nasa-gesdisc/es-publications-researchareas huggingface dataset:
Dust storms and their horizontal dust loading in the Sistan region, Iran (2012)

The Sistan region in southeast Iran is considered as one of the most active dust source regions in South west Asia. The strong Levar winds in summer favor the uplift of large quantities of dust from the Hamoun basin, which is located in the northern part of Sistan. After a dry period at the end of the 1999s, and due to land-use change and desiccation of the Hamoun lakes, the frequency and severity of dust storms have been significantly increased. Within this framework, this study analyses the aerosol characteristics, dust loading and air quality over the Sistan region. The dust loading was measured using dust traps up to four and eight meters height (with a one meter distance between the traps) at two locations near the Hamoun basin during the period August 2009 to July 2010. The results show large quantities of transported dust that strongly dependent on the duration of the dust events, and secondarily, on the wind speed and distance from the source region. The grain size distribution of the dusts reveals that the coarser calibers are found at the station nearer to Hamoun, while the large differences in the grain-size distribution found between the two stations indicate significant spatio-temporal variation in dust characteristics. Furthermore, to assess the air quality, Particulate Matter (PM10) concentrations were measured over Zabol city during September 2010 to July 2011, and the Air Quality Index (AQI) was obtained. Daily PM10 levels during intense dust storms rise up to 2000gm3, even reaching to 3094gm3, while the monthly mean PM10 variation shows extreme values (>500gm3) for the period June to October. Analysis of the AQI shows that 61% of the days are associated with a high health risk, while 30.1% are even identified as hazardous.

Research areas: Air Quality, Land Surface/Agriculture Indicators
The Effect of Lockdown Period during the COVID-19 Pandemic on Air Quality in Sydney Region, Australia (2021)

In early 2020 from April to early June, the metropolitan area of Sydney as well as the rest of New South Wales (NSW, Australia) experienced a period of lockdown to prevent the spread of COVID-19 virus in the community. The effect of reducing anthropogenic activities including transportation had an impact on the urban environment in terms of air quality which is shown to have improved for a number of pollutants, such as Nitrogen Dioxides (NO2) and Carbon Monoxide (CO), based on monitoring data on the ground and from a satellite. In addition to primary pollutants CO and NOx emitted from mobile sources, PM2.5 (primary and secondary) and secondary Ozone (O3) during the lockdown period will also be analyzed using both statistical methods on air quality data and the modelling method with emission and meteorological data input to an air quality model. By estimating the decrease in traffic volume in the Sydney region, the corresponding decrease in emission input to the Weather Research and ForecastingCommunity Multiscale Air Quality Modelling System (WRF-CMAQ) air quality model is then used to estimate the effect of lockdown on the air quality especially CO, NO2, O3, and PM2.5 in the Greater Metropolitan Region (GMR) of Sydney. The results from both statistical and modelling methods show that NO2, CO, and PM2.5 levels decreased during the lockdown, but O3 instead increased. However, the change in the concentration levels are small considering the large reduction of ~30% in traffic volume.

Research areas: Air Quality, Environmental Impacts
Modeling relationship between land surface temperature anomaly and environmental factors using GEE and Giovanni (2022)

Land surface temperature (LST) and vegetation cover changes are two indicators of landscapes in a region. The relationship between LST anomalies, elevation, vegetation, and urban growth is significant to conservation. This study addresses this issue using night-time satellite imagery, kernel methods (points aggregation), and the trend analysis for a long-term period (20012017) in Iran. Variables for two seasons (summer and winter) in urban and natural land uses were derived using the Google Earth Engine (GEE) and NASA's Giovanni. Point data derived from raster maps were quantified using statistical kernel and trend analysis. As result, it was observed that LST rise in various elevations, seasons, and land uses. The LST was analyzed through kernels (point aggregation in scatter graphs), which shifted to the right. The LST anomaly in the daytime had the highest maximum value (>4 C) and lowest minimum value (

Research areas: Atmospheric/Ocean Indicators, Habitat Conversion/Fragmentation
Characterizing a landmark biomass-burning event and its implication for aging processes during long-range transport (2020)

Springtime biomass burning (BB) in peninsular Southeast Asia (PSEA) has a large impact on the downwind air quality as has been frequently observed at the Lulin Atmospheric Background Station (LABS). Numerous PSEA BB long-range transport events have been observed at LABS in the past decade, of which the biggest event (based on the carbon monoxide (CO) mixing ratio and particulate matter (PM) loading) occurred on March 18, 2009. In this study, for the first time, in-situ observations from LABS, MERRA-2 reanalysis data, and satellite data were combined to elucidate this remarkable event. This event lasted over 29 h and seriously impacted the air quality at LABS. Average concentrations (S.D.) of CO, ozone (O3), and PM10 were 586.2  164.5 ppb, 105.2  23.4 ppb, and 90.4  24.4 g m3, respectively, which were enhanced ranging from 98% to 280% over the March 2009 average. Furthermore, significant increases in toxic air pollutants (e.g., gaseous elemental mercury (GEM) and dibenzo-p-dioxin/furan) concentrations were also observed, implying a severe impact from BB smoke on ecosystems and human health. The transport pathway and BB smoke layer height were investigated with backward trajectories, daily satellite aerosol products, and lidar observations. The mean SSA440 value of 0.87 suggested that the plume contained highly adsorbing aerosols, and the high char-EC/soot-EC ratio (low-temperature elemental carbon/high-temperature elemental carbon) of 29.4 suggested predominance of BB aerosols. In addition, plume aging indicators (e.g., GEM/CO, O3/CO, char-EC/soot-EC) suggest the BB plume was only weakly aged (i.e. low air mass intermixing, low chemical transformation, low cloud interaction) and in a nearly pristine state during the whole of the long-range transport. This event study can serve as a valuable benchmark when identifying unaged BB plumes that have been transported from PSEA to LABS (>2000 km) and will be useful for characterizing PSEA BB and its impact on greater Asia environment.

Research areas: Environmental Impacts, Air Quality
Satellite validation strategy assessments based on the AROMAT campaigns (2020)

Abstract. The Airborne ROmanian Measurements of Aerosols and Trace gases (AROMAT) campaigns took place in Romania in September 2014 and August 2015. They focused on two sites: the Bucharest urban area and large power plants in the Jiu Valley. The main objectives of the campaigns were to test recently developed airborne observation systems dedicated to air quality studies and to verify their applicability for the validation of space-borne atmospheric missions such as the TROPOspheric Monitoring Instrument (TROPOMI)/Sentinel-5 Precursor (S5P). We present the AROMAT campaigns from the perspective of findings related to the validation of tropospheric NO2, SO2, and H2CO. We also quantify the emissions of NOx and SO2 at both measurement sites. We show that tropospheric NO2 vertical column density (VCD) measurements using airborne mapping instruments are well suited for satellite validation in principle. The signal-to-noise ratio of the airborne NO2 measurements is an order of magnitude higher than its space-borne counterpart when the airborne measurements are averaged at the TROPOMI pixel scale. However, we show that the temporal variation of the NO2 VCDs during a flight might be a significant source of comparison error. Considering the random error of the TROPOMI tropospheric NO2 VCD (), the dynamic range of the NO2 VCDs field extends from detection limit up to 37  (2.61016 molec. cm2) and 29  (21016 molec. cm2) for Bucharest and the Jiu Valley, respectively. For both areas, we simulate validation exercises applied to the TROPOMI tropospheric NO2 product. These simulations indicate that a comparison error budget closely matching the TROPOMI optimal target accuracy of 25 % can be obtained by adding NO2 and aerosol profile information to the airborne mapping observations, which constrains the investigated accuracy to within 28 %. In addition to NO2, our study also addresses the measurements of SO2 emissions from power plants in the Jiu Valley and an urban hotspot of H2CO in the centre of Bucharest. For these two species, we conclude that the best validation strategy would consist of deploying ground-based measurement systems at well-identified locations.

Research areas: Air Quality
On the relationship between Arctic ice clouds and polluted air masses over the North Slope of Alaska in April 2008 (2014)

Abstract. Recently, two types of ice clouds (TICs) properties have been characterized using the Indirect and Semi-Direct Aerosol Campaign (ISDAC) airborne measurements (Alaska, April 2008). TIC-2B were characterized by fewer (< 10 L1) and larger (> 110 m) ice crystals, and a larger ice supersaturation (> 15%) compared to TIC-1/2A. It has been hypothesized that emissions of SO2 may reduce the ice nucleating properties of ice nuclei (IN) through acidification, resulting in a smaller concentration of larger ice crystals and leading to precipitation (e.g., cloud regime TIC-2B). Here, the origin of air masses forming the ISDAC TIC-1/2A (1 April 2008) and TIC-2B (15 April 2008) is investigated using trajectory tools and satellite data. Results show that the synoptic conditions favor air masses transport from three potential SO2 emission sources into Alaska: eastern China and Siberia where anthropogenic and biomass burning emissions, respectively, are produced, and the volcanic region of the Kamchatka/Aleutians. Weather conditions allow the accumulation of pollutants from eastern China and Siberia over Alaska, most probably with the contribution of acidic volcanic aerosol during the TIC-2B period. Observation Monitoring Instrument (OMI) satellite observations reveal that SO2 concentrations in air masses forming the TIC-2B were larger than in air masses forming the TIC-1/2A. Airborne measurements show high acidity near the TIC-2B flight where humidity was low. These results support the hypothesis that acidic coating on IN could be at the origin of the formation of TIC-2B.

Research areas: Atmospheric/Ocean Indicators, Air Quality, Environmental Impacts, Volcanic Eruptions
Urbanization and environmental change during the economic transition on the Mongolian Plateau: Hohhot and Ulaanbaatar (2016)

Driven by drastic socioeconomic changes in China and Mongolia, urbanization has become one of the most significant driving forces in the transformation of the Mongolian Plateau in the past 30 years. Using Hohhot and Ulaanbaatar as case studies, we developed a holistic approach to examine the socioeconomic and natural driving forces for urbanization and to investigate the impact on the urban environment. We used a multidisciplinary approach and relied on a variety of data sources to assess the changes of the landscape and environment of the two cities. We detected a rapid urbanization in Hohhot and Ulaanbaatar, both in terms of urban population growth and urban land expansion, from 1990 to 2010, with a much faster speed in 20002010. The local geo-physical conditions have constrained the spatial direction of expansion. Ulaanbaatar lagged behind Hohhot for about a decade when measured by indicators of urban population and urban land. Both cities have a degraded urban environment and a growing air pollution epidemic. While Hohhot had worse air pollution than Ulaanbaatar in the early 2000s, the gap between the two cities became smaller after 2010. The research presented here highlights the following as key determinants for urbanization and environmental change: (1) the co-evolution of urbanization, economic development, and environmental change; (2) the urbanization of transitional economies driven by the change of the economic structure, i.e., the development by both manufacturing and tertiary sectors and the change in the primary sector; and (3) the recent institutional changes and increased integration with the global economy.

Research areas: Habitat Conversion/Fragmentation, Air Quality
Aerosol optical depth of the main aerosol species over italian cities based on the NASA/MERRA-2 model reanalysis (2019)

The Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2) provides data at 0.5  0.625 resolution covering a period from 1 January 1980 to the present. Natural and anthropogenic aerosols are simulated in MERRA-2, considering the Goddard chemistry, aerosol, radiation, and transport model. This model simulates the sources, sinks, and chemistry of mixed aerosol tracers: dust, sea salt, hydrophobic and hydrophilic black carbon and organic carbon, and sulfate. MERRA-2 aerosol reanalysis is a pioneering tool for investigating air quality issues, noteworthy for its global coverage and its distinction of aerosol speciation expressed in the form of aerosol optical depth (AOD). The aim of this work was to use the MERRA-2 reanalysis to study urban air pollution at a national scale by analyzing the AOD. AOD trends were evaluated for a 30-year period (19872017) over five Italian cities (Milan, Rome, Cagliari, Taranto, and Palermo) in order to investigate the impacts of urbanization, industrialization, air quality regulations, and regional transport on urban aerosol load. AOD evolution predicted by the MERRA-2 model in the period 20022017 showed a generalized decreasing trend over the selected cities. The anthropogenic signature on total AOD was between 50% and 80%, with the largest contribution deriving from sulfate.

Research areas: Air Quality, Habitat Conversion/Fragmentation
Design and installation of a Prototype Geohazard Monitoring System near Machu Picchu, Peru (2010)

Abstract. The town of Machu Picchu, Peru, serves the >700 000 tourists visiting Machu Picchu annually. It has grown threefold in population in the past two decades. Due to the limited low-lying ground, construction is occurring on the unstable valley slopes. Slopes range from <10 on the valley floor to >70 in the surrounding mountains. The town has grown on a delta formed at the confluence of the Alcamayo, Aguas Calientes and Vilcanota Rivers. Geohazards in and around the town of particular concern are 1) large rocks falling onto the town and/or the rail line, 2) flash flooding by any one of its three rivers, and 3) mudflows and landslides. A prototype early warning system that could monitor weather, river flow and slope stability was installed along the Aguas Calientes River in 2009. This has a distributed modular construction allowing components to be installed, maintained, salvaged, and repaired by local technicians. A diverse set of candidate power, communication and sensor technologies was evaluated. Most of the technologies had never been deployed in similar terrain, altitude or weather. The successful deployment of the prototype proved that it is technically feasible to develop early warning capacity in the town.

Research areas: Land Surface/Agriculture Indicators, Floods, Habitat Conversion/Fragmentation
Evaluation of the visible and shortwave infrared drought index in China (2013)

In this article, the performance of the Visible and Shortwave infrared Drought Index (VSDI), a drought index recently developed and validated in Oklahoma, United States, is further explored and validated in China. The in-situ measured soil moisture from 585 weather stations across China are used as ground-truth data, and five commonly used drought indices are compared with VSDI for surface drought monitoring. The results reveal that VSDI is robust and reliable in the estimation of surface dryness-it has the highest correlation with soil moisture among the six indices when computed using both the original and cloud removed data. All six indices show the highest correlation with soil moisture at the 10 cm layer and the averaged 1050 cm layer. The spatiotemporal patterns of surface moisture indicated by the MODIS-based VSDI are further compared with the precipitation-based drought maps and the Global Land Data Assimilation System (GLDAS) simulated surface soil moisture maps over five provinces located in the Middle-Lower Yangtze Plain of China. The results indicate that despite the difference between the spatial and temporal resolutions of the three products, the VSDI maps still show good agreement with the other two drought products through the rapidly alternating drought and flood events in 2011 in this region. Therefore, VSDI can be used as an effective surface wetness indicator at both the provincial and the national scales in China.

Research areas: Droughts, Land Surface/Agriculture Indicators
The impact of large-scale forest fires on atmospheric aerosol characteristics (2014)

Aerosol optical thickness and aerosol index variations, caused by large-scale forest fires in central Yakutia in 2002 were studied using remote-sensing data (Earth Observing System (EOS) Terra, Earth Probe). Total emissions of CO2, CO, CH4, etc., were calculated using a modelling approach and Moderate Resolution Imaging Spectroradiometer (MODIS)/Terra burned area data. A comparison of the total emissions from forest fires in central Yakutia with global fire and volcanic emissions are made. Furthermore, long-range transport events of aerosol particles during maximum activity of forest fires are examined. It was shown that forest fires have a significant impact on the lower atmosphere; in particular, aerosol plumes are noticeable at a distance of around 3000 km from the study area.

Research areas: Wildfires, Air Quality
Spatio-temporal runoff estimation using TRMM satellite data and NRSC-CN method of a watershed of Upper Subarnarekha River basin, India (2016)

Geographical Information System (GIS) and Remote Sensing (RS) have acquired great significance in the recent years for estimation of runoff from watersheds and agricultural fields. This study has made use of the well-established tool, Natural Resources Conservation Service Curve Number (NRCS-CN) method to observe runoff over the study area in conjunction with GIS and RS. Pixel-wise runoff depth of the catchment was estimated by incorporating Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Digital Elevation Model (ASTER GDEM) data, Tropical Rainfall Measuring Mission (TRMM) multi-satellite precipitation analysis data for the years 20012011, and Landsat Enhanced Thematic Mapper (ETM)+ Land Use/Land Cover (LULC) information within the simple rainfall-runoff model. NRSC-CN was modified for Indian condition and the Hydrologic Engineering Centers Geospatial Hydrologic Modeling System (HEC-Geo-HMS) extension was utilized for evaluating the Curve Number (CN). Rainfall-Runoff model was executed to compute pixel-wise runoff, utilizing the model builder interface of ARC GIS 10. It was observed that there had been an increase in the average runoff depth ranging from 2.25 to 2.48 mm in different micro-watersheds of the study area. There was also an increase in total runoff depth from 61.24 to 68.47 m following an increase in mean CN value from 55 in the year 2001 to 57 in the year 2011. This indicated a lesser increase in lower runoff level range and a greater increase in higher runoff level range. In terms of runoff within the watershed, a higher percentage of its micro-watersheds showed lower runoff range compared to the micro-watersheds with higher runoff range. A direct correlation was observed between reduction in agriculture with increased runoff, increase in open land, and decrease in vegetation.

Research areas: Land Surface/Agriculture Indicators
Exploring large-scale blackcarbon air pollution over Northern Eurasia in summer 2016 using MERRA-2 reanalysis data (2020)

The abnormally high temperature and the deficit of precipitation in Siberia in summer 2016 contributed to the development of massive forest fires, which resulted in pyrogenic emission in the atmosphere of various biomass burning products. This paper presents the analysis results of the spatial and temporal variations of black carbon (BC) in the atmosphere over Northern Eurasia during the 2016 Siberian wildfires using the MERRA-2 reanalysis data. The spatiotemporal evolution of BC anomalies is presented, with estimates of the increase in BC mass during wildfire period. The peculiarities of large-scale atmospheric circulation responsible for BC transport from Siberia to Central Europe are discussed. The estimates of spatial scale, effective height and speed of the long-range anomalous (from east to west) transfer of air masses in the atmosphere over Northern Eurasia in July 2016 are obtained. Changes in the optical and microphysical characteristics of biomass-burning aerosol during its long-range transport are also discussed. A comparison of daily variations in surface BC concentrations at the polar observatory Tiksi with those in BC column mass density from MERRA-2 revealed a high correlation between local and integral characteristics of BC during arriving air masses from Siberian wildfires.

Research areas: Wildfires, Air Quality
Modeling of tropospheric NO2 column over different climatic zones and land use/land cover types in South Asia (2018)

We have applied regression analyses for the modeling of tropospheric NO2 (tropo-NO2) as the function of anthropogenic nitrogen oxides (NOx) emissions, aerosol optical depth (AOD), and some important meteorological parameters such as temperature (Temp), precipitation (Preci), relative humidity (RH), wind speed (WS), cloud fraction (CLF) and outgoing long-wave radiation (OLR) over different climatic zones and land use/land cover types in South Asia during October 2004December 2015. Simple linear regression shows that, over South Asia, tropo-NO2 variability is significantly linked to AOD, WS, NOx, Preci and CLF. Also zone-5, consisting of tropical monsoon areas of eastern India and Myanmar, is the only study zone over which all the selected parameters show their influence on tropo-NO2 at statistical significance levels. In stepwise multiple linear modeling, tropo-NO2 column over landmass of South Asia, is significantly predicted by the combination of RH (standardized regression coefficient,  =  49), AOD ( = 0.42) and NOx ( = 0.25). The leading predictors of tropo-NO2 columns over zones 15 are OLR, AOD, Temp, OLR, and RH respectively. Overall, as revealed by the higher correlation coefficients (r), the multiple regressions provide reasonable models for tropo-NO2 over South Asia (r = 0.82), zone-4 (r = 0.90) and zone-5 (r = 0.93). The lowest r (of 0.66) has been found for hot semi-arid region in northwestern Indus-Ganges Basin (zone-2). The highest value of  for urban area AOD (of 0.42) is observed for megacity Lahore, located in warm semi-arid zone-2 with large scale crop-residue burning, indicating strong influence of aerosols on the modeled tropo-NO2 column. A statistical significant correlation (r = 0.22) at the 0.05 level is found between tropo-NO2 and AOD over Lahore. Also NOx emissions appear as the highest contributor ( = 0.59) for modeled tropo-NO2 column over megacity Dhaka.

Research areas: Air Quality, Habitat Conversion/Fragmentation