Lund University
Department of Political Science
STVK12
Tutor: Magdalena Bexell
Chinese (in)action:
Seeing breathing as a means to understand
citizens’ (in)action
Linda Angerbjörn
Abstract
Civic engagement plays an important role in governmental transparency –
so how does transparency work in a non-democracy like China where the political
and juridical systems repress public participation? Through quantitative methods
this paper examines how a selection of citizens in Shanghai, China, make use of
environmental information made available through the Chinese government’s
Open Environmental Information (OEI) transparency measures. The findings
indicate that information on air quality is only utilized by a small percentage of
the research sample, while the majority do not adhere to warnings of heath risks
associated with smog. Previous studies show that, while the country’s polluted air,
soil and water cause hundreds of thousands of premature deaths each year, public
engagement and participation in environmental affairs in China remains low.
Theories hold that for information disclosure to lead to anything other than words
and numbers on a paper it must first change people’s perceptions and behaviour.
It is hypothesised that the individuals in the research sample did not protect
themselves because the air pollution data did not create enough awareness of
associated health risks to induce a change of behaviour.
Keywords: Transparency, governmental information, information
disclosure, environmental awareness, public perception of air pollution
Total words: 9,637
2
List of Abbreviations
AQI
Air Quality Index
IER
Institute for Energy Research
IPE
Institute of Public and Environmental affairs
MEP
Ministry of Environmental Protection
NGO Non Governmental Organization
NRDC Natural Resources Defence Council
OEI
Open Environmental Information
SEMC Shanghai Environmental Monitoring Centre
SEPA State Environment Protection Agency in China
WHO World Health Organization
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Table of Content
1
INTRODUCTION ...................................................................................................... 5
1.1 THE POLLUTION PROBLEM..................................................................................... 6
1.2 ENVIRONMENTAL DATA: STATE SECRETS OR RIGHT-TO-KNOW? .......................... 6
2
PREVIOUS STUDIES ............................................................................................. 10
2.1 HOW DOES TRANSPARENCY WORK IN AN AUTHORITARIAN SETTING? ................ 10
3
THEORIES ............................................................................................................... 12
3.1 WHAT IS TRANSPARENCY?.................................................................................. 12
3.2 DIFFERENT KINDS OF TRANSPARENCY ................................................................ 12
3.3 TARGETED TRANSPARENCY ................................................................................ 13
3.4 FROM TRANSPARENCY TO BEHAVIOURAL CHANGE ........................................... 13
4
METHODOLOGY AND DATA COLLECTION ................................................. 17
4.1 STRUCTURED OBSERVATIONS ............................................................................. 17
4.1.1 Research Site ................................................................................................ 17
4.1.2 Sampling method .......................................................................................... 18
4.1.3 Limitations and strengths of structured observations .................................. 18
4.1.4 Ethical issues with structured observations ................................................. 19
4.2 AIR QUALITY DATA ............................................................................................. 19
4.3 SURVEY ............................................................................................................... 20
4.3.1 Limitations and strengths of online survey .................................................. 21
5
ANALYSIS: .............................................................................................................. 22
5.1 MASK-USAGE ...................................................................................................... 22
5.1.1 Mask-usage in relation to air quality data ................................................... 25
5.1.2 Mask-usage in relation to AQI China vs. AQI US ....................................... 27
5.2 ONLINE POLL....................................................................................................... 29
6
RESULT OF ANALYSIS: ....................................................................................... 33
7
CONCLUSION:........................................................................................................ 34
8
REFERENCES ......................................................................................................... 36
4
1
Introduction
China’s authoritarian regime keeps tight control over flows of information
in the country through censorship of media and the Internet and low transparency
in governmental affairs. Environmental data, such as governmental readings of
pollution levels of soil, water and air have historically been classified as ‘state
secrets’. But the fact that China suffers from environmental degradation is plain
for everyone to see. Polluted farmlands, food scares, toxic rivers and smog are
part of everyday life for hundred of millions of Chinese - affecting their heath and
quality of life. In 2008, the Chinese government composed the Open
Environmental Information (OEI) - an environmental disclosure policy that allows
for a range of environmental data to become public. Readings of air pollution
levels is one type of data that became available from government agencies as an
effect of this policy. However, the government is not the only source of
environmental data in China: since 2008 the US Consulate has been posting
hourly air quality measures from their Beijing compound. Reported air pollution
levels from the US Consulate tend to be higher than those from Chinese
authorities, causing the trustworthiness of the governmental information to be
questioned in local media and on social networking sites. So how do Chinese
citizens perceive the newly disclosed information derived from their government?
Do they use readings on air pollution derived from the Chinese authorities, or the
US Consulate or some other source? Through quantitative methods this paper
examines how a sample of citizens in Shanghai, China, use air pollution data. The
study also aims to find indicators on whether the sample use air pollution data
derived from the Chinese authorities or the US Consulate in Shanghai.
My research question is:
How do citizens in an authoritarian state use governmental data on air
pollution?
The next section gives a historic account of environmental issues in China
in order to explain the politics surrounding the subject of pollution. Previous
research on transparency measures and public perception of pollution in an
authoritarian setting is then reviewed. The theoretical part focuses on mechanisms
of transparency and what is needed for transparency policies to lead to change.
The methodology and analysis section describes how the data was collected,
sampling procedures employed and the analysis of the different kinds of data:
mask-usage ratio; AQI levels from Chinese governmental agencies and US
Consulate in Shanghai; and results from the online poll. Numeral and textual data
have been composed in spreadsheets. The results and proposals for further
research are finally discussed in the conclusion chapter.
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1.1 The pollution problem
For three decades China has experienced exceptional economic growth
teamed with increased living standards for a majority of the country’s 1.3 billion
people (World Bank, 2013). In just ten years China’s car fleet increased by 570%
- from 24 million in 2003 to 137 million in 2013 (Ministry of Public Security,
2014). Today the country is the largest energy consumer in the world: it uses more
electricity than any other country, it is the world's second-largest consumer of oil
and the world’s largest producer and consumer of coal (IER, 2015).
The cost of this development has proven to be severe degradation of the
country’s air, water and soil – which in turn affects people’s health. According to
the World Health Organization (WHO, 2014) an estimated 7 million premature
deaths occur worldwide every year due to air pollution – 2.8 million of which
occur in the Western Pacific Region alone. The most dangerous culprit of this
human tragedy is the PM2.5. This is a particular matter (PM) less than 2.5
microns in diameter made up by dust, dirt, soot, smoke or liquid droplets emitted
from power plants and motor vehicles. These minute particles can be suspended in
the air for long periods of time as atmospheric aerosol. PM2.5 are too small to see
with the naked eye and can only be detected with an electron microscope. Some
particles are large or dark enough to be seen as soot or smoke – so called smog.
PM2.5 are easily breathed in and lodge deeply into human lungs, allowing for
harmful chemicals to be carried into the internal organs. Children and the elderly
are especially vulnerable to ‘the silent killer’ that seeps effortlessly in to homes,
kindergartens, schools and offices. China suffers from the heaviest PM2.5
pollution in the world with at least 300 million Chinese living in areas with
polluted air (Greenpeace East Asia, 2012 and Ministry of Environmental
Protection, 2014).
1.2 Environmental data: state secrets or rightto-know?
Acquiring accurate data on the quality of air is thus a matter of life and
death for Chinese citizens. However, China’s central government has a tradition
of keeping environmental data firmly under wraps. One of many examples of this
practice dates back to 2007, when a report produced by the World Bank in cooperation with Chinese government ministries found that about 750,000 people
die prematurely in China each year due to air pollution. However, the calculations
of premature deaths were cut from the final report as China’s State Environment
Protection Agency (SEPA) and health ministry felt the information was too
sensitive and could cause social unrest (Financial Times, 2007). But when China’s
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capital of Beijing experienced the worst smog ever recorded in the area during the
winter of 2012 it was no longer possible to stay in denial. Not only did Beijing
residents’ own physical senses tell them the air was unhealthy, but a foreign
source of environmental data reported the air to be much more polluted than
official Chinese readings: the US Consulate in Beijing.
The liaisons between the Chinese authorities and US Consulate with regards
to disclosing environmental data showcase the politics surrounding the issue of
pollution. Since 2008, the US Consulate in Beijing had posted hourly
measurements of air pollution taken at their compound in Beijing on Twitter - a
social networking site that is blocked in China. The disclosure attracted much
attention in independent national and international media, and the air pollution
measurements could soon be found reposted on websites and mobile applications
across the country. The Consulate’s air pollution readings attracted attention
because they were considerably higher than those of the Chinese authorities –
causing many to question the accuracy of the Chinese authorities’ readings (The
Wall Street Journal, 2012; Global Times, 2013; Greenpeace East Asia, 2012).
The Consulate calculated the air quality by converting PM2.5 readings
taken from their Beijing compound into an Air Quality Index (AQI) – a system to
indicate potential health impact of the air. Meanwhile, Beijing Municipal
Environmental Protection Bureau also employed AQI to indicate impact of air
pollution on human health – but this AQI was calculated with measurements of
SO2, NOx and PM10 only, which are larger and less harmful particles (Huang,
2015). This meant that the air was not deemed as polluted by the Chinese
measures as by the US Consulate.
The Chinese authorities applied pressure on the Consulate to stop publishing
the data with the standpoint being "the monitoring and publishing of China's air
quality are related to the public interests and as such are powers reserved for the
government" (Wu Xiaoqing, Vice Minister of Environment Protection, 5 June
2012, quoted in Reuters, 2013). But the Consulate persisted, and when AQI
readings went off the scale during the Beijing smog episode of 2012, the public
demanded more accurate air quality readings from their government (Huang
2015). This is a rare case of Chinese authorities not impeding active public
participation, but rather responding to public requests (Huang 2015) - because the
public protests following the Beijing smog episode of 2012 did result in Beijing’s
municipal government including PM2.5 readings in AQI calculations from 2013.
Since 2013, AQI readings from the two sources have come closer, but there
is still a persistent difference, particularly at midlevels of AQI (see graph 1).
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Graph 1: AQI differ from Chinese and US authorities at mid-range 2.5PM
The US Consulate using a stricter system to determine AQI explains the
discrepancy; while PM2.5 measurements are objective, AQI is subjective. E.g.
AQI 50 by US standards would correspond to a PM2.5 density of 15.4
micrograms per cubic meter, while AQI 50 by Chinese standards would
correspond to a PM2.5 density of 35 micrograms per cubic meter – more than
twice as high (Zhao, 2013). In other words, the US authorities deem human health
to be affected at a lower level of PM2.5 than the Chinese. In addition to AQI, both
sources post advice on how citizens should protect themselves from smog –
including keeping windows shut, avoiding outdoor sports or wearing respirators.
Because these recommendations are connected to AQI, recommendations from
the two sources frequently diverge as illustrated in picture 1.
Today, Chinese authorities and US Consulate continue to publish hourly
measurements of air quality from several major Chinese cities. AQI readings from
the two sources are re-posted and compared on websites and mobile applications
across the country. Picture 1 illustrates AQI readings from Shanghai in March
2015 (Air.fresh-ideas.com, 2015). The PM2.5 readings are almost identical from
the Chinese authorities (‘City Average’) and from the US Consulate – 68 and 69.
However, US Consulate deem the air ‘Unhealthy’ with an AQI of 158 and
recommend respirators to be worn (indicated by the symbol to the right), while
Chinese authorities state the air quality is ‘Good’ enough (at AQI 91) to do
outdoors sports (indicated by the symbol to the right). At the time of this research
project (2015) the government had ordered Chinese digital platforms to remove
US Consulate’s AQI readings from, amongst others, Beijing – as can be seen at
the top of picture 1.
The phenomenon of air quality measures and recommendations for
protection against smog diverging from the two sources of environmental data is
being investigated closer in this study. By calculating the ratio of the sample who
chose to wear respirators on days when Chinese authorities report high levels of
air pollution and recommend a respirator to be worn, and compare this to days
when the US Consulate reports high levels of air pollution and recommend a
respirator to be worn, the aim is to find indicators on whether the sample use air
pollution data derived from Chinese authorities or US Consulate.
8
Picture 1: Compared AQI
from Chinese government
and US Consulate
To conclude, due to severe environmental degradation in China, air
pollution has become a political issue. When the US Consulate decided to make
air pollution measurements public, they angered the Chinese government who
held that state sovereignty had been violated by these acts. The disclosure leads to
public scrutiny of governmental environmental data, civil protests and a
subsequent change of governmental practice. However, Chinese authorities still
assess health to be less affected by lower levels of PM2.5 than the US. This
situation provides an opportunity to find indicators on whether Chinese citizens
follow advice on air pollution protection from their government or the US
Consulate.
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2
Previous studies
2.1 How does transparency work in an
authoritarian setting?
In a democracy, transparency holds a normative value: indeed it is seen as
essential to the democratic system as citizens can use the information to hold their
government accountable, and in that way improve institutional performance. In a
non-democracy, however, transparency policies are driven by technocratic
objectives, such as achieving tangible results (Tan, 2014). So how does
transparency work in an authoritarian setting? I will in this section look at
previous studies on how citizens perceive and use information made available
through transparency measures in China.
In a study of the impact of China’s 2008 Open Environmental Information
(OEI) policy, Tan (2014) found little evidence that citizens access or use
information made available through the OEI to deal with environmental problems.
This notion is backed up by NGOs that assess that information has not yet become
a tool for active public participation in China (NRDC and IPE, 2010, cited in Tan,
2014). So are the citizens not interested in environmental data because they do not
perceive pollution as a problem? Several surveys of public perception of smog in
China rebut this notion: the vast majority of respondents in heavily industrialized
districts in eastern China (Shandong and Shannxi Province) perceived smog as a
“serious” or “very serious” problem. But despite the awareness, respondents were
not found to be particularly willing to take part in actions to monitor or improve
the environment; this is seen as the job of the government (Feng and Reisner,
2011 and Wang et al., 2015). This lack of public participation in environmental
protection is due to the government structure in the Chinese society, Wang et al.
(2015) argue. China’s juridical system may also repress active civic engagement:
Tan (2014) argues that the ability for nonstate actors to use the disclosed
environmental information to hold the state accountable is limited by the juridical
and political system in China. This notion is backed up by Matthew Collins (IPE,
2015) who in an interview for this study argues that the juridical system in China
is not independent of business interest: government agencies have economic
interests to take in to account, which often trump environmental issues. The cost
of using the disclosed environmental information to confront powerful state and
business interests is thus likely to be too high for civil society to be able to act on
it (Tan, 2014).
However, the government cannot tackle China’s pollution problems through
a top-down approach alone - civil society needs to be on-board, engaged and
actively participating. The government acknowledges this and officially backs
10
public participation in environmental affairs, according to Agenda 21 (ACCA,
1994 cited in Wang et al., 2015). But even though environmental information
transparency has increased in recent years and the government officially support
civic engagement – the studies discussed above indicate that utilization of
environmental information and civic engagement in environmental affairs remains
weak because:
 The State and business interests are intertwined, making it too costly for
civil society to take action against (Tan, 2014)
 The juridical system is state-controlled and not independent of business
interests (Tan, 2014 and IPE, 2015)
 The nature of the governing structure in China does not encourage civil
society engagement (Wang et al., 2015 and Huang, 2015)
Whether they lead to the expected result or not, transparency policies
require bureaucracy to be implemented. Hence, transparency policies are costly
affairs that do not always lead improved governance as can be seen from previous
studies discussed in this chapter. To investigate what is needed for transparency
measures to be successful we need to look closer at the concept of transparency in
a theoretical view.
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3
Theories
3.1 What is Transparency?
Dassen and Cruz Vieyra (2012) define transparency as government
‘porosity’ that makes data pertaining to government actions available to citizens,
which enables oversight of the acts of government officials and civil society
participation. Several studies have found that government actions that promote
information flow - such as active communication with citizens, increased
information delivery and policy transparency - increase political trust and public
trust in a society (Sun and Wang, 2012; Tao, Yang, Li and Lu, 2013). Advocates
of transparency tend to attach both normative and technocratic values to
transparency: it is viewed as an end to itself, while access to information is
assumed to improve welfare and accountability (Tan 2012). In this process there
are two actors: disclosers of information (‘disclosers’) and users of information
(‘users’). In the case of the OEI, the discloser is government agencies. There are
many potential users of the data: civil society, NGOs and enterprises are some of
them. I will for simplicity focus on civil society as the sole information user in
this study.
3.2 Different kinds of Transparency
There are two different kinds of transparency policies that work differently
and have different objectives (Fung, Graham, and Weil, 2007):
‘First generation’ transparency is connected to concepts of monitoring and
accountability. This concerns broader “right-to-know” and “open-government”
acts that grant citizens access to information that they can then use as a tool to
watch what the government is doing (Rose-Ackerman, 1999). Transparency
policies like these are fundamental to modern democracies because they allow
citizens to participate in government management (Dassen and Cruz Vieyra,
2012) – indeed the very idea of democracy is built on citizens being engaged and
well-informed (Dahl, 1989).
‘Second generation’ transparency measures concern so-called ‘targeted
transparency’. Only specific information is disclosed through these policies with
the aim to achieve tangible goals (Dassen and Cruz Vieyra, 2012). Food labelling
is a one example of successful targeted transparency: the disclosed nutritional
information on the label helps the consumer (user) make an informed decision on
12
whether to eat the food or not while encouraging the food manufacturer
(discloser) to produce healthier food (Weil, et al., 2006).
So while some transparency measurements are driven by normative values
connected to democratic ideals – others are used to achieve specific goals. In a
non-democracy, due to its very nature, transparency is not driven by normative
values, but by technocratic objectives (Tan, 2014). The OEI in China can be
described as a ‘second generation’ targeted transparency policy and I will
therefore focus on targeted transparency in the following sections.
3.3 Targeted Transparency
According to Fung, Graham and Weil’s theoretical model for targeted
transparency (2007), a number of conditions need to be fulfilled for a
transparency policy to be successful:
1)
the information must have value to potential users meaning that the information has to be relevant to those receiving it
2)
the information needs to be comprehensible to users
and must create sufficient awareness in order to change users’
previous opinion about a particular subject
3)
the costs of accessing and acting on the information
must be less than benefits
4)
feedback needs to be transmitted back from user to
disclosers on how (or if) their information is being used, or incentive
to continue the disclosure will be lost
If we apply this model on the OEI, we can see that several of these
conditions are not met:
1)
Due to the state-controlled juridical system and state
and business interests being interlinked, the cost of using the disclosed
environmental information to confront powerful state and business
interests is likely to be too high for civil society to act on it (Tan, 2014
and IPE, 2015)
2)
The nature of the political system and low civic
engagement in environmental affairs limit the capacity for feedback on
how disclosers’ information is being used
3.4 From Transparency to Behavioural
change
13
For information disclosure to achieve anything more than words or numbers
on a paper, the information must change the behaviour of the user or the discloser
of the information. Users change behaviour through actions, while disclosers
change behaviour though responses (Fung, Graham, and Weil, 2007). As
illustrated by the Targeted Transparency Policy Cycle (figure 1) the transparency
policy might start a chain-reaction in the following way: if the disclosed
information generates a change in users’ (e.g. citizens’) perceptions, this could
lead to a change of their behaviour – for example by them not buying products or
services, or by them complaining and voting accordingly. It is then up to the
disclosers (e.g. government agents) to decide whether it is in their interest to
respond to the users’ complaints and determine what possible action would
optimize their expected net benefits - keeping in mind what actions users, in turn,
would take in response (Dassen and Cruz Vieyra, 2012).
Figure 1: Targeted Transparency Policy Action Cycle
In the example of the food labelling policy, the nutritional label encourages
the consumer (user) to change their behaviour by choosing a healthier food - and
this in turn gives the manufacturer (discloser) incentive to produce healthier foods
- the incentive being increased sales (Weil, et al., 2006)
However information disclosure does not always lead to behavioural
change: when voters in Mexico were given information about corruption, the
population responded with apathy, and electoral participation fell by almost 6 per
cent (Chong et al., 2010 cited in Dassen and Cruz Vieyra, 2012, p.28);
congressmen in Uganda did not improve their performance when faced with
exposure to greater transparency, nor did this transparency affect their chances of
re-election (Humphreys and Weinstein, 2012 cited in Dassen and Cruz Vieyra,
2012, p.28).
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The OEI did also not result in a change of behaviour in some areas: it did
not increase active public demand for information, nor strengthen accountability
of government agents or polluting corporations (Tan, 2014). These failures can be
connected to theories on opportunity cost – for users as well as disclosers of
information:
1)
Opportunity cost for users (including comprehension
of information and coordination to solve the collective action problem for
example) is put in relations to citizens’ perception of probability of
change: If citizens believe that chances of them being able to generate a
change are low, they will not mobilize in the first place. A vicious cycle or
‘self-fulfilling prophecy’ might develop here: citizens do not expect that
their complaints will lead to a change in behaviour, and therefore they
decide not to act - hence the situation stays the same (Dassen and Cruz
Vieyra, 2012). The nature of the juridical and political system in China is
likely to further increase such opportunity cost for civil society to confront
powerful state and business interests (Tan, 2014).
2)
Opportunity cost for disclosers is connected to
incentives: Disclosers of information will only give in to demands from
information users when the benefit associated with the change - whether in
terms of reputation, popularity, or future sales - is greater than the cost of
doing nothing. Therefore the objective of the targeted transparency needs
to be aligned with the incentives of both users and disclosers of
information for it to lead to a change in behaviour (Dassen and Cruz
Vieyra, 2012). In the case of Uganda, the transparency did not affect the
politicians’ chances of being re-elected, and therefore they had low
incentive to change.
The results from the research done for this study also indicate that the air
pollution data led to little behavioural change on a personal level: few of the
individuals (users) in the sample used the information to change their behaviour
by protecting themselves from the smog. Fung, Graham and Weil’s (2007)
theoretical model holds that the disclosed information must create sufficient
awareness in order to change users’ previous opinion about a particular subject.
This is the first step in the Targeted Transparency Policy Action Cycle (figure 1):
without this initial stage, citizens will not move on to changing their behaviour,
which in turn should lead disclosers changing their perception and behaviour. So
why did the disclosed information not create sufficient awareness? I will
problematize through theories on ‘rational inattention’ and risk perception:
1)
Sims theory of ‘rational inattention’ (2003) holds that
individuals have a limited capacity to pay attention, and must therefore
choose what to pay attention to. By this theory, the most rational choice
might be for people to not pay attention to certain information if it
competes with other, relatively more important, information. Introducing
new information does therefore not always lead to change in perception or
behaviour. In order for information to change behaviour, “it must win
15
many battles for the user’s attention before it can inform decision making”
(Dassen and Cruz Vieyra, 2012)
2)
Risk perception theory recognizes that scientific facts
and public perception of the dangers do not always match. Why people
smoke or are scared of flying can be explained by this theory. Information
showing that air pollution lead to many premature deaths each year does
not automatically lead to people perceiving smog as dangerous
Both these theories present us with the same question related to this study’s
result: How ‘important’ or ‘dangerous’ do Chinese citizens perceive smog to be?
A study found that, while the vast majority of respondents in a heavily polluted
eastern China town perceived smog to be a serious problem, self-protective
consciousness was low. However, after partaking in information of heath risks
connected to smog, people were more willing to protect themselves (Wang et al.,
2015). Similar results were drawn from a review of an awareness-raising
campaign about water contamination in India. It was observed that after being
informed of the probability of their water supply being contaminated, families
who had initially lacked any sort of water purifying system were 11% more likely
to use water purifying systems (Dassen and Cruz Vieyra, 2012). Hence,
individuals not connecting smog to personal health may explain the low level of
self-protection found in my sample. It can be hypothesised then that the research
participants in this study did not act on the air pollution data by protecting
themselves because they did not perceive the information as pertaining to their
health.
To conclude; transparency policies can lead to greater accountability,
improved governance and welfare - but they cost resources and do not always lead
to change. For information disclosure to achieve anything more than words or
numbers on a paper, the information must be perceived as important and relevant
to users in order to lead to change in perceptions and behaviour. This awareness
can be the first step in an action cycle that leads to change - however, the cost of
taking action must be lower than the cost of doing nothing for change of
behaviour to happen.
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4 Methodology and Data
Collection
This chapter will detail the methodology used in this research including
research methods, data collected and limitation and reliability of these methods
and data.
4.1 Structured observations
For my study I chose the method of structured observations. This is a rarely
used method in social science that entails the researcher directly observing and
recording the behaviour of individuals according to a pre-established set of
criteria (Bryman, 2008).
The observations for this study were made in Shanghai, China, over a
six week-period in February and March 2015 and involved observing a sample of
individuals and calculating the ratio that wear protective respirators in this
sample. All the individuals in a sample would be counted with one tally counter,
and the amount of individuals wearing a mask would be counted with another
tally counter. At the end of each observation the total number of people in the
sample, and the total number of people in the sample who wore mask would be
registered. From these number the ratio of individuals who chose to wear a mask
in the sample would be calculated and noted accordingly. In order to find
indicators on what source of information the sample seem to use - the Chinese
authorities or the US Consulate – the ratio of the sample that wore respirators on
days when the US Consulate recommended respirators were compared to the ratio
of the sample that chose to wear masks on days when the Chinese authorities
recommend respirators to be worn.
The observations were made in a public space that will be described in
detail in the section below. In order to maximize the chance of observing the same
individuals at each observation occasion, the observations would be done at the
same time and place each day: weekdays 8:00am-9:00am and 5:00pm-7:00pm.
The method employed is called by Webb et al. (1966, quoted in Bryman, 2008,
p.273) simple observation in that the researcher does not influence the observed
situation or participate in the setting in any way. Also the research participants
were not made aware they were being observed.
4.1.1 Research Site
17
My research was conducted at two different locations in Shanghai. The first
location being a train- and bus station in northern Shanghai (Shanghai Train
Station) with depots for long-distance busses, long-distance trains, local trains and
the Metro (subway). Individuals from a variety of socio-economic and
geographical backgrounds arrive from and depart to a range of cities across
southeast China from this hub. This location was selected because of the high
number of individuals passing through and because of the wide range of socioeconomic and geographical backgrounds these individuals belong to. The second
location comprises a Metro station in a business district in central Shanghai
(Hanzhong). This location was selected because many office workers could be
found here who assumedly live in the Shanghai area. Hence, the two locations
present individuals of different socio-economical and geographical background. I
found that the ratio of mask-usage differed between the two locations to some
extent - something that will be examined further in my analysis.
4.1.2 Sampling method
The sample was picked out by behaviour sampling where an entire group of
individuals is observed and a certain kind of behaviour recorded (Bryman, 2008).
The recorded behaviour in this study was the use of protective respirators.
Because an entire group of individuals was observed in a natural setting, choosing
a suitable location for the research was imperative in order to achieve a sample
that would be representative of the wider population. The location had to contain
an even flow of individuals and high enough amount of individuals to count. The
long-distance train- and bus station described above (Shanghai Train Station) was
selected due to it being frequented by a large number of individuals from different
socio-economic and geographical backgrounds. Approximately 2000 to 5000
individuals would be counted at each session. The large number was essential for
the results to be statistically significant due to the relatively small amount of
observed individuals wearing masks.
4.1.3 Limitations and strengths of structured observations
It is not easy conducting a study concerning a political issue in an
authoritarian state such as China. Therefore structured observation was chosen as
the main method for data collection as the researcher can then observe and record
behaviour, and as such elicit information from the research participants directly,
without compromising their safety or integrity (Bryman, 2008). Structured
observations also generate honest replies: research participants tend to change
their behaviour when they know they are being surveyed and may for example
overestimate how often they use a respirator as they feel they ought to protect
themselves more from air pollution (Bryman, 2008). Further, the method of
observation allows for participants to not be identified in any way, which is
particularly important when conducting research with a political context in an
18
authoritarian state. However, Bryman (2008) notes that since structured
observations indicate ‘if’ an observed individual do something rather than ‘why’,
the method works best when accompanied by other methods. In my study I
therefore supplemented the observations with an online poll and an in-depth
interview with a representative of an NGO in China that works with making
public environmental information derived from the government.
Despite the general advantages of the method, the observations done
for this study did not generate a generalizable result due to challenges concerning
the sampling method. As the research was conducted in a public space and the
overall size of the population of the experiment was not known, no procedure
could be employed to select a random sample. Instead behaviour sampling was
employed where an entire group is observed and a certain kind of behaviour is
recorded. Therefore no test of statistical significance, nor the chi-square test,
could be carried out meaning that we do not know to what extent the sample is
representative of the wider Chinese population. Therefore the result of this study
is not generalizable, but rather only applicable to the sample of Shanghai
commuters that were involved in the social experiment of this study.
4.1.4 Ethical issues with structured observations
Studies involving human research participants should be based, as far as
practically possible, on informed consent of the subjects according to the Ethical
Guidelines of the Social Research Association (SRA). This means that individuals
being observed should be given as much information of the research as necessary
for them to make an informed decision of whether or not they wish to participate
in the study. But because of the nature of the applied method of simple
observation, that is based on subjects not being aware they are being observed,
achieving informed consent from the research participants was not possible for
this study. There is also the issue of invasion of privacy that is linked to the issue
of informed content, because when research participants are informed of what the
research is likely to entail, there is an underlying acknowledgement that the right
of privacy will be surrendered for that limited domain (Bryman, 2008). These two
issues where taken into consideration while doing this study. However, as the
observations were conducted in the Shanghai Metro (subway) and in a railwayand bus station – both which would be regarded as public spaces - an invasion of
privacy is not deemed to have taken place, despite the lack of informed consent.
The research participants were also not identified in any way and as such their
identities were protected.
4.2 Air quality data
The air pollution measurements were collected from the website of the
governmental agency that is responsible for air quality readings in Shanghai:
19
Shanghai Environmental Monitoring Centre (SEMC). This agency records data
from eleven air pollution monitoring sites in Shanghai. Air pollution data for
comparison was collected from the webpage of the Consulate General of the
United States in Shanghai (in this paper called the US Consulate). SEMC also
publishes hourly snapshots from the Bund area of central Shanghai that were
copied and kept on file in order to illustrate the air quality of the days the research
was conducted. My own visual and physical perception of the air quality, i.e. how
far it was possible to see and how the air felt to breath, were also recorded on the
days of the research.
4.3 Survey
To supplement the quantitative research described above, an online poll was
conducted where respondents were asked to indicate how accurate they think the
Chinese authorities’ measurement of air quality is compared to those of the US
Consulate. Respondents were also asked to indicate whether they use other
methods of measuring air pollution, such as own measuring device or visual
perception. The poll was posted on WeChat - a Chinese social networking site
similar to Facebook. The aim of the poll was to measure how respondents
perceive environmental data sourced from the Chinese authorities versus the US
Consulate. The poll contained one question and four sub-questions and was
written in Chinese in order to appeal to Chinese-speaking respondents only.
Replies were noted along a five-point Likert scale in order to capture the degree
of the respondents’ consent to the four statements, which is particularly useful
when measuring values and perceptions. Participants were asked to choose from
“Very good”, “Good”, “Fair”, “Poor”, and “Very poor” for each of the four
questions. 45 valid responses were obtained from the poll, the results of which
will be examined in the Analysis section. An English version of the poll can be
found below.
Online poll
In your view, how accurate are the following air quality measures?
Use the sliders to indicate your answers.
After answering the four questions, press submit to see the statistics of the
poll.
1.
Your own visual observation:
2.
Governmental source:
3. Readings from US Consulate:
20
4. My own measuring device:
5 = Very good
4 = Good
3 = Fair
2 = Poor
1= Very poor
4.3.1 Limitations and strengths of online survey
Online surveys is an effective and convenient method to reach out to a large
amount of people – but unfortunately they tend to generate a biased sample
(Bryman, 2008). The poll conducted for this study was posted on a social
networking site by a Shanghai resident, meaning that respondents are part of the
online community, and at least some of them are probably based in the Shanghai
metropolitan area. Hence, we are looking at younger, urban and possibly better
educated and wealthier respondents than the average citizen. Therefore the results
of the poll cannot be generalized on the wider population, but rather reflects the
perceptions of individuals from the online community with these characteristics.
However, an anonymous online poll allows participants to not have to meet the
researcher face-to-face meaning identities and responses are completely
anonymous, which should encourage respondent to express their true feelings.
21
5
Analysis:
After collecting the raw materials, different methods have been introduced
to analyse the air pollution data, the ratio of mask-usage and the online poll. The
data of each method have been processed in Excel documents that are illustrated
in this section.
5.1 Mask-usage
In this study, the variable ratio of people wearing protective face-masks (the
‘mask-usage ratio’ variable) is used as a way to measure how research
participants use environmental data. The mask-usage ratio was recorded in a
spreadsheet on the days the research took place, together with reported AQI
numbers from Shanghai Environmental Monitoring Centre (SEMC) and the US
Consulate in Shanghai. An assumption was made that individuals will protect
themselves with a respirator if they perceive the air to be unhealthy. It was also
assumed that individuals would use environmental data of some kind to asses the
quality of the air as smog cannot always be seen with the naked eye. The research
was conducted in a public place and involved counting the total amount of
individuals in a group as well as the amount of individuals who wore a respirator.
A ‘mask-usage’ ratio was then calculated. As can be seen in the spreadsheet in
table 1 the mask-usage ratio was calculated as the proportion of research
participants who wore masks per 10,000 people. This method was applied because
the size of the sample varies between the different observation occasions. A total
number of 56 research participants who wore masks in a sample of 3,836 thus
equals a mask-usage ratio of 145.98 research participants per 10,000 people. The
AQI numbers taken from the websites of SEMC and the US Consulate in
Shanghai on the corresponding research occasions are noted in the columns ‘AQI
China’ and ‘AQI US’.
Samples Shanghai Train Station
Time
2015-
AQI
AQI
Mask usage /
sam
posit
China
US
10.000
ples
ive
147
-
280,3738318
214
6
312
316
369,1813804
623
23
73
147
173,7756714
633
11
02-09
201502-12
201502-15
22
2015-
130
177
157,3604061
1970
31
154
175
149,2537313
1809
27
209
227
200,0000000
3000
60
123
170
210,4874446
2708
57
62
107
162,2971286
4005
65
78
107
117,1783454
4267
50
32
84
145,9854015
3836
56
38
102
109,1830766
5129
56
36
66
115,6440732
3113
36
34
84
115,0000000
2000
23
18
74
162,7313338
3134
51
164
184
222,6027397
4088
91
110
167
198,3705278
2823
56
41
68
198,4732824
5240
104
33
93
177,2264067
2257
40
33
110
137,2212693
4081
56
22
74
154,6029515
2846
44
51
99
165,8564484
3497
58
53
134
146,9420175
2518
37
72
153
117,0117012
2222
26
95
164
166,0113587
2289
38
201
207
140,4056162
1282
18
103
154
112,2694467
2494
28
02-16
201502-16
201502-17
201502-18
201502-23
201502-24
201502-25
201502-26
201502-27
201502-27
201502-28
201503-02
201503-03
201503-05
201503-06
201503-06
201503-09
201503-11
201503-11
201503-11
201503-13
201503-14
201503-18
23
Samples Hanzhong
Time
2015-
AQI
AQI
Mask usage /
sam
posit
China
US
10.000
ples
ive
154
184
127,5992439
1058
27
110
167
132,6570425
2563
68
54
68
147,2471191
1562
46
48
76
102,7397260
3358
69
22
84
104,0744021
2258
47
33
93
141,9141914
1515
43
33
110
82,3244552
2065
34
22
74
89,2307692
1625
29
92
186
81,9061802
1343
22
44
99
117,6209498
2253
53
72
153
98,2704403
1272
25
95
164
143,5602953
1219
35
03-02
201503-03
201503-04
201503-04
201503-05
201503-06
201503-06
201503-09
201503-09
201503-11
201503-11
201503-13
Table 1: Mark-usage ratio and AQI readings from SEMC and US Consulate
in Shanghai
It can be asserted from table 1 that only a small percentage of the sample
chose to protect themselves from air pollution with a respirator. At Shanghai
Train Station the average percentage of the sample that wore respirators over all
observation occasions was 1.58% - the corresponding figure at Hanzhong was
2.26%. Drawing from previous studies on this subject and connected theories it
can by hypothesised that the low level of self-protection detected in the sample is
due to:
1)
‘Rational inattention’ (Sims 2003): individuals have a
limited capacity to pay attention and must therefore choose what to pay
attention to. Individuals might choose not to pay attention to air pollution
data, because it is not valued as high as other information.
2)
Risk perception: this concept is connected to ‘rational
inattention’ – if air quality is not perceived by individuals as important or
pertaining to risk - such as ill health - they will disregard the information.
24
It can also be noted that, on average, a higher percentage of the sample wore
masks at Hanzhong. Research show that people with high socio-economic status
tend to be more aware of air pollution problems and more willing to protect
themselves than those with low incomes (Bickerstaff and Walker, 2001 and Wang
et al., 2015). It can be hypothesised, then, that the noted difference is due to social
factors: while much of the sample at Hanzhong could be described as urban
office-workers, Shanghai Train Station is frequented by individuals from the
wider south-east China area and of generally lower socio-economic status.
5.1.1 Mask-usage in relation to air quality data
Graph 1 illustrates the relation between mask-usage at Shanghai Train
Station and AQI reported by SEMC and the US Consulate in Shanghai. Data from
Hanzhong is compiled in a separate graph (graph 2) as mask-usage was generally
higher at this location and therefore distorted the combined data (illustrated in
graph 3). The dates of the observations can be found on the X-axis. The Y-axis
shows the AQI as reported by the Chinese authorities (black line); AQI as
reported by the US Consulate (grey line); and the ratio of individuals in the
sample using respirators (dotted line).
Graph 1: US and China AQI in relation to mask-usage ratio at Shanghai
Train Station
From graph 1 it is possible to see that AQI reported by SEMC and US
Consulate do follow the same trend line, but AQI reported by the US Consulate is
25
consistently higher than SEMC’s figures – a phenomena discussed earlier in this
paper. The biggest disparity can be found at the lower AQI figures. As explained
earlier, the US authorities deem PM2.5 at lower quantities to be damaging to
human health, and therefore calculate AQI to be higher. At higher quantities of
PM2.5, the Chinese and US authorities calculate the AQI to be approximately the
same.
It is also possible to see a positive correlation between reported levels of air
pollution and ratio of facemask usage, which indicates that more people use
facemask when air pollution levels are high. It is important to establish this
correlation early in the analysis to clarify whether individuals in the sample use
respirator for reasons other than protection against air pollution. Based on the
positive correlation found in graph 1, an assumption has been made that at least a
majority of mask-users in the sample do use masks as protection against air
pollution.
Another trend that can be distinguished from graph 1 is that the maskusage ratio lags slightly behind the two AQI curves. E.g. on the 15th of February
there is a sharp dip in reported AQI levels from the Chinese authorities and US
Consulate (73 by SEMC and147 by the US Consulate) – however mask-usage
does not dip until the next day. The spike in mask-usage on the 25th of February
(ratio 146:10,000) corresponds to the increased AQI of the previous day (78 by
SEMC and 107 by US Consulate). This finding indicates that individuals in the
sample obtain the AQI information some time before making the decision to use a
mask.
Graph 2: US and China AQI in relation to mask-usage ratio at Hanzhong
Graph 2 depicting data collected at Hanzhong is not as easy to read as it
contains too few readings to be useful. The mask-usage ratio at Hanzhong Metro
was however consistently higher than the ratio at Shanghai Train Station and
putting the two readings together distorted the data to some extent – as can be
seen in graph 3 below.
26
Graph 3: US and China AQI in relation to mask-usage ratio at Shanghai
Train Station and Hanzhong
5.1.2 Mask-usage in relation to AQI China vs. AQI US
The next part of the analysis concerns what source of environmental
information the individuals using respirators seem to rely on: has their decision to
wear a respirator been based on information derived from the Chinese government
or the US Consulate? As illustrated in graph 1 the Chinese authorities consistently
report lower levels of AQI compared to the US Consulate and the trustworthiness
of the governmental information has therefore been questioned by civil society.
So does a higher ratio of the sample wear a mask when the US Consulate reports
high levels of air pollution compared to when the Chinese authorities report high
levels of air pollution? In order to find this out we need to examine whether the
mask-usage ratio has a stronger relationship with AQI readings from the Chinese
authorities or the US Consulate. The computer software SPSS was used to analyse
this relationship through the method of Pearson’s r. This is a method that indicates
how strong a relationship between two variables is on a scale from 0 to 1, where 1
indicates a perfect relationship and 0 indicates there is no relationship at all
between the two variables. The result from the analysis of the data taken at
Shanghai Train Station can be found in table 2. AQI reported by the Chinese
authorities is noted as ‘AQI China’, AQI reported by the US Consulate is noted as
‘AQI US’. ‘SH train station' stands for Shanghai Train Station.
Correlations
27
AQI
AQI
Mask
US at SH China at SH ratio at SH
train station train station train station
AQI US at
Pearson
1
.960**
.659**
SH train station Correlation
Sig.
(2.000
.000
tailed)
N
25
25
25
AQI China
Pearson
.960**
1
.681**
at
SH
train Correlation
station
Sig.
(2.000
.000
tailed)
N
25
25
25
Mask ratio
Pearson
.659**
.681**
1
at
SH
train Correlation
station
Sig.
(2.000
.000
tailed)
N
25
25
25
**. Correlation is significant at the 0.01 level (2-tailed).
Table 2: Correlation between mask-usage and AQI China versus AQI US
at Shanghai Train Station
The Pearson’s r-value of the correlation between the mask-usage ratio
variable at Shanghai Train Station and AQI US is +0.659, while the
corresponding figure for AQI China is +0.681. This means that the mask-usage
variable has a slightly stronger relationship with the AQI derived from the
Chinese authorities. The difference however is negligible and hence we cannot
ascertain from this data whether the sample used information sourced from the
Chinese authorities or the US Consulate. Table 3 below shows the same method
applied on the data derived from Hanzhong.
Correlations
AQI
US
Hanzong
AQI US at
Pearson
Hanzong
Correlation
Sig.
(2tailed)
N
AQI China
Pearson
at Hanzong
Correlation
Sig.
(2tailed)
N
AQI
Mask
at China
at ratio
at
Hanzong
Hanzong
.861**
.013
.000
.968
12
12
12
.861**
1
.307
1
.000
12
28
.332
12
12
Mask ratio
Pearson
.013
.307
1
at Hanzong
Correlation
Sig.
(2.968
.332
tailed)
N
12
12
12
**. Correlation is significant at the 0.01 level (2-tailed)
Table 3: Correlation between mask-usage and AQI China versus AQI US
at Hanzhong
The Pearson’s r-value of the correlation between the mask-usage ratio
variable at Hanzhong Metro station and AQI US is +0.013, while the
corresponding figure for AQI China is +0.307. This means that no correlation can
be distinguished between mask-usage AQI derived from the Chinese authorities
or the US Consulate, and again we cannot ascertain from this data whether the
sample used information sourced from the Chinese authorities or the US
Consulate.
5.2 Online Poll
In the online poll respondents indicated along a Likert scale how accurately
they perceived air quality measures to be from these four sources: own visual
observation; governmental source; US Consulate; and own measuring device. The
responses were scored in the following way: Very good (5) Good (4), Fair (3),
Poor (2), Very Poor (1). There is an on-going discussion on whether Likert scales
measures of concepts generate ordinal variables or ration variables (Bryman,
2008) - however, because the distance between the responses in this poll is not
equal across the range – i.e. the distance between ‘Good’ and ‘Very Good’ is not
necessarily equal to the distance between ‘Fair’ and ‘Good’ - the responses have
been treated as ordinal variables. The online poll generated 45 valid replies that
were compiled in to four frequency tables - one for each of the four sources
(figure 1).
Survey Visual perception
Frequenc
y
nt
V
1
5
alid
2
8
3
19
4
11
5
2
Total
45
29
Perce
Valid
Percent
11.1
11.1
17.8
17.8
42.2
42.2
24.4
24.4
4.4
4.4
100.0
100.0
Cumul
ative Percent
11.1
28.9
71.1
95.6
100.0
Survey China AQI
Frequen
cy
V
1
5
alid
2
13
3
15
4
8
5
4
T
45
otal
Survey US AQI
Frequen
cy
V
1
2
alid
2
6
3
18
4
15
5
4
T
45
otal
Percent
11.1
28.9
33.3
17.8
8.9
100.0
Percent
4.4
13.3
40.0
33.3
8.9
100.0
Valid
Percent
11.1
28.9
33.3
17.8
8.9
Cumulative
Percent
11.1
40.0
73.3
91.1
100.0
100.0
Valid
Percent
4.4
13.3
40.0
33.3
8.9
Cumulative
Percent
4.4
17.8
57.8
91.1
100.0
100.0
Survey Own measuring device
Frequen
Valid
Cumulative
cy
Percent Percent
Percent
V
1
3
6.7
6.7
6.7
alid
2
6
13.3
13.3
20.0
3
27
60.0
60.0
80.0
4
3
6.7
6.7
86.7
5
6
13.3
13.3
100.0
T
45
100.0
100.0
otal
Table 4: Frequency tables compiling responses to the online poll
To make the data more comprehensible, a table combining the responses to
the four sub-questions relating to different sources can be found in table 5.
Own
Source
Very
visual
Governme
US Consulate
Own
observation
ntal source
source
measuring device
4,44%
8,89%
8,89%
13,33%
30
Good
No.
2
4
4
6
Good
24,44%
17,78%
33,33%
6,67%
No.
11
8
15
3
Fair
42,22%
33,33%
40,00%
60,00%
No.
19
15
18
27
Poor
17,78%
28,89%
13,33%
13,33%
No.
8
13
6
6
Poor
11,11%
11,11%
4,44%
6,67%
No.
5
5
2
3
Total
45
45
45
45
Very
Table 5: Combined responses to the online poll
From table 5 we can see that only 4.44% of respondents indicated the
accuracy of their own visual observations as ‘Very Good’. Indeed the most
damaging particles to human heath are PM2.5 that cannot be seen with the naked
eye. A majority of respondents indicated the accuracy of ‘Own measuring device’
as ‘Fair’, which suggests that respondents do not use their own measuring devices
to a major extent. The widest range of scores can be found for the sources of the
Chinese authorities and the US Consulate. 33% of the respondents felt accuracy of
air quality readings from the Chinese authorities was ‘Fair’, and 40% of the
respondents indicated that accuracy of readings from the US Consulate was ‘Fair’.
However, 33% of respondents indicated that accuracy of the US Consulate’s air
quality readings were ‘Good’, compared to only 17.78% for the Chinese
authorities. An average score for the responses, with the value of 1 to 5, was
calculated for all the sources and the result is illustrated in bar chart 1.
Bar chart 1: Average poll results for the four sources
The average score for accuracy relating to air quality readings from the
31
Chinese authorities was 2.84, compared to 3.29 for readings from the US
Consulate. The US Consulate received the highest average score of all sources,
while readings from the Chinese authorities received the lowest average score. As
previously mentioned, online surveys tend to generate a biased sample (Bryman
2008). The respondents of this poll are likely to be younger, better educated and
wealthier than the average Chinese citizen. These characteristics also pertain to
people who tend to trust the government in China the least, according to a survey
to measure political trust in China (Zhong, 2014).
32
6
Result of analysis:
We can ascertain three points from the analysis of the data taken from the
observations made for this study:
1. Only a small percentage of the sample in this study did use respirators, even
when air pollution was reported as high
2. The trend lines drawn from AQI reported from SEMC and the US Consulate
in Shanghai follow each other closely, but readings from the US Consulate
are consistently higher
3. The mask-usage ratio trend line follows the two reported AQI trend lines;
hence, we can verify that more individuals in the sample use respirators
when reported AQI is high. It can be assumed then that respirators are
mainly used as protection against smog. It can also be assumed that the
individuals in the sample who wore a respirator based their decision to
wear a mask on environmental data of some kind, because much of the
pollution is made up by particles that are invisible to the naked eye, and
hence you can not see it
From the collected data we cannot infer whether individuals in the
sample were using environmental information derived from SEMC or the US
Consulate in Shanghai - indeed we cannot ascertain they used information derived
by either of these sources. Smog can be measured by privately owned devices, or
by individuals’ own physical perception of the air quality.
The results from the online poll show that respondents perceive AQI
readings from the US Consulate to be more accurate than readings from Chinese
authorities. It must be kept in mind however that the poll generated a limited
number of responses and the sample cannot be generalized on the wider
population. However, one can say that the findings of the poll are compatible with
the likely characteristics of the respondents: the online community is said to be
younger, urban, better educated and wealthier than the average Chinese citizen
(Bryman, 2008). These are also the characteristics of people who tend to trust the
government in China the least, according to the results of Zhong’s (2014) survey
to measure political trust in China.
33
7
Conclusion:
The research question for this paper was:
How do citizens in an authoritarian state use governmental data on air
pollution?
In order to answer this question, research was conducted to examine how a
sample of citizens in Shanghai, China, uses air pollution data. As described in the
background section, public disclosure of environmental data is surrounded by
controversy in China. Therefore the method of structured observation was
employed in order to elicit information from research participant without
compromising their safety or integrity. The results indicate that those individuals
who use respirators base their decision to do so on environmental data of some
kind, because when reported levels of pollution are high, more individuals in the
sample wear a protective mask.
What source of information the sample got their environmental information
from was also part of the analysis. Environmental data can be derived from the
Chinese authorities, the US Consulate or private measuring devices. However, the
vast media reporting on the issue, and the fact that smog cannot always be seen by
the naked eye, indicate that many Chinese citizens use information from the two
major sources of environmental data: the Chinese authorities and the US
Consulate. However, what source of information individuals in the sample base
their decision upon cannot be ascertained from the results of this study. The
online poll indicate that more trust is placed in the data derived from the US
Consulate compared to the Chinese authorities – however the sample can not be
generalized on the wider population.
The most significant result of this study was that only a small percentage
(1.1%-3.8%) of the sample chose to protect themselves from air pollution: the
vast majority did not wear a respirator even at ‘Hazardous’ or ‘Severely Polluted’
pollution levels. As such we can conclude that individuals in the sample did not
act on the disclosed air pollution data by protecting themselves from the smog to a
great extent. This paradox can be explained by ‘rational inattention’ theory (Sims,
2003) that holds that individuals might not absorb information if it is not seen as
important in relation to other issues. Further, ‘Risk perception’ theories and
previous studies on environmental awareness show that individuals can perceive
smog as a problem, but still not connect to personal health.
On a national level, previous studies on the impact of the OEI show that the
environmental information disclosure did not lead to stronger accountability or
civic engagement in environmental affairs. For information disclosure to achieve
anything more than words or numbers on a paper, the information must first
34
change the perception of the user and discloser of the information - and for this
change of mind to lead to a change of behaviour opportunity cost must not be too
high. Theories on opportunity cost hold that for something to happen the benefit
of doing something must be higher than the cost incurred of doing so. Put in
relation to the environmental data disclosure we can say that the costs of
accessing and acting on the environmental data must be less than benefits, in
order for behaviour to change. In the case of China, the political and juridical
systems might make the cost for civil society to confront powerful state and
business interest too high in relation to potential benefits of a cleaner
environment.
If the World Bank estimate (2007) is correct, then 750,000 Chinese citizens
stand to lose out on years of their lives due to air pollution in 2015 alone. In this
situation, adopting greener policies is of course paramount for the Chinese
government – however before these policies can take effect, civic engagement in
environmental affairs and public awareness of health risks associated with
pollution could save many lives.
35
8
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