Engineering topics

Martin, Randall

Publications and source records attributed to Martin, Randall.

4 records

DOE OSTI2024

Characterizing the Atmospheric Mn Cycle and Its Impact on Terrestrial Biogeochemistry

Abstract The role of manganese (Mn) in ecosystem carbon (C) biogeochemical cycling is gaining increasing attention. While soil Mn is mainly derived from bedrock, atmospheric deposition could be a major source of Mn to surface soils, with implications for soil C cycling. However, quantification of the atmospheric Mn cycle, which comprises emissions from natural (desert dust, sea salts, volcanoes, primary biogenic particles, and wildfires) and anthropogenic sources (e.g., industrialization and land‐use change due to agriculture), transport, and deposition, remains uncertain. Here, we use compiled emission data sets for each identified source to model and quantify the atmospheric Mn cycle by combining an atmospheric model and in situ atmospheric concentration measurements. We estimated global emissions of atmospheric Mn in aerosols (<10 μm in aerodynamic diameter) to be 1,400 Gg Mn year −1 . Approximately 31% of the emissions come from anthropogenic sources. Deposition of the anthropogenic Mn shortened Mn “pseudo” turnover times in 1‐m‐thick surface soils (ranging from 1,000 to over 10,000,000 years) by 1–2 orders of magnitude in industrialized regions. Such anthropogenic Mn inputs boosted the Mn‐to‐N ratio of the atmospheric deposition in non‐desert dominated regions (between 5 × 10 −5 and 0.02) across industrialized areas, but that was still lower than soil Mn‐to‐N ratio by 1–3 orders of magnitude. Correlation analysis revealed a negative relationship between Mn deposition and topsoil C density across temperate and (sub)tropical forests, consisting with atmospheric Mn deposition enhancing carbon respiration as seen in in situ biogeochemical studies.

Environmental Sciences & Ecology↗

NASA NTRS2022

An Advanced Open-Source Platform for Air Quality Analysis, Visualization, and Prediction

Ambient air pollution is the largest environmental health risk factor, leading to several million premature deaths globally per year. The challenge of combating poor air quality is exacerbated by growing urban populations, changing emissions, and a warming climate. While there have been many advances monitoring and modeling of atmospheric composition, reflected in the dramatic increase in archived Earth Observations, there is no single measurement or method that alone can provide an accurate depiction of the entire atmosphere. The rapidly growing collections of observational and modeling data require us to be smarter about what data to include, and how such data is used. In recent years, NASA has invested significantly in advancing the concepts for Analytics Collaborative Framework (ACF) [5] and New Observing Strategies (NOS) [4] to tackle our software infrastructure need for harmonized data management and dynamic acquisition of diverse measurements for on-demand, interactive, multivariate analysis, and access [3]. It is not enough to have a big data, standalone analytics solution; it is critical that we start integrating data from remote sensing, modeling, and in-situ networks in a harmonized manner that enables timely and data-driven decision-making for air quality management. This work presents the design and development of an Air Quality Analytics Collaborative Framework (AQ ACF), as part of NASA’s Advanced Information Systems Technology (AIST) effort, to establish a data, machine-learning, and numerically driven platform for air quality analysis, visualization, and prediction.

Liu, Qian↗

NASA NTRS2007

Chemical Data Assimilation Estimates of Continental US Ozone and Nitrogen Budgets during INTEX-A

Global ozone analyses, based on assimilation of stratospheric profile and ozone column measurements, and NOy predictions from the Real-time Air Quality Modeling System (RAQMS) are used to estimate the ozone and NOy budget over the Continental US during the July-August 2004 Intercontinental Chemical Transport Experiment-North America (INTEX-A). Comparison with aircraft, satellite, surface, and ozonesonde measurements collected during the INTEX-A show that RAQMS captures the main features of the global and Continental US distribution of tropospheric ozone, carbon monoxide, and NOy with reasonable fidelity. Assimilation of stratospheric profile and column ozone measurements is shown to have a positive impact on the RAQMS upper tropospheric/lower stratosphere ozone analyses, particularly during the period when SAGE III limb scattering measurements were available. Eulerian ozone and NOy budgets during INTEX-A show that the majority of the Continental US export occurs in the upper troposphere/lower stratosphere poleward of the tropopause break, a consequence of convergence of tropospheric and stratospheric air in this region. Continental US photochemically produced ozone was found to be a minor component of the total ozone export, which was dominated by stratospheric ozone during INTEX-A. The unusually low photochemical ozone export is attributed to anomalously cold surface temperatures during the latter half of the INTEX-A mission, which resulted in net ozone loss during the first 2 weeks of August. Eulerian NOy budgets are shown to be very consistent with previously published estimates. The NOy export efficiency was estimated to be 24 percent, with NOx+PAN accounting for 54 percent of the total NOy export during INTEX-A.

Pierce, Robert B.↗

NASA NTRS2000

Dust in the Sky: Atmospheric Composition. Modeling of Aerosol Optical Thickness

Aerosol is any small particle of matter that rests suspended in the atmosphere. Natural sources, such as deserts, create some aerosols; consumption of fossil fuels and industrial activity create other aerosols. All the microscopic aerosol particles add up to a large amount of material floating in the atmosphere. You can see the particles in the haze that floats over polluted cities. Beyond this visible effect, aerosols can actually lower temperatures. They do this by blocking, or scattering, a portion of the sun's energy from reaching the surface. Because of this influence, scientists study the physical properties of atmospheric aerosols. Reliable numerical models for atmospheric aerosols play an important role in research.

Chin, Mian↗