Atmospheric Changes and Ozone Increase in Mexico City during 2020 Lockdown Period

doi:10.21203/rs.3.rs-544962/v1

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Atmospheric Changes and Ozone Increase in Mexico City during 2020 Lockdown Period

https://doi.org/10.21203/rs.3.rs-544962/v1

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Atmospheric pollutant (NO₂, SO₂, CO, O₃ and PM_2.5) variations during the COVID-19 pandemic (during 2020) have been studied from Mexico City in Central America. Meteorological factors (i.e) rainfall, temperature along with relative humidity played an important role in increasing the photochemical reaction for the formation of O₃ and PM_2.5. Concentration pattern of O₃ and PM_2.5 were higher in all the stations in spite of the reduced primary pollutants. However, higher level of O₃ and PM_2.5 during the lockdown period in 2020 is mainly due to the air-mass exchange which happened through the broader channel in the north (Tenango del Aire Pass) and in the southeast (Cuautla-Cuernavaca valley). The higher values of particulate matter are compensated by domestic heating (“Quédate en Casa”/ Stay at Home), whereas the increase of O₃is supported by the higher solar radiation and household activities (both indoor/ outdoor). Monitoring stations (BJ, GAM, UAM, SFE) in Mexico City indicate that the level of pollutants (except GAM) were within the WHO guidelines. Comparison of pollutants with other countries indicate a spike in NO₂, O₃ and PM_2.5 levels. Overall results indicate that the anthropogenic activities which is influenced by the meteorological parameters has affected the air quality in Mexico City and it persisted during the lockdown period.

Environmental Chemistry

Toxicology

Mexico City Metropolitan Area (MCMA)

Ozone

Air Pollutants

Meteorological influences

COVID-19

Mexico.

The COVID-19 is a worldwide ongoing pandemic, initially chronicled in Wuhan, capital of Hubei province in China (Raibhandari et al., 2020) during late December 2019. This contagious disease created chaos across the globe affecting 208 countries including the developed countries like USA, UK, Australia, Europe, Japan, Germany, Africa, Mexico, India, Singapore, Malaysia, Canada and several other Latin American countries with a total affected human cases of 44 million (as of 30th October, 2020).

Without any exception, Mexico also reported its first case during mid-January, 2020 in the state of Nayarit and Tabasco and gradually all over the country totaling 1,957,889 cases and deaths were upto 167,760 persons (as of 10th February, 2020). Among the different states in Mexico, the most affected cases was detected in Mexico City (as of 10th February, 2020). The Mexican government initiated the lockdown slowly during mid-March 2020 by ceasing all high activities and closing schools, movie theaters, restaurants, public malls to avoid large people gatherings for social distancing. Recently, air pollution is the most important environmental problem labelled in most of megacities posing threats for human health due to the presence of primary and secondary pollutants resulted from anthropogenic activities and in-situ atmospheric reactions. Mexico City, renowned as one of the five largest populated cities in the world is bustled with heavy human activities and residents > 22 million habitants (United Nations, 2018). On this context, Mexico City always pinpointed for the air pollution since 1940, the era of industrial activities and gradual rise in pollution (Lezama, 2000). There are numerous studies which reported the strangling air problems in Mexico City Metropolitan Area (MCMA) especially the high ozone (O₃) and PM_2.5 concentrations making this the most polluted City in North America (Molina et al. 2007). Despite the huge population, the Mexico City host a large vehicular fleet available as taxi cab, passenger car, ride hauling services, light duty vehicles and heavy vehicles for cargo system. After a very serious episodes of severe air pollution for several years, the Mexican government introduced Bus Rapid Transit (BRT) system as an initiative to minimize the air pollution. Since the epoch of industrialization, there was a regular increase in vehicles for freight systems considered as an important source for emitting pollutants in interurban areas and general vehicle fleet in urban areas (Bel, 2018).

Most of the megacities faces air pollution risking human health (Holgate, 2017), in recent decades, Mexico City has reported major air pollution calamity due to the high concentrations of air pollutants such as NO₂, SO₂, CO, O_3, PM_2.5 which was high compared to the permissible Air Quality Standards guidelines (WHO, 2019). The majority of these pollutants are emitted through urban road transport containing massive vehicle fleet (metro, metro bus, microbus) and simultaneous traffic congestion, which is generally used by 12 million people (INEGI, 2018). Besides the immense use of this public transit, a study conducted on vehicle pollutant measurements discloses the commuter exposure to PM_2.5, CO and benzene especially in microbuses, buses and metro in Mexico City, which causes carcinogenic health problems (Gomez-Perales et al., 2004; Shiohara et al., 2005).

Since 1940, the Mexico City Metropolitan Area experienced a major air pollution due to urbanization and industrial activities, hence the Mexican government steps into implementing several strategies during the late 20th century to control and reduce the emissions triggering air pollution by restraining the emissions from industries also for the transport sector such as driving restrictions called “No Driving Day” (Hoy No Circula program in Spanish) in 1989. Implementing the control measures, it brought down significant changes in improving the air quality, which also happened due to the change in composition of gasoline and verification of vehicle engine (Davis, 2008; INEGI, 1988). However, particulate matter (PM) were a major pollutant emitted from the industrial areas present in the City which has happened due to in-house hold activities and different chemical additives from various sector (Soto-Coloballes, 2017; Sicard et al., 2020).

The immediate lockdown period announced across the globe made a substantial difference in the environment and the atmosphere, which was well documented through many research articles and social media. We made use of this period (upto June 2020) to identify and understand the causes, processes accountable for persisting air pollution in Mexico City Metropolitan Area. The main objective of the present study was to document and understand the changes due to the lock down which happened through industrial and transport sectors and the direct effect on the changes in the atmospheric conditions in Mexico City.

Geographical information of the Study area

Mexico City is an inland basin located at elevated position of 2240 m above mean sea level (MSL) enclosed with high mountains of Ajusco and Sierra Chicchinautzin in the south, Iztaccíhuatl- Popocatépetl dormant volcanic mountains in the east bordering the State of Mexico and Puebla (Fig. 1). Mexico City Metropolitan Area consists of 16 localities formerly known as “Mexico City”, comprising 59 metropolises in State of Mexico and 1 metropolis in State of Hidalgo. The topography of Mexico City indicates that it is surrounded with high mountains. In addition, a board opening in the north and a narrow passage in the south-south east at the border of the basin formerly called “Tenango del Aire” acts as natural ventilators for the City between the Mexico City basin and Cuautla- Cuernavaca Valley in the State of Morelos. Since 2000, the drastic transformation in the Mexico City caused urbanization and it expanded over some municipalities bordering the basin from the states of Mexico, Puebla, Tlaxcala, Morelos and Hidalgo which are under increasing population growth forming a grand urban complex in Mexico “Mexico City Megalopolis” as the most polluted City in the World (Fig. 1).

Meteorological settings

The Mexico City basin falls under sub-tropical highland climate, which is classified into three patterns: 1) dry winter (November to March); 2) dry summer (April to May and 3) rainy season (June to October) mainly to understand the changes. The summer is the driest season in Mexico adjoined by the presence of clear skies with low humidity and high pressure system with an average ambient temperature of 12 to 24 ˚C. The driest month have westerly current experiencing the anti-cyclonic flow along with strong thermal inversion at night (Collins and Scott, 1993). This (flow) that often lasts after the sunrise due to turbulent mixing and the strong heating by the sun enhances the photochemical reaction of the ozone (O₃) recording higher values of pollutants in Mexico City. In contrary, the rainy season have easterly winds prevailing over the mountains surrounding the Mexico City basin, which is due to convection and the thermal inversions of high moisture concentration. However, during early morning the turbulent eddies are generated from the heat from the sun causing severe vertical mixing of the pollutants (Giovanni et al., 2017).

The average annual rainfall in Mexico City is about 820 mm, which is intense from July to September. The diverse meteorological condition in Mexico city is responsible for the persisting air pollution, triggering activities in the photochemical ozone production and other secondary pollutants such as aerosol loadings and particulate matter (PM_2.5 & PM₁₀) (Garrido-Perez et al., 2018).

Mexico City suffer several episodes of ozone pollution since the last few decades especially during summer season, which is found higher than permissible limits of Mexican Air Quality Standards and WHO guidelines. The summer seasons are suspected to have UV radiations boosting the photochemical reactions. However, in the rainy season after precipitation by mid-day the ozone pollution is happening throughout the year (Molina., 2002). The low wind velocity prevailing in Mexico City with high ozone concentration during summer and low during winter (1994–2014) is very well correlated with the particulate matter contents with similar changes (Barrett and Raga, 2016). Hence, the meteorological variables were considered as most important factor towards understanding the air quality and pollution in Mexico City.

Pollutant data collection

This study was carried out by analyzing various set of data which is considered as important for determining and the understanding the discrepancies of air quality in Mexico City Megalopolis during the lockdown period. We used the meteorological data such as 1) temperature (in °C); 2) relative humidity (in %); 3) wind speed (in m/s); 4) precipitation (in mm) and air pollutant data (i.e) NO₂, SO₂, CO, O₃, PM_2.5 (in µg/m³ expect for CO measured in mg/m³) from a real time monitoring stations.

In this article, we have limited our data by mentioning only the diurnal average concentrations of the pollutants from January – May 2020 compared along with the annual average concentration for 2017, 2018 and 2019. The selection of the data and period was selected primarily to identify the periods which is considered as regular movements in the city limits during the past years. The open data was obtained from government network called “Red Autómatico de Monitoreo Atmosférico” (RAMA, 2020). This network comprises 34 stations in Mexico City and State of Mexico with regular maintenance of the laboratories and the monitoring equipment. Among the 34 stations, we selected only 5 stations for the study based on importance with massive human activities and vehicular congestions in Mexico city limits. The selected stations are as follow as: a) Benito Juarez (BJ) (Alt. 2250 MSL); b) Coyoacán (COY) (Alt. 2280 MSL); c) Gustavo A. Madero (GAM) (Alt. 2227 MSL); d) Sante Fe (SFE) (Alt. 2599 MSL) and e) UAM Xochimilco (UAM) (Alt. 2246 MSL) respectively. The studied pollutants NO₂, SO₂, CO and PM_2.5 were obtained as hourly average concentration and O₃ was obtained on average for 8 hrs to comply the standard quality.

Satellite- borne data

The primary data of pollutants concentrations were cross referred with the satellite image through spatial and temporal analysis of the pollutants. The satellite images were procured from the open access platform from NASA, which is officially available as “NASA GIOVANNI V4.34”. The data obtained were manipulated with the aid of Geographical Information System (GIS) for the above mentioned pollutants for the period of 2018 to 2020 (January- May). The spatial distribution of each pollutant were obtained and specified for our area of interest. We have collected different atmospheric pollutants (CO, NO₂, O₃, PM_2.5, and SO₂) satellite data from 2018 to 2020 for Mexico City. The data accessed from the GIOVANNI (Goddard Earth Sciences Data and Information Services Center, or GES DISC), indicates various Geo science data from NASA satellites directly on the web portal (https://earthdata.nasa.gov/), without any disturbances of traditional data acquisition and analysis methods. The pollutants CO, SO₂, and PM_2.5 were obtained from the source MERRA 2model (GMAO 2015) and NO₂, and O₃ from the source OMDOAO3e (Veefkind et al., 2012) with a spatial resolution of 0.25°. The data were available as vector files obtained data as a vector file which can be opened in Arc GIS software (Arc Map 10.3) and further the data was classified into four groups which was used to reclassify for the pollutants.

Mexican legislatures for air quality

The Mexico City megalopolis had a great history of air pollution because of economic and demographic growth. Hence the Mexican government made a remarkable advance in improving air quality since 1990s by initiating numerous regulations in transport and industrial sectors. The Secretariat of Environment (SEDEMA) is in authority for organizing Mexico City Environmental Programs towards air quality and other environmental problems in Mexico City megalopolis and other surrounding municipalities in states of Mexico, Puebla, Tlaxcala, Morelos and Hidalgo. Moreover, Mexico City have many other governmental officialdoms for the environmental policies and problems. The Mexican Secretariat of the Environment and Natural Resources (SEMERNAT) for the protection and management of natural resources through some environmental standards known as “Official Mexican Standards” (Norma Oficial Mexicana). The abrupt actions taken by Mexican government through these environmental agencies were executing the air quality standards, monitoring the stations in majority of the municipalities, regulating vehicle engines verifications for their emission inventories, modifying the composition in the gasoline and supporting newer technologies through scientific research. In 1994, the Mexican government imposed its air quality standards for major air pollutants especially for nitrogen dioxide (NO₂), sulfur dioxide (SO₂), carbon monoxide (CO), ozone (O₃) and particulate matter (PM_2.5). The above parameters were used in this study as a quality guideline for determining air quality pertained to human health and the changes during the lockdown periods.

Spatial & temporal distribution of air pollutants in Mexico City

The average concentrations of air pollutants (NO₂, SO₂, CO, O₃, PM_2.5) from five studied monitoring stations in Mexico City is shown in Table 1. Likewise, satellite images for the months of January to May 2020 (Fig. 2) were used to observe the changes in the air pollutants along with the three previous years (2017, 2018 & 2019) (Suppl. Fig. F1).

Table 1

Mean concentration of major air pollutants of five municipalities in Mexico City during lockdown and its comparisons
Locations	Year	NO₂ (µg/m³)	SO₂ (µg/m³)	CO (mg/m³)	O₃ (µg/m³)	PM_2.5 (µg/m³)
Benito Juárez	Annual Avg. 2018	-	42.25	1.78	163.45	22.37
Coyoacán		-	-	-	-	-
Gustavo A. Madero		12.78	-	-	131.70	23.69
Santa Fe		41.65	26.19	0.89	142.79	14.74
UAM Xochimilco		68.81	37.28	1.27	138.24	19.90
Avg.		41.03	35.24	1.31	144.05	20.18
Benito Juárez	Annual Avg. 2019	59.86	11.93	0.96	137.87	15.36
Coyoacán		-	-	-	-	-
Gustavo A. Madero		83.44	0.76	-	157.39	39.34
Santa Fe		63.32	19.62	0.16	123.66	30.63
UAM Xochimilco		55.86	14.08	0.86	144.20	27.47
Avg.		65.62	11.60	0.66	140.78	28.20
Benito Juárez	2020*	76.06	31.37	13.5	148.91	30.43
Coyoacán		-	-	-	-	-
Gustavo A. Madero		83.23	-	-	169.06	16.95
Santa Fe		65.27	16.43	7.11	148.60	36.13
UAM Xochimilco		60.53	21.51	8.37	171.69	39.23
Avg.		71.27	23.10	9.66	159.57	35.26
NOM-023-SSA1-1994		400/hr	-	-	-	-
NOM-022-SSAI-2010		-	290/24 hr	-	-	-
NOM-021-SSAI-1993		-	-	12.5/8 hr	-	-
NOM-020-SSAI-2014		-	-	-	137/8 hr	-
NOM-025-SSAI-2014 WHO Guidelines		- 200/ hr	- 20/24 hr	- -	- 100/8 hr	45/24 hr 25/24 hr
*Mean concentration for January to May

Based on the available data set compared to the annual average of 2018, 2019 and 2020 (January to May) the pollutants were seen in the concentrated in the following order: NO₂: 2020 > 2019 > 2018; SO₂: 2018 > 2020 > 2019; CO: 2020 > 2018 > 2019; O₃: 2020 > 2018 > 2019 and PM_2.5: 2020 > 2019 > 2018. Compared to the WHO values for SO₂ (20/24 hr µg/m³), O₃ (100/8hr µg/m³) and PM_2.5 (25/24 hr µg/m³) the present local values indicates higher values during the lockdown period of March to May 2020. The significant reduction in SO₂, CO, O₃ during 2019 period indicate that they were mainly seen during the fuel scarcity period (García-Franco, 2019). It should also be observed that nearly 70 explosions (January to May 2020) occurred in the volcano Popocatepetl emitting approximately 2500 tons/day load of SO₂ into the atmosphere (CENAPRED, 2020). This is very well supported by the plume and wind direction which is NW-W-NNE during the months of March, April and May 2020 (Suppl. Table T1) (de Foy et al., 2009; Martin Del-Pozzo, 2009; Schiavo, 2020; SEDEMA-CDMX, 2018). In addition, the higher NO₂, CO, SO₂ values during the January, February period of 2020 is also attributed to the smoke plumes released from the fireworks used during the festival seasons during the end of the year releasing high quantity of sulfate nitrate, ammonium and potassium, which is responsible for the 50% of total particulate matter (García-Franco, 2019; Retama et al., 2019).

Carbon monoxide values in Mexico City varied from 7.11 to 13.5 mg/m³ in the five studied locations. However, overall calculated values were well below the permissible limits of NOM-021-SSAI-1993 (Mexican Norm.). Comparing the previous two years (2018-19) data on CO in Mexico City, the values indicate a five to seven-fold increase during the lockdown period. Higher values of CO during the lockdown period in Mexico City is mainly due to the indoor emission of CO mainly due to low grade solid fuel, biofuels clogged chimneys, gas burners, home cooking, wood-burning fire places, decorative fire places etc., could vent CO into indoor spaces and subsequently to the main route (Howard et al., 1991; Buchholz et al., 2016; Murphy et al., 2007; Wolff et al., 2013). In contrast, the lower values during the two previous years (2018-19) indicate that the major population in the City limits are often out in the streets due to the various workload as individuals and are well stretched in industrial sectors (Levesque et al., 2001; Maroni et a., 2002). The above distribution of personal in different work places also reduces the use of individual emission of CO mainly in indoor conditions. In addition, the presence of road side restaurants and food stalls, which is often popular in developing mega cities like Mexico also increases the presence of CO and its subsequent reduction in CO in April-May 2020 (Velasco et al., 2019).

Higher values of PM_2.5 in the lockdown period is mainly due to the presence of secondary pollutants, which is generated through photochemical reaction through NO₂, SO₂ and CO (Garcia-Franco, 2020). This is also supported by the temperatures (18–22°C) during the months of April and May 2020, where the photochemical reaction is triggered. Earlier report on PM_2.5 concentrations in Mexico indicates that high values are found in areas close to metro stations and rapid transit system, which includes the metro and metrobuses (Velasco et al., 2019). Moreover, in congested cities and high traffic zones the high presence of PM_2.5 suggest that the majority of PM_2.5 is due to the transport sector, which are trapped during morning and evening periods (Hernandez-Paniagua, 2018). Recent studies during the lockdown periods in different countries also suggest that the increase in particulate matter was counter balanced by domestic heating (Sicard et al., 2020). Likewise, the higher values of SO₂, PM_2.5 combine during the lockdown period is not associated to the reduction of vehicles rather than the volcanic explosions from Popocatepetl during the latter half of the lockdown period (March to May 2020) (Suppl. Table T1).

Role of wind in transporting pollutants

Mexico City have three types of seasons namely dry summer, dry winter and rainy season. During the dry summer (April and May) the photochemical reactions of VOC, NO₂ and SO₂ often causes smog, aerosol loadings (values in µg/m³) with high O₃ (159.57) and PM_2.5 (35.26) (Cohen et al., 2018; Salcedo et al., 2012). Higher concentrations (values in µg/m³) of NO_x (71.27) and O₃ (148.60) during early morning are from the vehicle rush during the peak hours (8 to 10 am) is directly linked to the photochemical reaction. Moreover, the pollutants have a tendency to circulate through synoptic pattern throughout the year due to their regional settings of high latitudes and altitude (Edgerton, 1999). In addition, the topography of Mexico City basin shows it is surrounded by high elevated mountain causing a circulation pattern effectively promoting the diurnal movement of airborne particles of O₃ and PM_2.5 within the basin, causing a persistent O₃ enrichment (de Foy et al., 2006). Despite the (in central Mexico region) circulation pattern, the pressure system which prevails in the basin creates a great difference in distribution of pollutants inside the basin. This is supported by the broader opening in the north of the basin which acts as a natural window of the City providing ventilation and in the south the “Tenango del aire pass (TAP)”. The natural openings/ channels transmit the polluted air by northerly and southerly winds from TAP with high O₃ (110 µg/m³) towards MCMA. The enriched values (µg/m³) of NO_x (71.27), O₃ (159.57) is mainly through the corridors of Cuautla – Cuernavaca valley under high pressure system (S-SSE-SE wind direction) (Fig. 3). Meanwhile, the Cuautla – Cuernavaca valley in the south transmits the clean air from Amecameca prevailed with southerly winds under low pressure system (LPS) with lowest ozone concentration (80 µg/m³) due to the air mass exchange event which happened in a circular manner inbetween the mountain openings (Garcia-Reynoso et al., 2009; Salcedo et al., 2012; Garcia-Yee et al., 2018). Moreover, the increase of O₃ is also due to the reduction in particulate matter content (compared to before lockdown), which also leads to surface O₃ levels through higher solar radiation and possibly through house hold garden related activities (Deng et al., 2010; Li et al., 2013; Su et al., 2003).

Meteorological influence of wind over the pollutants (NO₂, SO₂, CO, O₃, PM_2.5, Wind speed) in the present study is analyzed for four stations (BJ, GAM, SFE, UAM) in the study area (Fig. 3a-x). Results from the northern monitoring station GAM indicates higher concentration (in µg/m³) of NO₂ (83.23), O₃ (169.06), PM_2.5 (16.25), which also follows a NNE-NE-ENE direction. The wind velocity was 5.5 to 8.8 m/s causing pollutants to more a longer distance from north to south by the strong influence of wind (Fig. 3g, j-l) (Fast et al., 2007). No clear distribution pattern is observed in SO₂ and CO. The trajectory of the pollutants suggests that the ventilation of polluted air is transferred through the broad channel in the northern part of Mexico City and it is also depending on the velocity and air pressure (Fast et al., 2007). Data from the central monitoring station indicates elevated higher values (in µg/m³) of NO₂ (71.27), CO (9.66), O₃ (159.27) and lower values of PM_2.5 (35.26) and SO₂ (23.10) respectively. The wind direction follows a S-SSE-SE and N-NNE-NE-ENE-E, where pollutants are carried away with a maximum velocity of 4.4 to 5.4 m/s (Fig. 3a-f).

The two southern monitoring stations UAM and SFE indicates that the concentration (values in µg/m³) pattern is at the intermediate level: NO₂: 60.53, 65.27; SO₂: 21.51, 16.43; CO: 8.37, 7.11; O₃: 171.69, 148.60; PM_2.5: 39.23, 36.13 and wind speed (in m/s): 7.7, 8.8 indicating a SSE-SE-ESE direction respectively. The air mass exchange is mainly through the volcanic mountain series of Xaltepec used Teuhtli. Furthermore, it is evident that there is a presence of “Rossby wave” breaking event, which is an anticyclonic process where cold air passes towards equator and the warm air towards westward direction (Rodrigues and Wollings, 2017). This massive instability in the atmospheric conditions in Mexico City clearly affects the air quality conditions in the region (Silva-Quiroz et al., 2019).

Role of temperature in distribution of pollutants

Temperature is another important factor governing all the meteorological factors like rainfall and pressure. Like wind, temperature is also an important factor for the formation of secondary pollutants (values in µg/m³) O₃ (UAM: 171.69), PM_2.5 (UAM: 39.23). However, the primary pollutants like NO₂ (GAM: 82.33); SO₂ (BJ: 31.37); CO (BJ: 13.5) are formed due to the photochemical reaction (Garcia-Franco, 2020; Sicard et al., 2020). The above results are very well supported by previous studies indicating a variability in the upper-troposphere circulation “Madden-Julian Oscillation”, where low UV radiation and less ozone exists (Barret and Raga 2016). Ozone concentration studies in 2015 indicates that the temperature reaches higher values during the hot-dry seasons accompanied by a minimum boundary layer height (Garzon et al., 2015). The major correlation with the higher values (µg/m³) of PM_2.5 (UAM: 39.25) and O₃ (UAM: 171.69) during the March to May period, where the temperature inversions occurs in the day and vertical mixing of air column happens during the night time (Whiteman et al., 2000; Garcia-Franco et al., 2020).

Changes in vehicle and industrial emission inventories

As this article mainly infers the origin of pollutants from the transport sector which was later affected by the meteorological influences. The record of the inventories of transport sector (including road & air) and industrial emissions where the reduction in emission ceased during February to May 2020.

General surface/ ground transportation movements in Mexico City involves 17 million commuting trips during week days (INEGI, 2017). The aviation movements for national/ international movements is documented in Table 2. Six different regions aviation movements were considered from the available data sets: a) Domestic & International (DL); b) American international (AI); c) Canadian International (CI); d) Central & Latin America (CL); e) European (E) and f) Asian (A). The movement of air traffic for the month of February and March 2020 were reduced from different routes were: February 2020 (in %): DI (11.22) > E (9.83) > A (7.56) > CL (7.26) > AI (6.65) > CI (2.78) and March 2020: CL (35.44) > DI (24.50) > CI (23.75) > AI (13.33) > A (11.46) > E (2.96) respectively. The data also infers that the movement of air traffic is based on the policies of each country and region. This is also inferring that CO₂ reduction takes place due to the reduction of air traffic (Le Quere et al., 2020).

Table 2 Air carriers services and it’s reduction during the initial lockdown period in Mexico
Air Carriers	2020 (No. of flights)					Reduction in flights (%)
	Jan	Feb			Mar	Jan⁺		Feb	Mar
Domestic & International (DL)
Aeromar	2163		1930	1860		100	89.23			85.99
Aeromexico	7307		6277	5225			85.90			71.51
Aeromexico Connect	10054		8953	7511			89.05			74.71
Aerounion*	291		236	263			81.10			90.38
Estafeta*	341		285	325			83.58			95.31
Interjet	10219		9081	6309			88.56			61.74
Mas Air*	126		104	110			82.54			87.30
Magnicharters	494		306	310			61.94			62.75
Vivaaerobus	6534		5809	5492			88.90			84.05
Volaris	11895		10899	9908			91.63			83.30
Total Services & CO₂	49424		43880	37313		100	88.78			75.50
American International (AI)
Alaska Airlines	1139		1136	1228		100	99.74		107.81
American Airlines	3113		3141	2897			100.90		93.06
Amerijet International*	24		26	24			108.33		100.00
Atlas Air*	40		42	42			105.00		105.00
Compass Airlines	70		62	62			88.57		88.57
Continental Express	595		578	462			97.14		77.65
Delta Airlines	3115		2708	2271			86.93		72.91
Envoy Air, Inc	1086		1016	863			93.55		79.47
FEDEX*	167		161	166			96.41		99.40
Frontier	353		352	306			99.72		86.69
Jet Blue Air	324		274	263			84.57		81.17
Mesa Airlines	1783		1605	1549			90.02		86.88
Southwest Airlines	1070		962	904			89.91		84.49
United Airlines	2839		2609	2586			91.90		91.09
Total Services & CO₂	15718		14672	13623		100	93.35		86.67
Canadian International (CI)						100
Air Canada	886		839	745			94.70		84.09
West Jet	1179		1182	930			100.25		78.88
Total Services & CO₂	2065		2021	1675		100	97.22		76.25

Central & Latin America (CL)
Aerolineas Argentinas	52	50	40	100	96.15	76.82
Aerorepublica	59	41	24		69.49	40.68
Avianca	309	290	206		93.85	66.67
Copa	850	792	580		93.18	68.24
Lanperu	212	200	108		94.34	50.94
Volaris Costa Rica	115	108	73		93.91	63.48
Total Services & CO₂	1597	1481	1031	100	92.74	64.56
European (E)
Air France	151	137	123		90.73	81.46
British Airways	88	84	86		95.45	97.73
Cargolux Airlines*	90	61	96		67.78	106.67
Iberia	126	122	114	100	96.83	90.48
KLM (Royal Dutch Airlines)	62	58	56		93.55	90.32
Lufthansa	120	116	90		96.67	75.00
Turkish Airlines	70	68	62		97.14	88.57
Total Services & CO₂	707	646	627	100	90.17	97.04
Asian (A)
Emirates Arabes	155	150	112		96.77	72.26
Korean Air	20	24	24	100	120.00	120.00
Qatar Airlines	73	79	81		108.22	110.96
Total	248	253	217	100	92.44	88.54

*Cargo services. ⁺For the month of January 2020 for calculation purpose, the values are kept at 100.

Based on the surface transport movements in Mexico City from January to May 2020 indicates a wide variations and non-reduction of movements in some sectors. The usage (in millions) from January to May (2020) is as follows: metrosystem 130.709 (January) to 35.900 (May); public transport 12.4 (local and long distance buses) (in January) to 33.22 (May) and short transport system 44.16 (micro bus) (in January) to 11.61 (in May) (INEGI, 2020). Eventhough based on the above data there was a reduction in public transport movement during the lock down, other services were operating as it is during the normal conditions. This clearly contributes more towards emissions of NO₂, SO₂, CO, PM_2.5 and VOC as they are mostly perceived from the transport sector. The above inference is very well supported by earlier studies in Mexico City that apart from transport sector, industrial source (for NO₂, SO₂) and soil erosion (for PM_2.5) and solvent paints (for VOCs) are responsible for the presence of these pollutants (Molina et al., 2019). Likewise, the adaptations from MOBILE 6.2 - Mexico and Moves – Mexico found significant reduction in total emissions (in %) for NO_x by -37, CO by -52 and VOCs by 26 percent. However, there was an increase observed (in %) for O₃ by 6.6 due to the operations in urban traffic stations PM₁₀ by + 8 and PM_2.5 by 6 mainly due to the contributions from gasoline based taxis and passenger cars (Guevara et al., 2017).

Industrial sector in Mexico City which has 26 different types (paper, manufacture, mining, fabrication, plastics, rubber) plays a major role in the emission and in transporting the pollutants. The “Monthly industrial activity indice (MIAI)” was calculated based on the data from 2019 (April-May). The calculated MIAI values for the construction industry indicates that it was 105, 99.5 (April, May 2019) and 64.7, 63.8 (April, May 2020) respectively. Likewise, for manufacturing industries it was 115.4, 114.9 (April, May 2019) and 74.3, 74.1 (April, May 2020). Overall, the reduction of industrial activity was between 35.7 to 40.3% (construction) and 40.8 to 41.1% in manufacturing sector. In the mining industry it is almost maintained the same way 70.3 to 73.1% (for April-May 2019) and 68.2 to 72.3% (for April-May 2020) for Mexico City (Suppl. Fig. F2a-j). Air quality/ emission studies from these industries often indicate that toxic metals (As, V, Fe, Cu) dominate due to the increase in PM_2.5 (Morales-García et al., 2014). The above MIAI values suggest that the main contributors exist due to the emissions which also has a direct effect on the higher values of VOCs that often has a direct impact on O₃ (Koupal and Palacios 2019).

Statistical Information

Statistical analysis was done with the available data as well as the meterological variables of temperature and rainfall for the year 2020. Dendrograms were generated which indicated two different clusters which high linkage distance (Fig. 4). The long linkage distance between O₃ and rainfall (avg. rainfall of 20.92 mm for March to May 2020) infers the presence of high O₃ and the production during the dry seasons (Velasco, 2017). The short linkage values of PM_2.5 and SO₂ indicates that the particulate matter contents are mainly due to the geothermal activity mixed with wind direction (NW) along with the vehicle emissions. The individual linkage of NO₂ with other parameters (O₃, PM_2.5, CO, SO₂) suggest that NO₂ is the controlling factor for the formation of O₃ and for the generation of PM_2.5 which also depends in the temperature and other pollutants (Murphy et a., 2007). The above inference is also supported by the notion “Stay at Home” (Quédete en Casa), where household heating has increased multiple times (Sicard et al., 2020). The short linkage distance between CO and temperature specifies the absorption of particular radiation where the generation of CO and temperature has a direct relationship.

Correlation matrix results (p > 0.05) clearly infers a negative value (r² = -0.87) with NO₂ indicate that the SO₂ in is from an external source mainly due to the explosions in volcan Popocateptl assisted by the wind direction. However, the strong association between O₃ vs NO₂ (r² = 0.57) and O₃ vs CO (r² = 1.00) indicates photochemical reaction and O₃ increase (Chin et al., 1994). Particulate matter indicates positive correlation with NO₂ (r² = 0.94) which is a governing factor, whereas the negative relationship with SO₂ (r² = -0.98) indicates the less conversion process responsible for the PM_2.5 particles. Positive correlation (r²) of temperature with NO₂ (1.00), CO (0.54) and PM_2.5 (0.96) suggest that temperature is the dependent factor for the conversion of NO₂ and SO₂ for sulfate and nitrates (Eatough 1994; Khoder, 2002; Lin et al., 2019). The negative relationship (r²) of rainfall with NO₂ (-0.84), CO (-0.93), PM_2.5 (-0.61) and temperature (-0.81) specifies the low reaction rate for the conversion of NO₂ and SO₂ to nitrate and sulfate during precipitation time. The moderate positive value for SO₂ vs rainfall (0.46) indicate the higher rate of conversion process due to the surface inversion during the night period (Lin et al., 2019). Overall results indicate that the distribution of pollutants is dependent on meteorological parameters, whereas the insignificant associations shows the independency of the factor for their fate and state in the atmosphere.

Comparative Studies

Based on the available data compared to the air pollutants reported from different countries during the present pandemia from January till date (Before the lockdown & After lockdown), we have collected the available data and it has been compared with reference to WHO guidelines (Table 3).

Table 3

Comparison of air pollutants reported before and after lockdown across the globe
Country	Locations	Before Lockdown (before March 2020)					After Lockdown (after March 2020)					Reference
Country	Locations	NO₂	SO₂	CO	O₃	PM_2.5	NO₂	SO₂	CO	O₃	PM_2.5	Reference
India	Delhi	45.59	16.08	1.03	34.05	80.51	20.16	13.19	0.72	34.32	37.75	Mahato et al., 2020
China*	44 cities	-	-	-	-	-	13.66	6.76	4.58	-	5.93	Bao & Zhang., 2020
Brazil	Sao Paulo	24.4	-	0.4	40.2	12.4	19.2	-	0.1	44.6	12.4	Nakada & Urban., 2020
Rio de Janeiro^†	Bangu	-1.8	-	-15.2	-	33.5	-16.8	-	-42.4	-7.8	-	Dantas et al., 2020
	Iraja	28.8	-	-	-	31.1	1.4	-	-	-2.7	-	Dantas et al., 2020
	Tijuca	-	-	12	-	63	-	-	-30.3	34	-	Dantas et al., 2020
Kazakhstan	Almaty	37	49	674	30	27	24	52	343	34	38	Kerimray et al., 2020
China	Yangtze River Delta	50	7	0.9	43	56	40	6	0.7	64	30	Li et al., 2020
Europe^a	Nice	30.9	-	-	39.5	10.9	12.5	-	-	77.6	12.4	Sicard et al., 2020
	Rome	46.4			33.3	21.8	21.5			61.9	14.3	Sicard et al., 2020
	Turin	51.3			25.2	37.6	23.9			64.4	16.6	Sicard et al., 2020
	Valencia	27.8			31.6	18.8	8.3			65.8	10.7	Sicard et al., 2020
Mexico	2020	January to March					April to May
	Benito Juárez	46.75	17.39	16.88	62.27	27.13	36.26	7.70	8.38	84.97	32.63	Present study
	Gustavo A. Madero	48.93	-	-	73.21	36.82	41.15	-	-	94.79	3.71
	Santa Fe	39.01	9.79	9.63	72.10	29.33	31.81	3.94	3.94	78.16	34.28
	UAM Xochimilco	28.36	11.64	9.41	73.60	33.83	34.74	5.94	5.91	96.76	39.62
WHO Guidelines	-	200/ hr	20/24 hr	-	100/8 hr	25/ 24 hr	200/ hr	20/24 hr	-	100/8 hr	25/ 24 hr
^aMean concentrations recorded at four station before and during lockdown; All values in µg/m³ (except CO as mg/m³); *Air Quality Index; ^†Variation in the air pollutants (%)

NO₂ values after the lockdown period in Mexico City is high compared to other countries, which is mainly due to the direct emissions from vehicles. Likewise, SO₂ and CO values indicate spike in some monitoring stations (especially in Benito Juárez), but it was lower than the permissible limits of WHO. The higher values in BJ alone is mainly due to topographical features of the station and the wind direction S-SSE-SE. Ozone values were well within the permissible limits of WHO, but it two to three fold higher than other countries. PM_2.5 values were higher in Mexico City when compared to other countries as well as WHO values which is mainly attributed to the photochemical reactions and solar radiations of the primary pollutants (Garcia-Yee et al., 2018; Sicard et al., 2020).

Mexico City is well known as one of the most polluted cities in North America and the present article focuses on the changes in the air quality status amid the present pandemic which has shook the whole world in one way or the other.

Primary and secondary data sets were generated to monitor the pollutants (NO₂, SO₂, CO, O₃ and PM_2.5) in four different monitoring stations located in the Mexico City area. The results indicate that higher values in GAM for all the pollutants which is two to three fold higher than the WHO permissible limits. The increase in pollutants were mainly due to the meteorological factors like rainfall, temperature, relative humidity, wind speed and its direction which foster the photochemical reaction. This is very well supported by the evaluation of statistical analysis indicating that the enrichment of pollutants (NO₂, SO₂, CO) were from vehicular fleet and industries. The higher temperatures often promote the intense photochemical reactions which enhances the formation of O₃ and PM_2.5 which is observed in all the stations despite the lockdown period which were are highly controlled by the wind direction and precipitation. It is clearly observed that Mexico City suffers severe air pollution through both natural as well as anthropogenic ways and the persistency of the pollutants happens via broad channel in the narrow passage (Tenango del Aire) and Cuautla-Cuernavaca Valley in the south. It is clear that the government should form strong strategies towards air quality management tools with updated technology for both transport vehicles and cars with changes in emissions standards, which will help cooperate restore the air quality standards.

BJ: Benito Juárez; CO: Carbon monoxide; GAM: Gustavo A Madero; MCMA: Mexico City Metropolitan Area; MIAI: Monthly industrial activity índices; MOBILE 6.2: Mobile Source Emission Factor Model for Mexico; NO₂: Nitrogen dioxide, O₃: Ozone; PM_2.5: Particulate matter; SFE: Santa Fe; SO₂: Sulfur dioxide; UAM: Universidad Autónoma de Metropolitana; WHO: World Health Organization

Ethics approval and consent to participate

Not applicable

Consent for publication

Not applicable

Availability of data and materials

All data generated or analyzed during this study are included in this published article (and its supplementary information files)

Competing interests

All authors certify that they have no affiliations with or involvement in any organization or entity with any financial interest or non-financial interest in the subject matter or materials discussed in this manuscript.

Funding

No funds, grants or other support was received.

Author´s contributions

Conceptualization: Sakthi Selvalakshmi Jeyakumar, Jonathan Muthuswamy Ponniah; Data curation: Sakthi Selvalakshmi Jeyakumar, Gopalakrishnan Gnanachandrasamy, Sandra Soledad Morales-García, Pedro Francisco Rodriguez-Espinosa; Formal analysis: Sakthi Selvalakshmi Jeyakumar, Gopalakrishnan Gnanachandrasamy; Funding acquisition: Jonathan Muthuswamy Ponniah; Investigation: Gopalakrishnan Gnanachandrasamy, Pedro Francisco Rodriguez-Espinosa, Diana Cecilia Escobedo-Urias; Methodology: Sakthi Selvalakshmi Jeyakumar, Gopalakrishnan Gnanachandrasamy, Gowrapan Muthusankar; Diana Cecilia Escobedo-Urias; Project administration: Jonathan Muthuswamy Ponniah; Resources: Jonathan Muthuswamy Ponniah; Software: Sakthi Selvalakshmi Jeyakumar, Jonathan Muthuswamy Ponniah, Gopalakrishnan Gnanachandrasamy, Gowrapan Muthusankar; Supervision: Jonathan Muthuswamy Ponniah; Validation: Sandra Soledad Morales-García, Pedro Francisco Rodriguez-Espinosa, Gowrapan Muthusankar, Diana Cecilia Escobedo-Urias; Visualization: Jonathan Muthuswamy Ponniah; Roles/Writing - original draft: Sakthi Selvalakshmi Jeyakumar, Jonathan Muthuswamy Ponniah; Writing - review & editing: Sakthi Selvalakshmi Jeyakumar, Jonathan Muthuswamy Ponniah.

Acknowledgement

SSJ wishes to thank CONACyT (Mexico) for the research fellowship. SSMG, PFRE and DCEU wishes to express their gratitude to Sistema Nacional de Investigadores (SNI), CONACyT, Mexico. This work is a partial contribution from the Earth System Science Group (ESSG), Mexico & Chennai India (Participating members: JSS, GMS and MPJ.

Barrett B, Raga G (2016) Variability of winter and summer surface ozone in Mexico City on the intraseasonal time scale. Atmospheric Chemistry Physics 16(23):15359–15370. https://doi.org/10.5194/acp-16-15359-2016
Bel G, Holst M (2018) Evaluation of the impact of Bus Rapit Transit on air pollution in Mexico City. Transp Policy, 63, 209–220. https://doi.org/10.1016/ j.tranpol.2018.01.001
Buchholz RR, Paton-Walsh C, Griffith DWT, Kubistin D, Fisher JA, Deutscher NM, Kettlewell G, Riggenbach M, Macantangay R, Krummel PB, Langenfelds RL (2016) Source and meteorological influences on air quality (CO, CH₄ & CO₂) at a Southern Hemisphere urban site. Atmos Environ 126:274–289. http://dx.doi.org/10.1016/j.atmosenv.2015.11.041
CENAPRED (2020) Centro Nacional De Prevención De Destres. Reportes del volcán Popocatépetl. http://www.cenapred.unam.mx/reportesVolcanGobMX. (Accessed on 18/08/2020)
Chin M, Jacob DJ, Munger JW (1994) Relationship of ozone and carbon monoxide over North America. J Geophys Res 99(D7):14565–14573. https://doi.org/10.1029/94JD00907
Cohen Y, Petetin H, Thouret V, Marécal V, Josse B, Clark H, Boulanger D (2018) Climatology and long-term evolution of ozone and carbon monoxide in the upper troposphere–lower stratosphere (UTLS) at northern mid-latitudes, as seen by IAGOS from 1995 to 2013. Atmospheric Chemistry Physics 18(8):5415–5453. https://doi.org/10.5194/acp-18-5415-2018
Collins CO, Scott SL (1993) Air pollution in the valley of Mexico. Geographical Reviews 2:119–133. https://doi.org/10.1016/j.atmosres.2017.04.035
Davis LW (2008) The effect of driving restrictions on air quality in Mexico City. J Polit Econ 116(1):38–81. https://doi.org/10.1086/529398
De Foy B, Krotkov NA, Bei A, Herndon N, Huey LG, Martínez A-P, Ruíz-Suárez LG, Wood EC, Zavala M, Molina LT (2009) Hit from both sides: Tracking industrial and volcanic plumes in Mexico City with surface measurements and OMI SO₂ retrievals during the MILAGRO field campaign. Atmospheric Chemistry Physics 9:9599–9617. https://doi.org/10.5194/acp-9-9599-2009
De Foy B, Varela JR, Molina LT, Molina MJ (2006) Rapid ventilation of the Mexico City basin and regional fate of the urban plume. Atmospheric Chemistry Physics 6:2321–2335. https://doi.org/10.5194/acp-6-2321-2006
Deng JJ, Wang TJ, Liu L, Jiang F (2010) Modeling heterogeneous chemical processes on aerosol surface. Particuology, 8, 308–318. https://doi.org/ 10.1016/j.partic.2009.12.003
Eatough D, Caka F, Farber R (1994) The Conversion of SO₂ to Sulfate in the Atmosphere. Isr J Chem, 34, 301–314. https://doi.org/ 10.1002/ijch.199400034
Edgerton SA, Bian X, Doran JC, Hubbe JM, Malone EL, Shaw WJ, Whiteman CD, Zhong S, Arriaga JL, Ortiz E, Ruiz M, Sosa G, Vega E, Limon T, Guzman F, Archuleta J, Bossert JE, Elliot SM, Lee JT, McNair LA, Chow JC, Watson JC, Coulter R, Doskey PV, Gaffney JS, Marley NA, Neff W, Petty R (1999) Particulate Air Pollution in Mexico City: A collaborative Research Project. J Air Waste Manag Assoc 49:10–1221. https://doi.org/10.1080/10473289.1999.10463915
Fast JD, de Foy B, Rosas FA, Caetano E, Carmichael G, Emmons L, McKenna D, Mena M, Skamarock W, Tie X, Coulter RL, Barnard JC, Wiedinmyer C, Madronich S (2007) A meteorological overview of the MILAGRO field campaigns. Atmospheric Chemistry Physics 7:2233–2257. https://doi.org/10.5194/acp-7-2233-2007
García-Franco JL (2020) Air Quality in Mexico City during the fuel shortage of January 2019. Atmos Environ, 222, 117131. https://doi.org/ 10.1016/j.atmosenv.2019.117131
García-Franco J, Stremme W, Bezanilla A, Ruiz-Angulo A, Grutter M (2018) Variability of the mixed-layer height over Mexico City. Bound-Layer Meteorol 167(3):493–507. https://doi.org/10.1007/s10546-018-0334-x
Garcia-Reynoso A, Jazcilevich A, Ruiz-Suarez LG, Torres-Jardon R, Lastra MS, Juarez NAR (2009) Ozone weekend effect analysis in Mexico City. Atmosfera 22:281–297
García-Yee JC, Torres-Jardón R, Barrera-Huertas H, Castro T, Peralta O, García M, Gutiérrez W, Robles M, Torres-Jaramillo JA, Ortínez-Álvarez A, Ruiz-Suárez LG (2018) Characterization of NO_x- O_x relationships during daytime interchange of air masses over a mountain pass in the Mexico City megalopolis. Atmos Environ, 22, 100–110. https://doi.org/10.1016/ j.atmosenv.2017.11.017
Garrido-Perez JM, Ordóñez C, Garcia-Herrera R, Barriopedro D (2018) Air stagnation in Europe: spatiotemporal variability and impact on air quality. Sci Total Environ, 645, 1238–1252. https://doi.org/10.1016/ j.scitotenv.2018.07.238
Garzón JP, Huertas JI, Magaño M, Huertas ME, Cárdenas B, Watanabe T, Maeda T, Wakamatsu S, Blanco S (2015) Volatile organic compounds in the atmosphere of Mexico City. Atmos Environ 119:415–429. https://doi.org/10.1016/j.atmosenv.2015.08.014
Giovanni C, Estévez HR, Valdés-Barrón M, Bonifaz-Alfonzo R, Riveros-Rosas D, Velasco-Herrera VM, Vázquez-Gálvez FA (2017) Aerosol climatology over the Mexico City basin: Characterization of optical properties. Atmos Res 194:190–201. https://doi.org/10.1016/j.atmosres.2017.04.035
Gómez-Perales J, Colvile R, Nieuwenhuijsen M, Fernández-Bremauntz A, Gutiérrez- Avedoy V, Páramo-Figueroa V, Blanco-Jiménez S, Bueno-López E, Mandujano F, Bernabé-Cabanillas R, Ortiz-Segovia E (2004) Commuters' exposure to PM_2.5, CO, and benzene in public transport in the metropolitan area of Mexico City. Atmos Environ 38:1219–1229. https://doi.org/10.1016/j.atmosenv.2003.11.008
Guevara M, Tena C, Soret A, Serradell K, Guzmán D, Retama A, Camacho P, Jaimes- Palomera M, Mediavilla A (2017) An emission processing system for air quality modelling in the Mexico City Metropolitan Area: Evaluation and comparison of the MOBILE6.2-Mexico and MOVES-Mexico traffic emissions. Sci Total Environ, 584–585, 882–900. https://doi.org/10.1016/ j.scitotenv.2017.01.135
Hernández-Paniagua IY, Andraca-Ayala GL, Diego-Ayala U, Ruiz-Suarez LG, Zavala-Reyes JC, Cid-Juárez S, Torre-Bouscoulet L, Gochicoa-Rangel L, Rosas-Párez I, Jazcilevich A (2018) Personal exposure to PM_2.5 in the mega City of Mexico: a multi-mode transport study. Atmosphere, 9 (2), 57. https://doi.org/ 10.3390/atmos9020057
Holgate ST (2017) Every breath we take: the lifelong impact of air pollution–a call for action. Clin Med 17(1):8–12. https://doi.org/10.7861/clinmedicine.17-1-8
Howard PH (1991) Handbook of environmental degradation rates. 1st Edition, Boca Raton Publs., 776p
Instituto Nacional de Ecologia (INE) (1998) Segundo Informe sobre la Calidad del Aire en Ciudades Mexicanas – 1997, Mexico City, online available at: https://sinaica.inecc .gob .mx /archivo /informes /2doInforme .pdf
Instituto Nacional de Estadística Geografía (INEGI) (2017) Encuesta origen-destino en hogares de la Zona Metropolitana del Valle de México (EOD 2017). http://www.be ta.inegi.org.mx/proyectos/enchogares/especiales/eod/2017/
Instituto Nacional de Estadística Geografía (INEGI) (2018) Available online: https://www.inegi.org.mx/temas/transporteurb/2018-Red de Transporte de Pasajeros
Instituto Nacional de Estadística Geografía (INEGI) (2020) Transportes/Información general
Khoder M (2002) Atmospheric conversion of sulfur dioxide to particulate sulfate and nitrogen dioxide to particulate nitrate and gaseous nitric acid in an urban area. Chemosphere 49:675–684. https://doi.org/10.1016/s0045-6535(02)00391-0
Koupal J, Palacios C (2019) Impact of new fuel specifications on vehicle emissions in Mexico. Atmos Environ, 201, 41–49. https://doi.org/10.1016/ j.atmosenv.2018.12.028
Lin CA, Chen YC, Liu CY, Chen WT, Seinfeld JH, Chou CCK (2019) Satellite – Derived correlation of SO₂, NO₂ and aerosol optical depth with meteorological conditions over East Asia from 2005 to 2015. Remote Sensing 11:01738. https://doi.org/10.3390/rs11151738
Lévesque B, Allaire S, Gauvin D, Koutrakis P, Gingras S, Rhainds M, Prud′Homme H, Duchesne J-F (2001) Wood burning appliances and indoor air quality. Sci Total Environ, 281 (1–3), 47–62. https://doi.org/ 10.1016/S0048-9697(01)00834-8
Lezama JL (2000) Aire dividido, Crítica a la política del aire en el Valle de México. El Colegio de México, México
Le Quere C, Jackson RB, Jones MW, Smith AJP, Abernethy S, Andrew RM, De-Gol AJ, Wills DR, Shan Y, Canadell JG, Friedlingstein P, Creutzig F, Peters GP (2020) Temporary reduction in daily global CO₂ emissions during the COVID-19 forced confinement. Nature Climate Change, 10, 647–653. https://doi.org/ 10.1038/s41558-020-0797-x
Liu H, Wang XM, Pang JM, He KB (2013) Feasibility and difficulties of China’s new air quality standard compliance: PRD case of PM_2.5 and ozone from2010 to 2025. Atmospheric Chemistry Physics 13:12013–12027. https://doi.org/10.5194/acp-13-12013-2013
Del-Pozzo M AL (2009) Precursors to eruptions of Popocatépetl Volcano. Mexico Geofísica Internacional 51(1):87–107
Maroni M, Carrer P, Cavallo D, Jantunen M, Katsouyanni K, Kuenzli N (2002) Air pollution exposure of adult population in Milan (Expolis study). In: Procd. of Indoor Air 2002, The 9th Int. Conf, 4. on Indoor Air Quality & Climate, Monterey, pp 455–460
Molina LT, Kolb CE, de Foy B, Lamb BK, Brune WH, Jimenez JL, Ramos-Villegas R, Sarmiento J, Paramo-Figueroa VH, Cardenas B, Gutierrez-Avedoy V, Molina MJ (2007) Air quality in North America's most populous City – overview of the MCMA- 2003 campaign. Atmospheric Chemistry Physics 7:2447–2473. https://doi.org/10.5194/acp-7-2447-2007
Molina LT, Velasco E, Retama A, Zaval M (2019) Experience from Integrated Air Quality Management in the Mexico City Metropolitan Area and Singapore. Atmosphere, 10 (9), 512. https://doi.org/10.3390/atmos10090512
Molina LT, Molina MJ (2002) Air Quality in the Mexico MegaCity: An Integrated Assessment. Kluwer Academic Publishers, 384p
Morales-García SS, Rodríguez-Espinosa PF, Jonathan MP, Navarrete-López M, Herrera- García MA, Muñoz-Sevilla NP (2014) Characterization of As and trace metals embedded in PM₁₀ particles in Puebla City, México. Environmental Monitoring Assessment, 186, 55–67. https://doi.org/ 10.1007/s10661-013-3355-4
Murphy JG, Day DA, Cleary PA, Wooldridge PJ, Millet DB, Goldstein AH, Cohen RC (2007) The weekend effect within and downwind of Sacramento – part 1: observations of ozone, nitrogen oxides, and VOC reactivity. Atmospheric Chemistry Physics 7:5327–5339. https://doi.org/10.5194/acpd-6-11427-2006
Raibhandari B, Phuyal N, Shrestha B, Thapa M (2020) Air medical evacuation of Nepalese citizen during epidemic of COVID-19 from Wuhan to Nepal. Journal of Nepal Medical Association 58(222):125–133. https://doi.org/10.31729/jnma.4857
Retama A, Neria-Hernández A, Jaimes-Palomera M, Rivera-Hernández O, Sánchez-Rodríguez M, López-Medina A, Velasco E (2019) Fireworks: A major source of inorganic and organic aerosols during Christmas and New Year in Mexico City. Atmospheric Environment X, 2, 100013. https://doi.org/10.1016/ j.aeaoa.2019.100013
Rodrigues RR, Woollings T (2017) Impact of atmospheric blocking on South America in austral summer. J Clim, 30 (5), 1821–1837. https://doi.org/ 10.1175/JCLI-D-16-0493.1
Salcedo D, Castro T, Ruiz-Suárez LG, García-Reynoso A, Torres-Jardón R, Torres- Jaramillo A, Mar-Morales BE, Salcido A, Celada AT, Carreón-Sierra S, Martínez AP, Fentanes-Arriaga OA, Deustúa E, Ramos-Villegas R, Retama- Hernández A, Saavedra MI, Suárez-Lastra M (2012) Study of the regional air quality south of Mexico City (Morelos state). Sci Total Environ 414:417–432. https://doi.org/10.1016/j.scitotenv.2011.09.041
Schiavo B, Morton-Bermea O, Salgado-Martinez E, Hernandez-Alvarez E (2020) Evaluation of possible impact on human health of atmospheric mercury emanations from the Popocatépetl volcano. Environmental Geochemistry Health, 1–13. https://doi.org/10.1007/s10653-020-00610-6
SEDEMA-CDMX (2018) Inventario de Emisiones de la Ciudad de México 2016: contaminantes criterio, tóxicos y compuestos de efecto invernadero. Secretaría del Medio Ambiente de la Ciudad de México. Dirección General de Gestión de la Calidad del Aire, Dirección de Programas de Calidad del Aire e Inventario de Emisiones
Shiohara N, Fernández-Bremauntz A, Blanco-Jiménez S, Yanagisawa Y (2005) The commuters' exposure to volatile chemicals and carcinogenic risk in Mexico City. Atmos Environ, 39, 3481–3489. https://doi.org/ 10.1016/j.atmosenv.2005.01.064
Sicard P, De Marco A, Agathokleous E, Feng Z, Xu X, Paoletti E, Rodriguez JJD, Calatayud V (2020) Amplified ozone pollution in cities during the COVID-19 lockdown. Sci Total Environ 735:139542. https://doi.org/10.1016/j.scitotenv.2020.139542
Silva-Quiroz R, Rivera AL, Ordoñez P, Gay-Garcia C, Frank A (2019) Atmospheric blockages as trigger of environmental. contingencies in Mexico City Heliyon 5:e02099. https://doi.org/10.1016/j.heliyon.2019.e02099
Soto-Coloballes NV (2017) El control de la contaminación atmosférica en México (1970–1980): tensiones y coincidencias entre el sector salud y los industriales. Dynamis 37(1):187–209
Su FC, Mukherjee B, Batterman S (2003) Determinants of personal, indoor and outdoor VOC concentrations: an analysis of the RIOPA data. Environ Res 126:192–203. https://doi.org/10.1016/j.envres.2013.08.005
United Nations (2018) Revision of World Urbanization Prospects. Available online: https://www.un.org/development/desa/publications/2018-revision-of-world-urbanization-prospects.html
Veefkind JP, Aben I, McMullan K, Förster H, De Vries J, Otter G, Claas J, Eskes HJ, De Haan JF, Kleipool Q, Van Weele M, Hasekamp O, Hoogeveen R, Landgraf J, Snel R, Tol P, Ingmann P, Voors R, Kruizinga B, Vink R, Visser H, Levelt PF (2012) TROPOMI on the ESA Sentinel-5 Precursor: A GMES mission for global observations of the atmospheric composition for climate, air quality and ozone layer applications. Remote Sens Environ 120:70–83. https://doi.org/10.1016/j.rse.2011.09.027
Velasco E, Retama A (2017) Ozone’s threat hits back Mexico City. Sustainable Cities Society 31:260–263. https://doi.org/10.1016/j.scs.2016.12.015
Velasco E, Retama A, Segovia E, Ramos R (2019) Particle exposure and inhaled dose while commuting by public transport in Mexico City. Atmos Environ 219:117044. https://doi.org/10.1016/j.atmosenv.2019.117044
Whiteman C, Zhong S, Bian X, Fast J, Doran J (2000) Boundary layer evolution and regional-scale diurnal circulations over the Mexico Basin and Mexican plateau. Journal Geophysical Research Atmosphere 105(D8):10081–10102. https://doi.org/10.1029/2000JD900039
Wolff GT, Kahlbaum DF, Heuss JM (2013) The vanishing ozone weekday/weekend effect. Journal of Air Waste Management Association 63:292–299. https://doi.org/10.1080/10962247.2012.749312
World Health Organization (2019) Ambient (outdoor) air quality and health, Available online: https://www.who.int/en/news-room/fact-sheets/detail/ambient-(outdoor)-air-quality-and-health

SUPPLEMENTARYMATERIALS.doc
Suppl. Table T1 Eruptions in volcan de Popocatépetl during January – May 2018, 2019 and 2020. Suppl. Table T2 Correlation matrix analysis of major air pollutants and meteorological factors (January-May) in Mexico City, Mexico. Suppl. Fig. F1 Satellite images of pollutants NO2, SO2, CO, O3 and PM2.5 from 2019 and 2020. Suppl. Fig. F2 Graphical representation and variation of industries shut down during the lock down period in Mexico City and State of Nuevo Leon (North Mexico), Mexico.

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Atmospheric Changes and Ozone Increase in Mexico City during 2020 Lockdown Period

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