Spatial Patterns and Risk Assessment of Heavy Metals in Soils in a Resource-Exhausted City, Northeast China.

Northeast China is an intensive area of resource-exhausted city, which is facing the challenges of industry conversion and sustainable development. In order to evaluate the soil environmental quality influenced by mining activities over decades, the concentration and spatial distribution of arsenic (As), cadmium (Cd), chromium (Cr), copper (Cu), nickel (Ni), lead (Pb), and Zinc (Zn) in surface soils (0-20cm) of a typical resource-exhausted city were investigated by analyzing 306 soil samples. The results showed that the average concentrations in the samples were 6.17 mg/kg for As, 0.19 mg/kg for Cd, 51.08 mg/kg for Cr, 23.27 mg/kg for Cu, 31.15 mg/kg for Ni, 22.17 mg/kg for Pb, and 54.21 mg/kg for Zn. Metals distribution maps produced by using the inverse distance weighted interpolation method and results revealed that all investigated metals showed distinct geographical patterns, and the concentrations were higher in urban and industrial areas than in farmland. Pearson correlation and principal component analysis showed that there were significant positive correlations (p<0.05) between all of the metals, and As, Cd, Cr, Mn, Ni, Pb, and Zn were closely associated with the first principal component (PC1), which explained 39.81% of the total variance. Cu and As were mainly associated with the second component (PC2). Based on the calculated Nemerow pollution index, percentage for slightly polluted (1<P ≤ 2) surface soils were reached 57.33%, while 42.65% topsoil samples are moderate polluted (2<P≤ 3). According to the results above-mentioned, different soil environmental function areas were classified and proper soil environmental management policy was proposed to decrease the environmental risks in the process of industrial city transformation.

Introduction

Due to the non-renewable characters and cumulative effects of mineral resource, many mining cities are facing the crisis of resource exhaustion, and their development also face many difficulties[1]. In order to transit smoothly from industrial society to post-industrial society, and create a certain competitive and livable city, lots of resource-exhausted cities have transformed or are transforming. Therefore, the problem of how to fasten economy transformation and social development for the resource-exhausted mine city has been a hotspot nowadays.

Northeast China has rich mineral resources, fertile land, and a strong industrial base and has made great contribution to the construction of new China[2]. However, like the most resource-based cities, with the exploitation of resources and the gradual reduction of resource reserves, mining zones whose developments mainly depend on their own resources are facing downfalls[3]. In the meantime, abandoned mines, land subsidence, water pollution, hills of gangue and flyash by years of industrial and mining production in these cities cause the destruction and waste of resources, ecological degradation, and damage to the environmental landscape[4]. The transition of resource-based cities has become an irreversible trend in Northeast China. As the most important coal resource-exhausted city in northeast China, Fuxin city is the first pilot city of economic transition in China.

Fuxin is an important mineral-rich region in China. About 43 minerals are found in Fuxin, the dominant minerals extracted being coal, silica sand, zeolite, marble, and gold. Taking coal as an example, the cumulative amount of coal that has been produced in Fuxin has been estimated to be up to 600 million ton, and 790 million ton of coal reserves remain. Coal has been mined in Fuxin for more than 50 years, and these mining activities have produced 2667 ha of mining wasteland and 4,000 ha of spoil heaps. The development of coal resources brought great economic benefit, but caused a series of ecological and environmental problems such as mining subsidence and soil damage. According to the government policy and its development situation, Fuxin city has gradually stepped into the period of industrial transformation. Except mining industry, agriculture is the second pillar industry in Fuxin city. There are 7730km2 farmland in Fuxin, and 5.5 billion marketable grains are produced every year. With the course of the constantly industry transformation, modern agriculture has become the most important developing direction in Fuxin. Some land surrounding the mining area or urban area may be used as the agriculture soil. However, there is little research on the soil environmental quality in Fuxin.

As an important part of the environment, soil is very sensitive to environmental changes[5]. Long-term mining production and rapid urbanization have led to increasingly serious soil pollution problems in coal resource-exhausted city inevitably. The pollution of soils with heavy metals is the most notable of these problems [6], and it is directly related to food security and the human health [7, 8]. The contamination incident called “cadmium rice”, which occurred in China, illustrates the ecological risks posed by heavy metals, and these risks have become of global concern [9, 10]. Therefore, it is necessary to study the heavy metal pollution in soil and assess its potential ecological risk to the agricultural products and human health[11].

Heavy metal contamination can be assessed using various methods and criteria. The main assessment method that is used is the analysis of the spatial distributions of contaminants in a region [12], and this involves assessing the soil quality and locating the pollution sources[13] The complexities of and interactions within datasets have led to multivariate geostatistical and geographic information system methods being widely used to extract the most meaningful information from a dataset without losing useful information. Surveys of the concentrations of potentially toxic elements in soils provide the fundamental information required for environmental planning and management processes, so such surveys have been conducted in some regions in recent years [14,15]

The objectives of the research presented here were to (1) estimate the concentrations of heavy metals in surface soils in Fuxin, (2) determine the spatial distribution patterns of the heavy metal concentrations and the degree to which the soil is polluted with the heavy metals, and (3) assess the quality of the soil environment and potential risk, and provide appropriate soil environmental management measures for the cities in transition.

Materials and Methods

2.1 Study area

Fuxin is in an important mineral-rich region in Northeast China, and has a total area of 10355 km2, extending from 41° 41′ 19.52″ N to 42° 50′ 39.52″ N and from 121° 2′ 17.78″ E to 122° 58′ 33.81″ E (Fig 1). Fuxin is in the intergradational zone between the Inner Mongolian Plateau and the Liaohe River Plain, and it has a northern temperate continental monsoon climate. The main soil types, cinnamon soil is calcium carbonate’s leaching, illuviation and humification genesis with thin humus layer and middle or thick solum.

Fig 1

Location of Fuxin City in Liaoning Province, northeastern China and the sampling sites.

2.2 Sampling and chemical analysis

The authority responsible for the local government. No specific permissions were required for sampling the soil in the study area because the location is not privately-owned or protected in any way and these are no endangered or protected species in the soil sampled. A total of 306 soil samples were collected between October 2012 and May 2013 (Fig 1). A uniform grid method was used to determine the sampling sites in the general sampling area, using a regular 8 km × 8 km grid for arable land, a 16 km × 16 km grid for forested land, and a 40 km × 40 km grid for unused land. Moreover, the density of sample point was increased surrounding the urban area and industrial and mining enterprises. The locations of the sampling sites were determined using a hand-held global positioning system. Samples of soil from the soil surface to 15 cm deep were collected using a small shovel [16]. At each sampling site, soil samples (0–20 cm) were taken from five points, distributed as an ‘S’, and then the samples were fully mixed to form one sample. The samples were transferred to the laboratory, air-dried at room temperature for 10 d, and then sieved through a 2 mm mesh. The soil samples were then stored in glass bottles at 4°C until they were analyzed.

The heavy metals were extracted from the soil samples by microwave assisted acid digestion. A subsample of each soil was digested in 8 mL 65% nitric acid, 5 mL 30% hydrogen peroxide, and 3 mL 30% hydrofluoric acid[17], then the extract was evaporated to near dryness, and 10 mL Milli Q water was added. The extract was then stored in a 10 mL polyethylene vial at 4°C until it was analyzed. Triplicates were used for extracting each sample. The concentrations of the heavy metals were measured by ICP-OES (PE OPTIMA3000). The quality control measures that were taken were to 1) analyze 20 randomly selected samples and 9 national standard samples and 2) reanalyze a random selection of samples to ensure that the mean deviation between replicate analyses was less than 3%.

2.3 Data processing

Descriptive statistical parameters were calculated using the SPSS 19.0 software package. Pearson's correlation coefficient analysis and principal component analysis (PCA) were performed to identify relationships between the heavy metal concentrations in the soil samples and to identify the possible sources of the heavy metals [18].

2.4 Geostatistical methods

The spatial interpolation technique predicts values for cells in a raster from a limited number of sample data points. Interpolation is the process of predicting the values of an attribute at unsampled sites[19]. Unlike classic modeling approaches, spatial interpolation methods incorporate information about the geographic positions of the sample points [20]. The rationale behind spatial interpolation is that parameters for points that are close to each other are more likely than parameters for points further away to correlate and show similarities[21]. In the study presented here, the ordinary kriging method was used to determine the spatial distribution patterns for individual heavy metals and radial basis functions to express the Nemerow synthetic pollution index.

2.5 Pollution index method

The Nemerow pollution index was used to assess the quality of the soil environment across the sampling area. The Nemerow synthetic pollution index is widely applied to reflect the total pollution level and evaluate environmental quality. This method not only considers the average condition of the single-factor pollution index but also integrates its maximum. The heavy metal concentrations were examined to assess the soil pollution status against the Chinese Soil Quality Criterion GB 15618–2008 [22]. A single-factor pollution index was used to evaluate the presence of a specific metal and to assess the pollution levels in the sampling area. However, the Nemerow synthetic pollution index was used to reflect the overall pollution situation caused by the simultaneous presence of a number of metals [23]. The Nemerow index was calculated as shown below.

The single-factor pollution index was defined as P = C / S , where C is the measured pollutant concentration and S is the natural background concentration of the pollutant.

The Nemerow synthetic pollution index was defined as P N = { [(Ci / Si)max 2 + (Ci / Si)ave 2] / 2}, where P N is the synthetic pollution index, (Ci / Si)max is the maximum pollution index value for all of the pollutants, and (Ci / Si)ave is the average pollution index value for all of the pollutants.

The P value indicates the degree of pollution, and the classifications used were: P ≤ 1, soil has not been contaminated; 1