Tracing and Quantifying Contributions of Proximal, Regional, and Global Sources to Primary Particulate Matter in an Urban Atmosphere Using Radiogenic Isotopes, Platinum Group Metals, and other Trace and Major Elements
Bibliographic record
Abstract
This research focuses on rare earths, platinum group metals, and Sr, Nd, and Hf isotopes along with a wide spectrum of other trace and major elements to accurately trace and quantify contributions of various source categories to primary ambient airborne particulate matter (PM) in an urban atmosphere. The overarching goal of this research is to establish strong tracers for individual distal and proximal sources and quantify local, regional, and global sources influencing urban aerosols. The work principally focuses on natural mineral dust (from a remote desert and locally resuspended soil), anthropogenic mineral dust from construction activities, anthropogenic emissions from motor vehicles, both natural and anthropogenic biomass burning aerosols, and PM from oil combustion, petroleum refineries, coal combustion, and sea salt. The city of Houston, Texas, a representative urban metroplex which suffers pollution input from both local and distal sources (such as dust from the Saharan-Sahelian region and Central American biomass burning), was chosen as a test bed to prove our hypotheses. \n\nThe first part of the research demonstrates the superiority of coupled Sr-Nd-Hf isotopes compared with metal tracers to uniquely trace different natural and anthropogenic mineral dust sources with overlapping elemental composition and accurately isolate various urban PM sources. To achieve this, a novel high-yielding gravity flow column chromatography scheme was developed to separate Sr, Nd, and Hf prior to multi collector – inductively coupled plasma – mass spectrometry (MC-ICP-MS). Thereafter, we fingerprinted several sources including vehicular PM from an underwater tunnel, petroleum refinery PM from fluidized-bed catalytic cracking units, local soil, concrete/cement dust, and trans-Atlantic North African dust in Barbados. We also measured 87Sr/86Sr, 143Nd/144Nd, and 176Hf/177Hf ratios along with elemental concentrations in Houston aerosols, which aided in apportioning ambient PM2.5 to various sources during two North African dust events in the year 2017. A novel mathematical model was developed to unify elemental and isotopic mass balance equations for sources, which consequently demonstrated the superiority of the selected radiogenic isotopes in tracing and differentiating amongst various mineral sources. \n\nThe second part of the research demonstrates platinum group elements (PGEs – Rh, Pd, and Pt) in surface roads to be exclusively emitted from motor vehicles, since their relative abundances were coherent with catalytic converters. Therefore, PGEs were utilized to accurately quantify PM from vehicular emissions. Further, we used the estimates of vehicular contributions to determine the performance of other traffic-related metals as PM tracers for vehicles. \n\nThe third part of this research focuses on PM transported to Houston from distal locations and identifies two major sources (i) desert dust from North Africa and (ii) potassium-rich smoke particles linked to forest fires or anthropogenic agricultural burning in Central America, Canada, and southeastern United States. Additionally, the influence of Saharan dust and biomass burning episodes on concentrations of PM10, PM2.5, and anthropogenic metal tracers (rare earths, vanadium, and potassium) were evaluated, demonstrating the need to separate the non-mineral component of these metals.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".