nasa-gesdisc/es-publications-researchareas huggingface dataset:
Top-down estimates of biomass burning emissions of black carbon in the Western United States (2014)

Abstract. We estimate biomass burning and anthropogenic emissions of black carbon (BC) in the western US for MayOctober 2006 by inverting surface BC concentrations from the Interagency Monitoring of PROtected Visual Environment (IMPROVE) network using a global chemical transport model. We first use active fire counts from the Moderate Resolution Imaging Spectroradiometer (MODIS) to improve the spatiotemporal distributions of the biomass burning BC emissions from the Global Fire Emissions Database (GFEDv2). The adjustment primarily shifts emissions from late to middle and early summer (a 33% decrease in SeptemberOctober and a 56% increase in JuneAugust) and leads to appreciable increases in modeled surface BC concentrations in early and middle summer, especially at the 12 and 23 km altitude ranges. We then conduct analytical inversions at both 2  2.5 and 0.5  0.667 (nested over North America) horizontal resolutions. The a posteriori biomass burning BC emissions for JulySeptember are 31.7 Gg at 2  2.5 (an increase by a factor of 4.7) and 19.2 Gg at 0.5  0.667 (an increase by a factor of 2.8). The inversion results are rather sensitive to model resolution. The a posteriori biomass burning emissions at the two model resolutions differ by a factor of ~6 in California and the Southwest and by a factor of 2 in the Pacific Northwest. The corresponding a posteriori anthropogenic BC emissions are 9.1 Gg at 2  2.5 (a decrease of 48%) and 11.2 Gg at 0.5  0.667 (a decrease of 36%). Simulated surface BC concentrations with the a posteriori emissions capture the observed major fire episodes at most sites and the substantial enhancements at the 12 and 23 km altitude ranges. The a posteriori emissions also lead to large bias reductions (by ~30% on average at both model resolutions) in modeled surface BC concentrations and significantly better agreement with observations (increases in Taylor skill scores of 95% at 2  2.5 and 42 % at 0.5  0.667).

Research areas: Environmental Impacts
Emergence of monopoly–Copper exchange networks during the Late Bronze Age in the western and central Balkans (2022)

In this paper we present the first results of an interdisciplinary research project focused on Late Bronze Age metallurgy in the western and central Balkans. The comprehensive chemical and lead isotope analysis, and a strict consideration of archaeological criteria, has provided a deeper insight into supra regional metal exchange networks between the 14th and 9th century BC in this part of Europe. Particularly interesting and surprising are results regarding the provenance of raw materials for copper production, which have a chemical composition and lead isotope ratios that closely correspond to ore deposits in the southern Alps (North Italy). Based on the examination of 57 objects of different functions, chronology and distribution, it becomes apparent that copper from the southern Alps was almost an omnipresent raw material in the territories of the western and central Balkans with only a few finds from North Macedonia to indicate alternative sources. The analyses demonstrate that the reuse of fahlore-based copper is attested for the first time in the regions under study. The remarkable fact that other archaeological parameters do not indicate such an intensive connection between the Balkan area and Northern Italy raises a number of questions. The sustained and long-lasting networks of raw material procurement stand in contrast to the expected cultural interaction between metal producing and metal consuming prehistoric societies. The results of this work also highlight the currently underestimated role of the southern Alps as one of the main copper producing areas in Bronze Age Europe, and demonstrate for the first time that the region of western and central Balkans was one of the major recipients.

Research areas: Habitat Conversion/Fragmentation
Vertical structure of biomass burning aerosol transported over the southeast Atlantic Ocean (2022)

Abstract. Biomass burning in southwestern Africa produces smoke plumes that
are transported over the Atlantic Ocean and overlie vast regions of
stratocumulus clouds. This aerosol layer contributes to direct and indirect
radiative forcing of the atmosphere in this region particularly during the
months of August, September, and October. There was a multi-year
international campaign to study this aerosol and its interactions with
clouds. Here, we report on the evolution of aerosol distributions and
properties as measured by the airborne high spectral resolution lidar
(HSRL-2) during the ORACLES (Observations of Aerosols above Clouds and their
intEractionS) campaign in September 2016. The NASA Langley HSRL-2 instrument
was flown on the NASA ER-2 aircraft for several days in September 2016. Data
were aggregated at two pairs of 2  2 grid
boxes to examine the evolution of the vertical profile of aerosol properties
during transport over the ocean. Results showed that the structure of the
profile of aerosol extinction and microphysical properties is maintained
over a 1 to 2 d timescale. In the 35 km altitude range, 95 % of
the aerosol extinction was contributed by particles in the 0.050.50 m radius size range with the aerosol in this size range having an average
effective radius of 0.16 m. This indicates that there is essentially
no scavenging or dry deposition at these altitudes. Moreover, there is very
little day-to-day variation in these properties, such that time sampling as
happens in such campaigns may be representative of longer periods such as
monthly means. Below 3 km, there is considerable mixing with larger aerosol,
most likely continental source near land. Furthermore, these measurements
indicated that there was often a distinct gap between the bottom of the
aerosol layer and cloud tops at the selected locations as evidenced by a
layer of several hundred meters that contained relatively low aerosol
extinction values above the clouds.

Research areas: Environmental Impacts
Open-source methods for estimating health risks of fine particulate matter from coal-fired power plants: A demonstration from Karachi, Pakistan (2021)

Environmental impact assessments (EIAs) effectiveness and accessibility by the public is determined by local environmental enforcement and regulation. Massive energy infrastructure projects like China's Belt and Road initiative (BRI) could accentuate social and economic costs, as regulation is deferred to host countries with varying levels of domestic enforcement. To fill major gaps in the public evaluation of EIA practices and results, our objective here is to present an open-source approach for evaluating localized air pollution health impacts for BRI-financed coal-fired power plants. This analysis focuses on one specific problem, additional attributable mortality from stroke, ischemic heart disease, and chronic obstructive pulmonary disease for adults ages 2584 from fine particulate matter (PM2.5), known to be major risk factor for premature deaths globally. As a concrete example, we examine the case of the Port Qasim power plant located near Karachi, Sindh Province, Pakistan. We present results for two main scenarios: a base case, assuming fully operational pollution control technologies, in particular electrostatic precipitators (ESP); and an alternative case without ESPs. All material and methods for replicating this analysis for the case study and for other projects are available in our institutional open repository. Our approach can be applied immediately to virtually any source location in the world, due to the public and global availability of input data.
Synopsis
We present an open-source approach for evaluating localized health impacts due to fine particulate matter emitted from coal-fired power plants.

Research areas: Energy Production/Use
Integration of Sentinel optical and radar data for mapping smallholder coffee production systems in Vietnam (2021)

Perennial commodity crops, such as coffee, often play a large role globally in agricultural markets and supply chains and locally in livelihoods, poverty reduction, and biodiversity. Yet, the production of spatial information on these crops are often overlooked in favor of annual food crops. Remote sensing detection of coffee faces a particular set of challenges due to persistent cloud cover in the tropical coffee belt, hilly topography in coffee growing regions, diversity of coffee growing systems, and spectral similarity to other tree crops and agricultural land. Looking at the major coffee growing region in Dak Lak, Vietnam, we integrate multi-temporal 10 m optical Sentinel-2 and Sentinel-1 SAR data in order to map three coffee production systems: i) open-canopy sun coffee, ii) intercropped and other shaded coffee and iii) newly planted or young coffee. Leveraging Google Earth Engine (GEE), we compute five sets of features in order to best enhance separability between coffee and other land cover and within coffee production systems. The features include Sentinel-2 dry and wet season composites, Sentinel-1 texture features, Sentinel-1 spatiotemporal metrics, and topographic features. Using a random forest classification algorithm, we produce a 9-class land cover map including our three coffee production classes and a binary coffee/non-coffee map. The binary map has an overall accuracy of 89% and the three coffee production systems have user accuracies of 65, 56, 71% for sun coffee, intercropped coffee and newly planted coffee, respectively. This is a first effort at large-scale distinction of within-crop production styles and has implications across many applications. The binary coffee map can be used as a high-resolution crop mask, whereas the detailed land cover map can inform monitoring of deforestation dynamics, biodiversity, sustainability certification and implementation of climate adaptation strategies. This work offers a scalable approach to integrating optical and radar Sentinel data for production of spatially explicit agricultural information and contributes particularly to tree crop and agroforestry mapping, which often is overlooked in between agricultural and forestry sciences.

Research areas: Agriculture
The downstream air pollution impacts of the transition from coal to natural gas in the United States (2020)

The recent shift in the United States from coal to natural gas as a primary feedstock for the production of electric power has reduced the intensity of sectoral carbon dioxide emissions, butdue to gaps in monitoringits downstream pollution-related effects have been less well understood. Here, I analyse old units that have been taken offline and new units that have come online to empirically link technology switches to observed aerosol and ozone changes and subsequent impacts on human health, crop yields and regional climate. Between 2005 and 2016 in the continental United States, decommissioning of a coal-fired unit was associated with reduced nearby pollution concentrations and subsequent reductions in mortality and increases in crop yield. In total during this period, the shutdown of coal-fired units saved an estimated 22,563 (5%95% confidence intervals (CI), 1,69743,429) lives and 329 million (169490 million) bushels of corn in their immediate vicinities; these crop estimates increase when pollution transport-related spillovers are included. Changes in primary and secondary aerosol burdens also altered regional atmospheric reflectivity, raising the average top of atmosphere instantaneous radiative forcing by 0.50 W m2. Although there are considerable benefits of decommissioning older coal-fired units, the newer natural gas and coal-fired units that have supplanted them are not entirely benign.

Research areas: Energy Production/Use
Preparing for the unprecedented—Towards quantitative oil risk assessment in the Arctic marine areas (2017)

The probability of major oil accidents in Arctic seas is increasing alongside with increasing maritime traffic. Hence, there is a growing need to understand the risks posed by oil spills to these unique and sensitive areas. So far these risks have mainly been acknowledged in terms of qualitative descriptions. We introduce a probabilistic framework, based on a general food web approach, to analyze ecological impacts of oil spills. We argue that the food web approach based on key functional groups is more appropriate for providing holistic view of the involved risks than assessments based on single species. We discuss the issues characteristic to the Arctic that need a special attention in risk assessment, and provide examples how to proceed towards quantitative risk estimates. The conceptual model presented in the paper helps to identify the most important risk factors and can be used as a template for more detailed risk assessments.

Research areas: Environmental Impacts
Spatial and Temporal Variations of Predicting Fuel Load in Temperate (2022)

The prediction of fuel load areas and species associated with these events reduces the response time to fight forest fires. The objective of this study was to estimate the annual fuel load from 20092013, predict the annual fuel load in the rest of the ecosystem, identify species that contribute most to this load and compare the percentage of area by risk category in the temperate forests of Tamaulipas. Fuel load was estimated with inventory data using three models. Fuel load was predicted with elevation, total annual precipitation, mean annual temperature, and enhanced vegetation index from satellite scenes using partial least squares regression. The highest concentration of fuel load was associated with the oak, oak-pine, pine forest and mountain mesophyll forest ecosystems. The contribution of genera to fuel load was different. Quercus contributed the most variation among clusters, and the contribution among Quercus species was similar. The results highlight the importance of focusing fuel management programs on this type of ecosystem, emphasizing actions in particular Quercus, and the results can also serve as a basis for future research, such as carbon sequestration and forest management programs.

Research areas: Wildfires
Stranded coal power assets in China: a case study of Jilin Province (2019)

This article conducts the first provincial case study on the effect of environment-related risks on coal-fired power plants in Jilin, China, which creates stranded assets. Using power capacity expansion model and project evaluation model, the article first quantifies the rational coal power capacity during 20162020. Then, we calculate the value of stranded assets. The estimated scale of excess coal power capacity by 2020 ranges from 8,190 MW to 18,480 MW. The total value of stranded assets will decline over time under the different scenarios. Finally, policy implications for policymakers on power market reforms are proposed.

Research areas: Energy Production/Use
Sustainable alternatives to carbon intensive paddy field burning in India: A framework for cleaner production in agriculture, energy, and construction industries (2019)

Field burning of rice straw as a method of disposal by farmers is a major concern as the smoke and harmful emissions from it causes dangerous levels of pollution. Seven out of ten cities with the poorest air quality in the world are in India, and paddy field burning has been cited as one of the main reasons. Hazardous emissions from paddy field burning is combined with greenhouse gas emissions from coal fired power plants and cement manufacturing units, causing severe respiratory illnesses and other fatal health issues. The recent literature indicates an increased interest in rice straw valorisation, possibly in response to the increasing concerns over paddy field burning. However, a systematic study that compiles and compares various rice straw valorisation routes is lacking in the existing literature. This paper provides a comprehensive review of literature on various alternative uses of rice straw in energy and construction industries. Effective use of rice straw as a biomass fuel in energy sector not only reduces the field burning, but also decreases the dependency on non-renewable fossil fuels. Moreover, the proposed utilisation of secondary by-products from rice straw-based energy production in the construction industry can help to attain the goals of resource cascading. The availability of rice straw in major rice producing states of India and the feasibility of establishing rice straw-based power plants are also examined in this study. The potential reduction of harmful emissions from such resource recycling has been determined as per the guidelines issued by the intergovernmental panel on climate change. From the review of literature and the findings of the present study, a sustainable framework has been developed with well-defined cleaner production pathways to create a seamless material flow chain between the agricultural, energy, and construction sectors.

Research areas: Environmental Impacts
Correlation between the Production of Electricity by Offshore Wind Farms and the Demand for Electricity in Polish Conditions (2022)

Energy transition forcing a change in the structure of the electricity generation system is a particularly difficult task in countries such as Poland, where the dominant source of energy is fossil fuels. Due to the nature of renewable sources (stochastic and seasonally variable), it is necessary to study their impact on the power system. Much research was conducted on this subject. They consider modelling power systems in terms of dealing with an increasing amount of renewable energy sources, stabilization of electricity generation or environmental aspects. This article examines one of the key sources of future power systemsoffshore wind turbines (OWT). The influence of offshore wind sources on the power system in the fields of stability of generation, methods of regulatory strategies, and economics were examined. One of the aspects that are less considered is the correlation of energy production in OWT with energy demand and with generation in other renewable energy sources, especially in the region of the southern Baltic Sea and the distribution of energy demand in countries such as Poland. The key aspect of the research is to fill this gap. The obtained results indicate that the average monthly power generation in OWT is strongly positively correlated with the demand, and the hourly average is positively correlated moderately. Correlation between generation in OWT and photovoltaic sources is very high negative, and between onshore and offshore wind turbines is highly positive. The study indicates that the OWT has a significant potential for the development and replacement of conventional sources, due to the very high capacity and a positive correlation with demand. Moreover, future offshore wind farms can cooperate with photovoltaic sources as these sources complement each other. On the other hand, a significant saturation of the system with offshore and onshore wind sources may pose a threat to the power system due to their positive correlation.

Research areas: Energy Production/Use
Forest aboveground biomass mapping and estimation across multiple spatial scales using model-based inference (2016)

Remotely sensed data have been widely used in recent years for mapping and estimating biomass. However, the characterization of the uncertainty of mapped or estimated biomass in previous studies was either based on ad-hoc approaches (e.g., using model fitting statistics such root mean square errors derived from purposive samples) or mostly limited to the analysis of mean biomass for the whole study area. This study proposed a novel uncertainty analysis method that can characterize biomass uncertainty across multiple spatial scales and multiple spatial resolutions. The uncertainty analysis method built on model-based inference and can propagate errors from trees to field plots, individual pixels, and small areas or large regions that consist of multiple pixels (up to all pixels within a study area). We developed and tested this method over northern Minnesota forest areas of approximately 69,508km2 via a unique combination of several datasets for biomass mapping and estimation: wall-to-wall airborne lidar data, national forest inventory (NFI) plots, and destructive measurements of tree aboveground biomass (AGB). We found that the pixel-level AGB prediction error is dominated by lidar-based AGB model residual errors when the spatial resolution is near 380m or finer and by model parameter estimate errors when the spatial resolution is coarser. We also found that the relative error of AGB predicted from lidar can be reduced to approximately 11% (or mean 5.1Mg/ha; max 43.6Mg/ha) at one-hectare scale (or at 100m spatial resolution) over our study area. Because our uncertainty analysis method uses model-based inference and does not require probability samples of field plots, our methodology has potential applications worldwide, especially over tropics and developing countries where NFI systems are not well-established.

Research areas: Land Surface/Agriculture Indicators
Mapping Threats of Spring Frost Damage to Tea Plants Using Satellite-Based Minimum Temperature Estimation in China (2021)

Spring frost damage (SFD), defined as the disaster during the period of newly formed tea buds in spring caused by lower temperature and frost damage, is a particular challenge for tea plants (Camellia sinensis), whose capacity to adapt to extreme weather and climate impacts is limited. In this paper, the region of the Middle and Lower Reaches of the Yangtze River (MLRYR) in China was selected as the major tea plantation study area, and the study period was focused on the concentrated occurrence of SFD, i.e., from March to April. By employing the standard lapse rate of air temperature with elevation, a minimum temperature (Tmin) estimation model that had been previously established was used based on reconstructed MYD11A1 nighttime LST values for 3  3 pixel windows and digital elevation model data. Combined with satellite-based Tmin estimates and ground-based Tmin observations, the spatiotemporal characteristics of SFD for tea plants were systematically analyzed from 2003 to 2020 in the MLRYR. The SFD risks at three scales (temporal, spatial, and terrain) were then evaluated for tea plants over the MLRYR. The results show that both SFD days at the annual scale and SFD areas at the daily scale exhibited a decreasing trend at a rate of 2.7 days/decade and 2.45  104 ha/day, respectively (significant rates at the 0.05 and 0.01 levels, respectively). The period with the highest SFD risk appeared mainly in the first twenty days of March. However, more attention should be given to the mid-to-late April time period due to the occurrence of late SFD from time to time. Spatially, areas with relatively higher SFD days and SFD risks were predominantly concentrated in the higher altitude areas of northwestern parts of MLRYR for both multi-year averages and individual years. Fortunately, in regions with a higher risk of SFD, the distribution of tea plants was relatively scattered and the area was small. These findings will provide helpful guidance for all kinds of people, including government agencies, agricultural insurance agencies, and tea farmers, in order that reasonable and effective strategies to reduce losses caused by spring frost damage to tea plants may be recommended and implemented.

Research areas: Agriculture