Journal of Environmental Protection, 2014, 5, 1-8
Published Online January 2014 (http://www.scirp.org/journal/jep)
http://dx.doi.org/10.4236/jep.2014.51001
Air Quality Monitoring and Its Implication on the
Environmental Licensing Process in Brazil
José Carlos de Moura Xavier1,2, Wilson Cabral de Sousa Junior1
1Department of Water Resources and Environmental Sanitation, Aeronautics Institute of Technology (ITA), São José dos Campos,
Brazil; 2São Paulo State Environmen tal Company (CETESB), São Paulo, Brazil.
Received October 8th, 2013; revised November 5th, 2013 ; accep ted December 3rd, 2013
Copyright © 2014 José Carl os de Mour a Xavier, Wilson Cabral de Sousa Junior. This is an op en access article dis tributed und er the
Creative Co mmons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the
original work is properly cited. In accordance of the Creative Commons Attribution License all Copyrights © 2014 are reserved for
SCIRP and the owner of the intellectual property José Carlos de Moura Xavier, Wilson Cabral de Sousa Junior. All Copyright ©
2014 are guarded by law and by SCIRP as a guardi an.
ABSTRACT
In the stat e of Sao Paulo, Brazil, public policies reg arding the air qua lity aimed at the w elfare of the populat ion
are strongly dependent on monitoring conducted by the Sao Paulo State Environmental Company (CETESB),
which can be influenced by faulty monitors and equipment support and cut s in power supply, among others. A
research conducted from 1998 to 2008 indicated that a significant portion of the air quality automatic stations in
the state of Sao Paulo did not meet the criterion of representativeness of measurements of PM10, NO2, O3, CO
and SO2 concentrations which resulted in the classification of some municipalities as the nonattainment area, a
situation evidenced for PM 10 and O3 parameters. The network unavailability for each parameter was estimated
and co mpared with t he monit oring netw orks operat ed in Canada and the U K. This paper discusses the implica-
tions of the lack of representativeness of measurements in the environmental licensing process of pollution
sources from 2008, when by the effect of state law, municipalities have been qualified according to their air qual-
ity nonatta inment le vel.
KEYWORDS
Air Quality Monito r ing; Public Policies; Envir on mental Licensing
1. Introduction
The air q uality improve ment in ind ustrialized regio ns ca n
be achieved by knowing environmental pollutant con-
centrations, which are measured through monitoring the
quantity emitted by each source, and imposing emission
restrictions for new industries and the expansion of ex-
isting ones. In many cou ntries , this searc h is con solida ted
through the environmental license of industrial activities
and by establishing targets and timetables for the pollu-
tant reduction.
Brazil has experienced the intense industrialization
since 1960s. Howe ve r, the first pollutant measurements
carried out were restricted to monthly rates of sulfation,
settleable dust and corrosiveness [1], which are characte-
ristics of industrial acti vity. Subsequentl y, the systematic
monitoring of air quality that began in Rio de Janeiro in
1967 [2] and in Sao Paulo in 1972 [1] broadened the
spectrum encompassing vehicul ar pollutants.
In 1976, the Sao Paulo State Environmental Company
(CETESB) has started the pollution source licensing
process, which currently considers the nonattainment
level concept by specific pollutant as part of the strategy
to accept new pollution sources as well as the expansion
of existing ones [3].
The determination of nonattainment areas depends on
CETESB monitoring, which is performed by manual and
automatic networks. Its distinctive role in the establish-
ment and maintenance of public policies aimed at popu-
lation welfare is strongly dependent on the quality of
these measurements. They are routinely checked and the
inconsistent ones are disregarded for the purposes of the
value expression of a pollutant concentration. It also de-
pends on the amount of measurements that can be influ-
enced by equipment failures or supplementary services
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Air Quality Monitoring and Its Implication on the Environmental Licen s ing P r ocess in B r azil
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failures such as power and telephone networks, among
others [4].
This paper discusses the implications of measurement
amount reduction of an air quality automatic monitoring
network on the environmental licensing process of pollu-
tion sources in the state of Sao Paulo, Brazil.
2. Air Quality Monitoring in
Sao Paulo, Brazil
The air quality measurement and its result interpretation,
both considered as a synonym for monitoring, have been
carried out since 1973 by CET ESB, through manua l and
automatic networks which regularly follow the concen-
trations of air pollutants in urban areas of cities either
well industrialized or with more than 500,000 inhabi-
tants.
The dissemination of these monitoring results is made
by reporting them in the communication international
network (internet) in real time and daily bulletins. They
are also sent to the media, with a summary of atmos-
pheric po llution results in the p revio us 24 hours. I t is also
issued an annual report reflecting the air quality in the
state.
The air q uality monito ring by the CET ESB’s a uto mat-
ic network also subsidizes the licensing of new emission
sources by classifying regions in relation to the nonat-
tainment level associated with certa in p ollutants.
3. Availability of Automatic Network: Data
Failures and Repres en ta ti v en es s
The correct information of the air quality depends on
the proper operation of the automatic network com-
posed of stations with pollutant monitors and infra-
struc ture, such as co mputers and air conditioners. Proper
operation means: 1) functioning when necessary; 2)
working properly and, finally; 3) functio nin g fo r the time
desired or sufficient to maintain the data (or measure-
ment) generated accordingly to the representativeness
criterion adopted.
For the measurements performed by the automatic
network, the following representativeness criterion is
adopted [4]:
1) Hourly average valid when 75% of the measure-
ments are considered valid at the hour;
2) Daily average valid when 66.7% of the hourly av-
erage is considered valid on the day;
3) Monthly aver age valid when 66. 7% of the daily av-
erage is considered valid in the month;
4) Annual average valid when 50% of the daily aver-
age is considered valid for the four-month per io d J a nuary
to April, May to August and September to December.
The inter mittent oper ation o f a station a nd, p articularly,
of a measuring device, may disqualify its measurements,
based on previous criterion. As a result, decision
processes as the environmental licensing of a new plant
or control actions of pollutant sources may be jeopar-
dized because of this lack of data, a situation illustrated
and discussed below.
Table 1 was made based on the research conducted b y
[5] using annual reports and daily bulletins of air qualit y
issued by CETESB for the period from 1998 to 2008.
The figures r epresent per parameter and per year the
fraction of stations which were in operation and that did
not meet the representativeness criterion due to monitors
and infrastructure failures, being these data of effective
interest for the purpose of assessing the automatic net-
work availability.
Monitors and infrastructure failures should be seen in
different perspectives concerning their causes. For mon-
itors, CETESB carries out a preventative maintenance
program since long time. Maintenance tasks are per-
formed by a monitoring network dedicated team with
period ic visits to the stations f or the pro gram application,
besides testing the proper operation of the monitors. It
can be inferred that there is, therefore, a reasonable con-
trol over the failure causes, which are generally asso-
ciated with component degradation leading to a relative
regularity in the disqualification of the measured data
over the period of observation. Yet, infrastructure fail-
ures have different origins, some of them are external to
CETESB, such as telephony failures which prevent the
transmission of the measured data to the central, or even
different areas of the company itself, such as mainten-
ance (ground of stations, air conditioning equipments)
and hardware and software support (central server and
data acquisition system). Failure increasing since 2002
may be related to infrastructure aging, at least, internal to
CETESB and with the absence of a preventive mainten-
Table 1. Percentage of stations in operation that did not
meet the representativeness criterion.
Year PM10 NO2 O3 CO SO2
2008 0.205 0.174 0.161 0.067 0.333
2007 0.366 0.333 0.217 0.176 0.666
2006 0.241 0.400 0.316 0 0.455
2005 0.266 0.500 0.056 0.333 0.166
2004 0.233 0.428 0.158 0.154 0.462
2003 0.142 0.417 0.187 0.154 0.091
2002 0.153 0.182 0.062 0 0.231
2001 0.115 0.231 0 0 0
2000 0.310 0.417 0 0 0.077
1999 0.200 0.181 0.077 0 0.100
1998 0.208 0.100 0 0.100 0.444
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Air Quality Monitoring and Its Implication on the Environmental Licensing Process in Brazil
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ance program [5].
Until now, it was shown that a significant portion of
the annual environmental monitoring is jeopardized by
non-compliance to the measurement representativeness
criterion, and the main causes are monitors and infra-
structure failures. The average, minimum and maximum
percentages of unavailability at the time of observation,
per parameter, can be seen in Ta ble 2.
Comparison with other Air Quality
Monitoring Networks
It is interesting to see if the situation presented and
summarized in Table s 1 and 2 is similar to other air
quality monitoring automatic networks. A search in the
scientific and technical literature and institutional infor-
mation led to reports issued by Environment Canada,
Canada’s environmental agency, and the environmental
agencies1 of the United Kingdom (UK) about the beha-
vior of their national monitoring networks.
The environmental agency of Canada [6-13] presents
extensive diagnosis of air quality in Canada. The report
covering the years 2005 and 2006 informed the presence
of 319 automatic stations, being 236 in urban areas and
the rest in rural areas. There are 145 SO2 monitors, 79
CO, 152 NO2, 219 O3, 59 PM10, and 196 PM2.5 monitors.
Table 3 shows the fraction of stations that did not meet
the representativeness criterion from1998 to 2006. These
reports show by season, year and parameter, the monthly
and annual averages of measured concentrations and the
signal (-) when measurements did not meet the afore-
mentioned crite rion.
References [14-19] presented a detailed diagnosis of
the air quality in the UK. The 2008 report informs the
presence of 127 automatic stations, being 102 in urban
areas (18 in London) and 25 in rural areas. There are 45
SO2 monitors, 27 CO, 111 NO2, 80 O3, 77 PM10 and 53
PM2,5 monitors. T he fraction of statio ns that did no t meet
the representativeness criterion between 2003 and 2008
can be seen in Table 4.
Despite the significant difference in the number of sta-
tions and monitors, it is reasonable to compare the lack
of data representativeness (or unavailability) of monitor-
ing performed by the Canada and UK networks against
CETESB’s network in Brazil.
A simple comparison of the mean values in Table 2
with the ones in Ta b le 5 (Environment Canada and the
UK environmental agencies) leads to the conclusion that
the mean unavailability of the CETESB’s automatic
network is greater than these environmental agencies as
well as the maximum values achieved especially for NO2
and SO2.
Table 2. Average, minimum, and maximum values of CE-
TESB’s automatic network unavailability, by parameter.
Parameter Unavailability
Minimum Averag e Ma ximum
PM10 0.115 0.222 0.366
NO2 0.100 0.306 0.500
O3 0 0.112 0.360
CO 0 0.089 0.333
SO2 0 0.275 0.666
Table 3. Unavailability of the Environment Canada auto-
matic netw ork.
Year Unavailability
PM10 NO2 O3 CO SO 2
2006 0.083 0.135 0.070 0.056 0.090
2005 0.076 0.156 0.154 0.123 0.165
2004 0.035 0.072 0.119 0.105 0.097
2003 0.086 0.182 0.083 0.097 0.062
2002 0.121 0.155 0.095 0.095 0.091
2001 0.221 0.189 0.120 0.122 0.116
2000 0.162 0.182 0.140 0.176 0.095
1999 0.131 0.252 0.178 0.154 0.094
1998 0.196 0.204 0.133 0.160 0.123
Source: adap ted fro m ref eren ces [6-13].
Table 4. Unavailability of the United Kingdom automatic
ne twork.
Year Unavailability
PM10 NO2 O3 CO SO2
2008 0.169 0.081 0.051 0.074 0.044
2007 0.026 0.044 0 0.026 0.064
2006 0.031 0.045 0.059 0.063 0.039
2005 0.014 0.045 0.011 0.051 0.039
2004 0.123 0.045 0.057 0.025 0.051
2003 0.069 0.123 0.071 0.088 0.064
The figures presented in Tables 1, 3 and 4 reflect the
measurement representativeness criteria adopted by the
institutions. Tabl e 6 presents these criteria, making it
clear that CETESB and Environment Canada ones are
similar, especially in the annual average, which is re-
ported in the quality report of the institutions, by para-
meter and station.
Reports from Environment Canada and the Environ-
mental Agencies in the UK do not have the c ause s for the
1Department for Environment, Food and Rural Affairs (DEFRA); The
Welsh Assembly Government; The Scottish Gover
nment; The D
e-
partment of Environment in Northern Ireland.
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Table 5. Minimum, average and maximum values of unavailability of automatic network of Environment Canada and the
United Kingdom environmental agenc ies, as a parameter.
Parameter
Unavailability
Minimum Averag e Ma ximum
Canada UK Canada UK Canada UK
PM10 0.035 0.014 0.123 0.072 0.221 0.169
NO2 0.072 0.044 0.170 0.064 0.252 0.123
O3 0.070 0 0.121 0.042 0.178 0.071
CO 0.056 0.025 0.121 0.055 0.176 0.088
SO2 0.062 0.039 0.104 0.050 0.165 0.064
Table 6. Criteri a of measurement represe ntativ eness .
CETESB Environment Canada United Kingdom
Hourly a ver age Valid when 3/4 of measurements
are cons idered valid Not mentioned Requires that at least 3 measured aver ages of 15 min are considered valid
Daily average Valid when 2/3 of the ho ur l y
average are considered valid Calculated if 3/4 of hourly measurements are available V alid w he n 3 / 4 of t he hourly aver ag e are considered valid
Monthly
avera ge Valid when 2/ 3 of the dail y
average are considered valid Calcula ted fro m 50% das of the ho urly measurements available in the period Monthly average valid wh en 3/4 of daily average are considered valid
Annual
avera ge
Val id w hen 1/ 2 of the daily
average are c onsidered valid for
January-April, May-August and
Septemb er-December
Calcula ted fro m 50% of hurly
mea s ur e m ents av a i l a bl e in the peri o d and
the monthly average in two months of
each quarte r
The crite r ion is not cle ar . Ho w e ver, it w as
observed that an average with 58,6% of
th e v alid measurements was reported;
another average was not rep orted with
48% of the valid mea surements
Sources: reference [20]; adap ted from reference [13]; adapted from reference [19].
measurements invalidation; it is not possible, based on
these reports, a further comparison between these institu-
tions and C ET ESB.
4. Classification of Municipalities regarding
the Air Quality Nonattainment Level
Environmental licensing of pollution sources in the state
of Sao Paulo is governed by la w n˚ 997/76 and its rules,
approved by decree n˚ 8468/76 and its amendments. For
sources that emit air pollutants, licensing procedures in
force in 2009 [21-23] established 1) the criterion for de-
termining the air quality nonattainment level of the mu-
nicipalities covered by the monitoring network of CE-
TESB, 2) the qualificat ion o f this level i n terms of sever-
ity and 3) restrictions on the establishment of these
source s in cit ies classi fied a s nonattainment area or close
to the nonattainment area.
Applying the criterion, the city can be classified as at-
tainment area (ATA), close to the nonattainment area
(CNAA) or nonattainment area (NAA). The goal is to
establish a rule for environmental licensing of pollution
sources [24]. In general, one can say that for a new
source to be established in the NAA or CNA A zone, it is
necessary to prove that the industry will promote the re-
duction of emissio ns to the minimal a mount equal to that
emitted by the new source [24].
The criterion [21-23] requires measurements of the
environmental monitoring of the three years previous to
the year of the ranking, which is approved by the Envi-
ronment Secretariat [20]. It is therefore, heavily depen-
dent on the availability of the data generated by the ma-
nual and automatic monitoring stations, requiring mea-
surement periods for three consecutive years to establish
the nonattainment level. If data are available for shorter
periods, the criterion provides more restrictive values for
establishing the nonattainment level. Table 7 shows the
applicatio n of the criterion for pollutants, considerin g the
existence of measurements valid for 3, 2 and 1 year.
Cities considered NAA or CNAA by one or more re-
gulated pollutants, which are: particulate matter (which
includes P M10, black smoke and total suspended particu-
late matter), NO2, SO2, CO and O3, are presented in a
report by CETESB. There are 214 municipalities classi-
fied based on the monitoring results for the years 2006,
2007 and 2008.
4.1. Monitoring and Nonattainment Level of
PM10 Parameter
The same report shows the list of stations that measure
PM10, especially those classified as nonattainment level
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Table 7. Municipality classification criterion for pollutants with automatic monitoring.
NR nonattainment level (NA A) Close to non attainment level (C NAA) attainment level (AT A )
PM10
long term
3 AA > 50 µg∙m−3 AA > 45 µg∙m−3 AA ≤ 45 µg∙m−3
2 AA > 4 5 µg∙m−3 AA > 40 µg∙m−3 AA ≤ 40 µg∙m−3
1 AA > 4 5 µg∙m−3 AA > 4 0 µg∙m−3 AA ≤ 40 µg∙m−3
0 UN UN UN
SO2
long term
3 AA > 8 0 µg∙m−3 AA > 72 µg∙m−3 AA ≤ 72 µg∙m−3
2 AA > 7 2 µg∙m−3 AA > 6 4 µg∙m−3 AA ≤ 64 µg∙m−3
1 AA > 7 2 µg∙m−3 AA > 6 4 µg∙m−3 AA ≤ 64 µg∙m−3
0 UN UN UN
O3
short term
3 4˚ DV > 160 µg∙m−3 3˚ DV > 144 µg∙m−3 3˚ DV ≤144 µg∙m−3
2 3˚ DV > 160 µg∙m−3 2˚ DV > 144 µg∙m−3 2˚ DV ≤ 144 µg∙m−3
1 2˚ DV > 160 µg∙m−3 1˚ DV > 144 µg∙m−3 1˚ DV ≤ 144 µg∙m−3
0 2˚ DV > 160 µg∙m−3 1˚ DV > 144 µg∙m−3 UN
CO
short term
3 4˚ DV > 9 ppm 3˚ DV > 8.1 ppm 3˚ DV ≤ 8.1 ppm
2 3˚ DV > 9 ppm 2˚ DV > 8.1 ppm 2˚ DV ≤ 8.1 ppm
1 2˚ DV > 9 ppm 1˚ DV > 8.1 ppm 1˚ DV ≤ 8.1 ppm
0 2˚ DV > 9 ppm 1˚ DV > 8.1 ppm UN
NO2
long term
3 AA > 100 µg∙m−3 AA > 90 µg∙m−3 AA ≤ 90 µg∙m−3
2 AA > 9 0 µg∙m−3 AA > 8 0 µg∙m−3 AA ≤ 80 µg∙m−3
1 AA > 9 0 µg∙m−3 AA > 8 0 µg∙m−3 AA ≤ 80 µg∙m−3
0 UN UN UN
NR—number of r epresenta tive years, UN—unrated, DV—daily value, AA—arithmetic average of the annual averages; Sou rce: Adapted from reference [20].
or close to the nonattainment level, based on the criteria
of short and long terms. For this parameter 28 cities are
monitored, including Sao Paulo, with several automatic
stations. Table 8 contains the stations and consequently,
municipalities where the arithmetic average (AA) of the
valid years indicated the NAA classification when the air
quality standard was exceeded or CNAA when the aver-
age was approximated to the standard.
Out of the 49 stations, only 11 showed representative
average for three years.
In Table 8, the city of Osasco was classified as NAA
based on PM10 arithmetic average (AA) of 46 μg∙m−3. If
AA was originated from three years of valid measure-
ment s, t he municipality would be classified as CNAA. In
the case of particulate matter, only the municipality in
which there is a station measuring the parameter is clas-
sified. For the same reason, we can verify that the muni-
cipality of Sao Paulo has been classified as CNAA as a
result of the classification validated for two years or less
of Cambuci, Centro, Congonhas, Parque D. Pedro II and
Parelheir os stations.
4.2. Monitoring and Nonattainment Level of
O3 Parameter
For ozone, the report [20] presents the list of stations tha t
measure the pollutant, mostly classified as nonattainment
level or close to the nonattainment level, based on the
short term criterion. There are 34 stations located in 20
municipalities, including the Metropo litan Region of Sao
Paulo with 15, being 11 of them in Sao Paulo. Twen-
ty-seven stations showed nonattainment level to the pol-
lutant, and only si x with representative average for three
years.
Table 9 listed just some of the stations previously
mentioned, more specifically those in which the classifi-
cation brings aspects of interest for this work. In the case
of ozone, the measurements are short-term, indicated as
the one with t he hi ghest d aily va lue (DV). Fo r classifica-
tion, the four DV obtained during three years of mea-
surement are of interest, even if one or more of these
years have not been considered valid according to the
criterion.
If the values in Tab le 9 were taken from two years of
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Table 8. Classification of sub-re gion by PM10 (long-term) nonattainment level.
Statio n Yearly arithmetic avarage (µg∙m−3) AA
(µg∙m−3) NR Classification
2006 2007 2008
Osasco 45 - 47 46 2 NAA
Cubatã o —Vila P ar i si 99 108 99 102 3 NAA
Cambuci 39 46 - 43 2 CNAA
Cen tro - 45 45 45 2 CNAA
Congonhas - 46 44 45 2 CNAA
Parelheiros - - 42 42 1 C NAA
Parque D . Pedro II 40 41 - 41 2 C NAA
NR—number of r epresenta tive years, AA—ar ithmetic ave rage of the annua l averages . S ource: Adapted from referen ce [20].
Table 9. Classification of the sub-region by O3 (short term) non attainment level.
Statio n Maximum in the past three yea rs (µg∙m−3) NR Classification
1˚ DV 2˚ DV 3˚ DV 4˚ DV
Ribeirão Preto 175 169 162 160 1 NAA
Cubatã o —Centro 221 220 204 203 3 NAA
Cubatã o —Vale do Mogi 163 161 158 149 0 NAA
Cubatã o —Vila Parisi 177 176 167 145 0 NAA
Araraqua ra 1 51 132 132 126 0 CNAA
Bau ru 181 128 126 126 0 CNAA
Jaú 149 143 141 140 0 CNAA
Sao Jose do R.Preto 154 145 143 141 0 CNAA
Araçatuba 146 144 142 139 0 CNAA
NR—number of r epresenta tive years; DV—daily value. Source: Adapted from reference [20].
valid measurements, Cubatão—Vale do Mogi would be
classified as CNAA instead of NAA; Cubatão—Vila
Parisi and Ribeirão Preto would be CNAA within three
years. The municipalities of Araraquara, Bauru, Jau and
Araçatuba, within two years, and Sao Jose do Rio Preto,
three years would be classified as attainment area (ATA)
instead of CNAA. It should be noted that these last five
stations went into operation in the second quarter of 2008,
therefore they show NR = 0. More specifically, it seems
that the city of Ribeirão Preto was classified as NAA for
O3 based on one year of valid data. If the monitoring
values for this city (Ta bl e 9) were based on three years
of valid measure ments, its classi ficatio n would be CNAA,
instead of NAA.
For SO2 and NO2 parameters, the air quality standard
has not been exceeded and for measurements of CO, the
classification was based on data of three years.
5. Implications of the Measurement Number
Reduction in Environmental Licensing
The above mentioned legislation [21-23] states that the
installation of new pollution sources or expansion of ex-
isting sub-zones classified as nonattainment area (NAA)
or close to the nonattainment ar ea (CNAA) are subject to
the emissions offset, under the following conditions: 1)
the total of added emission is ≥100 t∙year−1 for par ticulate
matter (PM); 2) ≥40 t∙year−1 for nitrogen oxides (NOx); 3)
≥40 t∙year−1 for non-volatile organic compounds other
than methane (VOCs, non-CH4); 4) ≥250 t∙year−1 for
sulfur oxides (SOx); and 5) ≥100 t∙year−1 for carbon mo-
noxide (CO). The offset will be in 110% of the total pol-
lutant emissions added to the sub-region classified as
NAA and at 100% for the ones classified as CNAA.
From the above, it is concluded that the industry that
request environmental licensing in a sub-zone classified
as NAA or CNAA will have to promote environmental
offsetting if the total of new emissions added by pollutant
is greater than the values mentioned above. In case the
zone is classified within the upper range, for example,
NAA rather than CNAA due the absence of one or more
years of valid measurements, the industry is subject to
more severe compensation, that is 110% to classification
NAA or 100% for the classification CNAA. For example:
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Air Quality Monitoring and Its Implication on the Environmental Licensing Process in Brazil
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a new industry that may be installed in a nonattainment
area for particulate matter and that has a predicted emis-
sion of particulate material of 200 t∙year−1, is required to
reduce 220 t∙year−1 of that polluta nt in the nonattainment
area by compensation.
6. Conclusions
The absence of three year valid measurements from 2006
to 2008 has resulted in the classification of some muni-
cipalities in 2009 as the nonattainment area when the
proper classification would possibly be close to the non-
attainment area. Also, some cities classified as close to
the nonattainment area would be considered the attain-
ment area, a situation evidenced for parameters PM10 and
O3.
Effects in the environmental licensing of air pollutant
emission sources result from this classification, with the
need for the environmental compensation in municipali-
ties classified as the nonattainment area or close to the
nonattainment area based on two or less years of valid
meas urements.
The absence of valid measurements, which arises pre-
dominantly from monitors and infrastructure failures,
shows the need to improve the automatic network main-
tenance program in an attempt to increase the reliability
of the monitors and to reduce the stoppage due to their
component failures, increasing the ability to recover the
meas ureme nt funct ion i n a sho rter time. It is advisab le to
establish progressive targets to reduce the network aver-
age unavailability, once the initial objective to be reached
may be linked to the values of Environment Canada,
Table 5, since they result from a measurement represen-
tativeness criterion similar to the one adopted by CE-
TESB (see Table 6).
If on one hand, we can advocate the precautionary
principle which is used to adopt more restrictive values
to establish the air quality nonattainment level . Reducing
the automatic monitoring network availability has con-
tributed to the reduction of the atmospheric monitoring
effectiveness in its most important element: the imme-
diate awareness of the air quality status of monitored
zones.
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