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Emission characteristics of PM2.5-bound chemicals from residential Chinese cooking
Building and Environment 149 (2019) 623–629
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Emission characteristics of PM2.5-bound chemicals from residential Chinese cooking
T
Yuejing Zhaoa, Chen Chena, Bin Zhaoa,b,∗ a b
Department of Building Science, School of Architecture, Tsinghua University, Beijing, 100084, China Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing, 100084, China
A R T I C LE I N FO
A B S T R A C T
Keywords: Polycyclic aromatic hydrocarbons (PAHs) Chemical elements Organic carbon (OC) Elemental carbon (EC) Emission rates Source profile
The chemical composition of fine particulate matter (PM2.5) emitted during cooking such as polycyclic aromatic hydrocarbons (PAHs), chemical elements (especially heavy metals), organic carbon (OC), and elemental carbon (EC) are of great concern to human health in China. We collected five duplicate sets of samples of cooking emissions from a Chinese residential kitchen for the five most common cooking methods based on orthogonal design. Emission rates and concentrations of PM2.5-bound chemicals, including 16 PAHs, 21 elements, OC, and EC, were determined based on the corresponding mass fraction of species in PM2.5. The chemical profile of PM2.5 varied according to the cooking method. The results indicated that OC was the dominant component of the fine emitted particles and the emission rates ranged from 27.87 μg/min to 1916.68 μg/min. In comparison, the emission rates of EC ranged from 2.02 μg/min to 29.47 μg/min. The emission rates of the elements varied between 0.01 ng/min and 9.57 μg/min and S, Ca, Na, K, Al, Mg, and Fe were the most abundant elements in cooking profiles. The total emission rates of the 16 PAHs in PM2.5 ranged between 8.83 ng/min and 241.06 ng/ min and Nap, Pyr, Chr, BghiP, and Phe were the main PAHs released from residential cooking. Thereinto, Nap and Phe could be utilized as organic markers to distinguish between cooking and other non-cooking source emissions. These findings could assist in the determination of the concentrations of PM2.5-bound chemicals in regard to emission control strategies, as well as in the assessment of health risks.
1. Introduction Cooking has been identified as a major source of indoor particulate matter (PM), particularly in Chinese households. In this respect, fine particles (PM2.5, PM with an aerodynamic diameter less than 2.5 μm) are of concern to human health [1–5]. Previous studies have demonstrated that exposure to cooking oil fumes (COF) is associated with the development of lung cancer among non-smoking Chinese women [6–8]. The high temperatures in excess of 200 °C that are required for some traditional Chinese cooking methods, such as stir-, pan-, and deepfrying, generate fine particulate matter and the incomplete combustion or pyrolysis of organic matter that contains hydrogen and carbon to produce polycyclic aromatic hydrocarbons (PAHs), which have been identified as possible carcinogens [9,10]. Moreover, particle-bound PAHs (PPAHs) attached to fine particles may be more harmful to humans than the gaseous phase PAHs because PPAHs generally have a higher molecular weight and more carcinogenic [11]. It has been reported that the total percentage of particulate phase PAH in Chinese cooking is higher compared with Western cooking styles [12], and
∗
PPAHs are predominantly absorbed onto PM2.5 with a 59–97% total particulate phase proportion [11]. In addition, toxic heavy metals adsorbed onto the large surface area of PM2.5 likely have a deleterious effect on the respiratory and nervous systems of humans [13,14]. Even though elemental compositions indicate only a small portion by mass of PM2.5, trace elements, such as Pb, As, and Cd may cause inflammation or DNA damage, and alter the permeability of cells by inducing the production of oxygen species in tissues, which are also considered to be possible carcinogens [15–17]. Therefore, chemical composition analysis of particles from cooking emissions is important for source identification, pollution control strategies, and health risk assessment. Furthermore, organic compounds are often signatures of their particular pollution sources [18], thus, the chemical analysis of PM2.5 would also aid in source apportionment studies to identify major sources, which can be useful in the development of improved control strategies. Previous studies on mass concentration and chemical composition of particles emitted from Chinese cooking activities mainly focused on commercial restaurants [1,12,19–24] or oil-heating processes [25,26], and seldom on the characterization of elemental composition [2]. The
Corresponding author. Dept. of Building Science, School of Architecture, Tsinghua University, Beijing, China. E-mail address: [email protected] (B. Zhao).
https://doi.org/10.1016/j.buildenv.2018.12.060 Received 30 October 2018; Received in revised form 24 December 2018; Accepted 28 December 2018 Available online 31 December 2018 0360-1323/ © 2018 Elsevier Ltd. All rights reserved.
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styles where gas stoves are used. Five key factors were examined (cooking method, the weight of ingredients, the type of meat, the ratio of meat to vegetables, and the type of oil, Table S6) in this investigation. The results of our previous studies have shown that the cooking method is the most important factor in particle emissions during Chinese residential cooking and stir-frying produces the highest emission rates of PM2.5, while steaming produces the lowest emissions among the five investigated cooking methods [30]. Therefore, a total of 25 dishes cooked using five cooking methods (stir-frying, pan-frying, deep-frying, boiling, and steaming) were selected based on orthogonal design. The details of the orthogonal design process were described in our previous study [30]. On each sampling day, only one sample was collected, where five experiments corresponding to the five different dishes were conducted based on the same cooking method. All the dishes were cooked by a professional chef using the same cooking utensils to ensure repeatability. For each cooking method the PM2.5 emissions were collected onto the same filter from indoor air in the vicinity of the cooking pan, which was 1.2 m above the floor. The fan of the exhaust hood was turned off during the entire measurement period and all the windows and doors were kept closed. The kitchen was forcedly ventilated to ensure that the PM2.5 concentration returned to the background level between each experiment. The background sample in the kitchen in the absence of cooking or gas burning was also collected. The experiments for each cooking method were repeated twice except for boiling and steaming. In these two cases, the experiment was conducted only once because the PM2.5 emission rates from these water-based cooking methods were much lower than the rates from the three oil-based cooking methods [30]. Ten samples, including one background sample obtained under the same experimental procedure, one solvent blank sample to evaluate the possibility of contamination and loss during pretreatment, and 8 samples collected for the different cooking methods (duplicate samples for stir-, pan-, deep-frying and single sample for boiling and steaming) were analyzed and the average values minus the background level were used for data analysis.
existing body of research on PM from Chinese cooking activities in domestic kitchens is deficient in that the effect of various cooking methods has not been considered [11,27]. See and Balasubramanian [28] conducted experiments using tofu as the main food material to characterize the fine particles emitted from different cooking methods; however, the cooking process involving tofu is not typical or representative of Chinese domestic cooking. Zhang et al. [29] collected five sets of PM2.5 cooking samples in a domestic kitchen that used five types of commonly used oils; however, the influence of cooking oils on emission characteristics may not be significant [30]. All these studies reported on mass concentrations rather than emission rates, but the concentrations can vary greatly because of differences in ventilation patterns and the scale of the kitchen. Hence, the results based on the concentrations of PM2.5 components would not be as accurate as those based on the emission rates for pollution control and risk assessment. In this study, a total of 25 typical Chinese dishes were chosen based on orthogonal design and five sets of experiments were conducted in a domestic kitchen that used five types of cooking methods. The chemical composition of PM2.5 was analyzed for organic carbon (OC), elemental carbon (EC), 21 elements, and 16 PAHs. The primary objective of our study was to build PM2.5 source profiles and to determine the emission rates of PM2.5 components during cooking in a residential kitchen. The results can provide a basis for indoor air quality control and health risk assessment, as well as PM2.5 source apportionment studies. 2. Methods 2.1. Instrumentation and measurements A residential kitchen with a volume of 10.88 m3 in Beijing was chosen for sampling from March 4, 2018, to April 2, 2018. The layout of the kitchen can be found in Chen et al. [30]. Two fans were used to fully mix the indoor air. The real-time mass concentrations of PM2.5 were monitored using one laser photometer equipped with a 2.5 μm impactor (AM510; TSI Inc., Shoreview, MN, USA) for the determination of emission rates. PM2.5 samples were collected at a flow rate of 10 L/min during cooking using two identical pumps (LP-20; A.P. Buck Inc., Orlando, FL, USA), and each pump was configured with a PM2.5 cutting head (PEM, Model 200, PEM-10-2.5; MSP Corp., Shoreview, MN, USA). One of the pumps was loaded with a 37 mm Teflon filter (Tisch Environmental Inc., Cleves, OH, USA) to analyze the elements, while the other with a 37 mm quartz-fiber filter (Munktell Filter AB, Falun, Dalarna, Sweden) was used to analyze PAHs, OC, and EC. The flow rate was calibrated using a soap-film calibrator (M-30; A.P. Buck Inc., Orlando, FL, USA) before and after sampling to ensure that it matched the required flow rate of the cutting head. The variance of the flow rate ranged from 0.02% to 2.71%. Prior to and after sampling, the Teflon filters were stored in a temperature and humidity chamber (KMF115, BINDER Inc., Bohemia, NY, USA) under a controlled temperature (25 °C ± 0.1 °C) and relative humidity (45% ± 2.5%) for 24 h, prior to being weighed on an electronic microbalance (XS3DU, Mettler-Toledo, Greifensee, Switzerland) with an accuracy of 0.001 mg in a clean room that was free from dust and under contaminants. For each filter, the average of three successive measurements with a difference of less than 0.003 mg was used. The weighing results of the Teflon filters were applied to the corresponding quartz filters because the two pumps for the Teflon and quartz filters were placed at the same location during sampling. The monitoring results of the AM510 could then be calibrated against the gravimetric measurements of the Teflon filters. The emission characteristics of particulate matter from Chinese cooking are associated with many factors, including the ingredients, type of oil, type of stove, and cooking methods [21,28,31–34]. Since the ingredients depend on the type and the weight of food materials, and natural gas is the most frequently used cooking fuel in China [35], we designed an orthogonal test based on a survey of cooking behavior (Tables S1–5) that took into consideration the typical Chinese cooking
2.2. Analytical procedure The exposed filters were sealed with tinfoil paper and stored at −18 °C prior to chemical analysis. A piece of quartz filter with an area of 0.552 cm2 was cut off to be analyzed for OC and EC using the thermal/optical reflectance (TOR) method following the Interagency Monitoring of Protected Visual Environments protocol (IMPROVE-A) and a DRI (Desert Research Institute) Thermal/Optical Carbon Analyzer (Model 2001A, Atmoslytic Inc., Calabasas, California, USA). The remaining quartz filter was used for the analysis of PAHs using gas chromatography coupled with mass spectrometry (GC/MS, GCMSQP2010 Plus, Shimadzu Corp., Kyoto, Japan) following the People's Republic of China national environmental protection standard (HJ 646–2013). A total of 16 PAHs including in the United States Environmental Protection Agency (USEPA) priority list were detected. They are Naphthalene (Nap), Acenaphthylene (Acy), Acenaphthene (Ace), Fluorene (Flu), Phenanthrene (Phe), Anthracene (Ant), Fluoranthene (Flt), Pyrene (Pyr), Benz[a]anthracene (BaA), Chrysene (Chr), Benzo[b]fluoranthene (BbF), Benzo[k]fluoranthene (BkF), Benzo [a]pyrene (BaP), Indeno[1,2,3-c,d]pyrene (IND), Dibenz[a,h]anthracene (DBA), and Benzo[g,h,i]perylene (BghiP). The analyzer was calibrated daily and the recovery test for the analytical procedure was performed using standard reagents to ensure the accuracy of the analysis. The results showed that the total recovery efficiencies of the PAHs ranged from 95.9% to 128.0% and the relative correlation for the standard curve was higher than 0.998. Each Teflon filter was dissolved in nitric acid and hydrogen peroxide in a microwave digestion system (Ultra WAVE, Milestone Srl, Sorisole, BG, Italy) to analyze Al, P, V, Cr, Mn, Fe, Ti, Co, Ni, Cu, Zn, As, Br, Cd, Sb, and Pb using inductively coupled plasma-mass spectrometry (ICP-MS, ELAN DRC II, PerkinElmer 624
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Inc., Waltham, MA, USA) and K, Na, Ca, Mg, and S using inductively coupled plasma atomic emission spectrometry (ICP-AES, iCAP6000, Thermo Fisher Scientific Inc., Waltham, MA, USA). Information on the detection limits of the analytical methods is listed in the Supplementary Material (Table S7). 2.3. Emission rates of PM2.5 species PM2.5 emissions can be determined using the following mass balance equation [36]:
dCin, p (t )/ dt = aPCout − (a + k ) Cin, p (t ) + Sp/ V
(1)
where Cin,p(t) is the real-time indoor mass concentration of PM2.5 at time t, Cout is the outdoor concentration of PM2.5, Sp is the emission rate of PM2.5 which is defined as the mass of PM2.5 generated from cooking activity (including the use of cooking utensils) per unit time, a is the air exchange rate, k is the removal rate due to the deposition of particles in the kitchen, P is the penetration factor for outdoor PM2.5 entering the indoor environment through the building envelope, and V is the volume of the kitchen. The emission rate of the PM2.5, Sp, can be calculated based on the nonlinear fitting of the indoor PM2.5 concentration increasing curves. The detailed calculations are described in Chen et al. [30]. The emission rate of PM2.5 species can be calculated as follows:
Sp, x = Sp⋅fm, x
Fig. 1. Percentage of chemical species in PM2.5 emitted from various Chinese cooking methods.
for EC), but approximately 0.8% higher than the results of Zhang et al. [29] (0.4% for EC and 0.7% for elements). Differences in food ingredients, oil types and chemical analysis methods could contribute to the observed discrepancy relative to the other studies. However, the chemical compositions of PM2.5 for steaming and boiling were different from each other. This is due to the reduction in oil consumption as well as the use of a cover lid with tiny holes during steaming. In this study, OC, EC, and elements contributed to 60%, 8.4%, and 3.7% of the boiling-emitted PM2.5 mass fraction. This result is similar to that of See and Balasubramanian [28]. The particularly large proportion of other species that originate from steaming might imply that inorganic ions are contained in a mass of steam produced during steaming. Specific information on the abundance of PM2.5-bound species emitted from various cooking methods is provided in Table S8.
(2)
where Sp,x is the emission rate of a PM2.5 species x and fm,x is the mass fraction of species x in PM2.5, including elements, PAHs, OC, and EC. 2.4. Calculation of the coefficient of divergence The chemical profiles of the PM2.5 may vary depending on the cooking method and any similarity of the PM2.5 generated from different cooking sources (cooking methods, in this study) can be quantified using the coefficient of divergence (CD), a self-normalizing parameter used to measure the spread of two datasets [29,37–39]. The CD can be calculated as follows: p
CDjk =
3.1.2. Similarity assessment of different cooking methods by the coefficient of divergence As shown in Table S9, all the CD values are greater than or equal to 0.3 except for the comparison between deep-frying and boiling. This result highlights the discrepancies in the PM2.5 emissions between various cooking methods [29,38,41]. The results also show that the cooking method was an important influencing factor for the determination of cooking-related PM2.5 emissions. The CD values between the oil-based cooking methods were close to 0.3, while much higher values were observed between steaming and the other cooking methods (all greater than 0.6), demonstrating the differences between oil-based and water-based cooking methods.
2
(1/ p) ∑ ((x ij − x ik )/(x ij + x ik )) i=1
(3)
where j and k represent the different cooking methods, CDjk represents the CD between cooking methods j and k, xij and xik represent the emission rate of the PM2.5 species i using cooking methods j and k respectively, and p represents the number of chemical species in the calculation. To better express the inherent characteristics of the chemical composition of the PM2.5, we used the emission rates instead of the concentration data as the values of xij and xik, which is different from the calculations described in the literature [29,37,38].
3.2. Elemental composition
3. Results
As shown in Table S10 of the Supplementary Material, the concentrations of PM2.5 in the samples collected during stir-frying, panfrying, deep-frying, steaming, and boiling were 0.68–0.99 mg/m3, 0.29–0.48 mg/m3, 0.14–0.24 mg/m3, 0.04 mg/m3, and 0.08 mg/m3, respectively, while the corresponding emission rates were 2.56–2.65 mg/min, 1.61–1.69 mg/min, 0.32–0.56 mg/min, 0.05 mg/ min, and 0.08 mg/min. The abundance of the 21 measured elements in the PM2.5 ranged from 76.40 ng/g to 20.36 mg/g for the different cooking methods. The emission rates and concentrations of elements were 0.01 ng/min–9.57 μg/min and 0.05 ng/m3–2.93 μg/m3, respectively. The concentrations as well as the abundance of the 21 PM2.5bound elements are listed in detail in the Supplementary Material (Figs. S1–2). A comparison between this study and previous studies based on the abundance of elements is shown in Fig. S3. Table S8 in the Supplementary Material shows that S, Ca, Na, K, Al, Mg, and Fe are the most abundant elements in the cooking profiles
3.1. Chemical profiles of PM2.5 from residential Chinese cooking 3.1.1. Species abundance in PM2.5 emitted from various cooking methods Fig. 1 shows the species mass fractions in PM2.5 emitted as a result of various Chinese cooking methods in a residential kitchen. In general, the three oil-based cooking methods share a similar chemical profile, where OC is the dominant proportion (72%–74%) in PM2.5. This value was higher than the OC fraction (63%) measured in the study by Zhang et al. [29]. The underestimation of organic compounds (organic carbon vs. organic matter) in Zhang's study [29] was possibly attributed to the assumption of a negligible contribution from the existing PM2.5 background in the apartment. The percentage of EC and measured elements from the oil-based cooking methods was 1.0%–1.3% and 1.0%–1.9%, respectively, in agreement with the results of Wen and Hu [40] (1%–2% 625
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et al. [29].
obtained for this study and their mass fractions account for approximately 98% of the measured elements, regardless of the cooking method, This is because the crustal materials make up a large portion of the total suspended particles [42]. The relatively high content of Ca, Na, Fe, Mg, and Al was in accordance with the results of See and Balasubramanian [28], Li, et al. [43], Wang, et al. [38], and Zhang et al. [29], however, S was the most dominant element in the result obtained by Wang et al. [38] and in this study. Although trace elements (As, Cd, Co, Cr, Cu, Mn, Ni, Pb, V, and Zn) were far less abundant in the samples, they are known to be more harmful to human health. In this study, Pb, Mn, and Cr were dominant among the heavy metals and they may pose a carcinogenic or a non-carcinogenic risk [17]. Cr was associated with the meat cooking process and could be leached into the air from stainless steel woks under high temperatures [28]. Trace metals, such as Pb and Mn could be emitted from cooking oil, especially peanut oil and canola oil, which have been utilized in our previous studies [44,45]. In addition, Mn could also be contained in the mushrooms used in our pan-frying and deep-frying. Na was likely derived from the salt used and K is associated with oil-based meat cooking [29,38]. Fe, Cr, Ni, and Cu were likely emitted from the stainless steel woks used for cooking when they were subjected to high cooking temperatures [28,42]. In addition, the emission rates of Cu and Zn during oil-based cooking were higher than those during water-based cooking, thus it is likely that they were released from the cooking oils (Fig. 2) [42]. Oil-based cooking, especially stir-frying, generates more emissions than water-based cooking (Fig. 2) and large emissions lead to high concentrations of elements (Fig. S2).
3.3.2. Percentage of PAHs with different aromatic ring numbers The distribution of PAHs with varying aromatic ring numbers was different for the various cooking methods (Fig. 3). Two-ring PAHs (Nap) predominated the total detected PM2.5-bound PAHs emitted from the oil-based cooking methods (above 40%), while the most abundant fraction for steaming and boiling was the three-ring (Acy, Ace, Flu, Phe, and Ant) and four-ring (Flt, Pyr, BaA, and Chr) PAHs, respectively. The percentage of six-ring PAHs (IND and BghiP) was the largest for waterbased (16%–24%) and the smallest for oil-based (6%–13%) cooking methods. The distribution pattern of the five-ring PAHs (BbF, BkF, BaP, and DBA) associated with the different cooking methods was similar to that of the six-ring PAHs. In this study, low molecular weight PAHs (LM-PAHs, containing two-to three-ring PAHs) from oil-based cooking methods accounted for over 50% of the total PM2.5-bound PAHs (53%, 64%, and 73% for stir-, pan-, and deep-frying, respectively), while the corresponding proportions from water-based cooking methods were approximately 35%. The amount of LM-PAHs emitted from deep-frying was higher than that from stir-frying and pan-frying, because high molecular weight PAHs (HM-PAHs, containing five-to seven-ring PAHs) can be decomposed or destroyed at high cooking temperatures during deep-frying, which facilitates LM-PAH formation [46]. Accordingly, the amount of HM-PAHs from deep-frying was the lowest (11%) of the three oil-based (14% for pan-frying and 20% for stir-frying) cooking methods. The most abundant component in PAHs due to boiling was the middle molecular weight PAHs (MM-PAHs, containing four-ring PAHs), accounting for 39%. The percentage of HM-PAHs in the total PAHs was the largest for steaming (39%). The percentage of carcinogenic PAHs (C-PAHs, including BaA, Chr, BbF, IND, DBA, and BaP) from stir-, pan-, and deepfrying was 20%, 13%, and 15% respectively, of the total detected PAHs in PM2.5.
3.3. PAHs 3.3.1. Characterization of PAHs emitted from different cooking methods Table 1 lists the emission rates of PM2.5-bound PAHs due to various Chinese cooking styles. The total emission rates of 16 PAHs in PM2.5 from stir-frying, pan-frying, deep-frying, steaming, and boiling were 180.09–270.59, 240.51–241.61, 79.87–117.59, 37.86, and 8.83 ng/ min, respectively, and the concentrations were 58.90–92.14, 41.23–72.57, 34.57–50.89, 29.54, and 8.00 ng/m3. Detailed information on PAH abundance and concentrations is provided in Tables S11–S12. The emission rates of Nap were the highest for all three oilbased cooking methods in this study, while Phe and Chr emissions were the highest for steaming and boiling. In general, Nap, Pyr, Chr, and BghiP were the main PAHs released during oil-based cooking activities, whereas Chr and Phe were the predominant PAHs in the emissions from water-based cooking activities. Pyr and Phe were also reported to be abundant in PM2.5-bound PAHs from Chinese cooking in investigations performed by He et al. [1], Zhao, et al. [21], Saito, et al. [4] and Zhang
3.4. OC & EC The OC emission rates were 1826.95 μg/min −2006.41 μg/min, 1164.46–1259.61 μg/min, 252.82 μg/min −368.84 μg/min, 36.12 μg/ min, and 27.87 μg/min for stir-frying, pan-frying, deep-frying, steaming, and boiling, respectively, while the corresponding EC emission rates were 24.55 μg/min −34.38 μg/min, 15.45 μg/min −16.59 μg/min, 3.48 μg/min −8.12 μg/min, 2.02 μg/min, and 3.95 μg/min. The mass fraction of the total carbon (TC) in PM2.5 varied from 46% to 75% for the different cooking methods, implying that carbonaceous particles were the dominant species in the PM2.5 emitted from cooking. No significant variance in OC or EC was observed for the
Fig. 2. Emission rates of elements in PM2.5 associated various Chinese cooking styles (the results for P element were below the field blank and are not shown in the figure). 626
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Table 1 Emission rates of PM2.5-bound PAHs due to various Chinese cooking methods. (ng/min)
Stir-frying
Pan-frying
Deep-frying
Steaminga
Boilinga
Nap Acy Ace Flu Phe Ant Flt Pyr BaA Chr BbF BkF BaP IND DBA BghiP Total
69.38–115.54 3.08–3.42 1.41–1.75 3.21–4.07 12.89–17.25 2.58–3.80 19.28–32.66 27.00–41.18 4.78–8.48 10.96–19.20 8.76–10.28 3.61–5.47 10.08–14.16 14.32–17.48 N.D. 13.60–16.40 180.09–270.59
131.37–152.23 2.21–2.43 1.32–1.86 2.26–2.70 0.20–3.54 7.83–7.89 11.86–12.84 21.56–24.34 4.49–5.39 13.91–15.57 N.D. 3.82–4.86 7.55–8.25 2.78–3.20 0.36–0.46 13.76–22.54 240.51–241.61
55.50–83.24 0.79–0.95 0.56–0.80 0.42–0.52 N.D. N.D. 0.33–2.53 1.86–5.74 1.44–1.94 7.59–9.85 N.D. 1.43–2.03 2.90–3.16 1.12–2.00 N.D. 2.39–8.35 79.87–117.59
0.66 N.D. 0.41 N.D. 10.77 0.95 N.D. N.D. 2.76 7.40 5.18 0.74 N.D. 4.18 N.D. 4.81 37.86
0.95 N.D. 0.43 N.D. 4.05 0.54 N.D. N.D. 1.56 4.99 1.16 0.52 N.D. 0.92 N.D. 1.61 8.83
N.D. means the results were below the detection limit and/or below the limit of the field blank. a The experiments involving steaming and boiling were conducted once due to the relatively low emission rates of PM2.5.
PM2.5 samples in various restaurants that use different cooking styles, including mixed cooking methods, which can be different from residential cooking. Zhang et al. [29] conducted measurements for different oil types in a domestic kitchen. The cooking method was the most influential factor for determining the emission rates of PM2.5 in our previous study [30], which suggests that experiments that consider the cooking method as opposed to other factors might be more reasonable. See and Balasubramanian [28] investigated five different types of commonly used cooking methods that were the same as those used in this study. In their investigation, tofu was chosen as the main ingredient. However, a simple cooking process with only one raw material may not be representative of the diversity of Chinese cooking methods. In this study, we designed orthogonal experiments to select the most representative Chinese cooking style for home cooking. Furthermore, we collected PM2.5 samples distinguished only by the cooking method to identify the variations in emissions and concentrations caused by this most influential factor. Previous research mainly focused on the concentrations of the PM2.5-bound species; however, concentration levels can depend on a variety of factors such as the scale and the ventilation conditions of the kitchen. Concentrations may also depend on control interventions; e.g., turning on the fan of the range hood. Therefore, emission rates are better indicators of the inherent characteristics of the PM2.5 chemical composition, as described in Chen et al. [30] Species concentrations can then be determined under different scenarios for corresponding emission rates, with application to the study of PM2.5 control strategies, as well as in the assessment of health risks. In addition, emission profiles of diverse cooking methods for residential cooking may enhance the database of cooking emissions inventories, which can improve the results of source apportionment studies. The concentration profile of the PM2.5-bound species measured in this study can be applied to source identification of various cooking methods by calculating the source signature ratios and diagnostic ratios. We can also use the measured elemental concentrations to analyze the enrichment factors of the elements. The analysis of source identification and elemental enrichment factors is described in the Supplementary Material (Page S11eS14, Fig. S4, Tables S13–14). In this study, the enrichment factors varied according to the cooking method; nevertheless, Sb was determined to be the most enriched element regardless of the cooking method. In summary, residential Chinese cooking was associated with the emissions of Ca, Cr, Cu, Zn, As, Cd, Pb, and Sb, while Na and K could have originated from oil-based cooking due to the use of large amounts of salt. Na, OC, Ni, Cr, and Ni had the highest signature ratios for stir-frying, pan-frying, deep-frying, steaming, and boiling, respectively. Nap had the highest
Fig. 3. Mass compositions of PAHs with different numbers of aromatic rings.
oil-based cooking methods, while there was a significant difference between the oil-based and water-based cooking methods. Steaming generated the lowest OC proportion (44%) while boiling produced the highest EC fraction (8%) in the PM2.5. Oil-based cooking emitted more OC than water-based cooking, because of the long-chain hydrocarbons in cooking oil [28]. The OC/EC ratios for stir-frying, pan-frying, deepfrying, steaming, and boiling were 65.2, 75.5, 57.0, 17.9, and 7.0, respectively. These values are larger than the background level (5.4) and these ratios can be used to identify the sources of PM2.5 in source apportionment studies [43]. Overall, the measured OC/EC ratios due to cooking were much higher than those from other sources (0.8–2.2 from vehicle emissions [43]). The OC/EC ratios for oil-based cooking and boiling in this study were consistent with the results reported by Li et al. [43]. However, differences in the OC/EC ratios between oil-based and water-based cooking methods were observed, which can be attributed to the chemism between oils and food materials during high-temperature cooking (the peak oil temperatures during oil-based cooking could approach 110 °C-180 °C according to our measurement). 4. Discussion The chemical characteristics of cooking-related fine particles has been a popular topic in recent years due to the potential carcinogenic and non-carcinogenic risks posed by some organic and elemental components. He et al. [1] Wang et al. [38] and Li et al. [43] collected 627
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References
signature ratios for PM2.5-bound PAHs emitted from the three oil-based cooking methods, while Phe had the highest ratios for the two waterbased cooking methods. This implies that Nap and Phe can be used as organic markers to distinguish between cooking emissions and other non-cooking sources. This study has a few limitations. The PM2.5 emission rates were multiplied by the mass fractions of the PAH species to obtain the emission rates of the PM2.5-bound PAHs. However, the particle/gas partition coefficients of PAHs are associated with the corresponding saturation vapor pressure which is influenced by the environmental temperature [47–49]. This may cause variations in the partition between particle- and gas-phase PAHs during cooking. Therefore, the emission rates of PM2.5-bound PAHs calculated with the average abundance spanning the entire cooking process might not represent the real transient emission rates during cooking. However, the impact was possibly not apparent considering that the increase in the measured ambient temperature was smaller than 5 °C for oil-based cooking and 8 °C for water-based cooking [49].
[1] L.Y. He, M. Hu, X.F. Huang, B.D. Yu, Y.H. Zhang, D.Q. Liu, Measurement of emissions of fine particulate organic matter from Chinese cooking, Atmos. Environ. 38 (38) (2004) 6557–6564. [2] S.W. See, R. Balasubramanian, Risk assessment of exposure to indoor aerosols associated with Chinese cooking, Environ. Res. 102 (2) (2006) 197–204. [3] K.L. Abdullahi, J.M. Delgado-Saborit, R.M. Harrison, Emissions and indoor concentrations of particulate matter and its specific chemical components from cooking: a review, Atmos. Environ. 71 (2013) 260–294. [4] E. Saito, N. Tanaka, A. Miyazaki, M. Tsuzaki, Concentration and particle size distribution of polycyclic aromatic hydrocarbons formed by thermal cooking, Food Chem. 153 (2014) 285–291. [5] Y.J. Zhao, B. Zhao, Emissions of air pollutants from Chinese cooking: a literature review, Build. Simul. 11 (5) (2018) 977–995. [6] P. Thomson, T. Robinson, I.J. Robbe, Lung cancer and indoor air pollution arising from Chinese-style cooking among nonsmoking women living in Shanghai, China, Epidemiology 11 (4) (2000) 481–482. [7] H.S. Hung, W.J. Wu, Y.W. Cheng, T.C. Wu, K.L. Chang, H. Lee, Association of cooking oil fumes exposure with lung cancer: involvement of inhibitor of apoptosis proteins in cell survival and proliferation in vitro, Mutat. Res. Genet. Toxicol. Environ. Mutagen 628 (2) (2007) 107–116. [8] X. Wang, Y. Zhang, X. Cheng, Lung cancer risk assessment of cooking oil fume for Chinese nonsmoking women, WIT Trans. Built Environ. 145 (2014) 243–250. [9] L.Y. He, M. Hu, L. Wang, X.F. Huang, Y.H. Zhang, Characterization of fine organic particulate matter from Chinese cooking, J. Environ. Sci. 16 (4) (2004) 570–575. [10] IARC Working Group on the Evaluation of Carcinogenic Risks to Humans, Household Use of Solid Fuels and High-temperature Frying IN IARC Monographs on the Evaluation of Carcinogenic Risks to Humans IARC Monographs on the Evaluation of Carcinogenic Risks to Humans, International Agency for Research on Cancer, Lyon, France, 2010. [11] L.Z. Zhu, H. Lu, S.G. Chen, T. Amagai, Pollution level, phase distribution and source analysis of polycyclic aromatic hydrocarbons in residential air in Hangzhou, China, J. Hazard Mater. 162 (2–3) (2009) 1165–1170. [12] Y. Chen, K.F. Ho, S.S.H. Ho, W.K. Ho, S.C. Lee, J.Z. Yu, E.H.L. Sit, Gaseous and particulate polycyclic aromatic hydrocarbons (PAHs) emissions from commercial restaurants in Hong Kong, J. Environ. Monit. 9 (12) (2007) 1402–1409. [13] G.C. Fang, Y.L. Huang, J.H. Huang, Study of atmospheric metallic elements pollution in Asia during 2000-2007, J. Hazard Mater. 180 (1–3) (2010) 115–121. [14] P.H. Li, S.F. Kong, C.M. Geng, B. Han, B. Lu, R.F. Sun, R.J. Zhao, Z.P. Bai, Assessing the hazardous risks of vehicle inspection workers' exposure to particulate heavy metals in their work places, Aerosol Air Qual. Res. 13 (1) (2013) 255–265. [15] P. Gemenetzis, P. Moussas, A. Arditsoglou, C. Samara, Mass concentration and elemental composition of indoor PM2.5 and PM10 in university rooms in Thessaloniki, northern Greece, Atmos. Environ. 40 (17) (2006) 3195–3206. [16] S.L. Lu, Z.K. Yao, X.H. Chen, M.H. Wu, G.Y. Sheng, J.M. Fu, D. Paul, The relationship between physicochemical characterization and the potential toxicity of fine particulates (PM2.5) in Shanghai atmosphere, Atmos. Environ. 42 (31) (2008) 7205–7214. [17] IARC Working Group on the Evaluation of Carcinogenic Risks to Humans, A Review of Human Carcinogens: Arsenic, Metals, Fibres, and Dusts IN IARC Monographs on the Evaluation of Carcinogenic Risks to Humans IARC Monographs on the Evaluation of Carcinogenic Risks to Humans, International Agency for Research on Cancer, Lyon, France, 2012. [18] L. Lin, M.L. Lee, D.J. Eatough, Review of recent advances in detection of organic markers in fine particulate matter and their use for source apportionment, J. Air Waste Manag. Assoc. 60 (1) (2010) 3–25. [19] C.T. Li, Y.C. Lin, W.J. Lee, P.J. Tsai, Emission of polycyclic aromatic hydrocarbons and their carcinogenic potencies from cooking sources to the urban atmosphere, Environ. Health Perspect. 111 (4) (2003) 483–487. [20] S.W. See, S. Karthikeyana, R. Balasubramanian, Health risk assessment of occupational exposure to particulate-phase polycyclic aromatic hydrocarbons associated with Chinese, Malay and Indian cooking, J. Environ. Monit. 8 (3) (2006) 369–376. [21] Y.L. Zhao, M. Hu, S. Slanina, Y.H. Zhang, Chemical compositions of fine particulate organic matter emitted from Chinese cooking, Environ. Sci. Technol. 41 (1) (2007) 99–105. [22] C.H. Pan, C.C. Chan, K.Y. Wu, Effects on Chinese restaurant workers of exposure to cooking oil fumes: a cautionary note on urinary 8-hydroxy-2 '-Deoxyguanosine, Cancer Epidemiol. Biomark. Prev. 17 (12) (2008) 3351–3357. [23] P. Zhao, K.P. Yu, C.C. Lin, Risk assessment of inhalation exposure to polycyclic aromatic hydrocarbons in Taiwanese workers at night markets, Int. Arch. Occup. Environ. Health 84 (3) (2011) 231–237. [24] J.W. Chen, S.L. Wang, D.P.H. Hsieh, H.H. Yang, H.L. Lee, Carcinogenic potencies of polycyclic aromatic hydrocarbons for back-door neighbors of restaurants with cooking emissions, Sci. Total Environ. 417 (2012) 68–75. [25] L.Z. Zhu, J. Wang, Sources and patterns of polycyclic aromatic hydrocarbons pollution in kitchen air, China, Chemosphere 50 (5) (2003) 611–618. [26] J. Gao, Y.T. Jian, C.S. Cao, L. Chen, X. Zhang, Indoor emission, dispersion and exposure of total particle-bound polycyclic aromatic hydrocarbons during cooking, Atmos. Environ. 120 (2015) 191–199. [27] X.Y. Zhao, Q.H. Hu, X.M. Wang, X. Ding, Q.F. He, Z. Zhang, R.Q. Shen, S.J. Lu, T.Y. Liu, X.X. Fu, L.G. Chen, Composition profiles of organic aerosols from Chinese residential cooking: case study in urban Guangzhou, south China, J. Atmos. Chem. 72 (1) (2015) 1–18. [28] S.W. See, R. Balasubramanian, Chemical characteristics of fine particles emitted
5. Conclusions In this study, PM2.5 source profiles were built and the emission rates of PM2.5 components were determined during typical Chinese cooking in a residential kitchen. The CD values indicated discrepancies in the chemical profile of the PM2.5 between the various cooking methods. The results showed that OC was the dominant component of the fine particles. In this case, the emission rates ranged from 27.87 μg/min to 1916.68 μg/min while the emission rates of EC ranged from 2.02 μg/ min to 29.47 μg/min. The emission rates of the measured elements varied within a wide range between 0.01 ng/min and 9.57 μg/min and S, Ca, Na, K, Al, Mg, Fe were the most abundant elements in the cooking profiles regardless of the cooking method, accounting for a mass fraction of approximately 98% of the measured elements. Oil-based cooking generated more element and OC emissions than water-based cooking. The total emission rates of the 16 PAHs in PM2.5 ranged from between 8.83 ng/min and 241.06 ng/min and Nap, Pyr, Chr, BghiP, and Phe were the main PAHs generated during residential Chinese cooking. The percentage of carcinogenic PAHs (including BaA, Chr, BbF, IND, DBA, and BaP) from stir-frying (20%) was the highest among the three oilbased cooking methods. The signature ratios of the measured chemical components in PM2.5 imply that Nap and Phe could be used as organic markers to distinguish between cooking emissions and that from other non-cooking sources. The measured results for species emission rates could assist in the determination of concentrations of PM2.5-bound chemicals under various scenarios. This could provide a basis for indoor air quality control as well as health risk assessment. In addition, the measured chemical profiles from cooking could also be applied to PM2.5 source apportionment studies. Competing financial interests The authors have declared that they have no actual or potential competing financial interests. Acknowledgement This work was financially supported by the National Key Project of the Ministry of Science and Technology, China on “Green Buildings and Building Industrialization” [grant number 2016YFC0700500]; and the Innovative Research Groups of the National Natural Science Foundation of China [grant number 51521005]. Appendix A. Supplementary data Supplementary data to this article can be found online at https:// doi.org/10.1016/j.buildenv.2018.12.060. 628
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45 (30) (2011) 5351–5365. [40] M.T. Wen, M. Hu, Physical and chemical characteristics of fine particles emitted from cooking emissions and its contribution to particulate organic matter in Beijing (in Chinese), Huanjing Kexue 28 (11) (2007) 2620–2625. [41] B. Han, S.F. Kong, Z.P. Bai, G. Du, T. Bi, X. Li, G.L. Shi, Y. Hu, Characterization of elemental species in PM2.5 samples collected in four cities of northeast China, Water Air Soil Pollut. 209 (1–4) (2010) 15–28. [42] S. Taner, B. Pekey, H. Pekey, Fine particulate matter in the indoor air of barbeque restaurants: elemental compositions, sources and health risks, Sci. Total Environ. 454 (2013) 79–87. [43] Y.C. Li, M. Shu, S.S.H. Ho, C. Wang, J.J. Cao, G.H. Wang, X.X. Wang, K. Wang, X.Q. Zhao, Characteristics of PM2.5 emitted from different cooking activities in China, Atmos. Res. 166 (2015) 83–91. [44] Y.L. Liu, X.Y. Wu, G.Q. Xiang, Determination of lead in oil seeds and edible oil (in Chinese), China Oils Fats 36 (8) (2011) 74–77. [45] L.L. Wang, L. Lin, Y.H. Chen, Determination of lead, arsenic, manganese, cadmium, chromium, copper and other elements in edible oil using direct sampling by ICP-MS (in Chinese), Environ. Chem. 30 (2) (2011) 571–573. [46] Y.-C. Li, J.-Q. Qiu, M. Shu, S.S.H. Ho, J.-J. Cao, G.-H. Wang, X.-X. Wang, X.-Q. Zhao, Characteristics of polycyclic aromatic hydrocarbons in PM2.5 emitted from different cooking activities in China, Environ. Sci. Pollut. Control Ser. 25 (5) (2018) 4750–4760. [47] C.Z. Zhou, X.H. Zhu, Z. Wang, X.D. Ma, J.P. Chen, Y.W. Ni, W. Wang, J. Mu, X.X. Li, Gas-particle partitioning of PAHs in the urban air of Dalian, China: measurements and assessments, Polycycl. Aromat. Comp. 33 (1) (2013) 31–51. [48] W.J. Wei, C. Mandin, O. Blanchard, F. Mercier, M. Pelletier, B. Le Bot, P. Glorennec, O. Ramalho, Distributions of the particle/gas and dust/gas partition coefficients for seventy-two semi-volatile organic compounds in indoor environment, Chemosphere 153 (2016) 212–219. [49] B. Zhou, Model Analysis on Population Inhalation Exposure to Polycyclic Aromatic Hydrocarbons and Associated Lung Cancer Risk (In Chinese), Department of Building Science, 2013 Master thesis.
from different gas cooking methods, Atmos. Environ. 42 (39) (2008) 8852–8862. [29] N. Zhang, B. Han, F. He, J. Xu, R.J. Zhao, Y.J. Zhang, Z.P. Bai, Chemical characteristic of PM2.5 emission and inhalational carcinogenic risk of domestic Chinese cooking, Environ. Pollut. 227 (2017) 24–30. [30] C. Chen, Y.J. Zhao, B. Zhao, Emission rates of multiple air pollutants generated from Chinese residential cooking, Environ. Sci. Technol. 52 (3) (2018) 1081–1087. [31] C.L. Wu, C.Y.H. Chao, G.N. Sze-To, M.P. Wan, T.C. Chan, Ultrafine particle emissions from cigarette smouldering, incense burning, vacuum cleaner motor operation and cooking, Indoor Built Environ. 21 (6) (2012) 782–796. [32] Q.F. Zhang, R.H. Gangupomu, D. Ramirez, Y.F. Zhu, Measurement of ultrafine particles and other air pollutants emitted by cooking activities, Int. J. Environ. Res. Publ. Health 7 (4) (2010) 1744–1759. [33] W.M. To, L.L. Yeung, Effect of fuels on cooking fume emissions, Indoor Built Environ. 20 (5) (2011) 555–563. [34] J. Gao, C.S. Cao, L. Wang, T.H. Song, X. Zhou, J. Yang, X. Zhang, Determination of size-dependent source emission rate of cooking-generated aerosol particles at the oil-heating stage in an experimental kitchen, Aerosol Air Qual. Res. 13 (2) (2013) 488–496. [35] X. Duan, Y. Jiang, B. Wang, X. Zhao, G. Shen, S. Cao, N. Huang, Y. Qian, Y. Chen, L. Wang, Household fuel use for cooking and heating in China: results from the first Chinese environmental exposure-related human activity patterns survey (CEERHAPS), Appl. Energy 136 (1) (2014) 692–703. [36] C.R. He, L.D. Morawska, J. Hitchins, D. Gilbert, Contribution from indoor sources to particle number and mass concentrations in residential houses, Atmos. Environ. 38 (21) (2004) 3405–3415. [37] Z.Q. Zhang, S.K. Friedlander, A comparative study of chemical databases for fine particle Chinese, Environ. Sci. Technol. 34 (22) (2000) 4687–4694. [38] G. Wang, S.Y. Cheng, W. Wei, W. Wen, X.Q. Wang, S. Yao, Chemical characteristics of fine particles emitted from different Chinese cooking styles, Aerosol Air Qual. Res. 15 (6) (2015) 2357–2366. [39] S.F. Kong, Y.Q. Ji, B. Lu, L. Chen, B. Han, Z.Y. Li, Z.P. Bai, Characterization of PM10 source profiles for fugitive dust in Fushun-a city famous for coal, Atmos. Environ.
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Emission characteristics of PM2.5-bound chemicals from residential Chinese cooking
T
Yuejing Zhaoa, Chen Chena, Bin Zhaoa,b,∗ a b
Department of Building Science, School of Architecture, Tsinghua University, Beijing, 100084, China Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing, 100084, China
A R T I C LE I N FO
A B S T R A C T
Keywords: Polycyclic aromatic hydrocarbons (PAHs) Chemical elements Organic carbon (OC) Elemental carbon (EC) Emission rates Source profile
The chemical composition of fine particulate matter (PM2.5) emitted during cooking such as polycyclic aromatic hydrocarbons (PAHs), chemical elements (especially heavy metals), organic carbon (OC), and elemental carbon (EC) are of great concern to human health in China. We collected five duplicate sets of samples of cooking emissions from a Chinese residential kitchen for the five most common cooking methods based on orthogonal design. Emission rates and concentrations of PM2.5-bound chemicals, including 16 PAHs, 21 elements, OC, and EC, were determined based on the corresponding mass fraction of species in PM2.5. The chemical profile of PM2.5 varied according to the cooking method. The results indicated that OC was the dominant component of the fine emitted particles and the emission rates ranged from 27.87 μg/min to 1916.68 μg/min. In comparison, the emission rates of EC ranged from 2.02 μg/min to 29.47 μg/min. The emission rates of the elements varied between 0.01 ng/min and 9.57 μg/min and S, Ca, Na, K, Al, Mg, and Fe were the most abundant elements in cooking profiles. The total emission rates of the 16 PAHs in PM2.5 ranged between 8.83 ng/min and 241.06 ng/ min and Nap, Pyr, Chr, BghiP, and Phe were the main PAHs released from residential cooking. Thereinto, Nap and Phe could be utilized as organic markers to distinguish between cooking and other non-cooking source emissions. These findings could assist in the determination of the concentrations of PM2.5-bound chemicals in regard to emission control strategies, as well as in the assessment of health risks.
1. Introduction Cooking has been identified as a major source of indoor particulate matter (PM), particularly in Chinese households. In this respect, fine particles (PM2.5, PM with an aerodynamic diameter less than 2.5 μm) are of concern to human health [1–5]. Previous studies have demonstrated that exposure to cooking oil fumes (COF) is associated with the development of lung cancer among non-smoking Chinese women [6–8]. The high temperatures in excess of 200 °C that are required for some traditional Chinese cooking methods, such as stir-, pan-, and deepfrying, generate fine particulate matter and the incomplete combustion or pyrolysis of organic matter that contains hydrogen and carbon to produce polycyclic aromatic hydrocarbons (PAHs), which have been identified as possible carcinogens [9,10]. Moreover, particle-bound PAHs (PPAHs) attached to fine particles may be more harmful to humans than the gaseous phase PAHs because PPAHs generally have a higher molecular weight and more carcinogenic [11]. It has been reported that the total percentage of particulate phase PAH in Chinese cooking is higher compared with Western cooking styles [12], and
∗
PPAHs are predominantly absorbed onto PM2.5 with a 59–97% total particulate phase proportion [11]. In addition, toxic heavy metals adsorbed onto the large surface area of PM2.5 likely have a deleterious effect on the respiratory and nervous systems of humans [13,14]. Even though elemental compositions indicate only a small portion by mass of PM2.5, trace elements, such as Pb, As, and Cd may cause inflammation or DNA damage, and alter the permeability of cells by inducing the production of oxygen species in tissues, which are also considered to be possible carcinogens [15–17]. Therefore, chemical composition analysis of particles from cooking emissions is important for source identification, pollution control strategies, and health risk assessment. Furthermore, organic compounds are often signatures of their particular pollution sources [18], thus, the chemical analysis of PM2.5 would also aid in source apportionment studies to identify major sources, which can be useful in the development of improved control strategies. Previous studies on mass concentration and chemical composition of particles emitted from Chinese cooking activities mainly focused on commercial restaurants [1,12,19–24] or oil-heating processes [25,26], and seldom on the characterization of elemental composition [2]. The
Corresponding author. Dept. of Building Science, School of Architecture, Tsinghua University, Beijing, China. E-mail address: [email protected] (B. Zhao).
https://doi.org/10.1016/j.buildenv.2018.12.060 Received 30 October 2018; Received in revised form 24 December 2018; Accepted 28 December 2018 Available online 31 December 2018 0360-1323/ © 2018 Elsevier Ltd. All rights reserved.
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styles where gas stoves are used. Five key factors were examined (cooking method, the weight of ingredients, the type of meat, the ratio of meat to vegetables, and the type of oil, Table S6) in this investigation. The results of our previous studies have shown that the cooking method is the most important factor in particle emissions during Chinese residential cooking and stir-frying produces the highest emission rates of PM2.5, while steaming produces the lowest emissions among the five investigated cooking methods [30]. Therefore, a total of 25 dishes cooked using five cooking methods (stir-frying, pan-frying, deep-frying, boiling, and steaming) were selected based on orthogonal design. The details of the orthogonal design process were described in our previous study [30]. On each sampling day, only one sample was collected, where five experiments corresponding to the five different dishes were conducted based on the same cooking method. All the dishes were cooked by a professional chef using the same cooking utensils to ensure repeatability. For each cooking method the PM2.5 emissions were collected onto the same filter from indoor air in the vicinity of the cooking pan, which was 1.2 m above the floor. The fan of the exhaust hood was turned off during the entire measurement period and all the windows and doors were kept closed. The kitchen was forcedly ventilated to ensure that the PM2.5 concentration returned to the background level between each experiment. The background sample in the kitchen in the absence of cooking or gas burning was also collected. The experiments for each cooking method were repeated twice except for boiling and steaming. In these two cases, the experiment was conducted only once because the PM2.5 emission rates from these water-based cooking methods were much lower than the rates from the three oil-based cooking methods [30]. Ten samples, including one background sample obtained under the same experimental procedure, one solvent blank sample to evaluate the possibility of contamination and loss during pretreatment, and 8 samples collected for the different cooking methods (duplicate samples for stir-, pan-, deep-frying and single sample for boiling and steaming) were analyzed and the average values minus the background level were used for data analysis.
existing body of research on PM from Chinese cooking activities in domestic kitchens is deficient in that the effect of various cooking methods has not been considered [11,27]. See and Balasubramanian [28] conducted experiments using tofu as the main food material to characterize the fine particles emitted from different cooking methods; however, the cooking process involving tofu is not typical or representative of Chinese domestic cooking. Zhang et al. [29] collected five sets of PM2.5 cooking samples in a domestic kitchen that used five types of commonly used oils; however, the influence of cooking oils on emission characteristics may not be significant [30]. All these studies reported on mass concentrations rather than emission rates, but the concentrations can vary greatly because of differences in ventilation patterns and the scale of the kitchen. Hence, the results based on the concentrations of PM2.5 components would not be as accurate as those based on the emission rates for pollution control and risk assessment. In this study, a total of 25 typical Chinese dishes were chosen based on orthogonal design and five sets of experiments were conducted in a domestic kitchen that used five types of cooking methods. The chemical composition of PM2.5 was analyzed for organic carbon (OC), elemental carbon (EC), 21 elements, and 16 PAHs. The primary objective of our study was to build PM2.5 source profiles and to determine the emission rates of PM2.5 components during cooking in a residential kitchen. The results can provide a basis for indoor air quality control and health risk assessment, as well as PM2.5 source apportionment studies. 2. Methods 2.1. Instrumentation and measurements A residential kitchen with a volume of 10.88 m3 in Beijing was chosen for sampling from March 4, 2018, to April 2, 2018. The layout of the kitchen can be found in Chen et al. [30]. Two fans were used to fully mix the indoor air. The real-time mass concentrations of PM2.5 were monitored using one laser photometer equipped with a 2.5 μm impactor (AM510; TSI Inc., Shoreview, MN, USA) for the determination of emission rates. PM2.5 samples were collected at a flow rate of 10 L/min during cooking using two identical pumps (LP-20; A.P. Buck Inc., Orlando, FL, USA), and each pump was configured with a PM2.5 cutting head (PEM, Model 200, PEM-10-2.5; MSP Corp., Shoreview, MN, USA). One of the pumps was loaded with a 37 mm Teflon filter (Tisch Environmental Inc., Cleves, OH, USA) to analyze the elements, while the other with a 37 mm quartz-fiber filter (Munktell Filter AB, Falun, Dalarna, Sweden) was used to analyze PAHs, OC, and EC. The flow rate was calibrated using a soap-film calibrator (M-30; A.P. Buck Inc., Orlando, FL, USA) before and after sampling to ensure that it matched the required flow rate of the cutting head. The variance of the flow rate ranged from 0.02% to 2.71%. Prior to and after sampling, the Teflon filters were stored in a temperature and humidity chamber (KMF115, BINDER Inc., Bohemia, NY, USA) under a controlled temperature (25 °C ± 0.1 °C) and relative humidity (45% ± 2.5%) for 24 h, prior to being weighed on an electronic microbalance (XS3DU, Mettler-Toledo, Greifensee, Switzerland) with an accuracy of 0.001 mg in a clean room that was free from dust and under contaminants. For each filter, the average of three successive measurements with a difference of less than 0.003 mg was used. The weighing results of the Teflon filters were applied to the corresponding quartz filters because the two pumps for the Teflon and quartz filters were placed at the same location during sampling. The monitoring results of the AM510 could then be calibrated against the gravimetric measurements of the Teflon filters. The emission characteristics of particulate matter from Chinese cooking are associated with many factors, including the ingredients, type of oil, type of stove, and cooking methods [21,28,31–34]. Since the ingredients depend on the type and the weight of food materials, and natural gas is the most frequently used cooking fuel in China [35], we designed an orthogonal test based on a survey of cooking behavior (Tables S1–5) that took into consideration the typical Chinese cooking
2.2. Analytical procedure The exposed filters were sealed with tinfoil paper and stored at −18 °C prior to chemical analysis. A piece of quartz filter with an area of 0.552 cm2 was cut off to be analyzed for OC and EC using the thermal/optical reflectance (TOR) method following the Interagency Monitoring of Protected Visual Environments protocol (IMPROVE-A) and a DRI (Desert Research Institute) Thermal/Optical Carbon Analyzer (Model 2001A, Atmoslytic Inc., Calabasas, California, USA). The remaining quartz filter was used for the analysis of PAHs using gas chromatography coupled with mass spectrometry (GC/MS, GCMSQP2010 Plus, Shimadzu Corp., Kyoto, Japan) following the People's Republic of China national environmental protection standard (HJ 646–2013). A total of 16 PAHs including in the United States Environmental Protection Agency (USEPA) priority list were detected. They are Naphthalene (Nap), Acenaphthylene (Acy), Acenaphthene (Ace), Fluorene (Flu), Phenanthrene (Phe), Anthracene (Ant), Fluoranthene (Flt), Pyrene (Pyr), Benz[a]anthracene (BaA), Chrysene (Chr), Benzo[b]fluoranthene (BbF), Benzo[k]fluoranthene (BkF), Benzo [a]pyrene (BaP), Indeno[1,2,3-c,d]pyrene (IND), Dibenz[a,h]anthracene (DBA), and Benzo[g,h,i]perylene (BghiP). The analyzer was calibrated daily and the recovery test for the analytical procedure was performed using standard reagents to ensure the accuracy of the analysis. The results showed that the total recovery efficiencies of the PAHs ranged from 95.9% to 128.0% and the relative correlation for the standard curve was higher than 0.998. Each Teflon filter was dissolved in nitric acid and hydrogen peroxide in a microwave digestion system (Ultra WAVE, Milestone Srl, Sorisole, BG, Italy) to analyze Al, P, V, Cr, Mn, Fe, Ti, Co, Ni, Cu, Zn, As, Br, Cd, Sb, and Pb using inductively coupled plasma-mass spectrometry (ICP-MS, ELAN DRC II, PerkinElmer 624
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Inc., Waltham, MA, USA) and K, Na, Ca, Mg, and S using inductively coupled plasma atomic emission spectrometry (ICP-AES, iCAP6000, Thermo Fisher Scientific Inc., Waltham, MA, USA). Information on the detection limits of the analytical methods is listed in the Supplementary Material (Table S7). 2.3. Emission rates of PM2.5 species PM2.5 emissions can be determined using the following mass balance equation [36]:
dCin, p (t )/ dt = aPCout − (a + k ) Cin, p (t ) + Sp/ V
(1)
where Cin,p(t) is the real-time indoor mass concentration of PM2.5 at time t, Cout is the outdoor concentration of PM2.5, Sp is the emission rate of PM2.5 which is defined as the mass of PM2.5 generated from cooking activity (including the use of cooking utensils) per unit time, a is the air exchange rate, k is the removal rate due to the deposition of particles in the kitchen, P is the penetration factor for outdoor PM2.5 entering the indoor environment through the building envelope, and V is the volume of the kitchen. The emission rate of the PM2.5, Sp, can be calculated based on the nonlinear fitting of the indoor PM2.5 concentration increasing curves. The detailed calculations are described in Chen et al. [30]. The emission rate of PM2.5 species can be calculated as follows:
Sp, x = Sp⋅fm, x
Fig. 1. Percentage of chemical species in PM2.5 emitted from various Chinese cooking methods.
for EC), but approximately 0.8% higher than the results of Zhang et al. [29] (0.4% for EC and 0.7% for elements). Differences in food ingredients, oil types and chemical analysis methods could contribute to the observed discrepancy relative to the other studies. However, the chemical compositions of PM2.5 for steaming and boiling were different from each other. This is due to the reduction in oil consumption as well as the use of a cover lid with tiny holes during steaming. In this study, OC, EC, and elements contributed to 60%, 8.4%, and 3.7% of the boiling-emitted PM2.5 mass fraction. This result is similar to that of See and Balasubramanian [28]. The particularly large proportion of other species that originate from steaming might imply that inorganic ions are contained in a mass of steam produced during steaming. Specific information on the abundance of PM2.5-bound species emitted from various cooking methods is provided in Table S8.
(2)
where Sp,x is the emission rate of a PM2.5 species x and fm,x is the mass fraction of species x in PM2.5, including elements, PAHs, OC, and EC. 2.4. Calculation of the coefficient of divergence The chemical profiles of the PM2.5 may vary depending on the cooking method and any similarity of the PM2.5 generated from different cooking sources (cooking methods, in this study) can be quantified using the coefficient of divergence (CD), a self-normalizing parameter used to measure the spread of two datasets [29,37–39]. The CD can be calculated as follows: p
CDjk =
3.1.2. Similarity assessment of different cooking methods by the coefficient of divergence As shown in Table S9, all the CD values are greater than or equal to 0.3 except for the comparison between deep-frying and boiling. This result highlights the discrepancies in the PM2.5 emissions between various cooking methods [29,38,41]. The results also show that the cooking method was an important influencing factor for the determination of cooking-related PM2.5 emissions. The CD values between the oil-based cooking methods were close to 0.3, while much higher values were observed between steaming and the other cooking methods (all greater than 0.6), demonstrating the differences between oil-based and water-based cooking methods.
2
(1/ p) ∑ ((x ij − x ik )/(x ij + x ik )) i=1
(3)
where j and k represent the different cooking methods, CDjk represents the CD between cooking methods j and k, xij and xik represent the emission rate of the PM2.5 species i using cooking methods j and k respectively, and p represents the number of chemical species in the calculation. To better express the inherent characteristics of the chemical composition of the PM2.5, we used the emission rates instead of the concentration data as the values of xij and xik, which is different from the calculations described in the literature [29,37,38].
3.2. Elemental composition
3. Results
As shown in Table S10 of the Supplementary Material, the concentrations of PM2.5 in the samples collected during stir-frying, panfrying, deep-frying, steaming, and boiling were 0.68–0.99 mg/m3, 0.29–0.48 mg/m3, 0.14–0.24 mg/m3, 0.04 mg/m3, and 0.08 mg/m3, respectively, while the corresponding emission rates were 2.56–2.65 mg/min, 1.61–1.69 mg/min, 0.32–0.56 mg/min, 0.05 mg/ min, and 0.08 mg/min. The abundance of the 21 measured elements in the PM2.5 ranged from 76.40 ng/g to 20.36 mg/g for the different cooking methods. The emission rates and concentrations of elements were 0.01 ng/min–9.57 μg/min and 0.05 ng/m3–2.93 μg/m3, respectively. The concentrations as well as the abundance of the 21 PM2.5bound elements are listed in detail in the Supplementary Material (Figs. S1–2). A comparison between this study and previous studies based on the abundance of elements is shown in Fig. S3. Table S8 in the Supplementary Material shows that S, Ca, Na, K, Al, Mg, and Fe are the most abundant elements in the cooking profiles
3.1. Chemical profiles of PM2.5 from residential Chinese cooking 3.1.1. Species abundance in PM2.5 emitted from various cooking methods Fig. 1 shows the species mass fractions in PM2.5 emitted as a result of various Chinese cooking methods in a residential kitchen. In general, the three oil-based cooking methods share a similar chemical profile, where OC is the dominant proportion (72%–74%) in PM2.5. This value was higher than the OC fraction (63%) measured in the study by Zhang et al. [29]. The underestimation of organic compounds (organic carbon vs. organic matter) in Zhang's study [29] was possibly attributed to the assumption of a negligible contribution from the existing PM2.5 background in the apartment. The percentage of EC and measured elements from the oil-based cooking methods was 1.0%–1.3% and 1.0%–1.9%, respectively, in agreement with the results of Wen and Hu [40] (1%–2% 625
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et al. [29].
obtained for this study and their mass fractions account for approximately 98% of the measured elements, regardless of the cooking method, This is because the crustal materials make up a large portion of the total suspended particles [42]. The relatively high content of Ca, Na, Fe, Mg, and Al was in accordance with the results of See and Balasubramanian [28], Li, et al. [43], Wang, et al. [38], and Zhang et al. [29], however, S was the most dominant element in the result obtained by Wang et al. [38] and in this study. Although trace elements (As, Cd, Co, Cr, Cu, Mn, Ni, Pb, V, and Zn) were far less abundant in the samples, they are known to be more harmful to human health. In this study, Pb, Mn, and Cr were dominant among the heavy metals and they may pose a carcinogenic or a non-carcinogenic risk [17]. Cr was associated with the meat cooking process and could be leached into the air from stainless steel woks under high temperatures [28]. Trace metals, such as Pb and Mn could be emitted from cooking oil, especially peanut oil and canola oil, which have been utilized in our previous studies [44,45]. In addition, Mn could also be contained in the mushrooms used in our pan-frying and deep-frying. Na was likely derived from the salt used and K is associated with oil-based meat cooking [29,38]. Fe, Cr, Ni, and Cu were likely emitted from the stainless steel woks used for cooking when they were subjected to high cooking temperatures [28,42]. In addition, the emission rates of Cu and Zn during oil-based cooking were higher than those during water-based cooking, thus it is likely that they were released from the cooking oils (Fig. 2) [42]. Oil-based cooking, especially stir-frying, generates more emissions than water-based cooking (Fig. 2) and large emissions lead to high concentrations of elements (Fig. S2).
3.3.2. Percentage of PAHs with different aromatic ring numbers The distribution of PAHs with varying aromatic ring numbers was different for the various cooking methods (Fig. 3). Two-ring PAHs (Nap) predominated the total detected PM2.5-bound PAHs emitted from the oil-based cooking methods (above 40%), while the most abundant fraction for steaming and boiling was the three-ring (Acy, Ace, Flu, Phe, and Ant) and four-ring (Flt, Pyr, BaA, and Chr) PAHs, respectively. The percentage of six-ring PAHs (IND and BghiP) was the largest for waterbased (16%–24%) and the smallest for oil-based (6%–13%) cooking methods. The distribution pattern of the five-ring PAHs (BbF, BkF, BaP, and DBA) associated with the different cooking methods was similar to that of the six-ring PAHs. In this study, low molecular weight PAHs (LM-PAHs, containing two-to three-ring PAHs) from oil-based cooking methods accounted for over 50% of the total PM2.5-bound PAHs (53%, 64%, and 73% for stir-, pan-, and deep-frying, respectively), while the corresponding proportions from water-based cooking methods were approximately 35%. The amount of LM-PAHs emitted from deep-frying was higher than that from stir-frying and pan-frying, because high molecular weight PAHs (HM-PAHs, containing five-to seven-ring PAHs) can be decomposed or destroyed at high cooking temperatures during deep-frying, which facilitates LM-PAH formation [46]. Accordingly, the amount of HM-PAHs from deep-frying was the lowest (11%) of the three oil-based (14% for pan-frying and 20% for stir-frying) cooking methods. The most abundant component in PAHs due to boiling was the middle molecular weight PAHs (MM-PAHs, containing four-ring PAHs), accounting for 39%. The percentage of HM-PAHs in the total PAHs was the largest for steaming (39%). The percentage of carcinogenic PAHs (C-PAHs, including BaA, Chr, BbF, IND, DBA, and BaP) from stir-, pan-, and deepfrying was 20%, 13%, and 15% respectively, of the total detected PAHs in PM2.5.
3.3. PAHs 3.3.1. Characterization of PAHs emitted from different cooking methods Table 1 lists the emission rates of PM2.5-bound PAHs due to various Chinese cooking styles. The total emission rates of 16 PAHs in PM2.5 from stir-frying, pan-frying, deep-frying, steaming, and boiling were 180.09–270.59, 240.51–241.61, 79.87–117.59, 37.86, and 8.83 ng/ min, respectively, and the concentrations were 58.90–92.14, 41.23–72.57, 34.57–50.89, 29.54, and 8.00 ng/m3. Detailed information on PAH abundance and concentrations is provided in Tables S11–S12. The emission rates of Nap were the highest for all three oilbased cooking methods in this study, while Phe and Chr emissions were the highest for steaming and boiling. In general, Nap, Pyr, Chr, and BghiP were the main PAHs released during oil-based cooking activities, whereas Chr and Phe were the predominant PAHs in the emissions from water-based cooking activities. Pyr and Phe were also reported to be abundant in PM2.5-bound PAHs from Chinese cooking in investigations performed by He et al. [1], Zhao, et al. [21], Saito, et al. [4] and Zhang
3.4. OC & EC The OC emission rates were 1826.95 μg/min −2006.41 μg/min, 1164.46–1259.61 μg/min, 252.82 μg/min −368.84 μg/min, 36.12 μg/ min, and 27.87 μg/min for stir-frying, pan-frying, deep-frying, steaming, and boiling, respectively, while the corresponding EC emission rates were 24.55 μg/min −34.38 μg/min, 15.45 μg/min −16.59 μg/min, 3.48 μg/min −8.12 μg/min, 2.02 μg/min, and 3.95 μg/min. The mass fraction of the total carbon (TC) in PM2.5 varied from 46% to 75% for the different cooking methods, implying that carbonaceous particles were the dominant species in the PM2.5 emitted from cooking. No significant variance in OC or EC was observed for the
Fig. 2. Emission rates of elements in PM2.5 associated various Chinese cooking styles (the results for P element were below the field blank and are not shown in the figure). 626
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Table 1 Emission rates of PM2.5-bound PAHs due to various Chinese cooking methods. (ng/min)
Stir-frying
Pan-frying
Deep-frying
Steaminga
Boilinga
Nap Acy Ace Flu Phe Ant Flt Pyr BaA Chr BbF BkF BaP IND DBA BghiP Total
69.38–115.54 3.08–3.42 1.41–1.75 3.21–4.07 12.89–17.25 2.58–3.80 19.28–32.66 27.00–41.18 4.78–8.48 10.96–19.20 8.76–10.28 3.61–5.47 10.08–14.16 14.32–17.48 N.D. 13.60–16.40 180.09–270.59
131.37–152.23 2.21–2.43 1.32–1.86 2.26–2.70 0.20–3.54 7.83–7.89 11.86–12.84 21.56–24.34 4.49–5.39 13.91–15.57 N.D. 3.82–4.86 7.55–8.25 2.78–3.20 0.36–0.46 13.76–22.54 240.51–241.61
55.50–83.24 0.79–0.95 0.56–0.80 0.42–0.52 N.D. N.D. 0.33–2.53 1.86–5.74 1.44–1.94 7.59–9.85 N.D. 1.43–2.03 2.90–3.16 1.12–2.00 N.D. 2.39–8.35 79.87–117.59
0.66 N.D. 0.41 N.D. 10.77 0.95 N.D. N.D. 2.76 7.40 5.18 0.74 N.D. 4.18 N.D. 4.81 37.86
0.95 N.D. 0.43 N.D. 4.05 0.54 N.D. N.D. 1.56 4.99 1.16 0.52 N.D. 0.92 N.D. 1.61 8.83
N.D. means the results were below the detection limit and/or below the limit of the field blank. a The experiments involving steaming and boiling were conducted once due to the relatively low emission rates of PM2.5.
PM2.5 samples in various restaurants that use different cooking styles, including mixed cooking methods, which can be different from residential cooking. Zhang et al. [29] conducted measurements for different oil types in a domestic kitchen. The cooking method was the most influential factor for determining the emission rates of PM2.5 in our previous study [30], which suggests that experiments that consider the cooking method as opposed to other factors might be more reasonable. See and Balasubramanian [28] investigated five different types of commonly used cooking methods that were the same as those used in this study. In their investigation, tofu was chosen as the main ingredient. However, a simple cooking process with only one raw material may not be representative of the diversity of Chinese cooking methods. In this study, we designed orthogonal experiments to select the most representative Chinese cooking style for home cooking. Furthermore, we collected PM2.5 samples distinguished only by the cooking method to identify the variations in emissions and concentrations caused by this most influential factor. Previous research mainly focused on the concentrations of the PM2.5-bound species; however, concentration levels can depend on a variety of factors such as the scale and the ventilation conditions of the kitchen. Concentrations may also depend on control interventions; e.g., turning on the fan of the range hood. Therefore, emission rates are better indicators of the inherent characteristics of the PM2.5 chemical composition, as described in Chen et al. [30] Species concentrations can then be determined under different scenarios for corresponding emission rates, with application to the study of PM2.5 control strategies, as well as in the assessment of health risks. In addition, emission profiles of diverse cooking methods for residential cooking may enhance the database of cooking emissions inventories, which can improve the results of source apportionment studies. The concentration profile of the PM2.5-bound species measured in this study can be applied to source identification of various cooking methods by calculating the source signature ratios and diagnostic ratios. We can also use the measured elemental concentrations to analyze the enrichment factors of the elements. The analysis of source identification and elemental enrichment factors is described in the Supplementary Material (Page S11eS14, Fig. S4, Tables S13–14). In this study, the enrichment factors varied according to the cooking method; nevertheless, Sb was determined to be the most enriched element regardless of the cooking method. In summary, residential Chinese cooking was associated with the emissions of Ca, Cr, Cu, Zn, As, Cd, Pb, and Sb, while Na and K could have originated from oil-based cooking due to the use of large amounts of salt. Na, OC, Ni, Cr, and Ni had the highest signature ratios for stir-frying, pan-frying, deep-frying, steaming, and boiling, respectively. Nap had the highest
Fig. 3. Mass compositions of PAHs with different numbers of aromatic rings.
oil-based cooking methods, while there was a significant difference between the oil-based and water-based cooking methods. Steaming generated the lowest OC proportion (44%) while boiling produced the highest EC fraction (8%) in the PM2.5. Oil-based cooking emitted more OC than water-based cooking, because of the long-chain hydrocarbons in cooking oil [28]. The OC/EC ratios for stir-frying, pan-frying, deepfrying, steaming, and boiling were 65.2, 75.5, 57.0, 17.9, and 7.0, respectively. These values are larger than the background level (5.4) and these ratios can be used to identify the sources of PM2.5 in source apportionment studies [43]. Overall, the measured OC/EC ratios due to cooking were much higher than those from other sources (0.8–2.2 from vehicle emissions [43]). The OC/EC ratios for oil-based cooking and boiling in this study were consistent with the results reported by Li et al. [43]. However, differences in the OC/EC ratios between oil-based and water-based cooking methods were observed, which can be attributed to the chemism between oils and food materials during high-temperature cooking (the peak oil temperatures during oil-based cooking could approach 110 °C-180 °C according to our measurement). 4. Discussion The chemical characteristics of cooking-related fine particles has been a popular topic in recent years due to the potential carcinogenic and non-carcinogenic risks posed by some organic and elemental components. He et al. [1] Wang et al. [38] and Li et al. [43] collected 627
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References
signature ratios for PM2.5-bound PAHs emitted from the three oil-based cooking methods, while Phe had the highest ratios for the two waterbased cooking methods. This implies that Nap and Phe can be used as organic markers to distinguish between cooking emissions and other non-cooking sources. This study has a few limitations. The PM2.5 emission rates were multiplied by the mass fractions of the PAH species to obtain the emission rates of the PM2.5-bound PAHs. However, the particle/gas partition coefficients of PAHs are associated with the corresponding saturation vapor pressure which is influenced by the environmental temperature [47–49]. This may cause variations in the partition between particle- and gas-phase PAHs during cooking. Therefore, the emission rates of PM2.5-bound PAHs calculated with the average abundance spanning the entire cooking process might not represent the real transient emission rates during cooking. However, the impact was possibly not apparent considering that the increase in the measured ambient temperature was smaller than 5 °C for oil-based cooking and 8 °C for water-based cooking [49].
[1] L.Y. He, M. Hu, X.F. Huang, B.D. Yu, Y.H. Zhang, D.Q. Liu, Measurement of emissions of fine particulate organic matter from Chinese cooking, Atmos. Environ. 38 (38) (2004) 6557–6564. [2] S.W. See, R. Balasubramanian, Risk assessment of exposure to indoor aerosols associated with Chinese cooking, Environ. Res. 102 (2) (2006) 197–204. [3] K.L. Abdullahi, J.M. Delgado-Saborit, R.M. Harrison, Emissions and indoor concentrations of particulate matter and its specific chemical components from cooking: a review, Atmos. Environ. 71 (2013) 260–294. [4] E. Saito, N. Tanaka, A. Miyazaki, M. Tsuzaki, Concentration and particle size distribution of polycyclic aromatic hydrocarbons formed by thermal cooking, Food Chem. 153 (2014) 285–291. [5] Y.J. Zhao, B. Zhao, Emissions of air pollutants from Chinese cooking: a literature review, Build. Simul. 11 (5) (2018) 977–995. [6] P. Thomson, T. Robinson, I.J. Robbe, Lung cancer and indoor air pollution arising from Chinese-style cooking among nonsmoking women living in Shanghai, China, Epidemiology 11 (4) (2000) 481–482. [7] H.S. Hung, W.J. Wu, Y.W. Cheng, T.C. Wu, K.L. Chang, H. Lee, Association of cooking oil fumes exposure with lung cancer: involvement of inhibitor of apoptosis proteins in cell survival and proliferation in vitro, Mutat. Res. Genet. Toxicol. Environ. Mutagen 628 (2) (2007) 107–116. [8] X. Wang, Y. Zhang, X. Cheng, Lung cancer risk assessment of cooking oil fume for Chinese nonsmoking women, WIT Trans. Built Environ. 145 (2014) 243–250. [9] L.Y. He, M. Hu, L. Wang, X.F. Huang, Y.H. Zhang, Characterization of fine organic particulate matter from Chinese cooking, J. Environ. Sci. 16 (4) (2004) 570–575. [10] IARC Working Group on the Evaluation of Carcinogenic Risks to Humans, Household Use of Solid Fuels and High-temperature Frying IN IARC Monographs on the Evaluation of Carcinogenic Risks to Humans IARC Monographs on the Evaluation of Carcinogenic Risks to Humans, International Agency for Research on Cancer, Lyon, France, 2010. [11] L.Z. Zhu, H. Lu, S.G. Chen, T. Amagai, Pollution level, phase distribution and source analysis of polycyclic aromatic hydrocarbons in residential air in Hangzhou, China, J. Hazard Mater. 162 (2–3) (2009) 1165–1170. [12] Y. Chen, K.F. Ho, S.S.H. Ho, W.K. Ho, S.C. Lee, J.Z. Yu, E.H.L. Sit, Gaseous and particulate polycyclic aromatic hydrocarbons (PAHs) emissions from commercial restaurants in Hong Kong, J. Environ. Monit. 9 (12) (2007) 1402–1409. [13] G.C. Fang, Y.L. Huang, J.H. Huang, Study of atmospheric metallic elements pollution in Asia during 2000-2007, J. Hazard Mater. 180 (1–3) (2010) 115–121. [14] P.H. Li, S.F. Kong, C.M. Geng, B. Han, B. Lu, R.F. Sun, R.J. Zhao, Z.P. Bai, Assessing the hazardous risks of vehicle inspection workers' exposure to particulate heavy metals in their work places, Aerosol Air Qual. Res. 13 (1) (2013) 255–265. [15] P. Gemenetzis, P. Moussas, A. Arditsoglou, C. Samara, Mass concentration and elemental composition of indoor PM2.5 and PM10 in university rooms in Thessaloniki, northern Greece, Atmos. Environ. 40 (17) (2006) 3195–3206. [16] S.L. Lu, Z.K. Yao, X.H. Chen, M.H. Wu, G.Y. Sheng, J.M. Fu, D. Paul, The relationship between physicochemical characterization and the potential toxicity of fine particulates (PM2.5) in Shanghai atmosphere, Atmos. Environ. 42 (31) (2008) 7205–7214. [17] IARC Working Group on the Evaluation of Carcinogenic Risks to Humans, A Review of Human Carcinogens: Arsenic, Metals, Fibres, and Dusts IN IARC Monographs on the Evaluation of Carcinogenic Risks to Humans IARC Monographs on the Evaluation of Carcinogenic Risks to Humans, International Agency for Research on Cancer, Lyon, France, 2012. [18] L. Lin, M.L. Lee, D.J. Eatough, Review of recent advances in detection of organic markers in fine particulate matter and their use for source apportionment, J. Air Waste Manag. Assoc. 60 (1) (2010) 3–25. [19] C.T. Li, Y.C. Lin, W.J. Lee, P.J. Tsai, Emission of polycyclic aromatic hydrocarbons and their carcinogenic potencies from cooking sources to the urban atmosphere, Environ. Health Perspect. 111 (4) (2003) 483–487. [20] S.W. See, S. Karthikeyana, R. Balasubramanian, Health risk assessment of occupational exposure to particulate-phase polycyclic aromatic hydrocarbons associated with Chinese, Malay and Indian cooking, J. Environ. Monit. 8 (3) (2006) 369–376. [21] Y.L. Zhao, M. Hu, S. Slanina, Y.H. Zhang, Chemical compositions of fine particulate organic matter emitted from Chinese cooking, Environ. Sci. Technol. 41 (1) (2007) 99–105. [22] C.H. Pan, C.C. Chan, K.Y. Wu, Effects on Chinese restaurant workers of exposure to cooking oil fumes: a cautionary note on urinary 8-hydroxy-2 '-Deoxyguanosine, Cancer Epidemiol. Biomark. Prev. 17 (12) (2008) 3351–3357. [23] P. Zhao, K.P. Yu, C.C. Lin, Risk assessment of inhalation exposure to polycyclic aromatic hydrocarbons in Taiwanese workers at night markets, Int. Arch. Occup. Environ. Health 84 (3) (2011) 231–237. [24] J.W. Chen, S.L. Wang, D.P.H. Hsieh, H.H. Yang, H.L. Lee, Carcinogenic potencies of polycyclic aromatic hydrocarbons for back-door neighbors of restaurants with cooking emissions, Sci. Total Environ. 417 (2012) 68–75. [25] L.Z. Zhu, J. Wang, Sources and patterns of polycyclic aromatic hydrocarbons pollution in kitchen air, China, Chemosphere 50 (5) (2003) 611–618. [26] J. Gao, Y.T. Jian, C.S. Cao, L. Chen, X. Zhang, Indoor emission, dispersion and exposure of total particle-bound polycyclic aromatic hydrocarbons during cooking, Atmos. Environ. 120 (2015) 191–199. [27] X.Y. Zhao, Q.H. Hu, X.M. Wang, X. Ding, Q.F. He, Z. Zhang, R.Q. Shen, S.J. Lu, T.Y. Liu, X.X. Fu, L.G. Chen, Composition profiles of organic aerosols from Chinese residential cooking: case study in urban Guangzhou, south China, J. Atmos. Chem. 72 (1) (2015) 1–18. [28] S.W. See, R. Balasubramanian, Chemical characteristics of fine particles emitted
5. Conclusions In this study, PM2.5 source profiles were built and the emission rates of PM2.5 components were determined during typical Chinese cooking in a residential kitchen. The CD values indicated discrepancies in the chemical profile of the PM2.5 between the various cooking methods. The results showed that OC was the dominant component of the fine particles. In this case, the emission rates ranged from 27.87 μg/min to 1916.68 μg/min while the emission rates of EC ranged from 2.02 μg/ min to 29.47 μg/min. The emission rates of the measured elements varied within a wide range between 0.01 ng/min and 9.57 μg/min and S, Ca, Na, K, Al, Mg, Fe were the most abundant elements in the cooking profiles regardless of the cooking method, accounting for a mass fraction of approximately 98% of the measured elements. Oil-based cooking generated more element and OC emissions than water-based cooking. The total emission rates of the 16 PAHs in PM2.5 ranged from between 8.83 ng/min and 241.06 ng/min and Nap, Pyr, Chr, BghiP, and Phe were the main PAHs generated during residential Chinese cooking. The percentage of carcinogenic PAHs (including BaA, Chr, BbF, IND, DBA, and BaP) from stir-frying (20%) was the highest among the three oilbased cooking methods. The signature ratios of the measured chemical components in PM2.5 imply that Nap and Phe could be used as organic markers to distinguish between cooking emissions and that from other non-cooking sources. The measured results for species emission rates could assist in the determination of concentrations of PM2.5-bound chemicals under various scenarios. This could provide a basis for indoor air quality control as well as health risk assessment. In addition, the measured chemical profiles from cooking could also be applied to PM2.5 source apportionment studies. Competing financial interests The authors have declared that they have no actual or potential competing financial interests. Acknowledgement This work was financially supported by the National Key Project of the Ministry of Science and Technology, China on “Green Buildings and Building Industrialization” [grant number 2016YFC0700500]; and the Innovative Research Groups of the National Natural Science Foundation of China [grant number 51521005]. Appendix A. Supplementary data Supplementary data to this article can be found online at https:// doi.org/10.1016/j.buildenv.2018.12.060. 628
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Y. Zhao et al.
45 (30) (2011) 5351–5365. [40] M.T. Wen, M. Hu, Physical and chemical characteristics of fine particles emitted from cooking emissions and its contribution to particulate organic matter in Beijing (in Chinese), Huanjing Kexue 28 (11) (2007) 2620–2625. [41] B. Han, S.F. Kong, Z.P. Bai, G. Du, T. Bi, X. Li, G.L. Shi, Y. Hu, Characterization of elemental species in PM2.5 samples collected in four cities of northeast China, Water Air Soil Pollut. 209 (1–4) (2010) 15–28. [42] S. Taner, B. Pekey, H. Pekey, Fine particulate matter in the indoor air of barbeque restaurants: elemental compositions, sources and health risks, Sci. Total Environ. 454 (2013) 79–87. [43] Y.C. Li, M. Shu, S.S.H. Ho, C. Wang, J.J. Cao, G.H. Wang, X.X. Wang, K. Wang, X.Q. Zhao, Characteristics of PM2.5 emitted from different cooking activities in China, Atmos. Res. 166 (2015) 83–91. [44] Y.L. Liu, X.Y. Wu, G.Q. Xiang, Determination of lead in oil seeds and edible oil (in Chinese), China Oils Fats 36 (8) (2011) 74–77. [45] L.L. Wang, L. Lin, Y.H. Chen, Determination of lead, arsenic, manganese, cadmium, chromium, copper and other elements in edible oil using direct sampling by ICP-MS (in Chinese), Environ. Chem. 30 (2) (2011) 571–573. [46] Y.-C. Li, J.-Q. Qiu, M. Shu, S.S.H. Ho, J.-J. Cao, G.-H. Wang, X.-X. Wang, X.-Q. Zhao, Characteristics of polycyclic aromatic hydrocarbons in PM2.5 emitted from different cooking activities in China, Environ. Sci. Pollut. Control Ser. 25 (5) (2018) 4750–4760. [47] C.Z. Zhou, X.H. Zhu, Z. Wang, X.D. Ma, J.P. Chen, Y.W. Ni, W. Wang, J. Mu, X.X. Li, Gas-particle partitioning of PAHs in the urban air of Dalian, China: measurements and assessments, Polycycl. Aromat. Comp. 33 (1) (2013) 31–51. [48] W.J. Wei, C. Mandin, O. Blanchard, F. Mercier, M. Pelletier, B. Le Bot, P. Glorennec, O. Ramalho, Distributions of the particle/gas and dust/gas partition coefficients for seventy-two semi-volatile organic compounds in indoor environment, Chemosphere 153 (2016) 212–219. [49] B. Zhou, Model Analysis on Population Inhalation Exposure to Polycyclic Aromatic Hydrocarbons and Associated Lung Cancer Risk (In Chinese), Department of Building Science, 2013 Master thesis.
from different gas cooking methods, Atmos. Environ. 42 (39) (2008) 8852–8862. [29] N. Zhang, B. Han, F. He, J. Xu, R.J. Zhao, Y.J. Zhang, Z.P. Bai, Chemical characteristic of PM2.5 emission and inhalational carcinogenic risk of domestic Chinese cooking, Environ. Pollut. 227 (2017) 24–30. [30] C. Chen, Y.J. Zhao, B. Zhao, Emission rates of multiple air pollutants generated from Chinese residential cooking, Environ. Sci. Technol. 52 (3) (2018) 1081–1087. [31] C.L. Wu, C.Y.H. Chao, G.N. Sze-To, M.P. Wan, T.C. Chan, Ultrafine particle emissions from cigarette smouldering, incense burning, vacuum cleaner motor operation and cooking, Indoor Built Environ. 21 (6) (2012) 782–796. [32] Q.F. Zhang, R.H. Gangupomu, D. Ramirez, Y.F. Zhu, Measurement of ultrafine particles and other air pollutants emitted by cooking activities, Int. J. Environ. Res. Publ. Health 7 (4) (2010) 1744–1759. [33] W.M. To, L.L. Yeung, Effect of fuels on cooking fume emissions, Indoor Built Environ. 20 (5) (2011) 555–563. [34] J. Gao, C.S. Cao, L. Wang, T.H. Song, X. Zhou, J. Yang, X. Zhang, Determination of size-dependent source emission rate of cooking-generated aerosol particles at the oil-heating stage in an experimental kitchen, Aerosol Air Qual. Res. 13 (2) (2013) 488–496. [35] X. Duan, Y. Jiang, B. Wang, X. Zhao, G. Shen, S. Cao, N. Huang, Y. Qian, Y. Chen, L. Wang, Household fuel use for cooking and heating in China: results from the first Chinese environmental exposure-related human activity patterns survey (CEERHAPS), Appl. Energy 136 (1) (2014) 692–703. [36] C.R. He, L.D. Morawska, J. Hitchins, D. Gilbert, Contribution from indoor sources to particle number and mass concentrations in residential houses, Atmos. Environ. 38 (21) (2004) 3405–3415. [37] Z.Q. Zhang, S.K. Friedlander, A comparative study of chemical databases for fine particle Chinese, Environ. Sci. Technol. 34 (22) (2000) 4687–4694. [38] G. Wang, S.Y. Cheng, W. Wei, W. Wen, X.Q. Wang, S. Yao, Chemical characteristics of fine particles emitted from different Chinese cooking styles, Aerosol Air Qual. Res. 15 (6) (2015) 2357–2366. [39] S.F. Kong, Y.Q. Ji, B. Lu, L. Chen, B. Han, Z.Y. Li, Z.P. Bai, Characterization of PM10 source profiles for fugitive dust in Fushun-a city famous for coal, Atmos. Environ.
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