Soil organic carbon stock in different urban land uses: high stock evidence in urban parks

A systematic analysis and review of soil organic carbon stocks in urban greenspaces

Urban greenspaces typically refer to urban wetland, urban forest and urban turfgrass. They play a critical role in carbon sequestration by absorbing carbon from the atmosphere; however, their capacity to retain and store carbon in the form of soil organic carbon (SOC) varies significantly. This study provides a systematic analysis and review on the capacity of different urban greenspace types in retaining and storing SOC in 30 cm soil depth on a global scale. Data came from 78 publications on the subject of SOC stocks, covering different countries and climate zones. Overall, urban greenspace types exerted significant influences on the spatial pattern of SOC stocks, with the highest value of 18.86 ± 11.57 kg m-2 (mean ± standard deviation) in urban wetland, followed by urban forest (6.50 ± 3.65 kg m-2), while the lowest mean value of 4.24 ± 3.28 kg m-2 was recorded in urban turfgrass soil. Soil organic carbon stocks in each urban greenspace type were significantly affected by climate zones, management/environmental settings, and selected soil properties (i.e. soil bulk density, pH and clay content). Furthermore, our analysis showed a significantly negative correlation between SOC stocks and human footprint in urban wetland, but a significantly positive relationship in urban forest and urban turfgrass. A positive correlation between SOC stocks and human footprint indicates that increased human activity and development can enhance SOC stocks through effective management and green infrastructure. Conversely, a negative correlation suggests that improper management of human activities can degrade SOC stocks. This highlights the need for sustainable practices to maintain or enhance SOC accumulation in urban greenspaces.

The fate of nitrogen in the urban area - The case of Zielona Góra, Poland

The anthropogenic change of the nitrogen (N) cycle is strongly triggered by urban demand (such as food and meat consumption, energy demand and transport). As a consequence of high population density, impacts on human health through water and air pollution also concentrate on a city environment. Thus, an urban perspective on a predominantly rural pollution becomes relevant. Urban N budgets may be considered less intrinsically connected, so that separation of an agri-food chain and an industry-combustion chain is warranted. Results have been obtained for Zielona Góra, Poland, a city of 140,000 inhabitants characterized by domestic and transport sources and forest-dominated surroundings. In addition to food imports in Zielona Gora amounting to about 30 %, in the suburban area a significant share of N amounting to 41 % is related to fertilizer imports. The remaining imports are in fuel, electronics, textiles, plastics and paper. Most of the agri-food N (45 %) is denitrified in wastewater treatment. N associated with combustion (mainly NOx emissions from vehicles) represents a much smaller share than N entering via the agri-food system, amounting to 22 % of the total N imports. This overall picture is maintained also when specifically addressing the city center, with the exception of mineral fertilizer that plays a much smaller role, with just 7 % of N imports to the city.

Construction of a methodology framework to characterize dynamic full-sector land-use carbon emissions embodied in trade

The globally massive land-use changes associated with unprecedented urbanization rate are leading to prodigious quantities of carbon emissions. Nonetheless, the dynamics of land-use carbon emissions, particularly driven by supply-chain activities across all relevant industrial sectors, remain largely unexplored, especially in non-agricultural sectors. Here, we constructed a novel methodological framework to quantify full-sector land-use carbon emissions in Shenzhen, China, an international megacity grappling with acute land resource scarcity. Then, we integrated this framework with multiregional input-output analysis to uncover the multi-scale embodied land-use emissions propelled by Shenzhen's supply-chain activities. Our results indicate a marked increase in Shenzhen's embodied carbon emissions, approximately two orders of magnitude greater than its physical emissions, tripling during 2005-2018. Remarkably, non-agriculture sectors contributed 81.3-90.5 % of physical and 46.6-58.4 % of embodied land-use emissions. The land-use changes occurred outside Shenzhen accounted for 6.5-13.3 % of Shenzhen's total embodied land-use emissions. The sectoral analysis revealed a transition from traditional manufacturing (e.g., metallurgy, chemical products, textiles, wood products) in 2010-2015 to high-tech sectors (e.g., electronic equipment and other manufacture) in 2015-2018. This shift was primarily attributed to concurrent industry transfer actions, leading to aggressive changes in land-use emission intensity discrepancies within and outside Shenzhen. This study provides a scientific basis for designing effective strategies to mitigate land-use carbon emissions associated with supply-chain activities.

Soil Black Carbon Increases Under Urban Trees with Road Density and Time: Opportunity Hotspots for Carbon Storage in Urban Ecosystems

Black carbon (BC) can comprise a significant fraction of the soil carbon pool in cities. However, vegetation cover and human activity influence the spatial distribution of urban soil BC. We quantified soil total carbon (TC), soil organic carbon (SOC), BC, and total nitrogen (TN) in a medium-sized city in Dallas-Fort Worth, Texas. Soils were sampled to 20 cm depth from underneath 16 paired Quercus stellata (post oak) trees and open lawns. Effects of vegetation cover, road density, and building age (a proxy for time since development) on soil C and N were analyzed. Soil OC concentrations were higher under post oak trees (5.5%) compared to open lawns (3.6%) at 0-10 cm, but not at 10-20 cm depth. In contrast, soil BC and TN did not differ by vegetation cover. There were significant interaction effects between vegetation cover and road density and vegetation cover and building age on soil BC. At 0-10 cm, soil BC concentrations, stock, and BC/SOC ratios increased more with road density under trees than lawns, indicating enhanced atmospheric BC deposition to tree canopies. Black carbon in tree soils also increased with building age as compared to lawn soils, likely due to higher BC retention under trees, enhanced BC losses under lawns, or both. Our findings show that urban tree soils are localized opportunity hotspots for BC storage in areas with elevated emissions and longer time since development. Conserving and planting urban trees above permeable surfaces and soils could contribute to long-term carbon storage in urban ecosystems.

Origin of non-exhaust PM in cities by individual analysis of particles collected by honey bees (Apis mellifera)

Urban areas present multiple challenges to scientists interested in unraveling the source, transport, and fate of airborne particulate matter (PM). Airborne PM consists of a heterogeneous mixture of particles with different sizes, morphologies, and chemical compositions. However, standard air quality stations only detect the mass concentration of PM mixtures with aerodynamic diameters ≤10 μm (PM₁₀) and/or ≤ 2.5 μm (PM_2.5). During honey bee foraging flights, airborne PM up to 10 μm in size attaches to their bodies, making them suitable for collecting spatiotemporal data on airborne PM. The individual particulate chemistry of this PM can be assessed using scanning electron microscopy coupled with energy-dispersive X-ray spectroscopy on a sub-micrometer scale, allowing accurate identification and classification of the particles. Herein, we analyzed the PM fractions of 10-2.5 μm, 2.5-1 μm, and below 1 μm in average geometric diameter collected by bees from hives located in the city of Milan, Italy. Bees showed contamination by natural dust, originating from soil erosion and rock outcropping in the foraging area, and particles with recurrent heavy metal content, most likely attributed to vehicular braking systems and possibly tires (non-exhaust PM). Notably, approximately 80% of non-exhaust PM was ≤1 μm in size. This study provides a possible alternative strategy to apportion the finer fraction of PM in urban areas and determine citizens' exposure. Our findings may also prompt decision-makers to issue policy addressal for non-exhaust pollution, especially for the ongoing restructuring of European regulations on mobility and the shift toward electric vehicles whose contribution to PM pollution is debated.

Improvement of spatial estimation for soil organic carbon stocks in Yuksekova plain using Sentinel 2 imagery and gradient descent-boosted regression tree

Carbon sequestration in earth surface is higher than the atmosphere, and the amount of carbon stored in wetlands is much greater than all other land surfaces. The purpose of this study was to estimate soil organic carbon stocks (SOCS) and investigate spatial distribution pattern of Yuksekova wetlands and surrounding lands in Hakkari province of Turkey using machine learning and remote sensing data. Disturbed and undisturbed soil samples were collected from 10-cm depth in 50 locations differed with land use and land cover. Vegetation, soil, and moisture indices were calculated using Sentinel 2 Multispectral Sensor Instrument (MSI) data. Significant correlations (p≤0.01) were obtained between the indices and SOCS; thus, the remote sensing indices (ARVI 0.43, BI -0.43, GSI -0.39, GNDI 0.44, NDVI 0.44, NDWI 0.38, and SRCI 0.51) were used as covariates in multi-layer perceptron neural network (MLP) and gradient descent-boosted regression tree (GBDT) machine learning models. Mean absolute error, root mean square error, and mean absolute percentage error were 3.94 (Mg C ha ^-1), 6.64 (Mg C ha^-1), and 9.97%, respectively. The simple ratio clay index (SRCI), which represents the soil texture, was the most important factor in the SOCS estimation variance. In addition, the relationship between SRCI and Topsoil Grain Size Index revealed that topsoil clay content is a highly important parameter in spatial variation of SOCS. The spatial SOCS values obtained using the GBDT model and the mean SOCS values of the CORINE land cover classes were significantly different. The land cover has a significant effect on SOC in Yuksekova plain. The mean SOCS for continuously ponded fields was 45.58 Mg C ha^-1, which was significantly different from the mean SOCS of arable lands. The mean SOCS in arable lands, with significant areas of natural vegetation, was 50.22 Mg C ha^-1 and this amount was significantly higher from the SOCS of other land covers (p<0.01). The wetlands had the highest SOCS (61.46 Mg C ha^-1), followed by the lands principally occupied by natural vegetation and used as rangelands around the wetland (50.22 Mg C ha^-1). Environmental conditions had significant effect on SOCS in the study area. The use of remote sensing indices instead of using single bands as estimators in the GBDT algorithm minimized radiometric errors, and reliable spatial SOCS information was obtained by using the estimators. Therefore, the spatial estimation of SOCS can be successfully determined with up-to-date machine learning algorithms only using remote sensing predictor variables. Reliable estimation of SOCS in wetlands and surrounding lands can help understand policy and decision makers the importance of wetlands in mitigating the negative impacts of global warming.

Topsoil Carbon Stocks in Urban Greenspaces of The Hague, the Netherlands

Urbanization influences soil carbon (C) stocks and flows, which, in turn, affect soil-derived ecosystem services. This paper explores soil C storage in urban greenspaces in the Dutch city of The Hague along a transect from the suburban seaside towards the city centre, reflecting a toposequence from dune to peaty inland soils. C storage and C mineralisation potential were evaluated in relation to soil type and greenspace categories. Several soil-quality characteristics were measured, including dissolved organic C, pH, electrical conductivity, nitrogen, phosphorus, sulphur, calcium carbonate, and the water-holding capacity of the soil to evaluate what drives soil C storage in the urban context. The total SOC storage of the upper 30 cm of the greenspaces in The Hague (20.8 km2 with 37% greenspace) was estimated at 78.4 kt, which was significantly higher than assumed given their soil types. Degradability of soil organic matter in laboratory batch tests varied between 0.2 and 3 mg C gSOC−1 day−1. Degradability was highest in the seaside dune soils; however, extrapolated to the topsoil using the bulk density, topsoil C mineralization was higher in the urban forest. Soils beneath shrubs appeared to be hotspots for C storage, accounting for only 13% of the aerial cover but reflecting 24% of the total C storage. Land ownership, land use, greenspaces size, litter management and soil type did not result in significantly different C stocks, suggesting that processes driving urban soil C storage are controlled by different factors, namely land cover and the urbanization extent.

Impact of Anthropogenic Pressure on Physico-chemical Characteristics of Forest Soils of Kashmir Himalaya

The present study was carried out during the years 2017-2018 and assessed the impact of anthropogenic activities on the physico-chemical characteristics of soil in the Kashmir Himalaya. At disturbed sites anthropogenic activities like deforestation, grazing, tourism, urbanization, traffic etc. are seen prominent and their effect on soil environment resulted in less vegetation cover and exhibited diminution in organic matter. There was a significant increase in moisture content (21.13 ± 1.51), organic carbon (2.65% ± 0.52%), available nitrogen (493.790 ± 2.105 kg/ha), and potassium (432.727 ± 1.738 kg/ha) at undisturbed area Baerabal Harwan. However, there was a reduced pH (5.39 ± 0.230) and available phosphorus (18.993 ± 1.370) at undisturbed area in contrast to disturbed sites. Significantly higher values of Fe, Cu, Zn and Ni were found in disturbed areas (46.33 ± 0.16, 3.972 ± 0.001, 2.224 ± 0.003 and 1.7033 ± 0.002 ppm) respectively. The present findings could be helpful in formulating conservation strategies of soil at disturbed areas that are affected by anthropogenic activities which effects the soil microbial health of the forest soils. The study therefore indicated the need for employing best forest management and effective enforcement with vigorous reforestation programmes and would be a way forward towards mitigating the ongoing deterioration of the plant-soil system, sustaining forest productivity and soil fertility in the long run, and protecting people's livelihoods.

Assessing Carbon Storage Potential of Forested Wetland Soils in Two Physiographic Provinces of Northern Virginia, USA

This study assessed the soil carbon storage potential in terms of the total carbon (TC) and total carbon stocks (TC stocks) and associated soil physicochemical properties (i.e., soil pH, bulk density (Db), and gravimetric soil moisture (GSM)) for four forested wetlands in the urbanized region of Northern Virginia (NOVA). The study sites were balanced between the two physiographic provinces of the region (Piedmont vs. Coastal Plain); at each site, soils were sampled and analyzed (n = 180) at three depth intervals (0–10 cm; 10–20 cm; 20–30 cm). There was no significant difference in TC stocks between physiographic provinces (p > 0.05); however, wetland soils had higher TC contents at the Coastal Plain (4.32 ± 0.41%) than in Piedmont (2.57 ± 0.22%; p < 0.05). Both Db and GSM significantly differed by physiographic province and were highly correlated to TC, indicating that the TC variability is strongly explained by Db (R2 = 0.38) or GSM (R2 = 0.39), respectively (p < 0.01 for all). These outcomes highlight the capacity of urban forested wetlands to store carbon, especially in their topsoil (top 10 cm). Elucidating the carbon storage potentials of forested wetlands in an urbanized landscape may assist with future efforts to combat urban carbon emissions.

Natural versus urban global soil organic carbon stocks: A meta-analysis

Increasingly, the human existence in urban environments is growing. In addition, anthropogenic activity has altered the global carbon (C) cycle and triggered climate change. Soil is the largest pool of organic C in terrestrial ecosystems, but its ability to retain and store C varies. As humans move forward to mitigate climate change, there is a growing need to understand the C storing capacity of soils and their interactions with factors like climate, vegetation or a footprint of human activity. Here, we constructed a meta-analysis which focused on 30 cm soil depth by collecting data from over 191 studies measuring soil organic carbon (SOC) stocks across natural, urban green space, and urban intensive habitats. We then compared the SOC data between different climatic zones, vegetation types, and anthropogenic influences with the human footprint index. The results indicate that SOC stocks in natural habitats (98.22 ± 49.10 Mg ha^-1) are significantly higher than those of urban green spaces (54.61 ± 22.02 Mg ha^-1) and urban intensive habitats (65.88 ± 35.27 Mg ha^-1). We find a significant and negative relationship between the human footprint and SOC stocks of natural habitats but not between the human footprint and either of the urban habitats. Urban intensive and urban green space habitat soils store less C than natural ones. However, when compared across climatic zones or vegetation types, the capacity of natural soils to store C is variable and vulnerable to human activity. Carbon storage in urban soils is likely limited by persistent and stable anthropogenic influences keeping variability low. This is most pronounced in urban green spaces where human management is high (i.e. a golf course) and SOC is low. A comprehensive understanding of C storage in soils is essential to land management and climate mitigation measures.

Drivers of Organic Carbon Stocks in Different LULC History and Along Soil Depth for a 30 Years Image Time Series

Soil organic carbon (SOC) stocks are a remarkable property for soil and environmental monitoring. The understanding of their dynamics in crop soils must go forward. The objective of this study was to determine the impact of temporal environmental controlling factors obtained by satellite images over the SOC stocks along soil depth, using machine learning algorithms. The work was carried out in São Paulo state (Brazil) in an area of 2577 km2. We obtained a dataset of boreholes with soil analyses from topsoil to subsoil (0–100 cm). Additionally, remote sensing covariates (30 years of land use history, vegetation indexes), soil properties (i.e., clay, sand, mineralogy), soil types (classification), geology, climate and relief information were used. All covariates were confronted with SOC stocks contents, to identify their impact. Afterwards, the abilities of the predictive models were tested by splitting soil samples into two random groups (70 for training and 30% for model testing). We observed that the mean values of SOC stocks decreased by increasing the depth in all land use and land cover (LULC) historical classes. The results indicated that the random forest with recursive features elimination (RFE) was an accurate technique for predicting SOC stocks and finding controlling factors. We also found that the soil properties (especially clay and CEC), terrain attributes, geology, bioclimatic parameters and land use history were the most critical factors in controlling the SOC stocks in all LULC history and soil depths. We concluded that random forest coupled with RFE could be a functional approach to detect, map and monitor SOC stocks using environmental and remote sensing data.

Urbanization drives convergence in soil profile texture and carbon content

Urban development has driven extensive modification of the global landscape. This shift in land use and land cover alters ecological functioning, and thereby affects sustainable management agendas. Urbanization fundamentally reshapes the soils that underlay landscapes, and throughout the soil profile, extends impacts of urbanization far below the landscape surface. The impacts of urbanization on deeper soils that are beyond the reach of regular land management are largely unknown, and validation of general theories of convergent ecosystem properties are thwarted by a dearth of both level of measurement effort and the substantial heterogeneity in soils and urban landscapes. Here, we examined two soil properties with strong links to ecological functioning-carbon and mineral-fraction particle size-measured in urban soils, and compared them to their pre-urbanization conditions across a continental gradient encompassing global soil diversity. We hypothesized that urbanization drove convergence of soils properties from heterogeneous pre-urban conditions towards homogeneous urban conditions. Based on our observations, we confirm the hypothesis. Both soil carbon and particle size converged toward an intermediate value in the full data distribution, from pre-urban to urban conditions. These outcomes in urban soils were observed to uniformly be fine textured soils with overall lower carbon content. Although these properties are desirable for supporting urban infrastructure (e.g. buildings, pipes), they constrain the potential to render ecosystem services. Since soil profile texture and carbon content were convergent and observed across 11 cities, we suggest that these property profiles can be used as a universal urban soil profile to: 1) provide a clear prediction for how urbanization will shift soil properties from pre-urban conditions, 2) facilitate the adoption of commonly-accepted soil profiles for process models, and 3) offer a reference point to test against urban management strategies and how they impact soil resources.