Introduction
O3 is a secondary air pollutant formed in the troposphere via the
photo-oxidation of CO, methane (CH4), and volatile organic compounds
(VOCs) in the presence of NO and NO2 (NO+NO2=NOx) (Jenkin and Clemitshaw, 2000). The system of O3
production is not linear and is termed NOx-limited, when
O3 production increases in response to increasing NOx
emissions and termed VOC-limited when it responds positively to emissions of
VOCs (Monks et al., 2015; Pusede et al., 2015). Tropospheric O3 is
of concern to policy makers due to its adverse impacts on human health,
agricultural crops, and vegetation and also due to its role as a greenhouse
gas despite its relatively short lifetime of around 22.3±3.0 days
(Stevenson et al., 2006; IPCC, 2013; WHO, 2014; Lelieveld et al., 2015). As
the predominant source of OH, tropospheric O3 controls the lifetime
of CH4, CO, and VOCs, among many other air pollutants (Revell et al.,
2015). In polluted regions, increased levels of O3 are prevalent
during seasons with stable high-pressure systems and intense photochemical
processing of NOx and VOCs (Dentener et al., 2005; Xu et al.,
2008) with downward transport from the stratosphere of lesser
importance
(Wang et al., 2012). By contrast, the main removal processes for tropospheric
O3 are chemical loss and dry deposition (Atkinson, 2000; Jenkin and
Clemitshaw, 2000).
Tropospheric O3 increased in the Northern Hemisphere (NH) during
1950–1980 due to rapid increases in precursor emissions during the
industrialisation and economic growth of Europe and North America (NA)
(Staehelin and Schmid, 1991; Guicherit and Roemer, 2000). Since the 1990s,
reductions in O3 precursor emissions in economically developed
countries have resulted in decreases in tropospheric O3 levels
(Schultz and Rast, 2007; Butler et al., 2012; Pusede et al., 2012); however,
in some regions, increases in O3 have also been reported. For
instance, from an analysis of O3 data from 179 urban sites over
France during 1999–2012, Sicard et al. (2016) reported an increasing trend
in the annual averages of 0.14±0.19 ppbyr-1, and in the
medians of 0.13±0.22 ppbyr-1, attributed to long-range
transport and reduced O3 titration by NO due to reductions in local
NOx emissions. However, Sicard et al. (2016) also reported during
the same period that at 61 rural sites, O3 decreased in the annual
averages by 0.12±0.21 ppbyr-1 and in the medians by 0.09±0.22 ppbyr-1.
In the US and Canada, O3 levels have decreased substantially at
different metrics during the last 2 decades in response to more stringent
emissions controls focused on on-road and industrial sources. In the greater
area of Toronto from 2000 to 2012, O3 levels decreased at urban
sites by approximately 0.4 % yr-1, and at suburban sites by
approximately 1.1 % yr-1, as a consequence of a reduction in
the midday averages of NO2 of 5.8–6.4 % yr-1 and in
the VOC reactivity of 9.3 % yr-1 (Pugliese et al., 2014).
Emissions estimates suggest an overall national scale decrease during
1980–2008 in US NOx and VOCs emissions of 40 and 47 %,
respectively, with city-to-city variability (EPA, 2009; Xing et al., 2013).
Lefohn et al. (2010) reported that for 12 US major metropolitan areas, the
O3 US EPA exposure metrics of the annual second highest 1 h average
and the annual fourth highest daily maximum 8 h average decreased during
1980–2008 at 87 and 71 % of the monitoring sites evaluated,
respectively. However, Lefohn et al. (2010) observed an increase in the
lower- and mid-O3 mixing ratios in response to decreased titration
by NO. More recently, Simon et al. (2015) assessed changes in the 1 h
average O3 mixing ratios at around 1400 sites across the US between
1998 and 2013, using the 5th, 25th, 50th, 75th, and 95th percentiles and the maximum
daily 8 h average. Overall, Simon et al. (2015) observed increases at the
lower end of the O3 data distribution of
0.1–1 ppbyr-1, mostly in urban and suburban areas, whereas
O3 decreased at the upper end of the data distribution between
1 and 2 ppbyr-1 in less urbanised areas. Such changes were
associated with the implementation of control strategies within the US, such as the NOx SIP call, and
tighter point and vehicle emissions standards to
abate peak O3 mixing ratios.
Air quality limit values stated in Mexican legislation.
Pollutant
Mexican official standard
Limit valuea
O3 (ppb)
NOM-020-SSA1-1993
110 (1 h), 80 (8 h)b, c
NOM-020-SSA1-2014
95 (1 h), 70 (8 h)b, c
PM10 (µgm-3)
NOM-025-SSA1-1993
75 (24 h), 40 (1 yr)
NOM-025-SSA1-2014
50 (24 h), 35 (1 yr)
PM2.5 (µgm-3)
NOM-025-SSA1-1993
45 (24 h), 12 (1 yr)
NOM-025-SSA1-2014
30 (24 h), 10 (1 yr)
CO (ppm)
NOM-02-SSA1-1993
11 (8 h)c
NO2 (ppm)
NOM-023-SSA1 -1993
0.21 (1 h)
a Average period. b Not to be exceeded more than four times in a calendar year.
c Running average.
In Mexico, studies of long-term trends in O3 have focused on the Mexico City metropolitan area (MCMA) (Molina and
Molina, 2004; Jaimes et al., 2012; Rodríguez et al., 2016), with reports of a decrease in O3 annual averages of
ca. 33 % during the last 2 decades (Parrish et al., 2011; SEDEMA, 2016a). O3 has received less consideration
in
other large metropolitan areas, where Mexican air quality standards are frequently exceeded (Table 1). Indeed, since 2000,
recorded O3 mixing ratios have exceeded Mexican official standards for 1 h average (110 ppb) and
8 h running average (80 ppb) O3 by more than 50 % in the Guadalajara metropolitan area (GMA, the second most populated
city) and in the Monterrey metropolitan area (MMA, the third most populated city) (INE, 2011; SEMARNAT, 2015). To date, only
Benítez-García et al. (2014) have addressed changes in ambient O3 in the GMA and MMA during 2000–2011,
reporting an increase in O3 annual averages of around 47 and 42 %, respectively. However, it should be noted that
the ordinary linear regression analysis used by Benítez-García et al. (2014) may be biased by extreme values and is
therefore not suitable to determine long-term O3 trends with significant confidence.
To improve air quality, the Mexican government has introduced several
initiatives to reduce primary pollutant emissions, with emissions estimates
reported in the Mexican National Emissions Inventory (NEI). The NEI suggests
that from 1999 to 2008, anthropogenic NOx emissions decreased in
the MCMA by 3.8 % yr-1, but increased in the GMA and the MMA
by 1.9 and 4.0 % yr-1, respectively (Fig. S1 in the Supplement) (SEMARNAT,
2006, 2011, 2014). These NEI NOx emissions estimates agree with
the decrease for the MCMA of 1.7 % yr-1 in the NO2
vertical column density during 2005–2014 reported by Duncan et al. (2016),
but disagree for the GMA and the MMA where decreases of
2.7 % yr-1 and of 0.3 % yr-1, respectively, are
reported. Similarly, Boersma et al. (2008) observed that NOx
emissions over Mexico derived from NO2 satellite observations were
higher by a factor of 1.5–2.5 times than bottom-up emissions estimates, which
were lower by a factor of 1.6–1.8 than data reported in the NEI 1999 base year.
The NEI anthropogenic VOC emissions estimates suggest a decrease in the MMA
by 0.2 % yr-1 but increases in the MCMA and in the GMA by
2.7 % yr-1 and by 3.2 % yr-1, respectively
(Fig. S1) (SEMARNAT, 2006, 2011, 2014). However, as for NOx, NEI
trends in VOCs disagree with existing reports for average VOC decreases
within the MCMA (Arriaga-colina et al., 2004; Garzón et al., 2015).
Local authorities have developed local emissions inventories for the MCMA and the MMA, although only for the MCMA have the inventories
been compiled with a frequency of 2 years since 1996 (SEDEMA, 1999, 2001, 2003, 2004, 2006, 2008, 2010, 2012, 2014, 2016b;
SDS, 2015). The accuracy of the MCMA emissions inventories has also been assessed during several field campaigns. For instance,
during the MCMA 2002–2003 campaign, Velasco et al. (2007) observed an overestimation in the 1998 inventory for VOC emissions of
alkenes and aromatics but an underestimation in the contribution of some alkanes. By contrast, for the 2002 MCMA inventory, Lei
et al. (2007) reported an underestimation in the VOC total emissions of around 65 %, based on a simulation of an O3
episode that occurred in 2003 within the MCMA. Therefore, since these emissions estimates are used to predict future air quality and
to design clean air policies, it is imperative to examine the results of the policies implemented to control emissions of
O3 precursors.
To our knowledge, no previous study has addressed trends in O3 and
odd oxygen in urban areas of Mexico. In this study, we describe trends in
ground-level O3 within the MMA and its response to changes in
precursor emissions during 1993–2014. Long-term and high-frequency
measurements of O3 were recorded at five air quality monitoring
stations evenly distributed within the MMA. In order to better assess
photochemical production of O3, odd oxygen defined as
([Ox]=[O3]+[NO2]) was also considered, as
O3 and NO2 are rapidly interconverted. Diurnal and annual
cycles of O3 and Ox are used to interpret net
O3 production within the MMA. We show that air mass origin
strongly influences the O3 annual increases. The trends in
O3, Ox, and precursor emissions are compared with those
observed within the MCMA and GMA. Finally, we describe how NEI emissions
estimates for NOx and VOCs disagree in the trend magnitudes with
ground-based NOx and VOCs measurements made in the urban areas
studied here.
This paper is organised as follows: Sect. 2 presents the data quality and
methodology used to derive the different trends presented. Section 3
describes in detail the O3 and Ox diurnal and annual
cycles and annually and seasonally averaged trends. Section 4 discusses the
origin of the O3 and Ox diurnal variations and trends
in the light of changes in precursor emissions. Finally, Sect. 5 provides
some conclusions regarding the trends observed in the urban areas studied.
(a) The MMA, MCMA, and GMA in the national context. (b) Topography of the MMA and distribution of the five monitoring sites over the area. (c) The five monitoring sites in relation to primary and secondary motorways, industries, and major residential areas. The red arrows show the predominant wind direction at each site from 1993 to 2014.
Site description and location of the five monitoring sites within the MMA.
Site
Code
Location
Elevation
Site description
(m a.s.l.)
Guadalupe
GPE
25∘40.110′ N,
492
Urban background site in the La Pastora park, surrounded by
100∘14.907′ W
a highly populated area, 450 m from Pablo Rivas Rd.
San Nicolás
SNN
25∘44.727′ N
476
Urban site surrounded by a large number of industries and residential
100∘15.301′ W
areas, 450 m from Juan Diego Díaz de Berlagna Rd.
Obispado
OBI
25∘40.561′ N,
560
Urban site near the city centre of MMA, 250 m from José
100∘20.314′ W
Eleuterio González Rd. and 250 m from Antonio L. Rodríguez Rd.
San Bernabé
SNB
25∘45.415′ N,
571
Urban site in a residential area downwind of an industrial area
100∘21.949′ W
with high traffic volume, 140 m from Aztlán Rd.
Santa Catarina
STA
25∘40.542′ N,
679
Urban site downwind of industrial sources, 200 m from
100∘27.901′ W
Manuel Ordóñez Rd.
Methodology
Monitoring of O3 in the Monterrey metropolitan area (MMA)
The MMA (25∘40′ N, 100∘20′ W) is located around 720 km N of Mexico City, some
230 km S of the US border in the state of Nuevo León (Fig. 1a). It lies at an average altitude of 500 ma.s.l. and is surrounded by mountains to the S and W, with flat terrain to the NE (Fig. 1b). The MMA is the largest urban area in
northern Mexico at around 4030 km2 and is the third most populous area in the country with 4.16 million inhabitants, which
in 2010, comprised 88 % of the population of Nuevo León State (INEGI, 2010). It is the second most important industrial area
in Mexico and has the highest gross domestic product per capita (Fig. 1c). Although the weather changes rapidly on a daily
timescale, the climate is semi-arid with an annual average rainfall of 590 mm and an annual average temperature of
25.0 ∘C with hot summers and mild winters (ProAire-AMM, 2008; SMN, 2016).
Within the MMA, tropospheric O3, six additional air pollutants (CO,
NO, NO2, SO2, PM10, and PM2.5), and seven
meteorological parameters (wind speed (WS), wind direction (WD), temperature
(Temp), rainfall, solar radiation (SR), relative humidity (RH), and pressure)
have been monitored continuously, with data summarised as hourly averages,
since November 1992 at five stations that form part of the Integral
Environmental Monitoring System (SIMA) of the Nuevo León State Government
(Table 2; SDS, 2016). From November 1992 to April 2003, and in accordance
with EPA EQOA-0880–047, Thermo Environmental Instruments Inc. (TEI) model 49 UV
photometric analysers were used to measure O3 with a stated precision
of less than ±2ppb O3 and a detection limit of
2 ppb O3. Similarly, in accordance with RFNA-1289-074, TEI
model 42 chemiluminescence detectors were used to measure
NO-NO2-NOx with a stated precision of less than
±0.5ppb NO and a detection limit of 0.5 ppb NO.
In May 2003, replacement TEI model 49C O3 and model 42C
NO-NO2-NOx analysers were operated as above, with a stated
precision of better than ±1ppb O3 and
±0.4ppb NO and detection limits of
1 ppb O3 and 0.4 ppb NO. To rule out
instrumentation influences on the air pollutant trends determined, long-term
trends based on annual averages were compared with those derived using 3-year
running averages, in accordance with Parrish et al. (2011) and Akimoto
et al. (2015) (Supplement Sect. S1.1; Fig. S2). Calibration, maintenance
procedures,
and quality assurance/quality control (QA/QC) followed protocols established
in the Mexican standards NOM-036-SEMARNAT-1993 and NOM-156-SEMARNAT-2012. The
SIMA data set has been validated by the Research Division of Air Quality of
the Secretariat of Environment and Natural Resources (SEMARNAT). The
monitoring of O3 and other air pollutants in the MCMA and the GMA
is detailed in the Supplement Sect. S1.2–3.
NEI data
NEI data for estimated NOx and VOC emissions for the 1999,
2005, and 2008 base years were obtained from the SEMARNAT website
(http://sinea.semarnat.gob.mx). The data comprised emissions sources
(mobile, point, area, and natural) and air pollutants (NOx, VOCs,
SOx, CO, PM2.5, and PM10) on national, state,
and municipality scales. The NEI emissions estimates are developed in
accordance with the Manual for the Emission Inventories Program of Mexico
(Radian, 2000), which is based on the US EPA AP-42 emissions factors
categorisation (EPA, 1995). The emissions factors are regionalised for each
Mexican state, based upon on-site measurements and survey information.
Updates to the emissions factors have been conducted for each released NEI,
although no changes in the methodology were implemented between the 1999 and
2008 base years. Overall, the mobile emissions were estimated using the
MOBILE6-Mexico model (EPA, 2003). The emissions from point sources were
derived using the annual operation reports submitted to SEMARNAT. The emissions from area sources were obtained using the
categorisation of Mexican area sources and the regionalised AP-42 emissions
factors.
The MCMA emissions inventories have been developed with a 2-year frequency since 1996 and were obtained from the MCMA
Environment Secretariat website (http://www.aire.cdmx.gob.mx/). The methodology used to construct the MCMA
inventory
estimates is consistent with that used in the NEI (SEDEMA, 2016a), which is based on the AP-42 EPA emissions factors. However, more
speciated emissions factors have been developed in each released version, considering updates in the local industrial activity,
survey information, and field measurement campaigns. To date, the only significant change in the methodology is the replacement of
the Mobile6-Mexico model with the MOVES model to obtain the 2014 base year mobile emissions (SEDEMA, 2016b). As for the MCMA
inventories, more speciated emissions factors than those contained in the NEI were developed to produce the MMA emissions inventory
2013 base year (SDS, 2015); although, estimates of mobile emissions were obtained with the Mobile6-Mexico model (EPA, 2003).
Analytical methods
SIMA, SIMAT (Atmospheric Monitoring System of the MCMA), and SIMAJ (Atmospheric Monitoring System of the GMA) instrumentation
recorded O3 data every minute, which were then validated and archived as 1 h averages. Total SIMA O3 data
capture by year and site is shown in Fig. S3. Data capture averaged during 1993–2014 ranged from 82.6 % at GPE (see Table 2 for all site abbreviations) to 93.3 %
at SNB, with data capture <50 % during 1998–2000 at GPE, in 1998 at SNN, and in 1999 at OBI. A threshold of 75 % data
capture was defined to consider data valid and representative (ProAire-MMA, 2008; Zellweger et al., 2009; Wilson et al.,
2012). All data were processed with hourly averages used to determine daily averages, which were used to calculate monthly
averages, from which yearly averages were obtained.
Data analysis methods
The SIMA, SIMAT, and SIMAJ O3 data sets were analysed extensively using the openair package v1.1–4 (Carslaw
and Ropkins, 2012) for R software v3.1.2 (R Core Team, 2013). In this study, the openair functions windRose,
timeVariation, and TheilSen were used to analyse air pollution data. Briefly, the windRose summarises wind speed and wind direction
by a given timescale, with proportional paddles representing the percentage of wind occurrence from a certain angle and speed
range. The timeVariation function was used to obtain normalised daily cycles by season, and weekly cycles, with the 95 %
confidence intervals in the cycles calculated from bootstrap resampling, which accounts for better estimations for non-normally
distributed data (Carslaw, 2015). Finally, long-term trends in air pollutants in the MCMA, GMA, and MMA were computed with the
TheilSen function, which is based on the non-parametric Theil-Sen method (Carslaw, 2015; and references therein). The Theil-Sen
estimate of the slope is the median of all slopes calculated for a given n number of x,y pairs, while the regression
parameters, confidence intervals, and statistical significance are determined through bootstrap resampling. It yields accurate
confidence intervals despite the data distribution and heteroscedasticity and is also resistant to outliers.
The trends computed with openair were contrasted with those calculated using the MAKESENS 1.0 macro (Salmi et al., 2002)
as follows. Firstly, the presence of a monotonic trend was tested with the non-parametric Mann–Kendall test. For the MCMA, GMA, and
MMA, the available yearly data are n>10; hence, positive values in the Z parameter correspond to positive trends and vice-versa
for negative values of Z. The significance of the estimated trend was tested at α=0.001, 0.01, 0.05, and 0.1 using
a two-tailed test. Secondly, slopes of linear trends were calculated with the non-parametric Sen's method, which assumes linear
trends, with a Q slope and a B intercept. To calculate Q, first the slopes of all data values were calculated in pairs,
with the Sen's estimator slope as the median of all calculated slopes. Finally, 100(1-α) % two-sided confidence
intervals about the slope estimate were obtained based on a normal distribution. Comparisons of estimated trends from both
approaches are shown in the Supplement Sect. S1.4 (Fig. S4).
The O3 and other air pollutant time series were decomposed into trend, seasonal, and residual components using the
seasonal trend decomposition technique (STL; Cleveland et al., 1990). STL consists of two recursive procedures: an inner loop
nested inside an outer loop, assuming measurements of xi (independent) and yi (dependent) for i=1 to n. The seasonal
and trend components are updated once in each pass through the inner loop; each complete run of the inner loop consists of
n(i) such passes. Each pass of the outer loop consists of the inner loop followed by a computation of the robustness weights,
which are used in the following run of the inner loop to minimise the influence of transient and aberrant behaviour on the trend
and seasonal components. The initial pass of the outer loop is performed with all robustness weights equal to 1, followed by
n(0) passes of the outer loop. The Kalman smoother (KS) was used to provide minimum-variance unbiased linear estimations of
observations and to impute missing data to satisfy the STL (Reinsel, 1997; Durbin and Koopman, 2012; Carslaw, 2015). Overall,
statistical seasonal autoregressive and moving averages with annual seasonal components were employed. Statistical analyses were
carried out with SPSS 19.0.
In order to carry out seasonal analyses of data, seasons were defined according to temperature records in the NH, as described
previously (Hernández-Paniagua et al., 2015): winter (December–February), spring (March–May), summer (June–August), and autumn
(September–November). Wind-sector analyses of data were performed by defining eight wind sectors each of 45∘ starting from
0±22.5∘. The lower bound of each sector was established by adding 0.5∘ to avoid data duplicity. Data were
assigned to a calm sector when wind speed was ≤0.36 kmh-1 (0.1 ms-1). To assess regional transport,
air mass back trajectories (AMBTs) were calculated using the HYSPLIT model v.4 (NOAA Air Resources Laboratory (ARL); Stein et al.,
2015), with the Global NOAA NCEP/NCAR reanalysis data files on a latitude–longitude grid of 2.5∘, downloaded from the
NOAA ARL website (http://ready.arl.noaa.gov/HYSPLIT.php). HYSPLIT frequency plots of 96 h AMBTs were constructed for every
6 h during the year 2014 with an arrival altitude of 100 ma.g.l.
Frequency of counts of measured wind direction occurrence by season and site within the MMA during 1993–2014.
Seasonal average daily profiles for O3, Ox,
NOx, NO, NO2, and SR within the MMA during 1993–2014. The
shading shows the 95 % confidence intervals of the average.
Results
Wind occurrence at the MMA
The MMA is highly influenced by easterly anticyclonic air masses that arrive from the Gulf of Mexico, especially during spring
and summer (Fig. S5). Figure 2 shows the frequency count of 1 h averages of wind direction by site and season within the MMA
during 1993–2014. At all sites, apart from OBI, the predominant wind direction is clearly E, which occurs between 35 and 58 % of
the time depending on season. Easterly air masses are augmented by emissions from the industrial area E of the MMA, which are
transported across the urban core and prevented from dispersing by the mountains located S-SW of the MMA. On average, the highest
wind speeds are observed during summer at all sites. By contrast, calm winds of ≤0.36 kmh-1
(0.1 ms-1) occurred less than 2 % of the time at all sites, most frequently in winter, and least frequently in
summer.
Time series in O3 and Ox recorded within the MMA during 1993–2014
Within the MMA, the highest O3 mixing ratios (1 h averages) are typically observed between April and September, whereas
the lowest values are usually recorded between December and January (winter) (Fig. S6). Table S1 summarises the minimum, maximum,
average (mean), and median hourly O3 mixing ratios recorded during 1993–2014. The highest O3 mixing ratios
recorded were 186 ppb at GPE in 1997, 146 ppb at SNN in 2004, and 224 ppb at SNB in 2001. At OBI and STA,
the highest O3 mixing ratios were both recorded on 2 June 1993: 182 ppb at 12:00 CDT at OBI, and 183 ppb
at 13:00 CDT at STA, during the occurrence of E winds. Note that all times below are given in CDT. Annual O3 averages
varied from 14±14 ppb at OBI in 2001 to 32±23 ppb at SNB in 1993, whereas O3 annual medians
ranged from 10 ppb at OBI in 2001 to 28 ppb at SNN in 1993.
Reaction with O3 rapidly converts NO to NO2, and therefore
mixing ratios of odd oxygen (Ox=O3+NO2) were
calculated to account for O3 stored as NO2 for each hour
during 1993–2014 at the five sites within the MMA (Table S2; Fig. S7). Minimum
values of Ox ranged from 2 ppb, observed at all sites
during 1993–2014 to 13 ppb at OBI in 2007. Maximum values of
Ox ranged from 99 ppb at SNN in 2002 to 330 at OBI in
1993. Ox annual averages varied from 23±17 ppb at
SNN in 2002 to 51±27 ppb at OBI and at STA in 2001 and 2006,
respectively, whereas Ox annual medians ranged from
21 ppb at SNB and SNN, in 2001 and 2002, respectively, to
46 ppb at OBI and STA in 2001 and 2006, respectively. It is clear
that the highest O3 and Ox mixing ratios were recorded
when control of precursor emissions of VOCs and NOx were less
stringent than subsequently.
Seasonal Ox de-trended daily profiles within the MMA
during 1993–2014. De-trended Ox daily cycles were constructed by
subtracting daily averages from hourly averages to remove the impact of
long-term trends.
Diurnal variations in O3 and Ox within the MMA
Here, O3 diurnal variations were used to assess changes in the net
O3 production. Figure 3 shows daily profiles by season of
O3, Ox, NO, NO2, NOx, and SR
averaged over the five sites within the MMA. O3 generally dips during
the morning rush hour due to titration with NO and mirrors the increase in
NO2, which occurs around 07:00 in spring and summer and around 08:00
in autumn and winter. The 1 h difference in the O3 dip derives
from the change to daylight saving time during spring and summer.
O3 generally peaks during the enhanced photochemical period, around
13:00 in spring, 12:00 in summer (coincident with SR), and about 14:00 in
autumn and winter. Similar profiles are observed for O3 in all
seasons, being negatively correlated with NO2 (r=0.93 (winter) to
r=0.97 (summer); p<0.05), due to the rapid photolysis of NO2.
Diurnal cycles of Ox behave as O3, with the lowest values
before the morning rush hour and the largest between midday (summer) and
15:00 (winter). During the daytime, Ox and O3 diurnal
cycles are strongly correlated in all seasons, ranging from r=0.97 in
winter to r=0.99 in autumn (p<0.05), which suggests net O3
production during the daytime.
Ox amplitude values (AVd's) derived from normalised daily
cycles were used as a proxy to assess differences in the net O3
production from site to site within the MMA. The normalised daily cycles were
constructed by subtracting daily averages from hourly averages. Figure 4
shows normalised Ox daily cycles. The lowest AVd's in
Ox occur in winter consistent with reduced SR and low photolysis
rates, with the largest values observed in summer. It is clear that during
the year, the largest AVd's are recorded at sites downwind of
industrial emissions sources, in particular at STA, while the lowest
AVd's are observed at sites upwind. The larger AVd's at
downwind sites are interpreted to indicate higher net O3
production, derived from the occurrence of photochemical processed air masses
from the E sector. The AVd's at upwind sites are less affected by
emissions from the MMA and especially the industrial area.
(a) Annual cycles of O3, temperature, rainfall, RH, and SR constructed by averaging records from 1993 to 2014 for a 1-year period. (b). Trends in AVs of O3 recorded at the five monitoring sites within the MMA from 1993 to 2014. The decline in AVs observed is due to the economic crisis experienced in Mexico during 1994–1996, followed by persistent increases in AVs since 1998. (c) Annual rates of change in O3 AVs by site before and after the 1994–1996 economic crisis.
Annual cycles of O3 and Ox within the MMA
Annual variations in O3 and Ox are correlated
positively with the seasonality of temperature, RH, and SR (Camalier et al.,
2007; Zheng et al., 2007). Annual average cycles for those meteorological
variables. O3 and Ox were constructed by averaging
monthly averages for the same month during the studied period. Figure 5a
shows that O3 exhibits the maxima during spring and minima in
winter, with a downward peak in early autumn, a behavioural characteristic of
tropospheric O3 in the NH. Ox peaks in spring and dips
in summer; although it is evident that NOx emissions lead to
apparently similar Ox levels in winter and spring despite the
decrease in O3 levels. A correlation analysis among monthly
averages for both O3 and Ox with temperature, rainfall,
RH, and SR revealed that the strongest relationship was between O3
and SR (r=0.72, p<0.001; Fig. 5a), with a relationship evident with
Ox.
The seasonal amplitude value (AVs) provide insight into
inter-annual variations in net O3 production in response to changes
in precursor emissions, meteorology, and O3 chemistry. The seasonal
cycles in O3 during 1993–2014 were determined by filtering monthly
averages with the STL technique (Cleveland et al., 1990) (Fig. S8).
O3 AVss were calculated as the difference from peak to trough
(spring peak). An average O3 AVs of 15.1±2.97
(1σ) ppb was calculated from 1993 to 2014 within the MMA, with the
lowest O3 AVs of 10.3 ppb determined in 1998, and
the largest O3 AVs of 19.0 ppb observed in 2014.
Figure 5b shows that O3 AVs decreased significantly at
all sites between 1993 and 1997–1998, at rates from
0.78 ppb O3 yr-1 at GPE to
2.28 ppb O3 yr-1 at SNN (Fig. 5c). O3
AVs's have increased constantly (p<0.05) at all sites since 1998,
ranging from 0.90 ppb O3 yr-1 at GPE to
0.75 ppb O3 yr-1 at SNN. Ox
AVss exhibited no discernible trends at all sites for the whole
studied period, although SNN showed a significant (p<0.05) decline during
1993–2001 (1.5 ppbyr-1) and STA showed an increase during
2004–2010 (1.3 ppbyr-1). The trends in Ox follow
those observed for NOx at SNN and STA during 1993–2014, which
indicates that nearby industrial emissions have a significant contribution to
the observed Ox levels within the MMA.
Seasonal trends in O3 within the MMA during 1993–2014. Each data point represents the average of the 3-month period that defines the season. The continuous lines show the Sen trend.
Results for O3 and Ox long-term trends
expressed in ppb yr-1 for 1993–2014 at the five sites within the MMA
by season.
Site
Period
Ozone (O3)
Odd oxygen (Ox=O3+NO2)
ppbyr-1
%yr-1
Significance
ppbyr-1
%yr-1
Significance
GPE
Annual
0.21
0.78
b
0.31
0.80
c
Spring
0.24
0.73
b
0.32
0.69
b
Summer
0.30
1.16
b
0.38
1.18
b
Autumn
0.14
0.53
0.25
0.62
Winter
0.12
0.53
0.14
0.33
b
SNN
Annual
0.33
1.40
d
0.45
1.25
b
Spring
0.39
1.38
b
0.49
1.22
b
Summer
0.47
2.24
b
0.58
1.87
d
Autumn
0.41
1.96
b
0.65
1.94
b
Winter
0.14
0.68
0.23
0.58
a
OBI
Annual
0.30
1.29
b
-0.17
-0.35
Spring
0.43
1.56
b
0.02
0.03
b
Summer
0.26
0.98
b
-0.04
-0.09
Autumn
0.29
1.33
a
-0.66
-1.15
Winter
0.25
1.46
-0.28
-0.53
SNB
Annual
0.19
0.65
a
0.61
1.66
c
Spring
0.37
1.07
a
0.67
1.65
a
Summer
0.31
1.06
d
0.66
2.17
d
Autumn
0.19
0.64
0.60
1.61
a
Winter
0.02
0.07
0.47
1.12
a
STA
Annual
0.01
0.01
-0.15
-0.28
Spring
-0.04
-0.11
-0.01
-0.02
Summer
0.09
0.28
0.13
0.27
Autumn
0.00
0.00
-0.22
-0.41
Winter
-0.09
-0.43
-0.63
-1.15
b
a Level of significance p<0.1.
b Level of significance p<0.05.
c Level of significance p<0.001.
d Level of significance p<0.001.
Long-term trends in O3 and Ox within the MMA during 1993–2014
Quantifying the absolute changes in ground-level O3 in response to
trends in its precursor emissions is crucial to evaluate the impacts of air
quality control (Parrish et al., 2009; Simon et al., 2015). The growing
economy within the MMA has increased O3 precursor emissions from
point and area sources due to the limited emissions control programs (INEGI,
2015; SDS, 2015). Moreover, predominant E-SE winds throughout the year
transport primary pollutants and their oxidised products downwind from the
industrial area, which can offset reductions in emissions from other sources.
Here, to characterise changes in net O3 production during
1993–2014 within the MMA in response to changes in its precursor emissions,
long-term trends for daytime (06:00–18:00 CDT) O3 and
Ox measurements were derived by averaging data in seasonal
periods. Seasonal averaging was used to minimise variability inherent in
longer-term averages and the de-seasonalisation process avoids confounding
overall trends, especially when seasons exhibit opposite trends (Parrish
et al., 2009).
Figure 6 shows seasonal trends in O3 within the MMA, and Table 3 summarises the parameterisation of the
trends. Significant increases (p<0.1) in O3 are observed at all sites, apart from STA, in spring and summer, while in
autumn, O3 increases significantly only at SNN and SNB. The increases in O3 range from
0.26 ppbyr-1 in spring at OBI to 0.47 ppbyr-1 in summer at SNN. Overall, the lowest O3 growth
rates are observed at the urban background GPE site, whereas the largest ones are at the industrial SNN site. It is worth noting
that only SNN and OBI exhibit significant increases in autumn, despite a decrease in the frequency of high wind speeds (>20 kmh-1). The existence of significant trends at all sites during spring–summer, except for OBI, is consistent with
the downwind transport of industrial emissions and the high frequency of photochemical processed air masses with NE-E-SE origin,
where the industrial area is located (Fig. S9).
Seasonal trends in Ox within the MMA during 1993–2014.
Each data point represents the average of the 3-month period that defines
the season. The continuous lines show the Sen trend.
Seasonal average diurnal cycles of O3, Ox, and
NOx during 1993–2014 for the MCMA and the MMA, and between
1996 and 2014 for the GMA. The shading shows the 95 % confidence intervals
of the average, calculated through bootstrap resampling (Carslaw, 2015).
Seasonal trends in Ox are shown in Fig. 7, with the parameters of
the trends listed in Table 3. Consistent with the seasonal O3
trends observed, significant increases (p<0.1) in Ox within
the MMA are determined in spring at all sites except for STA and range from
0.02 ppbyr-1 at OBI to 0.67 ppbyr-1 at SNB. It is
worth noting that the industrial SNN and SNB sites show significant
increases in Ox in all seasons, with the lowest growth rates in
winter and the largest in summer and spring. Moreover, STA
exhibits the only significant decrease in Ox of
0.63 ppbyr-1 during winter. As for O3, the
Ox increasing trends are consistent with the transport of primary
emissions during the high occurrence of NE-E-SE air masses at WS >10 kmh-1, which is highlighted during the photochemical season
(April–September). Furthermore, the small shift in wind direction at STA to
NW during winter coincides with the only observed decrease in net
O3 production within the MMA, which confirms that O3
precursors are emitted E of the MMA. This also makes evident that increasing
upwind industrial emissions have offset reductions in emissions from on-road
sources as revealed by the decline in NOx evident at OBI.
Comparison of MMA O3 and Ox weekly profiles with those in MCMA and GMA
O3 production varies from city to city in response to local
NOx and VOC emissions. Assessment of weekly profiles of
O3 and Ox may provide insights into the geographic
response in net O3 production to diurnal variations in precursor
emissions. Hourly O3 and Ox averages were used to
construct weekday and weekend average profiles for the MCMA from 1993 to
2014, and for the GMA from 1996 to 2014. Figure 8 compares weekly
O3 and Ox profiles by season within the MMA with those
for the MCMA and GMA. In each case, and consistent with observations in other
major urban areas of NA, the lowest O3 mixing ratios occur during
the morning rush hour due to O3 titration with NO emitted from
on-road sources, whereas peak values of O3 are apparent after
mid-day during periods of enhanced SR (Stephens et al., 2008; Jaimes-Palomera
et al., 2016). It should be noted that the peak value of O3 for the
GMA in winter and spring occurs an hour or so earlier than for the MMA and
MCMA, which is consistent with higher VOC/NOx emissions
ratios in the GMA (Kanda et al., 2016). As might be anticipated, larger
AVd's of 76.9±1.6 ppb O3 are observed for the
MCMA than for the GMA (46.1±1.0 ppb O3) and MMA (37.6±0.4 ppb O3), related to the levels of emissions of the
O3 precursors. The Ox profiles show a trough during the
morning rush hour and a peak between 12:00 and 14:00 in all urban areas.
Despite large variations between weekday and weekend NOx mixing
ratios in the three urban areas as shown in Fig. 8, no significant differences
(p>0.05) in O3 and Ox are observed in any of the
metropolitan areas between O3 and Ox weekend and
weekday AVd's.
Stephens et al. (2008) suggested that the most plausible explanation for the
lack of weekend O3 effect at MCMA during 1987–2007 is
a simultaneous decrease in NOx and VOC emissions on
weekends since the sole decrease in NOx emissions under
VOC-limited conditions would lead to an increase in O3 not
observed. Similarly, a VOC-limited O3 production regime was
reported for the MMA by Sierra et al. (2013), whereas Kanda et al. (2016)
reported that in the GMA the O3 production lies in the region
between VOC and NOx sensitivity. Therefore, it can be suggested
that simultaneous decreases in NOx and VOC emissions on
weekends in the GMA and MMA explain the similar behaviour in O3 and
Ox in the MCMA. Moreover, a change in
NOx-limited O3 production regime on weekends in the
three urban areas seems unlikely since this would result in lower
O3 levels on weekends, which is not observed in any of the
studied urban areas (Torres-Jardon et al., 2009). Wolff et al. (2013)
observed similar O3 levels during
weekdays and on weekends in several urban areas in the US despite lower O3 precursor emissions over
weekends. Furthermore, the number of sites in the US that exhibited a weekend
effect decreased from ca. 35 % to less than 5 % from 1997–1999 to
2008–2010, which was attributed to an increase in the
VOC/NOx emissions ratio derived from a greater decline in
NOx than in VOC emissions, mostly driven by reductions from
on-road sources.
Seasonal trends in O3 and Ox for the MCMA and
MMA during 1993–2014 and for the GMA during 1996–2014. Each data point
represents the average of the 3-month period that defines the season. The
dashed lines show the Sen trend.
Results for O3 and Ox long-term trends by
season expressed in ppb yr-1 during 1993–2014 for the MCMA and
MMA and during 1996–2014 for the GMA.
Urban area
Period
Ozone (O3)
Odd oxygen (O3+NO2)
ppbyr-1
%yr-1
Significance
ppbyr-1
%yr-1
Significance
MCMA
Annual
-1.15
-2.04
d
-1.87
-1.94
d
Spring
-0.97
-1.53
d
-1.77
-1.71
d
Summer
-0.97
-1.88
d
-1.44
-1.67
d
Autumn
-1.12
-2.20
d
-1.89
-2.15
d
Winter
-1.62
-2.64
d
-2.47
-2.27
d
GMA
Annual
-0.29
-0.81
-1.46
-1.85
+
Spring
-0.26
-0.57
-1.89
-2.07
b
Summer
-0.10
-0.32
-1.43
-1.89
b
Autumn
-0.09
0.33
-1.40
-1.97
b
Winter
-0.34
-1.01
-1.74
-2.08
d
MMA
Annual
0.22
0.84
c
0.13
0.30
Spring
0.32
1.04
c
0.29
0.63
Summer
0.27
0.99
d
0.28
0.72
d
Autumn
0.25
1.03
0.13
0.31
Winter
0.10
0.45
0.01
-0.01
a Level of significance p<0.1.
b Level of significance p<0.05.
c Level of significance p<0.001.
d Level of significance p<0.001.
Trends in NOx in the MCMA and MMA during 1993–2014
and in the GMA during 1996–2014. The dashed lines represent the Sen slopes.
All trends are statistically significant at p<0.05.
Long-term trends in MCMA, GMA, and MMA from 1993 to 2014
The high mixing ratios of O3 typically observed at the three largest
urban areas in Mexico have motivated the introduction of control strategies
to decrease emissions of the O3 precursors, NOx and
VOCs. The success of the control strategies implemented can be evaluated by
assessing trends in O3 and Ox. As for the MMA, seasonal
trends in O3 and Ox within the MCMA and GMA were
calculated from daytime measurements. Figure 9 shows a comparison of
inter-annual trends in O3 and Ox in the three urban areas
in Mexico, and Table 4 lists the parameters of the trends. Overall, during
1993–2014, daytime O3 in the MCMA decreased significantly
(p<0.05) by 1.15 ppbyr-1 (2.04 % yr-1) and
increased in the MMA by 0.22 ppbyr-1
(0.84 % yr-1); in the GMA no discernible trend was observed
during 1996–2014. For daytime Ox in the MCMA and GMA during the
same periods, significant decreases (p<0.05) of 1.87 and
1.46 ppbyr-1, respectively, were determined, while the MMA did
not exhibit a significant change. At the MCMA, the overall trends in
O3 and Ox are strongly driven by their wintertime
decreases of 1.62 and 2.47 ppbyr-1, respectively, whereas in the
MMA, the annual growth in O3 is driven by increases in spring and
summer of 0.32 and 0.27 ppbyr-1, respectively. However, in the
MMA, an increase in Ox of 0.28 ppbyr-1 is observed
only during summer. The overall Ox trend is strongly affected by
the non-significant trends in the other seasons. It is worth noting that in
the GMA, the overall decrease in Ox of 1.46 ppbyr-1
is similar for all seasons, which range between 1.40 ppbyr-1
(autumn) and 1.89 ppbyr-1 (spring).
The overall trends in net O3 production during 1993–2014 in the
MCMA and GMA are consistent with the significant (p<0.05) annual decreases
in NOx of 1.21 and 1.25 ppbyr-1, respectively
(Fig. 10). By contrast, while average NOx levels have increased
annually in the MMA at the rate of 0.33 ppbyr-1 (p<0.05), the average net
O3 production has remain steady. It is possible that the non-linear response in
Ox to the changes in NOx in an environment of high
NOx mixing ratios (>60 ppb) displaces the chemical
equilibrium to favour NO as the dominant component of NOx, which
does not account for the levels of Ox (Clapp and Jenkin, 2001).
It is also possible that the Ox trends derived from the combined data set for the MMA
do not represent local observed trends because there is a compensating effect between
Ox reductions and increases.
Annual exceedances of the O3 NOM for 1 h averages (110 ppb) and 8 h running averages (80 ppb) at the five monitoring sites within the MMA from 1993 to 2014.
Seasonal trends in 1 h O3 daily maxima at the MMA during 1993–2014. Each data point represents the average of the 3-month period that defines the season. The dashed lines show the Sen trend.
Results for O3 daily maximum long-term trends by season in ppbyr-1 during 1993–2014 at the five sites within the MMA.
Site
Period
Ozone (O3)
ppbyr-1
%yr-1
Significance
GPE
Annual
0.45
1.02
c
Spring
0.48
0.94
c
Summer
0.64
1.50
b
Autumn
0.35
0.74
Winter
0.26
0.63
SNN
Annual
0.79
2.13
d
Spring
0.87
2.01
d
Summer
0.85
2.42
d
Autumn
0.93
2.73
b
Winter
0.44
1.29
OBI
Annual
0.65
1.51
b
Spring
0.78
1.62
c
Summer
0.53
1.10
b
Autumn
0.75
1.77
Winter
0.21
0.55
SNB
Annual
0.40
0.80
d
Spring
0.85
1.58
d
Summer
0.67
1.36
d
Autumn
0.52
1.05
b
Winter
0.05
0.10
STA
Annual
0.01
-0.01
Spring
-0.05
-0.09
Summer
0.22
0.35
Autumn
-0.07
-0.12
Winter
-0.35
-0.75
a
a Level of significance p<0.1.
b Level of significance p<0.05.
c Level of significance p<0.001.
d Level of significance p<0.001.
Compliance with the 1 and 8 h Mexican standards for O3 within the MMA
Between 1993 and 2014, there were two official standards for maximum permitted mixing ratios of O3 in Mexico: (i)
a running 8 h average of 80 ppb, not to be exceeded more than four times per calendar year, and (ii) a 1 h average of
110 ppb (NOM-020-SSA1–1993). Since 19 October 2014, the maximum permitted O3 levels were lowered to a running
8 h average of 70 ppb and a 1 h average of 95 ppb, (NOM-020-SSA1-2014). However, because both standards are
applicable for whole calendar years, the old permitted O3 levels were used in this study to determine the number of
annual exceedances of both O3 standards. Figure 11 shows that within the MMA, the O3 1 h average and the
running 8 h standards were frequently exceeded (INE, 2011; SEMARNAT, 2015). The largest number of exceedances occurs at STA,
followed by SNB, GPE, and OBI, whereas the fewest breaches have been observed at SNN markedly since 2004. However, there have been
three
periods of clear decreased exceedances at all sites (except STA in 2014) during 1994–1995, 1999–2000, and 2012–2013, which are
consistent with marked changes in the national GDP during economic recessions in Mexico (Fig. S10a). However, national
GDP exhibits a notable decrease during the 2008–2009 global economic recession; only in 2009 do the O3 annual
exceedances within the MMA seem to follow (Fig. S10b).
Therefore, if O3 levels continue to increase within the MMA, as
determined in the long-term trend assessment, an increase in peak
O3 mixing ratios is also likely to occur. Hence, to analyse changes in
peak O3, daily maxima 1 h averages from 1993 to 2014 were used to
determine seasonal trends in peak levels. Figure 12 shows trends in 1 h
daily maxima and Table 5 lists the parameters of the trends. Daily maxima
O3 1 h averages increased significantly (p<0.05) in spring
and summer at all sites, except for STA, and also in autumn at the industrial
sites SNN and SNB. The largest increases in the daily maxima are seen at SNN,
where similar increases between 0.85 and 0.93 ppbyr-1 are
determined between spring and autumn. SNB exhibits slightly lower growth
rates in spring and summer but a large difference in autumn. We have shown
that predominantly E-SE winds transport photochemically processed air masses
to SNN and SNB during spring–summer leading to the observed exceedances.
Moreover, the change in the wind occurrence in autumn at SNB leads to a lower
growth rate than at SNN, where the calmest winds during the whole year drive
the largest increase, interpreted to be due to the photochemical processing of
precursors emitted locally. The GPE and OBI sites exhibit increases only in
spring and summer, with the lowest increases of all sites of 0.48 ppbyr-1 determined at OBI
in spring, which contrasts with the largest
increase at OBI during the same season. However, such increases are
consistent with an increase in the occurrence of NE and E air masses at high
speeds (>10 kmh-1) during spring–summer. STA shows
a significant decrease in the maximum daily O3 1 h averages of
0.35 ppbyr-1 in winter, which is consistent with an increase in
the occurrence of NW air masses at WS <5 kmh-1, loaded with
high NOx mixing ratios (50 ppb) that promote the
O3 titration.
Discussion
Strategies for air quality control in Mexico
The Mexican environmental authorities have focused largely on improving the air quality within the MCMA since 1986 by
implementing numerous strategies to control primary emissions, but they have paid less attention to other large metropolitan areas in
Mexico (PICCA, 1990; ProAire-MCMA, 2011). Control measures have been designed based on NAEI and local emissions inventory data,
which possess significant uncertainties (Arriaga-Colina et al., 2004; Velasco et al., 2007; Kanda et al., 2016). However, despite
these uncertainties, the emissions control strategies have helped to reduce O3 levels within the MCMA since 1991–1992
(ProAire-MCMA, 2001). Here, we describe the most effective measures introduced to control O3 precursor emissions within
the MCMA, and then we discuss potential benefits of implementing such measures within the MMA.
From 1993 to 2014, NOx levels within the MCMA decreased at a rate
of around 1.2 ppbyr-1 (1.6 % yr-1) as determined
from ground-based measurements. This decline is remarkably consistent with
the decrease in the NO2 column over the MCMA of
1.6 % yr-1 during 2005–2014 reported by Duncan et al. (2016). The decrease in
NOx was driven largely by reductions in emissions from
on-road sources, in response to the introduction of mandatory three-way catalytic
converters in new vehicles in 1993 (NOM-042; SEMARNAT, 1993b) and by the
introduction of a no-driving day and more stringent exhaust emissions
inspection programs for private cars in 1989 (NOM-041; SEMARNAT, 1993a).
The NOx reduction measures also required public transport
vehicles to switch from engines fuelled by petrol to engines fuelled by LP gas. New road corridors
were designed for improving the intracity transport and the public transport
fleet was renewed (ProAire-MCMA, 2001). For industrial sources, the switch
from fuel oil to LP gas fuel, relocation of highly polluting industries away
from the MCMA, and implementation of regular inspection programs of
NOx emission for industrial and area sources were also
implemented (ProAire-MCMA, 2001).
While the outlook for NOx levels within the MCMA is clear,
studies of VOC levels have reported no conclusive trends. For instance,
Arriaga-Colina et al. (2004) reported a decrease in VOCs of around 10 %
from 1992 to 2001 over the N MCMA, while Garzón et al. (2015) reported
that on average VOCs increased over most of the MCMA between 1992 and 2002 but
decreased by 2.4 ppbyr-1 between 2002 and 2012. However, the
decrease in VOCs from 2002 to 2012 reported by Garzón et al. (2015) is
consistent with a reduction in light alkane and aromatic levels during the
morning rush hour reported by Jaimes-Palomera et al. (2016). Continuous
measurements of VOCs have been recently introduced by the MCMA government,
which precludes an assessment of VOC long-term trends. The measures
implemented to control VOC emissions from on-road sources have included the
reformulation of petrol with the reduction of highly reactive VOCs and
addition of oxygenated compounds and fitting of three-way catalytic converters in
all new vehicles (NOM-042; SEMARNAT, 1993b; ProAire-MCMA, 2001). For area
sources, control measures include the introduction of vapour emissions
control systems at petrol stations and the introduction of a LP gas leak
detection program for the distribution network (ProAire-MCMA, 2011). As for
NOx, industrial VOC emissions sources have been subject to
regular emissions inspections and relocation of the most significant emitters
(ProAire-MCMA, 2011).
Therefore, the moderate success on controlling O3 levels within the
MMA can be interpreted as due to the implementation of effective control measures
on VOCs and NOx emissions. Thus, a comparison between VOCs and
NOx trends derived from the NAEI and local emissions inventories
with those determined from ground-level measurements can provide insight
into further improvements in decreasing O3 levels not only within
the MCMA but also in other large metropolitan areas in Mexico. Within the
MCMA, the NAEI NOx emissions trends are consistent with the
decrease determined from ground-based measurements made by SIMAT, but the
MCMA local inventory trends disagree with the SIMAT trends (Figs. S1 and 10).
For VOCs, the NAEI and the MCMA inventories oppose measured trends in VOCs
during 1993–2001 (Arriaga-Colina et al., 2004; Garzón et al., 2015).
This can be explained by underestimates of VOC emissions within the MCMA of
a factor of 2–3 (Arriaga-Colina et al., 2004; Velasco et al., 2007). Such
discrepancies suggest that significant improvements in NOx and
VOC emissions inventories are still required to better inform O3
control strategies.
Ground-level O3 and Ox variations within the MMA
The O3 and Ox diurnal variations result from the
particular chemical environment and meteorological conditions at each
monitoring site within the MMA. Thus, the largest O3 and
Ox mixing ratios, except for OBI, are typically observed for air
masses from the E and SE wind sectors, whereas at OBI, the largest
O3 and Ox values are recorded during the occurrence of
NE and E air masses. It is clear that short-range transport and large upwind
emissions of O3 precursors from the industrial area dominate the
MMA (SEMARNAT, 2006, 2011, 2014; SDS, 2015). This is underlined at OBI with
the highest values of Ox where the predominant wind direction is
NE, consistent with the transport of emissions from the industrial area
located to the NE and photochemical processing of air masses (Carrillo-Torres
et al., 2017). The daily cycles of O3 determined within the MMA are
consistent with those reported for Los Angeles (VanCuren, 2015) and Toronto
(Pugliese et al., 2014). In Toronto, the O3 maxima were enhanced by
the arrival of photochemically processed air masses transported from polluted
wind sectors, and decreased during clear air masses. This behaviour is
similar to that observed within the MCMA, with enhanced O3 maxima
during the occurrence of E-SE (polluted) air masses and decreased levels when W-SW
(relatively clean) air masses occurred.
Origin of the O3 annual cycles within the MMA
The annual O3 cycles within the MCMA are consistent with the spring maxima and winter minima characteristic of the southeastern US
regions (Strode et al., 2015) and follow the O3 cyclic pattern at NH mid-latitudes (Monks, 2000; Vingarzan,
2004). However, they are different from O3 annual cycles reported for the US west coast regions, particularly in
California, where the maxima in the cycle occurs between June and August, driven by the local influence of precursor emissions on
O3 production and photochemical conditions (Vingarzan, 2004; Strode et al., 2015). The recurrent downward spikes in the
O3 annual cycles within the MMA between July and August result from high wind speeds (>10 kmh-1 on average)
that disperse O3 precursors and increase the boundary layer height (ProAire-MMA, 2008). The peak in O3
observed in September is characteristic of humid regions and can be ascribed to an increase in OH radicals derived from the
increment in RH during the rainy season (Lee et al., 2014). A marked increase in RH within the MMA during September is consistent
with the increase in O3 observed as reported by Lee et al. (2014). Over the Midwestern and eastern US regions, that
O3 peak has become less noticeable since 2000 (Zheng et al., 2007).
The annual variability in O3 within the MMA is strongly coupled to
the economic conditions (GDP) in Mexico. For instance, the economic crisis of
1994–1996 caused a marked reduction in industrial emissions of VOCs and
NOx, which is confirmed by the significant decrease in
O3 annual variations at all sites within the MMA (Tiwari et al.,
2014; INEGI, 2016). During the global economic recession of 2008–2009,
Castellanos and Boersma (2012) reported a reduction of 10–30 % in
tropospheric NO2 over large urban European areas, which is consistent
with a faster decline of 8±5 % yr-1 in the NO2
column density during the same period for US urban regions (Russell et al.,
2012). Increases in the NO2 column density over the MMA as reported
by Duncan et al. (2016) are explained by the gradual recovery of the economy
since 1997 in Mexico. Moreover, increases in O3 precursor emissions
and in annual variability observed within the MMA are consistent with such
economic growth. This clearly explains the opposite trends in O3
annual variations before and after the economic crisis within the MMA, with
the lowest changes seen at the urban GPE site and the greatest ones detected
for the SNN industrial site.
Long-term trends for NOx at the five monitoring sites
within the MMA during 1993–2014. The dashed lines represent the Sen slopes.
Annual NOx rates of change are expressed as the slope (m) of the dashed lines in units of ppbyr-1. Levels of confidence are
represented as +=p<0.1, *=p<0.05, **=p<0.001, and ***=p<0.001.
Increasing O3 and Ox levels within the MMA
Ground-based measurements made during 1993–2014 reveal significant
(p<0.05) increases in NOx within the MMA at all sites, apart
from OBI, which exhibits a significant decrease (Fig. 13). Overall, the
NOx increase within the MMA of 1.24 % yr-1
(0.33 ppbyr-1) during 1993–2014 is larger than the increase in
the NO2 column density over the MMA of around
0.78 % yr-1 during 2005–2014 reported by Duncan
et al. (2016); although both have indicated a significant increase in the
NOx levels at least since 2005. The largest increases in
NOx correspond to industrial sites SNN
(0.51 ppbyr-1) and SNB (0.74 ppbyr-1). This is
interpreted as a response to growing industrial activity, in combination with
flexible emissions regulations within the MMA (INEGI, 2016). The influence of
industrial emissions upon O3 at the MMA becomes evident from the
lowest NOx growth rate of
0.19 ppbyr-1 observed at GPE since OBI has few occurrences of air masses
transporting pollutants from the largely industrialised areas throughout the
year (Fig. 2). By contrast, the NOx decrease of
-0.40 ppbyr-1 at OBI arises from decreases in emissions from on-road
sources (SDS, 2015). The large growth rates in O3 and
NOx at SNN and SNB are explained by increasing emissions of
O3 precursors from a growing number of industries and the urban
development E of the MMA. The most likely explanation for the O3
increase at OBI is a reduced titration effect from decreasing NOx
levels in combination with the non-linear response in O3 production
to decreasing NOx emissions under the VOC-sensitive MMA airshed
(Sierra et al., 2013; Menchaca-Torre et al., 2015).
The Ox long-term trends during 1993–2014 within the MMA were
consistent with those for O3 at all sites. Decreases in
NOx and O3 observed between 1994 and 1996 were the
response to the economic crisis during the same period in Mexico, when the
GDP decreased by 5.9 %, providing additional evidence of the dominant role
of industries within the MMA. Consistent with economic indicators, annual
averaged petrol sales in the Nuevo León State in 1995 decreased by 2.4 %
in relation to 1994, but increased linearly from 1996 to 2008 at an
approximate rate of 98 800 m3 petrol yr-1 (r=0.90)
(Fig. S11) (SENER, 2015). As for petrol sales, registered vehicles in Nuevo
León show significant variations between 1993 and 1996 but have increased linearly
since 1997 at a rate of around 100 000 vehicles yr-1 (r=0.99).
This confirms that despite the annual growth in the vehicular fleet, the
fitting of three-way catalyst technology and the reformulation of petrol introduced
in 1997 have controlled on-road primary emissions (ProAire-MCMA, 2001) The
decreases in NOx observed at OBI and at all sites during the
occurrence of W-SW-NW air masses reflect that if applied, stricter emissions
controls such as those for on-road sources can lead to a significant
abatement in primary emissions. It is clear that the industrial sources within the MMA must
be subject to similar emissions control measures as those implemented within
the MCMA for effectively reducing the O3 levels.
The opposite O3 trends in Mexican urban areas
The comparison of O3 and Ox trends in MMA, GMA, and MCMA
reveals different emissions trends at each of the cities studied. The trends
in O3 reported in this study for the MCMA agree with the reduction
of 20 ppb O3 during 1991–2011 for the MCMA (Jaimes et al.,
2012), and with the reduction of 8 ppb O3 during
2000–2011 for the MMA (Benítez-García et al., 2014). In the GMA,
the no-trend status in O3 determined here is in contrast with the
increase of 12 ppb O3 during 2000–2011
(Benítez-García et al., 2014), which is due to the different
periods assessed in both studies. Decreases in O3 in urban US areas
arise from effective control of O3 precursor emissions (Strode
et al., 2015), which has occurred at the MCMA.
Figure 10 shows that NOx decreased significantly within the MCMA
(1.57 % yr-1) and the GMA (1.83 % yr-1) during
1993–2014 and 1996–2014, respectively, but increased within the MMA
(1.83 % yr-1) during 1993–2014. Such NOx trends
are within the range of the trends in the NO2 column density reported
by Duncan et al. (2016) in Table S9, which reveals an increase of 0.78±1.12 % yr-1 for the MMA, but decreases of 1.82±0.84 % yr-1 for the GMA and of 0.10±1.67 % yr-1 for the MCMA, all during 2005–2014. To date,
long-term trends in VOCs have only been reported in the MCMA, with an
average decrease of ca. 2.4 ppbyr-1 since 2002, mostly in
propane, ethanol, and acetone (Garzón et al., 2016), while there are no
studies of long-term trends in VOCs within the MMA and the GMA.
It has been shown that O3 and Ox decreases within the
MCMA have been driven by reductions in NOx and VOC emissions
and that the implemented strategies described in Sect. 4.1 have proved to be
effective in controlling primary emissions (ProAire-MCMA, 2011;
Jaimes-Palomera et al., 2016). By contrast, growing industrial emissions
within the MMA must be subject to stringent controls to abate O3
levels. In the GMA, where the industrial activity is lower than in the MCMA
and MMA (Kanda et al., 2016), the policies introduced on a national scale for
controlling on-road source emissions have resulted in the decrease in
NOx emissions and in the stabilisation of O3 levels.
The results presented here demonstrate the merits of the assessment and
analysis of long-term O3 levels, which can be used by environmental
authorities to revise and to redesign programs and policies to improve air
quality. Continuing with ground-based O3 and NOx
monitoring is strongly recommended to better understand the response of changes in primary
emissions to further
changes in local and regional O3 levels. Monitoring of VOCs in the GMA and MMA is also recommended
since
the VOC emissions data reported in the NAEI possess significant
uncertainties. Finally, in accordance with the results presented here, we recommend
preferentially reducing VOC emissions, which may limit O3
production in response to a decrease in the VOC / NOx ratio.
However, simultaneously reducing NOx will have added health
benefits of less NO2.
Conclusions
Diurnal and annual cycles and long-term trends in O3 and
Ox within the MMA are interpreted as a response to changes in
NOx and VOCs emissions, photochemistry, and meteorology.
Continuous high-frequency and high-precision O3 and NOx
data recorded during 1993–2014 at five sites within the MMA and at 29 sites
within the MCMA and during 1996–2014 at 10 sites within the GMA were used
to calculate long-term trends. Within the MMA, the greatest mixing ratios in
O3 were recorded during E and SE winds, at sites downwind of
significant precursor emissions from industrial sources. By contrast, the lowest
O3 mixing ratios were recorded at SNN, and for all sites were
observed for the W and SW sectors, where air masses travel from central
Mexico over 100–300 km of semi-arid and sparsely populated area.
Maximum daily 1 h values of O3 and Ox increased
significantly at GPE, SNN, and SNB, owing to increasing emissions of
precursors, while at OBI increasing O3 and decreasing
Ox trends arise from the non-linear response to decreasing
NOx emissions from on-road sources.
Annual cycles in O3 at all sites peak in spring and trough in winter, with a downward spike during summer caused by
high winds that disperse O3 and increase the boundary layer height. Decreases in O3 precursor emissions
during the economic crisis experienced in Mexico between 1994 and 1996 caused significant declining trends in O3 annual
variations from 1993 to 1997 or 1998, depending on the site, followed by significant increases derived from the recovery of the
economy. The dominant role of industrial sources in O3 precursor levels within the MMA was evident at the industrial
site SNN during the 1994–1996 economic crisis.
In all metropolitan areas studied, O3 and Ox levels
showed no significant differences between weekdays and the weekend, although an
earlier occurrence of the O3 peak in the GMA was detected, ascribed
to a larger VOC/NOx emissions ratio. The lack of the weekend
effect was attributed to weekday O3 production being limited by
VOCs, whereas increases in the VOC/NOx ratio on
weekends in response to reduced emissions from mobile sources resulted in
similar O3 mixing ratios to those during weekdays. Larger
AVd's during weekdays and on weekends were seen in MCMA compared to GMA and
MMA, which was related to the relative emissions of the O3 precursors.
Significant seasonal trends in O3 and Ox during spring
were observed at all sites, apart from STA, whereas industrial sites
exhibited significant increases for Ox in all seasons. The
largest increases in O3 and Ox were observed during the
occurrence of E-NE-SE air masses. The only significant decrease in
Ox at STA was related to the NW wind occurrence during winter.
NOx mixing ratios increased significantly at all sites, except at
OBI, due to the dominant role of industrial sources in NOx
levels. The overall significant increasing trend of
0.22 ppb O3 yr-1 within the MMA contrasts
with a significant decreasing trend of 1.15 ppb
O3 yr-1 within the MCMA during 1993–2014, whereas
a non-significant trend is evident within the GMA during 1996–2014. At the
MCMA and GMA, the overall Ox trends reflect the trends in
O3 precursors. According to the long-term trends in O3
for the MMA, the number of exceedances of the air quality standards will very
likely increase as a result of increasing precursor emissions. The moderate
mitigation of O3 levels within the MCMA, derived from measures
implemented to control missions from on-road, industrial, and area sources,
emphasises the need for more stringent control of emissions mostly from
industrial sources within the MMA in order to improve air quality. Finally,
comparison between emissions inventory estimates of NOx and VOCs
with ground-based measurements indicate that significant reductions in
uncertainties are required to better inform air quality policies.