Principal Component Analysis With Multiple Linear Regression Research Articles

Major ions and potentially toxic elements in atmospheric precipitation during the COVID-19 lockdown in Moscow megacity

For the first time, the change in the physicochemical properties, ions composition, concentrations, and ratio of soluble and insoluble potentially toxic elements (PTEs), as well as sources contribution to the content of PTEs using principal component analysis with multiple linear regression (PCA-MLR) were determined in the Moscow precipitation before, during and after the lockdown (January–July 2020). The impact of the lockdown on the precipitation composition was ambivalent. The decrease in the precipitation pollution with PTEs (by 10–99% for soluble PTEs and 9–61% for insoluble ones) was caused by the purification of the atmosphere from aerosols during their long-term washing out by precipitation and a decrease in anthropogenic emissions. Air advection to Moscow from the suburbs, where wood, coal, household and agricultural wastes were burned, on the contrary, contributed to the growth of precipitation pollution with insoluble P, Pb, Cd, soluble P, Ag, Pb, Sb, As, Cd, as well as [Cl−] and [K+]. After the lockdown, the restoration of the level of precipitation pollution by PTEs occurred gradually due to the time lag between the increase in atmospheric pollution and the washing out of aerosols by precipitation, as well as dilution by exceptional rainfall amount. Faster restoration rates of insoluble PTEs compared to soluble ones are associated with the rapid increase in the activity of the urban source (road and construction dust, industrial and traffic emissions). The lifting lockdown restrictions reduced the contribution of industrial sources to the content of soluble PTEs forms (from 38–66% to 6%) due to an increase in the contribution of road dust and non-exhaust emissions, soil particles resuspension, waste and fuel combustion, and vehicle emissions. A decrease in the contribution of vehicle emissions, road dust resuspension, and construction dust to the content of insoluble PTEs from winter to summer due to the lockdown influence and a large amount of precipitation in late spring and early summer was confirmed. The results highlighted the need for further studies of the chemical composition and properties of precipitation in the city in similar periods for the correct separation of the influence of social, economic, emission, meteorological, and physicochemical factors on the content and the ratio of PTEs forms.

Source apportionment and risk assessment of metal pollution in natural biofilms and surface water along the Lancang River, China

Herein, surface water and periphytic biofilm samples were collected from 16 sites along the Lancang River, China, to assess the spatial distribution, enrichment factor (EF), potential ecological risk index (RI), and associated source-oriented health risks of heavy metal elements (As, Cd, Co, Cr, Cu, Ni, Pb, V, and Zn) in the samples. Results showed that the levels of heavy metals were significantly lower in the surface water samples than in the biofilm samples (one-way analysis of variance, p < 0.001). Moreover, 37.50 % of the biofilm samples were significantly polluted by these heavy metals with a mean EF of >5. As and V were the highest polluting metals, and the enrichment of Co and Ni were attributed to natural sources. RI assessment results showed a consistent ecological risk of As. Based on principal component analysis with multiple linear regression (PCA-MLR) and positive matrix factorization (PMF) models, the presence of heavy metal ions in the biofilm samples was largely attributed to industrial activities (PCA–MLR: 68.89 %; PMF: 76.39 %), followed by a mixed source of natural and agricultural activities (PCA–MLR: 18.12 %; PMF: 13.56 %), and traffic emissions (PCA–MLR: 12.99 %; PMF: 10.05 %). Both carcinogenic and noncarcinogenic risks for adults were negligible even though adults tended to be exposed to greater risk through ingestion. Source-specific risk evaluations indicated that industrial pollution was the most important source of health risks. Our findings highlight the potential threat of biofilms to the ecological and human health.

Assessing pollution characteristics and human health risk of exposure to PM2.5-bound trace metals in a suburban area in Hanoi, Vietnam

Fine particles (PM2.5) in the atmosphere, especially PM2.5 bounded with trace metals, pose potentially adverse human health risks. This study aimed to characterize the trace elements in PM2.5 in a suburban area of Hanoi from November 2019 to December 2020. The study area represented a mixture of industrial, agricultural, and residential areas. The results revealed that PM2.5 mass was highest in winter due to the stable meteorological conditions, which disfavor the particulate matter dispersion in the atmosphere. Fe, Mg, Zn, K, and Al were the most abundant elements in PM2.5, accounting for 29.6, 19.0, 16.3, 15.8, and 11.3% of the total concentration of metals, respectively. PM2.5-bound trace metals were highest in winter, followed by autumn and spring. Principal component analysis with multiple linear regression (PCA/MLR) illustrated that crustal dust, pesticide, and industrial emissions contributed to 73.6% of the total contribution sources, while vehicle exhaust mixed with coal combustion accounted for 64.1% of the total contribution sources. The health risk assessments suggested that As (HQ = 4.7) and Cd (HQ = 3.1) had non-carcinogenic risks for adults. The cumulative carcinogenic risk of elements was within the acceptable range for both children and adults. Notably, the source of As should be paid attention to as the As high concentration exceeding the safe level for non-carcinogenic risks in the study area.

Persistent organic pollutants (POPs) in deep-sea sediments of the tropical western Pacific Ocean

Persistent organic pollutants (POPs) are toxic compounds that can persist for extended periods in the environment. The marine environment is considered an important sink for POPs. However, information regarding POPs in deep-sea environments remains limited. In this study, surface sediments from depths below 2,000 m were collected in the western Pacific Ocean to analyze polycyclic aromatic hydrocarbons (PAHs), organic pesticides, and polychlorinated biphenyls (PCBs). The concentrations of PAHs were highest (5.2–24.6 ng g−1 dw). Hexachlorocyclohexanes (HCHs) were the predominant organic pesticide (30–1,730 pg g−1 dw). Dicofol, chlorpyrifos, and malathion were detected only at a few sites. PCBs were not detected in the study area. A principal component analysis with multiple linear regression (PCA-MLR) indicated that PAHs in sediments mainly originated from biomass and coal combustion (∼62%) and petrogenic (∼38%) sources. This study revealed the distribution and potential sources of POPs in sediments of a deep-sea region in the western Pacific Ocean. Further studies of the transformations, sedimentation, and biological interactions of POPs are needed to better understand the fates of POPs in the marine environment and the ecological risks they pose.

Typical antibiotics in the receiving rivers of direct-discharge sources of sewage across Shanghai: occurrence and source analysis.

In Shanghai, the antibiotics in the receiving rivers of direct-discharge sources of sewage (aquaculture farms, cattle farms and wastewater treatment plants) were investigated. Water and sediment samples from the receiving rivers of these sources were collected, and were screened for 19 typical antibiotics. The concentration of the antibiotics in the water and sediment ranged from not detected (ND) to 530.05 ng L−1 and ND to 1039.53 ng g−1, respectively, and sulfonamides and fluoroquinolones were identified as the main antibiotics in the water and sediment, respectively. According to principal component analysis with multiple linear regression (PCA-MLR), source contributions were estimated: wastewater treatment plants (66.8%) > aquaculture farms and cattle farms (21.2%), indicating that the contribution of human antibiotics was higher than veterinary antibiotics. Based on the risk quotients, ciprofloxacin was identified as the main antibiotic that causes medium risk in the aquatic ecosystem. This work systematically reflected the profile and source apportionment of antibiotics in Shanghai, which is helpful for antibiotic contamination control and environmental management.

Vertical distribution and affecting factors of Escherichia coli over a 0–400 cm soil profile irrigated with sewage effluents in northern China

Quantification and evaluation of the spatial distribution and the primary factors that affect Escherichia coli (E. coli) distribution in soils is important to assess soil pollution and potential contamination of groundwater. However, little information is available on distribution of E. coli in deep soil layers. To analyze the spatial distribution and factors affecting E. coli over a 0–400 cm soil profile, soil samples were collected from two land use type in the sewage irrigation fields. The primary factors dominating the spatial distribution of E. coli were quantified by the model of principal component analysis with multiple linear regression (PCA-MLR). The results indicated that the number of E. coli under cropland decreased greatly with soil depth. The average number of E. coli over the 0–400 cm profile under forestland was 49 × 104 colony-forming unit/g (cfu/g), which was significantly higher than that under cropland (20 × 104 cfu/g). For forestland and cropland, the average number of E. coli at depths of 300–400 cm decreased by 85% and 88%, respectively, compared to that at depths of 0–100 cm. The presence of E. coli at the depths of 300–400 cm was at high level (forestland: 3 × 104 cfu/g; cropland: 2 × 104 cfu/g) for the potential risks of shallow groundwater. The PCA-MLR model estimated that the factors of soil organism, soil salt and land type use contributed 28%, 29% and 43%, respectively, to the distribution of E. coli. According to the Monte Carlo simulation, the average number of E. coli over the 0–400 cm profile was 46 ± 17 × 104 cfu/g in the sewage irrigated area, and the interval distribution with a probability of 95% varied between 14 × 104 cfu/g and 78 × 104 cfu/g. The findings of this study are useful for understanding negative effects of sewage irrigation on pathogens in deep soil and are critical to assess the potential risks of groundwater pollution.

Atmospheric particle-bound polycyclic aromatic hydrocarbons, n-alkanes, hopanes, steranes and trace metals: PM2.5 source identification, individual and cumulative multi-pathway lifetime cancer risk assessment in the urban environment

The occurrence of atmospheric fine particles (PM2.5)-associated polycyclic aromatic hydrocarbons (PAHs), trace metals and organic molecular markers was investigated by conducting an intensive sampling campaign at the Eastern Mediterranean urban area of Nicosia (Cyprus). Sixty-two 24-hr PM2.5 samples were collected and analyzed for fifty parent and alkylated PAHs, twenty-five long chain n-alkanes, seventeen hopanes and twelve steranes used for source apportionment. The same number and kind of samples were analyzed to determine twenty-eight trace metals. Emphasis was given to investigate the air levels of the scarcely monitored although highly carcinogenic PAHs such as dibenzopyrenes, dibenzoanthracenes, 7H-benzo[c]fluorene and 5-methyl-chrysene, not included in the USEPA's sixteen PAH priority list (USEPA-16). UNMIX receptor model was applied to apportion the sources of atmospheric emissions of the determined organic compounds and trace metals and evaluate their daily contributions to the corresponding PM2.5 associated concentrations. For comparison purposes, principal component analysis with multiple linear regression (PCA/MLR) was also applied and its results are reported. The UNMIX receptor model, compared to PCA/MLR, offered a more precise source profile and more reliable daily mass source distributions by eliminating negative contributions. The individual and cumulative multi-pathway lifetime cancer risk (posed via inhalation, ingestion and dermal contact) by exposure to PM2.5-associated USEPA-16 listed and non-listed PAHs and selected airborne trace metals (As, Cd, Co, Ni, and Pb) were assessed. To estimate the contribution of each emission source to the total cancer risk, multiple linear regression analysis was performed, using as independent variables the daily source mass contributions and as dependent variables the respective cancer risk units. The estimated total cumulative cancer risk comprising all toxic PAHs, besides those included in the priority list, and metals was higher than the USEPA's threshold by a factor of eight, denoting a potential risk for long-term exposure of a population in the urban environment.

Occurrence, distribution and health risk assessment of organophosphate esters in outdoor dust in Nanjing, China: Urban vs. rural areas

With increasing use of organophosphate esters (OPEs) largely due to the phasing out of various brominated flame retardants, much more attention has been paid to their occurrence, distribution and potential health risks. In this study, we investigated the occurrence and distribution characteristics associated to their potential health risks of selected 13 OPEs in outdoor dust with a comparison between urban and rural areas in Nanjing, China as well as seasonal variations. Ten out of 13 OPEs showed higher concentrations in urban dust than those in rural dust (p < 0.05). Six OPEs congeners exhibited significantly different concentrations with seasonal variations (p < 0.01) in rural dust. Halogenated OPEs were the dominant group in both urban (median: 56.8%) and rural (median: 45.9%) dust, and tris(2-chloroisopropyl) phosphate (TCPP) was found to be the most abundant OPE in both urban (median: 48.7%) and rural (median:26.4%) dust. Principal component analysis with multiple linear regression (PCA-MLR) and spearman correlations showed the different sources of OPEs in urban and rural dust. The non-carcinogenic (Hazard Index, HI < 1.62 × 10−5) and carcinogenic risks (CR < 2.28 × 10−9) of ΣOPEs were much lower than the theoretical threshold of risk, revealing a negligible risk to local residents from the exposure of OPEs in outdoor dust.

Vehicular contribution of PAHs in size dependent road dust: A source apportionment by PCA-MLR, PMF, and Unmix receptor models

This study focuses on the source apportionments of polycyclic aromatic hydrocarbons (PAHs) in road dust (RD) with four size fractions through three receptor models of principal component analysis with multiple linear regression (PCA-MLR), positive matrix factorization (PMF) and Unmix. The concentrations of total PAHs range from 0.45 to 2.03μgg−1. Results show that the concentrations of PAHs increased with a decreasing size fraction. Similar potential sources to PAHs in RD were extracted by three models with a little difference in numbers and percent load contributions of each identified sources. The overall proportion of the identified sources were ranked as vehicular emission>coke oven>surface pavement>others in each size fractions. In terms of risk assessment, the mean values of incremental lifetime cancer risk (ILCR) of the total cancer risk of PAHs in RD were lower than the baseline value of an acceptable risk. However, PAHs in smaller size fraction prone to have a higher adverse effect on children via ingestion. Furthermore, the ecological risk assessment of hazard quotients and mean hazard quotients indicated that PAHs in RD had a 9% probability of being toxic to the benthic organisms and aquatic environment.

Occurrence of typical antibiotics and source analysis based on PCA-MLR model in the East Dongting Lake, China

The antibiotics residues in freshwater lakes are being highlighted around the world because of high potential threat to environment and human health. Understanding the current state of antibiotics and potential sources in lakes are important. The potential sources of antibiotics (Sewage treatment plants (STPs)), livestock and poultry farms and fishponds in the East Dongting was studied. Compared with other surface water bodies, the concentration of antibiotic in the East Dongting Lake was at a moderate or low level. Ten of 12 antibiotics likely originated from veterinary applications in livestock and poultry farms, especially in swine farms, and concentrations at these sources (ND-1240.41 ng L−1) were 1–3 orders of magnitude higher than in the effluent of local sewage treatment plants and fishponds. Based on a principal component analysis with multiple linear regression (PCA-MLR) model, we estimated source contributions of 79.95% for livestock and poultry farms, 0.27% for STPs, and 19.79% for aquaculture source and livestock and poultry farms. Overall, the predominance of sulfonamides and livestock and poultry farms in the East Dongting Lake has been identified, which can provide important information for regulating their veterinary use and environmental management.

Source contributions and mass loadings for chemicals of emerging concern: Chemometric application of pharmaco-signature in different aquatic systems

To characterize the source contributions of chemicals of emerging concern (CECs) from different aquatic environments of Taiwan, we collected water samples from different aquatic systems, which were screened for 30 pharmaceuticals and illicit drugs. The total estimated mass loadings of CECs were 23.1 g/d in southern aquatic systems and 133 g/d in central aquatic systems. We developed an analytical framework combining pollutant fingerprinting, hierarchical cluster analysis (HCA), and principal component analysis with multiple linear regression (PCA-MLR) to infer the pharmaco-signature and source contributions of CECs. Based on this approach, we estimate source contributions of 62.2% for domestic inputs, 16.9% for antibiotics application, and 20.9% for drug abuse/medication in southern aquatic system, compared with 47.3% domestic, 35.1% antibiotic, and 17.6% drug abuse/medication inputs to central aquatic systems. The proposed pharmaco-signature method provides initial insights into the profile and source apportionment of CECs in complex aquatic systems, which are of importance for environmental management.

Polycyclic aromatic hydrocarbons (PAHs) in indoor dusts of Guizhou, southwest of China: status, sources and potential human health risk.

Polycyclic aromatic hydrocarbons (PAHs) were analyzed for 136 indoor dust samples collected from Guizhou province, southwest of China. The ∑18PAHs concentrations ranged from 2.18 μg•g-1 to 14.20 μg•g-1 with the mean value of 6.78 μg•g-1. The highest Σ18PAHs concentration was found in dust samples from orefields, followed by city, town and village. Moreover, the mean concentration of Σ18PAHs in indoor dust was at least 10% higher than that of outdoors. The 4–6 rings PAHs, contributing more than 70% of ∑18PAHs, were the dominant species. PAHs ratios, principal component analysis with multiple linear regression (PCA-MLR) and hierarchical clustering analysis (HCA) were applied to evaluate the possible sources. Two major origins of PAHs in indoor dust were identified as vehicle emissions and coal combustion. The mean incremental lifetime cancer risk (ILCR) due to human exposure to indoor dust PAHs in city, town, village and orefield of Guizhou province, China was 6.14×10−6, 5.00×10−6, 3.08×10−6, 6.02×10−6 for children and 5.92×10−6, 4.83×10−6, 2.97×10−6, 5.81×10−6 for adults, respectively.

Source apportionment of polycyclic aromatic hydrocarbons in soils of Huanghuai Plain, China: Comparison of three receptor models

Receptor models are useful tools to identify sources of a specific pollutant and to estimate the quantitative contributions of each source based on environmental data. This paper reports on similarities and differences in results achieved when testing three receptor models for estimating the sources of polycyclic aromatic hydrocarbons (PAHs) in soils from Huanghuai Plain, China. The three tested models are Principal Component Analysis with Multiple Linear Regression (PCA-MLR), Positive Matrix Factorization (PMF) and Unmix. Overall source contributions as well as modeled ∑PAHs concentrations compared well among models. All three models apportioned three common PAH sources: wood/biomass burning, fossil fuel combustion and traffic emission, which contributed on average 27.7%, 53.0% and 19.3% by PCA-MLR, 36.9%, 27.2% and 16.3% by PMF, and 47.8%, 21.1% and 18.3% by Unmix to the total sum of PAHs (∑PAHs), respectively. Moreover, the spatial evolution of the common sources were well correlated among models (r=0.83–0.99, p<0.001). In addition, the PMF and Unmix models allowed segregating an additional source from the fossil fuel combustion source, with 19.6% and 11.8% contributions to ∑PAHs, respectively. The current findings further validate that different receptor models provide divergent source profiles, which are mainly attributed to both the model itself and/or the underlying dataset. It is therefore generally recommended to apply multiple techniques to determine the source apportionment in order to minimize individual-method weaknesses and thereby to strengthen the conclusion.