Study on Health Effects of
Indoor Air Pollution in China
Presented by Pan Xiao-chuan et al.
Dept. of Occupational and Environmental Health
Peking University School of Public Health
Workshop in Oslo, Oct.17-19, 2004
Introduction
„
The indoor air quality is concerned more and
more by the government and the public in China
nowadays and the health effects of indoor air
pollution are becoming a serious challenge in
both urban and rural areas of China. In order to
further study the health effects of indoor air
pollution and population exposure to them, it is
very important for us to know clearly what the
key pollutants is in the urban and rural areas of
China.
Key Indoor Air Pollutants
„ from
housing fitment and decoration:
„ Formaldehyde
„ Benzene,
toluene and xylene
„ Ammonia
„ VOCs
„ Radon
and dust mite
Key Indoor Air Pollutants
„ From
fuel combustion:
„ Particular
Matter
„ SO2
„ CO
„ Environmental
Tobacco Smoke (ETS)
Part one: The Indoor Air Quality
and Health Effects from Housing
Fitment/Decoration in China
Approaches
„
Indoor air monitoring: the average level of
ammonia, formaldehyde, total volatile organic
compounds (TVOC), house dust mites, moulds
and other allergens in 400-1400 households in 6
provinces of China, which measured by the
standard procedure and methods in 2001-2002.
„
Case-control epidemiologic studies: asthma,
leukemia and allergic rhinitis.
Results
Fig.1 Level of of the indoor air
form aldehyde in w inter(m g/m 3)
19.91%
14.06%
1.68%
46.67%
~0.1
0.1~0.3
17.69%
0.3~0.5
0.5~1.0
1.0~
Fig.2 the average level of indoor air
form aldehyde in 6 cities in w inter
formaldehyde
(mg/m3 )
0.7
0.6
0.5
0.4
0.3
0.142
0.2
0.1
0.0
ng
i
gq
n
ho
C
0.610
0.412
0.205
Sh
i
a
gh
n
a
0.210
Be
g
n
i
ij
0.290
0.267
jin
n
a
Ti
n
u
ch
g
n
ha
C
an
h
is
u
iz
h
S
al
t
To
Fig.3 Level of of the indoor air formaldehyde
in summer(mg/m3)
26.02%
11.17%
1.02%
6.35%
55.46%
~0.1
0.1~0.3
0.3~0.5
0.5~1.0
1.0~
Fig.4 the average level of indoor air
formaldehyde in 3 cities in summer
form alde hyde
(m g/m 3)
0.500
0.397
0.400
0.300
0.251
0.293
0.278
0.200
0.100
0.000
Shizuishan
B eijing
Chongqing
Total
mg/m3
Fig.5 the average level of indoor air
am m onia in 6 cities in w inter
0 .1
0.081 0.081
0 .0 8
0.06
0 .0 6
0.059
0.042
0 .0 4
0.037
0.022
0 .0 2
0
Be
g
n
i
ij
g
n
an
n
u
i
h
ch
ns
gq
g
u
n
n
iz
ho
h
ha
C
S
C
in
j
an
i
T
ai
h
ng
a
Sh
al
t
To
Fig. 6 The level of the indoor air
ammonia in summer(mg/m3)
27.38%
5.85%
2.46%
64.31%
~0.2
0.2~0.4
0.4~0.6
0.6~
Fig. 7 the level of indoor air TVOC in
4 cities in winter(mg/m3)
21.79%
16.07%
4.29%
27.86%
30.00%
~0.6
0.6~1.8
1.8~3.0
3.0~6.0
6.0~
Fig. 8 the average level of indoor air
TVOC in 4 cities in winter
mg/m3
5
4.142
4
2.216
3
2.110
1.900
1.354
2
1
0
Changchun
Shanghai
Shizuishan
Tianjin
Total
Fig. 9 the level of indoor air TVOC in
4 cities in summer(mg/m3)
31.73%
8.65%
5.77%
2.88%
50.96%
~0.6
0.6~1.8
1.8~3.0
3.0~6.0
6.0~
summer
c1
辛 5
基
醛
异
辛
醇
壬
2,
醛
2ch
癸
lo
ro
醛
b
ch
e
lo nze
ro
n
be e
na n ze
ph ne
th
al
en
e
c1
4
be
nz
en
to e
m lu e
_p n e
_x
yl
e
a_ n e
fo xy
rm len
al
e
de
hy
苯 de
乙
酰
ca
m
ph
or
c1
3
Fig. 10 The average level of indoor air 17
VOCs Compounds in winter and summer
mg/m3
0.5
0.4
0.3
0.2
0.1
0
winter
Tab.11 Level of the allergen from dust mite,
bacteria and epiphyte in the office buildings
OFFICE
A
B
C
D
E
F
G
H
I
J
K
L
Allergen（IU/100Ml）
Der.P
Der.f
1.22
1.13
1.44
0.69
1.29
1.35
1.29
1.25
3
Bacteria（cfu/m ）
75～800
38～212
25～425
62～825
0～1075
0～1000
25～1150
200～1025
462～1350
488～913
0～1863
363～2738
epiphyte（cfu/m3）
Sum
Mildew penicillium
0～1050 0～1050
12～88
0～50
0～25
0～12
0～38
0～25
0～12
0～238
0～25
0～100
0～250
0～38
0～150
0～200
0～38
0～50
0～5000
0～75
0～38
12～350 12～150
0～25
112～450 62～225
0～25
88～375 12～188
0～25
0～438
0～25
0～12
25～350
0～50
0～12
epidemiological study
Indoor environmental risk factors
for allergic asthma in adults
— a case-control study
Yue Wei, Pan Xiao-chuan et al.
Peking University School of Public health
1.Background
™ Allergic asthma is a kind of common disease. In recent
years, it has an obviously increasing trend in our China.
The prevalence in our China is about 1%，in adults is
about 0.5%.
™ To the epidemiological study about the adults’ allergic
asthma, many researches have been done in foreign
countries in recent 20 years. While in China, few
researches have been reported, especially the
researches between the adults’ allergic asthma and
indoor environmental risk factors.
™ This study is to investigate the risk factors of adults’
allergic asthma or its onset, especially the indoor
environmental risk factors. It is also one of the key
research subjects in our China.
2. Methods:
case-control study:
™ Questionnaire by face to face interview
™ Formaldehyde, NO2 and dust mite measure
102 cases
Asthma patients in
adults from the
Peking University
affiliated Renmin
H o s p i t a l .
Age: 20～70y
Gender: no
limited
Ratio 1：4
394 controls
Healthy residents from
Beijing Xicheng district
which is near the
Renmin hospital. They
all have no allergic or
respiratory diseases.
3.Results: Tab.1
Single risk factors analysis of the allergic asthma
in adults
Risk factors
case
control
P value
OR value
<0.01***
(95％CI)
1.87(1.19-2.93)
<0.05**
1.67(1.05-2.68)
Vocational exposure to
Yes
45
120
dust
Vocational exposure to
harmful gases
No
Yes
No
bungalow
55
35
64
8
274
97
297
13
Housing type
A storied
94
381
<0.05**
2.49(1.01-6.19)
<0.05**
1.64(1.03-2.61)
building
Drying bedding in
Not often
70
225
sunshine
often
32
169
Wood
31
72
<0.05**
1.95(1.20-3.20)
Not wood
Moderate/
71
13
322
40
<0.05**
2.44(1.08-5.51)
Floor of the living room
Cooking oil smoke
indoors
Family history of the
chronic
asthma
bronchitis
severe
Low
No
73
16
234
120
Yes
42
85
60
309
or No
2.34(1.31-4.20)
<0.01***
2.55(1.60-4.04)
Tab.2 Multiple risk factors logistic analysis of
the allergic asthma in adults
Risk factors
β
Sx(β)
waldχ2
P- value OR value
value
Intercept
-3.11
0.37
71.92
<0.0001
—
Vocational exposure to dust
0.58
0.24
5.76
0.0164
1.78
Housing type
1.18
0.51
5.41
0.0201
3.24
drying Bedding in the sunshine
0.42
0.25
2.74
0.0978
1.53
Floor of the living room
0.84
0.27
9.77
0.0018
2.33
Cooking oil smoke indoors
0.92
0.31
8.65
0.0033
2.52
Family history of the
0.84
0.25
11.40
0.0007
2.32
chronic bronchitis or asthma
SAS stepwise Sle＝0.10,Sls＝0.10.
Table3 Correlative analysis between the different
concentration of the indoor formaldehyde and
allergic asthma in adults
Level
(μg/m3)
N
Control (%)
Case (%)
Unadjusted OR value
(95%CI)
Adjusted OR value#
(95%CI)
1(24.68)
28
25(30.86%)
3(10.00%)
1
1
2(43.59) 27 23(28.40%)
4(13.33%)
1.45（0.29，7.18）
1.86（0.35，9.78）
Level
3(69.68) 28 22(27.16%)
6(20.00%) 2.27（0.51，10.18）
1.87（0.39，8.92）
4(120.11) 28 11(13.58%) 17(56.67%) 12.87（3.12，53.12）* 12.94（2.86，58.54）*
Trend Analysis
2.51（1.57，4.00）*
2.36（1.45，3.84）*
Original Formaldehyde concentration（μg/m3）
1.02（1.01，1.03）*
1.02（1.01，1.03）*
value
*: P value < 0.01
# the adjusted factors: age, sex, cigarette smoking,
family history of the chronic bronchitis or asthma
4.Conclusion & Indication：
There were 6 risk factors correlated with the allergic
asthma in adults in our study:
¾
¾
¾
¾
¾
¾
Vocational exposure to dust
Housing type
Drying Bedding in the sunshine
Floor type of the living room
Cooking oil smoke contamination indoors
Family history of the chronic bronchitis or
asthma
It indicated that the adults’ allergic asthma is a kind of
complicated disease caused by genetic and environmental multiple
factors. Meanwhile, there is concentration-response relationship
between the indoor air formaldehyde level and the adults’ allergic
asthma.
Ａ case-control study of the risk
factors for adult leukemia
DING Wen-qing, BAO li , HUANG xiao-jun, PAN
Xiao-chuan.
Peaking University School of Public Health and
Second Hospital
Introduction
„
With the increasing of the living standards of the
residents, the problems caused by the indoor air
pollution have been the hotspot in China
recently. In recent years, the incidence of
leukemia has the increasing tendency , some
reports says it is probably related with the
indoor decoration of the house. The purpose of
this study was to ascertain primarily the
relationship between the indoor decoration and
other suspicious risk factors related with adult
leukemia.
Methods
A total of 127 cases (age 15-75 years old) of
Adult leukemia survivors were interviewed with
health questionnaire by face to face,which
included general conditions, living environment,
harmful materials contact, living style, disease
and family history ,etc. The conditional Logistic
regression model in univariate and multivariate
analysis were used to seek the key risk factors,
specially for adult leukemia.
Result
In the single factor analysis,14 of
98 indexes were obviously
significant<0.05)
Tab. The Single Factor Analysis
Variables
1、Occupation
2、Times of common cold in past
two years
3、History of other blood diseases
4. The degree of the indoor decoration
5. Using indoor air-condition
6. Flower planting in the house
7. Frequently using pesticides
for flower at home
P value
OR value
0.004
0.030
0.90
1.23
0.020
0.001
0.001
0.009
0.018
0.49
3.81
3.84
3.40
12.56
„
Variables
P value
8. Having factory nearby house
0.020
(<500meters)
9. Using the cosmetic often
0.050
10. Using perfume often
0.020
11. Cigarette smoking
0.002
12. Milk drinking frequently
0.009
13. Over intake of salt
0.005
14. Number of cigarette smoking 0.004
OR value
0.292
0.437
0.400
4.420
0.530
0.436
3.452
the multi-factor stepwise regression
analysis
„
There were 4 variables significantly associated with
adult leukemia (P<0.05)
Variables
1 、The degree of the indoor decoration
2、 cigarette smoking
3、 flower planting in house
4、 Using indoor air-conditioner often
P value
0.006
0.011
0.009
0.022
OR value
5.46
6.52
3.40
4.51
Conclusion
„ It
is suggested that the degree of the
indoor decoration might be one of risk
factors for adult leukemia.
The Correlative relations between
Indoor Air pollution and allergic
rhinitis
--a pilot case-control study
Liu Ying, Pan Xiao-chuan et al.
Peking University School of public health
Methods
„
we chose 95 patients and 45 controls to perform
case-control study. Patients were selected from
Peking University affiliated hospitals, where they
had been diagnosed as allergic rhinitis. Controls
are patients from the same hospital but not
suffer from allergic rhinitis. Block-paired design
of Logistic regression was utilized to conduct
multi-factor analysis. We use SPSS 11.0 to do
the statistics.
results
Tab.3:the results of multi-factors
analysis
β
S.E
P value
OR value
age
-1.460
1.002
.145
.232
sex
-.047
.052
.361
.954
married
1.753
1.622
.280
5.770
Allergy history
-.930
1.513
.539
.395
Passive smoking in family
-1.797
1.267
.156
.166
Passive smoking in office
.306
1.083
.777
1.358
The cooking oil
.031*
The type of housing
.874
Family history of allergy
-1.239
1.610
.442
.290
Tab. Distribution of the Cooking oils
in the subjects
group
Salad oil* Peanut oil other
total
case
58
22
1
81
control 12
28
3
43
total
50
4
124
70
•P=0.008, OR value=12.918( Logistic Regression)
The results suggests that use of salad oil may cause
the increase of the prevalence rate of allergic rhinitis.
The Indoor Air Quality and
Health Effects from Fuel
Combustion in China
1999-2004
INDOOR AIR POLLUTION AND
RESPIRATORY HEALTH OF THE
PEOPLES IN BEIJING:
A COMMUNITY-BASED STUDY
Dept. of Occupational and Environmental Health,
Peking University School of Public Health,
Beijing 100083, P.R. China
Xiao-chuan Pan, et.al.
INTRODUCTION
„ In
recent years the housing of Beijing
peoples have been improved enormously
with the fast development of the economy
as well as living level. A lot of the new
fitments, soft furnishings, fitted carpets and
mechanical air ventilation systems are now
introduced into more and more households
in Beijing, especially in urban areas.
„ How about indoor air quality caused by
them?
METHODS
„
„
Participants: About 270 households, living in 3
communities of urban area were selected randomly for
indoor air monitoring, about 3000 individuals aged from
18 – 65 yr. from the study households and their
neighbors were interviewed by questionnaire for their
respiratory health.
The mass concentration of particles smaller than
10μm/2.5μm in diameter（PM10/PM2.5）and sulphur
dioxide (SO2) was measured in the bedroom and kitchen
of the study households in real time twice a day for two
weeks, respectively in winter and summer.
METHODS 2
„
Health: The health questionnaire was based
on that of the British Medical Respiratory
Committee and revised according to the
different status in Beijing. It consisted of age,
gender, education, occupation, and general
health status, living habits, exposure to indoor
microenvironment factors, cooking, and
smoking, respiratory symptoms and other
daily activities. The trained students of a
medical college conducted the health survey
with the questionnaire by face-to-face
interview.
METHODS 3
„
Determination
and
Data
analysis:
The
determination of levels of PM10, PM2.5 and SO2 was
taken with standardized procedures. The t-test
and X-square test were used for estimates of
variances of the pollutants level. Effect size of
various factors for respiratory symptoms and lung
function were estimated with two models. First, is
a linear model with an ordinary least-squares
regression of symptoms rates. We accounted for
clustering of observations in units of Household.
Second, we used a logistic probability model y=F
(X×β+u): y, X, andβare defined as in the linear
model; F=cumulative logistic distribution, F
(z)=exp (z) divided by [1+exp (z)].
RESULTS
Fig.1 Indoor Air PM10 Level in 3
Districts of Beijing(mg/M3)
0.8
0.6
0.4
0.2
0
B
K
B
K
Dongcheng Shijingshan
B
K
Haidian
Districts
B: bedroom, K: kitchen. the same as below
in winter
in summer
Fig.2: The Indoor Air PM2.5 Level among
Three Districts in Beijing(mcg/m3)
700
600
500
400
300
200
100
0
B
K
Dongcheng
B
K
Shijingshan
Districts
B
K
Haidian
in winter
in summer
Fig3: The Indoor Air SO2 Level among
Three Districts in Beijing(mcg/m3)
450
400
350
300
250
200
150
100
50
0
B
K
Dongcheng
B
K
Shijingshan
Districts
B
K
Haidian
in winter
in summer
Graph1: PM10 Level in 24 Hours in A Bedroom
in Haidian District in Beijing(in winter)
Graph2: PM2.5 Level in 24 Hours in A Bedroom
in Haidian District in Beijing(in winter)
Graph3: PM10 Level in 24 Hours in A Kitchen
in Shijingshan District in Beijing(in winter)
Graph4: PM2.5 Level in 24 Hours in A Kitchen
in Shijingshan District in Beijing(in winter)
Table 4. Coefficients of Logistic Regression for
Respiratory Symptoms and indoor air pollutants
and other factors
Variables
Cough
Phlegm
Asthma
intercept
-2.3494
-1.4326
-2.5023
PM10
PM2.5
SO2
Exp. To Occup. Dust
Exp. To Chemicls
Smoking
Passive Smoking
Much time to Cooking
0.5473
-0.3231
-0.0267
0.5650**
0.6498**
0.4653**
0.000928
-0.1010
0.4700
-0.0394
0.4816**
0.3329
1.0195**
-0.0201
-0.00069
1.5789
-2.7718
-0.1220
0.6822*
0.2164
0.4245
0.2571
0.0119*
smoke exhauster in kitch
Cooking oil indoors
-0.2730
-0.2569
-0.4170**
0.1618
-0.0809
-0.2516
*: P<0.05, **: P<0.01
Breathe
short
1.8412**
1.4811
-1.6727
1.0048
0.1579
-0.0642
-0.4009*
0.2228*
0.00711*
*
0.4238**
0.4215*
An Evaluation Of The Indoor Air
Pollution And Respiratory Health Of
Farmers in Anhui Province, China
Cooperated with Harvard University of USA
and World Bank
INTRODUCTION
„ more
and more people living in urban
areas of China spend the greater part of
their time indoors, where concentrations
of many air pollutants are higher than
outdoors, and the health effects maybe
the same as that in the urban areas.
„ But similar studies in China have
scarcely counted indoor air pollution in
rural areas and their adverse health
effects.
INTRODUCTION
„
„
„
Now, more than 70 percent of China’s populations
also live in rural areas and some of them have
quite poor living conditions, where respiratory
diseases are also the leading cause of death.
Nowadays the research on health effects of indoor
air pollution in developing countries has been
hindered by lack of detailed data about human
exposure and adverse outcomes. The basic study
should be conducted first.
In the present study we measured the level of
indoor air pollution and examined primarily the
related health effects (respiratory symptoms) in
rural areas of southeast China.
Methods
„
Participants
„
The study field covered more than 30 small towns of 4
counties, consisting of lake, plain, hill and mountain areas
in Anhui province of China. 189 households (62 from the
lake area, 74 from the plains and 53 from the mountain
area) were selected randomly to represent various
geographic and socioeconomic background of this area.
They had similar tribal backgrounds, living habits, and diet.
At the same time, about 500 individuals aged from 15 – 65
yr. from the study households were interviewed by
questionnaire for their respiratory health conditions.
„
Methods
„
„
„
„
Exposure
We did the research in the winter of 1999. The
level of sulphur dioxide (SO2), particulate matter
smaller than 10μm in diameter（PM10）and
carbon monoxide (CO) indoors were selected as the
index of indoor air pollution for the study.
We monitored the level of these pollutants in the
bedrooms, kitchens, courtyards and the farmlands
of the study households in real-time measure, twice
a day for two weeks.
We also interviewed household members about
household energy use technology and their timeactivity patterns with questionnaire by face-to-face
interview.
RESULTS
Table 1. Demographic
information of study group
Male
Female
Total
Sex
246
221
467
Mean (SD) Age
35.67±13.70
36.58±12.84
36.12±12.62
Education (years)
6.73±3.4
2.71±3.8
5.06±4.4
Smokers
134
11
145
Table.2 The level of PM10, SO2&CO
indoors/outdoors (Mean±SD)
Kitchen
Bedroom
Yard
Farmland
N
373
504
366
55
PM10 (µg/m3)
518±27*
340±9
287±9
270±10
SO2 (µg/m3)
12.4±36
10.9±18
11.0±19
10.8±18
CO (mg/m3)
2.0±9.9
1.62±6.0
1.62±4.5
2.0±4.5#
*(t-test, P<0.01, kitchen/bedroom) ；#（t-test, P<0.01，farmland/yard）
Table.3 Level of indoor air pollutants
during cooking and non-cooking time
Cooking
Non-cooking
P (T-test)
N
123
228
-
PM10 (µg/m3)
1251±39.2
332±10
<0.001
SO2 (µg/m3)
13.9±49.4
11.8±33
0.26
CO (mg/m3)
3.0±2.1
1.62±5.5
<0.001
Table.4 the daily time-activity
patterns for the subjects（hours）
Male
Female
t-test
P
N
245
222
-
-
Bedroom (χ±s.d)
9.59±4.09
10.56±3.59
2.72
<0.01
Kitchen (χ±s.d)
1.36±2.15
3.78±2.48
11.2
<0.01
Yard (χ±s.d)
2.44±2.51
2.69±2.16
1.15
0.25
Farmland (χ±s.d)
0.84±2.66
0.62±1.49
1.10
0.27
Others (χ±s.d)
8.87±6.12
5.07±6.06
6.71
<0.01
Table.5 the factors associated with
asthma, cough and phlegm (Logistic
model)
Symptoms
Variables
OR
95% CI
P
Using the pesticides often
1.13
0.98～1.03
0.06
Warming with the
charcoal stove
2.85
1.61～5.03
<0.00
1
Phlegm
Using the pesticides often
1.19
1.04～1.37
0.01
Cough
Room cleaning often
0.41
0.19～0.87
0.02
Asthma
attack
(N＝467)
Table.6 Regression coefficient (×1000) of
exposure indices to PM10 and the lung
functions
Place
FVC (n=324)
β±SE
FEV1 (n=325)
β±SE
FEV1% (n=324)
β±SE
Bedroom
-11±6
-25±7**
-6±1**
Kitchen
-4±6
-2±7
-0.5±1
11±27
-2±6
-38±48
-3±8
Yard
Farmland
-37±42
FVC: forced vital capacity; FEV1: forced expiratory volume in first second **: (P<0.01 )
FEV1%: percentage of forced expiratory volume in first second to forced vital capacity
CONCLUSION
„
There is quite serious indoor air pollution in
the households of the rural areas of China,
about 1/3 of them > 450μg/m3 of PM10.
„ Exposure
indices to PM10 in bedrooms were
negatively associated with the level of lung
functions of study subjects(P<0.01).
„ The
one cause of the indoor air pollution in
the rural areas comes from the fuel
combustion when cooking in kitchen as well
as heating in winter.
Household fuel Structure and
Effect on Indoor Air Quality
in Rural North Sichuan
Province
Cooperated with China Agriculture University in
Beijing
Methods
„
The questionnaire and indoor air monitoring
were carried out at the same period from May 18
to June 9, 2004, in 3 villages, Shuanglong,
Zhaoban, Sifangzui, in north Sichuan Province.
„
Twenty-four-hour averaged PM2.5
concentrations were obtained by using 1.5-literper-minute SKC universal sample pumps. 150
families were random selected to monitor the
concentration of PM2.5 of kitchen in 5 counties
of 3 Province (Sichuan, Hunan, Hubei)
Monitoring methods:
Sampling
time
Pollutants
Instruments
Monitoring time
CO
XH-3050
Infrared CO
Analyzer
9:00, 12:00,
15:00, 18:00
――
HOBO CO
HOBO CO
logger
9:00 to next
day’s 9:00
24 hours
9:00, 12:00,
15:00. 18:00
20 min
SO2
QC-1 air
sampling
instrument
The pollution level of SO2 and CO in 3 villages
Average concentration
Pollutants
SO2
CO
Villages
Samples
No.
Shuanglong
Median
(mg/m3)
Average
(mg/m3)
Maximum
(mg/m3)
30
0.318
2.666
21.839
Zhaoban
30
0.129
0.284
4.133
Sifangzui
30
1.872
2.996
16.309
Shuanglong
30
5.687
8.896
101.875
Zhaoban
30
4.938
9.413
129.875
Sifangzui
30
12.063
17.859
128.5
Indoor air PM2.5 Level in Rural Areas of
Sichuan Province in China (2004.5)
County
N
Langzhong
Yilong
Nanbu
Enshi
Yongshun
30
30
30
30
30
PM2.5
concentration
(ug/m3)
221.7±137.9
123±68.6
212.7±163.2
192±180.3
186.4±168.4
Temp. Humid. air P.
%
(Kpa)
℃
24.3
23.1
24.8
24.5
24.3
71%
79%
68%
77%
85%
96.5
96.6
97.7
95.5
95.2
Daily energy consumption in three
villages
Discussion
„
„
„
Health effects of indoor air pollution should be
considered as a factor in evaluation of
environmental cost model.
Exposure-response relations: the population
study on health effects of indoor air pollution
remains in primary stage now and there is few
on quantitative evaluation for it in China.
the pollutants and microenvironment indoors
are very complicated, so the health effects
should be the integrated results caused by both
pollutants and microclimates.
Thanks for your
attention !