Richard Poirot - Academia.edu (original) (raw)
Papers by Richard Poirot
This study applies and compares results of four receptor modeling techniques to a common set of I... more This study applies and compares results of four receptor modeling techniques to a common set of IMPROVE-like, speciated fine particle measurement data collected at remote site in northwestern Vermont between 1988 and 1995. Two multivariate mathematical models - Positive Matrix Factorization and UNMIX - were applied to the measurement data, and identified seven "common" sources, which have similar compositions and
Wood smoke from forest fires or anthropogenic activities can be a significant contributor to regi... more Wood smoke from forest fires or anthropogenic activities can be a significant contributor to regional haze and PM2.5, but routine methods to quantify the extent of this source's contribution to visibility impairment and ambient levels of PM2.5 have not been developed and evaluated. This paper evaluates an approach to semi-quantitatively measure the fraction of PM that is from wood smoke
Current approaches and recent developments and software related with multivariate factor analysis... more Current approaches and recent developments and software related with multivariate factor analysis and related methods in the analysis of environmental data for the identification, resolution and apportionment of contamination sources are discussed and compared
Source types or source regions contributing to the concentration of atmospheric fine particles me... more Source types or source regions contributing to the concentration of atmospheric fine particles measured at Brigantine National Wildlife Refuge, NJ, were identified using a factor analysis model called Positive Matrix Factorization (PMF). Cluster analysis of backward air trajectories on days of high- and low-factor concentrations was used to link factors to potential source regions. Brigantine is a Class I visibility
Journal of Toxicology and Environmental Health, Part A, 2007
The human health effects of fine particulate matter (PM 2.5 ) have provided impetus for the estab... more The human health effects of fine particulate matter (PM 2.5 ) have provided impetus for the establishment of new air quality standards or guidelines in many countries. This has led to the need for information on the main sources responsible for PM 2.5 . In urban locations being impacted by regional-scale transport, source-receptor relationships for PM 2.5 are complex and require the application of multiple receptor-based analysis methods to gain a better understanding. This approach is being followed to study the sources of PM 2.5 impacting southern Ontario, Canada, and its major city of Toronto. Existing monitoring data in the region around Toronto and within Toronto itself is utilized to estimate that 30-45% of the PM 2.5 is from local sources, which implies that 55-70% are transported into the area. In addition, there are locations in the city that can be shown to experience a greater impact from local sources such as motor vehicle traffic. Detailed PM 2.5 chemical characterization data were collected in Toronto in order to apply two different multivariate receptor models to determine the main sources of the PM 2.5 . Both approaches produced similar results indicating that motor-vehicle-related emissions, most likely of local origin, are directly responsible for about 20% of the PM 2.5 . Gasoline engine vehicles were found to be a greater overall contributor (13%) compared to diesel vehicles (8%). Secondary PM 2.5 from coal-fired power plants continues to be a significant contributor (20-25%) and also played a role in enhancing production of secondary organic carbon mass (15%) on fine particles. Secondary fine particle nitrate was the single-most important source (35%) with a large fraction of this likely related to motor vehicle emissions. Independent use of different receptor models helps provide more confidence in the source apportionment as does comparison of results among complementary receptor-based data analysis approaches.
Journal of the Air & Waste Management Association, 2009
A previously unobserved multi-state region of elevated particulate nitrate concentration was dete... more A previously unobserved multi-state region of elevated particulate nitrate concentration was detected as a result of the expansion of the Interagency Monitoring of Protected Visual Environments (IMPROVE) network of remote-area particulate matter (PM) speciation monitoring sites into the midwestern United States that began in 2002. Mean winter ammonium nitrate concentrations exceed 4 microg/m3 in a region centered in Iowa, which makes it responsible for as much as half of the particle light extinction. Before these observations, particulate nitrate in the United States was only observed to be a dominant component of the fine PM (PM2.5) in parts of California and some urban areas. Comparisons of the spatial patterns of particulate nitrate with spatial patterns of ammonia and nitrogen oxide emissions suggest that the nitrate bulge is the result of the high emissions of ammonia associated with animal agriculture in the Midwest. Nitrate episodes at several locations in the eastern United States are shown to be associated with transport pathways over the Midwest, suggesting long-range transport of either ammonia or ammonium nitrate. Thermodynamic equilibrium modeling conducted by others on data from the Midwest shows the relative importance of atmospheric ammonia and nitric acid in the production of PM2.5. This is a particular concern as the sulfur dioxide emissions in the United States are reduced, which increases the amount of ammonia available for ammonium nitrate production.
Journal of the Air & Waste Management Association, 2009
Rocky Mountain National Park is experiencing reduced visibility and changes in ecosystem function... more Rocky Mountain National Park is experiencing reduced visibility and changes in ecosystem function due to increasing levels of oxidized and reduced nitrogen. The Rocky Mountain Atmospheric Nitrogen and Sulfur study (ROMANS) was initiated to better understand the origins of sulfur and nitrogen species as well as the complex chemistry occurring during transport from source to receptor. As part of the study, a monitoring program was initiated for two 1-month time periods, one during the spring and the other during late summer/fall. The monitoring program included intensive high time resolution concentration measurements of aerosol number size distribution, inorganic anions, and cations, and 24-hour time resolution of fine and coarse mass, sulfate, nitrate, carbon, and soil-related elements concentrations. These data are combined to estimate high time resolution concentrations of fine and coarse aerosol mass and fine mass species estimates of ammoniated sulfate, nitrate, and organic and elemental carbon. Hour-by-hour extinction budgets are calculated by using these species concentration estimates and measurements of size distribution and assuming both internal and external particle mixtures. Summer extinction was on the average about three times higher than springtime extinction, while during spring months all species contributed approximately equal amounts of extinction and during the summer months carbonaceous material extinction was 2-3 times higher than other species.
Journal of the Air & Waste Management Association, 2009
Crocker Nuclear Laboratory uses a custom built energy-dispersive X-ray fluorescence system with a... more Crocker Nuclear Laboratory uses a custom built energy-dispersive X-ray fluorescence system with a molybdenum anode to provide routine analysis of elements from nickel to zirconium and lead in Interagency Monitoring of Protected Visual Environments (IMPROVE) samples. Standard methods are used to ensure accuracy and statistical control of the data, including repeated analysis of single-element standards, standard reference materials, and selected actual samples from the IMPROVE network. This paper compares the short-term (week) precision and long-term (2-yr) reproducibility revealed by the actual sample reanalyses. Currently reported analytical uncertainties are shown to predict actual 2-yr reproducibility within a factor of 2.
Journal of the Air & Waste Management Association, 2009
Precision is a concept for which there is no universally accepted metric. Reports of precision va... more Precision is a concept for which there is no universally accepted metric. Reports of precision vary depending on the formula and inclusion criteria used to calculate them. To properly interpret and utilize reported precisions, the user must understand exactly what the precision represents. This paper uses duplicate Interagency Monitoring of Protected Visual Environments (IMPROVE) measurements to illustrate distinctions among different approaches to reporting precision. Three different metrics are used to estimate the precision from the relative differences between the duplicate measurements: the root mean square (RMS), the mean absolute value, and a percentile spread. Precisions calculated using the RMS relative difference yield wide distributions that tend to overestimate most of the observed differences. Precisions calculated using percentiles of the relative differences yield narrower distributions that tend to fit the bulk of the observed differences very well. Precisions calculated using the mean absolute relative difference lie between the other two precision estimates. All three approaches underestimate the observed differences for a small percentage of outliers.
Journal of the Air & Waste Management Association, 1997
Confidence interval construction for central tendency is a problem of practical consequence for t... more Confidence interval construction for central tendency is a problem of practical consequence for those who must analyze air contaminant data. Determination of compliance with relevant ambient air quality criteria and assessment of associated health risks depend upon quantifying the uncertainty of estimated mean pollutant concentrations. The bootstrap is a resampling technique that has been steadily gaining popularity and acceptance during the past several years. A potentially powerful application of the bootstrap is the construction of confidence intervals for any parameter of any underlying distribution. Properties of bootstrap confidence intervals were determined for samples generated from lognormal, gamma, and Weibull distributions. Bootstrap t intervals, while having smaller coverage errors than Student's t or other bootstrap methods, under-cover for small samples from skewed distributions. Therefore, we caution against using the bootstrap to construct confidence intervals for the mean without first considering the effects of sample size and skew. When sample sizes are small, one might consider using the median as an estimate of central tendency. Confidence intervals for the median are easy to construct and do not under-cover. Data collected by the Northeast States for Coordinated Air Use Management (NESCAUM) are used to illustrate application of the methods discussed.
During early July 2002, dense smoke from a number of large forest fires in central Quebec Provinc... more During early July 2002, dense smoke from a number of large forest fires in central Quebec Province was transported south by prevailing winds into the New England and Mid-Atlantic states. Given the high concentrations of smoke, strong flows from the north, and relative absence of other emissions in that direction, this event provides a unique opportunity to evaluate impacts of nearly pure wood smoke at multiple monitoring sites in the Northeast. Continuous measurements of PM 2.5 mass from State and Federal monitoring programs and light scattering from (a few) IMPROVE nephelometers and (many) ASOS forward scatter meters reveal highly complex spatial and temporal patterns of smoke impacts at the surface on July 6-8, 2002. Maximum observed 24-hour smoke impacts at most US surface sites occurred on July 7 th , which was coincidently a routine filter sampling day for the IMPROVE, STN and FRM (fine mass-only) networks. Combining the continuous PM, light scattering and filter-based chemical data provides insights into the chemical and physical features of the smoke during this "event of opportunity".
The discussion followed the issues and general timing as presented in the meeting agenda (Appendi... more The discussion followed the issues and general timing as presented in the meeting agenda (Appendix B).
Environmental Science & Technology, 2001
This study applies and compares results of four receptor modeling techniques to a common set of I... more This study applies and compares results of four receptor modeling techniques to a common set of IMPROVE-like, speciated fine particle measurement data collected at remote site in northwestern Vermont between 1988 and 1995. Two multivariate mathematical models - Positive Matrix Factorization and UNMIX - were applied to the measurement data, and identified seven "common" sources, which have similar compositions and
Wood smoke from forest fires or anthropogenic activities can be a significant contributor to regi... more Wood smoke from forest fires or anthropogenic activities can be a significant contributor to regional haze and PM2.5, but routine methods to quantify the extent of this source's contribution to visibility impairment and ambient levels of PM2.5 have not been developed and evaluated. This paper evaluates an approach to semi-quantitatively measure the fraction of PM that is from wood smoke
Current approaches and recent developments and software related with multivariate factor analysis... more Current approaches and recent developments and software related with multivariate factor analysis and related methods in the analysis of environmental data for the identification, resolution and apportionment of contamination sources are discussed and compared
Source types or source regions contributing to the concentration of atmospheric fine particles me... more Source types or source regions contributing to the concentration of atmospheric fine particles measured at Brigantine National Wildlife Refuge, NJ, were identified using a factor analysis model called Positive Matrix Factorization (PMF). Cluster analysis of backward air trajectories on days of high- and low-factor concentrations was used to link factors to potential source regions. Brigantine is a Class I visibility
Journal of Toxicology and Environmental Health, Part A, 2007
The human health effects of fine particulate matter (PM 2.5 ) have provided impetus for the estab... more The human health effects of fine particulate matter (PM 2.5 ) have provided impetus for the establishment of new air quality standards or guidelines in many countries. This has led to the need for information on the main sources responsible for PM 2.5 . In urban locations being impacted by regional-scale transport, source-receptor relationships for PM 2.5 are complex and require the application of multiple receptor-based analysis methods to gain a better understanding. This approach is being followed to study the sources of PM 2.5 impacting southern Ontario, Canada, and its major city of Toronto. Existing monitoring data in the region around Toronto and within Toronto itself is utilized to estimate that 30-45% of the PM 2.5 is from local sources, which implies that 55-70% are transported into the area. In addition, there are locations in the city that can be shown to experience a greater impact from local sources such as motor vehicle traffic. Detailed PM 2.5 chemical characterization data were collected in Toronto in order to apply two different multivariate receptor models to determine the main sources of the PM 2.5 . Both approaches produced similar results indicating that motor-vehicle-related emissions, most likely of local origin, are directly responsible for about 20% of the PM 2.5 . Gasoline engine vehicles were found to be a greater overall contributor (13%) compared to diesel vehicles (8%). Secondary PM 2.5 from coal-fired power plants continues to be a significant contributor (20-25%) and also played a role in enhancing production of secondary organic carbon mass (15%) on fine particles. Secondary fine particle nitrate was the single-most important source (35%) with a large fraction of this likely related to motor vehicle emissions. Independent use of different receptor models helps provide more confidence in the source apportionment as does comparison of results among complementary receptor-based data analysis approaches.
Journal of the Air & Waste Management Association, 2009
A previously unobserved multi-state region of elevated particulate nitrate concentration was dete... more A previously unobserved multi-state region of elevated particulate nitrate concentration was detected as a result of the expansion of the Interagency Monitoring of Protected Visual Environments (IMPROVE) network of remote-area particulate matter (PM) speciation monitoring sites into the midwestern United States that began in 2002. Mean winter ammonium nitrate concentrations exceed 4 microg/m3 in a region centered in Iowa, which makes it responsible for as much as half of the particle light extinction. Before these observations, particulate nitrate in the United States was only observed to be a dominant component of the fine PM (PM2.5) in parts of California and some urban areas. Comparisons of the spatial patterns of particulate nitrate with spatial patterns of ammonia and nitrogen oxide emissions suggest that the nitrate bulge is the result of the high emissions of ammonia associated with animal agriculture in the Midwest. Nitrate episodes at several locations in the eastern United States are shown to be associated with transport pathways over the Midwest, suggesting long-range transport of either ammonia or ammonium nitrate. Thermodynamic equilibrium modeling conducted by others on data from the Midwest shows the relative importance of atmospheric ammonia and nitric acid in the production of PM2.5. This is a particular concern as the sulfur dioxide emissions in the United States are reduced, which increases the amount of ammonia available for ammonium nitrate production.
Journal of the Air & Waste Management Association, 2009
Rocky Mountain National Park is experiencing reduced visibility and changes in ecosystem function... more Rocky Mountain National Park is experiencing reduced visibility and changes in ecosystem function due to increasing levels of oxidized and reduced nitrogen. The Rocky Mountain Atmospheric Nitrogen and Sulfur study (ROMANS) was initiated to better understand the origins of sulfur and nitrogen species as well as the complex chemistry occurring during transport from source to receptor. As part of the study, a monitoring program was initiated for two 1-month time periods, one during the spring and the other during late summer/fall. The monitoring program included intensive high time resolution concentration measurements of aerosol number size distribution, inorganic anions, and cations, and 24-hour time resolution of fine and coarse mass, sulfate, nitrate, carbon, and soil-related elements concentrations. These data are combined to estimate high time resolution concentrations of fine and coarse aerosol mass and fine mass species estimates of ammoniated sulfate, nitrate, and organic and elemental carbon. Hour-by-hour extinction budgets are calculated by using these species concentration estimates and measurements of size distribution and assuming both internal and external particle mixtures. Summer extinction was on the average about three times higher than springtime extinction, while during spring months all species contributed approximately equal amounts of extinction and during the summer months carbonaceous material extinction was 2-3 times higher than other species.
Journal of the Air & Waste Management Association, 2009
Crocker Nuclear Laboratory uses a custom built energy-dispersive X-ray fluorescence system with a... more Crocker Nuclear Laboratory uses a custom built energy-dispersive X-ray fluorescence system with a molybdenum anode to provide routine analysis of elements from nickel to zirconium and lead in Interagency Monitoring of Protected Visual Environments (IMPROVE) samples. Standard methods are used to ensure accuracy and statistical control of the data, including repeated analysis of single-element standards, standard reference materials, and selected actual samples from the IMPROVE network. This paper compares the short-term (week) precision and long-term (2-yr) reproducibility revealed by the actual sample reanalyses. Currently reported analytical uncertainties are shown to predict actual 2-yr reproducibility within a factor of 2.
Journal of the Air & Waste Management Association, 2009
Precision is a concept for which there is no universally accepted metric. Reports of precision va... more Precision is a concept for which there is no universally accepted metric. Reports of precision vary depending on the formula and inclusion criteria used to calculate them. To properly interpret and utilize reported precisions, the user must understand exactly what the precision represents. This paper uses duplicate Interagency Monitoring of Protected Visual Environments (IMPROVE) measurements to illustrate distinctions among different approaches to reporting precision. Three different metrics are used to estimate the precision from the relative differences between the duplicate measurements: the root mean square (RMS), the mean absolute value, and a percentile spread. Precisions calculated using the RMS relative difference yield wide distributions that tend to overestimate most of the observed differences. Precisions calculated using percentiles of the relative differences yield narrower distributions that tend to fit the bulk of the observed differences very well. Precisions calculated using the mean absolute relative difference lie between the other two precision estimates. All three approaches underestimate the observed differences for a small percentage of outliers.
Journal of the Air & Waste Management Association, 1997
Confidence interval construction for central tendency is a problem of practical consequence for t... more Confidence interval construction for central tendency is a problem of practical consequence for those who must analyze air contaminant data. Determination of compliance with relevant ambient air quality criteria and assessment of associated health risks depend upon quantifying the uncertainty of estimated mean pollutant concentrations. The bootstrap is a resampling technique that has been steadily gaining popularity and acceptance during the past several years. A potentially powerful application of the bootstrap is the construction of confidence intervals for any parameter of any underlying distribution. Properties of bootstrap confidence intervals were determined for samples generated from lognormal, gamma, and Weibull distributions. Bootstrap t intervals, while having smaller coverage errors than Student's t or other bootstrap methods, under-cover for small samples from skewed distributions. Therefore, we caution against using the bootstrap to construct confidence intervals for the mean without first considering the effects of sample size and skew. When sample sizes are small, one might consider using the median as an estimate of central tendency. Confidence intervals for the median are easy to construct and do not under-cover. Data collected by the Northeast States for Coordinated Air Use Management (NESCAUM) are used to illustrate application of the methods discussed.
During early July 2002, dense smoke from a number of large forest fires in central Quebec Provinc... more During early July 2002, dense smoke from a number of large forest fires in central Quebec Province was transported south by prevailing winds into the New England and Mid-Atlantic states. Given the high concentrations of smoke, strong flows from the north, and relative absence of other emissions in that direction, this event provides a unique opportunity to evaluate impacts of nearly pure wood smoke at multiple monitoring sites in the Northeast. Continuous measurements of PM 2.5 mass from State and Federal monitoring programs and light scattering from (a few) IMPROVE nephelometers and (many) ASOS forward scatter meters reveal highly complex spatial and temporal patterns of smoke impacts at the surface on July 6-8, 2002. Maximum observed 24-hour smoke impacts at most US surface sites occurred on July 7 th , which was coincidently a routine filter sampling day for the IMPROVE, STN and FRM (fine mass-only) networks. Combining the continuous PM, light scattering and filter-based chemical data provides insights into the chemical and physical features of the smoke during this "event of opportunity".
The discussion followed the issues and general timing as presented in the meeting agenda (Appendi... more The discussion followed the issues and general timing as presented in the meeting agenda (Appendix B).
Environmental Science & Technology, 2001