Research Interests

The Stanier Research Group has wide-ranging interests in atmospheric science, climate science, and air pollution.

Our main current projects focus on (1) health effects of atmospheric pollution, focusing on ultrafine particulate matter; (2) modeling of CO2, CO, and other carbon and nitrogen species in the environment; and (3) chemistry and physics of ultrafine, nanosized, and nucleated atmospheric particles.

Our research includes atmospheric science problems motivated by both climate change and by human health. The investigations share a set of tools that we have developed in our lab and in collaborator labs. These include measurements such as Scanning Mobility Particle Sizing, thermal and hygroscopic TDMA, gas monitors for atmospheric pollutants, and cloud condensation nuclei. This also includes 3D chemical transport models that we apply to carbon cycle gases, gas phase pollutants, and aerosols. We also have developed box, 1D and 2D process models that combine dispersion, motor vehicle emissions, and new particle formation.

Many of our projects involve detailed data analysis at the interface between models and measurements. This is particularly true for carbon cycle gases, new particle formation, and particulate matter.

Some photos and figures from our research are below. For more information, please see the publications page.

Gallery of Some Images and Figures from Our Research

Output from the CGRER High Resolution Midwestern CO2 Simulation. All panels for July 8, 2008. Panels show the progression from high CO2 levels in the early morning (from accumulation of respiration CO2 in the stable nocturnal boundary layer), followed by decreases in the CO2 concentrations from boundary layer ventilation and photosynthetic uptake.

By Aditsuda Jamroensan, Charles Stanier, and Greg Carmichael

Simulation at 4 km using WRF-VPRM (Ahmadov, 2007). VPRM preprocessor codes by Roberto Kretschmer (, and Anthropogenic Fluxes from Vulcan (Gurney, 2009)



From Sinan Sousan's presentation at the CMAS conference in 2010, statistical combination of satellite-derived aerosol concentrations with 3 dimensional CMAQ modeled aerosols. These are on a monthly basis using optimal interpolation.

A conceptual model of particulate matter pollution and human exposure during wintertime episodes in the Upper Midwest.

From our project on data analysis of the LADCO Winter Nitrate Study, modeling ammonia partitioning (x axis) versus measured ammonia partitioning (y axis). Measurements are hourly values from LADCOs 2009 field campaign in Eastern Wisconsin. (The model we are using is ISORROPIA by Nenes et al. 1998). Ammonia is a key pollutant in the Upper Midwest during the wintertime, and having a large database of model and measurement pairs for ammonia gas and ammonium aerosol allows us to investigate the effects of ammonia and nitrate reductions on air pollution concentrations.

Upward looking photo of the WKWB transmitter tower which is now (as of July 1, 2007) sampling CO2 and CO as part of the NOAA global monitoring network (station ID WBI -- for West Branch Iowa). Met stations can be seen sticking out to the left. There are three of them, one is all the way at the top, very difficult to make out. Carbon dioxide and carbon monoxide are continuously pumped down from the three levels of the tower and analyzed by continuous spectroscopic analyzers. The idea is that a network of sites like these provides the data for "top down" estimation of carbon fluxes, particularly those associated with forest regrowth and crop production. For more information, go to the NOAA global monitoring division website.

NASA DC-8 CO2 measurements CO2 along ICARTT DC-8 flight path on July, 20, 2004. These were the inspiration and data source for much of Elliott Campbell's thesis. These summertime flights offered a test of the models and carbon flux estimates that we combined to make atmospheric CO2 predictions. Measured values shown in top and bottom plots. Modeled CO2 is black line, bottom plot. Model-measurement agreement deteriorates at low altitudes over agricultural lands, indicating underestimate (and poor predictive ability) of crop CO2 drawdown in model.

Obvious to most folks... this is not from our research but rather from the Intergovernmental Panel on Climate Change (IPCC). This figure is from the "Summary for Policy Makers" of the Fourth Assessment Report work Working Group I (Climate Science Group). This figure is important to the motivation for our work. Our carbon cycle work is tied to the largest positive forcing (long-lived greenhouse gases). Our New Particle Formation research is motivated by the largest negative forcing -- the cloud albedo effect.

In the jargon, the source is IPCC 2007:WG1-AR4 SPM. Links to IPCC and to the Working Group 1 AR4 documents for download.

A cool picture taken by Alica Kalafut during the MILAGRO field campaign in Mexico City. We took our Dry-Ambient Aerosol Size Spectrometer to Mexico City and sampled at the T0 station. Greg Carmichael's group from the University of Iowa worked on forecasting for the field study, and Bill Eichinger's group did LIDAR measurements throught central mexico.

The main pieces of the dry-ambient aerosol size spectrometer awaiting tubing and wiring in building 32 in Mexico City, site T0.

Cover of JGR Special Issue showing corresponding between new particle formation (NPF) and aerosol composition. Aerosol composition data from Qi Zhang and Jose Luis Jimenez (University of Colorado) Link to special section of JGR here. New Particle Formation (NPF) is important as a source of atmospheric particles that can serve as cloud condensation nuclei. NPF occurs in both remote and polluted (including urban) environments. There is likely a large difference in the health effects between nucleated sulfate-organic particles and nanosized combustion particles. Tools for separating these particles and their health effects are needed.

Our aerosol sampling trailer at the Bondville Experimental Atmospheric Research Site near the University of Illinois. This was our first deployment. We sampled NPF events on 25% of the days, based on 21 days of sampling.

Regression result to determine the aerosol mass fraction (yield) of secondary organic aerosol with accurate temperature dependence and uncertainty bounds. These types of regressions are required to put secondary organic aerosols into Chemical Transport Models. Example is for alpha pinene ozonolysis but technique is general. See The Coupled Partitioning, Dilution, and Chemical Aging of Semivolatile Organics and other papers involving secondary organic aerosols in the publications page.




Page maintained by C. Stanier