R. Subramanian, Ph.D.

Affiliations: 
2004 Carnegie Mellon University, Pittsburgh, PA 
Area:
Mechanical Engineering, Environmental Engineering
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"R. Subramanian"
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Cross-listing: Envirotree

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Allen Robinson grad student 2004 Carnegie Mellon
 (Sampling, analysis, and source apportionment of ambient carbonaceous aerosols.)
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Publications

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Rose Eilenberg S, Subramanian R, Malings C, et al. (2020) Using a network of lower-cost monitors to identify the influence of modifiable factors driving spatial patterns in fine particulate matter concentrations in an urban environment. Journal of Exposure Science & Environmental Epidemiology
Zimmerman N, Li HZ, Ellis A, et al. (2020) Improving Correlations between Land Use and Air Pollutant Concentrations Using Wavelet Analysis: Insights from a Low-cost Sensor Network Aerosol and Air Quality Research. 20: 314-328
Tanzer R, Malings C, Hauryliuk A, et al. (2019) Demonstration of a Low-Cost Multi-Pollutant Network to Quantify Intra-Urban Spatial Variations in Air Pollutant Source Impacts and to Evaluate Environmental Justice. International Journal of Environmental Research and Public Health. 16
Malings C, Tanzer R, Hauryliuk A, et al. (2019) Development of a general calibration model and long-term performance evaluation of low-cost sensors for air pollutant gas monitoring Atmospheric Measurement Techniques. 12: 903-920
Saha PK, Zimmerman N, Malings C, et al. (2018) Quantifying high-resolution spatial variations and local source impacts of urban ultrafine particle concentrations. The Science of the Total Environment. 655: 473-481
Saliba G, Subramanian R, Bilsback K, et al. (2018) Aerosol Optical Properties and Climate Implications of Emissions from Traditional and Improved Cookstoves. Environmental Science & Technology
Omara M, Zimmerman N, Sullivan MR, et al. (2018) Methane emissions from natural gas production sites in the United States: Data synthesis and national estimate. Environmental Science & Technology
Bilsback KR, Eilenberg SR, Good N, et al. (2018) The Firepower Sweep Test: A Novel Approach to Cookstove Laboratory Testing. Indoor Air
Zimmerman N, Presto AA, Kumar SPN, et al. (2018) A machine learning calibration model using random forests to improve sensor performance for lower-cost air quality monitoring Atmospheric Measurement Techniques. 11: 291-313
Tasoglou A, Subramanian R, Pandis SN. (2018) An inter-comparison of black-carbon-related instruments in a laboratory study of biomass burning aerosol Aerosol Science and Technology. 52: 1320-1331
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