Distribution and bioconcentration of seven Polybrominated diphenyl ethers (PBDEs) on the Qinghai-Tibet Plateau

doi:10.21203/rs.3.rs-3326483/v1

Poly Brominated Diphenyl Ethers (PBDEs) are typical persistent organic pollutants (POPs), but studies on their distribution in terrestrial ecosystems at various trophic levels are scarce. The concentrations of PBDEs in soil, grass and rat liver ranged from 29.1 to 91.6, 71.5 to 644.4 and 43.2 to 519.0 ng g^-1dw, respectively, with BDE-154 predominating in all samples. A clear enrichment occurred from soil to grass in the soil-grass-plateau pika food chain, and a less clear trend of enrichment from grass to plateau pika. By correlation analysis, pollutants in soil and grass are not strongly correlated, so it can be assumed that some of the contaminants in grass come from other sources. A correlation comparison of contaminant concentrations in grass and liver, the majority of the substances (BDE-47, BDE-100, BDE-154, BDE-183) were found to be strongly correlated, this is related to the fact that grass is the main source of food for plateau pika in the Qinghai-Tibetan Plateau region. Highly brominated contaminants are generally more concentrated in each medium than lowly brominated contaminants. Only three contaminants (BDE-28, BDE-153 and BDE-154) be detected in all soil sample, yet 7 PBDEs detected in grass and liver samples, PBDEs are widely found in soil, grasses and plateau pika on the Qinghai-Tibetan plateau. According to the principal component analysis, the distribution pattern of pollutants is affected by many factors, and the pollutants in the Qinghai-Tibet Plateau may have the same source.

Poly Brominated Diphenyl Ethers

Qinghai-Tibetan Plateau

Bioconcentration

Food Chain

Correlation

Persistent organic pollutants (POPs), with semi-volatile, environmentally persistent, bioaccumulative and toxic. Semi-volatility and environmental persistence determine its ability to enter the atmosphere by volatilization and persist in the atmosphere for a long time, long-range transport in gaseous or particulate form with the atmospheric circulation, eventually widely distributed globally(Nizzetto et al. 2010; Arellano et al. 2011). According to the provisions of the international Stockholm Convention, dozens of substances such as DDT, decabromodiphenyl ether(commercial mixture, c-decaBDE), dieldrin, hexabromobiphenyl, hexabromocyclododecane, lindane, mirex, pentachlorobenzene, short-chained chlorinated paraffins are banned or restricted from production and use in Parties. However, there are also substances that are unintentionally emitted during the production of other substances, such as hexachlorobenzene, this is also forbidden. It's been more than several decades since the convention was enacted, it is evident from previous research that these pollutants continue to be widely present in the environment (Wang et al. 2016).

PBDEs are synthetic substance, this is one of the most crucial brominated flame retardants, with the chemical formula C₁₂H_10-m-nBr_m+mO (where m + n ≤ 10), according to the different content of bromine atoms, PBDEs can be mainly divided into three different industrial products: pentabromodiphenyl ethers (penta-BDEs), octabromodiphenyl ethers (octa-BDEs) and decabromodiphenyl ethers (deca-BDEs)(Alaee et al. 2003; La Guardia et al. 2006). Due to the biological toxicity, environmental persistence and long-range transport of PBDEs have also been listed as banned and restricted chemicals in recent years. Long-term and widespread use of flame retardants, PBDEs as a crucial component of flame retardants, have a high propensity to infiltrate the environment, the concentration of PBDEs in the environment has been steadily increasing over an extended period of time (de Wit 2002; Breivik et al. 2011). PBDEs have been demonstrated to undergo biomagnification in both aquatic and terrestrial food webs, and lower brominated PBDEs are more enriched than higher brominated(Voorspoels et al. 2006, 2007; Betts 2008). Different from aquatic food chain, the study of PBDEs in terrestrial food chains still needs to be refined, and it has been demonstrated in the literature that certain substances exhibit no biomagnification within aquatic food webs, yet possess the potential for amplification within terrestrial food webs, the aforementioned is influenced by various factors, including distinct octane-water partition coefficients (K_OW) and octane-air partition coefficients (K_OA) and additionally, there are distinct metabolic processes between aquatic and terrestrial animals. Therefore, it is imperative to investigate the distribution and transportation of PBDEs within the terrestrial food web. (Kelly et al. 2008; Li et al. 2019; Huang et al. 2022).

The Qinghai-Tibet Plateau, the Arctic and the Antarctic are known as the three poles of the Earth, it boasts an expansive area exceeding 2.5 million square kilometers and maintains an average altitude surpassing 4000 meters. (Qiu 2008). The alpine ecosystem of the Qinghai-Tibetan Plateau is widely recognized as one of the most vulnerable and delicate ecosystems in terms of climate change and human activities, the unique and fragile plateau ecosystem is an important part of China's ecosystem(Huang et al. 2022). Until the 1960s, it was thought that the three poles were completely unpolluted areas, but the fact is that pollution still exists in the three poles, and among the many POPs have received a lot of attention due to their nature and location (Van Ael et al. 2013; Wang et al. 2019). There are three air masses above the Qinghai-Tibet Plateau, from European and Central Asian countries, the Indian Ocean air mass blowing from the south of the plateau, and the bottom-up, at the same time, there exist numerous densely populated industrialized cities surrounding the lower plateau. ( Sichuan Province, China, and the Indian subcontinent). It is widely recognized that POPs can be globally distributed through atmospheric migration, the Qinghai-Tibet Plateau as the third pole of the Earth, unlike the Antarctic and the Arctic, is surrounded by a dense human, the location is optimal for studying the ultimate fate of POPs. (Wang et al. 2016). POPs, such as PBDEs, polycyclic aromatic hydrocarbons(PAHs), and polychlorinated biphenyls(PCBs) have been found at high altitudes around the world (such as the Alps, the Rocky Mountains)(Arellano et al., 2011; Bogdal et al., 2010; Gabrieli et al., 2010; Bartrons et al., 2011; Bizzotto et al., 2009). PBDEs, as one of the persistent organic pollutants, are transported to the Qinghai-Tibetan Plateau through atmospheric circulation and emissions from surrounding urban areas. (Wang et al. 2016).

2.1 Sample collection

The sampling process was concluded in August of 2020. All samples were from 5 sites on the Qinghai-Tibetan Plateau. The names of the five regions are Golmud, Delingha, Qinghai Lake, Eling Lake and Unoccupied area, hereafter referred to as S1, S2, S3, S4, S5 respectively(Fig. 1,Table 1 ~ 4). Golmud was located in the west-central part of Qinghai Province and the hinterland of Qinghai-Tibet Plateau. Delingha was located at the northeastern edge of the Qaidam basin. Qinghai Lake was located in the northeastern part of the Qinghai-Tibetan Plateau, Qinghai Province. It was at the junction of Gonchar County, Republican County, and Haiyan County, it was the largest inland lake and saltwater lake in China. Euling lake located in the western part of Maddow County, Qinghai Province, was a large brackish water lake on the Qinghai-Tibet Plateau, an important fishery base and a breeding ground for various bird species. Unoccupied area located at the crossroads of Tibet-Xinjiang-Qinghai, the area had an average altitude of over 4,600 meters and an area of 45,000 square kilometers, with no communication signal in most of the territory, it had a complex topography and was always cold, with summer temperatures still around minus 7 degrees Celsius. Depending on the size and vegetation cover of the five sampling areas, the number of sampling points within each area varied. The number of sampling points for soil samples in the five regions were 3, 2, 8, 2 and 5, respectively. The number of sampling points for grass samples were 1, 1, 4, 2 and 5. The specific location of the sampling point was randomly selected. All samples were collected with a clean spatula and then placed into pre-prepared centrifuge tubes and sealing film, respectively, and marked immediately. Three copies of samples for each sampling site.

Table 1

Sampling point name and location information(Soil)
	Name	No.	Elevation/m	Latitude	Longitude
S1	Golmud	T1	2787	36°49′09″N	94°25′42″E
		T2	2790	36°42′78″N	94°83′52″E
		T3	2815	36°39′58″N	94°63′57″E
S2	Deringha	T4	2856	37°15′07″N	97°29′16″E
S2	Deringha	T5	2870	37°25′17″N	97°48′79″E
S3	Republic	T6	2732	36°23′13″N	100°64′69″E
	Gonchar	T7	3200	37°13′07″N	100°27′32″E
	Gonchar	T8	3280	37°17′58″N	100°07′28″E
	Qinghai lake	T9	3210	36°55′49″N	100°51′22″E
		T10	3215	36°56′23″N	100°54′37″E
		T11	3250	36°55′47″N	100°51′21″E
		T12	3300	36°55′21″N	100°50′36″E
		T13	3310	36°55′28″N	100°51′30″E
S4	Maddow	T14	4218	34°89′11″N	98°17′70″E
	Euling lake	T15	4577	34°40′58″N	97°53′07″E
S5	Tuotuo river	T16	4528	34°23′49″N	92°42′91″E
	Tuotuo river	T17	4635	34°28′63″N	92°20′48″E
	Viewing platform	T18	4598	35°26′70″N	93°18′56″E
	Unoccupied area	T19	4609	35°37′92″N	93°22′59″E
	Wudaoliang	T20	4613	35°21′41″N	93°08′96″E

Table 2

Sampling point name and location information(Grass)
	Name	No.	Elevation/m	Latitude	Longitude
S1	Golmud	C1	2790	36°42′78″N	94°83′52″E
S2	Deringha	C2	2860	37°15′07″N	97°29′16″E
S3	Qinghai lake	C3	3215	36°56′23″N	100°54′37″E
	West ocean1	C4	3310	36°55′28″N	100°51′30″E
	West ocean2	C5	3210	36°55′49″N	100°51′22″E
	Gonchar	C6	3280	37°17′58″N	100°07′28″E
S4	Mado county	C7	4218	34°89′11″N	98°17′70″E
S4	Euling lake	C8	4577	34°40′58″N	97°53′07″E
S5	Tuotuo river	C9	4528	34°23′49″N	92°42′91″E
	Tuotuo river	C10	4635	34°28′63″N	92°20′48″E
	Viewing platform	C11	4598	35°26′70″N	93°18′56″E
	Unoccupied area	C12	4609	35°37′92″N	93°22′59″E
	Wudaoliang	C13	4610	35°12′50″N	93°05′23″E

Table 3 Sampling point name and location information(Rats)

	Name	No.	Elevation/m	Latitude	Longitude
S1	Golmud	G1	2787~2815	36°39′58″N~ 36°49′09″N	94°25′42″E~ 94°83′52″E
		G2
		G3
S2	Deringha	G4	2856~2870 3210~3310 4218~4577	37°15′07″N~	97°29′16″E~
		G5		37°25′17″N	97°48′79″E
S3 S4	Qinghai lake Euling lake	G6 G7 G8 G9 G10 G11 G12 G13 G14 G15 G16 G17 G18 G19		36°23′13″N~ 37°17′58″N 34°40′58″N~ 34°89′11″N	100°07′28″E~ 100°64′69″E 97°53′07″E~ 98°17′70″E

Table 4

Introduction to the five sampling regions
	Introduction
S1	located northeast of the city of Golmud, around Lake Dabson
S2	southeast of Delingha City, around Gahai
S3	northeast of Qinghai Lake, Gonchar and Haiyan counties
S4	southeastern corner of Lake Euling and the northwestern corner of Lake Dondzona
S5	southeast of Lake Kusai, around Heidenauer and Salt Lake and northeast of the Tuotuo River

A total of 103 plateau pika samples were collected from the Qinghai-Tibet Plateau scientific research, in this study, a total of 19 plateau pika were randomly selected for the study. They were from S1, S2, S3, and S4, and their numbers are 3, 3, 8, and 5, respectively. Liver portion were removed from the collected plateau pika samples in a nearby laboratory and placed in prepared centrifuge tubes.

The whole process were wearing gloves to work. All samples were first stored away from light and then stored in a laboratory − 20°C refrigerator after sampling(Huang et al. 2011; Ren et al. 2017).

2.2 Sample pretreatment

Soil: The samples were subjected to lyophilization in a freeze-dryer for 48 hours. The samples were subsequently placed in a mortar to remove any stones, leaves, or other extraneous matter. They were then ground and passed through a 100-mesh standard sieve. 2 grams of soil powder were precisely weighed and transferred into a centrifuge tube, followed by the addition of 6 milliliters of dichloromethane and n-hexane (v:v = 1:1) for extraction. A series of extraction measures followed(Jin et al. 2018; Hu et al. 2021; Mao et al. 2022), first re-suspend the sample by vortexing vigorously for 10 minutes, next the ultrasonic-assisted extraction was conducted for 15 minutes at a frequency of 40 kHz, last centrifuged at 4000rpm for 10 minutes and decant the supernatant using a pipette. The aforementioned extraction steps were iterated thrice and the resultant supernatant was ultimately amalgamated. The supernatant was combined and subsequently concentrated to a volume of approximately 5 mL using a nitrogen evaporator, the concentrated solution was subjected to solid phase extraction using a Florisil column, followed by nitrogen blowing until complete dryness, then 1 ml of hexane and 0.1 µg BDE-77 were added and transferred to a brown injection vial and sealed. Put into − 20℃ refrigerator and wait for the machine.

The pre-treatment method for grass and liver is basically the same as that for soil, but the difference is that the mass of the sample is different, 0.5g and 0.1g for grass and liver respectively, and the liver sample is re-dissolved to 100µL.

2.3 Chemicals and Instrument analysis

Instruments and supplies: 6890N-5975 gas chromatograph-mass spectrometer (Agilent Technologies, USA), lyophilizer (Labconco, Germany), centrifuge (Shanghai Shampo Instruments & Equipment Co., Ltd.), powerful multi-tube vortex mixer (Beijing Codenos Technology Co., Ltd.), ultrasonic cleaner (Ningbo Xinzhi Biotechnology Co. Ltd.), analytical balance (Mettler Toledo, Shanghai), round water bath nitrogen blowing instrument (Bonsey Instrument Technology, Shanghai), pipette (Eppendorf, China), centrifuge tube (Corning Life Science Co., Ltd., China), threaded mouth brown injection bottle (Sinopharm Chemical Reagent Co., Ltd.), liquid nitrogen (99.99%), solid phase extraction column (J&K Scientific, China). Standards and recovery indicators: BDE-28, BDE-47, BDE-100, BDE-99, BDE-100, BDE-153, BDE-154, BDE-183, ¹³C₁₂-BDE-209(recovery rate indicator) and BDE-77(internal standards) were purchased from J&K Scientific (China). Reagents: n-hexane and dichloromethane are chromatographically pure(Aladdin, China).

The gas chromatograph tandem single quadrupole mass spectrometer (GC-MS) was employed to analyze seven PBDEs, the substances were separated using a DB-5MS column (30m×0.25mm×0.25µm) with an injection port temperature set at 280°C, injection volume of 1µL, carrier gas of helium, and a ramp-up procedure of 70°C held for 2min, 10°C/min to 250°C, held for 1min. The electron bombardment source was utilized at an electron energy level of 70 eV. The ion source and transmission line were maintained at a temperature of 330°C, while the selected ion monitoring (SIM) detection mode was employed (Alaee et al. 2001; Sen et al. 2011; Berton et al. 2016). The qualitative and quantitative ions, as well as the corresponding retention times for each substance, are presented in Table 5.

Table 5

Quantitative ions, qualitative ions and retention times of PBDE
	Quantify ions(m/z)	Qualitative ion(m/z)	Retention time(min)
BDE-77^*	486	488	11.1
BDE-28	406	408,248	9.09
BDE-47	486	488,326	10.58
BDE-99	566	406	11.96
BDE-100	566	404	11.59
BDE-153	484	643,482	13.03
BDE-154	484	643,482	13.75
BDE-183	562	722,456	16.60

*: Internal standards for quantification

2.4 Quality Analysis and quality control

The implementation of rigorous quality assurance and control measures was employed, the reagents and reagent transfer containers used during the experiment are disposable, and gloves and masks are worn throughout. To monitor background contamination, we implemented a procedure of setting four blanks every ten samples. To ensure the monitoring of instrument contamination, a set of solvent blanks consisting of 500 µL n-hexane (n = 3) were added to every 10 samples. There were no apparent contaminations of PBDEs in both procedural and solvent blanks. The instrument detection limit was established as the concentration range that produced signal-to-noise ratios of 3, with values ranging from 0.059 to 0.100 ng g-1 dw. Quantification of PBDEs in samples by internal standard method, preparation of 1, 10, 50, 100, 200 and 250 ng/ml PBDE standard solutions. The standard curves of the seven PBDEs are shown in Table 6. The retrieval of PBDEs was assessed through the use of three quality control samples (these samples underwent identical pretreatment procedures and were spiked with 50 ng/mL of PBDE standards and a recovery rate indicator). The recoveries of all substances fell within the range of 68–122%, and the relative standard deviations varied between 2% and 20%, the details are presented in Table 7.

Table 6

Standard curves and R² values of 7 PBDEs
PBDEs	Regression equation	Correlation coefficient(R²)
BDE-28	y = 1.2534x + 0.0036	0.9998
BDE-47	y = 0.8228x + 0.0014	0.9998
BDE-99	y = 0.3155x − 0.003	0.9996
BDE-100	y = 0.4548x − 0.0011	0.9999
BDE-153	y = 0.6039x − 0.0059	0.9993
BDE-154	y = 0.5368x − 0.0028	0.9996
BDE-183	y = 0.2109x − 0.0032	0.9993

Table 7

Recovery rate and relative standard deviation of each substance
	Recovery rate(%)	Relative standard deviation(%)
BDE-28	72	11
BDE-47	94	2
BDE-99	108	15
BDE-100	68	18
BDE-153	114	6
BDE-154	122	18
BDE-183	75	9

2.5 Statistical analysis

Substances below the detection limit of this paper is defined as non-detect. The sum of the concentrations of the seven PBDEs in the three media at each sampling site and the average of the PBDEs in each sampling area were calculated and the units were converted uniformly to ng g^-1 dw. Spearman analysis was used to assess the correlation of contaminants in different media at the same location. The data from the experiments were plotted and analyzed using ArcMap (10.8), Excel (2021), Origin (2018), and IBM SPSS Statistics 23.

3.1 Levels and distribution.

Concentrations of total PBDEs in soil, grass and rat liver based on dry weight are shown in Table 8–11 and Fig. 2(D). The concentrations of the total PBDE_S ranged from 29.1 to 91.6(mean:48.6)、from 71.5 to 644.4(mean:227.3) and from 43.2 to 519.0(mean:214.7) ng g^− 1 dw in soil、grass and liver, respectively. In soil samples from five regions, BDE-99, BDE-100 and BDE-183 were below the detection limit, and BDE-153 and BDE-154 were significantly greater than BDE-28 and BDE-47. This indicates that PBDEs are widely present in soil in the Qinghai-Tibet Plateau region, and the concentration of highly brominated contaminants is significantly greater than that of lowly brominated contaminants, this is consistent with previous studies(de Wit et al. 2006; Hu et al. 2020). Comparison of contaminants in soil in five regions, regional S5 (Tuotuo River) had the highest concentration of 59.3 ng g^− 1 dw, region S4 (Lake Euing) had the lowest 32.9 ng g^− 1 dw. In generally, there was no significant difference in the concentration magnitude of total PBDEs in these five regions. And the composition of pollutants in the soil was similar in all regions, are shown in Fig. 2(A), this suggests that PBDEs in most parts of the Tibetan Plateau come from the same source(Li et al. 2016b, 2017). The concentration of the total PBDEs in the soil of the Qinghai-Tibet Plateau region is slightly higher compared to other remote regions of the world. The concentrations of PBDEs in the soils of the Palang Mountains on the eastern Tibetan Plateau ranged from 4.3 to 61 pg g^− 1 dw(Zheng et al. 2012), this is 2 to 3 orders of magnitude lower than the present study, the Palong Mountains are located in the Wolong Nature Reserve and are mainly influenced by the Central Asian and Indian Ocean monsoons, sources of organic pollutants are mainly atmospheric transportation. The sampling sites in present study are mainly located along the water sources in the central of the Qinghai-Tibetan Plateau and have various levels of human activities. This may explain the high concentrations in this study. PBDEs concentrations in soils from remote areas of Europe ranged from 0.065 to 12 ng g^− 1 dw, with BDE-47, -99, -100, -153 and − 154 dominating(Hassanin et al. 2004), the present study is consistent with this result. PBDEs concentrations in Russian Arctic soils ranged from 0.16 to 0.23 ng g^− 1 dw(de Wit et al. 2006). The concentrations in soils near the Antarctic Ice Free Zone study site is 33 ng g^− 1 dw(Vecchiato et al. 2015), lower concentrations in soils in remote areas of Antarctica and the Arctic, 2.3–33 and 5.6–270 pg g^− 1 dw respectively(Sun et al. 2022). The present results are similar to the concentrations at the Antarctic ice-free zone study sites, but much higher than those at remote areas of the North and South Poles.

Table 8

Concentrations of Σ₇PBDE_s in environmental and biological samples from the Qinghai-Tibet Plateau
		Σ₇PBDE_s
		AV	SD	Max	Min
soil	ng g^− 1 dw	48.6	13.3	91.6	29.1
grass	ng g^− 1 dw	227.3	140.4	644.4	71.5
liver	ng g^− 1 dw	214.7	118.9	519.0	43.2
dw: dry weight, AV: average value, SD: standard deviation, Max: maximum value, Min: minimum value.

Table 9 Concentrations of PBDE in soil at each sampling site

	S1				S2
	1	2	3	Mean	1	2	Mean
BDE-28	0.7	0.3	1.5	0.8	0.5	0.7	0.6
BDE-47	ND	ND	ND	/	ND	ND	/
BDE-99	ND	ND	ND	/	ND	ND	/
BDE-100	ND	ND	ND	/	ND	ND	/
BDE-153	30.3	20.9	34.0	28.4	22.6	7.9	15.3
BDE-154	20.6	16.1	23.8	20.2	15.9	32.4	24.1
BDE-183	ND	ND	ND	/	ND	ND	/
Σ₇PBDE_S	51.5	37.3	59.3	49.4	39.0	41.0	40.0

ND: Below detection limit

Table 9 Concentrations of PBDE in soil at each sampling site(Continue1)

	S3
	1	2	3	4	5	6	7	8	Mean
BDE-28	0.6	0.5	0.5	0.4	0.4	0.4	0.3	0.4	0.4
BDE-47	ND	ND	ND	ND	3.9	ND	ND	ND	0.5
BDE-99	ND	ND	ND	ND	ND	ND	ND	ND	/
BDE-100	ND	ND	ND	ND	ND	ND	ND	ND	/
BDE-153	21.6	32.5	25.1	38.9	19.3	28.4	27.4	19.9	26.6
BDE-154	16.0	22.1	18.3	27.1	18.1	21.7	21.8	15.2	20.0
BDE-183	ND	ND	ND	ND	ND	ND	ND	ND	/
Σ7PBDES	38.2	55.1	43.9	66.4	41.8	50.5	49.6	35.5	47.6

Table 9 Concentrations of PBDE in soil at each sampling site(Continued2)

	S4			S5
	1	2	Mean	1	2	3	4	5	Mean
BDE-28	0.3	0.8	0.6	1.1	0.4	1.2	0.6	0.7	0.8
BDE-47	ND	ND	/	ND	ND	ND	ND	ND	/
BDE-99	ND	ND	/	ND	ND	ND	ND	ND	/
BDE-100	ND	ND	/	ND	ND	ND	ND	ND	/
BDE-153	6.5	15.9	11.2	54.4	32.9	27.0	29.4	26.3	34.0
BDE-154	22.2	20.1	21.1	36.2	20.6	21.2	21.1	23.3	24.5
BDE-183	ND	ND	/	ND	ND	ND	ND	ND	/
Σ₇PBDE_S	29.1	36.7	32.9	91.6	53.9	49.4	51.2	50.4	59.3

Table 10 Concentration of each PBDE in grass at each sampling site

	S1	S2	S3
			1	2	3	4	Mean
BDE-28	1.6	6.2	8.8	141.5	3.1	4.2	39.4
BDE-47	ND	8.9	4.2	3.3	11.2	2.8	5.4
BDE-99	ND	ND	ND	ND	ND	ND	/
BDE-100	14.1	29.4	36.6	9.1	18.4	30.0	23.5
BDE-153	25.7	33.7	23.7	23.4	16.3	15.2	19.7
BDE-154	30.1	63.1	58.7	56.2	104.1	86.3	76.3
BDE-183	ND	60.5	54.1	14.8	ND	68.2	34.3
Σ₇PBDE_S	71.5	201.8	186.0	248.3	153.1	206.7	198.5

Table 10 Concentration of each PBDE in grass at each sampling site(Continued)

	S4			S5
	1	2	Mean	1	2	3	4	5	Mean
BDE-28	4.8	2.0	3.4	12.4	2.1	1.0	2.5	3.8	4.4
BDE-47	ND	10.5	5.3	6.5	10.1	24.7	8.7	ND	10.0
BDE-99	ND	ND	/	ND	ND	ND	ND	ND	/
BDE-100	23.9	7.4	15.7	59.4	15.3	4.6	45.7	34.3	31.9
BDE-153	31.6	28.1	29.8	0.0	37.2	33.2	41.4	21.9	26.7
BDE-154	56.8	47.5	52.2	65.0	85.2	75.3	63.2	45.1	66.8
BDE-183	527.2	ND	263.6	190.7	ND	17.7	156.3	84.3	89.8
Σ₇PBDE_S	644.4	95.5	369.9	334.0	149.9	156.6	317.7	189.5	229.5

Table 11 Concentrations of PBDE in the liver of rats in each sampling area

	S1				S2
	1	2	3	Mean	1	2	3	Mean
BDE-28	13.7	55.3	11.9	27.0	0.7	1.8	2.2	1.6
BDE-47	109.1	4.2	24.5	45.9	12.0	11.6	59.6	27.7
BDE-99	ND	ND	ND	/	ND	ND	ND	/
BDE-100	ND	102.2	24.0	42.1	1.4	16.0	9.7	9.0
BDE-153	144.0	50.0	16.2	70.1	5.5	12.3	12.2	10.0
BDE-154	252.2	63.3	3.1	106.2	69.0	116.0	106.8	97.2
BDE-183	ND	ND	1.4	0.5	ND	57.5	43.2	33.6
Σ₇PBDE_S	519.0	275.0	81.1	291.7	88.5	215.2	233.7	179.1

Table 11Concentrations of PBDE in the liver of rats in each sampling area (Continued1)

	S3
	1	2	3	4	5	6	7	8	Mean
BDE-28	0.3	1.8	97.8	0.2	38.1	1.5	0.1	46.0	23.2
BDE-47	3.2	35.1	96.6	37.3	100.8	8.8	3.5	5.9	36.4
BDE-99	ND	ND	ND	2.0	ND	ND	ND	112.8	14.4
BDE-100	ND	7.0	18.4	6.3	128.1	20.5	1.2	13.7	24.4
BDE-153	3.1	32.0	72.5	1.0	ND	26.0	3.7	26.0	20.5
BDE-154	79.1	106.3	20.2	52.3	153.5	41.4	21.0	10.3	60.5
BDE-183	ND	ND	43.8	122.9	ND	51.0	13.6	ND	28.9
Σ₇PBDE_S	85.7	182.2	349.3	221.9	420.4	149.2	43.2	214.7	208.3

Table 11Concentrations of PBDE in the liver of rats in each sampling area (Continued2)

	S4
	1	2	3	4	5	Mean
BDE-28	1.4	73.4	0.8	2.0	82.1	32.0
BDE-47	0.9	13.5	10.7	1.8	45.7	14.5
BDE-99	ND	ND	ND	ND	ND	/
BDE-100	13.1	33.1	4.8	3.6	ND	10.9
BDE-153	ND	ND	ND	100.3	30.1	26.1
BDE-154	36.0	96.7	198.1	79.5	143.1	110.7
BDE-183	28.4	ND	ND	ND	ND	5.7
Σ₇PBDE_S	79.8	216.7	214.4	187.2	301.1	199.8

The average concentrations of the total PBDEs in grasses across the five regions were 71.5, 201.8, 198.5, 369.9, and 229.5 ng g^− 1 dw, respectively. It can be clearly seen that the concentration is higher than that in the soil, as shown in Fig. 2(B)and TableS8, this is consistent with the soil-grass distribution pattern of Italian alpine pastures(Parolini et al. 2012). Compared to other regions with less human activity, the concentration of PBDEs in the grasses detected in this study was significantly higher than that found in grasses from the Xilinguole grassland(0.04 ~ 4.28 ng g^− 1 dw)(Bute et al. 2020), this can be determined by many factors, atmospheric long-range transport, cold trapping effect(the sampling sites in this study rang from 3,000 to 5,000 meters above sea level) and different types of grass. Only BDE-99 was below the detection limit, all other congeners were detected in all grass samples. Concentrations of contaminants in grasses are generally greater than those in the corresponding soils due to bioconcentration and air-leaf exchange,it has long been demonstrated that plants can enrich organic pollutants in the air through the above part of the soil(Trapp and Matthies 1995; Hu et al. 2020).

From Fig. 2(C), it can be seen that the concentration of organic pollutant in the rat's liver is about the same as in the grass, and it can be seen that BDE-153 and BDE-154 dominated in all samples. From previous studies, it is known that contaminants in mammals come from sources related to dietary intake(Morris et al. 2018). Plateau pikas feed on a variety of plants(Li et al. 2016a), it had been shown that organic pollutants entered the liver first when they enter the organism and that the liver was the main detoxification organ in fish(Martins et al. 2023). Mouse samples were only collected from four areas as the S5 area is in a desert area and no trace of mouse was found. Their concentrations are 291.1, 179.1, 208.3, 199.8 ng g^− 1 dw, respectively S1、S2、S3、S4. Higher concentrations in regions S1 and S3 may be related to the fact that these two regions are in more populated cities with more complex food sources for plateau pika. Overall, the distribution patterns of PBDE concentrations in soil, plants and plateau pika on the Qinghai-Tibetan Plateau are consistent with previous work on Short-Chain Per- and Polyfluoroalkyl Substances in these media(Huang et al. 2022).

3.2 Enrichment potential of PBDEs in grasses

Based on previous studies, it is known that different parts of grasses (roots, stems, and leaves) vary in their ability to absorb pollutants and the way they do it(Hu et al. 2020). The part of the soil below the roots was chosen for this experiment, and the source of the pollutants was mainly from uptake into the soil. An organism absorbs a substance from its surroundings (water, soil, atmosphere) in a non-swallowing manner, so that its concentration in the body is greater than that of the surroundings is called bioaccumulation(Bergen et al. 1993; Martin et al. 2010). The following equation is used to calculate the bioaccumulation factors(BCFs) in this paper,

$$BCFs=\frac{{C}_{grass}}{{C}_{Soil}}$$

where C_grass and C_soil represent the concentrations of PBDEs(ng g^− 1 dw) in grass and soil at the same location, respectively. It can be seen that at each sampling site, all of the BCF values are shown in Table 12, most values are greater than 1. PBDEs in soils of the Qing-hai Tibetan Plateau can bioaccumulate through the root system of plants, which is consistent with studies by others on other different contaminants(Li et al. 2019; Xian et al. 2021).

Table 12

BCFs of PBDEs in each sampling area
	BCFs
	BDE-28	BDE-153	BDE-154	Σ₇PBDE_S
S1	2.26	0.85	1.47	1.39
S2	12.83	1.49	3.97	5.17
S3	23.36	0.61	2.17	2.80
S3	7.77	0.47	3.90	3.75
S4	2.57	1.77	2.37	2.60
S4	13.90	4.88	2.55	22.17
S5	11.76	0.00	1.79	3.64
	0.82	1.23	3.55	3.17
	3.91	1.41	3.00	6.21
	5.16	0.83	1.94	3.76

We analyzed soil and grass samples from the same locations and found some correlation between the various contaminants in different media. Data were obtained from 13 sampling sites with both soil and grass samples. Correlation analysis of pollutants, the BDE-47, 99, 100 and 183 are not discussed because they are below the detection limit in soil. From the data we conclude that only BDE-154 has a strong correlation (r = 0.604, p < 0.05) in both soil and grass("r" refers to the correlation coefficient and "p" refers to the correlation), while the correlation between the other two congeners is not strong, BDE-28 (r = 0.530, p = 0.063), and BDE-153 (r = 0.297, p = 0.325). This may be related to the fact that some contaminants migrate from the root system of plants to the upper part of the soil and are less likely to be transported upwards by highly brominated compared to less brominated substances(Hu et al. 2020), a trend that was also shown in the present study. Analysis of plants and plateau pika in the vicinity of sampling sites, four congeners were found to be correlated in concentrations in plant and rat livers, they are BDE-47(r = 0.958, p ≤ 0.01), BDE-100(r = 0.690, p ≤ 0.05), BDE-154(r = 0.832, p ≤ 0.01) and BDE-183(r = 0.750, p ≤ 0.05). Unlike the diversity of contaminant sources within plants, PBDEs enriched in the livers of plateau pika in the Tibetan Plateau may be mainly from grasses.

3.3 Effect of different factors on the distribution of PBDEs

With regard to the distribution of PBDEs, there are a number of influencing factors, we can flesh out the magnitude of these effects through mathematical formulas, principal component analysis(PCA) was used to accomplish this process(Xian et al. 2021; Martins et al. 2023).

In the present study, data for soil and grass (BDE-28, BDE-153, BDE-154, elevation, longitude, latitude) were standardized and normalized into two principal components(PCs), eigenvalues of PCs greater than 1. 43% and 26.4% for PC1 and PC2, respectively, via downscaling, this two-dimensional coordinate plot reflects 69.4% of the original data, which is already representative of the source data to a certain extent. From Table 13 and Fig. 3, in soil samples, it can be seen that the three PBDEs and altitude occupy the majority of the PC1. Furthermore, compounds with a lower percentage of bromine and lower relative molecular mass may be more readily transported and equilibrated in the environment. Latitude occupies a relatively high proportion of the PC2, but the effect of altitude decreases. In grass samples, latitude and longitude influenced PC1, accounted for 47.5% of the total variance, PC2 is 22.7%, relatively high proportion of highly brominated pollutants. The six influence factors selected in this paper have a large overlap between soil and grass, and the differences are not strong, this suggests that the PBDEs in the Qinghai-Tibet Plateau may have the same source.

Table 13

Component pattern for PBDEs and environmental parameters in Qinghai-Tibetan plateau soils and grass by PCA.
	soil		grass
	PC1	PC2	PC1	PC2
BDE28	0.361	0.389	0.280	-0.629
BDE153	0.308	0.489	-0.209	0.681
BDE154	0.324	0.472	0.081	0.080
Elevation	0.452	-0.468	-0.547	-0.194
Latitude	-0.488	0.401	0.544	0.300
Longitude	-0.477	0.078	0.525	0.080
Loading %	50.1	20.7	47.5	22.7

The seven PBDEs were widely present in the environment and organisms on the Qinghai-Tibetan plateau, with a higher proportion of highly brominated PBDEs than lowly brominated ones, in which some enrichment of BDE-28, BDE-153, BDE-154 and Σ₇PBDES occurred from soil to grass. The contaminant levels in rat liver were comparable to those in grass, and there is a significant correlation between the contaminants in the two media. Since pollutants in plants do not correlate strongly with pollutants in soil at the same locations, it can be assumed that pollutants in plants in the Qinghai-Tibetan Plateau region are partly from air-leaf exchange. The high concentrations of pollutants measured in this paper compared to previous studies on the Qinghai-Tibetan Plateau are related to the different study areas, most of the sampling sites in this study were in the vicinity of water sources and urban perimeters, high values need attention. Compared to those in other remote areas of the world, it can be concluded that local sources of pollution are also significant. Moreover these 7 PBDEs showed a similar pattern of content in the three different media, and it was further verified by PCA that these contaminations come from the same source. This may be related to the industrial cities surrounding the Qinghai-Tibetan Plateau, where pollutants come to the plateau as a result of atmospheric circulation and alpine cold trapping effects.

Alaee M, Arias P, Sjodin A, Bergman A (2003) An overview of commercially used brominated flame retardants, their applications, their use patterns in different countries/regions and possible modes of release. Environ Int 29:683–689. https://doi.org/10.1016/S0160-4120(03)00121-1
Alaee M, Sergeant DB, Ikonomou MG, Luross JM (2001) A gas chromatography/high-resolution mass spectrometry (GC/HRMS) method for determination of polybrominated diphenyl ethers in fish. Chemosphere 44:1489–1495. https://doi.org/10.1016/S0045-6535(00)00311-8
Arellano L, Fernández P, Tatosova J, et al (2011) Long-Range Transported Atmospheric Pollutants in Snowpacks Accumulated at Different Altitudes in the Tatra Mountains (Slovakia). Environ Sci Technol 45:9268–9275. https://doi.org/10.1021/es202111n
Bergen B, Nelson W, Pruell R (1993) Bioaccumulation of Pcb Congeners by Blue Mussels (mytilus-Edulis) Deployed in New-Bedford Harbor, Massachusetts. Environ Toxicol Chem 12:1671–1681. https://doi.org/10.1002/etc.5620120916
Berton P, Lana NB, Rios JM, et al (2016) State of the art of environmentally friendly sample preparation approaches for determination of PBDEs and metabolites in environmental and biological samples: A critical review. Anal Chim Acta 905:24–41. https://doi.org/10.1016/j.aca.2015.11.009
Betts K (2008) Does a key PBDE break down in the environment? Environ Sci Technol 42:6781–6781. https://doi.org/10.1021/es8018463
Bogdal C, Nikolic D, Lüthi MP, et al (2010) Release of Legacy Pollutants from Melting Glaciers: Model Evidence and Conceptual Understanding. Environ Sci Technol 44:4063–4069. https://doi.org/10.1021/es903007h
Breivik K, Gioia R, Chakraborty P, et al (2011) Are Reductions in Industrial Organic Contaminants Emissions in Rich Countries Achieved Partly by Export of Toxic Wastes? Environ Sci Technol 45:9154–9160. https://doi.org/10.1021/es202320c
Bute, Chen W, Li T, et al (2020) Distributions and biomagnification of polybrominated diphenyl ethers in a grassland ecosystem food chain. Sci Total Environ 747:141141. https://doi.org/10.1016/j.scitotenv.2020.141141
de Wit CA (2002) An overview of brominated flame retardants in the environment. Chemosphere 46:583–624. https://doi.org/10.1016/S0045-6535(01)00225-9
de Wit CA, Alaee M, Muir DCG (2006) Levels and trends of brominated flame retardants in the Arctic. Chemosphere 64:209–233. https://doi.org/10.1016/j.chemosphere.2005.12.029
Gabrieli J, Vallelonga P, Cozzi G, et al (2010) Post 17th-Century Changes of European PAH Emissions Recorded in High-Altitude Alpine Snow and Ice. Environ Sci Technol 44:3260–3266. https://doi.org/10.1021/es903365s
Hassanin A, Breivik K, Meijer SN, et al (2004) PBDEs in European background soils: Levels and factors controlling their distribution. Environ Sci Technol 38:738–745. https://doi.org/10.1021/es035008y
Hu H, Zhang Y, Zhao N, et al (2021) Legacy and emerging poly- and perfluorochemicals in seawater and sediment from East China Sea. Science of The Total Environment 797:149052. https://doi.org/10.1016/j.scitotenv.2021.149052
Hu Y, Sun Y, Pei N, et al (2020) Polybrominated diphenyl ethers and alternative halogenated flame retardants in mangrove plants from Futian National Nature Reserve of Shenzhen City, South China. Environ Pollut 260:114087. https://doi.org/10.1016/j.envpol.2020.114087
Huang H, Zhang S, Christie P (2011) Plant uptake and dissipation of PBDEs in the soils of electronic waste recycling sites. Environ Pollut 159:238–243. https://doi.org/10.1016/j.envpol.2010.08.034
Huang K, Li Y, Bu D, et al (2022) Trophic Magnification of Short-Chain Per- and Polyfluoroalkyl Substances in a Terrestrial Food Chain from the Tibetan Plateau. Environ Sci Technol Lett 9:147–152. https://doi.org/10.1021/acs.estlett.1c01009
Jin H, Shan G, Zhu L, et al (2018) Perfluoroalkyl Acids Including Isomers in Tree Barks from a Chinese Fluorochemical Manufacturing Park: Implication for Airborne Transportation. Environ Sci Technol 52:2016–2024. https://doi.org/10.1021/acs.est.7b06241
Kelly BC, Ikonomou MG, Blair JD, Gobas FAPC (2008) Bioaccumulation behaviour of polybrominated diphenyl ethers (PBDEs) in a Canadian Arctic marine food web. Sci Total Environ 401:60–72. https://doi.org/10.1016/j.scitotenv.2008.03.045
La Guardia MJ, Hale RC, Harvey E (2006) Detailed polybrominated diphenyl ether (PBDE) congener composition of the widely used penta-, octa-, and deca-PBDE technical flame-retardant mixtures. Environ Sci Technol 40:6247–6254. https://doi.org/10.1021/es060630m
Li H, Bu D, Fu J, et al (2019) Trophic Dilution of Short-Chain Chlorinated Paraffins in a Plant-Plateau Pika-Eagle Food Chain from the Tibetan Plateau. Environ Sci Technol 53:9472–9480. https://doi.org/10.1021/acs.est.9b00858
Li H, Li T, Beasley DE, et al (2016a) Diet Diversity Is Associated with Beta but not Alpha Diversity of Pika Gut Microbiota. Front Microbiol 7:1169. https://doi.org/10.3389/fmicb.2016.01169
Li W-L, Ma W-L, Jia H-L, et al (2016b) Polybrominated Diphenyl Ethers (PBDEs) in Surface Soils across Five Asian Countries: Levels, Spatial Distribution, and Source Contribution. Environ Sci Technol 50:12779–12788. https://doi.org/10.1021/acs.est.6b04046
Li W-L, Ma W-L, Zhang Z-F, et al (2017) Occurrence and Source Effect of Novel Brominated Flame Retardants (NBFRs) in Soils from Five Asian Countries and Their Relationship with PBDEs. Environ Sci Technol 51:11126–11135. https://doi.org/10.1021/acs.est.7b03207
Mao W, Mao L, Zhao N, et al (2022) Disposition of Bisphenol S metabolites in Sprague-Dawley rats. Science of The Total Environment 811:152288. https://doi.org/10.1016/j.scitotenv.2021.152288
Martin JW, Asher BJ, Beesoon S, et al (2010) PFOS or PreFOS? Are perfluorooctane sulfonate precursors (PreFOS) important determinants of human and environmental perfluorooctane sulfonate (PFOS) exposure? J Environ Monit 12:1979–2004. https://doi.org/10.1039/c0em00295j
Martins MF, Costa PG, Bianchini A (2023) Bioaccumulation and potential impacts of persistent organic pollutants and contaminants of emerging concern in guitarfishes and angelsharks from Southeastern Brazil. Sci Total Environ 893:164873. https://doi.org/10.1016/j.scitotenv.2023.164873
Morris AD, Muir DCG, Solomon KR, et al (2018) Bioaccumulation of Polybrominated Diphenyl Ethers and Alternative Halogenated Flame Retardants in a Vegetation-Caribou-Wolf Food Chain of the Canadian Arctic. Environ Sci Technol 52:3136–3145. https://doi.org/10.1021/acs.est.7b04890
Nizzetto L, Macleod M, Borga K, et al (2010) Past, Present, and Future Controls on Levels of Persistent Organic Pollutants in the Global Environment. Environ Sci Technol 44:6526–6531. https://doi.org/10.1021/es100178f
Parolini M, Guazzoni N, Binelli A, Tremolada P (2012) Polybrominated Diphenyl Ether Contamination in Soil, Vegetation, and Cow Milk From a High-Mountain Pasture in the Italian Alps. Arch Environ Contam Toxicol 63:29–44. https://doi.org/10.1007/s00244-012-9753-8
Qiu J (2008) The third pole. Nature 454:393–396. https://doi.org/10.1038/454393a
Ren J, Wang X, Wang C, et al (2017) Biomagnification of persistent organic pollutants along a high-altitude aquatic food chain in the Tibetan Plateau: Processes and mechanisms. Environmental Pollution 220:636–643. https://doi.org/10.1016/j.envpol.2016.10.019
Sen W, Tong W, HongLin H, et al (2011) Analysis of hydroxylated polybrominated diphenyl ethers in plant samples using ultra performance liquid chromatography-mass spectrometry. Sci China-Chem 54:1782–1788. https://doi.org/10.1007/s11426-011-4383-y
Sun H, Li Y, Wang P, et al (2022) First report on hydroxylated and methoxylated polybrominated diphenyl ethers in terrestrial environment from the Arctic and Antarctica. Journal of Hazardous Materials 424:127644. https://doi.org/10.1016/j.jhazmat.2021.127644
Trapp S, Matthies M (1995) Generic One-Compartment Model for Uptake of Organic-Chemicals by Foliar Vegetation. Environ Sci Technol 29:2333–2338. https://doi.org/10.1021/es00009a027
Van Ael E, Covaci A, Das K, et al (2013) Factors Influencing the Bioaccumulation of Persistent Organic Pollutants in Food Webs of the Scheldt Estuary. Environ Sci Technol 47:11221–11231. https://doi.org/10.1021/es400307s
Vecchiato M, Zambon S, Argiriadis E, et al (2015) Polychlorinated biphenyls (PCBs) and polybrominated diphenyl ethers (PBDEs) in Antarctic ice-free areas: Influence of local sources on lakes and soils. Microchem J 120:26–33. https://doi.org/10.1016/j.microc.2014.12.008
Voorspoels S, Covaci A, Jaspers VLB, et al (2007) Biomagnification of PBDEs in three small terrestrial food chains. Environ Sci Technol 41:411–416. https://doi.org/10.1021/es061408k
Voorspoels S, Covaci A, Lepom P, et al (2006) Remarkable findings concerning PBDEs in the terrestrial top-predator red fox (Vulpes vulpes). Environ Sci Technol 40:2937–2943. https://doi.org/10.1021/es060081k
Wang X, Gong P, Wang C, et al (2016) A review of current knowledge and future prospects regarding persistent organic pollutants over the Tibetan Plateau. Sci Total Environ 573:139–154. https://doi.org/10.1016/j.scitotenv.2016.08.107
Wang X, Wang C, Zhu T, et al (2019) Persistent organic pollutants in the polar regions and the Tibetan Plateau: A review of current knowledge and future prospects. Environ Pollut 248:191–208. https://doi.org/10.1016/j.envpol.2019.01.093
Xian H, Hao Y, Lv J, et al (2021) Novel brominated flame retardants (NBFRs) in soil and moss in Mt. Shergyla, southeast Tibetan Plateau: Occurrence, distribution and influencing factors. Environ Pollut 291:118252. https://doi.org/10.1016/j.envpol.2021.118252
Zheng X, Liu X, Jiang G, et al (2012) Distribution of PCBs and PBDEs in soils along the altitudinal gradients of Balang Mountain, the east edge of the Tibetan Plateau. Environ Pollut 161:101–106. https://doi.org/10.1016/j.envpol.2011.09.036

No competing interests reported.

Distribution and bioconcentration of seven Polybrominated diphenyl ethers (PBDEs) on the Qinghai-Tibet Plateau

Status:

Version 1

Abstract

Figures

1. Introduction

2. Materials and methods