate urban water management, driven by high population density and rapid urbanization. The city boasts an intensive network of urban waterways, comprising both natural canals, formed by rivers and estuaries, and artificial canals, which are human-made structures designed to enhance water flow, connect different water bodies, and support urban development. These canals play a vital role in the city's hydraulic infrastructure. They facilitate navigation, support stormwater management, and help control monsoon-induced floods by channeling excess rainwater and preventing waterlogging in densely populated areas. The main canals are Nhieu Loc–Thi Nghe (Nhieu Loc), Tan Hoa–Lo Gom, Tau Hu–Ben Nghe, Kenh Doi–Kenh Te (Kenh Te), and Tham Luong–Ben Cat–Vam Thuat (Vam Thuat). These waterways are essential for enabling transportation and connectivity between the Mekong Delta and Ho Chi Minh City (Givental 2014). In addition, the canal systems in HCMC are also responsible for carrying domestic and industrial wastewater to the Saigon River estuary and finally emptying in the East Sea of Vietnam (Strady et al. 2017; Babut et al. 2019; Nguyen et al. 2020b). Over time, surface water in HCMC’s canals has become heavily contaminated with organic matter, nutrients (Nguyen et al. 2020b), heavy metals (Nguyen et al. 2020a), microplastic (Lahens et al. 2018), and micropollutants such as endocrine-disrupting compounds (Minh et al. 2016; Caracciolo et al. 2023). These pollutants have significantly degraded water quality, negatively affecting aquatic habitats and public health (Caracciolo et al. 2023, Nguyen et al. 2023). In aquatic habitats, pollutants such as heavy metals, nutrients, and organic waste disrupt the delicate balance of ecosystems by reducing dissolved oxygen levels, promoting harmful algal blooms, and causing bioaccumulation of toxins in the food chain. This degradation results in a loss of biodiversity, with sensitive species struggling to survive while more tolerant species may dominate, altering ecosystem dynamics (Taiwo Adekanmi 2022; Liu et al. 2024). With respect to public health, the presence of contaminants like heavy metals, pathogens, and endocrine-disrupting chemicals in water sources can lead to acute and chronic health issues. These include gastrointestinal diseases, neurological disorders, and developmental problems caused by prolonged exposure to toxins (de Almeida Rodrigues et al. 2019; Gondi et al. 2022). Additionally, polluted waterways often serve as breeding grounds for vectors such as mosquitoes, exacerbating the spread of diseases like dengue fever and malaria (Fazeli-Dinan et al. 2022; Magalhães et al. 2023). Contaminated water also affects livelihoods, particularly for communities reliant on fisheries or agriculture, further amplifying its social and economic consequences (Hussain and Reza 2023). Presently, efforts are being made to improve water quality in HCM’s canals such as sludge dredging and enhancing domestic wastewater treatment capacity (Linh and Quan 2019). However, full-scale renovation requiring extensive infrastructure modifications remains costly. As a result, only one canal, Nhieu-Loc, has undergone comprehensive renovation. Other canals, such as Tan Hoa–Lo Gom, Tau Hu–Ben Nghe, Kenh Te, and Vam Thuat, have primarily relied on periodic dredging to remove accumulated polluted sediments (VNEXPRESS 2021).

Several methods, including the Vietnamese Water Quality Index (VN-WQI) have been proposed to assess and integrate multiple water quality parameters into a single index. In Vietnam, the Vietnamese Water Quality Index (VN-WQI) is computed according to Decision 1460/QD-TCMT, transferring the concentrations of pH, pesticides, heavy metals, organic matter, nutrients, and microorganism parameters into one single index (Drasovean and Murariu 2021). A study by Hung et al. (2023) evaluated the water quality index (WQI) of five urban canals in HCMC over the period 2012–2020. The results showed minimal variation in WQI values across years and canals, with the notable exception of Nhieu Loc, which underwent renovation efforts during this time. While the WQI provided a general assessment of water quality, it failed to capture critical parameters such as trace metals (Parvin et al. 2022), which are prevalent contaminants in HCMC's urban canals (Strady et al. 2017; Nguyen et al. 2020a). This limitation highlights the need for complementary indices or methods to provide a more comprehensive understanding of water quality, particularly in urban environments with complex pollution profiles.

One such tool is the water pollution index (WPI), which is designed to evaluate water quality based on the degree of surface water pollution, and it is one of the most comprehensive and flexible approaches (Hemachandra and Sewwandi 2023; Hossain and Patra 2020). The WPI can provide an overview of water quality parameters, including the physical, chemical, or biological characteristics of water bodies, drawing upon existing water quality standards tailored to different purposes. Similarly, the Heavy Metal Evaluation Index (HEI) provides an effective means of assessing water quality by calculating the combined influence of individual heavy metals based on the maximum allowable concentration (Kamali Maskooni et al. 2020). Together, these indices offer a more detailed and integrated assessment of water quality, addressing gaps left by traditional methods.

This study aims to comprehensively assess the water quality condition and the effectiveness of efforts to improve water quality in the urban canals of HCMC by using a comprehensive array of parameters for the water pollution index (WPI) and heavy metals evaluation index (HEI). Statistical methods, including the Principal Component Analysis (PCA) and Redundancy Analysis (RDA) to identify the main factors determining the intensity of HEI and WPI are also performed. This will contribute to priority elements in efforts to improve water quality in the canal system in HCMC.

2. MATERIALS AND METHODS

2.1 Study area

Three urban canals of HCMC that connect directly to the Saigon River were targeted for sampling, with 16 strategically distributed sampling sites distributed along the Vam Thuat (VT), Kenh Te (KT), and Nhieu Loc (NL) canals (Figure 1). These sites were chosen based on their proximity to key pollution sources, such as industrial zones, residential areas, and wastewater discharge points, to capture the variation in contamination levels along the canals. Additionally, the sampling sites were selected to reflect differences in canal usage and renovation status, allowing for a comprehensive assessment of water quality and pollution gradients across the system. This approach ensures that the data represents a range of environmental conditions and potential hotspots of contamination, providing valuable insights into the impacts of urban activities and wastewater management on canal water quality.

Figure 1 Map of the sampling sites in the canal system and Saigon River in HCMC.

2.2 Sampling and chemical analysis

The sampling campaign was carried out on 15^th November 2022, during the rainy season, specifically at low tide. The water samples were collected 50 cm below the surface using a water sampler (HYDRO-BIOS 2.0 L) in the middle of the canal. Therefore, a total of 16 samples were collected from three canals: Vam Thuat (VT), Kenh Te (KT), and Nhieu Loc (NL). The water samples were on-site filtered on GF/F filters (0.7 µm Whatman®, 47 mm diameter pre-weighed and pre-heated at 500^oC). The filtered samples were used for dissolved nutrient analyses (Strady et al. 2017). The water samples were filtered for trace metal analyses by using 0.22 μm PTFE syringe filters. The filtrate was then acidified (1% (v/v) Ultrapure HNO₃ and stored in a 60 ml acid pre-cleaned Polypropylene bottle (10 % (v/v) Ultrapure HNO₃ at 4^oC (Turetta et al. 2004).

Dissolved nutrients (PO₄^3-, NO₃^-, NH₄⁺) were measured using standard colorimetric methods according to the American Public Health Association (APHA and AWWA 1995). A total of 16 dissolved trace metals (Cr, B, Mn, Fe, Al, Ni, Cu, Zn, As, Se, Cd, Sb, Ba, Hg, Mo, and Co) were measured by Thermo Scientific iCAP RQ ICP-MS using an added internal solution Ir and Rh to correct signal drifts. The detection limits for the analyzed heavy metals in water samples are as follows (in µg/L): Cr (0.04), B (0.03), Mn (0.1), Fe (0.6), Al (0.5), Ni (0.03), Cu (0.03), Zn (0.04), As (0.05), Se (0.06), Cd (0.05), Sb (0.04), Ba (0.04), Hg (0.03), Mo (0.04), and Co (0.05).

Dissolved anions such as chloride (Cl^-), fluoride (F^-), sulfate (SO₄^2-) and major cations, including calcium (Ca²⁺), magnesium (Mg²⁺), sodium (Na⁺), and potassium (K⁺), were analyzed using ion chromatography (IONUS, Germany).

2.3 Statistical analyses

Water pollution index (WPI)

The 30 water quality parameters (dissolved nutrients, trace metals, and ion species) were used for the calculation of WPI (Equation 1). The status of water pollution was grouped into four categories based on WPI: Group 1: high pollution (WPI > 1), Group 2: moderately polluted (0.75 < WPI < 1), Group 3: good water (0.5 < WPI < 0.75), and Group 4: excellent water (WPI < 0.5) (Hossain and Patra 2020)

	(1)

Where:

n	=	number of parameters; if the measured concentration of a parameter is non-detected, it should be excluded from the total n for that sample,
PLi	=	pollution load of the ith parameter,
Ci	=	observed concentration of the ith parameter (mg/L), and
Si	=	standard permissible limit for the respective parameter.

Heavy metal evaluation index (HEI)

HEI presents the overall surface water quality with respect to concentrations of 16 trace metals (Equation 2).

(2)

Where:

Hc	=	concentration of dissolved metal (mg/L), and
HMac	=	maximum permissible concentration of each trace metal (mg/L), compiled by Siegel et al. (Siegel 2002).

Classification of surface water quality based on HEI values are < 10 for low pollution, 10–20 for moderate pollution and > 20 for high pollution (Ameh 2013).

Statistical analysis

The datasets were statistically analyzed with the determination of the minimum, the maximum, the mean, and the standard deviation. Multivariate statistical analyses are then applied including Pearson's correlation, PCA, principal component loading, RDA, and AHC. Pearson's correlation, denoted as 'r' and ranges from -1 to +1, quantifies the strength and direction of the linear relationship between two metric variables. Secondly, principal component analysis (PCA) is a mathematical method that simplifies datasets with a large number of correlated variables into a smaller set of uncorrelated factors called principal components. Thirdly, principal component loadings are correlations between an observed variable and an extracted factor (principal component) that indicate which variables contribute the most to each factor. All three methods, including Pearson's correlation (with a significance level of p < 0.05), principal component loadings and PCA were applied to determine the relationships between the physicochemical and heavy metals in the surface water samples and identify the potential sources of heavy metals. Redundancy Analysis (RDA) is a linear model that handles multiple dependent variables which is also considered as a multivariate extension of PCA applied to response variables. In the study, RDA defines the relationship between the physicochemical indicators, cations, anions, nutrients and the concentration of heavy metals at VT, KT, and NL canals. Agglomerative hierarchical clustering (AHC) is also a statistical method that groups a given set of objects based on their similarities across a large number of variables simultaneously. AHC was used to investigate the similarity between the sampling points of water samples using all the parameters in this study. The statistical analysis was performed with XLSTAT-LifeSciences 2023 (Addinsoft, Paris, France) software. XLSTAT is a statistical software package that integrates seamlessly with Microsoft Excel, empowering users to perform advanced data analysis. XLSTAT Life Sciences is a specialized solution within the XLSTAT statistical software suite designed to assist researchers in conducting in-depth analyses, especially laboratory data analysis.

3. RESULTS AND DISCUSSION

3.1 Spatial variation of nutrients and metals in the urban canals

The mean concentrations of physico-chemical parameters and trace metals in the canal water samples collected from VT, KT, and NL canals were compared with the allowable values of WHO guidelines and the Vietnamese surface water quality standards QCVN 08:2023/BTNMT (Table 1). It was found that the mean concentration of five trace metals (Mn, Fe, As, Cd, and Ba), along with nutrients (NH_3-N, and PO₄^3-), TSS and SO₄^2- exceeded the allowable thresholds of WHO guidelines (WHO 2022) and QCVN 08:2023/BTNMT (MONRE 2023).

Table 1 Concentration of heavy metals, nutrients, and physical parameters in three canals.

Groups	Variables	VAM THUAT		KENH TE		NHIEU LOC		At three canals		WHO (2022)	QCVN 08:2023/BTNMT, Level A
		Mean	Std	Mean	Std	Mean	Std	Mean	Std
Trace metal (mg/L)	B	0.4491	0.0882	0.5035	0.0792	0.2983	0.0392	0.4258	0.1134	2.4	-
	Al	0.0653	0.0408	0.0236	0.0232	0.0105	0.0043	0.0299	0.0321	0.1	-
	Cr	0.0130	0.0053	0.0051	0.0027	0.0008	0.0005	0.0057	0.0056	0.05	0.05
	Mn	1.1177	0.4703	1.6298	0.2151	0.3107	0.1919	1.0895	0.6412	0.08	0.1
	Fe	1.1639	0.2655	0.2241	0.2052	0.2719	0.1747	0.4740	0.4569	0.3	0.5
	Ni	0.0796	0.0352	0.0324	0.0099	0.0169	0.0019	0.0394	0.0302	0.07	0.1
	Cu	0.0141	0.0147	0.0013	0.0019	0.0010	0.0005	0.0044	0.0089	2	0.1
	Zn	0.2327	0.1350	0.2271	0.1033	0.4532	0.2047	0.2519	0.1425	3	0.5
	As	0.0266	0.0075	0.0401	0.0126	0.0211	0.0023	0.0308	0.0123	0.01	0.01
	Se	0.0042	0.0025	0.0021	0.0009	0.0010	0.0010	0.0023	0.0018	0.04	-
	Cd	0.0008	0.0004	0.0122	0.0177	0.0022	0.0023	0.0062	0.0125	0.003	0.005
	Sb	0.0024	0.0006	0.0011	0.0004	0.0007	0.0001	0.0013	0.0008	0.02	0.02
	Ba	1.9910	0.1119	1.2992	0.1509	0.7793	0.1336	1.3097	0.4837	1.3	-
	Hg	0.00002	0.00001	0.00002	0.000004	0.00006	0.00002	0.00003	0.00002	0.006	0.001
	Mo	0.0066	0.0010	0.0075	0.0014	0.0079	0.0006	0.0074	0.0012	0.01	-
	Co	0.0061	0.0009	0.0061	0.0024	0.0024	0.0014	0.0049	0.0025	-	-
Nutrients (mg/L)	NO3-N	0.825	0.465	0.629	0.138	0.440	0.152	0.619	0.281	50	2
	NH3 - N	3.265	1.065	2.094	0.741	2.254	0.664	2.437	0.901	0.2	0.3
	PO43-	1.125	0.543	0.326	0.222	0.100	0.023	0.455	0.498	-	0.1
Physical parameters	pH	8.651	1.061	6.956	0.263	7.449	0.267	7.534	0.873	6-8.5	6-8.5
	EC (µS/cm)	628.0	28.1	607.1	121.1	248.0	48.0	500.1	193.7	750	-
	TSS (mg/L)	86.2	44.7	88.7	31.1	28.6	10.6	69.3	40.3	-	20
	TDS (mg/L)	628.0	28.1	607.9	121.6	248.0	48.0	500.4	194.0	600	-
Anions and cations (mg/L)	Na+	53.00	17.57	69.13	17.99	20.03	8.63	49.75	26.14	200 200 75 50	-
	K+	11.98	2.50	13.99	2.63	6.26	2.42	11.07	4.18
	Ca2+	12.66	7.13	28.36	13.06	2.27	2.41	16.28	14.73
	Mg2+	3.85	2.33	10.01	3.11	0.21	0.12	5.41	4.95
	F-	0.27	0.18	0.38	0.14	0.14	0.08	0.28	0.17	1	1.5
	SO42-	40.96	28.45	94.92	30.07	17.54	7.33	57.25	42.38	250	250
	Cl-	134.00	11.37	108.37	40.86	58.80	8.79	99.29	40.26	250	250
Pollution index	HEI	34.632	10.923	42.262	6.992	11.061	4.732	30.604	15.635	-	-
	WPI	5.017	0.380	3.903	0.939	2.126	0.220	3.626	1.303

The longitudinal profile samples at the VT canal (from VT01 to VT04) indicated the most quantities of trace metals (Ba, Ni, Fe, Cu, Sb, Cr, Se and Al), nutrients (PO₄^3-, NO₃^-) and pH belonging to Group 2 (Figure 2). In contrast, the NL group (from NL01 to NL05) exhibit lower pollution of these physicochemical parameters. Additionally, the longitudinal profile samples at the KT canal (from KT03 to KT07) reveal high pollution of heavy metals (As, Mn, B), physical parameters (TDS, TSS, EC), cations (K⁺, Ca²⁺, Na⁺, Mg²⁺), and anions (F^-, SO₄^2-, Cl^‑) belonging to Group 1. Meanwhile, NL samples illustrate an opposite pattern, and the VT samples demonstrate intermediate quantities of parameters. The mean highest Fe, Ni, and Ba concentrations were recorded from the VT canal compared to another canal, whereas the mean highest As, Mn and Cd concentrations were found at the KT canal (Table 1). The presence of these trace metals may be the result of the discharging of untreated wastewater and solid waste from industrial areas, and surface/stormwater runoff from agricultural zones into the canals. Compared to other canal systems in developing countries, such as the St. Sebastian Canal in Colombo, Sri Lanka (Hemachandra and Sewwandi 2023), the Doi Canal in the Mekong Delta region of Vietnam (Pham et al. 2022), and the Mit-yazed Canal in the Nile Delta region of Egypt (Salem et al. 2019), the current study reported concentrations of trace metals including Ba, Ni, As, and Mn that were several to hundreds of times higher (Table 2). This stark disparity highlights the severe pollution levels in Ho Chi Minh City’s urban canals, likely driven by the combined impacts of untreated industrial discharges, domestic wastewater, and inadequate wastewater treatment infrastructure (Dao et al. 2020; Ho Jr 2023). These comparisons emphasize the urgent need for targeted interventions in Ho Chi Minh City to address heavy metal contamination. Enhanced wastewater treatment facilities, stricter industrial discharge regulations, and consistent monitoring of heavy metal concentrations are critical to mitigating the environmental and public health risks posed by such extreme pollution. Furthermore, these results underscore the importance of understanding the distinct pollution profiles of urban canals in different regions, which is crucial for designing effective remediation strategies tailored to specific environmental challenges.

Table 2 Comparison of heavy metal concentrations (mg/L) in other canals.

Canal	Pollutant source	Ba	Fe	Ni	As	Mn	Cd	Reference
Mit-yazed, Egypt	Domestic wastewater (DWW), industrial, agriculture	0.003	0.795	< LOD	0.004	0.026	< LOD	Salem et al. 2019
Qudaba, Egypt	DWW, industrial, agricultural	0.021	0.58	< LOD	0.004	0.04	< LOD	Salem et al. 2019
St. Sebastian, Sri Lanka	DWW, industrial	-	0.269	0.025	-	-	0.087	Hemachandra and Sewwandi 2023
Doi, Vietnam	DWW, industrial, agriculture, and waterway	-	3.25	0.049	< LOD	0.25	< LOD	Pham et al. 2022
Vam Thuat, Vietnam	DWW and industrial	1.991	1.164	0.079	0.027	1.118	0.00079	This study
Kenh Te, Vietnam	Urban	1.299	0.224	0.032	0.040	1.629	0.0122	This study
Nhieu Loc, Vietnam	Urban	0.779	0.271	0.017	0.021	0.310	0.0022	This study

Figure 2 Spatial distribution of heavy metals, nutrients, cations, anions, and physical parameters at KT, VT, and NL canals.
NOTE: The colour key represents the scaled relative abundance of each variable, with green indicating high relative abundance, and red indicating low relative abundance, clustered independently using ascendant hierarchical clustering based on Euclidean distances to measure the dissimilarity between the variables, ensuring that variables with similar distribution patterns are grouped together.

3.2 Pollution index

The WPI values are based on the standard permissible limits of the QCVN 08:2023/BTNMT and WHO 2022. In this study, WPI for each sample was calculated to evaluate the degree of pollution in surface water using 30 water quality parameters. WPI values of VT, KT, and NL canals ranged from 4.68–5.56, 1.85–4.48, and 1.87–2.45, respectively, significantly exceeding the critical value of 1, indicating all three canals were highly polluted. The highest WPI values were found at VT02, KT04, and NL01, respectively (Figure 3).

Figure 3 Spatial variation of HEI, WPI at VT (a), KT (b), and NL (c) canals.

The HEI values of VT, KT, and NL canals ranged from 25.6–49.9, 33.6–54.3, and 6.05–16.5, respectively (Figure 3). Based on the water quality classification of HEI, it can be seen that 100% of samples from the VT and KT canals were classified as experiencing high heavy metal pollution (HEI > 20). In contrast, the NL canal showed a more favorable distribution, with 60% of its samples categorized as low pollution (HEI < 10), and the remaining 40% as moderate-heavy metal pollution levels (10 < HEI < 20), respectively. The highest HEI values were recorded at sampling sites VT01, KT02, and NL05, highlighting localized hotpots of contamination within these canals (Figure 3).

The variation in HEI values can be attributed to differing levels of intervention and pollution sources. The NL canal, which underwent extensive restoration and renovation in 2012, provides a compelling example of the impact of rehabilitation efforts. This renovation was executed in two phases: Phase 1 focused on the resettlement of over 7,000 households across multiple districts, including Binh Thanh, Go Vap, Phu Nhuan, Tan Phu, 1, 3, and Tan Binh districts, while Phase 2 involved the construction of infrastructure to collect and treat domestic wastewater for the NL canal basin (Thi and Thoan 2023). These efforts significantly reduced pollution levels in the NL canal compared to unrenovated canals.

In contrast, the VT and KT canals continue to face severe pollution due to incomplete or ineffective remediation efforts. The VT canal, which receives treated wastewater from industrial parks (industrial fields such as food processing, textile, and mechanical engineering) and domestic wastewater from Binh Thanh, Tan Phu, Binh Tan, Go Vap, and 12 districts, highlights the limitations of current infrastructure. Although the Tham Luong–Ben Cat wastewater treatment plant (TL-BC WWTP) with a designed, capacity of 131.000 m³ per day has been built to reduce pollution of the VT canal, it only reaches approximately 10% of its capacity due to the lack of collecting sewers (Ho Jr. 2023). This infrastructural shortfall significantly limits the plant's effectiveness in treating wastewater. Similarly, the KT canal receives largely untreated wastewater from residential areas with high population density in HCMC (Truong et al. 2021), reflecting the broader challenge of insufficient wastewater treatment facilities in HCMC. Beyond financial constraints (Minh 2023), several other factors contribute significantly to the contamination of urban canals in HCMC. Rapid urbanization has outpaced the development of essential wastewater infrastructure, resulting in an overload of untreated domestic and industrial discharges (WEPA 2018). Additionally, illegal dumping and unregulated industrial effluents have compounded the pollution levels in these canals (VNEXPRESS 2023).

Overall, the results from this study emphasize the stark contrast in pollution levels between renovated and unrenovated canals. Renovation efforts in megacity canals like the NL canal have proven approximately five times more effective in reducing pollution compared to untreated sites. This underscores the urgent need for targeted investments in wastewater infrastructure and stricter enforcement mechanisms. Completing ongoing remediation projects and adopting integrated solutions will be critical to mitigating contamination and safeguarding both environmental and public health.

3.3 Multivariate statistical analysis

Based on PCA results of association of the 30 water quality parameters (14 physicochemical parameters and 16 heavy metals) in the first two components, representing 65% of the total variation (Figure 4). The first principal component (F1=43.4%) has a significant correlation to the nutrients in the water, such as NO₃^- -N, PO₄^3- -P, cations (Na⁺, K⁺, Ca²⁺, Mg²⁺), anions (Cl^-, SO₄^2- and F^-), physical parameters (TDS, EC, and TSS) and trace metals (B, Cr, Mn, Sb, Ba, and Hg). The second component (F2) is represented by pH and metals (Al, Fe, Ni, Cu, and As) (Table 3). The positive loadings of nutrients indicate the influence of untreated domestic wastewater, which can cause eutrophication in the canals. The presence of cations like Na⁺, K⁺, Ca²⁺, and Mg²⁺, is attributed to natural processes, particularly saltwater intrusion from the East Sea of Vietnam into the canal systems. Conversely, physicochemical parameters and trace metals are emitted from anthropogenic influence, including urban activities, household sources, industrial wastes, and chemical weathering of some minerals containing metals (Li et al. 2011). In addition, the impact of the geochemical characteristics of major elements in soils is associated with TDS and EC indicators (Loaiza et al. 2021).

Figure 4 PCA of 30 environmental variables at three canals.

Table 3 Principal component loadings for water quality indicators at VT, KT, and NL canals.

Variables	F1	F2	Variables	F1	F2	Variables	F1	F2
pH	0.025	0.388	Mg2+	0.528	0.375	Cu	0.133	0.486
EC	0.913	0.021	Cl-	0.377	0.127	Zn	0.062	0.011
TSS	0.753	0.000	SO42-	0.410	0.384	As	0.328	0.453
TDS	0.913	0.022	F‑	0.679	0.001	Se	0.225	0.143
NO3-N	0.272	0.133	B	0.607	0.145	Cd	0.035	0.078
NH3 - N	0.116	0.217	Al	0.243	0.380	Sb	0.406	0.404
PO43-	0.417	0.340	Cr	0.535	0.230	Ba	0.724	0.221
Na+	0.711	0.105	Mn	0.641	0.196	Hg	0.637	0.014
K+	0.734	0.110	Fe	0.178	0.732	Mo	0.178	0.012
Ca2+	0.508	0.372	Ni	0.350	0.381	Co	0.381	0.005

NOTE: Values in bold correspond for each observation to the factor for which the squared cosine is the largest

Different anthropogenic activities and economic developments in the studied regions are mainly responsible for various sources of elemental pollution. In addition to waste sources such as domestic or industrial waste that affect water quality, parameters such as hydrological regime, especially flow velocity and residence time, have a particularly significant influence on the difference in water quality. water quality. As observed by Nguyen et al. (2021), pollutants in the Saigon River exhibit fluctuations over a 10 km range and within a tidal cycle. The inability to escape from the river system and into the sea has caused pollution to increasingly accumulate in the Saigon River if there are no solutions to reduce pollution sources. Similarly, urban canals are also affected by the semi-diurnal tidal regime in the East Sea of Vietnam, so improving the flow speed and clearing the river bed not only helps eliminate pollution in bottom mud but also helps improve the ability to push pollutants out of urban canal systems and easily enter the Saigon River Estuary, and then the East Sea.

The environmental explanatory variables are physical parameters, ion species, and nutrient parameters, which are represented by red arrows. The response variable is the concentration of 16 trace metals in the water, indicated by the black dot (Figure 5). The length of the arrow signifies the influence of each of the explanatory variables. It can be found that the first RDA axes of Figure 5 explain 94.61% of the total variance. The arrows of TDS, EC, and TSS are longer than other environmental explanatory variables, exhibiting that these indicators have a more significant influence on changes in the concentration of trace metals. TDS and EC are significantly positively correlated with B, Cr, Mn, Ba, Sb, Ba, and As (p < 0.039) and significantly negatively correlated with Hg (p < 0.0004). Meanwhile, TSS are significantly negatively correlated with B, Cr, Mn, Ni, Ba, and Co (p < 0.035) and are significantly positively correlated with Hg (p < 0.0004).

Figure 5 Result of RDA between physicochemical indicators and heavy metals at three canals.

Our findings underscore the alarming extent of physicochemical and heavy metal contamination in Ho Chi Minh City's urban canals, which poses serious threats to both ecological systems and public health. This highlights the urgent need for a comprehensive approach to address the root causes of pollution, including inadequate wastewater treatment infrastructure, industrial discharge, and urban runoff.

These results provide a critical foundation for policymakers and authorities to design targeted rehabilitation plans tailored to local conditions. Such plans might include canal dredging to remove accumulated contaminants, reintroducing native aquatic vegetation to restore ecosystem balance, and creating buffer zones to prevent further contamination. Collaboration with stakeholders, including industries, local communities, and environmental organizations, will be essential to ensure the effectiveness and sustainability of these efforts.

Furthermore, the findings from this study provide a critical starting point for future researchers interested in tackling the issue of physicochemical and heavy metal contamination in urban canals, particularly in rapidly urbanizing cities like Ho Chi Minh City. Subsequent studies could build upon this work by exploring the temporal trends of contamination levels, assessing the effectiveness of implemented mitigation measures, or identifying specific pollution sources through advanced tracing techniques. Additionally, researchers might investigate the long-term ecological and health impacts of such contamination, focusing on bioaccumulation in aquatic organisms and its cascading effects on the food chain. Comparative studies across other urban areas could also offer valuable insights into shared challenges and innovative solutions, facilitating the development of best practices for urban waterway management.

4. CONCLUSION

According to the calculated WPI values, all samples collected from three canals represent high pollution in wet seasons. The mean values of heavy metals (Ba, Fe, As, Mn and Cd) exceed WHO and QCVN 08:2023/BTNMT standard limits, indicating that the water quality at these canals was only suitable for navigation purposes. Concerning the HEI values, the water quality at VT and KT canals was determined to be high heavy metal pollution. Meanwhile, HEI values in the NL canal were found to be low to moderate-heavy metal pollution levels, with more pollution in innovative canals. Hence, it can be seen that the water quality of the VT and KT canals has faced many challenges and obstacles concerning management and natural conditions. We recommend canal morphology optimization by reshaping canal banks and sludge dredging, which not only promotes natural pollution dispersion but also reduces the amount of debris, trash, and pollutants along the canal systems. Indeed, the RDA and PCA results both show that TSS is the parameter with the clear association with trace metals, followed by WPI and HEI.

ACKNOWLEDGEMENTS

This research was conducted under the framework of CARE-RESCIF initiative, Ho Chi Minh City University of Technology (HCMUT), VNU-HCM under grant number ĐA2024-20-01. We acknowledge Vietnam National University, Ho Chi Minh City for supporting this study. The authors thank members in CARE-RESCIF for their support in carrying out monitoring and providing equipment for analysis.

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