The Latin America and the Caribbean region (LAC) face various challenges at maintaining sustained observation networks and establishing regional modeling capabilities that have a direct influence in policymaking processes. Despite many structural limitations, research groups in LAC continue to collaborate in deepening the understanding of atmospheric chemistry processes and their impacts on air quality, atmospheric composition, and health. However, these scientific efforts cannot substitute for the much-needed coordinated action at national and regional levels to establish long-term programs that support monitoring and research, with the goal of informing policy design. Observation networks in LAC are generally managed by local or central governments, which have limited resources, and are mostly focused on monitoring air quality in large cities. However, not all stations measure all criteria pollutants. As per observations of other important species to atmospheric chemistry, volatile organic compounds have only been measured in very few countries. On the other hand, satellite observations are of crucial importance, but there is a general lack of systematic validations of these products in the region. Atmospheric composition networks are also scarce given the continental extension of LAC. These shortcomings hinder modeling efforts. At the same time, important advances in this field—such as improved emission models and mechanisms for the formation of secondary pollutants—are often overlooked by international research groups and agencies. In this work, we present the status of observations and modeling efforts in the region, and we discuss challenges and needs for coordinated efforts to break this pattern.

This work analyzes ground-level ozone trends in South America, an understudied region with scarce comprehensive trend estimates. We present an updated regional analysis and test a hypothesis proposing that the recent increase in ozone levels, particularly in urban environments, may be linked to intense wildfires induced by extreme meteorological events within a preexisting volatile organic compounds (VOC)-limited regime. Utilizing the quantile regression method, we estimate trends, quantify uncertainties, and identify change points. Short- and long-term exposure is assessed using the maximum daily 8-hour average and peak season metrics. Our findings reveal lower ozone levels in tropical cities (Bogotá and Quito), ranging between 39-43 ppbv for short-term and 26-27 for long-term exposure. In contrast, extratropical cities (Santiago and São Paulo) exhibit higher ozone levels, with short-term exposure at 61 ppbv and long-term exposures between 40-41 ppbv. Santiago (since 2017) and São Paulo (since 2008) show positive trends of 0.6 ppbv yr-1 and 0.2 ppbv yr-1, respectively, with very high certainty. We attribute these upward trends, or the absence of evidence of variation as observed in Bogotá and Quito, to the established VOC-limited regime. However, the higher increase in extreme percentile trends (≥ 90th) is linked to the impact of wildfires and biomass burning, particularly in southwestern South America, associated with extreme meteorological configurations.

South American cities experience high levels of air pollution. Studies on its health impacts, however, are scarce when compared with those in wealthier regions. This review focuses on recent research on air pollution and health impacts in this continent, including studies that have been focused on vulnerable groups such as infants and children, lower-income groups, and rural and indigenous populations. Impacts of household air pollution are also discussed. South America would greatly benefit from expanded monitoring networks, improved air quality modeling, and detailed health data to better understand exposure-health relationships and multi-pollutant interactions.

Tropospheric ozone trends are important indicators of climate forcing and surface pollution, yet relevant satellite observations are too uncertain for assessments. The assessment project TOAR-II has used multi-instrument, ground-based data for global trends over 2000–2022 (Van Malderen et al., 2025a, b). For the tropics, trends are derived from SHADOZ ozonesonde profiles (Thompson et al., 2021, “T21”; Stauffer et al., 2024) or combinations of satellite, SHADOZ and IAGOS aircraft measurements (Gaudel et al., 2024). We extend T21 that covered 1998–2019, analyzing SHADOZ data at five sites with a Multiple Linear Regression (MLR) model for 1998–2023 and reporting trends for two free-tropospheric (FT) segments, the lowermost stratosphere and the total tropospheric column (TrCOsonde). Trends for the Aura period, 2005–2023, are computed from OMI/MLS TrCOsatellite. We find the following: Extending SHADOZ analyses 4 years shows little change from T21; TrCOsonde trends are small (0.5–1 DU/decade) except over SE Asia. Annual trends for TrCOsonde and OMI/MLS TrCOsatellite agree within uncertainties at four of five sites, with the largest differences at Samoa. Sensitivity tests show the following: (a) Adding thousands of FT IAGOS profiles to SHADOZ yields little change in trends; SHADOZ sampling is sufficient. (b) Quantile Regression (QR) and MLR median trends are both near zero, but QR captures extremes (5th percentile, 95th percentile) with changes up to ±1 DU/decade (p< 0.10). (c) Twelve-year analyses for trends lead to uncertainty changes too large for an assessment. This study and Van Malderen et al. (2025a, b) provide the most reliable TOAR-II trends to date: over the past ∼ 25 years, tropical FT ozone changes have been modest, ∼ (−3–+3) %/decade, except over SE Asia.

Amid the current climate and environmental crises, cities are being called to reduce levels of atmospheric pollutants that also act as short-lived climate forcers, such as ozone and PM2.5. This endeavor presents new challenges, especially in understudied regions. Here, we use a chemical box model to investigate ozone production sensitivity to NOx and VOCs in Quito, Ecuador, and Santiago, Chile. We present ozone production rates (P(O3)) calculated using VOC measurements taken in Santiago, along with VOC vs. CO linear regressions (LRs), and complement the analysis with Monte Carlo (MC) simulations. In Quito, VOC measurements are unavailable. We therefore simulated a range of VOC concentrations using LRs and MC simulations. We modeled P(O3) in March 2021 and for typical conditions per season in 2022. We calculated a range of P(O3) in Quito of 15–50 ppbv h−1 year-round. In Santiago, we found that P(O3) is 23–50 ppbv h−1 in the ozone season (austral summer). Although the P(O3) magnitudes were found to be comparable, Santiago has a well-established ozone season, unlike Quito where concentrations are lower. From sensitivity experiments, alkenes and aromatics contribute 50 % to P(O3) in Santiago and could reach 70 %–90 % in Quito (noon and afternoon). Aldehydes and ketones contribute 30 %–40 % in Santiago and about 20 % in Quito (noon and afternoon). We estimate the isoprene contribution to be 20 % in Santiago and 10 % in Quito. VOC reduction experiments generally lowered P(O3) in both cities. In Santiago, NOx reductions increased the morning P(O3).

Abstract. Trends in tropical tropospheric ozone over the past ~20–30 years have been reported using ozonesonde profiles from five SHADOZ sites (Thompson et al., 2021, “T21”; Stauffer et al., 2024, “S24”) and a combination of satellite, SHADOZ and IAGOS aircraft measurements (Gaudel et al., 2024). Selected tropical sonde and aircraft trends also appear in Van Malderen et al. (2024a). We have extended T21 for monthly-averaged five-station SHADOZ data with a Multiple Linear Regression (MLR) model, covering 1998 to 2023. We report: (1) trends in two free tropospheric (FT) ozone layers, lowermost stratosphere (LMS) ozone, total tropospheric column (TrCOsonde) and tropopause height; (2) trends for 2000–2023 (no 1997–1998 ENSO) and 1998–2019 (no COVID-19). (3) TrCOsonde trends, 2005–2023, compared to OMI/MLS TrCOsatellite. The findings: (1) Extending SHADOZ trends four years does not change the T21 results: annual trends negligible except in one FT layer (Natal-Ascension) and for tropopause-referenced LMS. A slight reduction in FT trends may reflect a moderating effect of COVID-19. (2) Adding thousands of IAGOS profiles to SHADOZ data similarly showed near-zero MLR trends (p<0.05) in a pressure-defined lower FT; SHADOZ sampling is sufficient. (3) With the TrCOsonde adding 0–5 km ozone, trends are only detected over SE Asia and Natal-Ascension at 2–3 %/decade, p<0.05; comparison to trends from the TOAR II/HEGIFTOM activity (a 0–300 hPa TrOC) gives similar results. For 2005–2023 MLR annually averaged trends for TrCOsonde and OMI/MLS TrCOsatellite agree within uncertainties at four of 5 SHADOZ sites.

We use 2021 TROPOMI and GOSAT satellite observations of atmospheric methane in an analytical inversion to quantify national methane emissions from South America at up to 25 km × 25 km resolution. From the inversion, we derive optimal posterior estimates of methane emissions, adjusting a combination of national anthropogenic emission inventories reported by individual countries to the United Nations Framework Convention on Climate Change (UNFCCC), the UNFCCC-based Global Fuel Exploitation Inventory (GFEIv2), and the Emissions Database for Global Atmospheric Research (EDGARv7) as prior estimates. We also evaluate two alternative wetland emission inventories (WetCHARTs and LPJ-wsl) as prior estimates. Our best posterior estimates for wetland emissions are consistent with previous inventories for the Amazon but lower for the Pantanal and higher for the Paraná. Our best posterior estimate of South American anthropogenic emissions is 48 (41–56) Tg a−1, where numbers in parentheses are the range from our inversion ensemble. This is 55 % higher than our prior estimate and is dominated by livestock (65 % of anthropogenic total). We find that TROPOMI and GOSAT observations can effectively optimize and separate national emissions by sector for 10 of the 13 countries and territories in the region, 7 of which account for 93 % of continental anthropogenic emissions: Brazil (19 (16–23) Tg a−1), Argentina (9.2 (7.9–11) Tg a−1), Venezuela (7.0 (5.5–9.9) Tg a−1), Colombia (5.0 (4.4–6.7) Tg a−1), Peru (2.4 (1.6–3.9) Tg a−1), Bolivia (0.96 (0.66–1.2) Tg a−1), and Paraguay (0.93 (0.88–1.0) Tg a−1). Our estimates align with the prior estimates for Brazil, Bolivia, and Paraguay but are significantly higher for other countries. Emissions in all countries are dominated by livestock (mainly enteric fermentation) except for oil–gas in Venezuela and landfills in Peru. Methane intensities from the oil–gas industry are high in Venezuela (33 %), Colombia (6.5 %), and Argentina (5.9 %). The livestock sector shows the largest difference between our top-down estimate and the UNFCCC prior estimates, and even countries using complex bottom-up methods report UNFCCC emissions significantly lower than our posterior estimate. These discrepancies could stem from underestimations in IPCC-recommended bottom-up calculations or uncertainties in the inversion from aggregation error and the prior spatial distribution of emissions.

Tropospheric ozone results from in situ chemical formation and stratosphere-troposphere exchange (STE), with the latter being more important in the middle and upper troposphere than in the lower troposphere. Ozone photochemical formation is nonlinear and results from the oxidation of methane and non-methane hydrocarbons (NMHCs) in the presence of nitrogen oxide (NOx=NO+NO2). Previous studies showed that O3 short- and long-term trends are nonlinearly controlled by near-surface anthropogenic emissions of carbon monoxide (CO), volatile organic compounds (VOCs), and nitrogen oxides, which may also be impacted by the long-range transport (LRT) of O3 and its precursors. In addition, several studies have demonstrated the important role of STE in enhancing ozone levels, especially in the midlatitudes. In this article, we investigate tropospheric ozone spatial variability and trends from 2005 to 2019 and relate those to ozone precursors on global and regional scales. We also investigate the spatiotemporal characteristics of the ozone formation regime in relation to ozone chemical sources and sinks. Our analysis is based on remote sensing products of the tropospheric column of ozone (TrC-O3) and its precursors, nitrogen dioxide (TrC-NO2), formaldehyde (TrC-HCHO), and total column CO (TC-CO), as well as ozonesonde data and model simulations. Our results indicate a complex relationship between tropospheric ozone column levels, surface ozone levels, and ozone precursors. While the increasing trends of near-surface ozone concentrations can largely be explained by variations in VOC and NOx concentration under different regimes, TrC-O3 may also be affected by other variables such as tropopause height and STE as well as LRT. Decreasing or increasing trends in TrC-NO2 have varying effects on TrC-O3, which is related to the different local chemistry in each region. We also shed light on the contribution of NOx lightning and soil NO and nitrous acid (HONO) emissions to trends of tropospheric ozone on regional and global scales.

Abstract. Ozone formation is nonlinear, and results from the photochemical oxidation of methane and non-methane hydrocarbons (NMHCs) in the presence of nitrogen oxide (NOx=NO+NO2). Previous studies showed that O3 short- and long-term trends are nonlinearly controlled by near-surface anthropogenic emissions of carbon monoxide (CO), volatile organic compounds (VOCs), and nitrogen oxides. In this review article, we investigate tropospheric ozone spatial variability and trends from 2005 to 2019 and relate those to ozone precursors on global and regional scales. We also investigate the spatiotemporal characteristics of the ozone formation regime in relation to ozone chemical sources and sinks. Our analysis is based on remote sensing products of the Tropospheric Column of Ozone (TrC-O3) and its precursors, nitrogen dioxide (TrC-NO2), formaldehyde (TrC-HCHO), and total column of CO (TC-CO) as well as ozonesonde data and model simulations. Our results indicate a complex relationship between tropospheric ozone column levels, surface ozone levels, and ozone precursors. While the increasing trends of near-surface ozone concentrations can largely be explained by variations in VOC and NOx concentration under different regimes, TrC-O3 may also be affected by other variables such as tropopause height. Decreasing trends in TrC-NO2 have varying effects on the TrC-O3, which is related to the different local chemistry in each region. The concomitant increase or decrease in TrC-O3 and TrC-NO2 over the eastern US, and central Europe is due to dominant NO-sensitive conditions resulting from the strict measures to control NOx emissions over the last two decades. The decreasing trends of TrC-NO2 but increasing trends of TrC-O3 in some regions in the central US and parts of eastern Asia are due to high NOx conditions leading to VOC sensitivity in these regions. We also shed light on the contribution of NOx lightning and soil NO and nitrous acid (HONO) emissions to trends of tropospheric ozone on regional and global scales.

In this study, trends of 21st-century ground-level ozone and ozone precursors were examined across South America, a less-studied region where trend estimates have rarely been comprehensively addressed. Therefore, we provided an updated regional analysis based on validated surface observations. We tested the hypothesis that the recent increasing ozone trends, mostly in urban environments, resulted from intense wildfires driven by extreme meteorological events impacting cities where preexisting volatile organic compound (VOC)-limited regimes dominate. We applied the quantile regression method based on monthly anomalies to estimate trends, quantify their uncertainties and detect trend change points. Additionally, the maximum daily 8 h average (MDA8) and peak-season metrics were used to assess short- and long-term exposure levels, respectively, for the present day (2017–2021). Our results showed lower levels in tropical cities (Bogotá and Quito), varying between 39 and 43 nmol mol−1 for short-term exposure and between 26 and 27 nmol mol−1 for long-term exposure. In contrast, ozone mixing ratios were higher in extratropical cities (Santiago and São Paulo), with a short-term exposure level of 61 nmol mol−1 and long-term exposure levels varying between 40 and 41 nmol mol−1. Santiago (since 2017) and São Paulo (since 2008) exhibited positive trends of 0.6 and 0.3 nmol mol−1 yr−1, respectively, with very high certainty. We attributed these upward trends, or no evidence of variation, such as in Bogotá and Quito, to a well-established VOC-limited regime. However, we attributed the greater increase in the extreme percentile trends (≥ 90th) to heat waves and, in the case of southwestern South America, to wildfires associated with extreme meteorological events.

The aerosol and precipitable water vapor (PW) distribution over the tropical Andes region is characterized using Aerosol Robotic Network (AERONET) observations at stations in Medellin (Colombia), Quito (Ecuador), Huancayo (Peru), and La Paz (Bolivia). AERONET aerosol optical depth (AOD) is interpreted using PM2.5 data when available. Columnar water vapor derived from ozone soundings at Quito is used to compare against AERONET PW. MERRA-2 data are used to complement analyses. Urban pollution and biomass burning smoke (BBS) dominate the regional aerosol composition. AOD and PM2.5 yearly cycles for coincident measurements correlate linearly at Medellin and Quito. The Andes cordillera’s orientation and elevation funnel or block BBS transport into valleys or highlands during the two fire seasons that systematically impact South America. The February–March season north of Colombia and the Colombian-Venezuelan border directly impacts Medellin. Possibly, the March aerosol signal over Quito has a long-range transport component. At Huancayo and La Paz, AOD increases in September due to the influence of BBS in the Amazon. AERONET PW and sounding data correlate linearly but a dry bias with respect to soundings was identified in AERONET. PW and rainfall progressively decrease from north to south due to increasing altitude. This regional diagnosis is an underlying basis to evaluate future changes in aerosol and PW given prevailing conditions of rapidly changing atmospheric composition.

Abstract. Amid the current climate crisis, cities are being called to reduce levels of atmospheric pollutants that are short-lived climate forcers (SLCF) such as ozone and PM2.5. This endeavor presents new challenges in terms of control strategies. Here, we scrutinize the ozone production sensitivity to NOx and VOCs in Quito, Ecuador and Santiago, Chile, and we discuss the implications for precursor controls. To this end, we use a chemical box-model constrained with VOCs, meteorological, and air quality data. Comparable ozone production rates (P(O3)=15–35 ppbv h-1) were found to influence both cities, which lead to a well-established ozone season in Santiago, but not in Quito. A partial explanation to this difference is the distinct mixing conditions in both cities. Alkenes and aromatics contribute 60–90 % to ozone production in Quito and 50–60 % in Santiago. Aldehydes and ketones contribute an additional 20–30 % in Santiago. Isoprene contributes 10 % in Quito and 20 % in Santiago. Any isolated measure to reduce NOx alone would impact both cities negatively. For example, a 75 % reduction in NOx causes a 30 % increase in peak P(O3) in Quito and a 54 % increase in Santiago. In contrast, equal reductions in NOx and VOCs would have a beneficial effect. For example, a 75 % decrease in both precursors would cut the peak P(O3) by more than half in both cities. Therefore, only parallel controls on NOx and VOCs in both cities have the potential of curbing ozone from the simultaneous perspective of public health and climate action.

&lt;p&gt;Several Working Groups have been established within the frame of the second phase of the Tropospheric Ozone Assessment Report (TOAR-II). The Tropospheric Ozone Precursors focus Working Group (TOP WG) aims to examine the current regional and global distribution, variability and trends of ozone precursors. Part of our strategy has been to analyze in greater detail different regions of the globe. In particular, this work addresses South America, a region characterized by densely populated urban areas with high air pollution levels.&lt;/p&gt; &lt;p&gt;We use data from air quality monitoring networks that measure surface-level ozone, nitrogen oxides, carbon monoxide and meteorological variables. To date, we have validated and incorporated monitoring stations from Brazil (51), Chile (18), Colombia (13) and Ecuador (6) into our central database. To evaluate short- and long-term ozone exposure, we use the maximum daily 8-hour average (MDA8) and the peak season guideline proposed by the World Health Organization (WHO) set at 51 and 31 ppbv, respectively. We applied the Quantile Regression (QR) method to analyze ozone and precursor network trends. We also identified points in time series that mark changes in trends through a piecewise function.&lt;/p&gt; &lt;p&gt;The highest MDA8 ozone for 2015-2021 was found in S&amp;#227;o Paulo (52 ppbv) and Santiago (51 ppbv). In S&amp;#227;o Paulo, the short-term ozone exposure decreased by 7% compared to the average of the years prior to 2015 (period analyzed in TOAR phase I), while in Santiago, it increased by 10%. In Bogota and Quito, the MDA8 complied with the WHO guidelines (33 and 32 ppbv, respectively). Similarly, the long-term ozone exposure guideline was exceeded in S&amp;#227;o Paulo (39 ppbv) and Santiago (40 ppbv), while Bogota (25 ppbv) and Quito (26 ppbv) complied. The trend analysis showed that Quito was the only city with a negative ozone trend of -0.10 ppb/year (50th percentile) for the analyzed period. In turn, the S&amp;#227;o Paulo trend increased after 2008 (0.43 ppbv/year), while Santiago and Bogota have increased since 2017 (0.93 ppbv/year and 1.3 ppbv/year, respectively). We highlight that the positive trend in Santiago is driven mainly by the high percentiles (&gt;70th). Underlying processes that explain trends involve more efficient photochemical ozone formation (e.g., NO&lt;sub&gt;2&lt;/sub&gt;/NO&lt;sub&gt;x&lt;/sub&gt; trend) and meteorological factors.&lt;/p&gt; &lt;p&gt;This ongoing work aims to include more South American cities and background stations already available in the new TOAR database. Finally, we will project ozone trends for the next decade using machine learning techniques (random forest) under precursor emission scenarios and temperature projections.&lt;/p&gt;

Satellite observations of ozone in the tropics have feedback from in situ measurements at sea level stations, but the tropical Andes is a region that is yet to be included in systematic validations. In this work, ozonesondes launched from the equatorial Andes were used to evaluate total column ozone (TCO) measured by spaceborne sensors TROPOMI/S5P (2018–2021), GOME-2/MetOp-B, OMI/Aura, and OMPS/Suomi NPP (2014–2021). Likewise, we evaluated tropospheric column ozone (TrCO) measured by the first two. Additionally, we evaluated TCO and TrCO from reanalysis products MERRA-2 and CAMS-EAC4. Results indicate that TCO observations by OMPS/Suomi NPP produce the closest comparison to ozonesondes (− 0.2% mean difference) followed by OMI/Aura (+ 1.2% mean difference). Thus, they outperform the sensor with the highest spatial resolution of current satellite measurements, namely TROPOMI/S5P (+ 3.7% mean difference). This overprediction is similar to the one encountered for GOME-2/MetOp-B (+ 3.2% mean difference). A positive bias with respect to soundings was also identified in TrCO measured by TROPOMI/S5P (+ 32.5% mean difference). It was found that the climatology used by TROPOMI overpredicts ozone in the troposphere when compared with the mean of Andes measurements, while both data sets are essentially the same in the stratosphere. Regarding reanalysis products, MERRA-2 compares better to ozonesondes than CAMS, both for TCO and TrCO (mean differences are 1.9% vs. 3.3%, and 11.5% vs. 22.9%, respectively). Identifying spaceborne ozone measurements that currently perform the best over the region is relevant given the present conditions of rapidly changing atmospheric composition. At the same time, ozonesonde data in this work offer an opportunity to improve satellite observations in the Andean tropics, a challenging region for space measurements.

The steep slopes, highlands, and valleys of the Andes mountain chain are inhabited throughout its formidable length. This unique characteristic does not repeat in any other mountain region. The Andes shape weather and climate in South America. However, proper understanding of atmospheric phenomena influenced by a daunting altitudinal gradient is still behind what is needed to produce detailed and consistent climate projections. Despite significant advances, global models misrepresent key precipitation and circulation processes that are influenced by complex topography. Along with a lack of coordinated observations, the result is limited information to design preparedness measures, particularly to face extreme climate events. Of equal concern is the issue of air quality in densely urbanized countries that face decarbonization challenges and share a legacy of social inequity and political unrest. The complexity of the Andes region magnifies risks within all nations that share their influence. Thus, urgent action is needed to improve climate and air quality assessments with the direct purpose of strengthening policy-making processes.

Ozone, NO, NO2 as well as meteorological observations are continuously monitored at the Atmospheric Measurement Station (EMA, Spanish acronym) at Universidad San Francisco de Quito (USFQ) in Ecuador. The monitoring station is sited in Cumbayá, an Andean urban area in the valley east of Quito. In 2020, namely after the onset of the COVID-19 pandemic, primary emissions decreased due to various mobility restrictions and strategies applied in the city to try to curb the spread of the disease. These changes had an impact in ambient levels of NO and NO2 (collectively called NOx), which were recorded at EMA USFQ. On the other hand, an increase in ozone was detected when compared with measurements from previous years. In this work, the differences in NOx and ozone in 2020 with respect to levels observed in 2018 and 2019 are explored. To this end, an analysis that includes 10-minute measurements of the three species is presented along with meteorological data for 2018–2020. In addition, the typical diurnal patterns of the three species are analysed under regular traffic conditions as well as under different mobility restrictions adopted in 2020. Moreover, the seasonality of the three species is characterized within the context of weather patterns in the study region. Finally, an explanation of the observed levels of ozone, based on insight gained recently in regard to ozone production mechanisms in Quito, is presented.

In this study, we characterize atmospheric ozone over the tropical Andes in the boundary layer, the free troposphere, and the stratosphere; we quantify each contribution to total column ozone, and we evaluate the performance of the multi-sensor reanalysis (MSR2) in the region. Thus, we present data taken in Ecuador and Peru (2014–2019). The contribution from the surface was determined by integrating ozone concentrations measured in Quito and Cuenca (Ecuador) up to boundary layer height. In addition, tropospheric and stratospheric column ozone were quantified from ozone soundings (38) launched from Quito during the study time period. Profiles were compared against soundings at Natal (SHADOZ network) for being the closest observational reference with sufficient data in 2014–2019. Data were also compared against stratospheric mixing ratios from the Aura Microwave Limb Sounder (Aura MLS). Findings demonstrate that the stratospheric component of total column ozone over the Andes (225.2 ± 8.9 Dobson Units [DU]) is at similar levels as those observed at Natal (223.3 ± 8.6 DU), and observations are comparable to Aura MLS data. In contrast, the tropospheric contribution is lower over the Andes (20.2 ± 4.3 DU) when compared to Natal (35.4 ± 6.4 DU) due to a less deep and cleaner troposphere. From sounding extrapolation of Quito profiles down to sea level, we determined that altitude deducts about 5–7 DU from the total column, which coincides with a 3%–4% overestimation of the MSR2 over Quito and Marcapomacocha (Peru). In addition, when MSR2 data are compared along a transect that crosses from the Amazon over Quito, the Ecuadorian coast side, and into the Pacific, observations are not significantly different among the three first locations. Results point to coarse reanalysis resolution not being suitable to resolve the formidable altitude transition imposed by the Andes mountain chain. This work advances our knowledge of atmospheric ozone over the study region and provides a robust time series of upper air measurements for future evaluations of satellite and reanalysis products.

Abstract A characterization of ambient air levels of PM2.5, O3, SO2, NO2 and CO in the Galapagos Islands of Ecuador is presented from in situ and remote sensing observations. PM2.5 was derived from aerosol optical depth (AOD; AERONET) measured at the Universidad San Francisco de Quito, Galapagos Campus (2017–2019). Boundary layer (BL) ozone was obtained from Southern Hemisphere Additional Ozonesondes (SHADOZ) profiles (1998–2016). Background SO2 and pollution events during volcanic eruptions (2005–2018) were estimated from Ozone Monitoring Instrument (OMI) total column measurements through a well‐mixed volume approach. Similarly, ambient NO2 was estimated from OMI data (2012–2019). CO was obtained from Measurement Of Pollution In The Troposphere (MOPITT) observations (2012–2017). The study was complemented using Modern‐Era Retrospective Analysis for Research and Applications (MERRA‐2) reanalysis products and backward trajectory model runs. From the results, baseline levels of the analysed species (PM2.5 = 3.8 μg·m−3, O3 = 17 ppbv, SO2 = 3.6 ppbv, CO = 80 ppbv, NO2 in populated islands = 23 pptv as one year averages) are comparable with other pristine regions, but some factors can cause increased concentrations. First, high tourism seasons (February–April and July–September) raise background PM2.5, NO2 and CO. Furthermore, signals in July–September can be augmented by transport from biomass‐burning regions in the Amazon. This latter factor episodically causes ozone to increase up to 45–75 ppbv (1 hr mean). Lastly, volcanic eruptions raise SO2 up to almost 700 ppbv (24 hr mean) and increase PM2.5 to 29.5 μg·m−3 (1 hr mean). The present study provides for the first time baseline levels of air contaminants in the Galapagos, and identifies specific sources whose effect in time is necessary to monitor given global conditions of vulnerable environmental quality.