Distribution Characteristics and Influence Factors of Carbon in Coal Mining...

[Full title: Distribution Characteristics and Influence Factors of Carbon in Coal Mining Subsidence Wetland]

Citation: Yuan, T.; Lu, P.; Liu, Y.; Ren, F.; Zhang, H. Distribution Characteristics and Influence Factors of Carbon in Coal Mining Subsidence Wetland Sustainability 2023 , 15 , 7042 https://doi.org/10.3390/su 15097042 Academic Editor: Changwoo Ahn Received: 24 February 2023 Revised: 16 April 2023 Accepted: 18 April 2023 Published: 23 April 2023 Copyright: © 2023 by the authors Licensee MDPI, Basel, Switzerland This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/) sustainability Article Distribution Characteristics and Influence Factors of Carbon in Coal Mining Subsidence Wetland Tao Yuan 1,2 , Ping Lu 3, *, Yijun Liu 3 , Feng Ren 3 and Haoran Zhang 3 1 School of Architectural Decoration, Jiangsu Vocational Institute of Architectural Technology, Xuzhou 221116, China 2 School of Mechanics and Civil Engineering, China University of Mining and Technology, Xuzhou 221116, China 3 School of Environment and Spatial Informatics, China University of Mining and Technology, Xuzhou 221116, China * Correspondence: lupingcumt@126.com; Tel.: +86-15-862-187-731 Abstract: Coal mining subsidence wetlands, as important supplementary resources for wetlands, are of great significance for regulating climate change. This study investigated the distribution and influencing factors of carbon in the overlying water and sediment of coal mining subsidence wetlands in Xuzhou, China, during low-water, high-water, and dry seasons. The results revealed significant spatial and temporal variations in the physicochemical properties of the wetlands, with water hypoxia and a trend toward eutrophication due to excess nitrogen and phosphorus. Dissolved organic carbon (WDOC) and dissolved inorganic carbon (WDIC) in water exhibited opposite temporal trends, while sediment organic carbon (SOC) and dissolved organic carbon (SDOC) showed similar temporal and spatial variations. Inorganic carbon in sediment (SIC) and dissolved inorganic carbon (SDIC) showed consistent temporal changes but significant spatial differences. There was a significant positive correlation between WDOC and SDOC, and WDIC was positively correlated with SDOC and SDIC, indicating the interconnection and transformation of dissolved carbon between water and sediment WDIC was strongly correlated with water temperature and dissolved oxygen, while WDOC was weakly correlated with the physicochemical properties of water. Overall, these findings contribute to our understanding of the carbon distribution and cycling in coal mining subsidence wetlands, which are crucial supplementary resources to natural wetlands for regulating climate change Keywords: coal mining subsidence wetland; carbon; spatiotemporal distribution; influential factors 1. Introduction In the context of carbon peaking and carbon neutrality, it is important to consider not just reducing carbon dioxide (CO 2 ) emissions but also the storage or absorption of CO 2 . Wetlands, which are unique ecosystems formed by the interaction of water and land, have most of their surface area covered by permanent water, resulting in a long-term anaerobic state. This characteristic offers significant potential for carbon storage. The low decomposition rate of microorganisms in wetlands makes them an excellent habitat for carbon storage Despite covering only 4% to 6% of the world’s land area, wetlands account for 30% of the world’s carbon storage [ 1 , 2 ]. This means that wetlands play an essential role in regulating regional climate and the carbon cycle [ 3 , 4 ], and they have significant implications for the global carbon cycle [ 5 , 6 ]. Therefore, preserving and restoring wetlands is crucial for achieving carbon neutrality and combating climate change Wetlands can be divided into three main carbon storage media: sediment, plants, and water [ 7 ]. In natural water bodies, carbon is present in four forms: dissolved organic carbon (WDOC), inorganic carbon (WDIC), granular organic carbon (WPOC), and granular inorganic carbon (WPIC). These forms of carbon can transform among each other to Sustainability 2023 , 15 , 7042. https://doi.org/10.3390/su 15097042 https://www.mdpi.com/journal/sustainability

Sustainability 2023 , 15 , 7042 2 of 13 maintain the relative balance of the total carbon pool in the water body [ 8 ]. Sedimentary carbon can be classified into organic and inorganic carbon [ 9 ]. Organic carbon in wetland sediment (SOC) consists of various organic matter containing carbon, including plants, animals, microbial remains, excreta, and part of humus [ 10 ]. Organic matter is the primary carrier of SOC. Sediment-dissolved organic carbon (SDOC) is classified as unstable organic carbon and constitutes approximately 1–2% of the total organic carbon pool [ 11 ]. Inorganic carbon, on the other hand, constitutes a substantial portion of the sediment carbon pool, and in the wetlands of karst regions, its concentration exceeds that of organic carbon [ 12 ]. Sediment inorganic carbon (SIC) primarily includes HCO 3 − , CO 2 , and CO 3 2 − in the mineral form, mostly CaCO 3 and MgCO 3 [ 13 ]. Similarly to SDOC, sediment dissolved inorganic carbon (SDIC) is also an essential component of the inorganic carbon pool, accounting for about 0.31% of the inorganic carbon pool and playing a bridging role in the mutual conversion of inorganic carbon and organic carbon [ 14 ]. In recent years, numerous studies by domestic and foreign scholars have focused on dissolved carbon in water, with factors such as temperature, dissolved oxygen (DO), pH, rainfall, nitrogen, phosphorus, and algae believed to influence carbon content in water [ 14 , 15 ]. For instance, in a study by Ning et al. [ 16 ] on offshore seawater in the East China Sea, it was found that both DOC and DIC were negatively correlated with temperature. However, DOC was weakly correlated, mainly because temperature directly controls CO 2 , which has a more direct effect on DIC in water. Vecchio et al. [ 17 ] examined the temporal and spatial distribution of dissolved organic carbon (DOC) in the coastal waters of the Atlantic Ocean and found that the DOC content showed slight seasonal variations but was strongly correlated with salinity, with the trend of DOC variation being opposite to that of salinity. Jinliu et al. [ 18 ] performed dynamic monitoring of water dissolved organic carbon (DOC) concentration in Chaohu Lake for one year and discovered that the concentration was highest in summer and lowest in winter. Yunxiao et al. [ 19 ] conducted a monitoring study of dissolved inorganic carbon (DIC) concentration in the main stream of the Fenhe River along the river. They found that the primary source of DIC was rock weathering at the source, and it was discharged downstream by urban sewage Moreover, they observed that dissolved organic carbon (DOC) was decomposed into DIC through biological processes, leading to a high concentration of DIC. In addition, a study on the sediment carbon pool investigated the distribution of organic carbon in the wetland of Chongming Island, located in the Yangtze Estuary. The results showed a significant decrease in organic carbon content from the middle to the periphery of the wetland [ 20 ]. Dong et al. [ 21 ] studied three different wetland types in Yili Valley and observed that the changes in organic carbon content were consistent across these wetland types. They found that soil enzymes and oxygen content had a significant impact on organic carbon Yuanshan et al. [ 22 ] investigated the inorganic carbon content of saline-alkali marshes and discovered that reclamation could significantly increase the capacity of the inorganic carbon pool. Xueni et al. [ 23 ] conducted a study of the Aibi Lake wetland and found that soil inorganic carbon was positively correlated with water content and negatively correlated with soil surface pH. Meanwhile, Wenjie [ 24 ] examined the sediments of Hulun Lake and discovered that the lake’s topography had a significant influence on inorganic carbon. Additionally, they observed that organic matter was predominantly imported from internal sources. Pan et al. [ 25 ] demonstrated that the surface soil soluble organic carbon (SDOC) was significantly impacted by REDOX potential, whereas the deep soil was primarily influenced by pH. Furthermore, Ye et al. [ 26 ] investigated the active organic carbon components in the Sanjiang Plain wetland and observed a negative correlation between the content and distribution ratio of soil organic carbon and the frequency of flooding. Finally, Yi et al. [ 27 ] investigated the variation pattern of soluble organic carbon (SDOC) in an alpine wetland by simulating alternating dry and wet conditions. They found that intermittent, low-intensity dry and wet cycles were more favorable for SDOC accumulation. Another study conducted by Haixiao et al. [ 28 ] found that the content of SDOC in the Yellow River Delta wetland was highest in winter and lowest in autumn,

Sustainability 2023 , 15 , 7042 3 of 13 indicating significant spatio-temporal differences. While research on soluble inorganic carbon (SDIC) is limited, some notable studies have been conducted. For instance, Acour et al. [ 29 ] investigated SDIC in Mediterranean river sediments, while Wick et al. [ 30 ] highlighted that SDIC is generated when CO 2 dissolved in water infiltrates soil and creates subsurface carbon reservoirs in groundwater. Yan et al. [ 31 ] employed isotope tracer techniques and demonstrated that SDIC mainly originated from CO 2 in soil. Additionally, Xiaotong et al. [ 32 ] discovered a positive correlation between SDIC and salt content and a negative correlation between SDIC and pH in the Jiaozhou Bay wetland. Most research on carbon storage is centered on natural wetlands, such as coastal wetlands [ 33 ], lake wetlands [ 34 ], and alpine wetlands [ 35 ]. However, wetlands that form from coal mining collapses are crucial supplementary resources to natural wetlands, although their ecological structure and formation processes are distinct. Environmental changes can reduce the carbon storage capacity of these wetlands, causing them to shift from a “sink” to a “source,” thereby affecting the regional carbon cycle This paper investigates the sediments and water bodies of the Jiuli Lake wetland, which collapsed due to coal mining in Xuzhou, China. It examines the occurrence characteristics of carbon in these sediments and water bodies, as well as the key factors that affect carbon content. This study is significant because it provides insights into the ecosystem of a collapsed coal mining wetland, particularly the potential for carbon sequestration in an ecosystem marked by significant fluctuations in groundwater levels 2. Materials and Methods 2.1. Overview of the Study Area The research area is situated in the Jiuli Lake National Wetland Park in Xuzhou City, Jiangsu Province, China. The mines are located in a high phreatic water-level region that boasts abundant groundwater resources and a temperate monsoon climate [ 36 ]. Winds are predominantly from the east to the south, and the wind speed can reach up to 17 m/s throughout the year. The sunshine time in this area is between 2284 and 2495 h annually, and the average temperature is about 14 ◦ C. The highest temperature in summer could be more than 40 ◦ C, while the lowest temperature in winter is around − 10 ◦ C, leading to ice formation on the water’s surface [ 37 ]. The frost-free period lasts between 200 and 220 days, making it suitable for crop growth. The study area receives an average annual rainfall of 800 to 930 mm, but its distribution is highly uneven. Summer rains can account for 60% to 80% of the entire year’s rainfall, whereas winter rains make up only 3% to 7%. This variation in rainfall has significant implications on the water level and quantity, ultimately affecting the ecological environment of the lake body [ 38 ]. 2.2. Sample Collection and Analysis Based on the water system of Jiuli Lake wetland and the level of human disturbance, the east lake of Jiuli Lake was selected as the sampling area. Seven fixed sampling points were set in accordance with the characteristics of the lake area (refer to Figure 1 ). Sampling was carried out in April 2021 (the normal season), August 2021 (the wet season), and December 2021 (the dry season). A portable 2.5-liter plexiglass water collector was used to collect the overlying water (0.5 m above the surface), while the surface sediment (approximately 20 cm) was collected using a Peterson sediment sampler. All samples were collected on the same day and transported to the laboratory for analysis Physical and chemical parameters of water, including temperature, pH, dissolved oxygen, REDOX potential, and electrical conductivity, were measured on-site using a HACH portable water quality parameter instrument. TN and TP in the water samples were measured using relevant methods in the Monitoring and Analysis Methods of Water and Wastewater (Fourth Edition) [ 39 ]. WDOC and WDIC were filtered using a 0.45 µ m glass fiber filtration membrane (burned at 450 ◦ C for 6 h) and analyzed using a total organic carbon/nitrogen analyzer [ 40 ]. The sediment moisture content was determined using the gravimetric method [ 41 ], and the sediment pH and electrical conductivity (EC) were

Sustainability 2023 , 15 , 7042 4 of 13 measured using the extraction method. TN and TP contents in sediments were determined according to the “Regulation for Eutrophication Control of Lakes (2 nd edition)” [ 42 ]. The total sediment carbon (STC) was determined using an elemental analyzer, and SOC was determined by concentrated sulfuric acid-potassium dichromate oxidation water and the thermal method. SIC was calculated by subtracting STC and SOC [ 43 ]. Sustainability 2023 , 15 , x FOR PEER REVIEW 4 of 13 were measured using relevant methods in the Monitoring and Analysis Methods of Water and Wastewater (Fourth Edition) [39]. WDOC and WDIC were fi ltered using a 0.45 µm glass fi ber fi ltration membrane (burned at 450 °C for 6 h) and analyzed using a total organic carbon/nitrogen analyzer [40]. The sediment moisture content was determined using the gravimetric method [41], and the sediment pH and electrical conductivity (EC) were measured using the extraction method. TN and TP contents in sediments were determined according to the “Regulation for Eutrophication Control of Lakes (2 nd edition)” [42]. The total sediment carbon (STC) was determined using an elemental analyzer, and SOC was determined by concentrated sulfuric acid-potassium dichromate oxidation water and the thermal method. SIC was calculated by subtracting STC and SOC [43]. Figure 1. Schematic diagram of the sampling points and the study area. 2.3. Data Processing Experimental data were input into Microsoft Excel 2019 for integration. Correlation analysis was performed using SPSS ver.21, and ArcGIS (ver-10.7) was used for designing sampling points and creating spatial distribution maps. 3. Results and Discussion 3.1. Main Physicochemical Indexes of Water and Sediment As shown in Table 1. Overall, the study found that water temperature was highest in August and lowest in December, with a relatively concentrated distribution in each period. This variation in lake water temperature is closely related to seasonal changes, with higher temperatures in summer and lower temperatures in winter. These results are consistent with previous studies. Additionally, pH values of the bodies of water were weakly alkaline, ranging from 6 to 9, with the highest values in December, followed by April and August. Conversely, dissolved oxygen (DO) showed a pa tt ern opposite that of temperature, with the highest values in December, followed by April and August. The study also Figure 1. Schematic diagram of the sampling points and the study area 2.3. Data Processing Experimental data were input into Microsoft Excel 2019 for integration. Correlation analysis was performed using SPSS ver.21, and ArcGIS (ver-10.7) was used for designing sampling points and creating spatial distribution maps 3. Results and Discussion 3.1. Main Physicochemical Indexes of Water and Sediment As shown in Table 1 . Overall, the study found that water temperature was highest in August and lowest in December, with a relatively concentrated distribution in each period. This variation in lake water temperature is closely related to seasonal changes, with higher temperatures in summer and lower temperatures in winter. These results are consistent with previous studies. Additionally, pH values of the bodies of water were weakly alkaline, ranging from 6 to 9, with the highest values in December, followed by April and August. Conversely, dissolved oxygen (DO) showed a pattern opposite that of temperature, with the highest values in December, followed by April and August. The study also found that total nitrogen (TN) concentrations decreased gradually over time, with the highest values in April, followed by August and December. The seasonal variation in total phosphorus (TP) concentrations was slightly different from that of TN, with the highest values in April, followed by December and August, but the overall difference between August and December was not significant.

Sustainability 2023 , 15 , 7042 5 of 13 Table 1. Main physical and chemical properties of overlying water and sediment Time Temperature pH DO TN TP Water on top April 22.29 ± 0.41 8.35 ± 0.63 9.0 ± 0.34 2.70 ± 0.19 0.1 ± 0.02 August 28.94 ± 1.31 8.15 ± 0.67 9.03 ± 0.47 1.24 ± 0.17 0.07 ± 0.02 December 5.21 ± 0.21 8.92 ± 0.08 7.77 ± 1.66 1.14 ± 0.23 0.08 ± 0.01 Time pH EC Content of Water TN TP Deposit of sediment April 7.88 ± 0.08 876.00 ± 211.35 44.27 ± 12.76 1.27 ± 0.59 719.80 ± 118.84 August 7.73 ± 0.05 989.57 ± 183.24 44.37 ± 9.97 1.36 ± 0.58 754.14 ± 94.96 December 7.94 ± 0.12 729.43 ± 371.83 42.45 ± 10.33 1.29 ± 0.56 674.84 ± 31.92 Figure 2 illustrates the temporal variations of the physicochemical properties of sediments in East Lake of Jiuli during the study period. Sediment pH demonstrated a small variation range in each period, with the highest values observed in December, followed by April and August. The conductivity showed a pattern of August > April > December, with fluctuations observed among sampling points. The average sediment moisture content was over 40%, and there was a significant difference in the moisture content among sampling points, with fluctuations observed in April and December. The moisture content was highest in August, followed by April and December, indicating that the sediment moisture content was influenced by seasonal changes. This is likely due to abundant rainfall and a high water table during the summer and lower levels during the winter. The TN content in sediments varied with August > December > April, indicating higher TN content in summer and lower TN content in spring. The overall variation of TP content was relatively low and differed slightly from TN in terms of time variation, with the highest values observed in August, followed by April and December. The content of TP was higher in the summer and lower in the winter Sustainability 2023 , 15 , x FOR PEER REVIEW 5 of 13 found that total nitrogen (TN) concentrations decreased gradually over time, with the highest values in April, followed by August and December. The seasonal variation in total phosphorus (TP) concentrations was slightly di ff erent from that of TN, with the highest values in April, followed by December and August, but the overall di ff erence between August and December was not signi fi cant. Figure 2 illustrates the temporal variations of the physicochemical properties of sediments in East Lake of Jiuli during the study period. Sediment pH demonstrated a small variation range in each period, with the highest values observed in December, followed by April and August. The conductivity showed a pa tt ern of August > April > December, with fl uctuations observed among sampling points. The average sediment moisture content was over 40%, and there was a signi fi cant di ff erence in the moisture content among sampling points, with fl uctuations observed in April and December. The moisture content was highest in August, followed by April and December, indicating that the sediment moisture content was in fl uenced by seasonal changes. This is likely due to abundant rainfall and a high water table during the summer and lower levels during the winter. The TN content in sediments varied with August > December > April, indicating higher TN content in summer and lower TN content in spring. The overall variation of TP content was relatively low and di ff ered slightly from TN in terms of time variation, with the highest values observed in August, followed by April and December. The content of TP was higher in the summer and lower in the winter. Table 1. Main physical and chemical properties of overlying water and sediment. Time Temperature pH DO TN TP Water on top April 22.29 ± 0.41 8.35 ± 0.63 9.0 ± 0.34 2.70 ± 0.19 0.1 ± 0.02 August 28.94 ± 1.31 8.15 ± 0.67 9.03 ± 0.47 1.24 ± 0.17 0.07 ± 0.02 December 5.21 ± 0.21 8.92 ± 0.08 7.77 ± 1.66 1.14 ± 0.23 0.08 ± 0.01 Time pH EC Content of Water TN TP Deposit of sediment April 7.88 ± 0.08 876.00 ± 211.35 44.27 ± 12.76 1.27 ± 0.59 719.80 ± 118.84 August 7.73 ± 0.05 989.57 ± 183.24 44.37 ± 9.97 1.36 ± 0.58 754.14 ± 94.96 December 7.94 ± 0.12 729.43 ± 371.83 42.45 ± 10.33 1.29 ± 0.56 674.84 ± 31.92 Figure 2. Comparison of the main physicochemical properties of sediments.

Sustainability 2023 , 15 , 7042 6 of 13 3.2. Seasonal Variation Characteristics of Carbon Spatial Distribution in Overlying Water Figure 3 shows the distribution of dissolved organic carbon and dissolved inorganic carbon in the overlying water, which is analyzed in detail in this section. The concentration of WDOC in the water of East Lake Jiuli varies spatially and seasonally. Phytoplankton and hydraulic action are important factors affecting the distribution of WDOC [ 44 , 45 ]. In spring, with the rising temperature, the phytoplankton in the northwest part of the lake become more active and multiply rapidly, leading to a high WDOC concentration in the water. In summer, the prevailing northwest wind carries WDOC to accumulate in the southeast area of the lake, where the narrow terrain facilitates its enrichment. In winter, the concentration of WDOC is the lowest in the lake center due to the absence of phytoplankton Sustainability 2023 , 15 , x FOR PEER REVIEW 6 of 13 Figure 2. Comparison of the main physicochemical properties of sediments. 3.2. Seasonal Variation Characteristics of Carbon Spatial Distribution in Overlying Water Figure 3 shows the distribution of dissolved organic carbon and dissolved inorganic carbon in the overlying water, which is analyzed in detail in this section. The concentration of WDOC in the water of East Lake Jiuli varies spatially and seasonally. Phytoplankton and hydraulic action are important factors a ff ecting the distribution of WDOC [44,45]. In spring, with the rising temperature, the phytoplankton in the northwest part of the lake become more active and multiply rapidly, leading to a high WDOC concentration in the water. In summer, the prevailing northwest wind carries WDOC to accumulate in the southeast area of the lake, where the narrow terrain facilitates its enrichment. In winter, the concentration of WDOC is the lowest in the lake center due to the absence of phytoplankton. The concentration of WDIC is also a ff ected by various factors. In spring, the higher concentration of WDIC in the north may be due to the dissolution of carbonate ore and the higher content of inorganic carbon [46]. In summer, the concentration of WDIC is higher around the lake than in the central area, but overall it is lower than in spring. This is because the higher temperature in summer leads to a decrease in the partial pressure of carbon dioxide in the water, resulting in a decrease in the concentration of carbonate ions. Moreover, the rapid propagation of algae consumes inorganic carbon through photosynthesis, leading to a decrease in the concentration of inorganic carbon [47]. In winter, the lowest temperature leads to a rapid accumulation of inorganic carbon in the water, resulting in the highest concentration of WDIC in the year. The concentration of WDTC is jointly controlled by WDOC and WDIC and re fl ects the relative size of total carbon storage in water. In spring and summer, the distribution of WDTC concentrations is highly similar to that of WDIC. In winter, the concentration distribution of WDTC and WDOC is also similar. This indicates that the concentration of WDTC is mainly controlled by the concentration of WDIC, which determines the amount of carbon stored in the water of the collapsed wetland and a ff ects the characteristics of the “source sink” of carbon in the water of the wetland. Sustainability 2023 , 15 , x FOR PEER REVIEW 7 of 13 Figure 3. Distribution of dissolved organic carbon and dissolved inorganic carbon in overlying water. 3.3. Temporal Variation of Sediment Carbon The concentration of di ff erent forms of carbon in sediments exhibits seasonal variation. During the study period, the concentration of SOC ranged from 6.17 to 19.27 g·kg − 1 , with a mean value of 13.25 g·kg − 1 , and the order of seasonal variation was December > April > August. The SDOC content ranged from 116.11 to 302.59 mg·kg − 1 , with a mean value of 206.93 mg·kg − 1 , and the order of seasonal variation was December > April > August. SDOC is an active organic carbon form that varies similarly to sediment organic carbon, indicating their close relationship. The SIC content ranged from 0.86 to 27.61 g·kg − 1 , with a mean value of 111.44 g·kg − 1 , and the order of seasonal variation was August > December > April, which is roughly opposite to the seasonal variation of SOC. This indicates that there is mutual conversion between organic and inorganic carbon in sediments. In summer, high temperatures lead to the transformation of organic carbon into inorganic carbon by microorganisms, which is then released into the water source through interstitial water [48]. The content of SDIC ranged from 66.51 to 116.86 mg·kg − 1 , with an average of 80.03 mg·kg − 1 . The di ff erence among sampling points was greater in summer than in spring and winter, and the seasonal variation pa tt ern was August > December > April, which is similar to the change trend of the SIC, indicating a high correlation between them. The STC content ranged from 16.67 to 37.64 g·kg − 1 , with an average value of 24.58 g·kg − 1 . STC content fl uctuated greatly in spring and summer, with signi fi cant di ff erences among sampling points, while the fl uctuation was relatively small in winter, with small di ff erences among sampling points. From the perspective of time change, the general performance was December > August > April. 3.4. Spatial Distribution Characteristics of Sediment Carbon Figure 4 shows the spatial distribution of organic carbon, dissolved organic carbon, inorganic carbon, and dissolved inorganic carbon in the sediment, which will be analyzed accordingly. During the study period, the spatial distribution of sediment organic carbon varied signi fi cantly. In spring and winter, the southeast region had higher SOC content compared to the northwest region, while in summer, the northwest region had higher SOC content than the southeast region, indicating signi fi cant spatial heterogeneity. The spatial variation trends of SDOC and SOC showed similar but distinct characteristics. Generally, the east coast of the lake had higher SDOC and SOC content than the west coast in spring and summer, while the southwest region had higher SDOC and SOC content in winter. The spatial distribution of SIC content was higher in the southeast than in the northwest in spring and summer and higher on the east coast of the lake than on the west coast in winter. The composition of SIC is mainly determined by HCO 32 − , CO 2 , and carbonates (mainly CaCO 3 and MgCO 3 ). The high temperature in spring and summer, strong microbial activity in the sediments, poor water circulation in the southeast of the lake, and Figure 3. Distribution of dissolved organic carbon and dissolved inorganic carbon in overlying water.

Sustainability 2023 , 15 , 7042 7 of 13 The concentration of WDIC is also affected by various factors. In spring, the higher concentration of WDIC in the north may be due to the dissolution of carbonate ore and the higher content of inorganic carbon [ 46 ]. In summer, the concentration of WDIC is higher around the lake than in the central area, but overall it is lower than in spring. This is because the higher temperature in summer leads to a decrease in the partial pressure of carbon dioxide in the water, resulting in a decrease in the concentration of carbonate ions. Moreover, the rapid propagation of algae consumes inorganic carbon through photosynthesis, leading to a decrease in the concentration of inorganic carbon [ 47 ]. In winter, the lowest temperature leads to a rapid accumulation of inorganic carbon in the water, resulting in the highest concentration of WDIC in the year The concentration of WDTC is jointly controlled by WDOC and WDIC and reflects the relative size of total carbon storage in water. In spring and summer, the distribution of WDTC concentrations is highly similar to that of WDIC. In winter, the concentration distribution of WDTC and WDOC is also similar. This indicates that the concentration of WDTC is mainly controlled by the concentration of WDIC, which determines the amount of carbon stored in the water of the collapsed wetland and affects the characteristics of the “source sink” of carbon in the water of the wetland 3.3. Temporal Variation of Sediment Carbon The concentration of different forms of carbon in sediments exhibits seasonal variation During the study period, the concentration of SOC ranged from 6.17 to 19.27 g · kg − 1 , with a mean value of 13.25 g · kg − 1 , and the order of seasonal variation was December > April > August The SDOC content ranged from 116.11 to 302.59 mg · kg − 1 , with a mean value of 206.93 mg · kg − 1 , and the order of seasonal variation was December > April > August. SDOC is an active organic carbon form that varies similarly to sediment organic carbon, indicating their close relationship The SIC content ranged from 0.86 to 27.61 g · kg − 1 , with a mean value of 111.44 g · kg − 1 , and the order of seasonal variation was August > December > April, which is roughly opposite to the seasonal variation of SOC. This indicates that there is mutual conversion between organic and inorganic carbon in sediments. In summer, high temperatures lead to the transformation of organic carbon into inorganic carbon by microorganisms, which is then released into the water source through interstitial water [ 48 ]. The content of SDIC ranged from 66.51 to 116.86 mg · kg − 1 , with an average of 80.03 mg · kg − 1 . The difference among sampling points was greater in summer than in spring and winter, and the seasonal variation pattern was August > December > April, which is similar to the change trend of the SIC, indicating a high correlation between them. The STC content ranged from 16.67 to 37.64 g · kg − 1 , with an average value of 24.58 g · kg − 1 . STC content fluctuated greatly in spring and summer, with significant differences among sampling points, while the fluctuation was relatively small in winter, with small differences among sampling points. From the perspective of time change, the general performance was December > August > April 3.4. Spatial Distribution Characteristics of Sediment Carbon Figure 4 shows the spatial distribution of organic carbon, dissolved organic carbon, inorganic carbon, and dissolved inorganic carbon in the sediment, which will be analyzed accordingly. During the study period, the spatial distribution of sediment organic carbon varied significantly. In spring and winter, the southeast region had higher SOC content compared to the northwest region, while in summer, the northwest region had higher SOC content than the southeast region, indicating significant spatial heterogeneity. The spatial variation trends of SDOC and SOC showed similar but distinct characteristics. Generally, the east coast of the lake had higher SDOC and SOC content than the west coast in spring and summer, while the southwest region had higher SDOC and SOC content in winter. The spatial distribution of SIC content was higher in the southeast than in the northwest in spring and summer and higher on the east coast of the lake than on the west coast in winter. The composition of SIC is mainly determined by HCO 3 2 − , CO 2 , and carbonates (mainly CaCO 3 and MgCO 3 ). The high temperature in spring and summer,

Sustainability 2023 , 15 , 7042 8 of 13 strong microbial activity in the sediments, poor water circulation in the southeast of the lake, and low DO content in the water led to the dominance of anaerobic communities in the sediments. As a result, organic carbon was transformed into inorganic carbon, leading to an increase in the inorganic carbon content of the sediments and overlying water. In winter, the low temperature led to an increase in the solubility of carbonate, causing the CaCO 3 in the overlying water to settle into the sediment and resulting in an increase in the content of inorganic carbon in the sediment. The distribution of SDIC content in the three periods was highly similar, with higher content in the northwest region and lower content in the southeast region. Compared with the distribution of SIC content, there was an opposite trend between them, indicating mutual conversion between inorganic carbon and dissolved inorganic carbon in sediments. This may be due to the fact that SDIC is mainly present in sediment interstitial water and is composed of water-soluble CO 2 and decomposition products of carbonate minerals. In the northwest part of the lake, there were more aquatic plants and stronger biological effects, and the inorganic carbon in the sediments transferred into the interstitial water, resulting in a higher SDIC content. STC is an important index for measuring the sediment carbon pool, reflecting the variation law of the total capacity of organic and inorganic carbon pools in sediments. The total carbon content of sediments in the southeast corner of the lake area was highest in spring and summer and gradually shifted southward over time. Comparing the distribution map of SIC content, the similarity between the two was high, indicating that the carbon in the sediments was mainly in inorganic form, making the background value of the carbon pool in this region higher than that in other regions of the lake pool. The water mobility in the southeast region was the lowest, the accumulation rate of organic carbon was greater than its decomposition rate, and the accumulation of organic carbon increased, further increasing the total carbon content in the sediments Sustainability 2023 , 15 , x FOR PEER REVIEW 8 of 13 low DO content in the water led to the dominance of anaerobic communities in the sediments. As a result, organic carbon was transformed into inorganic carbon, leading to an increase in the inorganic carbon content of the sediments and overlying water. In winter, the low temperature led to an increase in the solubility of carbonate, causing the CaCO 3 in the overlying water to se tt le into the sediment and resulting in an increase in the content of inorganic carbon in the sediment. The distribution of SDIC content in the three periods was highly similar, with higher content in the northwest region and lower content in the southeast region. Compared with the distribution of SIC content, there was an opposite trend between them, indicating mutual conversion between inorganic carbon and dissolved inorganic carbon in sediments. This may be due to the fact that SDIC is mainly present in sediment interstitial water and is composed of water-soluble CO 2 and decomposition products of carbonate minerals. In the northwest part of the lake, there were more aquatic plants and stronger biological e ff ects, and the inorganic carbon in the sediments transferred into the interstitial water, resulting in a higher SDIC content. STC is an important index for measuring the sediment carbon pool, re fl ecting the variation law of the total capacity of organic and inorganic carbon pools in sediments. The total carbon content of sediments in the southeast corner of the lake area was highest in spring and summer and gradually shifted southward over time. Comparing the distribution map of SIC content, the similarity between the two was high, indicating that the carbon in the sediments was mainly in inorganic form, making the background value of the carbon pool in this region higher than that in other regions of the lake pool. The water mobility in the southeast region was the lowest, the accumulation rate of organic carbon was greater than its decomposition rate, and the accumulation of organic carbon increased, further increasing the total carbon content in the sediments. Figure 4. Cont .

Sustainability 2023 , 15 , 7042 9 of 13 Sustainability 2023 , 15 , x FOR PEER REVIEW 9 of 13 Figure 4. Distribution of sediment organic carbon, sediment dissolved organic carbon, sediment inorganic carbon, and sediment dissolved inorganic carbon. 3.5. In fl uencing Factors of Dissolved Carbon in Water In order to investigate the relationship between dissolved carbon content in water and the physicochemical properties of water, sediment properties, and the di ff erent forms of carbon in sediments, a Pearson correlation analysis was conducted. To di ff erentiate between the parameters, pH, conductivity, total nitrogen, and total phosphorus of the overlying water were expressed as pH-W, EC-W, TN-W, and TP-W, respectively, while the corresponding sediment pH, conductivity, total nitrogen, and total phosphorus were expressed as pH-S, EC-S, TN-S, and TP-S. As shown in Table 2, the analysis showed that WDOC and WDIC had an extremely signi fi cant negative correlation with TN-W ( p < 0.01), which may be due to poor water fl ow resulting in a local anaerobic environment, leading to strong denitri fi cation [49]. There was a signi fi cant positive correlation between WDIC and WDTC ( p < 0.05), indicating that WDIC was the main form of WDTC. Moreover, WDIC showed a signi fi cant negative correlation with temperature ( p < 0.05), a signi fi cant positive correlation with EC-W ( p < 0.01), a signi fi cant positive correlation with DO ( p < 0.05), and a signi fi cant negative correlation with TP-W ( p < 0.01). This could be explained by the fact that East Lake of Jiuli Lake is an algal lake, and high concentrations of WDIC lead to strong algae photosynthesis, which releases oxygen into the water and absorbs phosphorus, resulting in an increase in DO content and a decrease in TP-W content [50]. Figure 4. Distribution of sediment organic carbon, sediment dissolved organic carbon, sediment inorganic carbon, and sediment dissolved inorganic carbon 3.5. Influencing Factors of Dissolved Carbon in Water In order to investigate the relationship between dissolved carbon content in water and the physicochemical properties of water, sediment properties, and the different forms of carbon in sediments, a Pearson correlation analysis was conducted. To differentiate between the parameters, pH, conductivity, total nitrogen, and total phosphorus of the overlying water were expressed as pH-W, EC-W, TN-W, and TP-W, respectively, while the corresponding sediment pH, conductivity, total nitrogen, and total phosphorus were expressed as pH-S, EC-S, TN-S, and TP-S As shown in Table 2 , the analysis showed that WDOC and WDIC had an extremely significant negative correlation with TN-W ( p < 0.01), which may be due to poor water flow resulting in a local anaerobic environment, leading to strong denitrification [ 49 ]. There was a significant positive correlation between WDIC and WDTC ( p < 0.05), indicating that WDIC was the main form of WDTC. Moreover, WDIC showed a significant negative correlation with temperature ( p < 0.05), a significant positive correlation with EC-W ( p < 0.01), a significant positive correlation with DO ( p < 0.05), and a significant negative correlation with TP-W ( p < 0.01). This could be explained by the fact that East Lake of Jiuli Lake is an algal lake, and high concentrations of WDIC lead to strong algae photosynthesis, which releases oxygen into the water and absorbs phosphorus, resulting in an increase in DO content and a decrease in TP-W content [ 50 ].

Sustainability 2023 , 15 , 7042 10 of 13 Table 2. Correlation coefficient between soluble carbon in overlying water and physicochemical properties of water and sediment carbon Project T pH-W DO TN-W TP-W WDOC WDIC WDTC WDOC 0.384 0.077 0.194 0.766 ** 0.082 1.00 / / WDIC 0.513 * 0.254 0.497 * 0.38 0.455 ** 0.465 ** 1.00 / WDTC 0.698 * 0.308 0.487 * 0.165 0.478 * 0.18 0.955 ** 1.00 Project STC SOC SIC SDOC SDIC Content of Water pH-S EC-S TN-S TP-S WDOC 0.095 0.089 0.006 0.725 * 0.282 0.096 0.418 0.137 0.106 0.242 WDIC 0.168 0.345 0.194 0.476 * 0.585 ** 0.008 0.469 * 0.204 0.01 0.118 WDTC 0.154 0.354 0.217 0.598 ** 0.555 ** 0.042 0.661 * 0.273 0.046 0.29 “*” indicates significant correlation ( p < 0.05), and “**” indicates highly significant correlation ( p < 0.01) WDOC and SDOC showed a positive correlation ( p < 0.05), and there was a significant positive correlation between WDIC and SDOC ( p < 0.05), as well as an extremely significant positive correlation between WDIC and SDIC ( p < 0.01). This indicates that both SDOC and SDIC had an important influence on WDIC. When the organic matter content in sediments was high, dissolved organic carbon was released into the overlying water through diffusion under the influence of a concentration gradient. Additionally, the mineralization of organic matter produced more inorganic carbon, which was also released into the overlying water through the sediment-water boundary, leading to an increase in WDIC and WDOC contents 3.6. Analysis of Influencing Factors of Carbon Forms in Sediments As shown in Table 3 , STC showed a significant positive correlation with SOC, EC- S, TP-S, and SIC ( p < 0.05) and an extremely significant positive correlation with TN-S ( p < 0.05), indicating that total nitrogen content was more susceptible to the influence of total sediment carbon. There was a significant negative correlation between SOC and SIC ( p < 0.05) and a highly significant negative correlation between SOC and SDIC ( p < 0.01), suggesting that SDOC and SIC underwent mutual transformation, with the transformation to SDIC being more intense. There were significant positive correlations between SIC and SDIC, TP-S ( p < 0.05). The extremely significant positive correlation between SDOC and pH-S ( p < 0.01) indicated that pH-S had a promoting effect on SDOC. Relevant studies have shown that under alkaline conditions, protein is more easily dissolved in soil, resulting in an increase in organic matter content [ 51 ]. In general, the correlation between the carbon forms of sediments and the physical and chemical factors of the overlying water is weak The weak correlation between STC and SOC and the physical and chemical factors of the overlying water indicated that the total carbon and organic carbon in sediments were limited by the overlying water environment. There was a significant negative correlation between STIC and DO ( p < 0.01) and a significant negative correlation between SDOC and T ( p < 0.01), indicating that STIC and SDOC were lost in high oxygen and high temperature environments. There was also a significant negative correlation between SDIC and EC-W ( p < 0.01), indicating that SDIC was more easily released into the overlying water Table 3. Correlation coefficients between carbon forms in sediments and physicochemical properties of water bodies Project Content of Water pH-S EC-S TN-S TP-S STC SOC SIC SDOC SDIC STC − 0.095 0.063 0.436 * 0.733 ** 0.483 * 1.00 SOC 0.34 0.146 0.355 0.482 * 0.641 * 0.581 * 1.00 SIC 0.267 0.09 0.089 0.275 0.458 * 0.459 * 0.457 * 1.00 SDOC 0.039 0.611 ** 0.179 0.212 0.521 * 0.022 0.096 0.287 1.00 SDIC 0.182 0.275 0.169 0.103 0.045 0.451 * 0.490 * 0.49 0.287 1.00 Project T pH DO EC-W ORP TN-W TP-W STC 0.265 0.268 0.377 0.158 0.036 0.239 0.127

Sustainability 2023 , 15 , 7042 11 of 13 Table 3. Cont Project Content of Water pH-S EC-S TN-S TP-S STC SOC SIC SDOC SDIC SOC 0.316 0.323 0.214 0.413 0.041 0.126 0.294 SIC 0.055 0.059 0.645 ** 0.278 0.084 0.124 0.460 * SDOC 0.561 ** 0.028 0.348 0.563 ** 0.168 0.151 0.198 SDIC 0.386 0.171 0.106 0.539 ** 0.221 0.08 0.001 “*” indicates significant correlation ( p < 0.05), and “**” indicates highly significant correlation ( p < 0.01) 4. Conclusions (1) At different timescales, the physical and chemical parameters of Jiuli Lake’s overlying water showed fluctuations and significant differences in water quality. The sediment moisture content was high and had distinct seasonal variations; (2) The temporal variation of WDOC and WDIC showed opposite trends. WDTC is the sum of WDOC and WDIC, is jointly controlled by both, and is the main dissolved carbon in the water. The spatial distribution of WDOC and WDIC in the overlying water changes significantly with the seasons due to the influence of phytoplankton and hydraulic action in the lake area. The temporal variation of SOC and SDOC was similar, with higher concentrations in December, followed by April and August. Their spatial distribution was greatly affected by algae growth activities. SIC and SDIC exhibited consistent temporal variations, with higher concentrations in August and lower concentrations in December. The concentrations of SIC and SDIC complemented each other in their spatial distribution; (3) WDOC was strongly correlated with TN content. WDIC and WDTC had close correlations with other factors. WDIC was more susceptible to environmental factors. WDIC was positively correlated with SDOC and SDIC, indicating that dissolved carbon in the overlying water and sediment was interrelated and transformed. The correlation between carbon forms in sediments and the physical and chemical factors of overlying water was weak, and the effect of the physical and chemical factors of overlying water was limited Author Contributions: T.Y. designed the work concept, Y.L. drafted a thesis, F.R. and H.Z. collected data, and P.L. made important revisions to the paper. All authors have read and agreed to the published version of the manuscript Institutional Review Board Statement: Not applicable Informed Consent Statement: Not applicable Data Availability Statement: Not applicable Conflicts of Interest: The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results References 1 Liu, S.G.; Bliss, N.; Sundquist, E.; Huntington, T.G. Modeling carbon dynamics in vegetation and soil under the impact of soil erosion and deposition Glob. Biogeochem. Cycles 2017 , 17 , 187–194. [ CrossRef ] 2 Bernal, B.; Mitsch, W.J. Comparing carbon sequestration in temperate freshwater wetland communities Glob. Chang. Biol 2012 , 18 , 1636–1647. [ CrossRef ] 3 Peng, S.; Ren, H.; Zhang, Q. Theories and techniques of degraded wetland ecosystem restoration Chin. J. Appl. Ecol 2003 , 14 , 2026–2030. (In Chinese) 4 Bianchi, T.S.; Wysocki, L.A.; Stewart, M.; Filley, T.R.; McKee, B.A. Temporal variability in terrestrially-derived sources of particulate organic carbon in the lower Mississippi River and its upper tributaries Geochim. Cosmochim. Acta 2007 , 71 , 4425–4437 [ CrossRef ] 5 Qian, X.; Mao, S.; Jiang, Y.; Ye, C.; Lu, B.; Shan, N.; Yan, Y. Research progress of wetland carbon cycle in China based on bibliometrics J. Environ. Eng. Technol 2023 , 13 , 742–752. (In Chinese)

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