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All sourcesNASA NTRSDOE OSTI
NASA NTRS2006

Land-Cover and Land-Use Change in the Brazilian Amazon: Smallholders, Ranchers and Frontier Stratification

Tropical deforestation is a significant driver of global environmental change, given its impacts on the carbon cycle and biodiversity. Loss of the Amazon forest, the focus of this article, is of particular concern because of the size and the rapid rate at which the forest is being converted to agricultural use. In this article, we identify what has been the most important driver of deforestation in a specific colonization frontier in the Brazilian Amazon. To this end, we consider (1) the land-use dynamics of smallholder households, (2) the formation of pasture by large-scale ranchers, and (3) structural processes of land aggregation by ranchers. Much has been written about relations between smallholders and ranchers in the Brazilian Amazon, particularly those involving conflict over land, and this article explicates the implications of such social processes for land cover. Toward this end, we draw on panel data (1996-2002) and satellite imagery (1986-1999) to show the deforestation that is attributable to small- and largeholders, and the deforestation that is attributable to aggregations of property arising from a process that we refer to as frontier stratification. Evidently, most of the recent deforestation in the study area has resulted from the household processes of smallholders, not from conversions to pasture pursuant to the appropriations of smallholders' property by well-capitalized ranchers or speculators.

Aldrich, Stephen P.↗
NASA NTRS2009

Emissions from Biomass Burning in the Yucatan

In March 2006 two instrumented aircraft made the first detailed field measurements of biomass burning (BB) emissions in the Northern Hemisphere tropics as part of the MILAGRO project. The aircraft were the National Center for Atmospheric Research C-130 and a University of Montana/US Forest Service Twin Otter. The initial emissions of up to 49 trace gas or particle species were measured from 20 deforestation and crop residue fires on the Yucatan peninsula. This included two trace gases useful as indicaters of BB (HCN and acetonitrile) and several rarely, or never before, measured species: OH, peroxyacetic acid, propanoic acid, hydrogen peroxide, methane sulfonic acid, and sulfuric acid. Crop residue fires emitted more organic acids and ammonia than deforestation fires, but the emissions from the main fire types were otherwise fairly similar. The Yucatan fires emitted unusually amounts of SO2 and particle chloride, likely due to a strong marine influence on the peninsula.

Yokelson, R.↗
DOE OSTI2024

Increased Occurrence of Large–Scale Windthrows Across the Amazon Basin

Convective storms with strong downdrafts create windthrows: snapped and uprooted trees that locally alter the structure, composition, and carbon balance of forests. Comparing Landsat imagery from subsequent years, we documented temporal and spatial variation in the occurrence of large (≥30 ha) windthrows across the Amazon basin from 1985 to 2020. Over 33 individual years, we detected 3179 large windthrows. Windthrow density was greatest in the central and western Amazon regions, with ~33% of all events occurring in ~3% of the monitored area. Return intervals for large windthrows in the same location of these “hotspot” regions are centuries to millennia, while over the rest of the Amazon they are >10,000 years. Our data demonstrate a nearly 4–fold increase in windthrow number and affected area between 1985 (78 windthrows and 6,900 ha) and 2020 (264 events and 32,170 ha), with more events of >500 ha size since 1990. Such extremely large events (>500 ha up to 2,543 ha) are responsible for interannual variation in the overall median (84 ± 5.2 ha; ±95% CI) and mean (147 ± 13 ha) windthrow area, but we did not find significant temporal trends in the size distribution of windthrows with time. Our results document increased damage from convective storms over the past 40 years in the Amazon, filling a gap in temporal records for tropical regions. Our publicly accessible large windthrow database provides a valuable tool for exploring dynamic conditions leading to damaging storms and their ecological impact on Amazon forests.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Global impacts of vegetation clumping on regulating land surface heat fluxes

The clumping index (CI) quantifies the non-random distribution of vegetation across space, which regulates the canopy radiative transfer processes and land surface carbon, water, and energy cycles. However, its impact on global surface energy budget, particularly sensible heat fluxes and surface temperature, is not well understood. Additionally, while there have been studies showing significant seasonal variations in CI, the impacts of these variations on surface energy fluxes remain unclear. In this study, we incorporated satellite-derived spatially and temporally explicit CI data into the Community Land Model version 5 (CLM5) to evaluate the effects of CI on global land energy fluxes. Our results showed that including CI increased the global mean sensible heat flux dissipated from ground by 3.9 W m -2 (~18%), while decreasing the global mean vegetation sensible heat flux by 4.9 W m -2 (~65%), resulting in a total sensible heat decrease of 1.0 W m -2 (~3%). In contrast, CI increased the global mean latent heat flux by 0.8 W m -2 (~2%), primarily due to increased evapotranspiration (up to 11 W m -2 ) in tropical regions. We also found considerable impacts of seasonal variations in CI, particularly on sensible heat fluxes from ground and vegetation in evergreen needleleaf forests and deciduous needleleaf forests. Using constant CI rather than considering seasonal variations resulted in significant overestimation and underestimation of the sensible heat fluxes from vegetation and ground, respectively, in boreal summer. In conclusion, these changes in surface energy fluxes caused by CI and its seasonal variations led to up to 1.7 and 0.5 K differences in simulated mean ground temperature. These findings highlight the importance of including CI and considering its seasonal variations in modeling land surface energy fluxes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

A new data-driven map predicts substantial undocumented peatland areas in Amazonia

Tropical peatlands are among the most carbon-dense terrestrial ecosystems yet recorded. Collectively, they comprise a large but highly uncertain reservoir of the global carbon cycle, with wide-ranging estimates of their global area (441 025–1700 000 km 2 ) and below-ground carbon storage (105–288 Pg C). Substantial gaps remain in our understanding of peatland distribution in some key regions, including most of tropical South America. Here we compile 2413 ground reference points in and around Amazonian peatlands and use them alongside a stack of remote sensing products in a random forest model to generate the first field-data-driven model of peatland distribution across the Amazon basin. Our model predicts a total Amazonian peatland extent of 251 015 km 2 (95th percentile confidence interval: 128 671–373 359), greater than that of the Congo basin, but around 30% smaller than a recent model-derived estimate of peatland area across Amazonia. The model performs relatively well against point observations but spatial gaps in the ground reference dataset mean that model uncertainty remains high, particularly in parts of Brazil and Bolivia. For example, we predict significant peatland areas in northern Peru with relatively high confidence, while peatland areas in the Rio Negro basin and adjacent south-western Orinoco basin which have previously been predicted to hold Campinarana or white sand forests, are predicted with greater uncertainty. Similarly, we predict large areas of peatlands in Bolivia, surprisingly given the strong climatic seasonality found over most of the country. Very little field data exists with which to quantitatively assess the accuracy of our map in these regions. Data gaps such as these should be a high priority for new field sampling. This new map can facilitate future research into the vulnerability of peatlands to climate change and anthropogenic impacts, which is likely to vary spatially across the Amazon basin.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1989

Ecological applications of high resolution spectrometry

Future directions of NASA's space program plans include a significant effort at studying the Earth as a system of interrelated ecosystems. As part of NASA's Earth Observing System (Eos) Program a series of space platforms will be launched and operated to study the Earth with a variety of active and passive instruments. Several of the Eos instruments will be capable of imaging the planet's surface reflectance on a large number of very narrow portions of the solar spectrum. After the development of appropriate algorithms, this reflectance information will be used to determine key parameters about the structure and function of terrestrial and aquatic ecosystems and the pattern and processes of those systems across large areas of the globe. Algorithm development applicable to terrestrial systems will permit the inference of ecological processes from high resolution spectrometry data, similar to that to be forthcoming from the Eos mission. The first summer was spent working with tropical soils and relating their reflectance characteristics to particle size, iron content, and color. This summer the emphasis is on vegetation and work was begun with the Forest Ecosystems Dynamics Project in the Earth Resources Branch where both optical and radar characteristics of a mixed conifer/hardwood forest in Maine are being studied for use in a ecological modeling effort. A major series of aircraft overflights will take place throughout the summer. Laboratory and field spectrometers are used to measure the spectral reflectance of a hierarchy of vegetation from individual leaves to whole canopies for eventual modeling of their nutrient content using reflectance data. Key leaf/canopy parameters are being approximated including chlorophyll, nitrogen, phosphorus, water content, and leaf specific weight using high resolution spectrometry alone. Measurements are made of carbon exchange across the landscape for input to a spatial modeling effort to gauge production within the forest. A Geographic Information System approach is used to associate these data, images, and other collateral information for the forest into a database with a common projection suitable for spatial modeling.

Lawrence, William T.↗
NASA NTRS1994

A meteorological interpretation of the Arctic Boundary Layer Expedition (ABLE) 3B flight series

The Arctic Boundary Layer Expedition (ABLE) 3B was conducted to determine the summertime tropospheric distribution, sources, and sinks of important trace gas and aerosol species over the wetlands and boreal forests of central and eastern Canada. Isentropic trajectories and analyzed midtropospheric circulation patterns were used to group flights according to the transport histories of polar, midlatitude, or tropical air masses which were sampled. These data were then divided into bands of potential temperature levels representing the low, middle, and maximum aircraft altitudes to assess the effects of both local and long distance transport and natural and man-made pollutants to the measured chemical species. Detailed case studies are provided to depict the complex three-dimensional airflow regimes that transported air with differing chemical signatures to the study area. Mission 6 details the large-scale movement of smoke in the generally prevailing west to northwesterly airflow that was observed on the majority of flights. Mission 1 analyzes the horizontal and vertical motions of maritime Pacific air in the upper troposphere that was routinely mixed downward to the aircraft altitude. Finally, mission 14 tracks the far northward excursion of tropical air that had been associated with a Pacific typhoon. The following three factors all had important influences on the collected chemical data sets: (1) local and distant stratospheric in puts into the upper and middle troposphere; (2) biomass-burning plumes from active fires in Alaska and Canada; (3) a band of 'low ozone' upper tropospheric air that was observed by airborne differential absorption lidar (DIAL) above the aircraft maximum altitude. Other modification factors observed on some flights included urban pollution from U.S. and Canadian cities, tropical air that had been associated with a Pacific typhoon, and precipitation scavenging by clouds and rain. Many flights were affected by several of the above factors which led to complex chemical signatures that will be discussed in other companion papers.

Shipham, Mark C.↗
NASA NTRS2014

Far-Reaching Impacts of African Dust- A Calipso Perspective

African dust can transport across the tropical Atlantic and reach the Amazon basin, exerting far-reaching impacts on climate in downwind regions. The transported dust influences the surface-atmosphere interactions and cloud and precipitation processes through perturbing the surface radiative budget and atmospheric radiative heating and acting as cloud condensation nuclei and ice nuclei. Dust also influences biogeochemical cycle and climate through providing nutrients vital to the productivity of ocean biomass and Amazon forests. Assessing these climate impacts relies on an accurate quantification of dust transport and deposition. Currently model simulations show extremely large diversity, which calls for a need of observational constraints. Kaufman et al. (2005) estimated from MODIS aerosol measurements that about 144 Tg of dust is deposited into the tropical Atlantic and 50 Tg of dust into the Amazon in 2001. This estimated dust import to Amazon is a factor of 3-4 higher than other observations and models. However, several studies have argued that the oversimplified characterization of dust vertical profile in the study would have introduced large uncertainty and very likely a high bias. In this study we quantify the trans-Atlantic dust transport and deposition by using 7 years (2007-2013) observations from CALIPSO lidar. CALIPSO acquires high-resolution aerosol extinction and depolarization profiles in both cloud-free and above-cloud conditions. The unique CALIPSO capability of profiling aerosols above clouds offers an unprecedented opportunity of examining uncertainties associated with the use of MODIS clear-sky data. Dust is separated from other types of aerosols using the depolarization measurements. We estimated that on the basis of 7-year average, 118142 Tg of dust is deposited into the tropical Atlantic and 3860 Tg of dust into the Amazon basin. Substantial interannual variations are observed during the period, with the maximum to minimum ratio of about 1.6 and 2.5 for the deposition to the tropical Atlantic and Amazon, respectively. The MODIS-based estimates appear to fall within the range of CALIPSO-based estimates; and the difference between MODIS and CALIPSO estimates can be largely attributed to the interannual variability, which is corroborated by long-term surface dust concentration observations in the tropical Atlantic. Considering that CALIPSO generally tends to underestimate the aerosol loading, our estimate is likely to represent a low bound for the dust transport and deposition estimate. The finding suggests that models have substantial biases and considerable effort is needed to improve model simulations of dust cycle.

dust↗
DOE OSTI2021

Southwest Pacific tropical cyclone development classification utilizing machine learning and synoptic composites

This study evaluates the ability of machine learning algorithms to classify tropical depressions (TDs) and tropical storms (TSs) in the western region of the southwest Pacific Ocean (SWPO). Decision rules are generated to predict the environment required for a depression to fully develop into a mature storm, and the most influential predictors in the classification decision are ranked. TD and TS are discriminated based on a maximum sustained wind speed threshold (≥17 ms -1 ). Various aerosol, thermodynamic, and dynamic parameters are extracted closest to the initiation point of each non-developing and developing sample. The covariates associated with each labelled sample are used to train a decision tree and random forest model. Results using a testing dataset suggest the random forest approach more accurately distinguishes between non-developing and developing samples. The classification accuracy of the decision tree and random forest are 72% and 91%, respectively. Random forest outperformed the decision tree by providing higher accuracy in test data. The most important variables for binary classification are sea salt aerosol optical depth (AOD), 1,000 mb relative humidity, and sea surface temperature. AOD is a quantitative estimate of the aerosols presents in the air through the extinction of a ray of light as it passes through the atmosphere. Mean composite maps constructed in an unsupervised manner have been created for the most important variables identified by the random forest classifier during TD and TS events to highlight the difference in geophysical and aerosol variables' climatology during the two different classifications. This work will advance the risk management strategies for northeastern Australia and other SWPO basin islands to control their tropical cyclone related losses through prioritizing forecasting variables that are the strongest predictors of the strengthening of tropical depressions into tropical cyclones.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Oxidation of soil organic carbon during an anoxic-oxic transition

Redox reactions of iron (Fe) can play an important role in controlling the stability and transformation of organic carbon (OC) in soils. However, there is limited knowledge about the dynamics of Fe and OC in soils during anoxic-oxic transitions, which are common in temperate and tropical biomes. In this study, we investigated the fate and transformation of Fe and OC during a 5-day oxic incubation of four pre-reduced (8 days anoxic) forest soils. Up to 3.7% of total OC in the pre-reduced soils was oxidized to CO 2 , in conjunction with the oxidation of 31 –84% of the extractable Fe(II). OC oxidation in pre-reduced soils was lower than non-reducedcontrol soils, indicating that recently anoxically-incubated soils support lower OC metabolism upon re-oxidation than consistently oxic soils. Oxic OC oxidation was negatively correlated with the fraction of Fe-bound OC and also the fraction of short-range-ordered (SRO) Fe oxides. These results suggest that association with Fe oxides—especially SRO Fe oxides—can inhibit the availability of OC for oxidation. However, the difference between the oxidation of OC in pre40 reduced soils and consistently oxic controls could not be linked to the moderate changes in the Fe mineral composition during the anoxic-oxic transition, indicating the importance of longer term OC association with Fe oxides, as well as other processes, in regulating the oxidation of OC during the redox fluctuations. OC association with Fe oxides should be considered during simulations of biogeochemical cycling of OC in soils during the redox fluctuations, for which other processes such as the anoxic transformation of OC and response of the microbial community also need to be incorporated.

58 GEOSCIENCES↗
NASA NTRS2001

Measurements of an Anomalous Global Methane Increase During 1998

Measurements of atmospheric methane from a globally distributed network of air sampling sites indicate that the globally averaged CH4 growth rate increased from an average of 3.9 ppb/yr during 1995-1997 to 12.7 +/- 0.6 ppb in 1998. The global growth rate then decreased to 2.6 +/- 0.6 ppb during 1999, indicating that the large increase in 1998 was an anomaly and not a return to the larger growth rates observed during the late 1970s and early 1980s. The increased growth rate represents an anomalous increase in the imbalance between CH4 sources and sinks equal to approximately 24 Tg CH4 during 1998. Wetlands and boreal biomass burning are sources that may have contributed to the anomaly. During 1998, the globally averaged temperature anomaly was +0.67 C, the largest temperature anomaly in the modern record. A regression model based on temperature and precipitation anomalies was used to calculate emission anomalies of 11.6 Tg CH4 from wetlands north of 30 N and 13 Tg CH4 for tropical wetlands during 1998 compared to average emissions calculated for 1982-1993. In 1999, calculated wetland emission anomalies were negative for high northern latitudes and the tropics, contributing to the low growth rate observed in 1999. Also 1998 was a severe fire year in boreal regions where approximately 1.3x10(exp 5) sq km of forest and peat land burned releasing an estimated 5.7 Tg CH4

Dlugokencky, E. J.↗
NASA NTRS2013

Assessment and Applications of NASA Ozone Data Products Derived from Aura OMI-MLS Satellite Measurements in Context of the GMI Chemical Transport Model

Measurements from the Ozone Monitoring Instrument (OMI) and Microwave Limb Sounder (MLS), both onboard the Aura spacecraft, have been used to produce daily global maps of column and profile ozone since August 2004. Here we compare and evaluate three strategies to obtain daily maps of tropospheric and stratospheric ozone from OMI and MLS measurements: trajectory mapping, direct profile retrieval, and data assimilation. Evaluation is based upon an assessment that includes validation using ozonesondes and comparisons with the Global Modeling Initiative (GMI) chemical transport model (CTM). We investigate applications of the three ozone data products from near-decadal and inter-annual timescales to day-to-day case studies. Zonally averaged inter-annual changes in tropospheric ozone from all of the products in any latitude range are of the order 1-2 Dobson Units while changes (increases) over the 8-year Aura record investigated http://eospso.gsfc.nasa.gov/atbd-category/49 vary approximately 2-4 Dobson Units. It is demonstrated that all of the ozone products can measure and monitor exceptional tropospheric ozone events including major forest fire and pollution transport events. Stratospheric ozone during the Aura record has several anomalous inter-annual events including stratospheric warming split events in the Northern Hemisphere extra-tropics that are well captured using the data assimilation ozone profile product. Data assimilation with continuous daily global coverage and vertical ozone profile information is the best of the three strategies at generating a global tropospheric and stratospheric ozone product for science applications.

GMI↗
NASA NTRS2017

The Impact of Anthropogenic Land Use and Land Cover Change on Regional Climate Extremes

Recent research highlights the role of land surface processes in heat waves, droughts, and other extreme events. Here we use an earth system model (ESM) from the Geophysical Fluid Dynamics Laboratory (GFDL) to investigate the regional impacts of historical anthropogenic land useland cover change (LULCC) on combined extremes of temperature and humidity. A bivariate assessment allows us to consider aridity and moist enthalpy extremes, quantities central to human experience of near-surface climate conditions. We show that according to this model, conversion of forests to cropland has contributed to much of the upper central US and central Europe experiencing extreme hot, dry summers every 2-3 years instead of every 10 years. In the tropics, historical patterns of wood harvesting, shifting cultivation and regrowth of secondary vegetation have enhanced near surface moist enthalpy, leading to extensive increases in the occurrence of humid conditions throughout the tropics year round. These critical land use processes and practices are not included in many current generation land models, yet these results identify them as critical factors in the energy and water cycles of the midlatitudes and tropics.

Near-surface↗
DOE OSTI2023

A neotropical perspective on the uniqueness of the Holocene among interglacials

Abstract Understanding how tropical systems have responded to large-scale climate change, such as glacial-interglacial oscillations, and how human impacts have altered those responses is key to current and future ecology. A sedimentary record recovered from Lake Junín, in the Peruvian Andes (4085 m elevation) spans the last 670,000 years and represents the longest continuous and empirically-dated record of tropical vegetation change to date. Spanning seven glacial-interglacial oscillations, fossil pollen and charcoal recovered from the core showed the general dominance of grasslands, although during the warmest times some Andean forest trees grew above their modern limits near the lake. Fire was very rare until the last 12,000 years, when humans were in the landscape. Here we show that, due to human activity, our present interglacial, the Holocene, has a distinctive vegetation composition and ecological trajectory compared with six previous interglacials. Our data reinforce the view that modern vegetation assemblages of high Andean grasslands and the presence of a defined tree line are aspects of a human-modified landscape.

Science & Technology - Other Topics↗
NASA NTRS2021

Mapping the Extent of Mangrove Ecosystem Degradation by Integrating an Ecological Conceptual Model with Satellite Data

Anthropogenic and natural disturbances can cause degradation of ecosystems, reducing their capacity to sustain biodiversity and provide ecosystem services. Understanding the extent of ecosystem degradation is critical for estimating risks to ecosystems, yet there are few existing methods to map degradation at the ecosystem scale and none using freely available satellite data for mangrove ecosystems. In this study, we developed a quantitative classification model of mangrove ecosystem degradation using freely available earth observation data. Crucially, a conceptual model of mangrove ecosystem degradation was established to identify suitable remote sensing variables that support the quantitative classification model, bridging the gap between satellite-derived variables and ecosystem degradation with explicit ecological links. We applied our degradation model to two case-studies, the mangroves of Rakhine State, Myanmar, which are severely threatened by anthropogenic disturbances, and Shark River within the Everglades National Park, USA, which is periodically disturbed by severe tropical storms. Our model suggested that 40% (597 km2) of the extent of mangroves in Rakhine showed evidence of degradation. In the Everglades, the model suggested that the extent of degraded mangrove forest increased from 5.1% to 97.4% following the Category 4 Hurricane Irma in 2017. Quantitative accuracy assessments indicated the model achieved overall accuracies of 77.6% and 79.1% for the Rakhine and the Everglades, respectively. We highlight that using an ecological conceptual model as the basis for building quantitative classification models to estimate the extent of ecosystem degradation ensures the ecological relevance of the classification models. Our developed method enables researchers to move beyond only mapping ecosystem distribution to condition and degradation as well. These results can help support ecosystem risk assessments, natural capital accounting, and restoration planning and provide quantitative estimates of ecosystem degradation for new global biodiversity targets.

Calvin K. F. Lee↗
NASA NTRS2004

The GOES-R Lightning Mapper Sensor

The Lightning Mapper Sensor on GOES-R builds on previous measurements of lightning from low earth orbit by the OTD (Optical Transient Detector) and LIS (Lightning Imaging Sensor) sensors. Unlike observations from low earth orbit, the GOES-R platform will allow continuous monitoring of lightning activity over the Continental United States and southern Canada, Central and South America, and portions of the Atlantic and Pacific Oceans. The LMS will detect total (cloud-to-ground and intracloud) lightning at storm scale resolution (approx. 8 km) using a highly sensitive Charge Coupled Device (CCD) detector array. Discrimination between lightning optical transients and a bright sunlit background scene is accomplished by employing spectral, spatial, and temporal filtering along with a background subtraction technique. The result is 24 hour detection capability of total lightning. These total lightning observations can be made available to users within about 20 seconds. Research indicates a number of ways that total lightning observations from LMS could benefit operational activities, including 1) potential increases in lead times and reduced false alarms for severe thunderstorm and tornado Warnings, 2) improved routing of &rail around thunderstorms, 3) support for spacecraft launches and landings, 4) improved ability to monitor tropical cyclone intensity, 5) ability to monitor thunderstorm intensification/weakening during radar outages or where radar coverage is poor, 6) better identification of deep convection for the initialization of numerical prediction models, 7) improved forest fire forecasts, 8) identification of convective initiation, 9) identification of heavy convective snowfall, and 10) enhanced temporal resolution of storm evolution (1 minute) than is available from radar observations. Total lightning data has been used in an operational environment since July 2003 at the Huntsville, Alabama National Weather Service office. Total lightning measurements are obtained by the North Alabama Lightning Mapping Array (LMA) and have successfully been used in warning decisions. Every 2 minutes, total lightning counts in 2 km by 2 km horizontal, 1 km vertical grids are available to forecasters on an AWIPS (Advanced Weather Interactive Processing System) workstation. Experience with the LMA total lightning data is used to illustrate the potential use of LMS data that would be available to forecasters across the US. This abstract is for submission as a presentation to the National Weather Association Annual Meeting to be held 16-21 October 2004 in Portland, OR. This abstract will be published in the conference proceedings.

Buechler, Dennis↗
NASA NTRS2019

Trends and Seasonal Variability of Atmospheric NO2 and HNO3 Concentrations Across Three Major African Biomes Inferred from Long-Term Series of Ground-Based and Satellite Measurements

In the framework of the INDAAF (International Network to study Deposition and Atmospheric chemistry in AFrica) programme, part of the ACTRIS (Aerosols, Clouds, and Trace gases Research InfraStructure), European Research Infrastructure for the long-term observation of Aerosol, Cloud, and Trace gases, this paper aims to study trends and seasonal variability of surface atmospheric NO2 and HNO3 concentrations, and OMI (Ozone Monitoring Instrument) NO2 over 6 sites in tropical Africa. Sites are located in west and central Africa to represent the major African biomes: dry savanna (Banizoumbou, Niger and Katibougou, Mali), wet savanna (Djougou, Benin and Lamto, Côte d’Ivoire) and forest (Bomassa, Republic of Congo and Zoétélé, Cameroon). Ground-based NO2 and HNO3 concentrations were obtained over the period 1998–2015 using INDAAF passive samplers at a monthly basis, and NO2 Vertical Column Densities (VCDs) from OMI for a 1-degree grid cell around each sites were obtained from 2005 to 2015. Mean annual NO2 concentrations ranged from 2.3 plus or minus 1.2 to 0.9 plus or minus 0.4 parts per billion (ppb) from dry savannas to forests, representing a north-south gradient. In dry savannas, we observe two concentration peaks of NO2 appearing at the beginning and the end of the wet season both for ground-based and satellite measurements, whereas at wet savannas and forest sites, NO2 concentrations are highest in the dry season. The seasonality of surface NO2 observations provide further evidence for a large role of microbial soil NOx emissions in dry savannas and of biomass burning NOx emissions in wet savanna and forest sites. Mean annual HNO3 concentrations ranged from 0.4 to 0.5 ppb in dry and wet savannas to 0.2 to 0.3 ppb in forest. In dry ecosystems, higher HNO3 concentrations are measured in the early wet season, consistent with NO2 results. The analysis of a long-term dataset of surface O3 concentrations indicates that HNO3 production can mainly be explained by the photo-oxidation of NOx. Mann-Kendall and Seasonal Kendall statistical tests showed that NO2 surface concentrations have a significant decreasing seasonal and annual trends at multiple sites (p-value less than 0.05) ranging from -2.96 percent per year (at Zoétélé) to -0.64 percent per year (at Banizoumbou). HNO3 results indicate no trends except at Bomassa (1.07 percent per year). The decreasing NO2 ground-based concentration trends observed in wet savannas sites are correlated with OMI NO2 decreasing trends at these sites. Trends obtained for NO2 concentrations in wet savanna and forest ecosystems are consistent with trends of NOₓ biomass burning emissions.

Trends↗