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At least 793 records · Page 44

Comparison of chemical lateral boundary conditions for air quality predictions over the contiguous United States during pollutant intrusion events

The National Air Quality Forecast Capability (NAQFC) operated in U.S.’s National Oceanic and Atmospheric Administration (NOAA) provides the operational forecast guidance for ozone and fine particulate matters with aerodynamic diameters less than 2.5μm (PM2.5) over the contiguous 48 U.S. states (CONUS) using the Community Multi-scale Air Quality (CMAQ) model. The existing NAQFC uses climatological chemical lateral boundary conditions ( CLBCs), which cannot capture pollutant intrusion events originating outside of the model domain. In this study, we developed a model framework to use dynamic CLBCs from the Goddard Earth Observing System Model, version 5 (GEOS) to drive NAQFC. A mapping of the GEOS chemical species to the CMAQ’s Carbon Bond 5 (CB05)-Aero6 species was developed. The utilization of the GEOS dynamic CLBCs in NAQFC showed the best overall performance in simulating the surface observations during the Saharan dust intrusion and Canadian wildfire events in summer 2015.The simulated PM2.5 was improved from 0.18 to 0.37 and the mean bias was reduced from -6.74 μg/m3 to -2.96 μg/m3 over CONUS. Although the effect of CLBCs on the PM2.5 correlation was mainly near the inflow boundary, its impact on the background concentrations reached further inside the domain. The CLBCs could affect background ozone concentrations through the inflows of ozone itself and its precursors, such as CO. It was further found that the aerosol optical thickness (AOT) from satellite retrievals correlated well with the column CO and elemental carbon from GEOS. The satellite-derived AOT CLBCs generally improved the model performance for the wildfire intrusion events during a summer 2018 case study, and demonstrated how satellite observations of atmospheric composition could be used as an alternative method to capture the air quality effects of intrusions when the global model CLBCs, such as GEOS CLBCs, are not available.

Community Multi-scale Air Quality (CMAQ) model↗

Pre- and Post-Production Processes Increasingly Dominate Greenhouse Gas Emissions From Agri-Food Systems

We present results from the FAOSTAT emissions shares database, covering emissions from agri-food systems and their shares to total anthropogenic emissions for 196 countries and 40 territories for the period 1990–2019. We find that in 2019, global agri-food system emissions were 16.5 (95 %; CI range: 11–22) billion metric tonnes (GtCO2 eq. yr(exp -1)), corresponding to 31%(range: 19 %–43 %) of total anthropogenic emissions. Of the agri-food system total, global emissions within the farm gate – from crop and livestock production processes including on-farm energy use – were 7.2 GtCO2 eq. yr(exp -1); emissions from land use change, due to deforestation and peatland degradation, were 3.5 GtCO2 eq. yr(exp -1); and emissions from pre- and post-production processes – manufacturing of fertilizers, food processing, packaging, transport, retail, household consumption and food waste disposal – were 5.8 GtCO2 eq. yr(exp -1). Over the study period 1990–2019, agri-food system emissions increased in total by 17 %, largely driven by a doubling of emissions from pre- and post-production processes. Conversely, the FAOSTAT data show that since 1990 land use emissions decreased by 25 %, while emissions within the farm gate increased 9 %. In 2019, in terms of individual greenhouse gases (GHGs), pre- and postproduction processes emitted the most CO2 (3.9 GtCO2 yr(exp -1)), preceding land use change (3.3 GtCO2 yr(exp -1)) and farm gate (1.2 GtCO2 yr(exp -1)) emissions. Conversely, farm gate activities were by far the major emitter of methane (140 MtCH4 yr(exp -1)) and of nitrous oxide (7.8 MtN2Oyr(exp -1)). Pre- and post-production processes were also significant emitters of methane (49 MtCH4 yr(exp -1)), mostly generated from the decay of solid food waste in landfills and open dumps. One key trend over the 30-year period since 1990 highlighted by our analysis is the increasingly important role of food-related emissions generated outside of agricultural land, in pre- and post-production processes along the agri-food system, at global, regional and national scales. In fact, our data show that by 2019, pre- and post-production processes had overtaken farm gate processes to become the largest GHG component of agri-food system emissions in Annex I parties (2.2 GtCO2 eq. yr(exp -1)). They also more than doubled in non-Annex I parties (to 3.5 GtCO2 eq. yr(exp -1)), becoming larger than emissions from land use change. By 2019 food supply chains had become the largest agri-food system component in China (1100 MtCO2 eq. yr(exp -1)), the USA (700 MtCO2 eq. yr(exp -1)) and the EU-27 (600 MtCO2 eq. yr(exp -1)). This has important repercussions for food-relevant national mitigation strategies, considering that until recently these have focused mainly on reductions of non-CO2 gases within the farm gate and on CO2 mitigation from land use change. The information used in this work is available as open data with DOI https://doi.org/10.5281/zenodo.5615082 (Tubiello et al., 2021d). It is also available to users via the FAOSTAT database (https://www.fao.org/faostat/en/#data/EM; FAO, 2021a), with annual updates.

FAOSTAT agri-food systems emissions database↗

Performance Evaluation of a Vapor-compression-cycle Based Heat Pump System for a Lunar Habitat under the Impact of Dust Deposits on the Coupled Radiators

Space exploration gains new momentum. A near goal is set by NASA to return humans to the Moon andestablish a sustainable presence on the lunar surface for more repeatable and affordable expeditions.The lunar dust is one of the dangerous environment hazard causing serious problems for explorationactivities. In this paper, in order to study the impact of lunar dust on the performance of a thermalmanagement system for a lunar habitat, a dynamical model of an active thermal control system that iscomprised of a vapor-compression cycle heat pump and a radiator loop is developed. A heat pump to liftthe heat rejection temperature is required due to high lunar daytime surface temperature. Parametricstudies on radiator size, percentage of dust coverage on the radiator, and lunar habitat location arecarried out. The results show that lunar deposits can significantly increase the power consumption ofthe thermal management system. A dust covered radiator panel results in net heat input to the heattransfer fluid during the period of strong solar irradiance, causing deteriorated performance of theradiator loop. The lunar dust contamination problem raises the requirement of redundancy design of asystem for fault tolerance. A synergetic design of a thermal management system, a power generationsystem and robotic maintenance system is proposed to achieve maximal mass cut for a whole lunarhabitat system.

Chunjian Pan↗

The Dynamic Atmospheric and Aeolian Environment of Jezero Crater, Mars

Despite the importance of sand and dust to Mars geomorphology, weather, and exploration, the processes that move sand and that raise dust to maintain Mars’s ubiquitous dust haze have not been well quantified in situ, with missions lacking either thenecessary sensors and/or a sufficiently active aeolian environment. Perseverance rover’s novel environmental sensors and Jezero crater’s dusty environment remedy this. In Perseverance’s first 216 sols, four convective vortices raised dust locally, while on average four passed the rover daily, over 25% of which were significantly dusty (‘dust devils’). More rarely, dust lifting by non-vortex wind gusts was produced by daytime convection cells advected over the crater by strong upslope winds, which also control aeolian surface features. One such event covered ten times more area than the largest dust devil, suggesting dust devils and wind gusts could raise equal dust.

Claire E Newman↗

Constraints on Wildfire Smoke Source Strength, Injection Height, and Particle Evolution

Aerosol sources are represented in climate and air quality models with an injection height and a source strength. We have applied a combination of Multi-angle Imaging SpectroRadiometer (MISR) and MODerate resolution Imaging Spectroradiometer (MODIS) observations to help constrain these two key model variables for wildfire smoke plumes. Injection height is obtained from MISR stereo imagery, which makes it possible to map plume elevation and estimate the associated motion vectors at plume altitude near-source, where contrast features in the plume can be identified in the multi-angle views. A current limitation of injection-height mapping is the relatively narrow MISR swath width (~380 km) and 10:30 AM equator crossing time on the day side of Earth. However, upcoming missions, as well as advanced imagers on geostationary platforms, promise to greatly expand the spatial and temporal range over which this technique can be applied. We estimate source strength by matching forward-simulated plume aerosol optical depth (AOD) from models with AOD snapshots retrieved from MODIS observations. This technique works best for large, isolated plumes common in boreal forest, and tends to fail where plume AOD is low and/or background AOD, distinct from the specific source of interest, is high. These two approaches for constraining aerosol modeling with satellite observations have been the subject of ongoing AeroCom/AeroSat studies by our group. A third effort applies the combination of MISR plume heights, wind vectors, and particle microphysical property constraints to infer smoke-plume particle evolution processes and timescales, including the emission and subsequent evolution of black and brown smoke. In this presentation, we will provide an update on the status of these efforts.

wildfire↗

Update on AeroCom Biomass Burning Emission Injection Height experiment (BBEIH)

In BBEIH, we introduced the biomass burning injection heights based on MISR stereo-derived plume-height retrievals (Val Martin et al., 2010; 2018) in four participating CTMs. Specifically, we proposed 4 simulations for the year 2008: 1) BASE: using the biomass burning emissions from Global Fire Emissions Database version 4 with small fires (GFED4s) and the model default fire emission injection height; 2) BBIH: Same as BASE, but using the injection height derived from the seasonally and regionally varying MISR-retrieved plume heights; 3) NOBB: no fire emission; 4) Same as BASE, but using Fire Energetics and Emissions Research version 1.0 (FEER 1.0). We will address the following scientific questions: 1) To what extent are the model simulations sensitive to the assumed biomass burning injection height? 2) In which regions/seasons/surface-types are the aforementioned sensitivities most important? We will update the multi-model inter-comparison with a focus on the vertical aerosol distribution in near-source characteristics and downwind plume evolution." In order to test the sensitivity of model results to smoke injection height, we proposed the biomass burning emission injection height experiment (BBEIH) in the AeroCom 2019 workshop. The description of implementation methods and input data for BBEIH can be found in https://wiki.met.no/aerocom/phase3-experiments#biomass_burning_emission_injection_height_experiment_bbeih.

Xiaohua Pan↗

Multi-source Estimates of Land / Ocean Moisture Transport Variability over the Satellite Era

It is widely appreciated that atmospheric transport of water from the world’s oceans is a process key to planetary energy balance as well as Earth's habitability. What is not yet clear is the extent of variability in moisture transports, the relative importance of interdecadal variability versus climate change signals, and importantly, our ability to quantify these changes. This work assesses variations in moisture transport variability during the satellite era (~1980 to present) by comparing several different estimates. (i) The most direct estimate is the vertically integrated flux convergence of moisture from reanalyses which use observed wind and moisture information. (ii) One alternative estimate comes from P-ET over land taken from global hydrologic models constrained with precipitation and near-surface meteorology. Here we use an ensemble of six models. An adjunct to this method is to employ satellite derive ET (e.g., GLEAM or DOLCE). (iii) Complementary to this is E-P over the global oceans derived from satellite estimates of P such as TRMM, GPM and GPCP and SeaFlux V3 or J-OFURO3 estimates of E, all relying heavily upon microwave measurements. Transport between land and oceans must essentially balance at monthly scales, i.e., vanish globally. (iv) a fourth perspective comes from estimate of terrestrial RO + storage rate, delta S. G-RUN Ensemble which uses observed streamflow and P measurements to calibrate a statistical model provides the former while GRACE, GRACE-FO provide total water storage anomalies used to calculate storage rate changes. GRACE REC uses GRACE data to train a precipitation-driven statistical model to extend storage estimates before the GRACE era. (All of these alternatives to reanalysis estimates also consider the small atmospheric column water vapor contribution.) We examine the transport changes from these three different methodologies, their relative accuracies and discuss the origin of their differences. Regional trends in moisture flux divergence and their role in multi-decadal trends are considered. Interannual variability arising in connection with ENSO variability is a dominant signal, driven largely by P changes. Trends since 1980 include reductions in moisture delivery to the western U.S., eastern Brazil, and central Africa with recovery of moisture convergence to the Sahel and parts of eastern North America.

Franklin Robertson↗

Study the Vertical Structure and Transportation of the Extreme African Dust Storms using MERRA-2 Data

The Modern-Era Retrospective Analysis for Research and Application, Version 2 (MERRA-2) provides the first long-term global reanalysis to assimilate space-based observations of aerosols and represents their interactions with other physical processes in the climate system. In this study, we have examined the variations of atmospheric aerosols for the last 20 years since 2002 using the sub-daily MERRA-2 data and found seven extreme African dust storms that were transported westward across the Atlantic Ocean from the Sahara, crossing 70o-80oW. In particular, the well-known ‘Godzilla’ dust storm occurred in June 2020, and its dust cloud, with the highest-on-record aerosol optical depths, was transported toward the Americas. This storm greatly degraded air quality over large areas of the Caribbean Basin and the United States. The air quality index reached unhealthy levels for sensitive groups in more than ten U.S. states. In our study, the vertical structure and transport characteristics of the dust layers during this extreme dust event are investigated. The geopotential height and temperature were found anomalously low (around 600 hPa) over the Atlantic Ocean off northwest Africa before the June 2020 dust storm. This anomalous circulation pattern was persistent for more than 12 days starting from around May 30, breaking the regular easterly waves that transport dust from the Sahara Desert to the west. To verify the data quality, daily MERRA-2 PM2.5 data were calculated and compared with PM2.5 observations from the U.S. Environmental Protection Agency (EPA) at several selected ground stations in Florida. We provide this case study to illustrate how to effectively use various MERRA-2 data services at Goddard Earth Sciences Data and Information Services Center (GES DISC) where MERRA-2 data are archived, hoping to help data users in exploring their own topics of interest using data services at GES DISC.

data management, reanalysis↗

Characterizing Wildfires in Western US.: A Cloud-based Case Study for Interdisciplinary Research using NASA Resources

This presentation will demonstrate a case study of interdisciplinary research done in the Amazon Web Services (AWS) cloud platform, in addition to in the local machine. We conduct data analysis next to data by leveraging various cloud-based data in NASA Earthdata Cloud, which are distributed by different missions/NASA Distributed Active Archive Centers (DAACs), and cloud computing resources at NASA. For instance, we directly access multiple datasets stored in the AWS Simple Storage Service (S3) buckets using a Python Jupyter notebook through a JupyterHub interface hosted in AWS (without having to download data), and conduct data analysis next to data in the cloud. We will also show how to share the research results following Open Source policy. This case study characterizes the change in wildfire events in the western United States during the past 20 years. In particular, we focus on the wildfires in California in 2021, one of the most severe wildfire years occurring in the most recent 20 years in California. We will analyze the possible causes of wildfires, such as drought conditions and climate variability, and examine the impacts of wildfires on air quality and atmospheric composition, and on land cover. We will examine the data distributed by the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC), including aerosols and meteorological data from the NASA Modern-Era Retrospective analysis for Research and Applications version 2 (MERRA-2), precipitation from the Global Precipitation Measurement (GPM) and Global Precipitation Climate Project (GPCP), and aerosol index from Ozone Monitoring Instrument (OMI). We also utilize the data distributed by the Physical Oceanography (PO) DAAC, such as Sea Surface Temperature (SST) data from the Group for High Resolution Sea Surface Temperature (GHRSST), and the data distributed by Land Processes (LP) DAAC, such as Normalized Difference Vegetation Index (NDVI).

Xiaohua Pan↗