My research activities focus on using quantitative risk analysis including probabilistic models and data informatics to make recommendations on environmental health and safety policy including assessing the feasibility or effectiveness of system design mandates or regulations. A few short descriptions of current research initiatives follow below.
Though some grants and publications could conceivably apply to more than one of the broad initiatives below, each is only recorded once.
Additional information including some linked and downloadable content is available from my publications page or any of my public research profile sites:
Real world exposures to pollutants including particles or volatile chemicals are quite complex. Although most existing research just characterizes aerosol exposures by the mass concentration of PM10, PM2.5 or PM0.1, our group is performing a detailed size and chemical composition breakdown of these complex mixtures to reveal the size distributions of each particle type present in these complex aerosol mixtures. In addition to direct sample collection, we conduct air dispersion modeling and exposure assessment methodologies to predict exposures for various groups of people at risk of health impacts from heavy metals, organic chemicals, mineral dust, and combustion-related particulates from human activity.
"Trends in Marcellus-Utica Shale Regional Air Quality due to Unconventional Oil and Gas Development (TriMAQs)." PI: Gernand J. Total Budget: $469,297. Period of Performance: May 2024 to Apr 2025. Sponsor: Health Effects Institute
"Investigating Indoor Air Pollutant Variability, Source Contributions, and Respiratory Health in Senegal (RESPIRe)." PI: Gernand J. Total Budget: $50,000. Period of Performance: Nov 2021 to Jun 2024. Sponsor: Penn State Institute for Energy and the Environment
"Heavy Metal Exposures and Aggressive Prostate Cancer." PI: McDonald A. (Gernand J. - Collaborator). Total Budget: $50,000. Period of Performance: Jul 2018 to Jun 2020. Sponsor: Penn State Institute for Energy and the Environment
Collecting and Characterizing Saharan Dust and Associated Pathogens for Evaluating Disease Risk across the Meningitis Belt and Cape Verde." PI: Jenkins G. (Gernand J. - Co-PI). Total Budget: $25,000. Period of Performance: Mar 2016 to Dec 2016. Sponsor: Penn State Institute for Energy and the Environment
"Characterizing the Ambient Background Nanoparticle Distributions in Workplaces." PI: Gernand J. Total Budget: $12,960. Period of Performance: Apr 2014 to Aug 2015. Sponsor: National Institute of Occupational Safety and Health (NIOSH)
F. Ilci, M. Li, and J. Gernand, "Detailed Physico-Chemical Characterization of the Ambient Fine and Ultrafine Particulate Matter at a Construction Site," Aerosol Science and Engineering, vol. 5, p. 344-356, 2021, doi: 10.1007/s41810-021-00108-3.
Z. Banan and J. Gernand, "Emissions of Particulate Matter due to Marcellus Shale Gas Development in Pennsylvania: Mapping the Implications," Energy Policy, vol. 148, p. 41, 2021, doi: 10.1016/j.enpol.2020.111979.
A. Marone, C. Kane, G. Jenkins, and J. Gernand, "Characterization of Aerosol Bacteria from Dust Events in Dakar, Senegal," AGU GeoHealth, vol. 4, no. 6, p. 18, 2020, doi: 10.1029/2019GH000216.
K. Lai, S. Looi, M. Li, F. Ilci, H. Naushad, and J. Gernand, "Characterization of User PM Exposure During the Application of Aerosol Mineral-Based Sunscreens Shows Minimal Risk," Aerosol Science and Engineering, p. 25, 2020, doi: 10.1007/s41810-020-00079-x.
M. F. Mol, M. Li, and J. Gernand, "Particulate Matter Emissions Associated with Marcellus Shale Drilling Waste Disposal and Transport," Journal of the Air & Waste Management Association, vol. 70, no. 8, pp. 795-809, 2020, doi: 10.1080/10962247.2020.1772901.
S. Agrawal and J. Gernand, "Quantifying the Economic Impact of Hydraulic Fracturing Proppant Selection of Light of Occupational Particulate Exposure Risk and Functional Requirements," Risk Analysis, vol. 40, no. 2, pp. 319-335, 2020, doi: 10.1111/risa.13419.
Z. Banan and J. Gernand, "Evaluation of gas well setback policy in the Marcellus Shale region of Pennsylvania in relation to emissions of fine particulate matter," Journal of the Air & Waste Management Association, vol. 68, no. 9, pp. 988-1000, 2018, doi: 10.1080/10962247.2018.1462866.
The number of variations between different batches of nanomaterials (e.g. carbon nanotubes) makes the determination of the causes of observed differences in their toxicity more complicated than it is for organic chemicals. Our group develops and employs novel data mining techniques on the accumulated toxicity information on nanomaterials to help guide materials designers and regulators on the characteristics associated with increased toxic potential.
"Forecasting Pulmonary Inflammation from In Vitro Assay Results for Nanoparticles." PI: Gernand J. Total Budget: $133,470. Period of Performance: Sept 2015 to Aug 2017. Sponsor: National Institute for Occupational Safety and Health (NIOSH).
Testing the Predictive Power of Nanoparticle Characteristics for In Vitro and In Vivo Toxicity." PI: Gernand J. Total Budget: $87,795. Period of Performance: Jul 2014 to Aug 2015. Sponsor: Center for the Environmental Implications of Nanotechnology (CEINT), Duke University.
"Connecting Cells to Worms to Mice to Workers: Extending Nanomaterial Toxicity Modeling for Environmental and Occupational Risk Assessment." PI: Gernand J. Total Budget: $3,036. Period of Performance: Feb 2014 to Dec 2014. Sponsor: College of Earth and Mineral Sciences, Penn State University
V. Ramchandran and J. Gernand, "Evaluation of Risk and Uncertainty for Model-Predicted NOAELs for of Engineered Nanomaterials Based on Dose-Response-Recovery Clusters," ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, vol. 9, no. 1, p. 10, Mar. 2023, doi: 10.1115/1.4055157.
V. Ramchandran and J. Gernand, "Examining the In Vivo Pulmonary Toxicity of Engineered Metal Oxide Nanomaterials Using a Genetic Algorithm-Based Dose-Response-Recovery Clustering Model," Computational Toxicology, vol. 13, p. 43, 2020, doi: 10.1016/j.comtox.2019.100113.
V. Ramchandran and J. Gernand, "A dose-response-recovery clustering algorithm for categorizing carbon nanotube variants into toxicologically distinct groups," Computational Toxicology, vol. 11, pp. 25-32, 2019, doi: 10.1016/j.comtox.2019.02.003.
S. R. Edinger and J. Gernand, "N2-BET is a Proxy for Primary Particle Size and May Not Be Representative of Available Specific Surface Area for Aggregated Nanoparticle Aerosols," Journal of Nanoscience and Nanotechnology, vol. 18, no. 5, pp. 3049-3058, 2018, doi: 10.1166/jnn.2018.15353.
J. Gernand, "Limitations on the Reliability of In Vitro Predictive Toxicity Models to Predict Pulmonary Toxicity in Rodents," in Proceedings of IMECE 2016, 2016, p. 13, doi: 10.1115/IMECE2016-67151.
V. Stone, H. J. Johnston, D. Balharry, J. Gernand, and M. Gulumian, "Approaches to develop alternative testing strategies to inform human health risk assessment of nanomaterials," Risk Analysis, vol. 36, no. 8, pp. 1538-1550, 2016, doi: 10.1111/risa.12645.
J. Gernand and E. A. Casman, "Nanoparticle characteristic interaction effects on pulmonary toxicity: a random forest modeling framework to compare risks of nanomaterial variants," ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering, vol. 2, no. 2, p. 13, 2016, doi: 10.1115/1.4031216.
E. A. Casman and J. Gernand, "Nanotoxicology: Seeing the trees for the forest," Nature Nanotechnology, vol. 11, no. 5, p. 405, 2016, doi: 10.1038/nnano.2016.5.
J. Gernand, "Particulate Matter: Fine and Ultrafine-How Emerging Data on Engineered Nanomaterials May Change How We Regulate Worker Exposures to Dust," in Proceedings of IMECE 2015, 2015, p. 6, doi: 10.1115/IMECE2015-53056.
J. Gernand and E. A. Casman, "A Meta-Analysis of Carbon Nanotube Toxicity Experiments - How Physical Dimensions and Purity Affect the Toxicity of Carbon Nanotubes," Risk Analysis, vol. 34, no. 3, pp. 583-597, 2014, doi: 10.1111/risa.12109.
J. Gernand and E. A. Casman, "Machine learning for nanomaterial toxicity risk assessment," IEEE Intelligent Systems, vol. 29, no. 3, pp. 84--88, 2014, doi: 10.1109/MIS.2014.48.
J. Gernand and E. A. Casman, "Selecting Nanoparticle Properties to Mitigate Risks to Workers and the Public--A Machine Learning Modeling Framework to Compare Pulmonary Toxicity Risks of Nanomaterials," in Proceedings of IMECE 2013, 2013, p. 15, doi: 10.1115/IMECE2013-62687.
To ensure equity in terms of occupational and public risks to health and safety, governments typically turn to regulations to limit exposures, ensure reporting of problems, and reduce the risk of injuries and disease. These policies have limitations and one aim of my research is to evaluate the effectiveness and the efficiency of actual and proposed policies to reduce real risks to people.
J. Gernand, "The Occupational Safety Implications of the California Residential Rooftop Solar Photovoltaic Systems Mandate," Journal of Safety Research, vol. 82, pp. 144-150, Sep. 2022, doi: 10.1016/j.jsr.2022.05.005.
S. S. Eslambolchi, R. L. Grayson, and J. Gernand, "Policy changes in safety enforcement for underground coal mines show mine-size-dependent effects," Safety Science, vol. 112, pp. 223-231, 2019, doi: 10.1016/j.ssci.2018.10.005.
J. Gernand, "Occupational Safety Implications of the Changing Energy Mix," in Proceedings of IMECE 2018, 2018, p. 7, doi: 10.1115/IMECE2018-86678 .
J. C. York and J. Gernand, "Evaluating the Performance and Accuracy of Incident Rate Forecasting Methods for Mining Operations," ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering, vol. 3, no. 4, p. 16, 2017, doi: 10.1115/1.4036309.
J. Gernand, "Evaluation of the Risk Reduction Effectiveness in OSHA's Workplace Atmosphere Sampling Activities," in Proceedings of IMECE 2016, 2016, p. 6, doi: 10.1115/IMECE2016-65942.
J. Gernand, "Evaluating the effectiveness of mine safety enforcement actions in forecasting the lost-days rate at specific worksites," ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering, vol. 2, no. 4, p. 6, 2016, doi: 10.1115/1.4032929.
All humans have cognitive biases when considering risk and potential choices to mitigate those risks. However, engineers, who must make decisions about the risks to others, continually evaluate very consequential and very unlikely events, which can be prone to their own particular characteristics and challenges. My research in this area attempts to experimentally explore these biases and decision making processes through techniques developed in experimental psychology and behavioral economics to understand how to help engineers make better decisions regarding the risks of technology.
"An Engineering Design Simulator for Risk-Related Decision Making." PI: Gernand J. Total Budget: $3,972. Period of Performance: Jan 2019 to Dec 2019. Sponsor: College of Earth and Mineral Science, Penn State University
M. Midlick and J. Gernand, "Economic Viability vs. Risk Mitigation: An Experimental Investigation of Project Budget Investment Decisions in Engineering Students.," in Proceedings of IMECE 2022, 2022, vol. 9, p. 14, doi: 10.1115/IMECE2022-95484.
J. Gernand, "Understanding and Preparing for Human Bias in the Assessment of Risks," in Safety Leadership and Professional Development, American Society of Safety Professionals, 2018, Chapter 24, pp. 319-332. ISBN: 978-0-939874-18-7.
J. Gernand, "A Set of Preliminary Model Experiments for Studying Engineering Student Biases in the Assessment and Prioritization of Risks," in Proceedings of IMECE 2018, 2018, p. 8, doi: 10.1115/IMECE2018-87888.
J. Gernand, "Educating Engineering Students on Probabilistic Risk: Effects on the Perception of Ethics, Professional Responsibility, and Personal Agency," in Proceedings of IMECE 2015, 2015, p. 9, doi: 10.1115/IMECE2015-53055.