Air Monitoring of Polychlorinated Biphenyls and Organochlorine Pesticides in Eastern Siberia: Levels, Temporal Trends, and Risk Assessment

Abstract

In this study, we evaluate the long-term and seasonal variations of polychlorinated biphenyls (PCBs), hexachlorobenzene (HCB), α-, γ-hexachlorocyclohexanes (HCH), and p,p′-dichlorodiphenyltrichloroethane (p,p′-DDT) and its metabolites through a passive air sampling method at two (urban and suburban) stations in Eastern Siberia, Russia, in 2011–2017. The median levels of HCB, ∑HCHs, ∑DDTs, ∑PCB₃₉, and ∑PCB₆ in the air were 116, 84, 55, 128, and 41 pg/m³ and 83, 21, 11, 52, and 16 pg/m³ at the urban and suburban stations, respectively. PCB and HCH levels in the air of Irkutsk decreased considerably in the 2000s, in comparison to the late 1980s and early 1990s, while an increasing trend was observed for HCB during the 2010s. The seasonality of air concentrations (with summer concentrations higher than winter concentrations) was well exhibited by PCB, HCH, and DDT, but not HCB. Significant correlations were observed between approximately all studied persistent organic pollutants and the average air temperature, quantity of precipitation, and frequency of the prevailing wind direction during the sampling period. The daily doses of PCBs, DDTs, HCHs, and HCB under human exposure by inhalation amounted to 38, 21, 27, and 35 and 17, 6, 7, and 27 pg/kg body weight per day in urban and suburban areas, respectively.

1. Introduction

The group of persistent organic pollutants (POPs) consists of compounds that may persist in the environment for a long time, may be transported long distances from their primary source or use, accumulate along food chains, and are toxic to humans and other living organisms [1,2,3]. Polychlorinated biphenyls (PCBs) and organochlorine pesticides (OCPs) including α-, γ-hexachlorocyclohexanes (HCH), p,p′-dichlorodiphenyltrichloroethane (p,p′-DDT) and its metabolites, and hexachlorobenzene (HCB) are included in the list of POPs. The compounds are regulated by the Stockholm Convention [4,5,6]. The Stockholm Convention on Persistent Organic Pollutants (POPs) [4] was adopted on 22 May 2001 and entered into force on 17 May 2004. The Russian Federation joined the Stockholm Convention in 2002 [7] and ratified it in 2011 [8]. By virtue of the Stockholm Convention, levels of POPs in the atmosphere and other environmental compartments should be reduced, and the impacts of POPs on ecosystems and physiological functions of the human body should be decreased [4]. Evaluation of the effectiveness of the Stockholm Convention involves the assessment of environmental background concentrations in media with a high potential for comparability. For example, air monitoring and human exposure through breast milk have been used as core media for such evaluation [5,9].

Active air sampling (AAS) or passive air sampling (PAS) methods are generally used to measure POP concentrations in the atmospheric air [3,10,11,12,13,14,15,16].

In the former USSR, PCBs and OCPs were measured in the atmospheric air only in the framework of “Comprehensive Environmental Assessment of Territories of some regions and natural areas” by the Scientific and Production Association NPO “Typhoon”, which was one of the research institutions of Roshydromet ([17,18,19] and others).

At present, there is no unified state program for POP monitoring in environmental media in the Russian Federation [20]. The state monitoring of some POPs (usually DDT and its metabolites, HCB, HCHs, and, less commonly, PCBs) in surface water, seawater, soil, and sediments is included in the programs of the state monitoring network of Federal Service for Hydrometeorology and Environmental Monitoring (Roshydromet) [19,20]. In the Russian Federation, the determination of POP concentrations in ambient air has been limited to some POP groups at separate stations during certain periods of time conducted by several groups of researchers [10,17,18,21,22,23,24,25,26,27,28,29,30,31,32,33].

The first data on PCBs and OCPs concentrations in the atmospheric air of some settlements in the Lake Baikal region (the towns of Irkutsk, Angarsk, Baikalsk, Usol’e-Sibirskoe, and the settlement of Listvyanka) were obtained in the late 1980s [18]. In 2013, 2014, and 2016, POPs were analyzed in the air of several settlements along the shores of Lake Baikal (Listvyanka, Kultuk, Tankhoi) [22,34]. In the last three decades, “Typhoon” NPO engaged in the monitoring of POPs in the Arctic air under the Arctic Monitoring Assessment Program (AMAP) [24,35,36]. In Russia, such monitoring was performed at the following stations: Dunai (1993–1995), Valkarkai (2002–2003, 2008–2010), Amderma (1999–2001, 2015–2017), and Tiksi (2009–2011, 2015–2017), as well as at the station in Kaluga Region, for comparison [20,23]. The AAS method was employed for monitoring.

In addition, various Russian and international scientific groups are involved in POP determination in the air of some regions in the Russian Federation under global international projects [3,10,26], international collaborations [27,28], and Russian scientific projects (Chechen Republic [29]; Asian part of Russia [30,31,32,33]), using both active [27,28] and passive air sampling methods [29,30,31,32,33].

In contrast to AAS, passive air sampling allows data to be obtained over a longer, continuous period of time (from several weeks to 1 year, depending on the sorbing medium); it does not require the use of specialized equipment and power sources [37]. The PAS method is widely used for POP studies around the world, both in investigation programs in certain areas/countries and within the framework of international projects, including AMAP (the Arctic Monitoring and Assessment Program), MONET (Monitoring network), UNEP (the United Nations Environment Program), TOMP (the Toxic Organic Micro Pollutants), and GAPS (the Global Atmospheric Passive Sampling) [3,10,11,12,38,39].

In the European part of Russia, the first POP research was performed using PAS in the context of Global Atmospheric Passive Sampling (GAPS) studies at the settlement of Danki [3,10,29]. In the Asian part of Russia, the first data on POPs in air using a PAS method were obtained for settlements in Irkutsk Region, the Russian Far East, the Kamchatka Kray, Chukotka Autonomous Okrug, and Republic of Yakutia, in the summer of 2008 and winter of 2009–2010 [33,34]. Passive air samplers were installed in regional centers and their suburbs in Siberia and the Russian Far East [33,34]. Furthermore, seasonal variations of POP air concentrations were studied in two regional centers in the Russian Far East (Vladivostok and Khabarovsk) in 2010–2012 [35].

The aim of the current study is to present the results from continuous passive air monitoring of PCBs and OCPs at two stations in the southern part of Irkutsk Region in the period 2011–2017. We also focus on the seasonal variations in atmospheric PCB and OCP concentrations, changes in the concentrations of POPs and their relative composition since the late 1980s, and the current environmental and anthropogenic factors influencing PCB and OCP levels in air.

2. Materials and Methods

2.1. Sampling Site

The study site lies in the southern part of the Irkutsk–Tcheremkhovo plain, at the foot of the Eastern Sayan (Figure 1). The climate is determined by the physical and geographical conditions of the area, including its location in the center of the Eurasian continent, the relief and regulatory influence of water bodies (e.g., Lake Baikal, Angara River, and the Irkutsk reservoir), and atmospheric circulation (Asian anticyclone in winter and increased cyclonic activity in summer). The combination of these features results in a sharply continental climate, with severe prolonged low-snowfall winters with weak winds and frequent inversions of air temperature, and warm summers with heavy precipitation and increased wind activity [40,41]. In Irkutsk Region, the difference between the average temperatures of the warmest and coldest months reaches 30–45 °C [40]. The maximum daily air temperature amplitude can reach 30 °C, mainly due to night cooling [42]. The dominant wind directions are west and northwest [43,44]. In Irkutsk town, January is the coldest month during the year (mean temperature is −20.6 °C, absolute temperature minimum is −50 °C). June is the warmest month (mean temperature is 17.6 °C, absolute temperature maximum is 36 °C) [44].

We focused on two stations: (1) one in the residential area of Irkutsk (52°14′46.42″ N, 104°16′31.30″ E, altitude 470 m a.s.l.), and (2) another in the valley of River Olkha, 20 km from the first Irkutsk station, in a dacha cooperative (52°6′33.40″ N, 104° 5′36.50″ E, altitude 653 m a.s.l.). The dacha cooperative is a settlement used for summer vacationing and residence with the production of local vegetables, berries, and fruits on land without pesticides, as a hobby and for own consumption [45]. However, the application of pesticides is also possible for some households in the settlement. The second station is conditionally termed as a “suburban station” in this paper.

The town of Irkutsk is a regional center of Irkutsk Region with a population of over 620,000 people (25.9% of the population of Irkutsk Region [46]).

Irkutsk is part of the industrial zone of Irkutsk Region, which includes the towns of Irkutsk, Angarsk, Shelekhov, and Usol’e-Sibirskoe, having a total population of 1,108,400 people [47]. The industrial activities include oil refining, chemical industry, machine-building complexes, non-ferrous metallurgy, and the production of building materials [47]. Agriculture (animal husbandry and crop production) is developed around the cities, in order to supply the population with locally produced food.

Both stations lie downwind of the town of Usol’e-Sibirskoe, a former industrial site with a large organochlorine synthesis complex (Usol’ekhimprom). Usol’ekhimprom has been recognized as a source of PCBs and polychlorinated dibenzo-p-dioxins and furans (PCDD/F) [48]. Atmospheric emissions and wastewater discharges from the industrial source of PCDD, PCDF, and PCB in Usol’e-Sibirskoe affect the content of these compounds in environmental media and biota, in areas both near the source and at a considerable distance from the source [48,49]. PCB and PCDD/F levels in the blood and breast milk of residents of Usol’e-Sibirskoe are among the highest in the region [50,51].

2.2. Air Sampling

Passive air samplers consisting of a polyurethane foam (PUF) disc (14 cm diameter; 1.4 cm thick; 369 cm² surface area; 0.02 g·cm⁻³ density) housed in two stainless-steel dome chambers (external diameters: 22.5 and 18.5 cm) were deployed at the two sites from September 2010 to February 2018. In total, there were 42 and 43 sampling periods at the urban and suburban stations, respectively. The average duration of one sample period was 65 days.

Prior to each sampling campaign, the sampling chambers were prewashed with soap, solvent-rinsed (acetone and hexane), and stored in ziplocked polyethylene bags. The PUF discs were precleaned with synthetic detergents, followed by acetone, and then dichloromethane (DCM) in a Soxhlet apparatus for 10 h, after which the PUF discs were dried in a desiccator under negative pressure. Before and after exposure, the PUF discs were packed in chemically pure glass containers tightened with Teflon tape and stored at –20 °C until deployment and analysis.

2.3. Chemical Analysis

Organochlorine pesticide and polychlorinated biphenyl analyses were performed in the laboratory of the Institute of Geochemistry in Irkutsk, using the method described by [49,52].

PUF discs were extracted in a Soxhlet extractor with dichloromethane (DCM) for 12 h. Surrogate and internal standards (PCB-14 and PCB-65, respectively) were added to the extraction solvent before the Soxhlet extraction of PUF discs.

The extracts of samples were cleaned using a chromatographic column containing silica gel (3 g, activated at 400 °C), aluminum oxide (3 g, activated at 850 °C), and Na₂SO₄ (3 g). The columns were conditioned using 40 mL of DCM/n-hexane (1:1 v/v), followed by 10 mL of n-hexane. The sample extracts were loaded and eluted with 12 mL of n-hexane, followed by 40 mL of DCM/n-hexane (1:9 v/v). To prepare for gas chromatography, the fraction containing PCBs and OCPs was evaporated to 1 mL with a rotary evaporator, and further reduced to a volume of 30 μL using a stream of nitrogen.

The GC/ECD analyses were performed on an HP 5890A Series II gas chromatograph using a DB-5 capillary column (J&W Scientific, 0.25 μm film thickness, 0.25 mm inner diameter, 60 m long). The carrier gas was helium (He), and the makeup gas was nitrogen (N₂). The temperatures of the detector and the injector were 320 °C and 270 °C, respectively. The temperature program was as follows: 90 °C (2 min hold), 170 °C at 22 °C·min⁻¹, and then 280 °C at a rate of 1.32 °C·min⁻¹ (17 min hold). All the samples were analyzed for 39 congeners of PCBs (IUPAC Nos.: 8/5, 28, 31, 44, 47, 49, 52, 70/76, 74, 82, 85, 87/115, 91, 95/66, 97, 99, 101/90, 105, 110/77, 118; 128, 132, 138, 141, 149, 153, 158, 156, 170, 180, 183, 187, and 189), HCB, p,p′-DDT, p,p′-dichlorodiphenyldichloroethane (p,p′-DDD), p,p′-dichlorodiphenyldichlorethylene (p,p′-DDE), and α- and γ-HCH.

PCBs and OCPs were quantified on the basis of retention time found within 2 s of the standard, a signal-to-noise ratio of at least 3, response factors obtained from the standards for the individual compounds, and the concentration of the internal standard (PCB-65).

Twenty-two PCB congeners, including indicator PCB congeners, p,p′-DDTs, and α-HCHs, were confirmed in several samples using a Chromatec Crystal 5000 gas chromatograph-equipped mass spectrometer in the electronic ionization mode. Due to coelution, PCB-110 and PCB-77, PCB-47 and PCB-75, PCB-70 and PCB-76, PCB-95 and PCB-66, and PCB-87 and PCB-115 were quantified together.

Site- and season-specific sample air volumes were calculated according to the Tom Harner Template [53], considering site-specific seasonal average temperatures. A sampling rate of 4 m³/day was used to derive concentrations for all compounds.

All of the solvents used were distilled and checked for interference prior to use. Standards of individual PCB congeners, the PCB mixture, and the OCP mixture were purchased from the Dr. Ehrenstorfer Laboratory (Ausburg, Germany). Aluminum oxide and silica gel for column chromatography were purchased from MERCK (Darmstadt, Germany).

2.4. Quality Assurance/Quality Control (QA/QC)

Method recoveries were determined using spiked samples. They ranged between 83% and 119%. Corrections for recoveries were not made. To assess the potential pollution during air sampling and to estimate the purity of reagents and instruments for all types of sample processing, field blank samples (PUF discs without exposure, for assessing the sampling purity) and laboratory blanks (without the samples, for assessing the purity of reagents and laboratory vessels) were used. Field blanks were obtained by transporting, installing, and immediately removing PUF discs during each deployment campaign. Laboratory blanks were run with each batch of seven samples. Only samples in which the level of the analyzed compound exceeded the level of the blank by 3.5 times were taken into consideration. The levels in laboratory blanks never exceeded 2% of the quantities detected in PUF discs exposed and field blanks for PCBs and OCPs, indicating minimal contamination during the analysis. OCP and PCB contents in field blanks were 5.6% (0.4–11%) and 12% (1.9–30%) of OCP and PCB detected in exposed PUF discs, respectively (Table S1). All results were blank-corrected using field blanks, produced for each campaign. The recoveries for the PCB-14 surrogate that were added to each sample were 34–93% (mean 67%) for PUF discs. No correction was applied to the samples.

Method detection limits (MDLs) were derived from 43 field and 18 laboratory blanks and quantified as the average of blanks plus three standard deviations. MDLs ranged between 0.01 and 1.54 ng/PAS for PCBs (depending on the congener) and between 0.14 and 1.12 ng/PAS for OCP (Table S1). Concentrations below MDL were set to ½ MDL for the calculation of sum, average and median, standard deviation, and standard error, and for the statistical analysis.

To check for reproducibility, at one station, five PAS samplers were installed simultaneously for 60. The coefficients of variability of the POP concentrations were in the range of 8–25%, and they were low only for DDD (40%), PCB-74 (40%), and PCB-179 (57%).

2.5. Statistical Analyses

Statistical analyses were performed using the STATISTICA 6.0 software for Windows (StatSoft, Tulsa, OK, USA). Concentrations of PCBs and OCPs are reported as the mean and median, with the standard deviation (SD), standard error (SE), and ranges. The average annual POP values included data for the period of sampling from December of the prior year to November of the subsequent year, corresponding to four full seasons of the year concerned without division of the winter season into 2 years. For statistical analyses, all the data were ln-transformed. The significance of the difference in POP levels at two stations in total and in separate years was assessed using Student’s t-test, in independent groups. Linear and multiple regressions were conducted to analyze the temporal trends of atmospheric POPs, as well as the dependence of POP levels on temperature, precipitation values, west and northwest directions, and quantities of calms during periods of sampling. Spearman’s test was employed to evaluate correlations between POP levels determined in air at urban and suburban stations. The cluster analysis of the seasonal changes in the PCB composition was performed in accordance with Gusev et al. [54]. A confidence level of p < 0.05 was used as the criteria for statistical significance.

2.6. Daily Exposure and Health Risk Assessment

The daily exposure and health risk indices were investigated, using the risk assessment method [55,56,57]. The exposure pathway for PCBs and OCPs under inhalation of air was examined for adult residents. The exposure model for the exposure pathway is as follows:

$$I_i=\frac{C\times IR\times EF\times ED}{BW}\times \frac{1}{AT},$$

where I_i is the daily intake (mg/kg body weight per day), C is the concentration of contaminants in atmospheric air (mg/m³), IR is the inhalation rate (20 m³ per day), EF is the exposure frequency (days per year), ED is the exposure duration (70 years), BW is body weight (70 kg), and AT is the averaging time, i.e., the period over which exposure is averaged (70 years × 365 days/year for carcinogenic compounds).

The noncancer risk was defined by comparing daily intake with the level of harmless impact in the route. The total hazard index (THI) is the sum of hazard indices of the contaminants concerned [55,56,57]:

THI = ΣHQi,

where HQi is the hazard quotient of the i-th toxicant to come from inhalation air:

HQ_i = I_i/RfD,

where RfD is the reference dose (mg/(kg per day).

The total cancer risk (TCR) is calculated by using the values of exposure and factors of carcinogenic potential (slope factor):

TCR = ΣCR_i,

where CR_i is the cancer risk of the i-th carcinogen coming from the inhalational exposure pathway:

CR_i = I_i·SF,

where SF is the slope factor (mg/(kg per day)⁻¹) (see Table S2).

3. Results and Discussion

3.1. Levels and Comparison with Levels in Other Areas

The PCB and OCP levels are summarized in

Table 1. Mean, median, minimum–maximum, standard deviation (SD), and standard error (SE) of PCB and OCP levels in air at two stations in Irkutsk Region during 2010–2018 (pg/m³) and the significance of the difference (p) in air concentration between these two stations (* p < 0.05; ** p < 0.01; *** p < 0.001; “-“, p > 0.05; nd, not detected; BDL, below detected limit).

	Mean	Median	Min	Max	SD	SE	p	Mean	Median	Min	Max	SD	SE
	Urban, 1st station							Suburban, 2nd station
HCB	123	116	18.9	253	60.3	9.30	*	96	83	12.7	224	52	8.0
α-HCH	73	72	28	154	33	5.1	***	16	16	BDL	33	7.7	1.2
γ-HCH	21	19	1.6	59	15	2.4	***	9.4	6.8	BDL	34	9.3	1.4
∑HCH	94	84	30	209	47	7	***	26	21	0.8	67	15	2.4
α/γ-HCH	6.4	3.6	2.1	36	6.7	1.0	-	9.8	1.7	0.03	74	18	2.8
p,p′-DDT	35	27	1.7	141	34	5.2	***	14	7.5	BDL	66	15	2.3
p,p′-DDE	34	29	4.4	122	27	4.1	***	5.3	2.6	BDL	34	6.6	1.0
p,p′-DDD	3.9	1.7	BDL	31	5.9	0.9	**	1.7	0.6	BDL	14	3.1	0.5
∑p,p′-DDX	74	55	6.8	277	62	9.6	***	21	11	0.7	98	22	3.5
p,p′-DDT/p,p′-DDE	0.91	0.83	0.14	2.09	0.44	0.07	***	2.81	2.68	0.34	6.16	1.49	0.23
p,p′-DDT/(p,p′-DDE + p,p′-DDD)	0.81	0.77	0.12	1.80	0.36	0.06	***	2.16	2.10	0.16	5.10	1.22	0.18
PCB-8 + PCB-5	0.68	0.09	BDL	25	3.84	0.59	-	0.99	0.09	BDL	34	5.25	0.80
PCB-31	9.94	10.3	1.36	23	5.39	0.83	***	3.33	3.06	BDL	7.99	1.96	0.30
PCB-28	9.24	9.52	1.05	20	5.28	0.82	***	2.57	1.93	BDL	8.74	2.16	0.33
PCB-52	12.0	12.6	BDL	26.1	6.48	1.00	***	6.72	5.82	BDL	26.8	5.11	0.78
PCB-49	4.38	4.18	0.62	11.7	2.75	0.42	***	1.13	0.78	BDL	5.64	1.21	0.18
PCB-47	1.04	0.52	BDL	5.09	1.19	0.18	***	0.21	0.05	BDL	1.94	0.36	0.06
PCB-44	8.63	9.31	1.71	16.6	4.31	0.67	***	3.02	2.31	BDL	23.5	3.68	0.56
PCB-74	4.74	4.04	BDL	24.7	4.30	0.66	*	2.56	1.75	BDL	8.76	1.84	0.28
PCB-70 + PCB-76	3.20	1.46	BDL	14.1	3.61	0.77	**	0.53	0.20	BDL	7.95	1.24	0.19
PCB-95 + PCB-66	13.6	12.4	0.03	43.0	8.94	1.38	**	6.71	4.57	BDL	36.0	6.83	1.04
PCB-91	3.22	2.68	BDL	11.8	2.76	0.56	0.054	0.80	0.11	BDL	5.90	1.26	0.19
PCB-101 + PCB-90	13.6	13.2	BDL	83.7	13.2	2.03	***	6.62	3.79	BDL	41.7	8.72	1.33
PCB-99	6.33	6.37	BDL	24.7	4.57	0.70	***	2.93	2.35	BDL	13.1	2.55	0.39
PCB-97	1.88	1.52	BDL	6.59	1.53	0.24	***	0.96	0.52	BDL	6.35	1.25	0.19
PCB-87 + PCB-115	4.33	4.32	0.44	20.8	3.29	0.51	***	2.43	1.82	BDL	15.4	2.72	0.41
PCB-85	0.82	0.58	BDL	3.05	0.78	0.12	-	0.44	0.30	BDL	1.45	0.35	0.05
PCB-110 + PCB-77	9.43	9.06	BDL	27.9	7.27	1.12	**	5.11	3.89	BDL	21.6	4.99	0.76
PCB-82	0.47	0.40	BDL	1.68	0.45	0.07	-	0.37	0.23	BDL	2.85	0.57	0.09
PCB-149	3.82	3.59	BDL	11.6	3.13	0.64	***	0.48	0.06	BDL	2.51	0.64	0.10
PCB-118	9.96	9.27	2.45	36.9	6.28	0.97	***	5.55	4.32	0.48	21.9	4.49	0.69
PCB-153	4.32	3.62	BDL	14.7	4.04	0.62	***	1.58	0.61	BDL	11.1	2.40	0.37
PCB-132	0.35	0.25	BDL	1.13	0.33	0.07	*	0.06	0.01	BDL	0.29	0.08	0.01
PCB-105	2.55	2.28	BDL	8.21	2.18	0.34	**	1.24	0.36	BDL	9.46	2.12	0.32
PCB-141	0.44	0.11	BDL	2.16	0.57	0.09	***	0.09	0.02	BDL	1.18	0.21	0.03
PCB-138	5.72	4.94	BDL	18.0	4.42	0.68	***	2.73	1.56	BDL	19.1	3.48	0.53
PCB-158	0.30	0.15	BDL	1.56	0.34	0.05	*	0.21	0.08	BDL	1.98	0.40	0.06
PCB-187	0.67	0.45	BDL	2.78	0.76	0.12	***	0.09	0.01	BDL	0.77	0.18	0.03
PCB-183	0.49	0.38	BDL	1.49	0.43	0.07	***	0.18	0.10	BDL	0.80	0.21	0.03
PCB-128	0.81	0.64	BDL	3.10	0.73	0.11	***	0.45	0.20	BDL	5.27	0.85	0.13
PCB-156	0.25	0.19	BDL	1.31	0.27	0.04	***	0.18	0.02	BDL	4.03	0.62	0.09
PCB-180	0.79	0.39	BDL	4.08	0.93	0.14	***	0.23	0.02	BDL	3.11	0.66	0.10
PCB-170	0.29	0.19	BDL	1.79	0.35	0.05	***	0.12	0.02	BDL	2.24	0.38	0.06
∑PCB39	134	128	28	393	81	12	***	61	52	7.9	225	43	6.6
∑PCB6	45.7	41.3	9.66	158	30.1	4.6	***	20.5	16.5	1.7	72	16	2.4
diCB	0.68	0.09	0.04	24.9	3.84	0.59	-	0.99	0.09	BDL	34.5	5.25	0.80
triCB	19.2	20.4	3.59	42.9	10.4	1.61	***	5.90	5.36	BDL	15.3	3.88	0.59
tetraCB	46.1	41.7	8.67	118	25.3	3.90	***	20.9	18.4	3.61	80.3	15.8	2.41
pentaCB	51.3	50.0	6.17	207	36.3	5.61	***	26.6	20.6	2.73	113	22.8	3.48
hexaCB	14.2	13.1	0.94	42.0	11.4	1.76	***	5.77	3.53	BDL	40.6	7.30	1.11
heptaCB	2.26	1.49	0.05	9.38	2.33	0.36	***	0.63	0.31	BDL	6.59	1.14	0.17
octaCB	0.05	0.02	BDL	0.13	0.05	0.02	-	nd	nd	nd	nd	nd	nd
diCB, %	0.38	0.07	0.02	11.9	1.82	0.28	***	2.07	0.18	0.04	66.7	10.2	1.55
triCB, %	15.4	14.6	4.77	30.8	5.52	0.85	**	11.8	10.5	0.39	38.1	8.34	1.27
tetraCB, %	35.9	36.2	23.3	55.8	6.33	0.98	-	36.0	36.9	15.1	53.9	9.40	1.43
pentaCB, %	37.8	36.6	21.9	58.8	7.19	1.11	-	41.1	42.0	8.13	72.0	11.4	1.74
hexaCB, %	9.19	9.59	2.26	16.3	3.46	0.53	-	8.14	7.37	1.23	28.5	4.94	0.75
heptaCB, %	1.36	1.15	0.10	3.48	0.86	0.13	**	0.83	0.63	0.13	4.63	0.87	0.13
octaCB, %	0.03	0.01	0.01	0.09	0.04	0.02	-	nd	nd	nd	nd	nd	nd

. Levels of POPs found in the air at the urban and suburban Irkutsk stations were well below the maximum permissible levels accepted in Russia (DDTs: 0.001 mg/m³ [58], HCB: 0.013 mg/m³, HCHs: 0.001 mg/m³ [59], and PCBs: 1 mg/m³ [60]).

∑PCBs was slightly higher than HCB levels in air at the urban Irkutsk station (median: 128 and 116 pg/m³, respectively). The median HCB was about one-third greater than the median ∑PCB in air at the suburban station (83 and 52 pg/m³, respectively). PCBs and HCB were followed by ∑HCHs > ∑DDTs at both stations. POP levels in air at the urban station were significantly higher than those in air at the suburban station (Table 1), thus indicating the presence of a greater number of historical and/or current POP sources and more intensive emissions and/or reemissions of POPs in the urban area, compared to the suburban area. A strong positive correlation between the average total PCB concentration in air and the human population within a 25 km radius of each sampling site was also observed by Sun et al. [61].

At the same time, a significant strong positive correlation for each analyzed OCP was found between OCP levels in air at urban and suburban stations (Table S3), suggesting the same sources of OCPs at these stations and the influence of similar factors on the general patterns of the temporal OCP distributions. The correlations between the levels of most of the PCB congeners and homologs in the air at urban and suburban stations were significant but weaker than those of the OCP levels, which may be a result of the changing number of inhabitants during the year in the suburban area (from units of people in winter to hundreds in summer), correspondingly changing the number and intensity of combustion sources, transport load, and other potential PCB sources associated with human activity.

The PCB and OCP levels were compared to levels found in passive air sampling monitoring studies in Asian countries in the 2010s (see

Table 2. PCB and OCP levels in atmospheric air at Irkutsk, GAPS network stations, and Asian countries obtained using PAS sampling techniques in the 2010s (pg/m³).

				n	∑PCBs	α-HCH	γ-HCH	DDT	DDE	HCB	Reference
Irkutsk-1	Urban	2010–2018	AM/Med	40	134/128	73/72	21/19	35/27	34/29	123/116	This study
				6	46/41						This study
Irkutsk-2	Suburban	2010–2018	AM/Med	40	61/52	16/16	9.4/6.8	14/7.5	5.3/2.6	96/83	This study
				6	20/16						This study
GAPS	All	XII.2004-XII.2005	GM	48	26 (18–38)	4–7	6–15	BDL-1	1–5	-	[29]
GAPS	All /polar /background/rural/agricultural/urban	2011–2014	GM	7	4/ 10/ 2.5/ 4.8/ 5.8/ 27	4.8/ 36/ 4/ 2.2/ 5.3/ 3.5	4.1/ 7.8/ 3.2/ 2.0/ 4.9/ 9.4	-	-	-	[3]
Mongolia	Rural	2011–2015	range	28	6–254	1–56	0.2–34	0.1–26	0.1–21	11–143	[62]
				6	2–78
China, Beijing	Residential, industrial, suburban and rural	II.2011-III.2012	range	19	38.6–139	-	-	-	-	-	[63]
Southeast China	Rural	X.2012-IX.2013	AM	-	-	9.45	4.04	-	-	-	[64]
Yangtze River Delta, China	Urban, rural	VI.2010-VI.2011	AM	6	22–44	nd-38 *	-	106–215 @	105–178	17–376	[65]
Western China	Different areas	VII-X.2015	AM	-	-	9.46	7.78	2.3	2.46	22.9	[66]
China	Total	2016–2017	AM	18	69						[67]
China	Urban/ Rural/ Remote/ Industrial/ E-waste	2016–2017	Med	209	92/ 66/ 32/ 103/ 1344	-	-	-	-	-	[67]
India		IV-V.2013	range	32	254–432	-	-	-	-	-	[68]
India	Urban	XII.2013-III.2014	AM	7	140	60	48	72	28	-	[69]
India,	Urban	I.2015	AM (range)	25	9000 (500–52000)	-	-	-	-	-	[70]
India	Urban, suburban	III-IV.2015	AM	-	-	381	233	1079	610	-	[71]
northern India	Urban, suburban, rural	I-II.2017; V-VI.2017	range	25	25–1433	-	-	-	-	-	[16]
Nepal	Agricultural, urban	VIII.2014–VIII.2015; XI.2015– XI.2016	range	6	1.2–47	1.3–73	2–3300	2–621	2–364	6–350	[72]
Nepal	Urban	VIII-X.2014	range	26	30–1002	3.5–51	4–2720	8–3340	4.2–1760	2.2–146	[73]
Viet Nam	Urban	I-III.2013, IX-XI.2015	range	7	12–70	-	-	-	-	-	[74]
				29	21–336
Turkey	Rural, urban	V.2014-IV.2015	AM	43	108	64 *	-	134 **	-	45	[75]
Turkey	Agricultural	III.2014-III.2015	Med (range)	15	95 (nd-2764)	5.4 (3–12) #	-	67 (20–310) &	-	-	[76]

n, number of PCB congeners; AM, arithmetic mean; Med, median; GM, geometric mean; “-”, no data or data not presented in paper; *, the sum of four isomers of HCH; **, the sum of five DDX metabolites; @, the sum of six DDX metabolites; #, the sum of two isomers of HCH; &, the sum of three DDX metabolites.

) and other passive and active air sampling monitoring studies in Russia (see Tables S4 and S5). The POP levels in urban air in our study were higher than those found in the GAPS program, in both 2004–2005 and 2011–2014 [3,29]. Meanwhile, the levels of PCBs and HCHs in the air at the suburban station were in agreement with the levels in the air of urban areas within the GAPS network [3] (Table 2).

PCB levels in air at Irkutsk urban and suburban stations (134 and 61 pg/m³, respectively) were in the range of values of PCB levels at urban stations in Asian countries in the 2010s ((China: 92 pg/m³ [67], India: 140 pg/m³ [69], Vietnam: 21–336 pg/m³ [74]; Table 2), as well as at the rural PAS monitoring station in neighboring Mongolia lying at the shore of Lake Hovsgol during the same period of time (6–254 pg/m³) [62]. The concentrations of PCBs at Irkutsk stations were comparable to the lowest values or lower than those found in the settlements of the Asian part of Russia in 2008–2009 (29–3530 pg/m³) [30,31], as well as in line with the concentrations found in the regional centers of the southern Russian Far East in 2010–2011 (84–161 pg/m³) [32]. PCB concentrations were also lower than those found at sites in the European part of Russia for all the years of observation there (1.1–31 μg/m³ in the late 1980s; 109–843 pg/m³ in the 2000–2010s [3,10,17,23,26,77,78]; Table S4). At the same time, PCB levels were higher than those in the air at most observation sites in the Russian Arctic (5–55 pg/m³), with the exception of Valkarkai station in the early 2000s (~70 pg/m³ [79]).

The OCP levels observed in our study were comparable or lower than relevant values found in Asian countries (e.g., α-HCH in India: 60–381 pg/m³ [69,71]; Nepal: 1.3–73 pg/m³ [72]; Turkey: 64 pg/m³ [75]; DDT in China: 2.3–215 pg/m³ [65,66]; Turkey: 134 pg/m³ [75]; see Table 2), higher than or comparable to the highest values found in air in the Russian Arctic (DDT: 0.14–1.6 pg/m³ [35,36]; γ-HCH: 0.18–12 pg/m³ [35,36]; Table S5), and comparable to or higher than those at other air monitoring stations in Russia, including Moscow Region in 2004–2010, 20 stations in the towns of the Asian part of Russia in 2008–2009, two towns in the Russian Far East in 2010–2012, and 13 settlements in Irkutsk Region in certain years (Table S5). The DDT levels in Irkutsk stations were 1–2 orders of magnitude lower than those in areas where DDT is used at present or in the past (India: DDT = 1079 pg/m³ [71]; northern area of Irkutsk Region: ∑DDTs = 125–3975 pg/m³ [80]). The levels of HCB in the air at the urban and suburban Irkutsk stations (medians: 116 and 83 pg/m³, respectively) were higher than the calculated average HCB air concentration for the Northern Hemisphere (55 pg/m³) [81].

3.2. Temporal Trend of PCB and OCP in Air

The studies reporting PCBs in the air in Irkutsk in August 1988 [18], as well as PCBs, HCHs, and DDTs in June 1991 [28], allowed us to assess the temporal changes of these compounds in air of Irkutsk over roughly three decades. The PCB and OCP levels found in 2008–2009 at urban Irkutsk station are also included in the assessment of temporal changes [30,31]. The PCB and OCP levels in sampling periods close to the periods during 1988 and 1991 are compared in Figure 2.

The PCB levels in Irkutsk air decreased considerably in the 1990s and the 2000s, in comparison to the late 1980s (Figure 2a). The PCB levels in the air in 1991 (the sum of 41 PCB congeners) [28] and in the summer of 2008–2017 (the sum of 31 and 39 PCB congeners in 2008 and 2011–2017, respectively) (present study) were about 500 and 1600–6900 times lower than those in 1988 (unknown number of PCB congeners) [18]. PCB levels in air in 2008 and 2011–2017 decreased by three and 5–13 times, respectively, in comparison to those observed in 1991. It should be also noted that PCB levels in Irkutsk in the 2010s were 1.5–4 times lower than those in 2008–2009. A slight increase of POP levels in the air was also observed in the late 2000s at air monitoring stations both in Asian countries (China [67,82]; Mongolia [62]) and in the European and Asian parts of Russia [83].

The levels of α-HCH and γ-HCH in the summers of 2008–2017 were, respectively, 15–47 and 10–27 times lower than the values of these HCH isomers in 1991 (Figure 2b). The ratio of α/γ-HCHs also decreased from 4.6 in June 1991 [28] to 2.85–3.26 in summers of 2011–2013 and 2.28–2.55 in summers of 2014–2017 (Figure S1). In accordance with Shen et al. [84] and de la Torre et al. [85], an α-/γ-HCH ratio ranging between 4 and 7 indicates fresh input of technical HCH into the atmosphere. Technical HCH and lindane applications in agriculture were banned in 1986 and 1990, respectively, in Russia [86]. In the 1980s, 1100–2500 tons of pesticides were used annually in Irkutsk Region [87]. The contribution of organochlorine compounds, including a 12% mixture of HCH, keltan, and other OCPs, accounted for up to 40% of the total amount [87]. The pesticide load per unit of arable land in 1981–1985 was 1.12 kg of active substance per hectare, while the HCH load was 0.34 [87]. The α-/γ-HCH ratio suggests fresh inputs of technical HCH in 1991, with a decrease in the technical HCH application effect in subsequent decades. The input of HCH in environmental media was also possible from sites used for the storage of obsolete pesticides, including some areas of Irkutsk Region [88,89].

Unlike HCHs and PCBs, the sums of p,p′-DDT and p,p′-DDE in the summers of 2008–2013 were higher than their values in 1991 (Figure 2c). The p,p′-DDT + p,p′-DDE levels in the summers of 2014–2017 returned to approximately the same levels as in 1991. Some differences may also have resulted from different analytical methods (GC–MS and AAS in 1991 [28] and GC–ECD and PAS in our investigation in the 2010s). At the same time, the DDT/DDE ratio changed from 2.5 in June 1991 [28] to 1.16–1.79 in the summers of 2011–2013 and to 0.78–0.93 in the summers of 2014–2017 (Figure S1), thus indicating the decrease in fresh DDT inputs into the environment around Irkutsk. The agricultural application of DDT and pesticide mixtures containing DDT was officially banned in 1970 [86]. After this, DDT continued to be used against insects being carriers of pathogens of vector-borne diseases [88,90,91]. As is the case with HCH, DDT may enter the environment from storage sites after the use of such pesticides is banned [88]. There is no information about the unofficial application of obsolete OCPs in agriculture or for other purposes.

The temporal trend during the period from September 2010 to February 2018 was investigated using a linear regression analysis of ln-transformed average annual POP values versus ordinal number of the year in the investigations (the first variant of the calculation), or using data obtained in each period of sampling versus the ordinal number of the year plus middle month in each period of sampling relative to the number of months in the year (the second variant of the calculation). Significant results of the linear regression analysis are presented in Table S6. Significant changes observed in the first variant of the calculation were observed for α-HCH, the sum of HCHs, p,p′-DDD, p,p′-DDT, the sum of p,p′-DDTs, and five of the 39 analyzed PCB congeners in the air of the urban station only. Most of these changes represented a decreasing trend. There appeared to be no significant changes in average annual POP levels in the air at the suburban station during the period 2011–2017.

When using POP data for every sampling period, there was a reduction in both the number of POPs with significant changes in levels and the amount of data described by this model. It should be noted that HCB levels were significantly increased in the period 2010–2018, as opposed to the other analyzed POPs. The increase in HCB level was more noticeable when we took into account the data for 2008–2009 (Figure 3).

The same declining trends for PCBs, DDTs, and HCHs in air since the 1990s have been observed at various air monitoring stations around the world [3,11,36,38,85,92,93,94,95].

On the other hand, increasing HCB trends have been observed in the 2010s in the air at both urban/industrial and remote/background monitoring stations around the world [38,81,93,96,97,98], or the temporal trends were unclear [36,99,100,101]. At present, HCB is becoming one of dominant compounds among the OCPs and selected pesticides in environmental media including air [102]. The large chemical enterprise named Usol’ekhimprom, located in Usol’e-Sibiskoe area, is the only known significant industrial source of PCBs and PCDFs, as well as HCB, in the southern part of Irkutsk Region [48,49,103], which stopped operations in the middle of 2000s. The industrial area of Usol’ekhimprom remained without recultivation until the early 2020s, and it could remain a source of continued HCB atmospheric emission from its contaminated surfaces for a long time. The dominant wind directions in the area are west and northwest [43]. The Irkutsk town atmospheric air monitoring station is located about 70 km from the industrial area of Usol’ekhimprom along the River Angara valley in the direction of the dominant northwest winds, while the suburban station is located 80 km from Usol’e-Sibirskoe and 20 km perpendicularly to the River Angara, i.e., slightly away from the direction of the dominant winds. This geographical location of the Irkutsk suburban station may have resulted in the significant difference in HCB concentrations in air at the two stations. However, the ratio between HCB concentrations at urban and suburban stations was the smallest among all compounds studied (ratio of medians at the urban and suburban stations was 1.3–1.4 times for HCB vs. 1.7–56 times for other POPs, with the exception of diCB).

3.3. Seasonal Variation in Air

As a result of the current study, we observed a pronounced seasonality of HCH, DDT, and PCB levels and their composition in air at both Irkutsk air monitoring stations.

According to the Fourier spectral analysis, the periodicity of HCH and DDT changes in the air was about six observation periods, corresponding to a 1 year cycle (Figure S2). The seasonality in PCB change with a period of 1 year was typical of the urban station, as opposed to the suburban one. This likely resulted from the presence of a common PCB source affected by seasonal factors in the urban area, as well as the presence of an additional factor influencing the PCB level in air at the suburban station (Figure S2). One such factor is seasonal residence, accompanied by additional combustion sources and tillage in summer in the suburban area. The seasonality of HCB changes is also weakly expressed due to high volatility of HCB relative to other POPs [104].

The summer PCB, HCH, and DDT levels were typically higher than winter POP levels in air at both Irkutsk monitoring stations (Figure 4 and Figures S3–S4). The disturbances in the seasonal distribution of PCBs and DDTs seen in 2011–2012 were likely a result of the residual influence of elevated levels of these compounds in the late 2000s, as also observed in air of the Northern Hovsgol area [62]. The same seasonal distribution, with summer elevation of POP levels, has been found for HCHs in Japan [105] and the Arctic stations [27,39], as well as for PCB, DDT, and HCH in the Tibetan Plateau [106] and Italy [107]. On the other hand, other studies have revealed an opposite seasonal distribution (HCB in the Arctic [39]; PCB in rural areas of India [16]; PCB and OCP in China [65]) or absence of seasonality in POP distribution at all (PCBs, HCB, and DDTs in Czech Republic [108]; PCB in Australia [95]). Such different seasonal distributions of POP levels in air may be the result of intra-annual air temperature variability in the areas under study, as well as the intra-annual variability of POP emissions from various sources.

It should also be noted that there were seasonal/temporal changes in the ratios of individual POP compounds. The values of the α-HCH/γ-HCH ratio represent the seasonal effect, being 2.1–6.6 and 0.03–4.2 during spring–summer–fall and increasing up to 36 and 74 during the winter in urban and suburban stations, respectively (Figure 4b). The median α/γ-HCH ratio in air at the urban station was higher than that in air at the suburban station (3.6 and 1.7, respectively; Table 1). All values of the α/γ-HCH ratio at the urban station were above 1, while the ratio was lower than 1 in 16% of suburban station samples. An α/γ-HCH ratio <1 indicates the fresh input of lindane [84,85]. The lowest α/γ-HCH ratios were observed in spring and fall of 2012–2013 and during the spring–summer–fall of 2015 at the suburban station, assuming the fresh input of γ-HCH in the atmosphere there. It was assumed that α/γ-HCH ratios above 7–8 represent the result of long-range transport or aging technical HCH [85,108,109,110]. α/γ-HCH ratios >7–8 were found in 26% of all PUF at both stations. Moreover, all were sampled in the winters of 2010–2018, in agreement with the photochemical transformation of γ-HCH to α-HCH in the atmosphere, atmospheric transport of HCHs [110], and the absence of plant cultivation in winter as a potential source of γ-HCH.

The ratio of p,p′-DDT/p,p′-DDE is generally used as indicator of the age of DDT in the environment [111,112]. p,p′-DDT/p,p′-DDE < 1 was observed in 69% and 16% of PUF samples at urban and suburban stations, respectively (Figure S4). In addition, p,p′-DDT/p,p′-DDE decreased gradually during 2010–2018, indicating aging DDT in the environment of urban area. On the other hand, there was a long-term input of p,p′-DDT into the atmosphere at the suburban station. Taking into account the widespread practice of DDT application against insect vectors of infectious diseases in the past [88,113], the epidemic zone of tick-borne encephalitis [114], and presence of summer recreation areas for children nearby, it may be suggested that the application of DDT in the past was a likely source in the suburban station area that resulted in long-term evaporation of DDT from soil into air. At the same time, we cannot exclude the unofficial application of DDT by local residents or the transport of dung and humus potentially contaminated with DDT from other agricultural areas as an additional source of DDT in the suburban station area. The seasonal variation of p,p′-DDT/p,p′-DDE was also determined (Figure S4b). In the current study, the ratio of DDT/DDE in air at suburban station sharply increased after the snowmelt.

At both stations, the cluster analysis of ln-transformed PCB levels divided the sampling periods into two groups (Figure 5). Seasonal division of PUF was more expressed at the urban station, as compared to the suburban one. The first group at urban station includes almost all PUF samples in winter, when the mean air temperature during the sampling period was below zero (highlighted in blue in Figure 5). The second group comprised PUF samples in spring (with mean air temperature ranging between 0 °C and 10 °C; highlighted in green in Figure 5), summer (t > 10 °C, highlighted in red in Figure 5), and fall (0 °C < t < 10 °C; highlighted in yellow in Figure 5). At the suburban station, winter PUF was included in both groups, but the first group consisted predominantly of winter PUF. At both the urban and the suburban stations, the first group was characterized by lower PCB levels (Figure S5a,c), as well as a lower proportion of hexaCB (5.8 and 4.8% at urban and suburban stations, respectively) and heptaCB (0.6 and 0.7% at urban and suburban stations, respectively; Figure S5e), than those in the second group (hexaCB: 11 and 8.6–19% at urban and suburban stations, respectively; heptaCB: 1.8 and 0.7–2.9% at urban and suburban stations, respectively; Figure S5b,d,f).

In addition, in groups from the first to 2a and 2b at the suburban station, we observed decreasing proportions of diCB (6.5, 0.7, and 0.1, respectively), triCB (15, 11, and 3.5, respectively), and tetraCB (39, 36, and 26.5, respectively). There was no such perceptible variation between the proportions of diCB, triCB, and tetraCB in total PCBs in the first and second groups at urban station. The differences in seasonal distribution of lower chlorinated PCBs between urban and suburban stations may have been the result of distinct PCB sources at urban and suburban stations. The homological composition of PCB in PUF collected in warm periods (group 2), with the maximum in subgroup 2b at the suburban station, became more similar to the homological composition in the technical mixture of PCB (Sovol, analogous Arochlor 1254), but was not close to the less chlorinated PCB mixture—trichlorodiphenyl (TCD)—used in the former USSR [115] (Figure S5g), confirming the conclusion made in a previous study [48] regarding Sovol as a primary PCB source in the region [103]. The difference from the composition of Sovol is higher proportions of triCB and tetraCB and a lower proportion of hexaCB in the total PCB concentrations in air, which can be explained by the higher volatility of less chlorinated congeners, compared to more chlorinated ones [104].

3.4. Temperature, Precipitation, Calm, and Wind Direction Effect on PCB and OCP Levels in Air

A greater difference between the maximum and minimum absolute air temperatures and/or between the average temperatures of the warmest and coldest months observed in the study area [40,41] leads to a more pronounced effect of meteorological factors on the distribution of POP air concentrations. Thus, the seasonal variations of most POPs can be attributed to considerable intra-annual variations of air temperature due to the sharply continental climate in Irkutsk Region. The results for the relationship between ln-transformed POP levels in air at urban and suburban stations and some meteorological factors (absolute values of air temperature, ln-transformed values of precipitation, and proportions of calms and predominant wind directions) are presented in Figure 6 and Tables S7–S10. The data for the average daily air temperature and precipitation at the Irkutsk meteorological observatory during the period of study were taken from database of the Federal Service for Hydrometeorology and Environmental Monitoring (Roshydromet) [116]. On the basis of long-term observations of δ¹⁸O and δD in precipitation on Irkutsk and Lake Baikal stations, Kostrova et al. [43] found that moisture transport from the west predominates throughout the year. Taking into account the local geographical features of Irkutsk, located in the valley of the Angara River, resulting in the predominance of northwest winds [44], as well as the location of the main source of POP emissions in Usol’e-Sibirskoe lying northwest from Irkutsk [48,103], we chose the frequency of observations of west-northwest (W-NW) winds for investigation of the possible influence of atmospheric transport from long-term POP sources.

Significant relationships were observed among almost all the POPs investigated, the average air temperature, and the precipitation volume (Figure 6). The variation of HCH and DDT concentrations in air was in line with temperature fluctuations at both stations. PCB levels in air at the urban station more strongly depended on temperature fluctuations than those at the suburban station, likely related to the evaporation of PCB from soil and other surfaces more polluted with PCB in urban areas [33,103].

Multiple regression analysis using temperature, precipitation volume, west-northwest (W-NW) wind, and calms in total observation for winds as independent variables indicated, for the majority of compounds analyzed, the significant factor accounting for most of the variance was temperature as the sole independent variable (some PCB congeners) or in conjunction with W-NW winds (α-HCH, p,p′-DDT, PCB-31, 28 at suburban station; PCB-180 at urban station), calms (p,p′-DDE at urban station; PCB-70/76 at suburban station), or W-NW wind + calms (γ-HCH at urban station). Precipitation was the key factor influencing PCB-52, PCB-128, and p,p′-DDT as sole independent variables, or in conjunction with the calms or temperature + calms. The results of the regression analysis suggested an effect of both the local re-evaporation of POPs and atmospheric transport of POPs, with W-NW winds affecting the air concentrations of POPs at both urban and suburban Irkutsk stations.

In total, the relationship between POP levels and meteorological factors can be characterized as follows:

−

The influence of meteorological factors on air POP levels was more expressed at the urban station, as compared with the suburban one, which can be related to higher pollution with POPs, atmospheric particles, and other pollutants in the urban area. Taking into account that the quantity of air particles in the atmosphere at the Irkutsk urban station area was higher than that in the suburban station area, due to combustion processes in the heating period and transport emissions [117,118], and as the quantity of air particles may influence the ability of precipitation scavenging of POPs from air [119], these two factors may have resulted in the deposition of POPs on air particles, followed by the scavenging of POPs from air with precipitation together with particles. In addition, despite the relatively close location of the urban and suburban stations, the use of meteorological data for Irkutsk observatory for processing data for the suburban station may have led to an uncertainty factor, resulting in disturbance of the relationship between meteorological factors and POP levels in air at the suburban station;

−

The POP levels in air depend mainly on seasonal variations of air temperature followed by the quantity of precipitation, portion of W-NW winds, and calms (Tables S7–S10), thus indicating the predominance of POP evaporation from soil and other surfaces. The dependence of POP chemical properties on temperature is the deciding factor of the fate of POPs in environmental media [120], displayed both in seasonal variations of POP levels [24,36,61,105,106] and in the long-range, regional, and local air transport of POPs [104]. The temperature effect on soil volatilization, as the main source of POP emission into air, has been shown by Llanos et al. [121];

−

POP levels in air depend on the quantity of precipitation (Figure 6, Table S8). Dien et al. [99] and Wang et al. [106] found no correlation between rainfall rate and concentration of various POPs in air or a correlation between the concentrations of heavy chlorinated homologues of PCB only and rainfall rate. However, unlike the studies of Dien et al. [99] and Wang et al. [106], snow precipitation occurs about half the year in the Irkutsk area [44]. Snow is much more effective at scavenging POPs adsorbed onto atmospheric particles than rain, due to its porosity [119], which resulted in a significant relationship between POP levels in air and the quantity of precipitation in our investigation;

−

DDTs and HCHs, as opposed to PCBs, depend much more on the seasonal variations of air temperature and quantity of precipitation, which can be explained by seasonal evaporation from the soil contaminated with OCP, constant PCB sources such as emissions from transport or power stations, or sporadic PCB sources such as natural fires [95];

−

The negative effect of calm frequency (Table S10) indicated the atmospheric transport of some POPs. The regression slope increased from less chlorinated PCB to more chlorinated PCB, suggesting relevant atmospheric transport of more chlorinated homologs from the former industrial area of Usol’ekhimprom in the town of Usol’e-Sibirskoe;

−

Amongst the POPs investigated, HCB showed the lowest dependency on the meteorological factors, which may be due to the low octanol–air partition coefficient (K_OA) and higher volatility of HCB [104].

3.5. Daily Exposure and Health Risk Assessment

The daily intakes of PCBs, DDTs, HCHs, and HCB under human exposure by inhalation amounted to 38, 21, 27, and 35 pg/kg body weight per day, respectively, in the urban area, and 17, 6, 7, and 27 pg/kg body weight per day, respectively, in the suburban area (Table S12). A similar range of values for daily intake has been previously obtained for other towns and small settlements of Irkutsk Region [33]. In Irkutsk Region, the daily intake under inhalation is generally below 1% of total daily intake from every pathway including food, water, and soil [52,103].

The indices of noncancer (THR) and cancer (TCR) effects of the PCBs and OCPs investigated are presented in Table S13.

THRs detected were well below one for every target organ and system (the central nervous, endocrine, reproductive and immune systems, liver, development, kidney, and lung), thus suggesting no adverse effects in these target organs.

TCRs from PCBs and OCPs (Table S13) were below one case of cancer among one million people, which has been accepted as a negligible risk by the US EPA [56] and the Federal Center for State Sanitary and Epidemiological Surveillance of the Ministry of Health of Russia [55]. According to [55], these values do not require any additional measures for their reduction, and they should be subject only to periodic monitoring. However, it should be mentioned that the main part of the daily intake of the compounds discussed comes from food [52]. The daily intake values and the indices of noncancer and cancer risks from inhalation exposure can serve as indicative values for potential detection of elevated risk from consumption of local food items. In addition, the contribution of POP groups in TCR changed in 2011–2017 (Figure S7). The contribution of PCBs either decreased slightly in the suburban area or remained approximately at the same level in the urban area, and the contributions of HCHs and DDTs decreased; meanwhile, the contribution of HCB to TCR increased, thus indicating the increasing importance of HCB among POPs for environmental pollution and human health in the future.

4. Conclusions

The current study enabled the first assessment of long-term and seasonal variations in the distribution of PCBs and OCPs using a passive air sampling method in atmospheric air at two stations in Irkutsk Region, in the vicinity of the South Lake Baikal, Eastern Siberia, Russia, as well as the influence of meteorological factors on these fluctuations. POP concentrations found in the air at urban and suburban Irkutsk stations were well below the maximum permissible levels accepted in Russia. In this study, the POP concentrations in urban air were generally higher and the levels of PCBs and HCHs in suburban station air were in line with the POP contents obtained within the GAPS program in the 2000s–2010s.

Long-term observation of the studied POPs allowed us to conclude the decreasing trend of PCB and HCH levels in the 1990s–2010s, the decreasing trend of DDT levels in 2014–2017 following a short uptick of DDT values in 2008–2013, and increasing HCB levels in 2008–2017. These trends correspond to those found in investigations conducted at monitoring sites in neighboring countries and around the world.

We established the intra-annual variations of PCB, HCH, and DDT levels and their relative compositions. At the same time, the HCB fluctuations were weakly expressed. The summer PCB, HCH, and DDT levels were usually higher than the winter POP air concentrations at both Irkutsk stations.

The results of this study revealed the influence of meteorological factors, including air temperature, precipitation, portions of calms, and predominant directions of winds, on POP air levels at urban and suburban stations. The POP levels in air depend mainly on seasonal variations of air temperature, followed by the quantity of precipitation, portion of west-northwest prevailing winds, and calms, thus indicating the predominance of POP evaporation from soil and other surfaces, as well as atmospheric transport of some POPs from the former industrial area of Usol’ekhimprom in the town of Usol’e-Sibirskoe located northwest of the Irkutsk stations.

The indices of noncancer (THR) and cancer (TCR) effects of the investigated PCBs and OCPs under an inhalation scenario indicated the absence of adverse noncancer effects in target organs and a negligible cancer risk for the population in the region. It should be noted that the contribution of POP groups in TCR changed in 2011–2017, following changes in their respective levels.