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Emission Rates of Multiple Air Pollutants Generated from Chinese Residential Cooking Chen Chen, Yuejing Zhao, and Bin Zhao Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.7b05600 • Publication Date (Web): 05 Jan 2018 Downloaded from http://pubs.acs.org on January 5, 2018
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Emission Rates of Multiple Air Pollutants Generated
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from Chinese Residential Cooking
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Chen Chen†,§, Yuejing Zhao†,§, Bin Zhao*,†,‡
4
†
5
China.
6
‡
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Beijing, 100084, China.
Department of Building Science, School of Architecture, Tsinghua University, Beijing, 100084,
Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University,
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KEYWORDS: Indoor air quality; particulate matter; volatile organic compounds; formaldehyde; range hood
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ABSTRACT
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Household air pollution generated from cooking is severe, especially for Chinese-style cooking.
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We measured the emission rates of multiple air pollutants including fine particles (PM2.5),
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ultrafine particles (UFPs), and volatile organic compounds (VOCs, including formaldehyde,
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benzene, and toluene) that were generated from typical Chinese cooking in a residential kitchen.
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The experiment was designed through five-factor and five-level orthogonal testing. The five key
17
factors were cooking method, ingredient weight, type of meat, type of oil, and meat/vegetable
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ratio. The measured emission rates (mean value ± standard deviation) of PM2.5, UFPs,
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formaldehyde, total volatile organic compounds (TVOCs), benzene, and toluene were 2.056 ±
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3.034 mg/min, 9.102 ± 6.909 × 1012 #/min, 1.273 ± 0.736 mg/min, 1.349 ± 1.376 mg/min, 0.074
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± 0.039 mg/min, and 0.004 ± 0.004 mg/min. Cooking method was the most influencing factor for
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the emission rates of PM2.5, UFPs, formaldehyde, TVOCs, and benzene, but not for toluene.
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Meanwhile, the emission rate of PM2.5 was also significantly influenced by ingredient weight,
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type of meat, and meat/vegetable ratio. Exhausting the range hood decreased the emission rates
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by approximately 58%, with a corresponding air change rate of 21.38 /h for the kitchen room.
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INTRODUCTION
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Cooking can generate high levels of multiple pernicious air pollutants including fine particles
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(PM2.5; particulate matter with aerodynamic diameter less than 2.5 µm)1, ultrafine particles
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(UFPs; particulate matter with diameter less than 0.1 µm)1 and other volatile organic compounds
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(VOCs)2, and polycyclic aromatic hydrocarbons (PAHs)3. Epidemiologic evidence confirmed the
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association between exposure to cooking fumes and lung cancer risk, especially in poor
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ventilation situations4-8. Considering the fact that people spend 60-70% of their time in
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residences9-12 and cooking is a significant source of indoor air pollutants13, assessing human
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exposure to residential cooking fumes is important. Compared with Western cooking, household
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air pollution generated from Chinese cooking is much more severe, with more air pollutants
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produced owing to the special cooking style14. The majority of Chinese women have cooked
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daily for years15, but over half of Chinese residential kitchens are poorly ventilated15-16, leading
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to long-term exposure to indoor high-concentration cooking-generated pollutants, and thus
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resulting in adverse health effects in China.
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Referring to the existing literature, we found the average or peak concentrations are frequently
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constructed as a direct parameter of Chinese cooking emissions in most of the previous studies3,
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14, 17-20
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conditions. A few previous studies on Chinese cooking (most are for commercial restaurants)
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present the emission rate to the atmosphere21-24, which is different from the emission rate to the
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indoor environment discussed in this study. The former is influenced by the exhaust air rate and
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the cooking procedures simultaneously and cannot be used to estimate the concentration levels of
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indoor pollutants. The previous emission rates of pollutants generated from Chinese cooking for
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the indoor environment are based on oil heating or a limited number of specific dishes; hence,
; however, they are always influenced by various durations, room volumes, and ventilation
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the results only focus on particle emissions but fail to consider gaseous pollutants25-30. Thus,
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detailed information regarding the emission rate of multiple pollutants generated from Chinese
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cooking, which is the base for ventilation or other controlling measures design, is still lacking.
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Therefore, it is of significance to study the emission rate of air pollutants generated via Chinese
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cooking, which has high potential use for population exposure assessment to air pollution and
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ventilation design in residential kitchens.
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We determined the emission rates of PM2.5, UFP, and VOCs based on orthogonal test methods
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considering five key factors, i.e., cooking method, ingredient weight, type of meat,
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meat/vegetable ratio, and type of oil. The removal efficiency of the range hood is also discussed.
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MATERIALS AND METHODS
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Survey of factors influencing Chinese cooking
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It has been summarized that emissions of air pollutants during cooking depend strongly on the
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ingredients, type of oil, type of stove, cooking duration and oil temperature3, 20, 26. Oil weight,
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cooking duration and oil temperature are always influenced by the cooking methods. In China,
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most household fuel used for cooking is gas31. Therefore, five key factors, i.e., cooking method,
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the weight of ingredients (meat and vegetables), type of meat, ratio of meat to vegetables, and
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type of oil, were taken into consideration in this study.
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We conducted an online survey of 309 families to determine common cooking behaviors in
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China. Detailed results of such are listed in the Supporting Information (Tables S1-S5). The
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majority of Chinese families use natural gas for cooking (Table S1). The five most popular
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cooking methods, ingredient weights, types of meat, and types of oil were incorporated based on
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the survey (Tables S2-S5). The meat/vegetable ratios ranged from 0.00 (only vegetables) to 1.00
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(only meat) in intervals of 0.25. The survey showed that Chinese people prefer to stir-fry, boil,
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steam, stew, pan-fry, and deep-fry at home, 84.5% of which stir-fry most frequently. However,
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different from the other cooking methods, less than 10% of people wait in the kitchen while
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stewing, thus the other five most prevalent cooking methods, i.e., stir-frying, boiling, steaming,
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pan-frying, and deep-frying, were chosen for this study. 98% Chinese families cook for no more
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than five persons, thus ingredient weights used in this study were for 1-5 persons. According to
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the professional cook who performed the cooking in the experiments, the suggestive value of
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total ingredient weight per person is 120 g. The survey showed that 78.5% Chinese people prefer
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pork for cooking while another 20.8% people prefer beef, mutton, fish or chicken. Besides,
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91.9% Chinese people use peanut oil, blend oil, canola oil, sunflower oil or soybean oil during
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cooking.
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Orthogonal test
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We designed an orthogonal test to cover the typical Chinese cooking styles considering the five
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key factors above and a dummy blank factor simultaneously. The blank factor was set for error
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estimation. The L25 (56) orthogonal table was designed with six factors (cooking method,
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ingredient weight, type of meat, type of oil, meat/vegetable ratio, and blank), as shown in the
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Supporting Information (Table S6), using SPSS 20.0 (IBM Corp., Armonk, NY, USA), each
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with five levels. The 25 rows correspond to 25 experiments. The cooking methods included stir-
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frying, boiling, steaming, pan-frying, and deep-frying. The ingredient weights were for one
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person to five persons. Pork, beef, mutton, fish and chicken were selected as the types of meat
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used in this study. The types of oil were peanut oil, blend oil, canola oil, sunflower oil and
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soybean oil. Meat/vegetable ratios were 0.00, 0.25, 0.50, 0.75 and 1.00.
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Determination of pollutant emission rates
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1) Emission rate of particulate matter
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Assuming that air is well mixed in the kitchen and the ambient concentration is steady, the mass
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balance equation for PM2.5 and UFPs can be expressed as:
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dCin, p ( t ) dt
= aPCout − λCin, p ( t ) +
Sp V
(1)
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where , is the real-time indoor concentration of particulate matter at the measuring
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moment , is the air change rate, is the penetration factor of outdoor particles entering the
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indoor environment through the building envelope, is the outdoor concentration of
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particulate matter, is the total removal rate due to coagulation, deposition and air change rate in
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the kitchen, is the emission rate of particulate matter, and is the volume of the kitchen.
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To solve equation (1), we determined the particle concentration at the start time , , , as
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the steady-state indoor particle concentration before measurement: Cin , p ( t0 ) =
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reasonable because we waited for a specific long amount of time (at least 22 minutes) before
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each measurement. Then, the solution of indoor PM2.5 or UFP concentration for equation (1) is:
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Cin , p ( t ) = −
Sp
λV
e − λ∆t + Cin , p ( t0 ) +
Sp
λV
aPCout
λ
, which is
(2)
where ∆ is the duration of cooking, which is equal to − .
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The range hood was off and the windows and door were closed during measurements, leading to
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a small value of air change rate , which is helpful for improving the fitting accuracy for . The
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air change rate was measured via the CO2-decay method. The total removal rate λ was
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determined by measuring particle concentration decay after the cooking finished32.
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With the results of air change rate , the total removal rate λ, concentration , , and room
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volume , the nonlinear fitting of the indoor particle concentration increasing curves based on
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equation (2) was conducted to obtain the emission rate with Origin 9.0.0 (OriginLab Corp.,
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Northampton, MA, USA).
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2) Emission rate of gaseous pollutants
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For gaseous pollutants, the real-time concentration derived from the mass balance equation is: S S Cin , g ( t ) = Cin , g ( t0 ) − g e − a∆t + g aV aV
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(3)
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where , is the real-time indoor concentration of gaseous pollutants at the measuring
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moment .
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The measured durations for formaldehyde and VOCs limit the measured frequencies, especially
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for a few minutes of stir-frying, pan-frying, and deep-frying. Therefore, formaldehyde and VOC
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concentrations were measured twice for each experiment. The first time was to measure the
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indoor gaseous pollutant concentration , at the start time ; the second time was to
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measure the average indoor gaseous concentration , during cooking (from to ), which can
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be expressed as:
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Cin , g
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Thus, the emission rate can be calculated as:
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Sg =
a 2V ∆t e − a∆t − 1 C Cin , g ( t0 ) + in , g − a∆t a ∆t + e −1 a ∆t
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(4)
(5)
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3) Removal performance of the range hood
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The range hood ran during the cooking period for most cases in real-life scenarios. To check the
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removal effect of the range hood for the cooking-generated pollutants, we also measured the
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emission rates of air pollutants when the range hood was on.
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The removal efficiency of the range hood is defined as:
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η = 1 −
S hood S
× 100%
(6)
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where is the emission rate of air pollutants generated from Chinese cooking measured with the
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range hood off, and is the emission rate measured with the range hood on, the detailed
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determination of which is shown in Supporting Information “DETERMINATION OF
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EMISSION RATES WITH THE RANGE HOOD ON”. The windows and the door were closed
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when the range hood was turned on to ensure the indoor air well mixed.
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Instrumentation and measurement
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A residential kitchen ( = 10.88 m! ) located in Beijing was chosen for measurements from
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April 27, 2017, to September 23, 2017. The layout of the kitchen is shown in Figure 1 and Figure
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S1-(a). Two fans were used to mix the indoor air. The measurement at different locations in the
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kitchen showed that the average relative differences in the PM concentration is 14%, which
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indicates the indoor air was mixed well (details shown in Figure S1-(b)).
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Figure 1. Layout of the residential kitchen (three-dimensional view).
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One laser photometer equipped with a 2.5 µm impactor (AM510; TSI Inc., Shoreview, MN,
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USA) was used to monitor the real-time mass concentrations of PM2.5. A pump (LP-20; A.P.
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Buck Inc., Orlando, FL, USA) and a cutting head (PEM, Model 200, PEM-10-2.5; MSP Corp.,
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Shoreview, MN, USA) were used to collect indoor PM2.5 at a flow rate of 10 L/min during
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cooking. We calibrated the flow rate using a soap-film calibrator (M-30; A.P. Buck Inc.,
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Orlando, FL, USA) before sampling to ensure it matched the cutting head. The Teflon filters
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were weighed on a microbalance accurate to 0.001 mg before and after sampling. The
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monitoring results of the AM510 were calibrated against the gravimetric measurements. The
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lowest cutoff of an identical condensation particle counter (CPC3007; TSI Inc., Shoreview, MN,
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USA) is 10 nm (in electrical mobility diameter), and a great majority of the particles produced
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are less than 100 nm33, so the CPC3007 was used as a UFP monitor in this study with a dilution
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system (total volume flowrate is 0.7 L/min with a dilution factor of 100; Huifen Corp., Shanghai,
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China).
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Formaldehyde in the air was absorbed into a solution in a glass tube containing 5.0 mL of 50
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µg/mL 3-methyl-2-benzothiazolinone hydrazine (MBTH) using a pump (QC-2; Beijing
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Municipal Institute Labour Protection, Beijing, China) at a flow rate of 300 mL/min. To
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determine the formaldehyde concentrations, we added 0.4 mL of 10 g/L ferric ammonium sulfate
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solution to the sampling tube, shook the tube, and then waited for 15 min. Formaldehyde was
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converted into a blue cationic dye by the MBTH, and its light absorbance was measured via a
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spectrophotometer (UNIC 7200; UNIC apparatus Co. Ltd, Shanghai, China) at 630 nm.
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VOCs in the air was absorbed into a Tenax-TA tube (Markes, UK) using the same pump at a
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flow rate of 300 mL/min. The Tenax-TA tubes were analyzed by a thermo-desorber (Markes,
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UK) and gas chromatograph-mass spectrometer (7890B-5977B; Agilent, Santa Clara, CA, USA).
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Analytes were chromatographically resolved on a capillary column (60.0 m × 200 µm × 1.1 µm
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film thickness, HP-VOC; Agilent). The column temperature program was as follows: 40 ºC for 3
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min, ramped to 160 ºC at 15 ºC/min and maintained for 2 min, and then ramped to 240 ºC at 10
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ºC/min (total time 21 min). The mass spectrometer was operated in total ion scan mode so that
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the entire mass range (35 ≤ m/z ≤ 550) was scanned at a frequency of 1.5 Hz. The thermal
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desorption system was a two-stage desorption unit. The sequence of operations to thermally
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desorb the sample from the sorbent tube and transfer it to the gas chromatograph was: (1)
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primary (tube) desorption (300 ºC, 10 min) and then (2) secondary (trap) desorption (300 ºC, 3
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min). The VOCs toluene, benzene, ethylbenzene, p-xylene, o-xylene, acetic acid butyl ester,
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styrene, and undecane were quantified using standard compounds whereas the results of other
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VOCs were expressed as toluene-equivalent concentration.
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The measuring procedures are shown in the Supporting Information (Figure S2). The pan for
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stir-frying, pan-frying, and deep-frying was heated for 7 minutes before each experiment to
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eliminate the influence of particles generated from heating the organic film on the surface34. The
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residential Chinese cooking procedures were conducted by a professional cook including
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weighing and preparing the ingredients, cooking, and washing the pans (more than 15 times to
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repeat scrubbing), which enforced consistency among the repeated experiments. We repeated the
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measurements for the cooking methods that generated much more pollutants relatively.
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We measured the air volume rate of the range hood by measuring the airflow speed in the pipe
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connecting the range hood with a hot-ball anemometer (FB-1; Tianjianhuayi Corp., Beijing,
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China).
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RESULTS AND DISCUSSION
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Emission rate of PM2.5
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The emission rates of PM2.5 generated from stir-frying, pan-frying, and deep-frying were
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calibrated by factors of 0.805, 0.832 and 0.911, respectively, against the gravimetric
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measurements. The emission rate of PM2.5 generated from Chinese cooking was 2.056 ± 3.034
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mg/min (mean value ± standard deviation, similarly hereinafter). The emission rate of PM2.5
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generated from stir-frying, pan-frying, and deep-frying was 3.352 ± 3.358 mg/min. The emission
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rate of PM2.5 generated from the actual cooking was much larger than the operation of the gas
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stove and the heating of the used pan, which was only 0.398 mg/min.
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As shown in Figure 2, cooking method, ingredient weight, type of meat, and meat/vegetable ratio
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were statistically significant factors effecting emission rates of PM2.5, compared to type of oil.
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The emission rates of PM2.5 generated from stir-frying and pan-frying were significantly higher
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than those of the other three cooking methods were. When the ingredient weight was small (for 1
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person), the emission rate of PM2.5 was significantly higher than that of the other four weights
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(for 2-5 persons). The different types of meat can be divided into three significantly different
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subsets (fish, chicken, and beef; beef and pork; pork and mutton). Chinese cooking for which the
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meat/vegetable ratio is 0.25 generated significantly more PM2.5 than the other four ratios did.
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Detailed PM2.5 results are shown in the Supporting Information (Table S7). In general, the
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emission rates of PM2.5 generated from Chinese cooking are in the same magnitude of the
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emission rates generated from Western cooking (details shown in Figure S5).
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Figure 2. Emission rates of PM2.5 generated from Chinese cooking (factors sorted from the
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largest F value to the smallest one).
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Emission rate of UFPs
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The emission rate of UFPs generated from Chinese cooking was 9.102 ± 6.909 × 1012 #/min,
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which was much larger than the operation of the gas stove and the heating of the used pan (5.048
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× 1011 #/min). As shown in Figure 3, cooking method was a statistically significant factor
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affecting emission rates of UFPs compared to the other factors. Stir-frying and pan-frying
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generated significantly more UFPs than deep-frying did, whereas deep-frying generated
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significantly more UFPs than boiling and steaming did. Detailed measured emission rates of
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UFPs are shown in the Supporting Information (Table S8). The emission rates of UFPs generated
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from Chinese cooking are higher than the emission rates generated from Western cooking due to
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its special cooking method (details shown in Figure S5).
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Figure 3. Emission rates of UFPs generated from Chinese cooking (factors sorted from the
231
largest F value to the smallest one).
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Emission rate of VOCs
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The emission rate of formaldehyde generated from Chinese cooking was 1.273 ± 0.736 mg/min.
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As shown in Figure 4, cooking method was a statistically significant factor affecting emission
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rates of formaldehyde compared to the other factors. Pan-frying and stir-frying generated
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significantly more formaldehyde than deep-frying did, whereas deep-frying generated
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significantly more formaldehyde than boiling and steaming did. Detailed measured emission
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rates of formaldehyde are shown in the Supporting Information (Table S9).
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Figure 4. Emission rates of formaldehyde generated from Chinese cooking (factors sorted from
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the largest F value to the smallest one).
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Benzene was generated from cooking for all the typical Chinese recipes, and toluene was
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generated from cooking for 68% of the recipes. The emission rate of benzene was 0.074 ± 0.039
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mg/min and that of toluene was 0.004 ± 0.004 mg/min. Detailed results are shown in the
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Supporting Information (Tables S10-11 and Figures S3-4).
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The emission rate of TVOCs generated from Chinese cooking was 1.349 ± 1.376 mg/min. As
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shown in Figure 5, cooking method and ingredient weight were statistically significant factors
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affecting emission rates of TVOCs compared to the other three factors. Pan-frying and stir-frying
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generated significantly more TVOCs than the other three methods did. The emission rate of
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TVOCs during cooking for a person was significantly higher than that during cooking for 2-5
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persons. Detailed results are shown in the Supporting Information (Table S11).
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Figure 5. Emission rate of TVOCs generated from Chinese cooking (factors sorted from the
254
largest F value to the smallest one).
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Removal performance of the range hood
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We measured the emission rates of PM2.5, UFPs, and formaldehyde for the 6th and 23rd Chinese
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recipes listed in Table S6 when the range hood was on. The reason why these two recipes were
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selected is that they are very common Chinese residential dishes and the pollutant emission rates
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for them are high.
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The measured exhaust air volume rate of the range hood was 3.88 m3/min for the repeated
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measurements of the emission rate, the corresponding air change rate of which was 21.38 /h for
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the kitchen room. The exhaust air rate is rated at 15 m3/min, which are in the range of the typical
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exhaust air rate in our survey (details shown in Figure S7).
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The removal efficiency of the range hood was 58 ± 6% for PM2.5, 49 ± 4% for UFPs, and 68 ±
265
8% for formaldehyde.
Removal efficiency of range hood
100% 90% 78%
80% 70% 60%
65% 63%
60% 63% 53%
52%
47%
50%
46%
40% 30% 20% 10% 0% PM2.5 PM
UFP UFPs
2.5
1st measurement
2nd measurement
Formaldehyde Formaldehyde 3rd measurement
266 267
Figure 6. Removal efficiency of the range hood.
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ASSOCIATED CONTENT
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Supporting Information. The following files are available free of charge:
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Survey results of cooking behaviors (Page S2, Tables S1-5).
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Orthogonal test design (Page S3, Table S6).
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Determination of emission rates with the range hood on (Page S4).
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Uniformity of spatial pm concentrations (Page S5, Figure S1-(a), Figure S1-(b)).
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The measuring procedures (Page S6, Figure S2).
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Air pollutant emission rates generated from typical Chinese cooking (Page S7-S20, Figure S3-4, Tables S7-12).
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Comparison of emission rates with previous studies (Page S21, Figure S5).
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Survey results of range hoods (Page S22, Figure S6).
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The duration time of typical Chinese cooking (Page S23, Table S13).
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The air change rate during measurement (Page S24, Table S14).
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Comparisons of flow rate and the efficiency of range hood with previous studies (Page S25, Figure S7).
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Comparison between two AM510 monitors (Page S26, Figure S8).
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AUTHOR INFORMATION
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Corresponding Author
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*Address correspondence to Dr. Bin Zhao, Department of Building Science, School of
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Architecture, Tsinghua University, Beijing 100084, PR China. Tel: 86-10-62779995. Fax: 86-10-
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62773461. Email:
[email protected] 291
Author Contributions
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§
293
Notes
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The authors declare no competing financial interest.
Co-first authors that contributed equally to this work.
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ACKNOWLEDGMENTS
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This work was financial supported by the National Key Project of the Ministry of Science and
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Technology, China on “Green Buildings and Building Industrialization” through Grant No.
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2016YFC0700500 and funding from Innovative Research Groups of the National Natural
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Science Foundation of China (No. 51521005). The authors would like to thank Prof. Xudong
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Yang, Ms. Caiyun Lu, Mr. Junzhou He, Mr. Mengqiang Lv, and Mr. Shen Yang for kindly
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helping with the measurements.
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