nasa-gesdisc/es-publications-researchareas huggingface dataset:
Perspectives on agroecological transition: the case of Guacheta municipality, Colombia (2023)

Specialization of agriculture in the Colombian Andes has increased smallholder vulnerability to climate change and global price fluctuations and has also affected the socio-economic and environmental conditions. Promoting sustainable agriculture in the region requires a holistic understanding of complex agroecosystems. This study identifies and analyzes the main challenges for agriculture and possibilities for agroecological transition of small-scale farms in Guacheta, Colombia. Using the Tool for Agroecology Performance Evaluation (TAPE), 10 elements of agroecology and core performance criteria were evaluated on seven farms. Several key actors were then interviewed, to triangulate data and understand current challenges and possible future pathways. It was found that drier climate and variations in rainfall patterns pose major challenges to current production systems. Limited possibilities for participation in land governance, lack of interest in agriculture among young people, and lack of access to markets hinder the development of sustainable agriculture. Current specialized practices in dairy and potato production are associated with reduced agricultural biodiversity and dependency on agrochemicals, leading to weak synergies and low profitability within agroecosystems. Implementation of agroecological principles and practices such as crop and income diversification and promoting joint action in agricultural development could help overcome sustainability issues in Guacheta.

Research areas: Agriculture
Modeling and improving Ethiopian pasture systems (2018)

The production of pasture in Ethiopia was simulated by means of a dynamic model. Most of the country is characterized by a tropical monsoon climate with mild temperatures and precipitation mainly concentrated in the JuneSeptember period (main rainy season). The production model is driven by solar radiation and takes into account limitations due to relocation, maintenance respiration, conversion to final dry matter, temperature, water stress, and nutrients availability. The model also considers the senescence of grassland which strongly limits the nutritional value of grasses for livestock. The simulation for the 19822009 period, performed on gridded daily time series of rainfall and maximum and minimum temperature with a resolution of 0.5, provided results comparable with values reported in literature. Yearly mean yield in Ethiopia ranged between 1.8 metric ton per hectare (t ha-1) (2002) and 2.6 t ha1 (1989) of dry matter with values above 2.5 t ha-1 attained in 1983, 1985, 1989, and 2008. The Ethiopian territory has been subdivided in 1494 cells and a frequency distribution of the per-cell yearly mean pasture production has been obtained. This distribution ranges from 0 to 7 t ha-1 and it shows a right skewed distribution and a modal class between 1.52 t ha-1. Simulation carried out on long time series for this peculiar tropical environment give rise to as lot of results relevant by the agroecological point of view on space variability of pasture production, main limiting factors (solar radiation, precipitation, temperature), and relevant meteo-climatic cycles affecting pasture production (seasonal and inter yearly variability, ENSO). These results are useful to establish an agro-ecological zoning of the Ethiopian territory.

Research areas: Agriculture
Geographic information systems-based land suitability assessment for switchgrass cultivation in marginal lands: a case study for Izmir-Turkey (2022)

Energy crop cultivation is considered the main factor in the rapid increase in the share of biomass energy in the future global energy supply. However, the most critical issue for the cultivation of energy crops will be establishing sustainable energy cropping systems and protecting agricultural areas devoted to food and feed crops. Therefore, the present study aims to identify key criteria for energy crop cultivation areas and to develop a Geographic information systems (GISs)- and multi-criteria evaluation model (MCE)-based methodology. This study employs a GIS-based MCE technique, including fuzzy standardization, analytic hierarchy process (AHP), and weighted overlay for analyzing land suitability to switchgrass cultivation for the case study in Izmir-Turkey. The criteria identified in this study include climatic parameters, soil characteristics, topography, and land restrictions for land-use compatibility. Climate data were employed by TerrSets Crop Climate Suitability Model to determine the climatic suitability of switchgrass in the city. Subsequently, an assessment model of land suitability for switchgrass cultivation was developed by integrating AHP in the ArcGIS environment. Here, the highest specific weight was attained for climatic suitability (0.22), and the lowest was found for elevation (0.094). Significantly, 69.4% (40,725 ha) of the potential cultivation area was moderately suitable and higher, and 30.5% (17,896 ha) was low suitable for switchgrass cultivation. Therefore, it was concluded that the applied methodology could be a practical approach for sustainable biofuels production and environmental protection and can be employed for different energy crops and regions.

Research areas: Agriculture, Energy Production/Use
Remote sensing and modelling analysis of the extreme dust storm hitting the Middle East and eastern Mediterranean in September 2015 (2017)

Abstract. The extreme dust storm that affected the Middle East and the eastern Mediterranean in September 2015 resulted in record-breaking dust loads over Cyprus with aerosol optical depth exceeding 5.0 at 550 nm. We analyse this event using profiles from the European Aerosol Research Lidar Network (EARLINET) and the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO), geostationary observations from the Meteosat Second Generation (MSG) Spinning Enhanced Visible and Infrared Imager (SEVIRI), and high-resolution simulations from the Regional Atmospheric Modeling System (RAMS). The analysis of modelling and remote sensing data reveals the main mechanisms that resulted in the generation and persistence of the dust cloud over the Middle East and Cyprus. A combination of meteorological and surface processes is found, including (a) the development of a thermal low in the area of Syria that results in unstable atmospheric conditions and dust mobilization in this area, (b) the convective activity over northern Iraq that triggers the formation of westward-moving haboobs that merge with the previously elevated dust layer, and (c) the changes in land use due to war in the areas of northern Iraq and Syria that enhance dust erodibility.

Research areas: Air Quality
Global-scale daily riverine DOC fluxes from lands to the oceans with a generic model (2020)

The export of riverine dissolved organic carbon (DOC) to the oceans is determinant in carbon exchanges of the estuaries and oceanic food webs. Past research returned a global DOC export around 160450 TgC.yr1 by using complex process-based models or yearly average estimates that could have been misjudged. In this study, we try to understand the complex processes explaining daily DOC exports among 341 exoreic watersheds covering 71% of freshwater flows to the oceans. Based on a dataset of DOC concentrations among rivers at the global scale, we were able to link DOC concentrations to daily discharge, the ration between the soil organic carbon content and the amount of precipitations and the average air temperature in the watersheds. We have found a global riverine DOC flux of 131.6 TgC.yr1 based on daily data and a generic model. Tropical and cold watersheds are the main contributors with 49.5% and 33.3% of the global riverine DOC flux on the two last decades while temperate, semi-arid and polar basins represent 15.9%, 0.7% and 0.6%, respectively. Temporal exports range from 0.1 to 0.16 TgC.day1 in tropical areas, 0.030.32 TgC.day1 in cold areas and 0.030.08 TgC.day1 in temperate areas. Atlantic and Arctic oceans receive the most important fluxes (0.120.2 and 0.010.26 TgC.day1). In a climate change context, this generic equation could be introduced in hydrological modelling tools to predict future DOC fluxes trends.

Research areas: Water Quality, Greenhouse Gases, Atmospheric/Ocean Indicators
Global ammonia emissions from synthetic nitrogen fertilizer applications in agricultural systems: Empirical and process-based estimates and uncertainty (2018)

AbstractExcessive ammonia (NH3) emitted from nitrogen (N) fertilizer applications in global croplands plays an important role in atmospheric aerosol production, resulting in visibility reduction and regional haze. However, large uncertainty exists in the estimates of NH3 emissions from global and regional croplands, which utilize different data and methods. In this study, we have coupled a processbased Dynamic Land Ecosystem Model (DLEM) with the bidirectional NH3 exchange module in the Community Multiscale AirQuality (CMAQ) model (DLEMBiNH3) to quantify NH3 emissions at the global and regional scale, and cropspecific NH3 emissions globally at a spatial resolution of 0.5 0.5 during 19612010. Results indicate that global NH3 emissions from N fertilizer use have increased from 1.9 0.03 to 16.7 0.5 Tg N/year between 1961 and 2010. The annual increase of NH3 emissions shows large spatial variations across the global land surface. Southern Asia, including China and India, has accounted for more than 50% of total global NH3 emissions since the 1980s, followed by North America and Europe. Rice cultivation has been the largest contributor to total global NH3 emissions since the 1990s, followed by corn and wheat. In addition, results show that empirical methods without considering environmental factors (constant emission factor in the IPCC Tier 1 guideline) could underestimate NH3 emissions in context of climate change, with the highest difference (i.e., 6.9 Tg N/year) occurring in 2010. This study provides a robust estimate on global and regional NH3 emissions over the past 50 years, which offers a reference for assessing air quality consequences of future nitrogen enrichment as well as nitrogen use efficiency improvement.

Research areas: Air Quality, Agriculture
New ground-based Fourier-transform near-infrared solar absorption measurements of XCO₂, XCH₄ and XCO at Xianghe, China (2020)

The column-averaged dry-air mole fractions of CO2 (XCO2), CH4 (XCH4) and CO (XCO) have been measured with a Bruker IFS 125HR Fourier-transform infrared (FTIR) spectrometer at Xianghe (39.75 N, 116.96 E, north China) since June 2018. This paper presents the site, the characteristics of the FTIR system and the measurements. The instrumental setup follows the guidelines of the Total Carbon Column Observing Network (TCCON): the near-infrared spectra are recorded by an InGaAs detector together with a CaF2 beam splitter, and the HCl cell measurements are recorded regularly to derive the instrument line shape (ILS) showing that the instrument is correctly aligned. The TCCON standard retrieval code (GGG2014) is applied to retrieve XCO2, XCH4 and XCO. The resulting time series between June 2018 and July 2019 are presented, and the observed seasonal cycles and day-to-day variations in XCO2, XCH4 and XCO at Xianghe are discussed. In addition, the paper shows comparisons between the data products retrieved from the FTIR measurements at Xianghe and co-located Orbiting Carbon Observatory-2 (OCO-2) and Tropospheric Monitoring Instrument (TROPOMI) satellite observations. The comparison results appear consistent with validation results obtained at TCCON sites for XCO2 and XCH4, while for XCO they highlight the occurrence of frequent high-pollution events. As Xianghe lies in a polluted area in north China where there are currently no TCCON sites, this site can fill the TCCON gap in this region and expand the global coverage of the TCCON measurements. The Xianghe FTIR XCO2, XCH4 and XCO data can be obtained at https://doi.org/10.18758/71021049 (Yang et al., 2019).

Research areas: Validation, Air Quality
Inferring and evaluating satellite-based constraints on NOx emissions estimates in air quality simulations (2022)

Abstract. Satellite observations of tropospheric NO2 columns can provide top-down observational constraints on emissions estimates of nitrogen oxides (NOx). Mass-balance-based methods are often applied for this purpose but do not isolate near-surface emissions from those aloft, such as lightning emissions. Here, we introduce an inverse modeling framework that couples satellite chemical data assimilation to a chemical transport model. In the framework, satellite-constrained emissions totals are inferred using model simulations with and without data assimilation in the iterative finite-difference mass-balance method. The approach improves the finite-difference mass-balance inversion by isolating the near-surface emissions increment. We apply the framework to separately estimate lightning and anthropogenic NOx emissions over the Northern Hemisphere for 2019. Using overlapping observations from the Ozone Monitoring Instrument (OMI) and the Tropospheric Monitoring Instrument (TROPOMI), we compare separate NOx emissions inferences from these satellite instruments, as well as the impacts of emissions changes on modeled NO2 and O3. OMI inferences of anthropogenic emissions consistently lead to larger emissions than TROPOMI inferences, attributed to a low bias in TROPOMI NO2 retrievals. Updated lightning NOx emissions from either satellite improve the chemical transport model's low tropospheric O3 bias. The combined lighting and anthropogenic emissions updates improve the model's ability to reproduce measured ozone by adjusting natural, long-range, and local pollution contributions. Thus, the framework informs and supports the design of domestic and international control strategies.

Research areas: Air Quality, Validation
Anthropogenic and volcanic point source SO2 emissions derived from TROPOMI on board Sentinel-5 Precursor: first results (2020)

Abstract. The paper introduces the first TROPOMI-based sulfur dioxide (SO2) emissions estimates for point sources. A total of about 500 continuously emitting point sources releasing about 10 kt yr1 to more than 2000 kt yr1 of SO2, previously identified from Ozone Monitoring Instrument (OMI) observations, were analyzed using TROPOMI (TROPOspheric Monitoring Instrument) measurements for 1 full year from April 2018 to March 2019. The annual emissions from these sources were estimated and compared to similar estimates from OMI and Ozone Mapping Profiling Suite (OMPS) measurements. Note that emissions from many of these 500 sources have declined significantly since 2005, making their quantification more challenging. We were able to identify 274 sources where annual emissions are significant and can be reliably estimated from TROPOMI. The standard deviations of TROPOMI vertical column density data, about 1 Dobson unit (DU, where 1 DU =2.691016 molecules cm2) over the tropics and 1.5 DU over high latitudes, are larger than those of OMI (0.61 DU) and OMPS (0.30.4 DU). Due to its very high spatial resolution, TROPOMI produces 1220 times more observations over a certain area than OMI and 96 times more than OMPS. Despite higher uncertainties of individual TROPOMI observations, TROPOMI data averaged over a large area have roughly 23 times lower uncertainties compared to OMI and OMPS data. Similarly, TROPOMI annual emissions can be estimated with uncertainties that are 1.52 times lower than the uncertainties of annual emissions estimates from OMI. While there are area biases in TROPOMI data over some regions that have to be removed from emission calculations, the absolute magnitude of these are modest, typically within 0.25 DU, which can be comparable with SO2 values over large sources.

Research areas: Air Quality
Global multi-year O<sub>3</sub>-CO correlation patterns from models and TES satellite observations (2011)

Abstract. The correlation between measured tropospheric ozone (O3) and carbon monoxide (CO) has been used extensively in tropospheric chemistry studies to explore the photochemical characteristics of different regions and to evaluate the ability of models to capture these characteristics. Here, we present the first study that uses multi-year, global, vertically resolved, simultaneous and collocated O3 and CO satellite (Tropospheric Emission Spectrometer) measurements, to determine this correlation in the middle/lower free troposphere for two different seasons, and to evaluate two chemistry-climate models. We find results that are fairly robust across different years, altitudes and timescales considered, which indicates that the correlation maps presented here could be used in future model evaluations. The highest positive correlations (around 0.8) are found in the northern Pacific during summer, which is a common feature in the observations and the G-PUCCINI model. We make quantitative comparisons between the models using a single-figure metric (C), which we define as the correlation coefficient between the modeled and the observed O3-CO correlations for different regions of the globe. On a global scale, the G-PUCCINI model shows a good performance in the summer (C=0.71) and a satisfactory performance in the winter (C=0.52). It captures midlatitude features very well, especially in the summer, whereas the performance in regions like South America or Central Africa is weaker. The UKCA model (C=0.46/0.15 for JulyAugust/DecemberJanuary on a global scale) performs better in certain regions, such as the tropics in winter, and it captures some of the broad characteristics of summer extratropical correlations, but it systematically underestimates the O3-CO correlations over much of the globe. It is noteworthy that the correlations look very different in the two models, even though the ozone distributions are similar. This demonstrates that this technique provides a powerful global constraint for understanding modeled tropospheric chemical processes. We investigated the sources of the correlations by performing a series of sensitivity experiments. In these, the sign of the correlation is, in most cases, insensitive to removing different individual emissions, but its magnitude changes downwind of emission regions when applying such perturbations. Interestingly, we find that the O3-CO correlation does not solely reflect the strength of O3 photochemical production, as often assumed by earlier studies, but is more complicated and may reflect a mixture of different processes such as transport.

Research areas: Validation, Air Quality
Data-Informed Models for the Coupled Dispersal of Microplastics and Related Pollutants Applied to the Mediterranean Sea (2023)

Abstract
            Microplastic pollution is a ubiquitous environmental threat, in particular to the oceans. In the marine environment, microplastics are not just passively transported by sea currents, but often get contaminated with organic pollutants during the journey. The uptake of chemicals onto microplastics can worsen the adverse effects of microplastics to marine organisms; however, investigation on this urgent phenomenon is hampered by the impossibility of monitoring and tracking such small plastic fragments during their motion at sea. This work aims at addressing the need for an effective modelling of the advectiondiffusion processes jointly involving microplastics and the pollutants they carry to further our understanding of their spatiotemporal patterns and ecological impacts, focusing on the Mediterranean Sea. Here we present the conceptual design, methodological settings, and modelling results of a novel, data-informed 2D LagrangianEulerian modelling framework that simultaneously describes (i) the Lagrangian dispersal of microplastic on the sea surface, (ii) the Eulerian advectiondiffusion of selected organic contaminants, and (iii) the gradient-driven chemical exchanges between microplastic particles and chemical pollutants in the marine environment in a simple, yet comprehensive way. Crucial to the realism of our model is exploiting the wide variety and abundance of data linked with drivers of Mediterranean marine pollution by microplastics and chemicals, ranging from national censuses to satellite data of surface water runoff and GPS ship tracking, other than the use of oceanographic reanalyses to inform microplastics motion at sea. The results of our method applied to a multi-year simulation contribute to a first basin-wide assessment of the role of microplastics as a vehicle of other pollutants of concern in the marine environment. The framework proposed here is intended as a flexible tool to help advance knowledge towards a comprehensive description of the multifaceted threat of marine plastic pollution and an informed support to targeted mitigation policies.

Research areas: Water Quality
Multi-scale Simulations of Atmospheric Pollutants Using a Non-hydrostatic Icosahedral Atmospheric Model (2018)

We have developed a seamless global-to-regional model to calculate atmospheric aerosol chemistry by coupling existing aerosol and chemical modules to a global cloud-system-resolving model (NICAM-Chem). The model can simulate air pollutants with various grid sizes ranging from global low resolution (~200 km) on yearly scales to regional high resolution (~10 km) on monthly scales and global high resolution (<10 km) on weekly scales. To date, we have confirmed that the NICAM-Chem simulated aerosols at low-to-high resolutions, and global-to-regional scales are generally comparable to validated observations. Furthermore, the very recent availability of cutting-edge computational capabilities provided by the K computer at RIKEN in Japan enabled us to perform seasonal air pollution simulations with a high global resolution model (14 km), which generally reproduced the observed aerosol distributions. In this paper, we introduce the following application studies using the NICAM-Chem model: future scenario experiments, downscaling using results obtained by a coupled atmosphere-ocean model, estimation of human health due to PM2.5, simulations of radioactive matter using a regional model, and aerosol assimilation by a localized ensemble transform Kalman filter.

Research areas: Air Quality