Mass balance-based regression modeling of Cd and Zn accumulation in urban soils of Beijing
Graphical abstract
Introduction
With increased urbanization, many potentially hazardous heavy metals such as Cd and Zn are released to near human habitats by transportation, coal use and resource consumption (Kong et al., 2011, Maas et al., 2010). Accumulation of heavy metals in urban soils has drawn great attention as it poses adverse impacts on public health and threatens the integrity of terrestrial ecosystems, plants and soil microbes (Maliszewska-Kordybach and Smreczak, 2003). The distribution patterns of heavy metals in urban soils have been broadly delineated (Wang et al., 2012a, Wei and Yang, 2010). However, the static spatial distributions of heavy metals in soil are inadequate to understand their complex accumulation processes and their ever changing emission sources in terms of urbanization progression.
Heavy metal accumulation in urban soil is complex and a dynamic process (Wong et al., 2006). Atmospheric deposition is the main influx of persistent pollutants accumulating in urban soils (Moller et al., 2005, Peng et al., 2012). Airborne heavy metals are emitted from diffused and scattered sources such as commercial establishments, traffic networks, and residential activities (Ajmone-Marsan and Biasioli, 2010, Xia et al., 2011). After they are released, pollutants from various sources may mingle with the wind and form a regional blanket baseline atmospheric deposition for a given urban area (Peng et al., 2013). This baseline input causes an increase of metals in urban soils which increase over time as the urban system continues to develop. Unfortunately, the long-term metal deposition fluxes were not recorded in the most of cities. The losses of heavy metals from soils are mainly caused by solute leaching, plant uptake and physical disturbance (Keller et al., 2001, Pouyat et al., 2007). The transport fluxes of heavy metals in soils are not easily measured and are impacted by soil pH, soil organic matter and physical disturbance (Mahanta and Bhattacharyya, 2011, Wang et al., 2011). The annual increments of heavy metal concentrations in urban soils are small and not readily detectable using short-term sampling and monitoring (Sun et al., 2011), while long-term in situ monitoring records of soil metals are often unavailable because soil environmental quality surveys are laborious and time-consuming (Cheng et al., 2014). Consequently, it is difficult to establish the time-dependent heavy metal accumulation pattern and to systematically predict the future trends using conventional soil surveys.
Historical trend of heavy metals accumulation in soil can be reconstructed by measuring the heavy metal contents in bricks manufactured at different time periods, moss/leaf collections from museums, downstream sediments, and sectioned soils layers (Cao et al., 2008, Liu et al., 2005, Rodríguez Martín et al., 2015, Shrivastav et al., 1998, Zhang et al., 2005). However, these approaches are only applicable to estuarine and coastal areas or at geologic timescales. None of those approaches is able to deduce the metal deposition patterns that have evolved through urban development.
Long term changes of heavy metals in soils can be modeled if the pathways and mass flows are properly quantified and validated (Chen et al., 2007). Previous studies adopted mass balance model to simulate the long term trends of heavy metal accumulation in agricultural soils (de Vries and McLaughlin, 2013, Oporto et al., 2012, Six and Smolders, 2014). However, those models require detailed information on metal input loads, soil properties, and plant growth and hydrogeological data. Qian and Follett (2002) described the changes of soil organic matter over a 45 year period based on the building age of the sampling golf courses using a quadratic with plateau model. Peng et al. (2015) introduced a mass balance-based nonlinear regression model to simulate the historical and future changes of polycyclic aromatic hydrocarbons in urban soil. The time series data of pollutant concentrations were obtained using a sampling strategy of trading space for time. Similarly, the mass balance of heavy metals accumulation in soils can be tracked with nonlinear regression model approach. For back casting, the pollution history may be revealed, and the impacts of urban expansion and industrialization on metal emissions can be evaluated. For forecasting, the future trends of metal concentrations in urban soil may be predicted, and the critical loads of emission sources can be established. These forecasts can be used to establish policies that prevent heavy metal accumulations that exceed health risk thresholds (Posch and de Vries, 2009).
Beijing has experienced a rapid urbanization in past decades. Since 1978, the population of Beijing grew from 8.7 to over 20.0 million and the total coal consumption has doubled (BSB, 2009) (Fig. 1). As a result, the heavy metal emissions of urban Beijing have increased over time (Chen et al., 2005). Okuda et al. (2008) reported clear trends of increasing Cd, Cu, Pb and Zn levels in the total suspended particles in Beijing from 2001 to 2006. Wang et al. (2005) found increasing Cu, Zn, As, Ba and Pb concentrations in the growth rings of trees during 1982 to 2004 in a suburban area of Beijing. In summary, the urban renewal and expansions have shifted the patterns of heavy metals deposition as well as their concentrations in the air, plant, and soil.
The objective of this research is to uncover the long-term trends of Cd and Zn accumulation in urban soils, which are expected to be closely related to urban activities, especially traffic and coal combustion in urban areas. A mass balance-based regression model is developed to delineate the dynamic changes of heavy metal in urban soils for yearly changes to inputs and outputs. The heavy metal concentrations in soils of urban green spaces with different building age are used to develop a model of heavy metal accumulation in soils. We then used the model to simulate the concentrations of Cd and Zn in urban soil of Beijing from 1978 to 2078. Uncertainties associated with model simulations are discussed.
Section snippets
Mass balance approach
For heavy metal accumulation in urban surface soil, the mass balance is given by Chen et al. (2007) s following:where, M(t) (mg/kg) is the metal content per unit soil mass. I (mg/kg/year) and L (mg/kg/year) represent annual input and output fluxes per unit soil mass, respectively.
For the first year, we assume that the soil receives an input of metal, I0 (mg/kg/year). During the course of urbanization, this baseline input would change over time according to population, traffic and
Data collection
Data on Cd and Zn concentrations in the urban soils from 68 residential green spaces inside the 5th ring road of Beijing were collected. These data have been previously reported (Peng et al., 2013). The sampled residential areas are spatially distributed in the urban center of Beijing, surrounded by high traffic density and population (Appendix A Figs. S1 and S2). These residential areas were enclosed by containment walls and separated from surrounding landscape. Therefore, the heavy metals in
Descriptive statistics of dataset
Table 1 summarizes the concentrations and background values of Cd and Zn in soils of Beijing. The mean concentrations of Cd and Zn in the residential soils of urban Beijing were 0.106 and 88.540 mg/kg respectively, which were considerably higher than that in the deep soils and rural soils of Beijing (Cheng et al., 2014, Luo et al., 2010). The previously reported soil background values of Cd and Zn showed large variances (Table 1). Those background values would fluctuate between sampling sites
Conclusions
We demonstrated that the mass balance-based regression model was able to describe the general trends of heavy metal concentration in Beijing urban soils. Data of residential soils installed at different location and times could be used for substituting long-term in situ monitoring data, and to reconstruct the pollution history of heavy metals in urban soils. Based on the regression estimates, we forecasted the accumulation and uncertainties of Cd and Zn in urban soils of Beijing. Concentrations
Acknowledgment
This work was supported by the National Natural Science Foundation of China (No. 41401588). The author Chi Peng is supported by the State Scholarship Fund organized by China Scholarship Council. He also appreciates the support from the Brook Byers Institute for Sustainable Systems, Hightower Chair, and the Georgia Research Alliance at the Georgia Institute of Technology.
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