Water eutrophication and climate change are global challenges. Addressing the imbalance of carbon, nitrogen, and phosphorus is crucial for mitigating eutrophication. Utilizing atmospheric CO2 offers an eco-friendly and economic approach to restore aquatic ecosystems and combine climate change. This study investigated the effect of pH on dissolved inorganic carbon (DIC) concentrations in ultrapure, lake, and river water. pH levels (3.5–12.0) were adjusted using H2SO4 and NaOH in 0.5 ± 0.03 intervals and maintained at 25 ± 1 °C in a static water bath for 3 days. Results showed that alkaline conditions (pH ≥ 7.5) effectively enhanced CO2 absorption, significantly increasing DIC content (P < 0.05). Compared to pH 7.0, the average DIC content over 3 days in ultrapure, lake, and river water at pH 9.0 increased by 36.89%, 44.24%, and 45.25%, respectively. A field test in a 1.5 km eutrophic river confirmed that pH had positive correlations with C/N (P < 0.05) and C/P (P> 0.05). These findings suggest that creating alkaline conditions could help mitigate atmospheric CO2. However, these conclusions are based on our experiments, demonstrating potential benefits but requiring caution in their applicability. Further research is necessary to validate their ecological impacts and broader applicability.

  • Atmospheric CO2 is the key that unites eutrophic water and climate change.

  • We tested how water pH affects dissolved inorganic carbon in three water types.

  • Alkaline conditions can pull significant volumes of atmospheric CO2 into water.

  • Raising pH to 9.0 harnesses atmospheric CO2 to effectively treat eutrophic water.

  • The increase in pH is beneficial for the balance of C/N and C/P.

Due to human activities, large volumes of nitrogen (N) and phosphorus (P) nutrients enter waterbodies, creating eutrophication with seriously imbalanced nutrient ratios (Kharbush et al. 2023). Eutrophication seriously damages aquatic ecosystems, leading to the increase of algal biomass and potential algal toxins, reduction in light penetration and dissolved oxygen (DO), mass death of fish, and loss of biodiversity (Moal et al. 2019; Vasseghian et al. 2024). Water pollution and eutrophication have been estimated to cause economic losses of $6–16 billion and more than 3 million deaths globally every year (Zhu et al. 2024). Therefore, finding economic and efficient methods to mitigate eutrophication is the future development direction.

Typically, eutrophication is addressed by restricting the influx of both endogenous and exogenous nutrients. Measures for removing excess N and P from water include biological, chemical, and physical methods (Yin et al. 2018; Zhu et al. 2020; Fan et al. 2021). Biological methods, such as microbial remediation, biofilm technologies, constructed wetlands, and aquatic phytoremediation, are limited by the environmental adaptability of microorganisms and often require long treatment cycles (Zhou et al. 2022). Chemical methods, involving copper sulfate (CuSO4), herbicides, and algicides, face challenges related to high costs, the generation of secondary pollution, and potential toxicity to non-target aquatic organisms, humans, livestock, and wildlife (Zhang et al. 2020). Physical methods, such as dilution, flushing, deep aeration, and sediment dredging, suffer from issues such as high energy consumption, limited treatment capacity, and unstable effectiveness (Zhang et al. 2020). Therefore, the development of innovative and more effective treatment approaches is urgently needed.

Meanwhile, carbon limitation also plays a significant role in influencing phytoplankton community structure in eutrophic waters. High dissolved inorganic carbon (DIC)/total nitrogen (TN) and DIC/total phosphorus (TP) ratios enhance photosynthesis and inhibit cyanobacteria blooms (Bao et al. 2022). Elevated CO2 levels can alter the community composition of aquatic vegetation, promote the growth of chlorophytes, Bacillariophyta, and submerged plants and decrease the toxicity of harmful algal blooms (Lai et al. 2023).

Climate change has also become a serious global environmental problem. There is a global consensus on the need to curtail greenhouse gas emissions, particularly CO2 emissions (Zheng et al. 2019). However, as concentrations continue to rise, simply limiting emissions is insufficient, since atmospheric CO2 levels are expected to triple by the end of the 21st century from the current 409.95 μatm (Vilar & Molica 2020). Reducing atmospheric CO2 and its adverse environmental impacts is critically important but challenging (Kumar et al. 2020).

Thus, CO2 plays a key role in two major environmental challenges: eutrophic water and climate change. Studies have demonstrated significant negative CO2 emissions in reservoir and lake systems (Wang et al. 2021). Utilizing atmospheric CO2 to enhance carbon sequestration in eutrophic water could be an ecologically friendly and economical way to restore aquatic ecosystems, helping achieve carbon neutrality and indirectly address climate change. Aquatic plants mainly utilize DIC in water, including CO2, , and , which are significantly influenced by pH (Tao 2017; Liu 2023). However, the precise role of pH in regulating atmospheric CO2 absorption in eutrophic water bodies has not been explored.

In this study, we conducted experiments with ultrapure water and two types of eutrophic water (lake water and river water) to investigate the effects of pH conditions on DIC content. This study sought to address the following research questions: (1) What is the effect of different pH conditions (3.5–12.0) on the amount of CO2 dissolved in eutrophic water? (2) Is there an ideal pH condition for eutrophic water treatment? (3) Can the amount of CO2 (an important greenhouse gas) absorbed resulting from pH variations during the process of eutrophic water treatment be quantified?

Water samples

Both ultrapure water and two types of urban eutrophic water samples were utilized in laboratory experiments. Ultrapure water, characterized by its low impurity levels that facilitate clear results, was prepared using FBZ1002-UP-P (Flom Technology, Qingdao, China). The urban eutrophic water samples were collected from a local lake and river in Chengdu, Southwest China (Figure 1). These water samples were immediately utilized upon arrival at the laboratory, which was situated near the water sampling sites. According to the Environmental Quality Standards for Surface Water (Chinese Standard GB 3838-2002), the indicators of both lake water and river water samples exceed the Class Ⅲ (Table 1). The Trophic Contamination Index (ICOTRO) (Acuna-Alonso et al. 2020) was used to indicate eutrophication by measuring the TP present. Water samples were categorized as oligotrophic, mesotrophic, eutrophic, or hypereutrophic based on TP concentrations: <0.01, 0.01–0.02, 0.02–1, and >1 mg/L, respectively. According to the ICOTRO and other basic water quality indicators, both the lake water and river water were determined to be eutrophic. Thus, the two types of eutrophic water samples with different nutrient contents were beneficial for observing the consistency of treatment outcomes.
Table 1

Basic water quality indicators of water samples

TP (mg/L)DP (mg/L)TN (mg/L)NH3-N (mg/L)CODMn (mg/L)pHDO (mg/L)EC (μS/cm)
GB3838-2002 (Class Ⅲ) ≤0.2 ≤0.05L&R – ≤1.0L&R ≤1.0 ≤6 6–9 ≥5.0 – 
Ultrapure water – – – – – 6.90 3.2 14.9 
Lake water 0.149 0.109 1.381 0.974 1.08 7.85 5.4 700 
River water 0.238 0.147 2.399 1.155 3.01 7.97 7.7 415 
TP (mg/L)DP (mg/L)TN (mg/L)NH3-N (mg/L)CODMn (mg/L)pHDO (mg/L)EC (μS/cm)
GB3838-2002 (Class Ⅲ) ≤0.2 ≤0.05L&R – ≤1.0L&R ≤1.0 ≤6 6–9 ≥5.0 – 
Ultrapure water – – – – – 6.90 3.2 14.9 
Lake water 0.149 0.109 1.381 0.974 1.08 7.85 5.4 700 
River water 0.238 0.147 2.399 1.155 3.01 7.97 7.7 415 

TP, total phosphorus; DP, dissolved phosphorus; TN, total nitrogen; NH3-N, ammonia nitrogen; CODMn, chemical oxygen demand; DO, dissolved oxygen; EC, electrical conductivity; L&R, the Environmental Quality Standards for lakes and reservoirs.

Figure 1

Location of two kinds of eutrophic water samples (lake and river water) collection.

Figure 1

Location of two kinds of eutrophic water samples (lake and river water) collection.

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Experimental design

To remove dissolved CO2 from ultrapure water, it was boiled for 15 min and then cooled under sealed conditions. Subsequently, 1 mL of 0.1 mol/L KCl solution was added to 1 L of cooled ultrapure water to maintain the ionic concentration, resulting in an initial DIC content of 4.49 mg/L. The eutrophic water samples were sterilized using a portable pressure steam sterilizer (YX-280, Hefei Huatai Medical Equipment Factory, China) for 30 min under 0.15 MPa pressure to remove dissolved CO2 and prevent disturbance from original organisms. After sterilization, the eutrophic water samples were filtered with non-woven cloth and cooled under sealed conditions. The initial DIC contents of the lake and river water were determined to be 14.57 and 18.94 mg/L, respectively.

From each water sample, 2,000 mL of cooled water was siphoned into separate 2,000 mL beakers. Different concentrations of H2SO4 (0.01, 0.05, 0.1, and 1.0 mol/L) and NaOH (0.01, 0.05, 0.1, and 1.0 mol/L) were then added dropwise to adjust the pH values. The pH was continuously monitored during the adjustment process to maintain the desired value. The initial pH range, from 3.5 to 12.0, was selected based on the carbonate equilibrium curve, with intervals of 0.5 ± 0.03 for each kind of water sample, resulting in a total of 54 treatments. All treatments were repeated three times, and mixed samples were obtained for analysis.

Once the desired pH was achieved, DO and electrical conductivity (EC) were immediately determined. The treated samples were then divided into two 1,000 mL beakers and placed in a static water bath at 25 ± 1 °C to simulate standard ambient temperature. One group of samples was used to determine pH, DO, and EC, while the other group was used to determine the contents of CO2, , and . These measurements were conducted every 24 h for 3 days. The total content of CO2, , and was calculated as the DIC content ().

Field test

It is essential to acknowledge that while NaOH served as a pH regulator in our laboratory study, its application in actual field settings requires consideration of weak alkaline agents with low corrosion and strong buffering capacity. Notably, cement has been demonstrated to effectively reduce Phosphorus content in water and regulate pH levels (Liu et al. 2020). To study the impact of pH on water quality in eutrophic systems, we investigated a eutrophic river restoration project located in Chengdu, China (Zhang et al. 2021). The river section has stone revetments built with mortar, and there is no vegetation along the banks. The water body is turbid, with a large amount of floating garbage and visible oil films on the surface. At some sewage discharge points, the water appears black-gray and emits a foul smell. In this 1.5 km long eutrophic river, a mixture of 80% ordinary Portland cement and 20% bentonite was applied at a dosage of 5 g/m3. Three monitoring sites were established in the upper, middle, and lower reaches of the 1.5 km river section, spaced approximately 0.75 km apart. The water quality was monitored monthly from December 2020 to June 2021. Key parameters monitored included pH, DO, TP, TN, ammonia nitrogen (NH3-N), and chemical oxygen demand (CODMn).

Determination methods

The determination of pH, DO, and EC was performed using a PHB-4 Portable pH Meter, a JBP-607A Portable DO Meter, and a DDS-307A Conductivity Meter, all from Shanghai Leici Instrument Factory, China. TP, dissolved phosphorus (DP), TN, NH3-N, and CODMn were determined by standard methods (APHA 2012). The CO2 content in water was determined by a fixed method of titration, with detection values of ≥0.004 mg/L and an accuracy of ±0.5 mg/L. The and contents were determined by double mixed indicator titration, with detection values of ≥0.003 mg/L and an accuracy of ±1.2% (Liu 1981).

Statistical analysis

Statistical analyses were performed using Microsoft Excel, Origin 2018, and SPSS 27.0. A multivariate analysis of variance (MANOVA) was conducted to assess the significance of differences in DIC content across different pH treatments, time points, and water types. Pearson correlation was used to analyze linear relationships between pH levels and other indexes, while Spearman correlation was employed for non-linear relationships or data sets that did not meet normality assumptions. Statistical significance was set at P < 0.05.

Effects of initial pH on the DIC content

The DIC content exhibited an exponential relationship with the initial pH (Figure 2). The initial DIC contents were 4.49 mg/L (ultrapure), 14.57 mg/L (lake), and 18.94 mg/L (river water). DIC content was measured every 24 h over 3 days. When the initial pH was ≥7.5, the DIC content in water samples exceeded the initial DIC content, except on the 1st day in ultrapure water. The water bath time significantly affected DIC content (P < 0.05). The maximum DIC contents observed after a 3-day water bath were 434.26 mg/L (ultrapure), 378.55 mg/L (lake), and 327.40 mg/L (river) at an initial pH of 12.0. At pH 7.0, the mean 3-day DIC concentrations in ultrapure, lake, and river water were 5.15 ± 1.09, 14.85 ± 0.79, and 16.93 ± 1.21 mg/L, respectively. At pH 9.0, the mean 3-day DIC concentrations in ultrapure, lake, and river increased to 7.05 ± 2.29, 21.42 ± 1.39, and 24.59 ± 2.20 mg/L, respectively, demonstrating a significant positive impact of initial pH on DIC content (P < 0.05). In an aqueous carbonate system, as pH increases, more bicarbonate is converted to carbonic acid, facilitating the entry of atmospheric CO2 into the water and increasing the DIC content (Lueker et al. 2000). Moreover, multi-factor analysis of variance revealed that the type of water samples had no significant influence on DIC content (P > 0.05).
Figure 2

The effect of initial pH on the DIC content in ultrapure, lake, and river water.

Figure 2

The effect of initial pH on the DIC content in ultrapure, lake, and river water.

Close modal

Variation in pH

At initial pH values of 8.5–10.0, substantial pH changes occurred after 1 day (Figure 3). Specifically, pH decreased by 2.14, 1.15, and 1.18 for ultrapure water (initial pH 9.5), lake water (initial pH 8.5), and river water (initial pH 8.5), respectively. The pH changes were more obvious in ultrapure water, indicating faster changes initially. According to the Environmental Quality Standard of Surface Water in China (GB 3838-2002), which specifies a pH range of 6.0–9.0, both ultrapure water (initial pH 6.0–10.0) and eutrophic water (initial pH 5.5–9.5) met the standard after 1 day. After 2 days, ultrapure water (initial pH 6.0–10.5) and eutrophic water (initial pH 5.0–10.0) met the standard. After 3 days, ultrapure water (initial pH 5.5–11.0) and eutrophic water (initial pH 5.0–11.0) met the standard. Following the adjustment of initial pH, ultrapure water tended to exhibit slightly acidic pH values (6.5–7.0), while eutrophic water tended toward slightly alkaline pH values (7.0–7.5). This observation may be attributed to differences in ion concentrations, with ultrapure water having less buffering capacity than eutrophic water.
Figure 3

Changes in pH over time for (a) ultrapure water, (b) lake water, (c) river water, and (d) difference between determined pH and initial pH (ΔpH) over 3 days.

Figure 3

Changes in pH over time for (a) ultrapure water, (b) lake water, (c) river water, and (d) difference between determined pH and initial pH (ΔpH) over 3 days.

Close modal

After 3 days, the difference between the determined pH and initial pH (ΔpH) showed comparable trends in both ultrapure and eutrophic water (Figure 3(d)). Positive ΔpH was observed when the initial pH of ultrapure water was 3.5–6.0 and eutrophic water was 3.5–7.0. Conversely, negative ΔpH occurred for ultrapure water with an initial pH value of ≥6.5 and eutrophic water with an initial pH value of ≥7.5. The maximum ΔpH values were 0.63 (ultrapure, initial pH 5.0), 1.42 (lake, initial pH 5.0), and 1.31 (river, initial pH 5.5). The minimum ΔpH values were −2.69 (ultrapure, initial pH 10.0), −2.14 (lake, initial pH 10.5), and −2.40 (river, initial pH 10.5).

Effects of initial pH on the DO content

Results showed that the initial pH had minimal influence on the DO content, with no significant changes observed with increasing pH levels (P > 0.05). Similarly, the water bath time had little impact on DO content, with variations within 0.6 mg/L over 1 day. For ultrapure water, the DO contents were 7.2–7.6 mg/L (1 day), 7.4–7.7 mg/L (2 days), and 7.6–7.8 mg/L (3 days). For lake water, the DO contents were 6.0–7.8 mg/L (1 day), 6.4–7.9 mg/L (2 days), and 6.5–8.0 mg/L (3 days). For river water, the DO contents were 6.8–7.7 mg/L (1 day), 6.8–8.0 mg/L (2 days), and 6.9–8.1 mg/L (3 days). This stability can be attributed to the absence of materials in the solutions that would consume oxygen.

Effects of initial pH on EC

In Figure 4, it was clearly observed that initial pH had a significant effect on EC (P < 0.05). The initial EC increased with the addition of H2SO4 or NaOH solutions. Before adjustment, the EC of the three water samples were 14.90 μS/cm (ultrapure), 321 μS/cm (lake), and 231 μS/cm (river). At an initial pH of 12.0, the maximum initial EC recorded was 2,670 μS/cm (ultrapure), 2,480 μS/cm (lake), and 2,020 μS/cm (river). As the water bath time increased, the EC decreased, especially when the initial pH was ≥10.5. After 3 days, the treatment groups with an initial pH value of 12.0 exhibited the most substantial decrease in EC, dropping to 1,269 μS/cm (ultrapure), 1,255 μS/cm (lake), and 1,056 μS/cm (river).
Figure 4

The effect of initial pH on EC in (a) ultrapure water, (b) lake water, and (c) river water.

Figure 4

The effect of initial pH on EC in (a) ultrapure water, (b) lake water, and (c) river water.

Close modal

Field test

Before the restoration, the river's water quality parameters were as follows: TP 0.16–9.35 mg/L, TN 10.9–27.6 mg/L, NH3-N 2.02–25.8 mg/L, and CODMn 7.3–36.0 mg/L. After the restoration, TP, TN, NH3-N, and CODMn concentrations were reduced to 0.133, 1.156, 0.076, and 5.13 mg/L, respectively, indicating a great improvement in water quality.

The results showed that pH, DO, TP, CODMn, C/N, and C/P concentrations followed a normal distribution, while TN and NH3-N did not. Therefore, Pearson correlation analysis was conducted for pH, DO, TP, CODMn, C/N, and C/P. In contrast, Spearman correlation analysis was performed for TN and NH3-N (Figure 5). Significant correlations with pH were found for DO (r = 0.80, P < 0.05), C/N (r = 0.81, P < 0.05), and TN (r = −0.57, P < 0.05). However, pH values exhibited weaker or insignificant relationships with TP, CODMn, C/P, and NH3-N concentrations (P > 0.05). This indicates that pH is positively correlated with DO, C/N, and C/P and negatively correlated with TP, COD, TN, and NH3-N concentrations.
Figure 5

Pearson (a) and Spearman (b) correlation analyses with field test data.

Figure 5

Pearson (a) and Spearman (b) correlation analyses with field test data.

Close modal

Optimal pH level for connecting eutrophic water to carbon sink

In this study, a clear exponential correlation between DIC content and pH level was observed. The DIC content exceeded the initial DIC content when the initial pH value was ≥7.5. For DIC alone, higher pH levels are preferable. Notably, when the initial pH value was ≥10.5, the EC of both lake and river water significantly exceeded the original EC before treatment. Elevated EC in aquatic ecosystems can disrupt the osmotic and ionic balance of organisms, impair critical physiological processes such as respiration and osmoregulation, and adversely affect growth and reproduction (Morgan et al. 2012). EC serves as a crucial indicator of water quality, reflecting the concentration of total dissolved solids and serving as a measure of water salinity (Canedo-Arguelles et al. 2013). Salinity can impact osmotic pressure in living cells and the normal growth of organisms (Sampaio & Bianchini 2002; Geng et al. 2016; He et al. 2017). Increased salinity has been shown to reduce species richness and abundance in aquatic plants and zooplankton communities (Nielsen et al. 2003; Bielanska-Grajner & Cudak 2014). Therefore, the EC should be controlled within a certain range. Additionally, pH levels directly affect the growth and reproduction of aquatic organisms (Barth & Wilson 2010; Kim et al. 2015). Elevated pH levels can also stress aquatic organisms, especially those with narrow pH tolerance ranges. For example, fish from the alkaline parts of a lake (pH 9.90) exhibited nearly three-fold higher plasma ammonia levels compared to fish from neutral waters, highlighting a significant disruption in ammonia excretion under such conditions (Scott et al. 2005). Phytoplankton are the most important primary producers in aquatic ecosystems (Weyhenmeyer et al. 2013; Yu et al. 2015). Studies indicated that within a pH range of 7.5–9.0, the average total phytoplankton biomass in eutrophic water increases with rising pH (Tian et al. 2016). Meanwhile, according to the Environmental Quality Standard of Surface Water in China, the acceptable pH ranges from 6.0 to 9.0 (SEPA 2002). Considering these factors, maintaining a pH value of around 9.0 for eutrophic water treatment is optimal, aligning with the suitable pH level for aquatic life and maximizing CO2 absorption into the water.

Alkaline pH facilitates eutrophication mitigation and carbon sink enhancement

Substantial input of N and P eutrophic water generally exhibits a distinct imbalance in the proportion of nutrient elements. In this study, the initial C/N ratios of the two eutrophic water samples were 0.78 (lake) and 1.25 (river), and the C/P ratios were 7.25 (lake) and 12.65 (river), indicating significant carbon deficiency compared to the Redfield Ratio of 106:16:1 (Redfield 1960). For instance, Taihu Lake in Jiangsu Province, a typical eutrophic lake in China, has water quality indices of pH 8.2, CODMn 6.61 mg/L, TN 2.25 mg/L, and TP 0.133 mg/L, with a C/ N/ P ratio of 49.7:16.9:1 (Zhang et al. 2011). In wastewater treatment, industrial glucose with approximately 99% purity is commonly utilized as a carbon source additive (Wang et al. 2014), priced at around US$280/t (Wujiang Minghao Chemical Co., China 2023). Assuming the eutrophication of Taihu Lake (total volume of 4.44 × 109 m3) could be alleviated by adding carbon sources, about 25,830 t of industrial glucose would be required to balance the deficient carbon proportion for US$7,232,400. In contrast, if NaOH (US$320/t) (Wujiang Minghao Chemical Co., China 2023) with a purity of about 98.5% were added to adjust the pH to 9.0, atmospheric CO2 would naturally enter the water, fulfilling the necessary carbon addition. This approach would only require 1,517 t of NaOH, costing US$485,440, which is approximately 6.7% of the expense associated with adding industrial glucose.

Traditional techniques require aeration and the supplementation of organic carbon sources, resulting in high treatment costs (Gu et al. 2023; Wang et al. 2025). In contrast, pH adjustment enables atmospheric CO2 to enter water bodies, promotes the growth of photosynthetic microorganisms, and strengthens the self-purification capacity of water. This approach not only eliminates the need to add carbon sources but also requires no energy consumption. Therefore, adjusting water pH to alkaline conditions is a more economical approach to increase the carbon content in water, alleviating eutrophic water pollution with lower costs and no secondary pollution.

As a powerful CO2 buffer system (Figure 6), water holds significant potential for capturing CO2 from the air, offering a promising avenue to alleviate climate change (Dai et al. 2013; Du et al. 2020). Aquatic organisms utilize CO2 through photosynthesis, converting it into oxygen and biomass (Tang et al. 2011). For example, seagrasses play an important role in C sequestration (Beer & Rehnberg 1997; Palacios & Zimmerman 2007), while microalgae can rapidly convert CO2 into valuable products such as proteins, carbohydrates, and fatty acids (Nakayama et al. 2020). In this study, pH adjustment resulted in the absorption of approximately 5.44 mg/L of atmospheric CO2 in eutrophic water samples over 3 days. Scaling this to the regional level, we took Dianchi Lake, a typical eutrophic lake in China, as an example (Wang et al. 2012; Zhou et al. 2021). With a water storage capacity of 1.57 × 109 m3, adjusting the lake's pH from 7.0 to 9.0 could lead to the absorption of approximately 8.54 × 106 kg of atmospheric CO2 within 3 days. This is equivalent to the CO2 sequestration capacity of 4,567 tons of wood over its lifetime (Pasztory et al. 2019). However, it is important to note that the majority of gas exchange between water and air typically occurs in the first few meters of the lake surface, suggesting that the calculated results might be higher than reality.
Figure 6

Schematic diagram of the carbon cycling process in eutrophic water systems, modified from Sun et al. (2019).

Figure 6

Schematic diagram of the carbon cycling process in eutrophic water systems, modified from Sun et al. (2019).

Close modal

Moreover, pH-induced CO2 absorption not only contributes to carbon sequestration but also helps mitigate eutrophication by increasing the availability of DIC for photosynthetic organisms. This increased carbon availability promotes the growth of autotrophic organisms, which can assimilate excess nitrogen and phosphorus, further alleviating eutrophication. Nevertheless, our findings suggest that regulating the pH of eutrophic water to alkalinity may potentially reduce atmospheric CO2 while concurrently alleviating eutrophic water pollution.

Limitations and future direction

The findings of this study are based on controlled laboratory experiments and limited field conditions, which may not fully represent the complexity of natural aquatic ecosystems. To improve the generalizability and robustness of our conclusions, large-scale studies encompassing broader spatial and temporal scales and diverse environmental settings should be conducted to validate these results and account for potential variability.

In this study, biological interference was eliminated to more accurately quantify dissolved CO2. Future studies should specifically consider the presence and impact of aquatic organisms when investigating the influence of water pH on atmospheric CO2 dissolution. Moreover, the applicability of this approach requires additional in-depth research and supporting data to determine whether increasing the alkalinity of eutrophic waterbodies will further damage or enhance their limnological features and ecosystems. Subsequent studies should also focus on how to capture or isolate the organic matter produced by increased DIC content to ensure atmospheric CO2 reduction. Additionally, the potential impact of excessive DIC on the water ecosystem warrants further consideration. Future research should focus on sustainable and cost-effective approaches, exploring the possibility of leveraging the power of natural ecosystems to enhance CO2 absorption and sequestration.

The nutrient imbalance in eutrophic water can be addressed by adding carbon sources to promote the growth of aquatic organisms and alleviate eutrophication. Based on our controlled laboratory and the field test, we propose the following preliminary conclusions:

  • (1) An alkaline pH effectively increases DIC content, with a significant positive correlation observed between pH levels and DIC concentrations (P < 0.05).

  • (2) Considering salinity, the carbon source, and the growth of aquatic organisms, a pH level of approximately 9.0 is optimal for eutrophic water treatment under the tested conditions.

  • (3) Adjusting pH levels to alkaline conditions facilitates the absorption of atmospheric CO2 into water. At pH 9.0, lake water and river water absorbed an additional 5.06 and 5.81 mg/L of CO2, respectively, within 3 days, compared to pH 7.0. This process provides a natural carbon source for alleviating eutrophication and contributes to the reduction of atmospheric CO2, a major greenhouse gas.

  • (4) A field test in a 1.5 km eutrophic river section confirmed positive correlations between pH and C/N (P < 0.05) and C/P (P > 0.05), indicating the potential effectiveness of alkaline pH in promoting balanced nutrient ratios.

Combining solutions to mitigate eutrophication and reduce atmospheric CO2 provides a promising strategy for addressing major environmental challenges, including climate change and ecosystem degradation. However, this study has certain limitations, such as the exclusion of biological interference and the lack of large-scale validation. Further studies are required to validate these findings in diverse water bodies and climatic conditions and to assess the ecological impacts of sustained alkaline pH levels on aquatic biodiversity and water chemistry.

We thank Prof. Yonghong Shui and her team from Chengdu Textile College for the data test and laboratory support. We also extend our thanks to Dunlian Qiu and Prof. Iain Taylor for editing assistance.

Y.Z. performed conceptualization, methodology, and formal analysis, wrote the original draft, and reviewed and edited the manuscript. B.L. carried out conceptualization and methodology and wrote the reviewed and edited manuscript. L.L. did the formal analysis and wrote the reviewed and edited manuscript. B.C.S. wrote the reviewed and edited manuscript.

This study was financially supported by the National Natural Science Foundation of China (51879174) and the Wastewater Treatment Technology Development Program (18H0364) commissioned by Sichuan Environmental Protection and Treatment Engineering Co. Ltd.

All relevant data are included in the paper or its Supplementary Information.

The authors declare there is no conflict.

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