nasa-gesdisc/es-publications-researchareas huggingface dataset:
Development of an Indigenous Sensor for Sub-micron Aerosol Monitoring in India (2017)

Environmental pollutants might be present in different media as well as
they can easily migrate between air, water and soil. These contaminants can migrate
from one media to another. Many epidemiological studies have linked particulate
matter (PM) and especially the PM 2.5 (aerodynamic diameter d p < 2.5 m) mass to
adverse cardiovascular and respiratory health effects. These health effects include
premature mortality, asthma exacerbation, decreased lung function, and increased
risk of myocardial infarction among others. These tiny inhalable particles are
composed of various heterogeneously mixed chemical species including sulfate,
nitrate, ammonium ions, sea salt, organic and elemental carbon, metals, and bio-
logical material. Past studies have suggested that specific toxic components like
heavy metals, PAHs or biological components like endotoxins are responsible for
irregular heart and lung function in animal models. Accurate measurement of
contaminants in various media is the first step towards their effective control. This
chapter describes the lab development and field evaluation of an inertial impaction
based indigenous sensor for sub-micron aerosol monitoring developed at IIT
Kanpur. Submicron particles (PM 1 ) were collected during the winter season at
Kanpur, India. These samples were chemically characterized for various species
like As, Ca, Cd, Cr, Cu, Fe, K, Mg, Mn, Na, Ni, Pb, Se, Ti, V, Zn, F  , Cl  , NO 3  ,
SO 42 and NH 4+ . These quantitative details were used to apportion air pollutant
sources using Positive Matrix Factorization (PMF) coupled with conditional
probability function (CPF) to determine the likely direction of each source from
receptor site. This low cost instrument is now commercially available in the Indian
market.

Research areas: Public Health, Environmental Impacts
Evidences of volcanic unrest on high-temperature fumaroles by satellite thermal monitoring: The case of Santa Ana volcano, El Salvador (2017)

On October 1st, 2005, Santa Ana volcano (El Salvador) underwent a VEI 3 phreatomagmatic eruption after approximately one century of rest. Casualties and damages to some of the local infrastructures and surrounding plantations were followed by the evacuation of the nearby communities. The analysis of MODIS (Moderate Resolution Imaging Spectroradiometer) infrared data reveals that the main explosion was preceded by a one-year-long thermal unrest, associated to the development of a fumaroles field, located at the western rim of the summit crater lake. By combining space-based thermal flux and ground-based measurements (seismicity, sulfur emissions and lake temperatures), we suggest that the activity observed at Santa Ana between 2004 and 2005 was driven by the gradual intrusion of an undegassed magma body at a very shallow depth. Magma injection induced thermal anomalies associated with sustained degassing from the fumaroles field and promoted the interaction between the magmatic-hydrothermal system and the overlying water table. This process culminated into the VEI 3 phreatomagmatic eruption of October 2005 that strongly modified the shallow structure of the crater area. The subsequent three-years-long activity resulted from self-sealing of the fracture system and by the opening of a new fracture network directly connecting the deeper hydrothermal system with the crater lake. Our results show that satellite-based thermal data allow us to detect the expansion of the high-temperature fumarolic field. This may precede an explosive eruption and/or a lava dome extrusion. In particular, we show that thermal records can be analyzed with other geochemical (i.e. SO2 emissions) and geophysical (seismicity) data to track a shallow magmatic intrusion interacting with the surrounding hydrothermal system. This provides a remarkable support for volcano monitoring and eruption forecasting, particularly in remote areas where permanent ground data acquisition is hazardous, expensive and difficult.

Research areas: Volcanic Eruptions
On the association of aerosol optical depth and total ozone fluctuations with recent earthquakes in Greece (2017)

A number of recent studies suggest that atmospheric changes that precede an earthquake might offer the hope of providing early warning. This study attempts to examine seismo-atmospheric anomalies around the time and the location of some of the major earthquakes in Greece in the period 20012015. Daily values of aerosol optical depth (AOD) and total ozone column (TOZ) obtained from satellite observations are used, in the time window between 25 days before and 14 days after each of these events, in a 1  1 area centred on the epicentre of each earthquake. For some of these earthquake events, abnormal increases in time series of AOD and TOZ data were detected before and after the occurrence of the earthquake. Nevertheless, in other cases, no clear anomalies were observed around the earthquake date. In addition, examining the statistics of AOD and TOZ daily values, there were many cases of prominent abnormal variations, without, however, being associated with an earthquake event. Therefore, no clear association was found between AOD and TOZ fluctuations and recent earthquakes in Greece.

Research areas: Earthquakes
Pre-monsoon air quality over Lumbini, a world heritage site along the Himalayan foothills (2017)

Abstract. Lumbini, in southern Nepal, is a UNESCO world heritage site of universal value as the birthplace of Buddha. Poor air quality in Lumbini and surrounding regions is a great concern for public health as well as for preservation, protection and promotion of Buddhist heritage and culture. We present here results from measurements of ambient concentrations of key air pollutants (PM, BC, CO, O3) in Lumbini, first of its kind for Lumbini, conducted during an intensive measurement period of 3 months (AprilJune 2013) in the pre-monsoon season. The measurements were carried out as a part of the international air pollution measurement campaign; SusKat-ABC (Sustainable Atmosphere for the Kathmandu Valley  Atmospheric Brown Clouds). The main objective of this work is to understand and document the level of air pollution, diurnal characteristics and influence of open burning on air quality in Lumbini. The hourly average concentrations during the entire measurement campaign ranged as follows: BC was 0.330.0 g m3, PM1 was 3.6197.6 g m3, PM2. 5 was 6.1272.2 g m3, PM10 was 10.5604.0 g m3, O3 was 1.0118.1 ppbv and CO was 125.01430.0 ppbv. These levels are comparable to other very heavily polluted sites in South Asia. Higher fraction of coarse-mode PM was found as compared to other nearby sites in the Indo-Gangetic Plain region. The BC  CO ratio obtained in Lumbini indicated considerable contributions of emissions from both residential and transportation sectors. The 24 h average PM2. 5 and PM10 concentrations exceeded the WHO guideline very frequently (94 and 85 % of the sampled period, respectively), which implies significant health risks for the residents and visitors in the region. These air pollutants exhibited clear diurnal cycles with high values in the morning and evening. During the study period, the worst air pollution episodes were mainly due to agro-residue burning and regional forest fires combined with meteorological conditions conducive of pollution transport to Lumbini. Fossil fuel combustion also contributed significantly, accounting for more than half of the ambient BC concentration according to aerosol spectral light absorption coefficients obtained in Lumbini. WRF-STEM, a regional chemical transport model, was used to simulate the meteorology and the concentrations of pollutants to understand the pollutant transport pathways. The model estimated values were  1. 5 to 5 times lower than the observed concentrations for CO and PM10, respectively. Model-simulated regionally tagged CO tracers showed that the majority of CO came from the upwind region of Ganges Valley. Model performance needs significant improvement in simulating aerosols in the region. Given the high air pollution level, there is a clear and urgent need for setting up a network of long-term air quality monitoring stations in the greater Lumbini region.

Research areas: Air Quality, Energy Production/Use, Environmental Impacts
The winter pack-ice zone provides a sheltered but food-poor habitat for larval Antarctic krill (2017)

A dominant Antarctic ecological paradigm suggests that winter sea ice is generally the main feeding ground for krill larvae. Observations from our winter cruise to the southwest Atlantic sector of the Southern Ocean contradict this view and present the first evidence that the pack-ice zone is a food-poor habitat for larval development. In contrast, the more open marginal ice zone provides a more favourable food environment for high larval krill growth rates. We found that complex under-ice habitats are, however, vital for larval krill when water column productivity is limited by light, by providing structures that offer protection from predators and to collect organic material released from the ice. The larvae feed on this sparse ice-associated food during the day. After sunset, they migrate into the water below the ice (upper 20 m) and drift away from the ice areas where they have previously fed. Model analyses indicate that this behaviour increases both food uptake in a patchy food environment and the likelihood of overwinter transport to areas where feeding conditions are more favourable in spring.

Research areas: Ecosystems
Thunderstorm-/lightning-induced ionospheric perturbation: An observation from equatorial and low-latitude stations around Hong Kong: Lightning-Induced Perturbations (2017)

Total electron content (TEC) computed from the network of Global Positioning System over Hong Kong area known as Hong Kong SatRefnetwork has been used to study perturbation in the ionosphere from thunder storm activity. Data for geomagnetic quiet day (Kp < 4, on 1 April 2014) have been analyzed. The lightning activity was measured from Total Lightning sensor LS8000 over/around the Hong Kong region. Deviation in vertical TEC (DTEC) and the rate of change of TEC index (ROTI) have been derived and compared for lightning day of 1 April 2014 and nonlightning day of 7 April 2014. An analysis showed reduction in TEC during evening hour (up to 1245 UT), whereas an enhancement during nighttime hour on the lightning day is observed. The variations in DTEC during nonlightning day are found to be insignificant in comparison to that during the lightning day. The ionospheric perturbation in TEC has been noticed up to a distance around ~500 km and more from the lightning center. ROTI is found to vary from 3 to 60 total electron content unit (TECU)/min (1 TECU = 1016 el m2) on the day of thunderstorm activity, whereas ROTI is insignificant on nonlightning days. Signature of density bubbles in slant TEC data and periodicities (10100 min) in DTEC data are observed. For the same pseudorandom numbers (1, 10, 13, 23, and 28) strong amplitude scintillations are also observed at a close by station. Amplitude scintillations are proposed to be caused by plasma bubbles. The results are tentatively explained by thunderstorminduced electric fields and gravity waves.

Research areas: Atmospheric/Ocean Indicators
Long-term variations of aerosol optical depth and aerosol radiative forcing over Iran based on satellite and AERONET data (2018)

In this study, three different sensors of satel-
lites including the Moderate Resolution Imaging
Spectroradiometer (MODIS), Multi-angle Imaging
SpectroRadiometer (MISR), and Total Ozone Mapping
Spectrometer (TOMS) were used to study spatial and
temporal variations of aerosols over ten populated cities
in Iran. Also, the Hybrid Single-Particle Lagrangian
Integrated Trajectory (HYSPLIT) model was used for
analyzing the origins of air masses and their trajectory in
the area. An increasing trend in aerosol concentration
was observed in the most studied cities in Iran during
19792016. The cities in the western part of Iran had the
highest annual mean of aerosol concentration. The
highest aerosol optic al depth (AOD) value
(0.76  0.51) was recorded in May 2012 over Ahvaz,
and the lowest value (0.035  0.27) was recorded in
December 2013 over Tabriz. After Ahvaz, the highest
AOD value was found over Tehran (annual mean
0.11  0.20). The results show that AOD increases with
increasing industrial activities, but the increased fre-
quency of aerosols due to land degradation and desert-
ification is more powerful in Iran. The trajectory analy-
sis by the HYSPLIT model showed that the air masses come from Egypt, Syria, and Lebanon and passed over
the Iraq and then reached to Iran during summer. Aerosol radiative forcing (ARF) has been analyzed for Zanjan (Aerosol Robotic Network site) during 20102013.
The ARF at surface and top of the atmosphere was
found to be ranging from  79 to  10W m 2 (average  33.45 W m 2 ) and from  25 to 6 W m 2 (average  12.80 W m 2 ), respectively.

Research areas: Atmospheric/Ocean Indicators
Mapping the yields of lignocellulosic bioenergy crops from observations at the global scale (2020)

Abstract. Most scenarios from integrated assessment models (IAMs) that project greenhouse gas emissions include the use of bioenergy as a means to reduce CO2 emissions or even to achieve negative emissions (together with CCS  carbon capture and storage). The potential amount of CO2 that can be removed from the atmosphere depends, among others, on the yields of bioenergy crops, the land available to grow these crops and the efficiency with which CO2 produced by combustion is captured. While bioenergy crop yields can be simulated by models, estimates of the spatial distribution of bioenergy yields under current technology based on a large number of observations are currently lacking. In this study, a random-forest (RF) algorithm is used to upscale a bioenergy yield dataset of 3963 observations covering Miscanthus, switchgrass, eucalypt, poplar and willow using climatic and soil conditions as explanatory variables. The results are global yield maps of five important lignocellulosic bioenergy crops under current technology, climate and atmospheric CO2 conditions at a 0.50.5 spatial resolution. We also provide a combined best bioenergy crop yield map by selecting one of the five crop types with the highest yield in each of the grid cells, eucalypt and Miscanthus in most cases. The global median yield of the best crop is 16.3 t DM ha1 yr1 (DM  dry matter). High yields mainly occur in the Amazon region and southeastern Asia. We further compare our empirically derived maps with yield maps used in three IAMs and find that the median yields in our maps are > 50 % higher than those in the IAM maps. Our estimates of gridded bioenergy crop yields can be used to provide bioenergy yields for IAMs, to evaluate land surface models or to identify the most suitable lands for future bioenergy crop plantations. The 0.50.5 global maps for yields of different bioenergy crops and the best crop and for the best crop composition generated from this study can be download from https://doi.org/10.5281/zenodo.3274254 (Li, 2019).

Research areas: Energy Production/Use, Greenhouse Gases, Agriculture
Enset-based agricultural systems in Ethiopia: A systematic review of (2020)

Societal Impact StatementEnset is a staple food for over 20 million people via its starchrich corm and pseudostem, yet it is virtually unknown outside a narrow zone of cultivation in southern Ethiopia. Due to acculturation and urbanization coupled with climate change, emerging pests and the introduction of new crops, the extensive indigenous knowledge associated with this crop is in danger of being lost, imperilling the future food security and prosperity of millions of Ethiopians. Here, we synthesize the current state of enset ethnobotanical research, identifying key gaps and challenges, and provide a framework for further enset research to safeguard this important, but neglected, tropical crop. Summary Enset (Ensete ventricosum (Welw.) Cheesman) is the major starch staple of the Ethiopian Highlands, where its unique attributes enhance the food security of approximately 20 million people and have earned it the title The Tree Against Hunger. Yet ensetbased agriculture is virtually unknown outside of its narrow zone of cultivation, despite growing wild across much of East and Southern Africa. Here, we review historical production data to show that the area of land under enset production in Ethiopia has reportedly increased 46% in two decades, whilst yield increased 12fold over the same period, making enset the second most produced crop species in Ethiopiathough we critically evaluate potential issues with these data. Furthermore, we address a major challenge in the development and wider cultivation of enset, by reviewing and synthesizing the complex and fragmented agronomic and ethnobotanic knowledge associated with this species; including farming systems, processing methods, products, medicinal uses and cultural importance. Finally, we provide a framework to improve the quality, consistency and comparability of data collected across culturally diverse ensetbased agricultural systems to enhanced sustainable use of this neglected starch staple. In conclusion, we discuss the challenges and opportunities for enset cultivation beyond its restricted distribution, and the regional food security potential it could afford smallholders elsewhere in Southern and East Africa.

Research areas: Agriculture
Agricultural windfalls and the seasonality of political violence in Africa (2022)

AbstractWhen the prices of cereal grains rise, social unrest and conflict become likely. In rural areas, the predation motives of perpetrators can explain the positive relationship between prices and conflict. Predation happens at places and in periods where and when spoils to be appropriated are available. In predominantly agrarian societies, such opportune times align with the harvest season. Does the seasonality of agricultural income lead to the seasonality of conflict? We address this question by analyzing over 55 thousand incidents involving violence against civilians staged by paramilitary groups across Africa during the 19972020 period. We investigate the crop year pattern of violence in response to agricultural income shocks via changes in international cereal prices. We find that a yearonyear one standard deviation annual growth of the price of the major cereal grain results in a harvesttime spike in violence by militias in areas where this cereal grain is grown. This translates to a nearly 10% increase in violence during the early postharvest season. We observe no such change in violence by state forces or rebel groupsthe other two notable actors. By further investigating the mechanisms, we show that the violence by militias is amplified after plausibly rich harvest seasons when the value of spoils to be appropriated is higher. By focusing on harvestrelated seasonality of conflict, as well as actors more likely to be involved in violence against civilians, we contribute to the growing literature on the economic causes of conflict in predominantly agrarian societies.

Research areas: Agriculture
How much land is available for sustainable palm oil? (2021)

Current consumption of palm oil accounts for one third of the growing world demand for vegetable oil. Amidst the burgeoning industry, huge ecological costs have been accrued within just three decades due to the rapid oil palm expansion in many parts of the world. Many oil palm plantations are linked to deforestation, biodiversity losses, land use change emissions, among other ecological problems. Total replacement of palm oil could result in even greater adverse environmental consequences as alternative crops will require more land. To satisfy the growing demands in a sustainable manner, any new plantations must be located in environmentally-benign lands. This study identifies and quantifies the potentially available lands in Malaysia and Indonesia through a novel fuzzy GIS-based land suitability analysis. Three maps were generated: biophysically suitable land, based on optimal conditions for oil palm cultivation, excluding peatlands and existing protected areas; environmentally suitable land, further excluding forest cover; and potentially available land, further excluding existing plantations and other land uses. About 4.5 million hectares of available land for new plantations have been identified that could provide 1.3 million tonnes per year of sustainable palm oil. However, most of these areas are fragmented and scattered throughout the entire archipelago, which could pose economic and socio-political hurdles to developers of sustainable palm oil. With affordable and fairer certification schemes, sustainable oil palm plantations can be achieved by smallholders on these potentially available lands. Yield improvement and biodiversity restoration of existing plantations should be the focus through revitalised sustainable agriculture and strategic forest conservation policies, respectively. The maps provide valuable policy insights into the possibility of future sustainable oil palm plantations and a starting point for on-the-ground assessment and further verification.

Research areas: Agriculture
Path dependencies in US agriculture: Regional factors of diversification (2022)

Concerns of declining agrobiodiversity and widening socioeconomic inequities in United States (US) agriculture highlight the critical need for systemic change. Despite surmounting evidence of the field and landscape scale benefits of diversifying agricultural systems, path dependencies of US agriculture present barriers to such diversification pathways. This study aims to elucidate path dependencies of agricultural landscapes that (dis)incentivize crop diversification at the regional scale through two main research questions: 1) what are the biophysical and socioecological factors most predictive of agricultural diversity across the US; and 2) how do these factors vary regionally? Using a novel panel dataset constructed from several open-source databases, we use random forest (RF) permutation variable importance measures to identify and compare the factors most predictive of county-level crop diversity across nine US regions. Our results show that climate, land use norms, and farm inputs are consistently the most important categories for predicting agricultural diversity across regions; however, variability exists in the relative regional importance of variables within these categories. Thus, factors most strongly predictive of agricultural diversity across US landscapes operate distinctly at a regional level, emphasizing the need to consider multiple scales of influence. These distinct regional relationships contribute to path dependencies that present resistance to enhancing agricultural diversity. By more appropriately addressing the regional factors of US agricultural landscapes the constrain agricultural diversification, with an eye towards future cropscapes, we can shift current path dependencies toward a more resilient and adaptive US agricultural future.

Research areas: Agriculture