Introduction

Dichlorodiphenyltrichloroethanes (DDTs) were widely used in the world as effective insecticides for vector-borne diseases control and for crop protection1. Due to their detrimental effects to wild life and human health, DDTs were banned decades ago by many countries, including China in 1983. In 2001, they were listed as one of the 12 persistent organic pollutants (POPs) by the Stockholm Convention2. In light of the current outbreak of Zika virus infections and their damaging consequences (e.g. microcephaly), an informed debate on whether DDT should be brought back is possible, but only if their post-application environmental processes are well understood.

Historical applications of technical DDTs and dicofol, which usually contains high levels of DDT compounds as impurities in the production process, are the two main sources of DDTs in the environment. DDTs can migrate from soils or transform to their metabolites via various mechanisms, including degradation, volatilization, leaching, run-off, adsorption and plant removal3. Geographic locations, meteorological conditions, and soil physicochemical or biological properties are the main factors influencing the environmental behaviors of organic pollutants4,5. Even though technical DDTs and dicofol were produced and applied more extensively in developed eastern than western China6, DDT residues were still found in western China due to their long-range migration as previous studies reported7. Like many chiral agricultural pesticides, o,p’-DDT consists of one pair of enantiomers. The enantiomeric fraction (EF) can be changed during biodegradation and is a good indicator of past versus fresh chiral pollutant inputs8,9. Compound-specific stable isotope analysis (CSIA) has been used in laboratory and field studies to characterize in situ biodegradation processes of organic pollutants10,11. Due to the different extent of transformation during atmospheric transport12,13, the EFs and carbon stable isotope compositions of DDT may be totally different between eastern and western part of China. A combination of EF analysis and CSIA might offer additional insights into the migration and transformation of organic contaminants11,14,15, especially on a large scale. After 30 years of ban, the main degradation production of DDTs was found to be DDE in Chinese arable soils7. Because of their different sources, DDT and DDE may exhibit distinct isotope characteristics. However, to date, little data from EF analysis and CSIA was obtained on the global cycling and fate of DDT and its metabolites using field samples on a large scale. The study exploring the biological factors influencing the preferential degradation of chiral o,p’-DDT is also rather limited, especially at a species level of bacteria. It is necessary to well understand their environmental behaviors under real complicated environment using the techniques mentioned above.

Therefore, in this study, we conducted a nationwide farmland sampling campaign across China and measured the concentrations, EFs and carbon isotope compositions (δ13C) of DDT and its main metabolites in arable soils. High-throughput techniques and network analysis were employed to characterize the microbial communities and explore their co-occurrence patterns with DDT and its metabolites in soils. The obtained data were used to estimate the migration and transformation of DDTs on a large scale and to explore the underlying influencing physicochemical and microbiological factors in arable soils after 30 years of DDT ban in China. Furthermore, results from this study would provide basic scientific data for the contamination management and risk avoidance of DDTs in Chinese soils.

Results

Concentrations and profiles of DDTs in arable soils across China

DDT and its metabolites were detected in all the soil samples we analyzed. Their concentrations are displayed in Table 1. The concentrations of ΣDDTs (sum of o,p’-DDE, p,p’-DDE, o,p’-DDD, p,p’-DDD, o,p’-DDT and p,p’-DDT) ranged from 0.025 to 211 ng/g, with a mean value of 8.06 ng/g. Among the six DDT components, p,p’-DDE, which is the main metabolite of DDT, had the highest mean concentration (3.29 ng/g). Regional variation of DDT concentrations and compositions in arable soils across China was mapped in Fig. 1 and Supplementary Fig. 1. Severe DDT contamination was found in soils in eastern China, especially at sites in Shanghai City, and Zhejiang, Fujian, Hebei, Gansu, Liaoning and Jilin provinces. The residue concentrations of DDTs were much lower in western China. The pH and soil organic matter (OM) content ranged from 4.01 to 8.70 and 0.367 to 6.88%, respectively16. A significant but weak correlation between ∑DDT concentrations and OM (R = 0.359, p < 0.0001, Fig. 2a) was found in this study. In addition, a significant relationship (p < 0.05) was also identified between the residual levels of DDTs and socioeconomic indicators (SIs), including gross regional product (GPR) and population (P) (Fig. 2b and c)17. Among the DDT components, p,p’-DDE was the most abundant in 63.1% of the samples, especially in soils from eastern and northern China (Fig. 1b). p,p’-DDT, the main component in technical DDTs, is the dominant component in 30.3% of soil samples located mainly at sites in Shanghai City, and in Gansu, Shanxi, Fujian and Hunan provinces.

Table 1 Descriptive Statistical Summary of DDT Component Concentrations in Agricultural Soils across Mainland China (ng/g, soil).
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Figure 1
figure 1

Residue distributions of total DDTs in agricultural soils across China.

The map was created using ArcGIS 9.3 software (ESRI, Redlands, California, USA, http://www.esri.com/software/arcgis/arcgis-for-desktop). Scientific Reports remains neutral with regard to jurisdictional claims in published maps.

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Figure 2
figure 2

Relationships of DDTs in soils with soil organic matter (SOM) and socioeconomic indicators.

GRP: Gross Regional Product; P: Population; SI: Socioeconomic Index.

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Considering complex factors impacting on the residue levels of DDTs, stepwise multiple regression analysis was employed to explore the dominant factors and develop a prediction model. Based on the results of correlation analysis above, variables including organic matter, temperature, longitude and latitude were included. However, after significance and multicollinearity testing, temperature was excluded in the analysis. The significant prediction equation is as follows:

where, C is the residue concentrations of ∑DDTs in agricultural soils (ng/g); OM is the content of organic matter (%); LONG is the longitude of sampling site (°E); LAT is the latitude of sampling site (°N).

Technical DDTs are composed of 75% p,p’-DDT, 15% o,p’-DDT, 5% p,p’-DDE, <0.5% p,p’-DDD, <0.5% o,p’-DDD, <0.5% o,p’-DDE and <0.5% unidentified compounds18. In this study, we found more than half of the analyzed soils have the ratio of (p,p’-DDE+ p,p’-DDD)/p,p’-DDT > 1 and of o,p’-DDT/p,p’-DDT < 0.2 (Supplementary Fig. 2a). The ratio of (p,p’-DDE+ p,p’-DDD)/p,p’-DDT was much higher in soils with higher organic matter contents (>2.3%) and higher temperatures (>14 °C) (Supplementary Fig. 2b and c). In addition, DDD/DDE ratios showed a weak positive correlation with elevation of the sampling sites (Supplementary Fig. 2d).

Enantiomeric fraction of o,p’-DDT

Ninety-four soil samples with sufficient o,p’-DDT levels were selected for enantiomeric analysis. In general, the EF values of o,p’-DDT in soils varied greatly, ranging from 0.066 to 1(Fig. 3a). The EF values deviating from 0.5 were observed in most soil samples. There were 51.1% of the samples having EF values lower than 0.5. Geographically, the EFs of o,p’-DDT were below 0.5 in over half of the sampled soils in eastern and northeastern China, while above 0.5 in more than 50% soils in central and western China (Supplementary Table 1). The deviation from racemic (DEVrac = absolute values of 0.5 − EF) is a parameter measuring the degree of enantioselective metabolism regardless of which enantiomer is preferentially degraded9. The DEVrac of o,p’-DDT was found to slightly increase with temperature (Fig. 3b). However, the soil pH was not found to well correlate with the concentration of either DDTs or enantiomer residues like those reported in Zhang et al.19.

Figure 3
figure 3

Enantiomeric signatures of o,p’-DDT in soils (a) and the relationship between DEVrac (deviation from racemic compound) of o,p’-DDT and temperature (b).

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Compound-specific carbon isotope composition of o,p’-DDT and p,p’-DDE

Compound-specific stable isotope analysis has been recognized in contemporary environmental science and successfully used in some studies as an indicator to provide insight into the sources and in situ biodegradation processes of pollutants10,11,14. Therefore, in this study, 10 representative soil samples were selected for stable carbon isotope analysis according to geographic locations, sources, and concentration ranges of DDTs (Supplementary Table 2). The carbon isotope composition of technical DDTs and dicofol may be different by various manufactures and even by produced dates20. In this study, we assumed the δ13C of DDTs obtained from Dr. Ehrenstorfer GmbH (Augsburg, Germany) as the initial stable carbon isotope composition of DDTs applied for agriculture. The δ13C of p,p’-DDE ranged from −24.81 ± 0.12‰ to −30.26 ± 0.06‰ and deviated either positively or negatively from those of the initial product (−28.77 ± 0.06‰, Supplementary Table 2), with a negative dependence on the normalized concentration by OM (R = 0.845, Fig. 4a). The δ13C of o,p’-DDT ranged from −25.89 ± 0.06‰ to −32.57 ± 0.28‰, deviating only positively from the δ13C of the initial product (−34.23 ± 0.13‰) but with a wider range (Supplementary Table 2). In addition, the δ13C of p,p’-DDE correlated negatively with the mean annual temperature of each site (R = −0.868, Fig. 4a), while those of o,p’-DDT correlated positively with temperature (R = 0.711, Fig. 4b). The stable carbon isotope and enantiomer compositions of o,p’-DDT are jointly displayed in Fig. 4c for comparison. The δ13C and EF values both deviated from the racemic standard product. More positive values of δ13C were observed in samples with EF < 0.5 than those with EF > 0.5.

Figure 4
figure 4

Stable carbon isotope signatures of p,p’-DDE (a) and o,p’-DDT (b) and the relationships with enantiomeric fraction of o,p’-DDT (c) in soils.

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Microbial communities and DDTs

Nineteen bacterial phyla were identified via Illumina sequencing from 28 samples across China. Proteobacteria was the most abundant phylum, followed by Actinobacteria (Supplementary Fig. 3). Network analyses showed that Acidimicrobiales and Gp3 correlated negatively and positively, respectively, with OM. Considerable numbers of taxa were observed to correlate well with the fractions of p,p’-DDT, o,p’-DDT, p,p’-DDE and p,p’-DDD, while few with the fractions of o,p’-DDE and o,p’-DDD (p < 0.01) (Fig. 5 and Supplementary Table 3). Bacteria of Thermodesulfovibrio, Coriobacteriaceae, Syntrophobacterales and unknown species of Chloroflexi correlated negatively with the abundance of p,p’-DDT, while positively with p,p’-DDE. Three species, including lamia_majanohamensis, ilumatobacter_fluminis and Ohtaekwangia_koreensis, showed inverse correlations with the relative abundance of parent compound p,p’-DDT and metabolite p,p’-DDD. Fifty-seven taxa of 9 phyla were found to strongly correlate with the fractions of o,p’-DDT or its enantiomers (Fig. 5a). Strong negative correlations was found between the abundance of Coribacteriaceae, Syntrophobacterales and Chloroflexi with o,p’-DDT. Peredibacter_starrii and Rhodobacteraceae correlated positively with both enantiomers of o,p’-DDT. In addition, both (+)-o,p’-DDT and o,p’-DDT showed positive correlations with Devosia, Adhaeribacter and Cellulomonadaceae, but negative correlations with Gp3, Clostridium_sensu_stricto, Nitrospiraceae and Chloroflexi. The abundance of both o,p’-DDT and its (−)-enantiomer has negative correlations with Caedibacter_caryophilus and positive correlations with Skermanella_aerolata, Brevundimonas_alba, Cellvibrio, Brevundimonas, Devosia, Rhodobacteraceae, and Caulobacterales.

Figure 5
figure 5

Mutual influences between microbial community and DDT residues in arable soils across China based on the Network Analysis.

The nodes with number were the bacterial taxa and their names were listed in Supplementary Information Table 3. The blue and red edges represent negative and positive correlations, respectively, and the stronger is in correlation, the darker in color.

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Discussion

Residues of DDTs are found to be ubiquitous in agricultural soils across China even after 30-year ban of their application. Being the main metabolite of p,p’-DDT, p,p’-DDE is more persistent than other DDT components21. That explains its most abundant concentrations in soils. Compared to recent worldwide data from agricultural soils (Supplementary Table 4), the ∑DDT concentrations measured in the present study are relatively low. The ban of technical DDT usage since 1983 and the decreasing production of dicofol may be responsible for the decline. The lower DDT concentrations observed in this study may also be the result of dissipation of DDTs in soils over years.

Historical usage is a crucial factor influencing the DDT concentrations in the environment. In this study, the spatial distribution pattern of ∑DDTs in arable soils roughly overlaps with the usage inventory map of technical DDTs in 1951–1983 and dicofol in 1984–2003 in China22. The average ratio of o,p’-DDT/p,p’-DDT in technical DDTs is 0.19, which is much lower than that in dicofol (7.0)23. The compositions of DDTs can be altered by biological and abiotic degradation, volatilization, and re-deposition in the environment due to their different properties. Therefore, the change in the ratios of different DDT compounds can be employed to gauge their age and origin19. The ratio data show that the residues of DDTs are mainly from historical technical DDTs and secondarily from the later dicofol usage. However, the increasing abundance of p,p’-DDT component with time compared to our previous study7 also reveals an increased fresh input of DDTs, which might be from the use of technical DDTs. Enantioselective degradation could result in enantiomer fractionation of chiral pollutants9,12. As our data show, the EF values of o,p’-DDT varied greatly in arable soils across China. Similar to previous studies9,19,24, most samples showed EFs deviating from the racemic compound, suggesting aged DDTs are dominating in today’s soils. Less amount of DDTs were applied in western China, where residual DDTs were still found. The EF values of o,p’-DDT in western China also deviated from that of the racemic compound. This might be due to long-range transport from other places and subsequent wet or dry deposition. The enantiomeric signatures of chiral chemicals may retain racemic or nearly racemic in the air12. Therefore, their smaller DEVrac of o,p’-DDT (mean = 0.016) compared to those at other sites further supports a significant DDT source from atmospheric deposition in western China. In addition, the different physiochemical and biological features of the soil environments might also contribute to the different EF values among the four geographic regions across China. Other studies also obtained EF values of o,p’-DDT either > or <0.5, indicating a complex degradation preference9,19,24. It has been reported that the enantioselective degradation of chiral pesticides can be altered by soil pH, OM and redox conditions19,25. In addition, environmental changes, such as tropical deforestation and global warming could also lead to enantiomer preferences26. In this study, we did find a significant enantioselective degradation of o,p’-DDT, but not on the enantiomer preference. It implies that the preferential degradation of o,p’-DDT enantiomers may be modulated by the integrated effects of multiple environmental factors in soil environment. However, the absolute degree of the enantioselective degradation of o,p’-DDT was found to be slightly elevated by temperature. It might be due to the higher enantioselective degradation rates related to higher microbial activities in sites with higher temperature.

Compound-specific isotope compositions can offer insights into the pathways of in situ degradation of POPs in various environments10. Badea et al.14 recommended a δ13C difference of at least 2‰ for reliably interpreting the sources of different sites considering environmental complexity. Different δ13C of p,p’-DDE and o,p’-DDT were observed in different soils in this study (Fig. 4 and Supplementary Table 2). o,p’-DDT is the main contributor of dicofol-type DDT pollution. The δ13C of o,p’-DDT in all measured soils are higher than that of the possible starting DDT. It indicates a Rayleigh-style degradation process which preferentially degrades 12C-enriched DDTs and results in the δ13C increase in residual DDTs in soils. However, p,p’-DDE is the main metabolite and more persistent than parent DDT4. Its carbon isotope composition could be influenced by both the degradation from parent DDTs (12C-enriched process) and its own dissipation (13C-enriched process). The fact that the Shanghai soil with an abnormally high concentration of p,p’-DDT (15.9 ng/g) bearing the lowest δ13C of p,p’-DDE is consistent with this explanation (Supplementary Table 2). The positive correlation between mean annual temperature and the δ13C of o,p’-DDT appears robust, a pattern we hypothesize as the consequence of warmer regions having higher degradation rates and subsequent higher 13C enrichment than cooler regions. Interestingly, this pattern seems to contradict to that of the main metabolite p,p’-DDE. It is likely due to a larger degree of degradation on p,p’-DDT than on p,p’-DDE, resulting in more 12C enrichment in p,p’-DDE at warmer sites. This trend is in agreement with the lower and higher fractions of p,p’-DDT and p,p’-DDE, respectively, at the sites with higher temperature (eastern China). In addition, DDE residues in eastern China are mainly from the degradation of DDT. Their residues in colder western China, where less amount of DDTs were used than eastern China, are mostly from the long-range transport via air from eastern China7. It is known that carbon isotope fractionation is smaller during physical than biodegradation process13. Therefore, more positive δ13C is found for p,p’-DDE in western China, which could partly account for the negative correlation between its δ13C and local temperature. This interpretation is also suitable for the positive correlation between the δ13C of o,p’-DDT and temperature. All these hypotheses should be further tested with controlled experiments or additional sampling. Milosevic et al.11 found more positive δ13C of BTEX at contaminated landfill with lower concentrations, which was due to their microbial degradation and subsequent enrichment of 13C. Likewise, this trend was also observed for p,p’-DDE in this study. However, the possible reason for our findings might be different due to the different initial usage amounts of DDTs across China. More technical DDTs and dicofol have been applied in eastern China than western China. Therefore, the relative newer and higher concentrations of DDT residues might be the main reason for the more negative δ13C of p,p’-DDE in eastern China.

The combination of the enantiomer and stable carbon isotope fractionation, in a two-dimensional approach, may aid to further understand the degradation pathways of chiral o,p’-DDT. Both the EF and δ13C values of o,p’-DDT in the measured samples differentiated from those of racemic standard products, further suggesting active metabolism of DDTs in soils. Interestingly, the stable carbon isotope compositions of o,p’-DDT showed different characteristics in soils with EF > 0.5 or <0.5. The δ13C of o,p’-DDT in soils with EF > 0.5 displayed more negative values than those in soils with EF < 0.5. Bashir et al. observed higher stable carbon isotope fractionation for (+)- than (−)-α-HCH during biodegradation27. If the enantiomers of o,p’-DDT also have the similar carbon isotope fractionation, the observed different isotope fractionation patterns between EF > 0.5 (preferential degradation of (−)-enantiomer) and <0.5 (preferential degradation of (+)-enantiomer) could be explained. This prediction can be further tested using enantiomer-specifics table isotope analysis in future laboratory study.

The initial use of chemicals can lead to a primary distribution pattern, which is controlled by the usage amount of chemicals28. A strong association between DDTs and SIs, similar to that reported by Simonich et al.29, was found in the present study. It is consistent with the fact that accumulatively more DDTs were produced and applied in more economically developed regions in China (eastern China). Once chemicals are released, their volatilization, deposition and runoff, etc., may lead them disperse in the environment and form the secondary distribution pattern28. The redistribution of organic pollutants depends on various environmental conditions and soil physicochemical or biological properties9,16,177,19. Temperature is an important factor influencing the degradation of DDTs. In arable soil sites with higher temperatures, the degradation of DDTs is enhanced and predominated by the aerobic metabolism of DDT to DDE. Soil OM has been reported to have the ability to sequester environmental contaminants in soils and a linear correlation between OM and POP residue concentrations has been obtained in an equilibrated soil-air system30. A typical secondary distribution characteristics modulated by soil OM were found in soils from south-western Spain and Zhejiang, China19,31. However, we only observed a weak correlation between OM and the residue concentration of DDTs in soils. This is expected because of the complexity of factors impacting the residue concentration of soil DDTs and the nature of our large-scale sampling. In addition, the enhanced metabolism of p,p’-DDT to p,p’-DDE and p,’p-DDD by soil OM and temperature was observed in this study. It might be associated with the higher microbial activities in sites with higher soil OM and temperature. The R2 value of the prediction equation based on stepwise multiple regression analysis is 0.222. It means that 22% of the total variations in DDT concentrations are explained by OM, longitude and latitude. The content of OM is the principal factor among these variables. Although the prediction model is significantly developed, the R2 value is still a little small. The initial usage amounts of technical DDTs might be the most predominant factor influencing the distribution and residue levels of DDTs in agricultural soils across China.

Soil microbial communities, which are influenced by environmental conditions, play critical roles in the degradation of contaminants. Various bacteria, such as Serratia marcescens DT-1P, Pseudomonas fluorescens and Alcaligenes sp. KK, Sphingobacterium sp. D6 and Chryseobacterium sp. PYR2 and Bacillus sp. BHD-4, have been documented to be capable of converting DDTs to their metabolites32,33,34,35,36,37. However, the abundances of these bacterial strains were not found to correlate directly with those of DDT residues in the present study. It might be due to the very low abundance of these bacteria in soils and/or the complex environmental conditions inherited in a field study. Microbes, including Chloroflexi, Coriobacteriaceae (belong to Actinobacteria) and Syntrophobacter, Thermodesulfovibrio, Caedibacter_caryophilus (belong to Gammaproteobacteria), whose abundances correlate negatively with the fraction of p,p’-DDT and positively with that of p,p’-DDE, may be capable of biodegrading DDTs. The significant positive correlation between the degree of DDT degradation and the abundance of Actinobacteria and Gammaproteobacteria was also identified by Sun et al.38. Sulfate- and iron- reducing bacteria distribute widely in the environment. They have been reported to be capable of anaerobically dechlorinating organochlorine chemicals, including DDTs, via co-metabolism with iron or sulfate reduction39,40,41. In this study, some sulfate- and iron reducing bacteria (Syntrophobacter and Thermodesulfovibrio, Fig. 5b) were found to correlate negatively with the abundance of p,p’-DDT but positively with that of its aerobic metabolite p,p’-DDE. It suggests that these bacteria may have the potency to dechlorinate DDT to DDE in aerobic environments. Clostridia are obligate anaerobes and found to be affected by the pollution of metal and petroleum hydrocarbons42,43, and may thrive in o,p’-DDD-polluted soil across China as suggested by Guo et al.44. In addition, the similarly positive correlations between o,p’-DDT with Alphaproteobacteria (including Devosia, Brevundimonas_alba, Skermanella_aerolata and Caulobacterales found in this study) and Sphingobacteria (Adhaeribacter found in this study) were also observed in Guo et al.44 For chiral chemicals, their enantioselective degradation is mainly the result of microbial activities but not abiotic reactions26,45. The enantiomeric fractionation of chiral pollutants could be caused by different degradation rates of the same or different enzymes46. In this study, Peredibacter_starrii and Rhodobacteraceae correlate positively with both (+)-o,p’-DDT and (−)-o,p’-DDT, indicating that different degradation rates by the same bacteria may be one possible explanation for the enantioselective dissipation of o,p’-DDT in soils. This result is consistent with those reported by Lewis et al.26. They found the enantiomers of the chiral chemicals they studied were transformed at different rates in all soil samples and bacterial isolates under field and laboratory experiments. Some bacteria, such as Gp3, Clostridium_sensu_stricto, Nitrospiraceae, Chloroflexi and Caedibacter_caryophilus, are only capable of degrading (+)- or (−)-enantiomer of o,p’-DDT. Thus, different bacteria can degrade different enantiomers which could also result in the EF values deviating from 0.5. Generally, the taxa we found to correlate well with the stereoisomers and metabolites of DDTs in this study are mostly at genus and species level, not of higher levels. Our results demonstrate that DDT residues can influence the specific microbes and they could in turn impact the redistributions of DDTs in Chinese arable soils.

Methods

Sample collection

A total of 123 surface soils (0–20 cm) were collected from agricultural fields covered 31 provinces across China in April and May 2013. Detailed information on sampling locations and strategy was described in our previous study and briefly presented in the Supplementary Information (Text and Supplementary Fig. 4).

Sample extraction and analysis

A mix of 6 DDT compounds (o,p’-DDE, p,p’-DDE, o,p’-DDD, p,p’-DDD, o,p’-DDT and p,p’-DDT) (their molecular structures are listed in Supplementary Fig. 5) was purchased from Dr. Ehrenstorfer GmbH (Augsburg, Germany). Detailed procedures of sample pretreatment were described in the Supplementary Information. Briefly, after being Soxhlet-extracted with dichloromethane (DCM), the concentrated extracts were cleaned up through a column containing anhydrous granular sodium sulfate (Na2SO4), neutral silica gel, alumina, and florisil. Then, the target analytes eluted by hexane/DCM (7:3) were further concentrated for analysis.

The concentrations of DDT and its metabolites were measured on an Agilent 7890A gas chromatograph (GC-ECD, Agilent Technologies, Avondale, PA, USA) equipped with BGB-172 chiral capillary column (20% tert-butyldimenthylsilylated-β-cyclodextrin in OV-1701, 30 m × 0.25 mm × 0.25 μm; BGB Analytik AG, Switzerland). The determination of enantiomeric fractions (EFs) of chiral o,p’-DDT were performed by a gas chromatograph-mass spectrometry (Agilent 7890A GC-5975C MS). A larger quantity of soils was used to obtain sufficient amounts of targets for isotope analysis. The stable carbon isotope composition (δ13C) of DDT and its metabolites was measured using an Agilent 7890A GC coupled to a GV Isoprime IRMS (GV Instruments, UK) (GC-C-IRMS) via a modified GC5 combustion interface at College of Environmental and Resource Sciences, Zhejiang University. Due to the limitation of concentration and the existence of interfering substances, only the δ13C of p,p’-DDE and o,p’-DDT were determined.

The instrumental conditions and columns used for the separation of DDT isomers in GC-ECD and GC-C-IRMS and the enantiomers in GC-MS were given in detail in the Supplementary Information.

DNA extraction and Illumina Miseq sequencing

Soil DNA was isolated from a 0.25 g fresh soil sample using Power Soil DNA kit (Mo Bio Laboratories, USA) based on the instructions of the manufacturer. 16S rRNA gene amplicons were pair-end sequenced at Shenzhen Huada Genomics Institute by using Illumina Miseq (300 bp-PE). The detailed procedures were described in Supplementary Information. The sequencing data were all deposited in GenBank (Accession Number: SRP072159).

Quality control and quality assurance

Blank controls were ministered for every 15 soil samples to check potential cross-contaminations and interferences. The recoveries of DDTs were in the range of 82.8% to 105%. The mean recoveries of surrogates, including TCmX and PCB209 were 93.9 ± 12% and 89.2 ± 15%, respectively. Three times of signal-to-noise ratio were calculated as the limits of detection (LOD), which ranged from 0.003 to 0.005 ng/g for target compounds. Potential thermal degradation of DDTs was checked daily and a ratio less than 6% was satisfied. Duplicate experiments were performed in the whole procedure.

The EF values of o,p’-DDT are defined as the portion of the (+)-enantiomer to the sum of the (−)- and (+)-enantiomers. Racemic standard of o,p’-DDT with every 10 samples were injected and the mean EF value was 0.498 ± 0.005. Data was deemed acceptable only if the EF differences between the two monitored ions were within 0.05. The o,p’-DDT in samples was considered to be racemic when the EF value was within the 95% confidence interval (CI) of the standard.

Additional Information

How to cite this article: Niu, L. et al. Enantiomer signature and carbon isotope evidence for the migration and transformation of DDTs in arable soils across China. Sci. Rep. 6, 38475; doi: 10.1038/srep38475 (2016).

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