Introduction

The simultaneous occurrence of rapid population growth and environmental pollution both in urban and rural areas are common and the principal eco-health problems in developing countries as Pakistan (Kamal et al. 2014a, 2014b). The use of solid fuels (coals and biomass in the form of wood, bushes, tree leaves, cow dung, and crop residues) continues to be a major source of household energy for cooking in several underdeveloped areas of Pakistan. However, biomass fuel, when burnt in raw form, results in the inefficient combustion and produces chemicals such as particulate matter (PM), carbon monoxide, sulfur dioxide, and several carcinogenic compounds including polycyclic aromatic hydrocarbons (PAHs).

The use of biomass fuel is very common in Pakistan with 66 % of households (22 % in urban areas and 90 % in rural areas). In general, these fuels are burnt indoor, using poorly functioning stoves and in scarcely ventilated ambience. As combustion is incomplete in most of these stoves, it can also serve as a key route to transfer high levels of indoor pollutants to those who are responsible for cooking and their family members. In particular, women (who do most of the cooking), children, and professional cooks are the population mainly exposed to the harmful effects of these combustion products. According to estimates of Word Health Organization (WHO), there is a strong evidence that acute respiratory infections in children and obstructive pulmonary diseases in women are associated with indoor biomass smoke.

PAHs, primarily formed by incomplete combustion of organic matter and fossil fuels, are related with several human morbidities including mutagenesis, carcinogenesis, potential toxicity, and hemolytic properties (Kamal et al. 2014a; Chen et al. 2013). The carcinogenic properties of PAHs are of great concern for exposed urban population (Szabova et al. 2008). The human exposure to PAHs is mostly due to inhalation and ingestion, while dermal contact exposure may affect DNA and lead to cancer or mutation in humans (Ngo Viet et al. 2014). PAH deposition is facilitated by both dry and wet deposition in rural and urban environments, in particular in soil and dust (Cincinelli et al. 2004; Wild and Jones 1995; Murakami et al. 2005; Yang et al. 2014).

The aim of this study was to determine the abundance and distribution of PAHs in dust samples from selected professional cooking workplaces and residential household cooking areas, where traditional and primitive cooking practices are still used, in order to investigate the carcinogenic risk for Pakistani human exposure to dust-bound PAHs via inhalation, dermal contact, and ingestion routes.

Materials and methods

Reagents

All solvents were pesticide grade and purchased from Supelco (Bellefonte, PA, USA) and tested for contaminants before use. Standard PAH mixture EPA was purchased from Supelco (Bellefonte, PA, USA). Benzo(e)pyrene and coronene were purchased from Alltech (Deerfield, USA). Silica (100–200 mesh) and sodium sulfate (Na2SO4) were purchased from the Merck (Darmstadt, Germany). Sodium sulfate was heated for 12 h at 450 °C to remove any organic matter and kept at 120 °C until use.

Sample collection and processing

Dust samples were collected from residential household cooking areas in the Gujranwala and Sohdra villages (WRs) and professional cooking workplaces (semi-outdoor cooking places) (WCs) in the city of Rawalpindi (Fig. S1; EMS). In general, three to four adjacent cooking shops were considered one unit, and dust samples collected from all these shops were combined into one representative/composite sample. Each dust sample (15–20 g) was collected using a new set of dustpan and sterile plastic brush to avoid cross-contamination. Dust samples were wrapped in pre-rinsed aluminum foil and stored in a pre-labeled zip-lock polyethylene bag for transportation to the analytical laboratory. The samples were sieved in laboratory to remove fibers, large dust particles, and other possible debris.

Sample preparation, extraction, cleanup, and analysis

Sample preparation and instrumental analysis are described in detail in previous publications (Martellini et al. 2012; Kamal et al. 2014a). Briefly, 3 g of dust from each sample was homogenized, spiked with a mixture of deuterated standards (d4p-terphenyl, d10-fluoranthene-, d12-benzo(a)anthracene, and d12-benzo(a)pyrene) and extracted in an ultrasonic bath for 15 min (in crushed ice), using a mixture of hexane and dichloromethane (1:1 v/v). Then the extracts were vortex stirred (1 min) and centrifuged for 5 min at 2500 rpm. The supernatants were reduced approximately to 1 ml under a gentle stream of ultra pure nitrogen, and were further subjected to cleanup using silica gel column chromatography (9 g; Fisher Scientific 100–200 mesh silica gel). The column was first eluted with 25 ml of hexane and then with 50 ml solution of a hexane and dichloromethane (4:1 v/v) (Martellini et al. 2012; Kamal et al. 2015b). The resulting extracts were concentrated to 1 ml volume under gentle stream of high-purity nitrogen and transferred into a vial for storage. Prior to instrumental analyses, the extracts were spiked with an internal standard mixture containing d8-naphthalene, d10-phenanthrene, d12-chrysene, and d12-indeno(1,2,3-c,d)pyrene. The samples were injected into a Hewlett–Packard 6890 gas chromatography-mass spectrometer (GC-MS), equipped with a 5973 MSD and a HP-5MS capillary column (J&W Scientific, Folsom, CA, USA, 30 m, 0.25 mm I.D., 0.25 mm film thickness). Compound identification was based on the MSD database (National Institute of Standards and Technology (NIST), 98) and GC retaining time of authentic PAH standards. The MSD was operated in selected ion monitoring mode (SIM).

Quality assurance and quality control (QA/QC)

Average PAHs recoveries and relative standard deviations (RSDs) were measured to evaluate the method performance by multiple analyses of clean sand samples spiked with PAH standard mixture containing 18 PAHs (acenaphthene (Ace), acenaphthylene (Acy), anthracene (Ant), benzo(a)anthracene (BaA), benzo(a)pyrene (BaP), benzo(b)fluoranthene (BbF), benzo(e)pyrene (BeP), benzo(ghi)perylene (BghiP), benzo(k)fluoranthene (BkF), chrysene (Chry), coronene (Cor), dibenzo(a,h)anthracene (DBA), fluoranthene (Fla), fluorene (Fl), indeno(1,2,3-c,d)pyrene (IP), naphthalene (Naph), phenanthrene (Phe), and pyrene (Pyr). BbF and BkF were reported together as BbkF. In order to determine any potential laboratory contamination, the procedural blanks were also periodically performed and evaluated. The percentage of recovery (spike) of individual PAHs were between 84.1 and 122.4 %, while that of surrogate PAHs were 93 ± 13 % for d12-benzo(a)pyrene-, 97 ± 12 % for d10-fluoranthene, 95 ± 7 % for d12-benzo(a)anthracene, and 94 ± 11 % for d4-p-terphenyl. The urban dust standard reference material (SRM1649a) from the National Institute of Standards and Technology (NIST) was used to evaluate the PAH mean recovery efficiency, which varied from 86 (Acy) to 95.2 % (BghiP) in good agreement with the certified concentrations. The diluted standards used were between the range of 0.16 and 10 ng μL−1, and a six-point calibration curve was drawn for quantification of PAHs in the dust samples. The limits of detection individual PAHs were in the range of 20–60 pg g−1 (dry weight basis).

Incremental lifetime carcinogenic risk model and parameters

The probabilistic incremental lifetime cancer risk (ILCR) was applied in this study to assess the potential lifetime carcinogenic risk of the exposure of people to ambient dust in their cooking workplaces/kitchens areas.

The ILCR model can be used in estimating the incremental probability of an individual developing a tumor over an average 70 years of lifetime (Meiners and Yandle 1995). The ILCR was calculated by summing the individual cancer risk calculated for each route of exposure (direct ingestion, dermal contact and inhalation) using the following EPA models:

$$ \begin{array}{l}\mathrm{ILCR}\kern0.5em \left(\mathrm{Ingestion}\right)\kern0.5em =\kern0.5em \frac{{\displaystyle \sum \mathrm{T}\mathrm{E}\mathrm{Q}\kern0.5em \times \kern0.5em \in \left\{{\mathrm{CSF}}_{\left(\mathrm{ingestion}\right)}\times {\left(\mathrm{B}\mathrm{W}/70\right)}^{1/3}\right\}\times \mathrm{E}\mathrm{D}\kern0.5em \times \kern0.5em \mathrm{E}\mathrm{F}\kern0.5em \times \kern0.5em Ing\mathrm{R}}}{\mathrm{BW}\kern0.5em \times \kern0.5em \mathrm{A}\mathrm{T}\kern0.5em \times \kern0.5em \mathrm{C}\mathrm{F}}\hfill \\ {}\mathrm{ILCR}\kern0.5em \left(\mathrm{Inhalation}\right)\kern0.5em =\kern0.5em \frac{{\displaystyle \sum \mathrm{T}\mathrm{E}\mathrm{Q}\kern0.5em \times \kern0.5em \in \left\{{\mathrm{CSF}}_{\left(\mathrm{inhalation}\right)}\times {\left(\mathrm{B}\mathrm{W}/70\right)}^{1/3}\right\}\times \mathrm{E}\mathrm{D}\kern0.5em \times \kern0.5em \mathrm{E}\mathrm{F}\kern0.5em \times \kern0.5em Inh\mathrm{R}}}{\mathrm{BW}\kern0.5em \times \kern0.5em \mathrm{A}\mathrm{T}\kern0.5em \times \kern0.5em \mathrm{P}\mathrm{E}\mathrm{F}}\hfill \\ {}\mathrm{ILCR}\kern0.5em \left(\mathrm{Dermal}\kern0.5em \mathrm{contact}\right)\kern0.5em =\kern0.5em \frac{{\displaystyle \sum \mathrm{T}\mathrm{E}\mathrm{Q}\kern0.5em \times \kern0.5em \in \left\{{\mathrm{CSF}}_{\left(\mathrm{dermal}\kern0.5em \mathrm{contact}\right)}\times {\left(\mathrm{B}\mathrm{W}/70\right)}^{1/3}\right\}\times \mathrm{ABS}\kern0.5em \times \kern0.5em \mathrm{A}\mathrm{F}\kern0.5em \times \kern0.5em \mathrm{S}\mathrm{A}\times \mathrm{E}\mathrm{D}\times \mathrm{E}\mathrm{F}}}{\mathrm{BW}\kern0.5em \times \kern0.5em \mathrm{A}\mathrm{T}\kern0.5em \times \kern0.5em \mathrm{C}\mathrm{F}}\hfill \end{array} $$

The details of values and units of parameters used in these formulae and the terminology have been explained in Table S1 (see ESM1), which were based on the risk assessment guidance of United States Environmental Protection Agency (U.S. EPA) and related publications.

Source contribution using multiple linear regressions

The percentage contribution of individual sources was also assessed using principal component analysis (PCA) following multiple linear regression (MLR) as described by Larsen and Baker (2003). The multiple linear regression was performed on statistical package for social sciences (SPSS), using step-wise method of variable entering, which allows independent variable to enter the regression analysis, only if can significantly increase the correlation. To perform MLR (based on basic Eq. (1)), PCA factor scores were taken as independent variables X i, while the sum total of PAHs (∑PAHs) was taken as dependent variable (Y). The dependent variable (i.e., PAHs) was first normally standardized using Eq. (2) and the influence of dependent variable on the independent variables was compared using regression coefficients. In the equation, X represent (any) variable, and x is the mean of X., σ x is the standard deviation of variable X and SND stands for standard normal deviation of X, which represents the distance in the units of standard deviations.

$$ Y=\kern0.5em {\displaystyle \sum \mathrm{m}i\kern0.5em {X}_{\mathrm{i}}\kern0.5em +b} $$
(1)
$$ \mathrm{S}\mathrm{N}\mathrm{D}(X)=\left(X-{M}_x\right)/\kern0.5em {\sigma}_x $$
(2)

Application of Eq. (3), do not change the X i, because the z (Eq. (4)) represents the standardized normal deviate of ∑PAHs, with the factor score having a mean of 0 and standard deviation of 1.

$$ z={\displaystyle \sum \kern0.5em \mathrm{Bi}\kern0.5em {X}_i} $$
(3)
$$ {R}^2\kern0.5em =\kern0.5em \in {\displaystyle \sum {\mathrm{Bi}}^2} $$
(4)
$$ \mathrm{Contribution}\kern0.1em \left(\%\right)=100\times \left(\mathrm{Bi}/{\displaystyle \sum \mathrm{Bi}}\right) $$
(5)

R 2 is the squared multiple correlation and Bi is partial correlation coefficient. The average contribution of the ith source is calculated using the Eq. (5).

Statistical analysis

All the concentrations of individual and total PAHs detected in dust samples and diagnostic ratios calculated for source identification have been presented in mean ± standard deviation, median, minimum, and maximum values; all the PAH results were presented on the basis of dry weight (d.w.). Normality of data was tested with the Kolmogorov-Smirnov (K–S) normality test. Principal component analysis (PCA) was also used for source identification using varimax rotation and extracting principal components having eigenvalues >1. Differences between sites were assessed using the Mann–Whitney’s U test. The concentration of B(a)P equivalent (BaP.Eq) were determined using the TEF provided by Nisbet and LaGoy (1992); U.S. EPA (1989; 2005; 2009), and Malcom and Dobson (1994). All statistical analyses were performed using SPSS software (version 20) for Windows.

Results and discussion

Profile and abundance of PAHs in the exposure sites (WC and WR)

The average concentrations of individual and total PAHs measured in surface dust samples together with the comparative analyses between sampling sites have been reported in Table 1. Generally, the concentrations of individual congeners of PAHs in surface dust samples of WC sites were higher than those measured in WR sites. B(a)P, a very high carcinogenic compound, was present in the dust samples from WC sites in the highest mean concentration (630 ng g−1 d.w.) followed by Chry (617 ng g−1 d.w.) > IP (564 ng g−1 d.w.) > BghiP (525 ng g−1 d.w.) > BaA (511 ng g−1 d.w.) = Phe (511 ng g−1 d.w.) > BbkF (498 ng g−1 d.w.) > BeP (360 ng g−1 d.w.) > Ant (277 ng g−1 d.w.) > Naph (196 ng g−1d.w.) > Cor (164 ng g−1 d.w.) > Acy (144 ng g−1 d.w.) > DBA (58 ng g−1 d.w.). Significant differences in the concentrations of BaA, Fla, BeP, Cor, and IP were observed (p < 0.05). The BaP mean concentration in WC workplaces was almost eight times higher than the mean value found in WR exposure sites. In fact, it should be taken into account that BaP is known to be a tracer of high-temperature cooking and/or heating combustion (Yang 2003). Moreover, the average concentrations of ∑PAHs, sum of combustion origin PAHs (∑COMB) and total sum of 7-carcinogenic PAHs (∑7-carcinogens) ranged from 1108 to 36710 ng g−1 d.w., from 388 to 20394 ng g−1 d.w., and from 823 to 30265 ng g−1 d.w., respectively, and these values were 3.5, 4.3, and 4.1 times higher in WC-dust samples than in WR workplaces, respectively. In addition, the total sum of high molecular weight PAHs, ranging between 852 and 30455 ng g−1 d.w., was significantly higher (almost 5.5 times higher, p < 0.01) in WC workplaces than in dust samples from WR exposure sites (Fig. 1).

Table 1 PAHs profile in dust samples from WC and WR sites and summary of diagnostic ratios used for source apportionment
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Fig. 1
figure 1

PAHs profile based on low, middle and high molecular weight (MW) distribution in residential household (WR) and professional (WC) workplace-dust samples

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The PAH concentrations showed differences between the two workplaces in term of levels and potential cancer risk associated with exposure to dust-bound PAHs. In particular, the WC workplaces represent unique exposure sites in some developing Asian countries such as India, Bangladesh, and Pakistan. In fact, the primitive technologies of cooking large amount of food (especially rice dishes) utilizing wood and coal biomass fuel makes this type of employment (also a family business) one of the most hazardous occupations in the Asian countries. The analytical results, which showed the  high concentration of carcinogenic PAHs (in particular BaP), evidenced a high probability for subjects exposed in WC-exposure sites  to develop cancer and/or respiratory diseases during routine exposure. In the case of residential cooking practices, the results showed slightly lower concentrations of carcinogenic PAHs. The difference in the PAH profile in the two exposure sites may be a reflection of choice of fuel selection by these two groups.

The diagnostic ratios of PAH isomeric compounds can be used for qualitative investigation of the source contribution (Kamal et al. 2015b). The specific ratios applied in this study to identify the sources are reported in Fig. 2.

Fig. 2
figure 2

Cross plots of diagnostic ratios for source apportionment of PAHs in WR and WC exposure sites

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The sum of the concentrations of the PAHs originating from the process of combustion (∑COMB) (Fl, Pyr, BaA, BbkF, BaP, BeP, IP, and BghiP) divided by the total concentration of the PAHs (∑PAHs) has often been used as a characteristic diagnostic parameter for PAHs produced by stationary combustion sources. The values of 0.73 ± 0.09 and 0.63 ± 0.12 for WCs and WRs, respectively, denoted that a considerable portion of PAHs mass could have originated from the combustion emission of the mobile sources.

The mean values of the ratio Fla/(Pyr + Fla) were 0.53 ± 0.2 and 0.52 ± 0.02 for WC and WR dust samples, respectively, indicating the contribute of coal wood combustion (De La Torre-Roche et al. 2009).

The average values of IP/(IP + BghiP) ratios obtained in this work were 0.52 ± 0.03 for WCs and 0.42 ± 0.09 for WRs. Values previously documented of 0.18 for gasoline emissions (Kavouras et al. 1999; Pio et al. 2001, Alves et al. 2001), 0.37–0.7 for diesel emissions (Kavouras et al. 1999, 2001; Pio et al. 2001; Cereceda-Balic et al. 2002), 0.56 for coal powder (Pio et al. 2001), and 0.62 for wood combustion emissions (Gogou et al. 1996) denote the importance of diesel and coal combustion emissions in the study sites. A petrogenic source was also suggested for both sites from the Ant/(Phe + Ant) >0.1 ratios (Pies et al. 2008). The BaA/(BaA + Chry) ratio is generally used to evaluate the contribution of vehicular emissions. The mean value of this ratio in both scenarios indicated the importance of gasoline and diesel engine emissions to the atmosphere.

Moreover, ∑4,5,6-rings PAHs/∑PAHs ratios >0.5 also suggested coal and soft wood combustion (Biache et al. 2014) origins. However the BaP/BghiP ratios showed different results for WCs and WRs, with a more evident traffic signature in the former and a probable mix signature of gasoline and coal combustion processes in the later (Hanedar et al. 2013; Han et al. 2009; Allen et al. 2008), as expected taking into account that most of the WC exposure sites are mainly located on the road, while WR exposure sites are located in residential and enclosed areas.

Source apportionment using PCA-MLR

Considering the suitability of PAH data for principal component analysis (PCA) and multiple linear regressions (MLR) analysis of surface dust samples of WC and WR exposur sites, it was employed to unveil independent source tracers within each group separately (Field 2009). Based on the PCA-MLR, two factors and three factors were extracted for the surface dust data from the WC and WR exposure sites, respectively.

For WC dust (Fig. 2b), factor 1 (PC-I) explained approximately 83.75 % of total variance with high loading of all investigated PAHs, in particular B(a)P, except the Ace. These compounds could be attributed to the mixture of combustion source with high temperature, such as fossil fuel combustion (coal or gasoline combustion). The DBA is often known as indication of large scale combustion of coal (Fang et al. 2004). Factor 2 (PC-II), representing 8.82 % of the total variance, is characterized by Ace which is representative of wood combustion source. According the results of MLR, wood and coal contributed to the ∼40 and ∼60 % of total PAHs, respectively, in WC-exposures sites (Fig. 2).

For WR dust samples (Fig. 3a), three factors were extracted. Factor 1(PC-I), accounted for 37.71 % of total variance with high loading of 5- to 6-rings PAHs (BaP, BeP, Fla, Ant, Pyr, BaA, Chry, Phe), which could have originated from fossil fuel combustion, coal combustion, or gasoline vehicle emission. Factor 2 (PC-II), which explains 24 % of the total variance, displayed a high abundance of Acy, Ace, Fl, and Naph, which could be associated with straw combustion (Zhang et al. 2008) or wood burning (Fang et al. 2004). Thus, factor 2 could be considered as a biomass combustion source. Factor 3 (i.e., PC-III, 16.50 % of total variance) is characterized by IP, DBA, and BghiP, indicating a possible source of coal combustion (Harrison et al. 1996; Simcik et al. 1999; Mastral et al. 1996). In general, high molecular weight PAHs may arise from the pyrogenic emission sources (Bouloubassi et al. 2012; Zakaria et al. 2002).

Fig. 3
figure 3

PCA-MLR analysis of dust-bound PAHs from WR (a) and WC (b) exposure sites

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The MLR further revealed that overall ∼14 % PAHs were contributed by coal, and 28 % by coal/petrogenic mixed sources and large proportion (58 %) PAHs in WR exposure sites were contributed by wood and coal mixed sources (Figs. 3 and 4). The prevalence of ∑COMB-PAHs was also confirmed from Fig. 4, which indicated that in both sites (>70–80 %), PAHs were originated from the combustion of biomass fuels.

Fig. 4
figure 4

Association between the ratios of ∑LMW-PAHS, ∑COMB-PAHs, and PAHs and ∑COMB-PAHs in the WR and WC exposure sites

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Health risk associated with exposure to dust-bound PAHs

The incremental lifetime cancer risk (ILCR) model was used as a tool to evaluate human health risk from the exposure to dust particle-bound PAHs. In particular, there are few studies regarding the characterization of PAHs in soil/dust samples from different occupational or residential settings in Pakistan.

Probabilistic risk assessment for personal exposure to carcinogenic PAHs via dermal contact, ingestion, and inhalation pathways showed that an ILCR between 10−6 and 10−4 indicates potential risk, whereas ILCR greater than 10−4 suggests high potential health risk. The acceptable level is equal or lower than 10−6 (see Table S1, in ESM1).

Our estimated values, which are reported in Table 2, are higher than our previously reported ILCR values for exposure of brick kiln workers to dust-bound PAHs (Kamal et al. 2014).

Table 2 Incremental lifetime cancers from individual and combined dermal, inhalation, and ingestion routes of exposure, calculated for adults and children
Full size table

The ILCR calculations are based on the model parameters specified for outdoor and indoor working classes exposed to dust-bound contaminant according to U.S. EPA (Table 1). Both adults and children (child labor) could be exposed to dust-bound PAHs in WC cooking sites, and similarly in WR residential households, as a routine exposure scenario. Thus, the ILCR values were calculated for both groups to compare the risk to both children and adult subjects. Children in particular, represents a sub-group which is the most vulnerable to the hazards associated with the exposure to pollutants (Martí-Cid et al. 2008). Considering the ambience of these cooking places, both WC and WR workplaces can be categorized into semi-outdoor exposure sites, since no single description of workplace exists in all place, rather the workplaces are designed according to the economical conditions and special variability. However, regardless of the economical differences, the workers are highly exposed to the combustion emission of biomass fuel.

The results of ILCR were almost similar for children and adults; however, the risk for children could be relatively high in some cases.

The ILCR values for different exposure pathways can be summarized as follows: WC (dermal > ingestion > inhalation) > WR (dermal > ingestion > inhalation). Cancer risk levels via dermal contact were ranging from 4.58 × 10−4 to 2.70 × 10−2 with an average of 4.45 × 10−3 and between 3.36 × 10−4 and 1.98 × 10−2 with an average of 3.26 × 10−3 for adults and children in WC sampling sites, respectively. The risk levels were slightly higher in WC-exposure sites than in those in the WR-exposure sites (ranging between 4.59 × 10−4 and 1.42 × 10−3 for adults and between 3.36 × 10−4 and 1.04 × 10−3 for children). Similarly, cancer risk levels via ingestion pathway in WC sites (ranging from 2.47 × 10−4 to 1.45 × 10−2 for adults and from 1.81 × 10−4to 1.07 × 10−2 for children) were also somewhat higher than those in WR-exposure sites ranging between 2.48 × 10−4 and 7.68 × 10−4 and between 1.81 × 10−4 and 5.62 × 10−4 for adults and children, respectively.

Minimum or negligible (i.e., >10−6) cancer risk levels were observed for inhalation pathways, ranging between 1.92 × 10-8 and 1.13 × 10-6 for adults and between 5.27× 10-9 and 3.10 × 10-7 for children exposed in WC-exposure sites, and from 1.92 × 10−8 to 5.95 × 10−8 for adults and from 5.28 × 10−9 to 1.64 × 10−8 for children exposed in WR-exposure sites. The total cancer risk due to PAH exposure from all the routes was 6.85 × 10−3 and 5.02 × 10−3 for adults and children exposed in WC-exposure sites, and 1.26 × 10−3 and 9.23 × 10−4 for adults and children exposed in WR-exposure sites.

The total ILCR values were compared with U.S. EPA’s acceptable risk range of 1 × 10−6-1 × 10−4. For both exposed population, the ILCR values exceeded the acceptable safe values proposed by U.S. EPA. The results of cancer risk assessment obtained in this study also signify the implication of lung cancer/respiratory disorders in exposed population.

Conclusions

In Pakistan, traditional and primitive household and professional cooking practices are widespread in the country, which is attributable both to poverty and severe energy crisis, present in the country for many years. Analysis of surface dust from residential and occupational areas showed high concentrations of PAHs in both the exposure sites. In particular, B(a)P, which is a potent carcinogenic PAH, was found in highest concentrations. Comparatively, the professional cooking sites present high concentrations of PAHs and consequent health risks compared to residential sites; however, both sites pose high potential lifetime cancer risk to humans from exposure to dust-bound PAHs in particular via both ingestion and dermal contact pathways. The issue needs control/remediation or preventive measures on urgent basis, by introducing pollution abatement policies and improving the conditions of household and occupational cooking environments.