About

John G. Watson is a Lecturer in Finance at Stanford Graduate School of Business and a Financial Engines Fellow. His academic training is in Applied Mathematics, having obtained his BS, MS, and PhD in Mathematics from Rensselaer Polytechnic Institute. He has taught at the University of Miami and Northwestern University, and was a research associate of J.B. Keller at Stanford University. Dr. Watson joined Financial Engines in November 1996, contributing to the development of the theory, patents, and code for simulation, style-analysis, and optimization engines that support the company's investment advisory services. His professional experience includes designing systems for optimizing hydroelectric power production, co-inventing a patented fingerprint-matching algorithm, and working on the Microsoft Excel Solver with Dan Fylstra, which automates spreadsheet analysis. His research focuses on post-retirement economics, modeling retiree spending and investment decisions, and he co-teaches a course on Modeling for Investment Management, covering techniques used by professional investment managers such as portfolio optimization and risk-neutral asset-pricing.

Research topics

• Environmental science
• Environmental chemistry
• Chemistry
• Atmospheric sciences
• Computer science

Selected publications

• Life Cycle Portfolio Choice with Human Capital and Social Security

  SSRN Electronic Journal · 2026-01-01

  preprintOpen accessSenior author
  PublisherDOI

• Combined effects of discontinuities and intact rock on weak rock at various scales

  Journal of Rock Mechanics and Geotechnical Engineering · 2025-04-27

  articleOpen access
  PublisherDOI

• Energies Within Rock Mass and the Associated Dynamic Rock Failures

  Rock Mechanics and Rock Engineering · 2025-01-18 · 11 citations

  articleOpen access1st authorCorresponding

  Abstract Catastrophic dynamic rock failure is one of the most challenging problems existing in the fields of civil tunneling and mining. It occurs in complex environments of geology, stress and excavation, and there is no one set of circumstances that is responsible for the phenomenon. However, a major contributing factor is believed to be energy storage and release. This paper studies and quantifies the energy release concept to advance the understanding and control of dynamic rock failures. The impacts of energy sources within rock masses on dynamic rock failures are assessed. The energy sources include strain and potential energy, the pressure energy of free and adsorbed gas and radiated seismic energy related to rock fracture or faulting. A new time-based coupled model is developed to estimate the ejection velocity when dynamic rock failures occur. Two burst scenarios are demonstrated using the proposed coupled model, i.e., a burst in the development heading of an unsupported face, and a ribside burst in a supported rib. The coupled model results show the superiority of bolts with a capacity for greater plastic elongation. Conveniently from the design perspective, maximum mesh tension is governed entirely by bolt capacity and mesh rupture strain. In addition, a rockburst hazard classification is proposed by examining a broad range of studies conducted in various disciplines to classify the relationship between injury severity and impact velocities. The hazard profile of dynamic rock failures caused by various mine layouts, structural domains, gas environments and geological sequences can then be estimated on the basis of the quantitative analysis.

  PublisherOA PDFDOI

• A worldwide aerosol phenomenology: Elemental and organic carbon in PM2.5 and PM10

  Atmospheric Environment · 2025-06-16 · 3 citations

  articleOpen access

  Elemental carbon (EC), organic carbon (OC), and particulate matter (PM) concentrations in the inhalable (PM 10 ) and fine (PM 2.5 ) size fractions are measured worldwide, albeit with different analytical methods. These measurements from many researchers were collected and analysed for Africa, America, Asia, and Europe for 2012 - 2019. EC/PM, OC/PM, and OC/EC ratios were examined based on region, site type, and season to infer potential sources and impacts. These analyses demonstrate that carbonaceous materials are important PM constituents throughout the world. Mean EC/PM ratios were lowest in PM 10 in Sahelian Africa and Europe (∼ 0.01), highest (> 0.07) in PM 2.5 at urban sites in North America, South America, and Japan. Mean OC/PM ratios were lowest in PM 10 in the Sahel (∼ 0.06) and in PM 2.5 in China and Thailand (0.10), and highest in central and eastern Europe (∼ 0.3) and North America (∼ 0.4). OC/EC ratios were elevated in western and northern Europe, and at regional background sites in North America. EC/PM increased with PM 10 in Thailand, while OC/PM increased with higher PM mass in Thailand, India, and North America, highlighting the specific contribution of carbonaceous aerosols to PM pollution in these regions. At European and North American background sites, OC/EC ratios increased with PM mass. Higher OC/EC ratios in dry periods indicate influence of wildfires, prescribed burns, and secondary aerosol formation. Elevated wintertime EC/PM ratios coincide with residential heating in temperate climate zones. • The carbon content of atmospheric particulate matter (PM) worldwide is assessed. • Data from hundreds of sites in Africa, Asia, America, and Europe are compared. • Organic carbon / PM ratios are highest in North America. • Elemental carbon / PM ratios are highest at urban sites. • Organic carbon / Elemental carbon ratios are highest in North America and Europe.

  PublisherDOI

• Spatiotemporal variability, atmospheric chemistry implications and health risk assessment of ambient volatile organic compounds in Central India

  Environmental Geochemistry and Health · 2025-05-29 · 2 citations

  article
  PublisherDOI

• Toxic gas and particle emissions from the pyrolysis of spacecraft materials

  Fire Safety Journal · 2025-03-22

  article
  PublisherDOI

• Brown Carbon Optical Variability in U.S. Urban Aerosols Revealed by an Enhanced Spectral/Mass Balance Approach

  Environmental Science & Technology Letters · 2025-12-05

  articleSenior author

  Light absorption by brown carbon (BrC) represents a major uncertainty in assessing the climatic effects of carbonaceous aerosols. Using 38,622 PM2.5 samples collected from the U.S. Chemical Speciation Network (2016–2018) and analyzed by a multiwavelength thermal/optical analyzer (TOA), we applied an enhanced spectral/mass balance receptor model to quantify black carbon (BC), BrC, and nonabsorbing white carbon (WtC) while allowing BrC optical properties to vary across samples. The model achieved excellent fits (r2 > 0.98) and revealed a wide range of BrC absorption Ångström exponent (AAE405–635 nm = 2.13 ± 0.74) and mass absorption efficiency (MAE532 nm = 2.03 ± 0.35 m2 g–1). An inverse AAE–MAE relationship was found, with strongly to moderately absorbing BrC being the most prevalent BrC classes. Seasonal patterns showed higher “organic brownness” (i.e., higher BrC mass fraction in organic carbon regardless of BrC class) but lower MAE in winter and the opposite in summer, reflecting the bleaching evolution of BrC with photochemical aging. BrC abundance also influenced the reconciliation between BC- and TOA-derived elemental carbon, likely through altered thermal–optical carbon analysis splits. This study provides the first nationwide characterization of BrC optical variability from national network data, establishing a scalable framework toward long-term monitoring of organic aerosol absorption within existing regulatory programs.

  PublisherDOI

• Sizing Accuracy of Low-Cost Optical Particle Sensors Under Controlled Laboratory Conditions

  Atmosphere · 2025-04-26 · 7 citations

  articleOpen access

  Low-cost particulate matter sensors have seen increased use for monitoring at personal and local levels due to their affordability, ease of operation, and high time resolution. However, the quality of data reported by these sensors can be questionable, and a thorough evaluation of their performance is necessary. This study evaluated the particle sizing accuracy of several commonly used optical sensors, including the Alphasense optical particle counter (OPC), TSI DustTrak DRX aerosol monitor, Plantower PMS5003 sensor, and Sensirion SPS30 sensor, using laboratory-generated monodisperse particles. The OPC and DRX agreed partially with reference instruments and showed promise in detecting coarse-size particles. However, the PMS5003 and SPS30 did not correctly size fine and coarse particles. Furthermore, their reported mass distributions do not directly correspond to their number distribution. Despite these limitations, field measurements involving a dust storm period showed that the SPS30 correlated reasonably well with reference instruments for both PM2.5 and PM10, though the regression slopes differed significantly. These findings underscore the need for caution when interpreting data from low-cost optical sensors, particularly for coarse particles. Recommendations for improving the performance of these sensors are also provided.

  PublisherOA PDFDOI

• Source Identification of Ambient PM _2.5 and VOCs in a Complex Urban–Industrial Environment of India: Application of Receptor Modeling

  ACS Earth and Space Chemistry · 2025-12-03

  article

  This study aimed to estimate source contributions to ambient fine particulate matter (PM2.5) and volatile organic compounds (VOCs) measured at Raipur, Central India, during the periods of October 2015–September 2016 and November 2021–June 2022. Chemical compositions (15 elements, nine water-soluble ions, organic carbon [OC], and elemental carbon [EC]) for 164 PM2.5 filter samples and 120 absorbent samples (21 VOCs) were used as input to receptor models (USEPA UNMIX 6.0 and PMF 5.0 models) for source apportionment. The results revealed four PM2.5 source types and average relative source contributions: (1) road traffic (29.7%), (2) industrial emission (25.4%), (3) biomass burning (24.0%), and (4) coal combustion (20.9%). Average VOC source attributions were (1) vehicle engine exhausts (37.7%), (2) biomass burning and coal combustion (20.3%), (3) industrial emission/solvent usage (34.1%), and (4) biogenic emissions (7.90%). Nineteen locally derived PM2.5 chemical source profiles for road traffic, domestic heating, and industrial emissions were used with the EV-CMB 8.2 model for comparison with PMF results, yielding similar source contributions.

  PublisherDOI

• Gaseous pollutant emissions from solid fuel combustion: Comparative study of real-world and simulated chamber-based experiments

  Atmospheric Pollution Research · 2025-10-25

  article
  PublisherDOI

Frequent coauthors

• Judith C. Chow

  894 shared

• Junji Cao

  364 shared

• Judith C. Chow

  Desert Research Institute

  346 shared

• L.‐W. Antony Chen

  University of Nevada, Las Vegas

  274 shared

• Xiaoliang Wang

  199 shared

• Kin‐Fai Ho

  Hong Kong Jockey Club

  141 shared

• Steven Sai Hang Ho

  128 shared

• J. C. Chow

  Savannah River National Laboratory

  114 shared

Education

• Ph.D., Oregon Graduate Institute

  Oregon Health and Science University

  1979

Awards & honors

• 2010 INFORMS Impact Prize (Solver Team)