| Home | E-Submission | Sitemap | Contact Us |  
Environ Eng Res > Volume 29(5); 2024 > Article
Reyes, Geronimo, Choi, Jeon, and Kim: Comprehensive evaluation of soil characteristics and carbon stocks variability in different urban land use types

Abstract

The terrestrial environment generally serves as an important carbon pool. This study mainly assessed the properties and carbon storage capabilities of soils from different urban land uses. Soil samples from roads/highways, parks, institutional areas, and constructed wetlands were collected to assess the effects of soil sealing on the characteristics and carbon content of urban soils. Soil sealing and compaction greatly influenced urban soil properties by altering the mass-balance, thereby resulting in a disproportionate amount of inflow and outflow of compounds in the soil strata. Using the Walkley-Black and loss-on-ignition (LOI) methods of soil organic carbon (SOC) analysis demonstrated that LOI-based analysis yielded up to 26 times higher SOC values than the wet-oxidation method due to the high weight losses prompted by the volatilization of hygroscopic and structural water and thermal decomposition of carbonate-containing minerals. Further analyses indicated that open soils contain 5% to 78% higher percentage of organic carbon as compared with their sealed counterparts and top soil layers tend to have higher amounts of SOC due to the continuous deposition of carbon-containing compounds from external sources. Generally, the results of this inquiry can serve as a baseline for formulating strategies to augment pedologic carbon stocks in urban environments.

Graphical Abstract

/upload/thumbnails/eer-2023-568f8.gif

1. Introduction

The terrestrial environment is one of the most important natural carbon reservoirs. Soil layers store 1500 Pg·C to 2400 Pg·C of carbon, which is mostly in the form of soil organic carbon (SOC) [1]. Despite the potential of terrestrial environment in storing large amounts of carbon, the disturbance of soil layers can also have considerable impacts on pedologic carbon stocks. One of the most prominent changes in global landscapes is the expansion of urban areas. Land development disrupts environmental processes due to soil sealing and clearing of natural vegetation. Furthermore, the transition of undisturbed landscapes into fragmented patches can pose negative effects on biodiversity and ecosystem productivity [2]. One distinct feature of urban areas is the increased rate of impermeability due to soil sealing. Urban expansion also increases the proportion of sealed soils by using materials, such as asphalt, concrete, and stone, that completely or partially cover the top soil layer. Considering the dynamics of carbon flux and storage, soil sealing can have two contrasting effects on SOC storage: 1) limitation or prevention of material inputs and outputs to and from the soil layer and 2) preservation of stored carbon in different soil strata.
Soil sealing involves the process of removing the top soil layer to create a new surface made from tarmac, concrete, or impermeable slabs. This limits the chemical reactions, mass circulation, and flow of energy between the soil and other environments, ultimately resulting in loss of soil carbon storage and detrimental effects on water regulation, and nutrient cycling [35]. In the case study presented by Tóth et al [6], soil sealing in the functional urban areas of Europe caused a four million-ton decline in the carbon sequestration potential and a 668 million m3 loss of water-holding capacity. A number of studies also presented a contrasting view about the effects of soil sealing in terrestrial carbon storage. Vasenev and Kuzyakov [7] noted the contribution of sealing to soil carbon storage by isolating the carbon stored in the soil sublayer and preventing mineralization. The inquiry conducted by Bae and Ryu [8] asserted the importance of the deep urban “cultural soil layers” carbon stocks. Cultural soil layers sealed by impervious surfaces represent soils that enclose historical records of human activities and habitation deposits which contain considerable amounts of carbon. Evidence suggests that carbon in urban deep layers is preserved due to soil sealing, making them important storage of carbon. As compared to natural ecosystems and landscapes, SOC stocks in urban areas are less understood and investigated. It is, therefore, necessary to evaluate the SOC content of urban soils to establish the terrestrial carbon storage capacity.
Apart from perceived effects of soil sealing, urban areas are among the primary contributors to climate change due to the large GHG emissions associated with energy consumption and industrial processes [9]. It is a common notion that urban areas are not plausible carbon sinks due to the complex structures that affect the biogeochemical properties of soil; however, it is still imperative to understand the underlying conditions that govern the carbon storage function of soils in different urban land use types since the terrestrial environment generally serves as an important carbon pool. Furthermore, most studies on soil organic carbon (SOC) stocks are focused on natural (i.e. forests and peatlands) and agricultural lands, whereas inquiries on SOC stocks on urban soils are still scarce [10]. This study was conducted to determine the characteristics of urban soils and to quantify the pedologic carbon stocks in various urban land use types. This inquiry also explored the influence of soil sealing both on the characteristics and the carbon storage potential of urban soils.

2. Materials and Methods

2.1. Site Description and Characteristics

The study area is located in Cheonan City, Chungnam Province, South Korea. The land cover data obtained from the Korea Ministry of Environment indicated that the major land use types in Cheonan City as of 2022 included paddy fields (18%), dry fields (16%), and orchards (13%). Built-up areas only account for approximately 9% of the total land use in Cheonan City, but most of the residential units are concentrated in urban areas and city centers. Based on the 10-year climate records (2012–2022), Cheonan City received an average annual precipitation of 1098 mm. Approximately 56% of the average annual rainfall depth was observed during the summer season (June to August), whereas only 6% was noted in winter. The highest mean temperature was recorded during the summer season (25.5°C) and the average temperatures during spring, fall, and winter were 12.1°C, 13.5°C, and −2.8°C, respectively.
In order to evaluate the soil carbon storage in urban areas, soil samples were collected at different urban land use types in Cheonan City. As shown in Fig. 1, the sampling sites consisted of institutional areas (I-sites), roads/highways (H-sites), parks (P-sites), and constructed wetlands (CW-sites). Roadsides and institutional areas represent urban land uses that are heavily impacted by soil sealing and other infrastructure-related developments, whereas parks and CWs constitute important fractions of green spaces in urban areas. Sites located on the roadsides were selected based on the presence of traffic monitoring systems managed by the Korea Institute of Civil Engineering and Building Technology, whereas institutional sites are comprised of major government complexes in Cheonan City. The parks included in the study were generally classified as small parks, children’s parks, and neighborhood parks under the descriptions stipulated in the Urban Parks and Green Areas Act of Korea [11]. The CW sites are green infrastructures (GIs) integrated into public parks. During the rainy season, all three wetlands serve as urban stormwater treatment and detention facilities. The characteristics of the sampling locations were summarized in Table 1.

2.2. Soil Sample Collection

Soil sampling was conducted from October 2022 to March 2023 to account for the periods with lower ambient temperatures (<20°C). Fall and winter seasons serve as critical periods for estimating SOC storage since the capacity of soils to assimilate materials tend to diminish due to the reduced metabolic activities of microorganisms at low temperatures [12]. Open and sealed soil samples were collected for each site. In the context of this study, open soil samples refer to soils found in undisturbed or landscaped areas where plants thrive. These are also exposed to atmospheric conditions due to the absence of artificial covers or pavements. On the other hand, sealed soils pertain to soils that are compacted and covered with engineered materials such as bricks or tiles. Sealed soils are fully or partially isolated from the external environment due to the layer of impermeable material overlaid in soils. In accordance with the IPCC Good Practice Guidance for Land Use, Land-Use Change and Forestry (LULUCF) [13], open soil samples were collected in three layers using a soil corer shown in Fig. 2. The topsoil samples were collected at a depth of 30 cm from the surface, middle samples were collected at a depth ranging from 31 cm to 50 cm, and bottom soil samples were collected at a depth of 51 cm to 70 cm. Since sealed soils are more compact and have limited depths, only the top (15 cm from the surface) and middle (16 cm to 30 cm from the surface) samples were collected. No sealed soil samples were collected in site H2 since there are no available or accessible areas for sealed soil sample collection.

2.3. Soil Property Analyses and SOC Quantification Methods

In-situ measurements of soil temperature were conducted alongside the collection of samples. The soil samples were transported into the laboratory and stored at 4°C up to a maximum holding time of 28 days [14]. Apart from the in-situ measurements, the samples were subjected to laboratory analyses to determine the soils’ physico-chemical characteristics, including pH, moisture content, particle size, bulk density, and electrical conductivity. The total nitrogen (TN), total phosphorus (TP), and heavy metal content of individual soils were quantified using the method proposed by Carter and Gregorich [15]. The Kjeldahl method was employed for quantifying TN in soil samples. In the case of TP and heavy metals, composite soil samples were made by combining all the samples collected from similar land use types. All samples are weighed equally before mixing to eliminate the bias. The composite samples were subjected to inductively coupled plasma mass spectrometry (ICP-MS) to determine the concentration of TP and heavy metals (i.e. Cd, Cr, Cu, Pb, and Zn) in the collected soil and sediment samples.
The SOC content of the soil was quantified using the Walkley-Black method (wet oxidation method) and the loss on ignition (LOI) method (dry combustion method). The Walkley-Black Method is one of the most commonly used methods for quantifying the organic carbon content of soils. This method involves the oxidation of carbon using a potassium dichromate solution. The equation used for calculating the SOC content of soils using the Walkley-Black method was expressed in Eq. (1) [13, 16]. The LOI method is also considered a typical approach for quantifying SOC. The process of SOC quantification using the LOI method is relatively simpler, inexpensive, and faster to execute as compared to the Walkley-Black method since this method does not involve the use of strong chemicals or acids [17]. As seen in Eq. (2), the value of SOC obtained in the dry combustion method (at a combustion temperature of 550°C) was derived by employing the widely used van Bemmelen constant or the LOI-to-SOC conversion factor of 0.58 [18, 19].
(1)
SOCw(%)=(Vblank-Vsample)×MFe2+×0.003×100×f×mcfW×f×mcf×100
where SOCw = Organic carbon content of soil (%) obtained through the Walkley-Black Method, Vblank = volume of titrant in the blank (mL), Vsample = volume of titrant in the sample (mL), MFe2+ = concentration of standardized (NH4)2 Fe(SO4)2.6H2O (molarity), 0.003 = carbon oxidized (constant), f = correction factor equivalent to 1.3, W= weight of soil (g), and mcf = moisture correction factor.
(2)
SOCd=LOI*0.58
where SOCd = Organic carbon content of soil (%) obtained through the LOI Method, LOI = weight lost after combustion, 0.58 = van Bemmelen constant.

2.4. Statistical Analyses

Descriptive statistics, including the analysis of mean, median, and standard deviation, was performed to summarize and compare the physico-chemical properties of the samples. The Shapiro-Wilk Test was employed to test the normality of the dataset. Hypothesis testing was conducted to investigate the potential differences in the observed values. For datasets that follow a normal (Gaussian) distribution, the Student’s T-test was performed to determine if the difference between the mean values of two datasets is significant, whereas a one-way analysis of variance (ANOVA) was applied to test the significance of the mean difference among three or more datasets [20]. In the case of datasets that do not comply with the assumption of normality, the non-parametric Wilcoxon signed rank test was used as an alternative to Student’s T-test and ANOVA. All hypotheses were tested at a 95% confidence level, noting that p-values <0.05 signify significant correlations or differences. Analyses and visual representations of processed data were accomplished in MS Excel and OriginPro 2023 software packages.

3. Results and Discussion

3.1. Characteristics and Properties of Soils from Various Urban Land Use Types

The properties of soils greatly vary depending on the land use type and degree of anthropogenic disturbance, and other external factors that may alter the components of soils. The comparison of the properties of sealed and open soils in different urban land use types was exhibited in Fig. 3. I-S had the highest mean electrical conductivity (EC), amounting to 129±119 μs/cm, whereas P-O exhibited the lowest mean EC with a mean value of 56±77 μs/cm. Sealed soils had up to 77% higher EC than open soils, which can be attributed to the application of deicing salt during the winter season. The salt may accumulate in the spaces between blocks and leach into underlying soils through stormwater, thus elevating the EC in sealed soils. In the case of CWs, stormwater runoff containing particulate-bound minerals and ionic compounds potentially increased the EC of sediments. Analysis of the population means indicated that the ECs of soils collected from different land use types are not significantly different (p>0.05).
Soil moisture links land surface temperature to air temperature. This parameter can also have great impacts on the water table and evapotranspiration in urban areas [21]. Generally, open soils had 23% to 45% greater moisture content as compared to sealed soils since greenspaces can retain water in the soil’s pore spaces. On the other hand, the entry of water from external sources is limited by the impermeable layer on top of sealed soils, thus resulting in less moisture content. The highest average moisture content (21%) was noted in the CW samples due to the constant flow of water in one of the facilities investigated. Particularly, the sediments collected in one of the free water surface (FWS) wetlands are frequently saturated due to the inflow from an urban stream. Significant differences (p<0.05) in the moisture content of the samples were observed, suggesting that soils from different land use types have large variations in water holding capacity, degree of saturation, or external sources of moisture.
The average bulk density of the soils ranged from 0.93±0.31 g/cm3 to 1.23±0.32 g/cm3 and no significant differences (p>0.05) were observed among the measured values. Despite the comparable bulk densities, it can be noted that sealed soils were 9% to 18% denser than open soils. Built environments usually have denser soils due to compaction during the development phase. Furthermore, constant traffic (vehicular or anthropogenic) exerts constant pressure on sealed soils that may result in greater compaction [22]. The sediments in CWs had an average bulk density of 1.08±0.42 g/cm3, which is consistent with the typical range of soil bulk densities in natural wetlands (0.5 g/cm3 to 1.5 g/cm3) [23]. In terms of particle size and texture, both open and sealed soils had a sandy texture with minimal silt content (0.49% to 2.22%). The results obtained from the sieve analysis were consistent with the site observations during the sample-collection stage, wherein paved surfaces are typically supported by a layer of coarse-grained sand. CW sediments were also composed of 93.37% to 95.03% sandy soils with small fractions of silt, ranging from 1.57% to 2.06%.
Open soils from parks had the lowest mean pH value (6.38±0.75), whereas the highest mean pH observation (7.24±0.61) was noted in the sealed soils from parks. The pH measurements in open soils were 1.4% to 14.3% lower than the sealed soils’ pH. Open soils are susceptible to acidification due to increased input leaf litter and decaying organic materials in the surrounding areas. Moreover, construction materials used in soil sealing often contain alkaline materials or calcareous wastes that can raise the pH of underlying soils [2426]. A comparison of means indicated that the mean pH of P-O is significantly different (p<0.05) from the mean pH of H-S, I-O, I-S, P-S, and CW.

3.2. Chemical Composition of Urban Soils

Urban soils may contain varying levels of nutrients and pollutants. As compared to natural landscapes, urban soils are more susceptible to disturbance; however, soil sealing may also inhibit the movement of chemicals and compounds in and out of the soil strata. The concentration of nutrients and heavy metals in different urban soils were displayed in Fig. 4. The average TN concentration in different urban soils ranged from 97±50 to 142±60 mg/kg. No significant differences (p>0.05) in TN concentrations were found among the soil samples, but open soils and CW sediments had 6% to 32% higher TN concentrations as compared to their counterparts. In the case of TP, the mean concentration in P-S soil (11±2.5 mg/kg) was found to be statistically different (p<0.05) with the mean concentrations obtained from I-O (2.4±0.14), CW (4.6±3.0), and CW-O (4.0±1.0). Contrary to the trend observed in TN, sealed soils exhibited higher TP concentrations (21% to 121%) as compared to open soils. These inconsistent observations may accentuate the effects of soil sealing on the nutrient dynamics in urban areas. The process and degree of soil sealing affect the nutrient mass-balance by the disproportionate amount of inflow and outflow of compounds in the soil strata. The study conducted by O’Riordan et al [27] also pointed out significant observations in nutrient dynamics in urban areas. It was highlighted that reduced nitrogen concentrations in sealed soils can be attributed to the losses incurred by the removal of top soil layers during the construction of paved surface, reduced litter inputs, and losses due to leaching (aqueous losses) and denitrification (gaseous losses). The high phosphorus concentrations in sealed soils can be explained by the reduced wash-off, leaching, and plant uptake due to the sealing layer. The average TN concentrations of all examined urban soils were above the critical nitrogen level (50 mg/kg), but the average TP concentrations were considerably lower than the typical range of phosphorus concentrations (30 mg/kg to 60 mg/kg) in non-urban soils [28].
Heavy metals are characteristic components of most urban soils due to large industrial and vehicular emissions. Among the heavy metals quantified from the samples, only the mean Cr concentration (369±174 ppb) in P-O exhibited a significant difference (p<0.05) from other soil groups. There were no definite patterns found regarding the concentration of heavy metals in sealed and open soils, suggesting that there are no substantial sources of heavy metals in the study areas. On a similar note, the study conducted by Charzyński et al [29] implied that soil sealing has a minimal effect on the heavy metal content of soils, but open soils are more susceptible to the accumulation of pollutants. CW sediments have pronounced average Cu (355±127 ppb) and Zn (2329±1355 ppb) concentrations. The CWs included in the study accommodate stormwater runoff from adjacent catchments with major transportation routes. Urban stormwater runoff, particularly road runoff, contains heavy metals from vehicular exhausts as a result of the wash-off process in impervious surfaces. A complex mixture of toxic heavy metals can be detected in urban stormwater runoff, but Zn and Cu can be identified as prominent components since Zn is a by-product of tire wear and Cu is a major component of brake pads [30].

3.3. Carbon Content of Urban Soils Based on LOI and Walkley-Black Methods

The SOC values obtained using the LOI and Walkley-Black methods were shown in Fig. 5. Considering the LOI method, the SOC content of soils and sediments from H, I, P, and CW-sites ranged from 0.54% to 14.5%, 0.39% to 7.6%, 0.16% to 12.2%, and 0.63% to 20.64%, respectively. The highest mean SOC concentration was noted in CW sediments (3.1±2.8%), followed by the soils from H-site (3.14±2.74%), P site (2.62±2.39%), then I-site (2.15±1.61%). Based on the results of the LOI method, no significant statistical differences (p=0.11) were observed among the SOC content of the samples. The SOC values derived from the Walkley-Black method exhibited a different trend relative to the values obtained from the LOI method. Measurements using the Walkley-Black Method yielded SOC values ranging from 0.34% to 5.66%, 0.38% to 3.78%, 0.21% to 2.77%, and 0.40% to 3.74% for H-, I-, P-, and CW-sites, respectively. Unlike the outcome of the LOI method, the highest mean SOC was noted from H-site soils (1.84±1.18%), succeeded by CW sediments (1.38±0.69%), I-site soils (1.35±0.77%), then P-site soils (1.16±0.68%). The average organic carbon content of H-site soils was also found to be significantly different (p<0.05) from the mean SOC measured in other soil groups.
A statistical comparison of the SOC values indicated that LOI and Walkley-Black method produced significantly different (p<0.05) results. Approximately 74% of the LOI-based SOC (SOCd) values were higher than the values obtained through the Walkley-black method (SOCw). Among these, 46% of the SOCd values were two to 26 times greater than SOCw. Similar findings were reported in the studies conducted by Maulood [31], Anand et al [32], and Barwari et al [33], among others, suggesting that LOI-based SOC quantification may result in higher estimates. Previous inquiries indicated that LOI overestimates the carbon content of soils due to the volatilization of hygroscopic and structural water and thermal decomposition of carbonate-containing minerals at temperatures above 375°C [3436]. While there are contrasting reports regarding the accuracy of SOC estimates using the Walkley-Black method, this procedure is commonly regarded to be more reliable than the LOI approach in terms of recovery and oxidation of organic matter [37, 38].
The resulting coefficients of determination (R2) from the regression analysis ranged from 7×10−9 to 0.1256, implying that SOCw and SOCd are independent of one another. Differing results regarding the correlation of carbon estimates using LOI and Walkley-black methods were also presented in other previous inquiries. A weak correlation (R2=0.35) between the SOC estimates from LOI and Walkley-Black methods was reported by Tuffour et al [39]. Using the Van Bemmelen organic matter-to-organic carbon conversion factor (0.58), Wang et al [40] derived a close relationship (R2=0.83) between the organic carbon values obtained through LOI and Walkley-Black methods. The optimum temperature used in the LOI method was also found to be sediment-specific, implying that the resulting SOC can be underestimated or overestimated depending on the sample and experimental conditions. Anand [32] also observed a significant positive correlation between the two methods (r=0.92, p<0.05). Despite the good correlation between the two methods, it was noted that SOC estimates using LOI are up to 8.51% higher than Walkley-Black’s and that the clay fraction in soils may cause considerable variations in SOC estimates. The study conducted by Roper et al [41] compared different methods of estimating SOC in different types of soils. Results showed that the correlation coefficients between LOI and Walkley-Black carbon estimates ranged from 0.29 to 0.64, indicating that the relationship between the two methods can be affected by the type of soil under consideration. It was also highlighted that the 0.58 conversion factor is not universal since the relationship between soil organic matter content and SOC is dynamic. Generally, the homogeneity and composition of soil samples, analytical procedure (i.e., heating temperature and duration), and soil type can influence the correlation between the two methods. Succeeding analyses in this study were performed using the Walkley-Black method since it is regarded as a more direct method of estimating organic carbon in soils as compared with LOI.

3.4. Variation of Carbon Stocks in Sealed and Open Soils

The chart containing the information regarding the average SOC content of open soils, sealed soils, and CW sediments were displayed in Fig. 6. Open soils contain 5% to 78% higher percentage of organic carbon as compared with their sealed counterparts. Open soils may exhibit greater mean SOC content as compared to sealed soils since these soils support plant growth and are exposed to greater organic matter inputs from leaf litter and other carbon-containing compounds. Similar with the case of nutrients, the SOC content of sealed soils may also be reduced due to the sealing layer that prevents organic matter inputs from accumulating into the soil. Wei et al [42] also demonstrated the negative impacts of sealing on the long-term SOC storage of urban soils due to the poor carbon mineralization rate, lower basal respiration, and lower microbial activities. Despite the lower SOC values quantified from sealed soils, no significant differences (p>0.05) were noted in the organic carbon content of the two soil groups. This observation was consistent with the results obtained by Edmondson et al [43] affirming that there is no significant difference in the organic carbon storage of greenspaces and impervious surfaces. This suggested that soils in paved areas, including roads, footpaths, and other load-bearing surfaces may also store considerable amounts of SOC.
Among the open soil group, the samples collected from the roadside (H1) had the highest average SOC content (2.15%), whereas the soils from parks contain relatively less organic carbon (1.18% to 1.43%). Several factors may influence the distribution of carbon in urban soils. The relatively high SOC values detected in highway and roadside soils may be attributed to the black carbon deposition from vehicular activities. Black carbon in urban soils, which mainly originates from the incomplete combustion of fuel from motor vehicles, may constitute a considerable fraction of SOC due to the continuous accumulation of vehicular exhaust in soil layers [43, 44]. It has been generally reported in previous studies that parks constitute significant portions of carbon stocks in urban areas [45, 46]; however, SOC pools are susceptible to large variations due to several factors, including land management practices, type of vegetation, and soil characteristics. Constructing urban parks involves the process of disturbing the original soil layer (i.e., topsoil removal, soil relocation, grading, and compaction), which affects the soil carbon equilibrium. Generally, newly developed parks or green spaces require a certain period of stability to attain optimum carbon storage potential [47].
The sediments collected from CWs also exhibited SOC fractions that are greater than or comparable with open soils in parks and institutional areas but were relatively less than roadside soils. Despite the short distance between sample collection points, CW sediments exhibited 7% to 86% greater SOC content than the open soils surrounding the facility. According to Yang et al [48], more than 90% of the total carbon in wetland ecosystems is stored in sediments. Since the amount of carbon stored in sediments is relevant to the amount of organic matter inputs and outputs, the SOC content of the investigated CW sediments is indicative of either small organic matter inputs or rapid decomposition. Another factor that can affect the amount of carbon stored in CW sediments is the age of facilities. Wetlands tend to sequester greater amounts of carbon as they age. Older wetlands have more developed soil properties due to the consistent input of organic matter in soils from litterfall, root turnover, and microbial biomass, thus providing greater opportunities for carbon storage [49,50]. Since all three CWs just started operating in 2016, the facilities may still be in the process of SOC accumulation and stabilization.

3.5. Analysis of SOC Concentration at Different Soil Depths

SOC stocks may vary along a specific depth profile due to various factors including temperature, precipitation, and land management practices [51]. The average SOC content of soils at different depths were illustrated in Fig. 7. Statistical analyses revealed that the mean SOC contents of soils from different urban land use types are not significantly different (p>0.05) but the variance exhibited a significant degree of difference (p<0.05). This suggested that despite the comparable mean SOC values, the measured SOC stocks in some land use types are more heterogeneous as compared with others. The major causes of carbon stock heterogeneity previously identified in published literature include differences in carbon inputs, decomposition rates of litter from different types of plants, profile distribution, and land use [52, 53].
Except for I2- and P2-sites, top soils (0–30 cm) collected from open greenspaces exhibited 10% to 143% greater SOC content as compared to the middle (31–50 cm) and bottom (51–70 cm) soil layers. This is in agreement with the results of the work presented by Bhunia et al [54], Craig et al [55], and Poirier et al [56] which also stated that upper soil layers exposed to greater carbon inputs tend to have higher SOC content. Comparative analysis between the SOC in the middle and bottom soils indicated that there are no clear patterns of carbon accumulation in these layers. In the case of soils collected from H3, I1, I2, I3, and P1, middle-layer soil had 3% to 43% higher SOC contents than the bottom soils, whereas for H1, H2, P2, and P3, bottom soils exhibited 11% to 64% greater SOC contents than the middle-layer soils. This observation suggested that SOC build-up in sub-soil layers is not solely governed by stock changes and may, therefore, be influenced by historical land use practices or other biogeochemical factors.
The SOC content of sealed soil samples also showed inconsistent trends with respect to depth. The sub-layer (10 – 20 cm) of sealed soils from H1, I3, and P1 had 6% to 19% more SOC content than the top layer (0 – 10 cm) samples but in the case of H3, I1, I2, P2, and P3, the top layer of sealed soils exhibited 17% to 51% higher SOC values than the sub-soil layers. Despite the limitations set by the sealing layer in the carbon accumulation potential of soils under impermeable pavements, it was observed that partially sealed soils may still be affected by the external environment. Fine grass roots can penetrate the gaps between bricks and reach the underlying soil surface. These roots provide exudates that contribute organic matter to the soil, which serves as an important source of SOC [57].
The top sediment layer (0 – 30 cm) collected from CWs had average SOC values that are 8% to 39% and 14% to 141% higher than the middle (31 – 50 cm) and bottom (51 – 70 cm) sediments, respectively. Apart from the contribution of plant detritus, the stormwater runoff from surrounding catchment areas also potentially contributes to the organic matter deposits on the top layer, thereby increasing SOC fractions in the sediments.

4. Conclusions

Urban soils are highly impacted by anthropogenic activities linked to the alteration of natural soil properties and pollutant dynamics. The results obtained from this study presented concrete evidence that soil sealing altered natural soil properties up to a certain degree. Specifically, the major effect of soil sealing was manifested through the direct interaction of underlying soils with the external environment. The sealing layer prevented the accumulation of pollutants (i.e., heavy metals) in the underlying soils; however, this same layer also disrupted the natural processes of mass transport, deposition, and storage. Based on the analysis of carbon stocks in different urban land uses, the values obtained using the LOI method were generally higher than the estimates from the Walkley-Black method. This observation was supported by previous studies which showed that the LOI method tended to overestimate the carbon content of soils due to the thermal decomposition of carbonate-containing minerals under high temperatures. Open soils were found to have 5% to 78% higher SOC stocks than sealed soils, which was attributed to the higher organic inputs from litterfall and other carbon-containing compounds in open soils. Further analyses also confirmed the CWs’ ability to store carbon at a relatively higher rate as compared to sealed areas or other green spaces in urban areas. Top soil layers (0 to 30 cm) contain higher amounts of SOC as compared to the middle and bottom layers due to the continuous replenishments of carbon from external sources, whereas middle and bottom soil samples exhibited indefinite patterns potentially caused by historical land use practices. In order to effectively analyze the short-term variations in urban SOC stocks, analyzing soil depths of up to 30 cm is recommended; however, it is also necessary to conduct further studies on deeper soil layers to evaluate long-term SOC storage. Overall, urban soils exhibited the capacity to store considerable amounts of carbon which can still be improved through the expansion of green spaces.

Acknowledgment

This work was supported by Korea Environmental Industry& Technology Institute (KEITI) through Wetland Ecosystem Value Evaluation and Carbon Absorption Value Promotion Technology Development Project, Funded by Korea Ministry of Environment (MOE)(2022003630005).

Notes

Conflict-of-Interest Statement

The authors declare that they have no conflict of interest.

Author Contributions

N.J.D.G.R. (Junior Engineer) conceptualized the research topic, collected the samples and conducted the experiments, summarized related literature, drafted the figures and tables, and wrote the whole manuscript. F.K.F.G. (Research Fellow) collected the samples, supervised the analysis of data, and reviewed the manuscript; H.C. (Researcher) collected the samples, reviewed the manuscript; M.J. (Senior Researcher) collected the samples; L.H.K. (Professor) Conceptualized the research topic, secured funding for the project, supervised data collection and analysis, and reviewed the manuscript.

References

1. Reddy NS, Badole WP, Nirgulkar MB, Bhoyar KD. Impact of Organic, Inorganic and Integrated Nutrient Management Practices On Carbon Pool and Nutrient Availability of Perennial, Annual and Seasonal Crops Grown Innagpur District. Int. J. Curr. Microbiol. Appl. Sci. 2021;10:1739–1751. https://doi.org/10.20546/ijcmas.2021.1001.204
crossref

2. Zambrano L, Aronson MFJ, Fernandez T. The Consequences of Landscape Fragmentation on Socio-Ecological Patterns in a Rapidly Developing Urban Area: A Case Study of the National Autonomous University of Mexico. Front. Environ. Sci. 2019;7:152. https://doi.org/10.3389/fenvs.2019.00152
crossref

3. O’Riordan R, Davies J, Stevens C, Quinton JN. The effects of sealing on urban soil carbon and nutrients. Soil. 2021;7:661–675. https://doi.org/10.5194/soil-7-661-2021
crossref

4. Chen Y, Wang X, Jiang B, Yang N, Li L. Pavement induced soil warming accelerates leaf budburst of ash trees. Urban For. Urban Green. 2016;16:36–42. https://doi.org/10.1016/j.ufug.2016.01.014
crossref

5. Wei ZQ, Wu SH, Zhou SL, Li JT, Zhao QG. Soil Organic Carbon Transformation and Related Properties in Urban Soil Under Impervious Surfaces. Pedosphere. 2014;24:56–64. https://doi.org/10.1016/S1002-0160(13)60080-6
crossref

6. Tóth G, Ivits E, Prokop G, Gregor M, Fons-Esteve J, Agràs RM. Impact of Soil Sealing on Soil Carbon Sequestration, Water Storage Potentials and Biomass Productivity in Functional Urban Areas of the European Union and the United Kingdom. Land. 2022;11:840. https://doi.org/https://doi.org/10.3390/land11060840
crossref

7. Vasenev V, Kuzyakov Y. Urban soils as hot spots of anthropogenic carbon accumulation: Review of stocks, mechanisms and driving factors. Land Degrad. Dev. 2018;29:1607–1622. https://doi.org/10.1002/ldr.2944
crossref

8. Bae J, Ryu Y. High soil organic carbon stocks under impervious surfaces contributed by urban deep cultural layers. Landsc. Urban Plann. 2020;204:103953. https://doi.org/10.1016/j.landurbplan.2020.103953
crossref

9. Chuai X, Feng J. High resolution carbon emissions simulation and spatial heterogeneity analysis based on big data in Nanjing City, China. Sci. Total Environ. 2019;686:828–837. https://doi.org/10.1016/j.scitotenv.2019.05.138
crossref pmid

10. Brown S, Miltner E, Cogger C. Carbon sequestration potential in urban soils. Rattan L, Augustin B, editorsCarbon Sequestration in Urban Ecosystems. Springer; Dordrecht: 2012. p. 173–196. https://doi.org/10.1007/978-94-007-2366-5_9
crossref pmid

11. Korea Legislation Research Institute. Enforcement Decree of the Act on Urban Parks and Green Areas [Internet]. c2023. [cited 08 April 2023]. Available from: https://elaw.klri.re.kr/eng_mobile/viewer.do?hseq=51379&type=part&key=33


12. Blume E, Bischoff M, Reichert JM, Moorman T, Konopka A, Turco RF. Surface and subsurface microbial biomass, community structure and metabolic activity as a function of soil depth and season. Appl. Soil Ecol. 2002;20:171–181. https://doi.org/10.1016/S0929-1393(02)00025-2
crossref

13. Penman J, Gytarsky M, Hiraishi T, et al. Good Practice Guidance for Land Use, Land-Use Change and Forestry. Hayama: IPCC; 2003. p. 3–81.


14. Schumacher B. Methods for the Determination of Total Organic Carbon (TOC) in Soils and Sediments. Cincinnati: USEPA; 2002. p. 1–20.


15. Carter MR, Gregorich EG. Soil Sampling and Methods of Analysis. 2nd edBoca Raton: CRC Press; 2007. p. 1–1264.


16. FAO. Standard operating procedure for soil organic carbon Walkley-Black method. Food and Agriculture Organization of the United Nations; 2019. p. 1–25.


17. Gerenfes D, Giorgis AG, Negasa G. Comparison of organic matter determination methods in soil by loss on ignition and potassium dichromate method. Int. J. Hortic. Food Sci. 2022;4:49–53. https://doi.org/10.33545/26631067.2022.v4.i1a.85
crossref

18. Ouyang X, Lee SY. Improved estimates on global carbon stock and carbon pools in tidal wetlands. Nat. Commun. 2020;11:317. https://doi.org/10.1038/s41467-019-14120-2
crossref pmid pmc

19. Jensen JL, Christensen BT, Schjønning P, Watts CW, Munkholm LJ. Converting loss-on-ignition to organic carbon content in arable topsoil: pitfalls and proposed procedure. Eur. J. Soil Sci. 2018;69:604–612. https://doi.org/10.1111/ejss.12558
crossref pmid pmc

20. Mishra P, Singh U, Pandey C, Mishra P, Pandey G. Application of student’s t-test, analysis of variance, and covariance. Ann. Card. Anaesth. 2019;22:407. https://doi.org/10.4103/aca.aca_94_19
crossref pmid pmc

21. Jiang Y, Weng Q. Estimation of hourly and daily evapotranspiration and soil moisture using downscaled LST over various urban surfaces. GIsci. Remote Sens. 2017;54:95–117. https://doi.org/10.1080/15481603.2016.1258971
crossref

22. Shober AL, Denny GC, Reisinger AJ, Bean EZ. Soil Compaction in the Urban Landscape [Internet]. Gainesville: University of Florida IFAS Extension; c2023. [cited 10 April 2023]. Available from: https://edis.ifas.ufl.edu/


23. Mobilian C, Craft CB. 2022. Wetland Soils: Physical and Chemical Properties and Biogeochemical Processes. Mehner T, Tockner K, editorsEncyclopedia of Inland Waters. Second EditionOxford: Elsevier; 2022. p. 157–168.
crossref

24. Wavrek MT, Jean-Philippe S, McKinney ML. Ecological and Soil Data Applied to Conservation Management of an Urban Forest. Forests. 2023;14:487. https://doi.org/10.3390/f14030487
crossref

25. Morel JL, Chenu C, Lorenz K. Ecosystem services provided by soils of urban, industrial, traffic, mining, and military areas (SUITMAs). J. Soils Sediments. 2015;15:1659–1666. https://doi.org/doi.org/10.1007/s11368-014-0926-0
crossref

26. Jim CY. Urban soil characteristics and limitations for landscape planting in Hong Kong. Landsc. Urban Plann. 1998;40:235–249. https://doi.org/10.1016/S0169-2046(97)00117-5
crossref

27. O’Riordan R, Davies J, Stevens C, Quinton JN. The effects of sealing on urban soil carbon and nutrients. Soil. 2021;7:661–675. https://doi.org/10.5194/soil-7-661-2021
crossref

28. Li ZG, Zhang GS, Liu Y, et al. Soil Nutrient Assessment for Urban Ecosystems in Hubei, China. PLoS One. 2013;8:e75856. https://doi.org/10.1371/journal.pone.0075856
crossref pmid pmc

29. Charzyński P, Plak A, Hanaka A. Influence of the soil sealing on the geoaccumulation index of heavy metals and various pollution factors. Environ. Sci. Pollut. Res. 2017;24:4801–4811. https://doi.org/10.1007/s11356-016-8209-5
crossref pmid pmc

30. Camponelli KM, Lev SM, Snodgrass JW, Landa ER, Casey RE. Chemical fractionation of Cu and Zn in stormwater, roadway dust and stormwater pond sediments. Environ. Pollut. 2010;158:2143–2149. https://doi.org/10.1016/j.envpol.2010.02.024
crossref pmid

31. Maulood MP. Determination of Organic Matter by Using Titrimetric and Loss on Ignition Methods for Northern Iraqi Governorates Soils. Al-Nahrain J. Sci. 2022;25:1–7. https://doi.org/10.22401/anjs.25.3.01
crossref

32. Anand S. Soil organic carbon: Associating the Walkley-Black Wet Oxidation Method to Loss on Ignition (Gravimetric method) and Clay Content for Selected Samoan Inceptisols. Eur. J. Appl. Sci. 2022;10:219–227. https://doi.org/10.14738/aivp.102.12049
crossref

33. Barwari VI, Hashim FA, Mohamad BH. Comparison between Walkley-Black and Loss-On-Ignition methods for organic carbon estimation in soils from different locations. Kufa J. Agric. Sci. 2021;9:292–306.


34. Chase AJ, Erich MS, Fernandez IJ, Birthisel SK. Changes in Agricultural Soil Organic Carbon in Northern New England: 1995 to 2021. SSRN Electronic Journal. 2023;4329774. https://doi.org/10.2139/ssrn.4329774
crossref

35. Braun KN, Theuerkauf EJ, Hurtgen MT, Masterson AL, Horton DE. Loss-On-Ignition Estimates for Soil Organic Carbon in Great Lakes Freshwater Coastal Wetlands. Wetlands. 2020;40:1201–1206. https://doi.org/10.1007/s13157-020-01270-z
crossref

36. Mustapha AA. Comparison of Different Methods for the Assessment of Soil Organic Carbon in Northern Guinea Savanna Zone of Nigeria. J. Sustain. Agric. Environ. 2020. 18:36–41. https://ojs.mouau.edu.ng/index.php/jsae/article/view/205/118


37. Pedreño JN, Benslama A, Lucas IG, Almendro MBC. Organic matter in farming systems in Southern Spain by LOI and Walkley-Black methods. EGU General Assembly. 2022:EGU22–9368. https://doi.org/https://doi.org/10.5194/egusphere-egu22-9368 2022;
crossref

38. Wang X, Wang J, Zhang J. Comparisons of Three Methods for Organic and Inorganic Carbon in Calcareous Soils of Northwestern China. PLoS One. 2012;7:e44334. https://doi.org/10.1371/journal.pone.0044334
crossref pmid pmc

39. Tuffour HO, Yeboah IB, Bonsu M, et al. Soil Organic Carbon: Relating the Walkley-Black Wet Oxidation Method to Loss on Ignition and Clay Content. Int. J. Sci. Res. Knowl. 2014;2:249–256. https://doi.org/10.12983/ijsrk-2014-p0249-0256
crossref

40. Wang Q, Li Y, Wang Y. Optimizing the weight loss-on-ignition methodology to quantify organic and carbonate carbon of sediments from diverse sources. Environ. Monit. Assess. 2011;174:241–257. https://doi.org/10.1007/s10661-010-1454-z
crossref pmid

41. Roper WR, Robarge WP, Osmond DL, Heitman JL. Comparing Four Methods of Measuring Soil Organic Matter in North Carolina Soils. Soil Sci. Soc. Am. J. 2019;83:466–474. https://doi.org/10.2136/sssaj2018.03.0105
crossref

42. Wei ZQ, Wu SH, Zhou SL, Li JT, Zhao QG. Soil Organic Carbon Transformation and Related Properties in Urban Soil Under Impervious Surfaces. Pedosphere. 2014;24:56–64. https://doi.org/10.1016/S1002-0160(13)60080-6
crossref

43. Edmondson JL, Stott I, Potter J, et al. Black Carbon Contribution to Organic Carbon Stocks in Urban Soil. Environ. Sci. Technol. 2015;49:8339–8346. https://doi.org/10.1021/acs.est.5b00313
crossref pmid

44. Gerke J. Black (pyrogenic) carbon in soils and waters: a fragile data basis extensively interpreted. Chem. Biol. Technol. Agric. 2019;6:1–8. https://doi.org/10.1186/s40538-019-0151-6
crossref

45. Canedoli C, Ferrè C, El Khair DA, Padoa-Schioppa E, Comolli R. Soil organic carbon stock in different urban land uses: high stock evidence in urban parks. Urban Ecosyst. 2020;23:159–171. https://doi.org/10.1007/s11252-019-00901-6
crossref

46. Takahashi T, Amano Y, Kuchimura K, Kobayashi T. Carbon content of soil in urban parks in Tokyo, Japan. Landscape Ecol. Eng. 2008;4:139–142. https://doi.org/10.1007/s11355-008-0043-6
crossref

47. Lindén L, Riikonen A, Setälä H, Yli-Pelkonen V. Quantifying carbon stocks in urban parks under cold climate conditions. Urban For. Urban Green. 2020;49:126633. https://doi.org/10.1016/j.ufug.2020.126633
crossref

48. Yang R, Fang J, Cao Q, Zhao D, Dong J, Wang R, Liu J. The content, composition, and influencing factors of organic carbon in the sediments of two types of constructed wetlands. Environ. Sci. Pollut. Res. 2021;28:49206–49219. https://doi.org/10.1007/s11356-021-14134-8
crossref pmid

49. Valach AC, Kasak K, Hemes KS, et al. Productive wetlands restored for carbon sequestration quickly become net CO2 sinks with site-level factors driving uptake variability. PLoS One. 2021;16:e0248398. https://doi.org/10.1371/journal.pone.0248398
crossref pmid pmc

50. Ahn C, Jones S. Assessing organic matter and organic carbon contents in soils of created mitigation Wetlands in Virginia. Environ. Eng. Res. 2013;18:151–156. https://doi.org/10.4491/eer.2013.18.3.151
crossref

51. Hobley EU, Wilson B. The depth distribution of organic carbon in the soils of eastern Australia. Ecosphere. 2016;7:e01214. https://doi.org/10.1002/ecs2.1214
crossref

52. Vasenev VI, Stoorvogel JJ, Vasenev II. Urban soil organic carbon and its spatial heterogeneity in comparison with natural and agricultural areas in the moscow region. Catena. 2013;107:96–102. https://doi.org/10.1016/j.catena.2013.02.009
crossref

53. Bambrick AD, Whalen JK, Bradley RL, et al. Spatial heterogeneity of soil organic carbon in tree-based intercropping systems in Quebec and Ontario, Canada. Agrofor. Syst. 2010;79:343–353. https://doi.org/10.1007/s10457-010-9305-z
crossref

54. Bhunia GS, Shit PK, Maiti R. Comparison of GIS-based interpolation methods for spatial distribution of soil organic carbon (SOC). J. Saudi Soc. Agric. Sci. 2018;17:114–126. https://doi.org/10.1016/j.jssas.2016.02.001
crossref

55. Craig ME, Turner BL, Liang C, Clay K, Johnson DJ, Phillips RP. Tree mycorrhizal type predicts within-site variability in the storage and distribution of soil organic matter. Global Change Biol. 2018;24:3317–3330. https://doi.org/10.1111/gcb.14132
crossref pmid

56. Poirier V, Angers DA, Rochette P, Whalen JK. Initial soil organic carbon concentration influences the short-term retention of crop-residue carbon in the fine fraction of a heavy clay soil. Biol. Fertil. Soils. 2013;49:527–535. https://doi.org/10.1007/s00374-013-0794-6
crossref

57. Panchal P, Preece C, Peñuelas J, Giri J. Soil carbon sequestration by root exudates. Trends Plant Sci. 2022;27:749–757. https://doi.org/10.1016/j.tplants.2022.04.009
crossref pmid

Fig. 1
Land use map and soil collection points in Cheonan City.
/upload/thumbnails/eer-2023-568f1.gif
Fig. 2
Soil sampling apparatus and core soil sample layers.
/upload/thumbnails/eer-2023-568f2.gif
Fig. 3
Properties of open (O) soils and sealed (S) soils in different urban land use types.
/upload/thumbnails/eer-2023-568f3.gif
Fig. 4
Nutrients and heavy metals concentration in soils from different urban land uses.
/upload/thumbnails/eer-2023-568f4.gif
Fig. 5
Comparison of SOC values using LOI and Walkley-Black method.
/upload/thumbnails/eer-2023-568f5.gif
Fig. 6
Carbon content of open soils, sealed soils, and CW sediments. aCW sediments; bopen soils nearby CWs.
/upload/thumbnails/eer-2023-568f6.gif
Fig. 7
SOC content of different soil layers.
/upload/thumbnails/eer-2023-568f7.gif
Table 1
Sampling location and characteristics
Site/Land use type Code Latitude Longitude Area/Facility size (m2)a
Singal Highway H1 36°51′26.14″N 127° 6′34.54″E 1369.1b,c
Sandong Highway (1) H2 36°50′8.58″N 127° 5′42.57″E 2308.9b,c
Sandong Highway (2) H3 36°49′30.97″N 127° 6′7.21″E 6809.5b,c
Seobuk District Office I1 36°52′41.55″N 127° 9′21.43″E 53248.2b
Dongnam District Office I2 36°48′57.44″N 127° 6′52.86″E 9721.5b
Cheonan City hall I3 36°48′24.02″N 127° 9′4.58″E 57534.6b
Ja-am Green Park P1 36°50′36.86″N 127° 6′24.08″E 26548.8b
Dujeong Park P2 36°50′11.05″N 127° 8′26.66″E 8013.1b
Seongjeong Park P3 36°49′46.12″N 127° 8′22.02″E 20871.6b
Mulchongsae CW CW1 36°48′32.39″N 127° 6′22.98″E 4925.2d
Nongsubodeul CW CW2 36°48′50.89″N 127° 6′12.30″E 40070.0d
Areumdeuri CW CW3 36°49′8.61″N 127° 6′22.55″E 439.5d

Area estimated using online satellite image;

lot area;

road with + 3-m buffer on each side;

CW area

TOOLS
PDF Links  PDF Links
PubReader  PubReader
Full text via DOI  Full text via DOI
Download Citation  Download Citation
  Print
Share:      
METRICS
1
Web of Science
0
Crossref
0
Scopus
1,479
View
89
Download
Editorial Office
464 Cheongpa-ro, #726, Jung-gu, Seoul 04510, Republic of Korea
FAX : +82-2-383-9654   E-mail : eer@kosenv.or.kr

Copyright© Korean Society of Environmental Engineers.        Developed in M2PI
About |  Browse Articles |  Current Issue |  For Authors and Reviewers