ABSTRACT
Landfill leachate and concentrates from nanofiltration (NF) and reverse osmosis (RO) processes pose potential environmental threats. This study investigates the seasonal variations in the physicochemical properties and acute toxicity of landfill leachate and concentrates from Shenyang, Liaoning, China. The hydrophilic matter (HyI) constituted the major component of dissolved organic matter (DOM) in landfill leachate (68.18% on average). Humic substances were enriched in NF and RO concentrates, accounting for 86.92 and 62.78%, respectively. Landfill leachate exhibited strong toxicity to Artemia salina, particularly in summer. Although biotreatment processes reduced toxicity, the concentrates remained toxic. Principal component analysis (PCA) revealed significant correlations between physicochemical variables and toxicity. Discriminant analysis indicated that certain variables could predict acute toxicity. This study highlights the need for effective management of landfill leachate and concentrates on mitigating environmental risks.
HIGHLIGHTS
Examined the seasonal changes of landfill leachate and concentrates for the first time.
Principal component analysis and discriminant analysis (DA) were utilized to explore correlations between physicochemical variables and acute toxicity.
Providing an innovative and straightforward bioassay method.
Offering detailed quantification across different treatment processes.
Offering targeted management recommendations for specific contaminants.
INTRODUCTION
Intensive production and modern lifestyles have contributed to the rapid development of the economy. However, some environmental problems result from development. One of the most serious is the production of a large amount of municipal solid waste (MSW). MSW is a term used to describe everyday items that are discarded by households and businesses. In China, the dumping of MSW has been found to generate a large amount of MSW leachate. This is thought to be due to the improper siting of landfills, which may be a result of urban planning and traffic conditions (Nanda & Berruti 2021). Landfill leachate is a type of wastewater containing high concentrations of pollutants that generally fall into the categories of dissolved organic matter (DOM), trace materials, heavy metals, and inorganic macro-components. However, existing research on landfill leachate tends to focus on general treatment processes and effluent quality, with limited attention given to the seasonal fluctuations of both raw landfill leachate and its membrane concentrates – particularly regarding acute toxicity. Recent studies on landfill leachate toxicity have highlighted knowledge gaps in how temperature, rainfall, and waste composition shifts affect toxicity drivers such as heavy metals and recalcitrant organics. Therefore, this study aims to bridge these gaps by systematically characterizing and comparing landfill leachate and its concentrates across multiple seasons, linking physicochemical changes to acute toxicity. This approach offers novel insights into how seasonal factors can exacerbate or mitigate environmental risks, thereby advancing the current understanding of leachate management (Ergene et al. 2022; Abdel-Shafy et al. 2024; Zhou et al. 2024).
Landfill leachate has been verified to pose serious risks to natural resources such as surface water and groundwater, soil, and ecology (Ma et al. 2022; Wijekoon et al. 2022). Due to these serious environmental risks, landfill leachate must be treated to meet strict emission standards before discharge into a sewer or receiving water body. There are four major categories of the conventional treatment processes for landfill leachate: (1) reinjection into landfill; (2) biological processes; (3) chemical methods; and (4) physical methods (Teng et al. 2021; De Almeida et al. 2023; Chen et al. 2024). Although membrane processes may require significant initial capital investment, their high removal efficiency and long-term operational cost-effectiveness make them competitive with traditional treatment methods (De Almeida et al. 2020). Membrane processes, including microfiltration, ultrafiltration (UF), nanofiltration (NF), and reverse osmosis (RO), in combination with other treatment technologies, have been extensively employed in the treatment of landfill leachate (Nanda & Berruti 2021; Teng et al. 2021; De Almeida et al. 2023).
However, the concentrates generated through the membrane separation processes account for approximately 15–30% of total leachate (Li et al. 2023b). The concentrates can be described as brown water containing a large number of refractory organic compounds such as humic acid (HA) and fulvic acid (FA), resulting in a low ratio of biochemical oxygen demand (BOD) to chemical oxygen demand (COD). An appropriate method to treat these concentrates remains elusive due to the wide variety of components. A number of studies have previously been conducted on these concentrates, with a particular focus on treatment processes such as reinjection, advanced oxidation processes (AOPs), and evaporation technology (Li et al. 2023a); however, reports on the variability of concentrates in landfill leachate remain limited. The selection of the optimal technology for treating concentrates relies heavily on their precise characterization. To date, limited research has focused on the seasonal variations in the physicochemical properties, DOM composition, and acute toxicity of landfill leachate.
This study aims to comprehensively characterize the physicochemical parameters and acute toxicity of landfill leachate, as well as the concentrates obtained from NF and RO processes across different seasons, to facilitate the effective management of this type of wastewater. Furthermore, the results of acute toxicity tests – potentially influenced by physicochemical parameters – were analyzed using principal component analysis (PCA) and discriminant analysis to determine the presence or absence of toxicity. Notably, while extensive studies have been conducted on desalination and wastewater treatment membrane concentrates, research specifically addressing the toxicity assessment of landfill leachate concentrates remains scarce.
MATERIALS AND METHODS
Sampling
Analysis of leachate and concentrates
Relevant water quality variables of landfill leachate and concentrates, such as pH, BOD5, COD, total phosphorus (TP), total nitrogen (TN), ammonia nitrogen (Amm.N), nitrate nitrogen (Nit.N), and nitrite nitrogen (NO2-N) were measured according to the standard methods recommended by UAEPA. The total organic carbon (TOC) measurement was performed using a Shimadzu TOC-VCPH analyzer. The metals (Cu, Fe, Zn, Ga, Cr, Cd, Hg, Pb) were first digested with nitric-perchloric acid, following which concentrations were determined using inductively coupled plasma mass spectrometry (Agilent 7500cx, USA).
Separation procedures to fractionate DOM in leachate and concentrates.
Toxicity testing
Artemia salina (brine shrimp) has gained popularity as a toxicity test organism because of its ease of culture, short generation time, cosmopolitan distribution, and the commercial availability of its dormant eggs (cysts) (Zani et al. 1995). Acute toxicity tests were conducted using A. salina according to Bortolotto (Bortolotto et al. 2009) with some modifications. Artemia was chosen due to its ease of culture, rapid hatching from cysts, and short life cycle, which make it ideal for acute toxicity tests. This method has been widely validated in previous studies (Tsarpali et al. 2012). Future studies may include additional organisms such as Daphnia or fish to further assess toxicity.
Nevertheless, we acknowledge that relying on a single test organism may not fully capture the ecological impacts of landfill leachate and its concentrates. Future work will consider additional bioassays (e.g., with Daphnia magna or fish species) to validate and broaden the toxicological assessment, thus providing a more comprehensive ecological risk evaluation.
A solution of standard artificial seawater of 35 ± 1‰ was used as the incubation medium for the cysts of A. salina. Instar ∼II–III larvae (n = 10) were exposed to 50 mL breakers by filling each beaker with 10 mL of each concentration (∼5–100%) or the control medium and illuminating the beaker, replicating each experiment five times. The salinity of all the dilutions was corrected to be the same as that of the incubation medium with the direct addition of synthetic sea salt. After 24 h of exposure, the number of dead organisms was observed and noted, and the mean lethal concentration (LC50) was calculated by the probability unit method.
Data analysis
The correlation between TU and physicochemical indices of leachate and concentrates from PCA and discriminant analysis were analyzed with SPSS 1.5 software.
RESULT AND DISCUSSION
Physicochemical characteristics of landfill leachate and concentrates
Seasonal characteristics of physicochemical variables of landfill leachate and concentrates are summarized in Table 1. The landfill leachates were neutral or weakly alkaline with pH values ranging from 7.44 to 8.36 in each sample. The decrease in leachate pH during summer and fall, driven by the accelerated degradation of waste under higher temperatures, facilitated the transition of the landfill into the methanogenesis phase (Ni et al. 2023). The pH values of nanofiltration concentrate (NFC) and reverse osmosis concentrate (ROC) were lower than those of the leachate. Alkalinity is consumed during the process of ammonia oxidation (7.14 g alkalinity per gram of ammonia), and the membrane retained some alkali organic and inorganic contaminats in the concentrates (De Almeida et al. 2023).
Chemical characteristics of landfill leachate and concentrates at various months (mg L−1 except for pH)
Wastewater . | Sample . | Time . | pH . | BOD . | COD . | Amm.N . | TN . | Nit.N . | Nitrite . | TP . | TOC . | Suspended solid . |
---|---|---|---|---|---|---|---|---|---|---|---|---|
Leachate | Spring | Mar | 8.12 | 2,516 | 6,045.32 | 1,405.15 | 1,441.21 | 13.44 | 0.23 | 3.86 | 2,006 | 320 |
May | 8.36 | 3,513 | 12,262.5 | 1,120.94 | 1,149.43 | 10.38 | 0.31 | 8.57 | 4,562 | 678 | ||
Apr | 8.24 | 1,730 | 5,944.33 | 1,422.17 | 1,491.04 | 28.56 | 0.82 | 8.62 | 2,036 | 497 | ||
Summer | Jul | 7.44 | 3,866 | 14,526.67 | 1,106.11 | 1,290.31 | 25.77 | 0.57 | 12.01 | 5,865 | 1,004 | |
Jun | 7.85 | 3,644 | 10,736.94 | 1,150.19 | 1,201.82 | 29.09 | 0.89 | 12.58 | 4,020 | 836 | ||
Aug | 7.86 | 3,502 | 9,550.52 | 1,256.81 | 1,307.37 | 25.15 | 0.88 | 12.02 | 4,013 | 812 | ||
Fall | Sep | 7.66 | 3,563 | 8,651.21 | 1,309.67 | 1,486.29 | 30.04 | 0.5 | 10.11 | 3,332 | 976 | |
Nov | 7.91 | 1,755 | 6,755.12 | 1,388.5 | 1,476.65 | 53.66 | 0.69 | 2.59 | 2,048 | 410 | ||
Winter | Oct | 8.05 | 1,720 | 4,982.48 | 1,464.72 | 1,552.77 | 40.17 | 0.87 | 1.06 | 1,677 | 365 | |
Feb | 8.21 | 1,336 | 3,012.54 | 1,451.02 | 1,543.87 | 35.58 | 0.73 | 3.4 | 1,848 | 552 | ||
NF concentrate | Spring | Mar | 6.42 | 10.3 | 5,295.51 | 55.93 | 321.83 | 228.05 | 15.44 | 14.74 | 1,148 | 0.05 |
May | 6.87 | 14.8 | 5,375.42 | 34.06 | 217.93 | 134.59 | 11.87 | 18.26 | 1,253 | 0.04 | ||
Apr | 7.08 | 13.3 | 5,395.67 | 53.09 | 310.05 | 234.33 | 9.66 | 18.05 | 1,351 | 0.03 | ||
Summer | Jul | 7.08 | 14.6 | 5,642.38 | 35.43 | 196.32 | 125.46 | 7.36 | 24.18 | 1,595 | 0.04 | |
Jun | 7.05 | 16.4 | 5,811.68 | 31.93 | 201.72 | 136.72 | 9.12 | 25.58 | 1,673 | 0.01 | ||
Aug | 7.17 | 11.1 | 5,410.26 | 30.53 | 185.86 | 112.42 | 7.52 | 21.73 | 1,410 | 0.04 | ||
Fall | Sep | 7.12 | 16.2 | 5,448.01 | 34.77 | 184.2 | 120.53 | 9.88 | 21.57 | 1,468 | 0.02 | |
Nov | 6.56 | 12.2 | 5,244.6 | 41.64 | 323.23 | 243.23 | 10.51 | 7.59 | 1,304 | 0.09 | ||
Winter | Oct | 6.54 | 9.6 | 5,155.39 | 63.46 | 395.23 | 303.64 | 13.31 | 2.61 | 1,255 | 0.1 | |
Feb | 6.25 | 10.5 | 5,003.17 | 61.21 | 404.39 | 311.21 | 11.09 | 10.26 | 1,210 | 0.14 | ||
RO concentrate | Spring | Mar | 6.39 | 18.2 | 1,487.85 | 7.76 | 1,029.62 | 1,004.59 | 1.52 | 4.02 | 565 | ND |
May | 6.15 | 37.3 | 1,645.02 | 4.97 | 750.03 | 645.88 | 0.66 | 11.63 | 712 | ND | ||
Apr | 6.41 | 11.5 | 1,480.67 | 13.55 | 1,054.27 | 982.35 | 2.02 | 10.19 | 605 | ND | ||
Summer | Jul | 6.24 | 21.7 | 1,451.67 | 5.26 | 811.11 | 781.62 | 0.53 | 10.39 | 762 | ND | |
Jun | 6.43 | 21.8 | 1,742.4 | 10.05 | 414.52 | 404.51 | 0.32 | 15.24 | 736 | ND | ||
Aug | 6.24 | 19.2 | 1,620 | 10.72 | 424.3 | 401.76 | 0.62 | 11.51 | 740 | ND | ||
Fall | Sep | 6.5 | 29.4 | 1,791.76 | 6.28 | 609.85 | 600.37 | 0.81 | 3.11 | 724 | ND | |
Nov | 6.01 | 13.6 | 1,241.68 | 19.35 | 900.81 | 880.14 | 1.94 | 1.48 | 620 | ND | ||
Winter | Oct | 5.67 | 8.7 | 955.59 | 27.8 | 1,213.77 | 1,168.56 | 2.08 | 1.36 | 586 | ND | |
Feb | 5.52 | 9.4 | 1,077.24 | 23.65 | 1,413.06 | 1,437.42 | 1.73 | 4.63 | 530 | ND |
Wastewater . | Sample . | Time . | pH . | BOD . | COD . | Amm.N . | TN . | Nit.N . | Nitrite . | TP . | TOC . | Suspended solid . |
---|---|---|---|---|---|---|---|---|---|---|---|---|
Leachate | Spring | Mar | 8.12 | 2,516 | 6,045.32 | 1,405.15 | 1,441.21 | 13.44 | 0.23 | 3.86 | 2,006 | 320 |
May | 8.36 | 3,513 | 12,262.5 | 1,120.94 | 1,149.43 | 10.38 | 0.31 | 8.57 | 4,562 | 678 | ||
Apr | 8.24 | 1,730 | 5,944.33 | 1,422.17 | 1,491.04 | 28.56 | 0.82 | 8.62 | 2,036 | 497 | ||
Summer | Jul | 7.44 | 3,866 | 14,526.67 | 1,106.11 | 1,290.31 | 25.77 | 0.57 | 12.01 | 5,865 | 1,004 | |
Jun | 7.85 | 3,644 | 10,736.94 | 1,150.19 | 1,201.82 | 29.09 | 0.89 | 12.58 | 4,020 | 836 | ||
Aug | 7.86 | 3,502 | 9,550.52 | 1,256.81 | 1,307.37 | 25.15 | 0.88 | 12.02 | 4,013 | 812 | ||
Fall | Sep | 7.66 | 3,563 | 8,651.21 | 1,309.67 | 1,486.29 | 30.04 | 0.5 | 10.11 | 3,332 | 976 | |
Nov | 7.91 | 1,755 | 6,755.12 | 1,388.5 | 1,476.65 | 53.66 | 0.69 | 2.59 | 2,048 | 410 | ||
Winter | Oct | 8.05 | 1,720 | 4,982.48 | 1,464.72 | 1,552.77 | 40.17 | 0.87 | 1.06 | 1,677 | 365 | |
Feb | 8.21 | 1,336 | 3,012.54 | 1,451.02 | 1,543.87 | 35.58 | 0.73 | 3.4 | 1,848 | 552 | ||
NF concentrate | Spring | Mar | 6.42 | 10.3 | 5,295.51 | 55.93 | 321.83 | 228.05 | 15.44 | 14.74 | 1,148 | 0.05 |
May | 6.87 | 14.8 | 5,375.42 | 34.06 | 217.93 | 134.59 | 11.87 | 18.26 | 1,253 | 0.04 | ||
Apr | 7.08 | 13.3 | 5,395.67 | 53.09 | 310.05 | 234.33 | 9.66 | 18.05 | 1,351 | 0.03 | ||
Summer | Jul | 7.08 | 14.6 | 5,642.38 | 35.43 | 196.32 | 125.46 | 7.36 | 24.18 | 1,595 | 0.04 | |
Jun | 7.05 | 16.4 | 5,811.68 | 31.93 | 201.72 | 136.72 | 9.12 | 25.58 | 1,673 | 0.01 | ||
Aug | 7.17 | 11.1 | 5,410.26 | 30.53 | 185.86 | 112.42 | 7.52 | 21.73 | 1,410 | 0.04 | ||
Fall | Sep | 7.12 | 16.2 | 5,448.01 | 34.77 | 184.2 | 120.53 | 9.88 | 21.57 | 1,468 | 0.02 | |
Nov | 6.56 | 12.2 | 5,244.6 | 41.64 | 323.23 | 243.23 | 10.51 | 7.59 | 1,304 | 0.09 | ||
Winter | Oct | 6.54 | 9.6 | 5,155.39 | 63.46 | 395.23 | 303.64 | 13.31 | 2.61 | 1,255 | 0.1 | |
Feb | 6.25 | 10.5 | 5,003.17 | 61.21 | 404.39 | 311.21 | 11.09 | 10.26 | 1,210 | 0.14 | ||
RO concentrate | Spring | Mar | 6.39 | 18.2 | 1,487.85 | 7.76 | 1,029.62 | 1,004.59 | 1.52 | 4.02 | 565 | ND |
May | 6.15 | 37.3 | 1,645.02 | 4.97 | 750.03 | 645.88 | 0.66 | 11.63 | 712 | ND | ||
Apr | 6.41 | 11.5 | 1,480.67 | 13.55 | 1,054.27 | 982.35 | 2.02 | 10.19 | 605 | ND | ||
Summer | Jul | 6.24 | 21.7 | 1,451.67 | 5.26 | 811.11 | 781.62 | 0.53 | 10.39 | 762 | ND | |
Jun | 6.43 | 21.8 | 1,742.4 | 10.05 | 414.52 | 404.51 | 0.32 | 15.24 | 736 | ND | ||
Aug | 6.24 | 19.2 | 1,620 | 10.72 | 424.3 | 401.76 | 0.62 | 11.51 | 740 | ND | ||
Fall | Sep | 6.5 | 29.4 | 1,791.76 | 6.28 | 609.85 | 600.37 | 0.81 | 3.11 | 724 | ND | |
Nov | 6.01 | 13.6 | 1,241.68 | 19.35 | 900.81 | 880.14 | 1.94 | 1.48 | 620 | ND | ||
Winter | Oct | 5.67 | 8.7 | 955.59 | 27.8 | 1,213.77 | 1,168.56 | 2.08 | 1.36 | 586 | ND | |
Feb | 5.52 | 9.4 | 1,077.24 | 23.65 | 1,413.06 | 1,437.42 | 1.73 | 4.63 | 530 | ND |
Note. ND, Not detected.
The concentration of COD in landfill leachate varied from 3,012.54 to 14,526.67 mg L−1, which showed dramatic seasonal variability. During summer and fall, the rapid degradation of surface fresh waste produced organic-rich leachate, which mixed with rainfall and percolated through the landfill mass. The ranges of ratios of BOD5 landfill leachate to COD, NFC, and ROC were 0.25–0.46, 0.0007–0.004, and 0.006–0.08, respectively. The high biodegradability of leachate observed during spring and winter can be primarily attributed to the decomposition of biodegradable fractions into CO2 and H2O or their utilization for microbial growth within biological treatment reactors (Moravia et al. 2021). Compared to the rainy season, leachate exhibited greater biodegradability in these seasons due to the interplay between biological activity and rainfall. While low temperatures generally reduce microbial activity, the limited rainfall during spring and winter minimized dilution effects, allowing organic matter concentrations to remain high and promoting more effective biodegradation.
Phosphorus adheres mainly to suspended particles and coarse colloids, which affects removal efficiency by aerobic/anaerobic treatment (N'Goran et al. 2019). The residues could be further removed by membrane processes and captured into concentrates. It is worth noting that the concentration of TP in summer and fall was more than 10-fold higher than that in winter and spring, which showed a close correlation between phosphorus concentrations and rainfall.
TN in landfill leachate varied from 1,211.04 to 1,801.82 mg L−1. The change in concentration of TN in leachate with season was not obvious. Amm.N comprised the major nitrogenous compound in raw leachate, accounting for 87–98% of TN. Compared to the single-stage anaerobic-aerobic system reported by Zhang et al. (2013), the two-stage nitrification–denitrification system had higher nitrogen removal ability. The concentrations of nitrite and Nit.N were lower (10.3–53.66 mg L−1 and 0.23–0.89 mg L−1, respectively) in landfill leachate but were higher in NFC (358.46–1,384.11 mg L−1 and 3.87–14.31 mg L−1, respectively) and ROC (81.62–1,637.42 mg L−1 and 0.32–2.08 mg L−1, respectively).
Metal content in landfill leachate and concentrates
The concentrations of metals in landfill leachate and concentrates varied according to the composition of the waste mass and the prevailing phase of stabilization in the landfill (Slack et al. 2005). The results for seven metals (Cr, Cd, Pb, Hg, Fe, Zn, and Cu) are listed in Table 2, which shows the distribution of concentrations in landfill leachate treatment processing. The concentration of Fe was the highest, ranging from 6.03 to 27.19 mg L−1. Extracellular activated sludge polymeric substances retain the strong biosorption capacity of metals (Miao et al. 2016) and the UF process allowed the separation of slurry and the metal-rich sludge to a biological reaction tank. Therefore, the excess sludge generated from landfill leachate treatment processes should be given sufficient attention. The seasonal variation in the concentrations of heavy metals was characterized. Cr, Fe, and Zn showed higher concentrations in summer and fall. Negligible heavy metals are leached in spring and winter because of the relatively higher pH, which also explains why fresh leachates, contain more heavy metals than old leachate (Kiddee et al. 2014). Samples collected during spring and winter showed high values due to the higher dissolution rate affected by a higher pH (Jia et al. 2007).
Metal characteristics of landfill leachate and concentrates at various months (mg L−1)
Wastewater . | Sample . | Time . | Cr . | Cd . | Pb . | Hg . | As . | Cu . | Fe . | Zn . |
---|---|---|---|---|---|---|---|---|---|---|
Landfill leachate | Spring | Mar | 0.4652 | 0.0025 | 0.1255 | 0.0477 | 0.1848 | 0.0642 | 8.0106 | 0.2144 |
May | 0.8531 | 0.0013 | 0.1216 | 0.0572 | 0.1026 | 0.0914 | 13.9035 | 0.5318 | ||
Apr | 1.4276 | ND | 0.121 | 0.0316 | 0.0559 | 0.1169 | 16.0788 | 0.4338 | ||
Summer | Jul | 1.204 | ND | 0.1644 | 0.0616 | 0.0516 | 0.135 | 21.8266 | 0.6981 | |
Jun | 1.2288 | ND | 0.157 | 0.0364 | 0.0763 | 0.031 | 20.4982 | 0.6047 | ||
Aug | 1.069 | 0.0017 | 0.1469 | 0.0402 | 0.0708 | 0.1009 | 27.1931 | 0.7937 | ||
Fall | Sep | 1.0678 | ND | 0.1456 | 0.0416 | 0.0916 | 0.0827 | 20.5514 | 0.2645 | |
Nov | 0.7506 | 0.0018 | 0.1438 | 0.0352 | 0.1232 | 0.0089 | 6.0315 | 0.1983 | ||
Winter | Oct | 0.5491 | 0.0025 | 0.1052 | 0.0231 | 0.2282 | 0.0056 | 6.146 | 0.1478 | |
Feb | 0.2512 | 0.019 | 0.1211 | 0.021 | 0.1785 | 0.0394 | 10.2509 | 0.4419 | ||
NF concentrate | Spring | Mar | ND | 0.18 | 0.06 | 0.1 | 0.012 | 3.07 | 1.05 | 0.88 |
May | 0.001 | 0.29 | 0.07 | 0.21 | 0.025 | 9.15 | 2.02 | 1.32 | ||
Apr | 0.002 | 0.27 | 0.05 | 0.34 | 0.034 | 12.72 | 2.47 | 1.91 | ||
Summer | Jul | 0.003 | 0.34 | 0.07 | 0.29 | 0.022 | 11.3 | 2.01 | 1.36 | |
Jun | 0.003 | 0.23 | 0.07 | 0.72 | 0.042 | 15.13 | 2.01 | 1.73 | ||
Aug | 0.002 | 0.35 | 0.08 | 0.66 | 0.043 | 19.14 | 1.67 | 1.27 | ||
Fall | Sep | 0.003 | 0.21 | 0.08 | 0.2 | 0.015 | 10.69 | 2.14 | 1.05 | |
Nov | 0.002 | 0.17 | 0.05 | 0.22 | 0.009 | 8.95 | 1.13 | 0.92 | ||
Winter | Oct | ND | 0.15 | 0.05 | 0.17 | 0.008 | 5.84 | 0.82 | 0.56 | |
Feb | 0.002 | 0.16 | 0.04 | 0.19 | 0.018 | 4.39 | 1.83 | 1 | ||
RO concentrate | Spring | Mar | 0.06 | ND | 0.13 | ND | 0.07 | 0.01 | 0.15 | 0.03 |
May | 0.02 | 0.03 | 0.2 | 0.01 | 0.21 | 0.01 | 0.31 | 0.04 | ||
Apr | 0.15 | 0.01 | 0.12 | 0.01 | 0.28 | 0.02 | 0.38 | 0.06 | ||
Summer | Jul | 0.35 | 0.06 | 0.28 | 0.01 | 0.12 | 0.01 | 0.51 | 0.07 | |
Jun | 0.1 | 0.06 | 0.2 | 0.02 | 0.44 | 0.01 | 0.66 | 0.13 | ||
Aug | 0.1 | 0.03 | 0.31 | 0.02 | 0.57 | 0.02 | 0.51 | 0.08 | ||
Fall | Sep | 0.42 | 0.03 | 0.14 | 0.01 | 0.1 | 0.01 | 0.6 | 0.01 | |
Nov | 0.26 | ND | 0.11 | ND | 0.04 | ND | 0.2 | ND | ||
Winter | Oct | 0.05 | ND | 0.13 | 0.02 | 0.07 | ND | 0.11 | ND | |
Feb | 0.1 | 0.01 | 0.14 | ND | 0.14 | ND | 0.16 | 0.07 |
Wastewater . | Sample . | Time . | Cr . | Cd . | Pb . | Hg . | As . | Cu . | Fe . | Zn . |
---|---|---|---|---|---|---|---|---|---|---|
Landfill leachate | Spring | Mar | 0.4652 | 0.0025 | 0.1255 | 0.0477 | 0.1848 | 0.0642 | 8.0106 | 0.2144 |
May | 0.8531 | 0.0013 | 0.1216 | 0.0572 | 0.1026 | 0.0914 | 13.9035 | 0.5318 | ||
Apr | 1.4276 | ND | 0.121 | 0.0316 | 0.0559 | 0.1169 | 16.0788 | 0.4338 | ||
Summer | Jul | 1.204 | ND | 0.1644 | 0.0616 | 0.0516 | 0.135 | 21.8266 | 0.6981 | |
Jun | 1.2288 | ND | 0.157 | 0.0364 | 0.0763 | 0.031 | 20.4982 | 0.6047 | ||
Aug | 1.069 | 0.0017 | 0.1469 | 0.0402 | 0.0708 | 0.1009 | 27.1931 | 0.7937 | ||
Fall | Sep | 1.0678 | ND | 0.1456 | 0.0416 | 0.0916 | 0.0827 | 20.5514 | 0.2645 | |
Nov | 0.7506 | 0.0018 | 0.1438 | 0.0352 | 0.1232 | 0.0089 | 6.0315 | 0.1983 | ||
Winter | Oct | 0.5491 | 0.0025 | 0.1052 | 0.0231 | 0.2282 | 0.0056 | 6.146 | 0.1478 | |
Feb | 0.2512 | 0.019 | 0.1211 | 0.021 | 0.1785 | 0.0394 | 10.2509 | 0.4419 | ||
NF concentrate | Spring | Mar | ND | 0.18 | 0.06 | 0.1 | 0.012 | 3.07 | 1.05 | 0.88 |
May | 0.001 | 0.29 | 0.07 | 0.21 | 0.025 | 9.15 | 2.02 | 1.32 | ||
Apr | 0.002 | 0.27 | 0.05 | 0.34 | 0.034 | 12.72 | 2.47 | 1.91 | ||
Summer | Jul | 0.003 | 0.34 | 0.07 | 0.29 | 0.022 | 11.3 | 2.01 | 1.36 | |
Jun | 0.003 | 0.23 | 0.07 | 0.72 | 0.042 | 15.13 | 2.01 | 1.73 | ||
Aug | 0.002 | 0.35 | 0.08 | 0.66 | 0.043 | 19.14 | 1.67 | 1.27 | ||
Fall | Sep | 0.003 | 0.21 | 0.08 | 0.2 | 0.015 | 10.69 | 2.14 | 1.05 | |
Nov | 0.002 | 0.17 | 0.05 | 0.22 | 0.009 | 8.95 | 1.13 | 0.92 | ||
Winter | Oct | ND | 0.15 | 0.05 | 0.17 | 0.008 | 5.84 | 0.82 | 0.56 | |
Feb | 0.002 | 0.16 | 0.04 | 0.19 | 0.018 | 4.39 | 1.83 | 1 | ||
RO concentrate | Spring | Mar | 0.06 | ND | 0.13 | ND | 0.07 | 0.01 | 0.15 | 0.03 |
May | 0.02 | 0.03 | 0.2 | 0.01 | 0.21 | 0.01 | 0.31 | 0.04 | ||
Apr | 0.15 | 0.01 | 0.12 | 0.01 | 0.28 | 0.02 | 0.38 | 0.06 | ||
Summer | Jul | 0.35 | 0.06 | 0.28 | 0.01 | 0.12 | 0.01 | 0.51 | 0.07 | |
Jun | 0.1 | 0.06 | 0.2 | 0.02 | 0.44 | 0.01 | 0.66 | 0.13 | ||
Aug | 0.1 | 0.03 | 0.31 | 0.02 | 0.57 | 0.02 | 0.51 | 0.08 | ||
Fall | Sep | 0.42 | 0.03 | 0.14 | 0.01 | 0.1 | 0.01 | 0.6 | 0.01 | |
Nov | 0.26 | ND | 0.11 | ND | 0.04 | ND | 0.2 | ND | ||
Winter | Oct | 0.05 | ND | 0.13 | 0.02 | 0.07 | ND | 0.11 | ND | |
Feb | 0.1 | 0.01 | 0.14 | ND | 0.14 | ND | 0.16 | 0.07 |
Note. ND, Not detected.
The concentrations of metals in landfill leachate differed from those of NF and RO concentrates. Cr, Pb, Hg, As, and Zn were higher in NF concentrate than in landfill leachate, particularly Zn (0.52–4.01 mg L−1). The concentration of Cd (0.06–0.002 mg L−1) was higher in ROC than in landfill leachate and NFC. However, the accumulating concentrations of metals in the present study were weaker than those reported by Zhang et al. (2013). We presume that possible reasons to explain this discrepancy include (1) less rainfall and precipitation intensity decrease the leaching effect in northeast China; (2) relatively low temperature (annual average temperature of 6.8–8.0 °C) inhibits biological activity and chemical action; (3) HA adsorbed heavy metals, which were removed by the NF concentrate reduction system; and (4) the ‘old’ leachate collected from landfill that had operated over 10 years contained lower metals than ‘recent’ and ‘intermediate’ leachate (Renou et al. 2008).
Notably, Cr, Cd, and Pb showed peak concentrations during summer and fall (Table 2), which coincided with lower LC50 values (i.e., higher toxicity) in these same seasons (Table 4). This finding suggests that elevated levels of these metals may play a significant role in the acute toxicity observed, in agreement with previous reports indicating that heavy metals can accumulate in leachates and exert detrimental effects on aquatic organisms. Furthermore, higher temperatures and increased rainfall in summer might enhance metal solubility and mobility, thereby intensifying the overall toxicity.
Composition of DOM in landfill leachate and concentrates
DOM fractions of mature leachate and biologically pretreated leachate consist of major refractory organic components (Ren et al. 2018; Li et al. 2023b). The selection of the appropriate treatment requires the exploration of the distribution and transformation of HA, FA, and HyI in leachate and concentrates. The fractionation of leachate and concentrates is presented in Table 3. The proportion of HA was higher in winter (8.43%). Lower temperatures and less rainfall preclude an environment for anaerobic fermentation, which benefits the generation of HA (Ye et al. 2019). The percentage contribution of HyI to DOM is consistently large over all seasons (68.2% on average), especially in summer and fall. During these seasons, the higher temperature promotes waste degradation, and abundant rainwater results in leachate generation. A large number of volatile fatty acids increase the proportion of HyI. HyI is preferentially degraded through the biotreatment process. The NF membrane performs poorly at intercepting these low-molecular organics. Hence, interception was lower in NFC, ranging from 8.8 to 18.7%. Finally, the remaining HyI was accumulated in ROC (accounting for 25.3–49.4%). Macromolecular organic matter (HA and FA) was mostly intercepted by the NF membrane. However, the macromolecular organic matter passed through the NF membrane and accumulated in ROC, which resulted in higher biodegradability of ROC compared to NFC. FA changed slightly in both leachate and concentrates over all seasons. According to the discriminating analysis described by Huo et al. (2008) and He et al. (2006), it is worth noting that leachate in this landfill was similar to aged leachate in summer and medium-aged leachate in winter.
Characteristics of DOM fractions in landfill leachate and concentrates
Var. . | Sample . | Spring . | Summer . | Fall . | Winter . |
---|---|---|---|---|---|
Mean (mg L−1) . | |||||
HA | Landfill leachate | 100.44 ± 14.22 | 72.55 ± 10.61 | 92.17 ± 12.78 | 117.5 ± 10.78 |
NFC | 293.89 ± 14.61 | 347.78 ± 7.72 | 330.34 ± 15.11 | 283.83 ± 3.67 | |
ROC | 10.67 ± 1.99 | 14.78 ± 3.95 | 9.17 ± 1.16 | 8.34 ± 0.89 | |
FA | Landfill leachate | 452.78 ± 11.72 | 553.89 ± 7.89 | 390 ± 26.22 | 389.5 ± 12.55 |
NFC | 781.56 ± 38.06 | 912.67 ± 25 | 913.17 ± 20.78 | 737.83 ± 15.67 | |
ROC | 406.55 ± 47.22 | 458.44 ± 13.56 | 428.33 ± 45.33 | 291.83 ± 3.67 | |
HyI | Landfill leachate | 1,158 ± 51.17 | 1,446.33 ± 28.67 | 1,201.17 ± 80.44 | 885.83 ± 16.33 |
NFC | 163.89 ± 5.89 | 252.78 ± 33.72 | 138.67 ± 16.44 | 148.5 ± 2.11 | |
ROC | 237.89 ± 8.72 | 230.67 ± 25.5 | 208.33 ± 25.33 | 274 ± 8 |
Var. . | Sample . | Spring . | Summer . | Fall . | Winter . |
---|---|---|---|---|---|
Mean (mg L−1) . | |||||
HA | Landfill leachate | 100.44 ± 14.22 | 72.55 ± 10.61 | 92.17 ± 12.78 | 117.5 ± 10.78 |
NFC | 293.89 ± 14.61 | 347.78 ± 7.72 | 330.34 ± 15.11 | 283.83 ± 3.67 | |
ROC | 10.67 ± 1.99 | 14.78 ± 3.95 | 9.17 ± 1.16 | 8.34 ± 0.89 | |
FA | Landfill leachate | 452.78 ± 11.72 | 553.89 ± 7.89 | 390 ± 26.22 | 389.5 ± 12.55 |
NFC | 781.56 ± 38.06 | 912.67 ± 25 | 913.17 ± 20.78 | 737.83 ± 15.67 | |
ROC | 406.55 ± 47.22 | 458.44 ± 13.56 | 428.33 ± 45.33 | 291.83 ± 3.67 | |
HyI | Landfill leachate | 1,158 ± 51.17 | 1,446.33 ± 28.67 | 1,201.17 ± 80.44 | 885.83 ± 16.33 |
NFC | 163.89 ± 5.89 | 252.78 ± 33.72 | 138.67 ± 16.44 | 148.5 ± 2.11 | |
ROC | 237.89 ± 8.72 | 230.67 ± 25.5 | 208.33 ± 25.33 | 274 ± 8 |
Acute toxicity of landfill leachate and concentrates
Month . | Landfill leachate . | NFC . | ROC . | |||
---|---|---|---|---|---|---|
24 h-LC50 . | TU . | 24 h-LC50 . | TU . | 24 h-LC50 . | TU . | |
Mar | 30.82 | 3.24 | 74.92 | 1.33 | 65.09 | 1.54 |
May | 15.13 | 6.61 | 53.97 | 1.85 | 93.84 | 1.07 |
Jul | 8.94 | 11.19 | 55.4 | 1.81 | 200 | 0.50 |
Sep | 25.95 | 3.85 | 67.11 | 1.49 | 98.45 | 1.02 |
Nov | 38.31 | 2.61 | 73.56 | 1.36 | 73.81 | 1.35 |
Dec | 39.28 | 2.55 | 80.5 | 1.24 | 61.98 | 1.61 |
Feb | 35.55 | 2.81 | 78.06 | 1.28 | 57.01 | 1.75 |
Apr | 28.09 | 3.56 | 71.43 | 1.40 | 72.18 | 1.39 |
Jun | 9.11 | 10.98 | 47.38 | 2.11 | 200 | 0.50 |
Aug | 11.04 | 9.06 | 53.52 | 1.87 | 200 | 0.50 |
Month . | Landfill leachate . | NFC . | ROC . | |||
---|---|---|---|---|---|---|
24 h-LC50 . | TU . | 24 h-LC50 . | TU . | 24 h-LC50 . | TU . | |
Mar | 30.82 | 3.24 | 74.92 | 1.33 | 65.09 | 1.54 |
May | 15.13 | 6.61 | 53.97 | 1.85 | 93.84 | 1.07 |
Jul | 8.94 | 11.19 | 55.4 | 1.81 | 200 | 0.50 |
Sep | 25.95 | 3.85 | 67.11 | 1.49 | 98.45 | 1.02 |
Nov | 38.31 | 2.61 | 73.56 | 1.36 | 73.81 | 1.35 |
Dec | 39.28 | 2.55 | 80.5 | 1.24 | 61.98 | 1.61 |
Feb | 35.55 | 2.81 | 78.06 | 1.28 | 57.01 | 1.75 |
Apr | 28.09 | 3.56 | 71.43 | 1.40 | 72.18 | 1.39 |
Jun | 9.11 | 10.98 | 47.38 | 2.11 | 200 | 0.50 |
Aug | 11.04 | 9.06 | 53.52 | 1.87 | 200 | 0.50 |
Acute toxicity test
The acute toxicity of landfill leachate, NFC, and ROC was evaluated using Artemia salina, with 24 h-LC50 values serving as the primary toxicity endpoint (Table 4). Overall, the results revealed that all three wastewater types posed a certain degree of acute toxicity to A. salina, although the severity and seasonal variation differed among samples (Ribé et al. 2012).
Specifically, landfill leachate exhibited the highest toxicity, particularly during the summer months (24 h-LC50 as low as 9.11% in June and 8.94% in July), suggesting that increased temperatures and microbial activity could intensify the production or release of toxic compounds. This observation is consistent with previous findings indicating that high ammonia concentrations and alkalinity can significantly contribute to the acute toxicity of leachates (Costa et al. 2019). In addition, certain organic pollutants such as phenols, which are often detected in landfill leachate, may further exacerbate toxicity (Kurata et al. 2008). Conversely, the leachate collected in winter and spring showed higher 24 h-LC50 values, indicating relatively lower toxicity during these seasons.
For the NFC, the 24 h-LC50 values ranged from 47.32 to 80.5% and exhibited notable seasonal variability. Although the biological treatment processes preceding NF helped to reduce some of the biodegradable fractions, humic substances, heavy metals, and other refractory compounds could still concentrate within the NFC, influencing its toxicity profile. The toxicity of the ROC also displayed discernible temporal fluctuations, with the highest toxicity observed in February (24 h-LC50 at 57.01%), whereas little to no significant toxicity was detected during the summer. One possible explanation is that smaller molecular weight organics and nitrogenous compounds (e.g., nitrite and nitrate) may accumulate more in ROC, potentially impacting A. salina at higher concentrations during cooler seasons. In contrast, lower apparent toxicity in summer might be associated with additional factors such as temperature-mediated volatilization or microbial transformation of certain toxicants.
When samples showed no measurable toxicity within tested concentrations, the 24 h-LC50 dilution was assigned as 200% to standardize data presentation and classification. This approach ensures that ‘non-toxic’ samples are still quantitatively accounted for in comparative analyses.
From an environmental perspective, these findings underscore the importance of seasonal monitoring and management strategies for landfill leachate treatment. Summer conditions may promote the formation or release of more toxic constituents, posing a greater risk to aquatic life if leachate or concentrates are inadequately treated prior to discharge. Conversely, winter and spring data suggest that certain biological or chemical processes might temporarily reduce acute toxicity. Overall, the observed fluctuations highlight the need for adaptive, seasonally informed treatment approaches. In particular, advanced or supplementary treatment steps – capable of further removing ammonia, phenols, and other refractory organics – may be required to mitigate the acute toxicity risk posed to local ecosystems.
Multivariate analysis of physicochemical variables and acute toxicity of landfill leachate and concentrates
The advantage of PCA is that every measured object and variable can be studied simultaneously and that the most important information about a dataset is captured in the first components (Ribé et al. 2012). Bernard et al. (1996) and (1997) found that ammonia and alkalinity contributed to the toxicity of leachate in a study of the characteristics of 22 landfill leachates in which relationships between measured physicochemical variables and acute toxicity were analyzed by PCA and regression. Ribé et al. (2012) used PCA to assess the toxicity of five landfill leachates before and after treatment by pink dark biosorbent. The increases in metal and phenol concentrations were correlated with an increase in toxicity.
Three-dimensional plot of PCA for the chemical analysis of landfill leachate and concentrates: (a) landfill leachate; (b) NFC – nanofiltration concentrate; (c) ROC – reverse osmosis concentrate. PC1 and PC2 explain 83.34% of the total variance in the leachate samples, with strong loadings from COD, NH4+, heavy metals (Cr, Cd), and LC50 values of A. salina. The negative correlation between PC1 scores and LC50 highlights the potential role of these parameters in driving toxicity.
Three-dimensional plot of PCA for the chemical analysis of landfill leachate and concentrates: (a) landfill leachate; (b) NFC – nanofiltration concentrate; (c) ROC – reverse osmosis concentrate. PC1 and PC2 explain 83.34% of the total variance in the leachate samples, with strong loadings from COD, NH4+, heavy metals (Cr, Cd), and LC50 values of A. salina. The negative correlation between PC1 scores and LC50 highlights the potential role of these parameters in driving toxicity.
Fitting relationship between TUs and first component scores of landfill leachate and concentrates: (a) landfill leachate; (b) NFC; and (c) ROC.
Fitting relationship between TUs and first component scores of landfill leachate and concentrates: (a) landfill leachate; (b) NFC; and (c) ROC.
The relationships between 21 variables of landfill leachate are shown in Figure 3(a). The first axis is characterized by the variables of BOD5, COD, Amm.N, TOC, Fe, FA, and HyI. It is worth noting that most of the metals had no obvious correlations with other physicochemical indices. It can be seen that Cu, Cd, Zn, Fe, Pb, and pH are linked. These metals were mainly identified in dissolved and exchangeable states, and lower pH would promote their release (Xie et al. 2015). Moreover, the properties of most metals are closer to those of humic substances, which will facilitate the migration of metals (Lee et al. 2023). The results of the PCA for NFC and ROC are represented graphically (Figure 2(b)). COD, TP, TOC, TN, Nit.N, Fe, FA, and HA comprise the first axis of PCA results of NF. In addition, the variables with larger weights for the first axis component of ROC were FA, COD, TN, Nit.N, nitrite, Cd, and Fe (Figure 3(c)).
In the factor load matrix, each load represents the correlation coefficient between the principal component and the corresponding variable. The feature vectors of different principal components were calculated according to the load values. The pollution levels of the three wastewaters were assessed based on scores that form the product of the principal component scores and the corresponding contribution rate (Table 5). The water quality statuses of landfill leachate, NFC, and ROC were lowest in July, September, and May, respectively, with composite scores of 3.36, 3.97, and 3.37, respectively. The quality of landfill leachate did not affect the quality of concentrates directly.
Principal component scores and composite score for evaluation of water quality
Month . | Score . | |||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
Landfill leachate . | NF concentrate . | RO concentrate . | ||||||||||
F1 . | F2 . | F3 . | Total . | F1 . | F2 . | F3 . | Total . | F1 . | F2 . | F3 . | Total . | |
Feb | −2.53 | −0.7 | −0.46 | −1.71 | −7.54 | −0.09 | −0.2 | −5.22 | −4.65 | 1.3 | −0.72 | −2.43 |
Mar | −1.44 | −2.16 | 1.55 | −1.1 | 1.74 | −2.26 | −1.07 | −0.8 | 1.74 | −1.13 | −1.74 | 0.64 |
Apr | −6.85 | 2.8 | 0.8 | −3.82 | −3.18 | −0.45 | 0.74 | −2.49 | −0.4 | 0.18 | −1.8 | −0.34 |
May | 3.21 | −1.29 | 1.75 | 1.94 | 4.1 | −1.6 | −0.42 | 1.41 | 6.06 | −0.35 | 0.62 | 3.37 |
Jun | 3.71 | 1.6 | −1.4 | 2.44 | 1.0 | 1.64 | 0.75 | 2.12 | 0.66 | 3.53 | 0.06 | 0.96 |
Jul | 5.17 | 0.74 | 0.46 | 3.36 | 2.13 | 1.35 | −0.14 | 2.58 | 0.15 | 2.07 | 0.67 | 0.48 |
Sep | 1.85 | 1.58 | 0.24 | 1.39 | 2.98 | −0.45 | 2.8 | 1.84 | −0.64 | −0.22 | 2.14 | −0.22 |
Oct | 0.03 | 0.76 | −0.09 | 0.12 | 4.22 | 1.42 | −1.58 | 3.97 | 3.52 | −1.52 | 0.2 | 1.72 |
Nov | −0.27 | −1.5 | −1.89 | −0.51 | −2.43 | 1.04 | −0.52 | −0.81 | −1.5 | −1.81 | −0.4 | −1.17 |
Dec | −2.88 | −1.83 | −0.97 | −2.12 | −3.02 | −0.6 | −0.35 | −2.59 | −4.93 | −2.05 | 0.98 | −3.01 |
Month . | Score . | |||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
Landfill leachate . | NF concentrate . | RO concentrate . | ||||||||||
F1 . | F2 . | F3 . | Total . | F1 . | F2 . | F3 . | Total . | F1 . | F2 . | F3 . | Total . | |
Feb | −2.53 | −0.7 | −0.46 | −1.71 | −7.54 | −0.09 | −0.2 | −5.22 | −4.65 | 1.3 | −0.72 | −2.43 |
Mar | −1.44 | −2.16 | 1.55 | −1.1 | 1.74 | −2.26 | −1.07 | −0.8 | 1.74 | −1.13 | −1.74 | 0.64 |
Apr | −6.85 | 2.8 | 0.8 | −3.82 | −3.18 | −0.45 | 0.74 | −2.49 | −0.4 | 0.18 | −1.8 | −0.34 |
May | 3.21 | −1.29 | 1.75 | 1.94 | 4.1 | −1.6 | −0.42 | 1.41 | 6.06 | −0.35 | 0.62 | 3.37 |
Jun | 3.71 | 1.6 | −1.4 | 2.44 | 1.0 | 1.64 | 0.75 | 2.12 | 0.66 | 3.53 | 0.06 | 0.96 |
Jul | 5.17 | 0.74 | 0.46 | 3.36 | 2.13 | 1.35 | −0.14 | 2.58 | 0.15 | 2.07 | 0.67 | 0.48 |
Sep | 1.85 | 1.58 | 0.24 | 1.39 | 2.98 | −0.45 | 2.8 | 1.84 | −0.64 | −0.22 | 2.14 | −0.22 |
Oct | 0.03 | 0.76 | −0.09 | 0.12 | 4.22 | 1.42 | −1.58 | 3.97 | 3.52 | −1.52 | 0.2 | 1.72 |
Nov | −0.27 | −1.5 | −1.89 | −0.51 | −2.43 | 1.04 | −0.52 | −0.81 | −1.5 | −1.81 | −0.4 | −1.17 |
Dec | −2.88 | −1.83 | −0.97 | −2.12 | −3.02 | −0.6 | −0.35 | −2.59 | −4.93 | −2.05 | 0.98 | −3.01 |
It is widely known that humic substances can decrease the toxicity of heavy metals (Borůvka & Drábek 2004; Hussain & Saeed 2024). However, the presence of HA might result in additional toxicity for some organic matter. Moreover, the high aromaticity of HA and high content of organic halogens in HA might have direct toxic effects on organisms (Oikari et al. 1992). Conventional biotreatment is not able to sufficiently degrade highly toxic organic compounds such as aromatic compounds and halohydrocarbons.
However, a negative relationship between scores of component 1 and TU was found for ROC (r = −0.93). The major contaminants changed with the degradation and separation of landfill leachate that was responsible for the variability of acute toxicity to A. salina. The same separation of groups cannot be observed for ROC. Nitrogen was the main contributor to ROC toxicity observed in the aquatic ecotoxicity test. Moreover, some studies have recognized the toxicity of Nit.N to aquatic organisms, and the sensitivity priority has been estimated by Moore & Bringolf (2020). The high concentration of Nit.N in ROC would result in the oxidization of hemoglobin to methemoglobin, thereby resulting in the loss of capability to carry oxygen. It is worth noting that there was a significant contribution from Amm.N in both NFC and ROC, which was different from leachate.
The scores of the first components of each wastewater sample could be used to predict the rate by discriminant functions (Pablos et al. 2011). The results listed in Table 6 show that the physicochemical variables can offer a good initial categorization of the predicted toxicity of the three wastewater variables. The toxicity categorizations based on physicochemical variables and bioassays were observed (90% for landfill leachate, 100% for NFC, and 80% for ROC). The false negative (toxic sample classified as ‘not toxic’) result was obtained for ROC (28.6%). However, the correlation was not based on a real cause-effect relationship but on a simple association between the toxicity and the characteristics of the three wastewater variables. The false negatives should be considered relatively low, as the toxicity classification of landfill leachate and concentrates will be seriously affected by some factors (toxic chemicals and serving age). However, the results from discriminant analysis indicate that these variables could be used as a preliminary screening of the acute toxicity of landfill leachate and concentrations on organisms.
Discriminant analysis regarding predictive toxicity based on the first component
Actual classification . | Measured value . | Predicted classification of highly acute toxicity . | Predicted classification of acute toxicity . |
---|---|---|---|
High acute toxicity | 2 | 1 (50%) | 1 (50%) |
Acute toxicity | 8 | 8 | 0 |
Acute toxicity | 10 | 10 | 0 |
Acute toxicity | 7 | 5 (71.4%) | 2 (28.6%) |
Slight acute toxicity | 3 | 0 | 3 |
Actual classification . | Measured value . | Predicted classification of highly acute toxicity . | Predicted classification of acute toxicity . |
---|---|---|---|
High acute toxicity | 2 | 1 (50%) | 1 (50%) |
Acute toxicity | 8 | 8 | 0 |
Acute toxicity | 10 | 10 | 0 |
Acute toxicity | 7 | 5 (71.4%) | 2 (28.6%) |
Slight acute toxicity | 3 | 0 | 3 |
CONCLUSIONS
The current study revealed seasonal variability in the composition of landfill leachate and concentrates. Although biotreatment could reduce the pollutants in landfill leachate, toxicity components were accumulated in concentrates. Owing to the degradation of biodegradable organic components in landfill leachate in the biological process, concentrates showed lower biodegradability than landfill leachate. The A. salina test indicated that the landfill leachate and concentrates were highly acutely toxic. Landfill leachate and NFC showed higher toxicity in summer and fall. In contrast, ROC was found to be more toxic in winter and spring. The PCA and discriminant analysis methods showed that physicochemical variables could be used as a low-cost and effective method for estimating the quality and toxicity of landfill leachate and concentrates. The main contributors to the toxicity of landfill leachate and concentrates varied; however, the toxic effect on other organisms should be studied further to better understand the most appropriate toxicity testing organism for these wastewater variables. These findings underscore the importance of seasonally adaptive management strategies in landfill leachate treatment. For instance, enhanced metal removal or AOPs could be prioritized during summer months when toxicity peaks. Additionally, monitoring protocols should incorporate multi-species bioassays to capture a broader spectrum of ecological risks. By integrating these approaches, landfill operators and regulators can more effectively mitigate the environmental impact of landfill leachate and concentrates across different seasons.
FUNDING DECLARATION
This research was supported by Liaoning Provincial Science and Technology Project (2022JH2/101300112).
Special thanks are due to the instrumental or data analysis from Analytical and Testing Center, Northeastern University, China and Shiyanjia Lab (http://www.shiyanjia.com).
AUTHOR CONTRIBUTION DECLARATION
Conceptualized by X.R., X.H., and F.W.; methodology was developed by X.R., F.W., X.H., and D.K.; support was rendered in formal analysis and investigated by X.R., X.H., and D.K.; the original draft was written and prepared by X.R. and X.H.; written, reviewed and edited by X.R. and X.H.; funding acquired by F.W.; resources contributed by F.W.; supervised by F.W.
DATA AVAILABILITY STATEMENT
All relevant data are included in the paper or its Supplementary Information.
CONFLICT OF INTEREST
The authors declare there is no conflict.
REFERENCES
Author notes
These authors contributed equally to this study.