Evaluation of effect of phytoremediation of heavy metal pollution in farmland soils around a lead-zinc mine, Southwest China

doi:10.21203/rs.3.rs-3630840/v1

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Evaluation of effect of phytoremediation of heavy metal pollution in farmland soils around a lead-zinc mine, Southwest China

https://doi.org/10.21203/rs.3.rs-3630840/v1

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Environmental pollution by heavy metals in mining areas is a major concern worldwide since it affects surrounding farmland soils as well as the food chain and human health. Phytoremediation is amongst the low cost and environment friendly method proposed to clean up heavy metals from contaminated soils. In this study, we investigate the farmland soils of the Sidi village in Xingping Town, Yangshuo County, Guilin City, Guangxi Zhuang Autonomous Region, which were contaminated by nearby abandoned lead-zinc mine. The contents of heavy metals (As, Cd, and Pb) in these soils have severely exceeded the threshold local values according to the China national standard GB15618-2018. It is therefore urgent to carry out effective remediation of soils polluted by heavy metals to ensure safety of crop production in farmland soils of this region. Hyperaccumulator plants and plant barrier were adopted to reduce the content of heavy metals in soils of slightly polluted areas. The contents of As, Cd, and Pb in soils of moderately polluted areas were reduced by using passivator combined with low heavy metal accumulation crops. Rotation of oilseed rape and oil sunflower has continuously prevented metal pollution in heavily polluted areas. After 15 months of remediation, the pH values of soils in all polluted areas were gradually changing from weakly acidic to near-neutral pH, which met the requirements for crop planting. This study provides a scientific reference to apply remediation methods for polluted soils by heavy metals for the restoration of ecological environment of farmland soils around lead-zinc mine.

Lead-zinc mine

Heavy metal pollution

Farmland soils

Phytoremediation

Ecological restoration

Heavy metals released into the environment are common during mining activities, and they have adverse effects on the environmental and human health (Arora et al. 2008; Khan et al. 2010; Ali et al. 2013). Environmental pollution of soil by heavy metals around mining areas has thus become a worldwide concern since it affects the soil ecosystem and water resources, which endanger the crop productivity and food chain (Zuo et al. 2023). Scholars have proposed innovative physical, chemical, and biological approaches in order to clean up heavy metals in contaminated soils (Suresh and Ravishankar 2004; Turan and Esringu 2007; Lone et al. 2008; Kawahigashi 2009; Sheoran et al. 2011; Wuana and Okieimen 2011). Although physical and chemical remediation methods are fast, they bear limitations such as intensive labor and high cost as well as secondary pollution issues, ecological disturbance, and irreversible changes (Ali et al. 2013). In contrast, the bioremediation is an alternative method which is efficient, low cost, and environment friendly (Mejáre and Bülow 2001; Alkorta et al. 2004; Lai and Chen 2004; Mesjasz-Przybylowicz et al. 2004; Zhuang et al. 2005, 2007; Jadia and Fulekar 2008; Krystofova et al. 2009; Van Aken 2009; Adesodun et al. 2010; Zhao et al. 2011; Ali et al. 2013; Zhang et al. 2023). With low installation and maintenance costs, the bioremediation approach is suitable for application at very large field sites where other remediation methods are not cost effective or practicable (Garbisu and Alkorta 2003).

There are more than 700 lead-zinc (Pb-Zn) mines in China, covering 27 provinces, mostly located in southern region. Soil heavy metal pollution generally occurs around the Pb-Zn mining areas of South China, where tailings and river sewage irrigation release diverse heavy metals (e.g., As, Pb, Cd, and Zn) into the surrounding farmland soils (Zuo et al. 2023). For instance, the Pb-Zn mining soils of the Puding County in Guizhou Province have recorded mean levels of Pb, Zn, Cd, and As, which are 14.5, 7.8, 5.5, and 4.4 times, respectively, higher than the background values of soils from this area, with highest contents of Pb, Zn, Cd, and As of 1476.00, 5036.00, 7.53, and 225.00 mg⋅kg^− 1, respectively (Zuo et al. 2023). Since agricultural soils in the Pb-Zn mining areas have suffered from various levels of heavy metal contamination, it is utmost necessary to reduce the environmental risks and impacts on the morphological and physiological changes in soil composition and soil microbiota. The application of bioremediation on such contaminated soils has the effect to reduce the risk of toxicity to crops as well as to restore cultivated pastures on soil properties and soil bacterial communities (Zuo et al. 2023).

The Yangshuo Pb-Zn mine has a long mining history in the Guangxi Zhuang Autonomous Region in southern China (Fig. 1a). Since the cadmium pollution accident in 2012 on the Longjiang River of Guangxi, the mining production has been suspended. The mining activities have released heavy metal pollutants (e.g. Cd, Pb, and As) into the streams, which led to heavy metal pollution of more than 0.933 km² surrounding the farmland soils of the Sidi Village in the northeast part of Guangxi. This study focuses on the remediation of As, Pb, and Cd in contaminated farmland soils of the Sidi village, which were subjected to a comprehensive treatment during 15 months. Thus, the main purposes of this study are presented as follows: (1) to compare the metal extraction of different remediation methods in distinct polluted areas, (2) assess the phytoextraction efficiency of Cd, Pb, and As with the application of these remediation methods, (3) to establish a comprehensive system remediation system of contaminated soils of the Sidi village based on the remediation, safe utilization, and planting structure adjustment. This aims to solve the problem of heavy metal-polluted soils as well as to improve the soil fertility, reduce the environmental risks resulting from Pb-Zn mining activities, and ensure a high-quality of agricultural products. The present study further serves as a scientific reference for the remediation of the same type of contaminated soils in southwestern China, which can provide an efficient environment-friendly guidance for the decontamination of heavy metal-polluted farmland soils elsewhere.

Study area

The study area is located in the Sidi village of Yangshuo County, Guilin City, with predominant geology composed of sandstone, shale, limestone, marl, and siliceous and carbonate rocks (Fig. 1b). The terrain is diverse and comprises hills, low and rocky mountains, and flat terraces, with land elevation ranging from 20 to 200 m above sea level. The study area belongs to the subtropical monsoon zone characterized by cold dry winter and heavy rainfall and hot sunshine in summer. The annual precipitation varies between 809.5 and 2443.9 mm, while the mean annual temperature ranges from 18 to 38 ℃. Soil types include red loam, loamy loam, sandy loam, calcareous, and rice soils. Land use is dominated by forest land and dry land. The main economic activity of the study area is agriculture.

A large number of data (546 samples including soil, water, agricultural products) were collected from previous studies conducted between May 2013 and December 2017 in the Sidi village (GUT 2018). Combined with this previous work and the results of chemical analyses on 375 soil tilled layer samples collected from the Sidi village, the comprehensive pollution index (Hu et al. 2021) was calculated following the method of the Chinese national standard of soil environmental quality GB15618-2018. The comprehensive pollution index of 1–2, 2–5, and > 5 correspond to the slightly, moderately, and heavily polluted sites, respectively, which occupy an area of 0.1443 km², 0.289 km², and 0.313 km², respectively (Fig. 1c).

Experimental design

According to the socio-economic conditions, soil type, and agricultural practice of the study area, this study adopts different remediation methods for each polluted area, which are shown in Table 1 and Fig. 1c. For the slightly polluted area (0.1443 km²), two methods were applied including the hyperaccumulator plants adopted for the slightly Cd-polluted area (0.0333 km²) using Amaranthus hypochndriacus, Celosia argentea, Hylotelephium erythrostictum, and the low heavy metal accumulation plants for the remaining 0.111 km² area using Helianthus annuus, Zea mays, and rape crop rotation, supplemented by agronomic control measures (Zu and Li 2003). Activator was applied once a year in the slightly Cd-polluted area to accelerate the effect of cadmium removal on these plants. For the moderately polluted area (0.289 km²), the fruit trees (orange, grape, peach, and chestnut) and low heavy metal accumulation plants (Zea mays) were adopted in combination with passivator to reduce the effectiveness of heavy metals which have high economic value. For the heavily polluted area (0.313 km²), oily plants such as ornamental sunflower and oilseed rape were planted in combination with passivator.

Table 1

Summary of remediation methods for polluted sites
Site	Area	Remediation method	Species
Slightly polluted site	0.0333 km²	Hyperaccumulator plants + Activator	Amaranthus hypochndriacus, Celosia argentea, and Hylotelephium erythrostictum
Slightly polluted site	0.111 km²	Low heavy metal accumulation plants	Helianthus annuus, Zea mays, and rape crop
Moderately polluted site	0.289 km²	Low heavy metal accumulation plants + Fruit trees + Passivator	Orange, grape, peach, and chestnut + Zea mays
Heavily polluted site	0.313 km²	Oily plants + Passivator	Sunflower (Helianthus annuus) and oilseed rape (Brassica napus)

Sample collection and preparation

Soil and crop samples were collected from the polluted sites in 2019 and 2020, and the requirements and quantities of sample collection are shown in Table 2. Soil samples were taken in three batches before treatment in August 2019 (2019.8), during treatment in May 2020 (2020.5), and after treatment in November 2020 (2020.11). A soil composite sample of about 2 kg composed of 5 sub-soil samples was collected at every sampling site according to a plum-shaped distribution. Sub-soil sample of 5 cm thick and 10 cm wide was cut with a spade to remove plant roots and gravel. The sampling depth ranged from 0 to 20 cm.

A crop composite sample composed of 5 sub-crop samples was further collected at every sampling site using a diagonal distribution. Crops were sampled according to the maturity, pest, and weed occurrence. The time of collection of crop samples was determined according to the maturity of different varieties and within the context of the occurrence and control of pests, diseases, and weeds in crops.

Table 2

Remediation area, point distribution, and sampling quantity
Site	Method	Area (km²)	Type	Sampling time/quantity						Sampling requirement
				Before treatment		During treatment		After treatment
				2019.8	2019.10	2019.12	2020.05	2020.07	2020.11
Slightly Polluted area	Hyperaccumulator plant + Activator	0.033	Soil	25	-	-	25	-	25	1 point / 0.00133 km²
	Hyperaccumulator plant + Activator	0.033	Crops	25	-	20	-	31	10	-
	Low heavy metal accumulation crops	0.111	Soil	33	-	-	33	-	33	1 point / 0.00333 km²
	Low heavy metal accumulation crops	0.111	Crops	16	13	-	21	-	20	-
Moderately polluted area	Fruit trees, Low heavy metal accumulation crops + Passivator	0.289	Soil	43	-	-	43	-	43	1 point / 0.00667 km²
Moderately polluted area		0.289	Crops	44	11	5	-	-	40	-
Heavily polluted area	Oily plants + Passivator	0.313	Soil	24	-	-	24	-	24	1 point / 0.0133 km²
Heavily polluted area	Oily plants + Passivator	0.313	Crops	48	-	22	48	22	48	-

Laboratory analysis and data processing

375 soil samples were collected from the topsoil, which included 174, 129, and 72 samples from the slightly, moderately, and heavily polluted sites, respectively. All soil samples collected were stored in clean polythene bags, labeled, and transported to the laboratory. All collected soil samples were air-dried in the laboratory for one week. Each soil sample was divided into three subsamples. One subsample was sieved through 20-mesh sieve for soil pH analysis. Another subsample was sieved through 100-mesh sieve for determining the element avalaibility in soil, while the remaining subsample was sieved through 100 mesh or more for analysis of total content of heavy metals in soil.

The soil pH was measured using a potentiometric method of water-soil ratio of 2.5:1, with a pH meter (PHS-3C, Shanghai REX, China). The total content of Cd and Pb and their availability in soil were determined by atomic absorption spectrometry (AAS; Z-2010, Hitachi, Japan) following the method of the Chinese Agricultural Industry Standard 1613–2008 and the China national standard GB/T 23739 − 2009. The total content of As was determined by atomic fluorescence spectrometry (AFS-3000, Beijing Kechuang Haiguang Instrument Co., Ltd, China) following the method of the Chinese national standard GB/T 22105.2–2008, while the element availability was determined by inductively coupled plasma mass spectrometry (ICP-MS; Thermo Fisher Scientific, USA) according to the technical provisions for the analysis of soil samples for detailed investigation of soil pollution in China.

A total of 444 crop samples were collected including 156, 100, and 188 samples from the slightly, moderately, and heavily polluted sites, respectively. Crop samples were air-dried and ground with an onyx mortar so that all samples passed through a 40 µm nylon sieve. The samples were then mixed, digested, and filtered. Crop samples were analyzed by ICP-MS (Thermo Fisher Scientific, USA) following the method of the Chinese standard GB/T 5009.11–2014.

Data processing was done using Microsoft Excel and Origin 2018 software for statistical analysis and graphical plot, respectively. SPSS 22.0 software was used to perform correlation analysis.

Characterization of soil heavy metals

The statistical results for heavy metals in the farmland soils of slightly polluted areas show that the coefficients of variation of As, Cd, and Pb in slightly polluted areas before phytoremediation (August 2019) range between 0.47–0.49, 0.85–1.15, and 0.91–1.30, respectively (Table 3). It is noteworthy that the coefficients of variation of Pb and Cd were larger, while these elements had variable contents. Considering that there was an uneven distribution of the contents of Pb and Cd in different sampling points, contaminant might exist around some sampling points. The coefficient of variation of As was less than 0.50, which indicates that the As content in soil is well-distributed.

Table 3

Statistics of heavy metal content (mg/kg) of soils in slightly contaminated areas
Sampling time	Statistic item	As	Cd	Pb
2019.08	Range	5.15–28.91	0.27–7.76	22.29-571.58
	Average	14.24	1.11	92.79
	Standard deviation	6.7	1.06	98.2
	Coefficient of variation	0.47	0.95	1.05
2020.05	Range	5.05–32.06	0.23–10.13	33.95–757.1
	Average	15.47	1.2	88.16
	Standard deviation	7.32	1.38	114.24
	Coefficient of variation	0.47	1.15	1.3
2020.11	Range	5.47–33.36	0.30–7.95	33.86-600.24
	Average	14.69	1.25	92.95
	Standard deviation	7.28	1.07	84.54
	Coefficient of variation	0.49	0.85	0.91

The statistical results for heavy metals in soils from the moderately polluted area showed that the coefficient of variation was arranged in decreased order as following: Pb (1.32–1.58) > Cd (0.78–1.25) > As (0.33–0.36) (Table 4). The coefficient of variation of Pb was greater than 1, which indicated that the Pb distribution was not uniform in these soils, and was greatly influenced by human activities.

Table 4

Statistics of heavy metal content (mg/kg) of soils in moderately contaminated areas
Sampling time	Statistic item	As	Cd	Pb
2019.08	Range	5.36–21.81	0.09–2.16	34.52-629.89
	Average	11.89	0.61	77.76
	Standard deviation	4.08	0.52	113.94
	Coefficient of variation	0.34	0.86	1.46
2020.05	Range	3.78–21.97	0.04–2.15	26.50-568.10
	Average	12.22	0.67	72.02
	Standard deviation	4.08	0.52	113.94
	Coefficient of variation	0.33	0.78	1.58
2020.11	Range	4.54–22.17	0.01–5.8	31.23-658.76
	Average	11.14	1.20	70.83
	Standard deviation	4.04	1.50	93.86
	Coefficient of variation	0.36	1.25	1.32

According to the statistical results of heavy metals in the farmland soil of heavily polluted areas (Table 5), the coefficients of variation of heavy metal content in the soil were different before and after phytoremediation. The coefficients of variation before and during phytoremediation were in order of Cd (0.67–0.89) > Pb (0.51–0.60) > As (0.33–0.44), and the coefficients of variation after phytoremediation were in order of Pb (1.07) > Cd (0.58) > As (0.38). The coefficients of variation of Pb and Cd were greater than 0.5, and that of As was less than 0.50.This indicates that there was an uneven distribution of the contents of Pb and Cd, which were greatly influenced by human activities.

Table 5

Statistics of heavy metal content (mg/kg) of soils in heavily contaminated areas
Sampling time	Statistic item	As	Cd	Pb
2019.08	Range	5.32–24.04	0.20-13.18	41.56-1926.20
	Average	12.76	4.46	745.17
	Standard deviation	5.62	3.96	449.92
	Coefficient of variation	0.44	0.89	0.60
2020.05	Range	5.69–23.77	0.81–11.04	119.94-1817.88
	Average	12.57	5.10	857.35
	Standard deviation	4.22	3.43	440.22
	Coefficient of variation	0.33	0.67	0.51
2020.11	Range	4.71–23.87	0.62–10.05	126.99-2389.17
	Average	13.10	4.99	951.08
	Standard deviation	4.94	2.90	1017.44
	Coefficient of variation	0.38	0.58	1.07

According to Fig. 2, the maximum and average values of heavy metal contents in soils of slightly polluted areas after phytoremediation are higher than those before phytoremediation, hyperaccumulator plant in combination with activators and low heavy metal accumulation plants were adopted in this area, which might caused by the fact that adsorbed heavy metals were re-released owing to the plant decay. This explained that the soil sampled after plowing land was not the same as that before.

Low heavy metal accumulation plants or Pd-Cd passivator were adopted in soils of moderately polluted areas. The maximum and average values of contents of Pb and Cd in these soils after phytoremediation were higher than those before phytoremediation, and the passivator had obvious effect.

Adjustment of planting and restriction of land use were adopted in soils of heavily polluted area. The maximum and average values of contents of As and Cd in these soils after phytoremediation were lower than that before phytoremediation. The heavy metal content of Pb during phytoremediation was lower than that before phytoremediation, which indicates that this treatment method had certain effect. However the content of Pb after phytoremediation was higher than that before phytoremediation. It is suggested that these results might be caused by the fact that soil sampled after plowing land was not the same as that before.

After 15 months of phytoremediation, the average contents of As, Cd, and Pb in soils were decreasing. While monitoring some sampling points, the removal rate of heavy metals in soils increased then decreased, which might be caused either by the re-release of adsorbed heavy metals due to plant decay or by the presence of different layers of soils in collected samples as a result of deep plowing of land during the treatment. At the same time, secondary planting can be carried out according to the change of heavy metal contents in soils in order to obtain the best removal effect and improve the efficiency of phytoremediation.

Analysis of heavy metal availability in soil

In order to analyze the changes of heavy metal availibility in soils treated by Pb-Cd passivator in soils of the moderately polluted area, the availibility of As, Pb, and Cd in soil was monitored to evaluate the removal effect. The results of mean values for heavy metal availability indicate that the availability of Cd and Pb in these soils has decreased (Fig. 3). Cd availibility decreased from 0.265 mg/kg to 0.238 mg/kg with a reduction rate of 10.18%, while Pb availability decreased from 17.100 mg/kg to 12.860 mg/kg with a reduction rate of 24.82%. As availability increased from 0.05 to 0.16 mg/kg, which might result either from using inappropriate As passivator or from the enhancement of As availability by the Pb-Cd passivator. The results showed that the availability of Cd and Pb in soils was decreasing after the application of Pb-Cd passivator compared to that before remediation, suggesting that the Pb-Cd passivator had a more pronounced effect on the availability of Cd and Pb in soils.

Soil pH and nutrient analysis

Soil pH value is an important indicator of the soil quality, and it is useful to determine the activity of heavy metals in soils. Low pH value of soil increase the availability of heavy metals such as Pb and Cd, and it also increases the risk of heavy metal pollution in soils. Table 6 indicates that the soil pH in slightly polluted area was increasing with average value of 7.33 to 7.72 before and after phytoremediation, respectively. The average pH value of soil in the moderately polluted area was 6.05 and 6.25 before and after phytoremediation, respectively. The average pH value of soil in the heavily polluted area was 5.81 and 6.67 before and after phytoremediation, respectively. A comparative analysis of soil pH values for all polluted areas before and after phytoremediation indicated that these values were increasing, with the soil pH gradually changing from weakly acidic to near-neutral.

The soil nutrients alkaline dissolved nitrogen (N), available phosphorus (P), and exchangeable potassium (K) also changed with the increase of soil pH (Table 6). In heavily polluted area, alkaline dissolved N showed an increasing trend with the increase of pH, and available P and exchangeable K showed an increasing and then decreasing trend. In moderately polluted area, available P and alkaline dissolved N showed an increasing trend with the increase of pH, and exchangeable K remained unchanged. The results showed that the nutrient contents in soils after the treatment showed variable values with the increase of soil pH. The fertility of soil was regulated and improved to some extent.

Table 6

Statistics of soil pH and nutrient content in different contaminated areas (mg/kg)
Site	Sampling time	Statistic item	pH	Alkaline dissolved nitrogen	Available phosphorus	Exchangeable potassium
Slightly polluted area	2019.08	Range	5.3–8.23	67.48-202.13	8.99–95.4	52.61-340.63
	2019.08	Average	7.33	118.91	32.69	107.95
	2020.05	Range	5.32–8.24	64.24-156.88	9.8-301.12	40.04-266.99
	2020.05	Average	7.29	108.77	51.29	122.44
	2020.11	Range	5.88–8.27	1.35-503.08	12.12–849.5	13.38-402.43
	2020.11	Average	7.72	139.59	125.02	118.72
Moderately polluted area	2019.08	Range	4.65–8.16	40.54-121.75	11.98–114	57.16-247.48
	2019.08	Average	6.05	82.15	37.33	124.26
	2020.05	Range	5.19–7.62	53.38-155.76	1.19–283.4	47.19-278.95
	2020.05	Average	6.03	100.99	87.27	143.4
	2020.11	Range	5.18–7.74	0.93-125.06	42.7-2274.3	10.19–80.19
	2020.11	Average	6.25	10.83	1146.28	19.08
Heavily polluted area	2019.08	Range	5.14–8.01	67-108.02	10.29–84.56	94.27-165.54
	2019.08	Average	5.81	90.1	45.38	119.79
	2020.05	Range	5.44–7.93	9-137	45.02-184.25	56.16-158.91
	2020.05	Average	6.67	117.25	82.33	120.61
	2020.11	Range	5.24–7.48	53.42-480.12	3.86 ~ 94.44	23.44–154.9
	2020.11	Average	6.67	153.86	44.35	73

Analysis of heavy metal content in crops

The crops planted in different polluted areas are different. According to the end use of crops, the standards of food, feed, and fertilizer were used to evaluate the standard compliance rate of heavy metal content in crops. The statistical results are shown in Table 7. Since there is no evaluation standard for accumulator plants, they were not analyzed. Edible corns planted in slightly and moderately polluted areas reached a standard compliance rate of 100% after sampling in 2020. At the same time, oil extracted from the oilseed rape was edible, and the oil cake can be used as fertilizer, both of which reach a standard compliance rate of 100%. And the pulp from fruit trees planted in moderately polluted area was 100% edible. Due to the high concentration of heavy metals in soils in heavily polluted areas, feed corn was planted, and the standard compliance rate was 100%. The standard compliance rate of oil extracted from oilseed rape and oil sunflower reached 100%, however the standard compliance rate of oil residue or oil cake ranged between 71.4% and 91.7%, which was thought to be caused by deep ploughing. In slightly polluted areas, safety production can be realized by adopting accumulator plants and activator in combination with low heavy metal accumulation crops, while a combination of passivator and low heavy metal accumulation crops can be adopted in moderately polluted areas. In heavily polluted areas, safe use of polluted farmland soils can be realized by planting ornamental oil sunflower and ornamental rapeto control the risk of soil pollution.

Table 7

Statistics on heavy metal content and compliance rate of crops before and after treatment (mg/kg)
Site	Sample time	Plants	As	Cd	Pb	Compliance rate (%)
Slightly polluted area	2019.08	Zea mays	0.0003–0.0142	0.0026–0.1028	0.0045–0.2431	93.33
	2020.05	Oil-rape crop	0.0015–0.0102	0.0002–0.0032	0.0028–0.009	100
	2020.05	Oilcake-rape crop	0.0062–0.0203	0.1126–0.2963	0.0180–0.0895	100
	2020.07	Zea mays	0.0023–0.011	0.0060–0.0902	0.0062–0.048	100
	2020.11	Zea mays	0.0046–0.014	0.0023–0.0230	0.0057–0.0530	100
Moderately polluted area	2019.08	Zea mays	0.005–0.0142	0.0026–0.1028	0.0045–0.2431	95
	2019.10	Fruit	0.0002–0.0003	0.00008-0.00012	0.000-0.0021	100
	2020.11	Fruit	0.00076–0.0017	0.00003-0.00018	0.0084–0.061	100
	2020.11	Zea mays	0.0048–0.011	0.0019–0.0370	0.0085–0.018	100
Heavily polluted area	2019.08	Oil-Helianthus annuus	0.0042–0.0115	0.003–0.0197	0.0025–0.0692	100
	2019.08	Oilcake-Helianthus annuus	0.0278–0.0860	0.4446–9.1812	0.0111–0.8317	87.5
	2020.05	oil-rape crop	0.0004–0.0018	0.0006–0.0212	0.0179–0.0798	100
	2020.05	oilcake-rape crop	0.0050–0.0531	0.4243–3.2346	0.0580–3.5555	91.7
	2020.07	Zea mays feed	0.0061–0.1221	0.0079–0.1469	0.0565–1.235	100
	2020.11	Oil-Helianthus annuus	0.0071–0.0120	0.0006–0.0045	0.011–0.0480	100
	2020.11	Oilcake-Helianthus annuus	0.0095–0.0266	0.9218–6.6508	0.209–0.2566	71.4
Food¹		Zea mays grain	0.5	0.1	0.2	/
		oil	0.1	/	0.1	/
		fruit	/	0.05	0.1
Feed²		Zea mays feed	2	1	10	/
Fertilizer³		Fertilizer	15	3	50
Note: China National standard for 1="Limits of Pollutants in Food"(GB2762-2017), 2="Feed Health Standards"(GB13078-2017), and 3= "Limited Requirements for Toxic and Harmful Substances in Fertilizers"(GB38400-2018).

(1) Accumulator plants in combination with activators and low heavy metal accumulation plants were adopted in slightly polluted area. When compared the contents of heavy metals in soils before and after phytoremediation, it was noted that the heavy metal contents increased in the slightly polluted soils, while the standard compliance rate of crops reached 100% after phytoremediation. The abnormal content of heavy metal in these soils was resulted by the fact that adsorbed heavy metals were re-released owing to the plant decay, which explained that the soil sampled after plowing land was not the same as that before.

(2) Available content of heavy metals in soils can be reduced by adopting passivator combined with low heavy metal accumulation crops in moderately polluted area. Available content of Cd decreased by 10.18%, while available content of Pb decreased by 24.82%, which indicated that the passivator was more effective on the availability of Cd and Pb in moderately polluted soils. The crop compliance rate in the moderately polluted area was 100%.

(3) Oilseed rape/oil sunflower crop rotation mode was adopted in heavily polluted area, which can meet the effective use of arable land resources and also realize safe production. The oily plants are ornamental and the edible rate of the oil made from them was 100%, which can produce certain economic benefits for the Yangshuo County.

(4) After 15 months of treatment, the soil pH value increased. The soil pH value before treatment was 5.81 to 7.33, and after treatment the overall soil pH value in this treatment area ranged from 6.5 to 7.5, corresponding to near-neutral pH which was suitable for crop growth. As the soil pH increased, the fertility of soil was regulated and improved to a certain extent.

(5) It is recommended that farmers continue to plant low heavy metal accumulation crops in the slightly and moderately contaminated areas, and to realize the rotation of oilseed rape and sunflower in heavily contaminated areas.

Acknowledgements

This research was jointly supported by the Guilin Environmental Supervision and Testing Service Procurement of 0.733 km² Farmland Safe Use Project of Sidi Village, Xingping Town, Yangshuo County (Government Procurement Project No. GLZC2019-C3-07045-HCDZ(R)) and the China Nonferrous Mining Group Corporation Science and Technology Plan Project No. 2019KJJH03.

Author contributions

Wenting Liu: Conceptualization, Data curation, Investigation, Formal Analysis, Visualization, Writing-original draft, Funding acquisition, Project administration, Ming Li: Data curation, Formal Analysis, Writing-review & editing, Landry Soh Tamehe: Data curation, Formal Analysis, Supervision, Resources, Writing-review & editing, Jianjie Fu: Supervision, Validation, Writing-review & editing, Tangyu Hong: Supervision, Validation, Writing-review & editing, Yujiao Shi: Conceptualization, Funding acquisition, Project administration, Resources, Supervision, Lishan Huang: Conceptualization, Resources, Supervision, Validation. All authors reviewed the manuscript.

Conflict of interest

The authors declare no competing interests.

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No competing interests reported.

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Evaluation of effect of phytoremediation of heavy metal pollution in farmland soils around a lead-zinc mine, Southwest China

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Abstract

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Introduction

Materials and methods

Study area

Experimental design

Sample collection and preparation

Laboratory analysis and data processing

Results and discussion

Characterization of soil heavy metals

Analysis of heavy metal availability in soil

Soil pH and nutrient analysis

Analysis of heavy metal content in crops

Conclusion

Declarations

References

Additional Declarations

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