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Final Report: Characterization and Modeling of Indoor Particulate Contaminants In a Heavily Industrialized Community

EPA Grant Number: R828598C749
Subproject: this is subproject number 749 , established and managed by the Center Director under grant R828598
(EPA does not fund or establish subprojects; EPA awards and manages the overall grant for this center).

Center: Gulf Coast HSRC (Lamar)
Center Director: Ho, Tho C.
Title: Characterization and Modeling of Indoor Particulate Contaminants In a Heavily Industrialized Community
Investigators: Ho, Tho C. , Chu, Hsing-wei
Institution: Lamar University
EPA Project Officer: Krishnan, Bala S.
Project Period: September 1, 2000 through August 31, 2003
RFA: Gulf Coast Hazardous Substance Research Center (Lamar University) (1996)
Research Category: Hazardous Waste/Remediation , Targeted Research

Description:

Objective:

The objectives of the project are to carry out long-term experiments and model analyses to characterize both outdoor and indoor particulate contaminants and to develop dynamic models to describe the relationships between them in a heavily industrialized community, i.e., in the Golden Triangle Area. Specifically, the project milestones are to carry out the following tasks:

1.         Conduct long-term experiments to characterize both outdoor and indoor particulate contaminants and to assess the impact of outdoor contaminants on indoor levels;
2.         Perform source contribution analysis to identify major sources contributing to the outdoor particulate contaminants using chemical material balance models;
3.         Estimate the effects of air transport and other essential factors on outdoor particulate contaminants through backward trajectory simulations and neural networks modelling;
4.         Develop dynamic models to predict indoor contaminants based on outdoor contaminants, indoor sources, and measurable model parameters, e.g., penetration factor and rates of deposition, re-suspension, and filtration;
5.         Evaluate the effectiveness of various methods to reduce indoor particulate contaminants through model simulations based on the developed models; and
6.         Accomplish technology transfer through publications, presentations, workshops, short courses, and the development of computer packages.

Summary/Accomplishments (Outputs/Outcomes):

The project has provided the public and the particulate matter research community with scientific insights regarding PM behaviour in Southeast Texas.  The information is critically needed in the effective management of PM pollution leading to a cleaner environment.

1. Concentration and Chemical Analysis: Both the concentrations of outdoor PM10 and PM2.5 are measured and observed to be highly fluctuating during the months from January to April in the region.  The average PM10 and PM2.5 concentrations are 28±8 and 13±5 µg/m3, respectively.  These observed values are below the NAAQS (National Ambient Air Quality Standards) annual average standards of 50 and 15 µg/m3 for PM10 and PM2.5, respectively. The major constituents have been found to include: sulfate, organic carbon, elemental carbon, and geological material.  Efforts to characterize the detailed PM chemical composition are currently ongoing and the results will be reported in the next progress report.  In addition to outdoor PM, the corresponding indoor PM concentrations have also been measured.  Preliminary results have indicated that, under the minimum indoor activity conditions, the indoor PM concentrations are generally lower than those of outdoors.  However, certain pollutant concentrations, especially chloride, are observed to be higher in indoor PM than in outdoor PM.  The use of chlorine-containing cleaners apparently has contributed to the higher chloride concentrations found in indoor PM.         

2. Source Contribution Analysis: The analysis is to estimate the contribution of various potential sources on the measured particulate contaminants.  The approach is to perform chemical material balance calculations on each predominant species found in the measured PM against that found in the PM from various specific emission sources and formation mechanisms.  Mathematically, the concept of chemical material balance can be expressed as:

 

                        C =  Σ Sj                      j from 1 to J                                                      (1)
and
                        Ci =  ΣFij Sj                j from 1 to J                                                      (2)

where:              C:         measured ambient PM concentration, µg/m3
                        Sj:        concentration of source j, µg/m3
                        Ci:        concentration of chemical species i in the measured PM, µg/m3
                        Fij:        mass fraction of chemical species i in source j, -

In this study, both the EPA endorsed CMB8 model and the currently developed linear goal programming model were involved in the analysis, where standard EPA source profiles, including vehicle exhaust, industry, road dust, and marine aerosol, were modified for the analysis based on types of vehicles and industries found in the region.  In addition, the formations of secondary aerosols of ammonium sulfate and ammonium nitrate were also considered in the analysis. 

The TNRCC’s 1997 Houston-Clinton site PM data were first selected for the analysis due to the availability of complete PM measurements.  Typical simulation results have indicated that the major sources contributed to the site’s PM contaminants are: (1) Secondary Formation of Ammonium Sulfate (30±7%); (2) Petroleum Industry (29±19%); (3) Vehicle Exhaust (29±9%); (4) Paved Road Dust (7±2%); (5) Secondary Formation of Ammonium Nitrate (3±5%); and (6) Marine Aerosol (2±13%).  The detailed results in this analysis are reported in the paper accepted for presentation at the upcoming International Conference on Information Systems in Engineering and Construction to be held in Cocoa Beach, FL, June 7-8, 2001.  The paper is entitled "Using Linear Goal Programming to Solve Chemical Mass Balance Model."     

3. Backward Trajectory Analysis: As reported previously, the observed PM concentrations are highly fluctuating during   the sampling period.  An analysis of Pearson Correlation has revealed that the fluctuating patterns are well-correlated among PM data measured from different monitoring locations in the region. This suggests that the observed PM fluctuations in the region may be originated from the same common air transport effect.  In this study, our first attempt to investigate the effect of air transport on PM concentrations was performed using the TNRCC’s 1997 Houston-Clinton site PM measurements, again due to the availability of the complete data set.  The analysis was carried out through running the HYSPLIT4 Model (Hybrid Single-Particle Lagrangian Integrated Trajectory, version 4.0) developed by NOAA (National Oceanic Atmospheric and Administration). In the simulation, backward trajectory was performed up to 48 hours prior to the day of PM measurement at three altitudes of 10, 50 and 100 meters above the ground.  The 48 hours was selected because small PM particles, especially PM2.5, can be suspended in air for up to 48 hours.

The HYSPLIT4 simulation results have indicated that a major air transport pattern corresponding to low PM concentrations found in Houston is when the air parcels come from the south, i.e., from the Gulf of Mexico where the air is relatively clean (see, e.g., Figure 1).  On the other hand, an air transport pattern corresponding to high PM concentrations found in Houston is when the air parcels come from the east where various heavy industries are concentrated (see, e.g., Figure 2).  The detailed results of the effect of air transport on PM concentrations are reported in the paper accepted for presentation at the upcoming International Conference on Information Systems in Engineering and Construction to be held in Cocoa Beach, FL, June 7-8, 2001.  The paper is entitled "Analysis of the Effect of Air Transport on PM2.5 Using NOAA HYSPLIT4 through Internet Applications."     

4. Neural Networks Modeling: An attempt has been carried out to incorporate the backward trajectory results as well as other essential parameters into a neural network model for predicting and forecasting PM concentrations in the region.  The "Process Insight" neural networks package developed by Pavilion Incorporation is available for this modeling development.  In addition to air transport, the local wind speed, temperature, humidity, and time of day have all been identified to contribute to the observed PM based on preliminary simulations.  One of the major goals for the second year investigation is to complete the development of this neural networks model for forecasting PM pollution in the region.

5. CMAQ Development: The CMAQ modeling system for regional haze simulations is far from being perfect and is constantly being updated by EPA for improved reaction mechanisms, aerosol dynamics and chemistry, and computational efficiency.  In this task, we have continued to keep up with EPA’s development of CMAQ modeling system by implementing new CMAQ releases for regional haze simulation once they become available.  For example, on April 26, 2004, the EPA released the most updated version of NEI99 (final version 3) in IDA format.  In this version of NEI, the ammonium emission inventory has been greatly improved and the mobile emission has been prepared for monthly specific emission. The emission files have been generated using MOBILE6 with a single set of month-specific min/max temperatures per state. The VOC emissions have been split from the MOBIL6 results into EVP (evaporative) and EXH (exhaust) for better assignment of speciation profile.

In addition, in May 2004, the EPA released a new aerosol model in CMAQ called CMAQ-MADRID (Community Multiscale Air Quality - Model of Aerosol Dynamics, Reaction, Ionization and Dissolution). The model treats the aerosol dynamics using a sectional size scheme as compared to the modal (log-normal distribution) size scheme in AERO2 and AERO3. The aerosol chemistry including SOA formation has been improved and the chemical species has also been expanded in the model. The dissolution of gaseous phase species also considers the ionization in the aqueous phase using effective Henry’s constants.

The accomplishments of the project have included seven additional funded projects from the Texas Commission on Environmental Quality, the Texas Air Research Center, and the Department of Agriculture through Sul-Ross University worth $722,050.  The title and the detailed information are:

(1).     “Field and Mechanistic Studies for Texas Upper Gulf Coast Air Quality,” $110,300 from the Texas Air Research Center, 12/1/2001- 11/30/2002.

(2).     “Development of CMAQ Air Quality Modeling”, $219,000 from the Texas Commission on Environmental Quality and the Texas Air Research Center, 1/1/02 to 8/31/02.

(3).     “Characterization of Airborne Particulate Matter in a Heavily Industrialized Community,” $132,000 from the Texas Air Research Center, 12/04/02 to 12/03/04.

(4).    “Satellite Assimilation in Meteorological and Air Quality Models for the TEXAQS2000 Study Period,” $60,500 from the Texas Air Research Center, 9/1/02 to 8/31/04.

(5).     “CMAQ One-Atmosphere Modeling,” $100,000 from the Texas Commission on Environmental Quality, 12/09/03 to 8/31/04.

(6).     “Development of Modeling and Field Measurement Infrastructure for Regional Haze Analyses,” $74,000 from the Texas Air Research Center, 9/1/04 to 8/31/05.

(7).     “Assessing the Impact of Airborne Pollutants on the Rio Grande Basin,” $26,250 from the Department of Agriculture through Sul-Ross University, 9/1/04 to 8/31/05. 

Future Activities: The PIs have developed several air quality analysis models and gained significant knowledge and experience from this project for carrying out particulate matter research.  We will continue to seek research funding for future research activities related to PM analysis and modeling.  

Journal Articles:

No journal articles submitted with this report: View all 10 publications for this subproject

Supplemental Keywords:

Ecosystem Protection/Environmental Exposure & Risk, Air, Geographic Area, Scientific Discipline, Health, RFA, Air Pollution Monitoring, Engineering, Chemistry, & Physics, Air Quality, indoor air, Risk Assessments, Physics, Analytical Chemistry, air toxics, Chemistry, particulate matter, Monitoring/Modeling, Environmental Monitoring, State, particle size measurement, indoor air quality, particles, measurement methods, deposition velocity curves, air sampling, particulate emissions, human health risk, monitoring, size distribution, particulate matter formation, air quality modeling, air quality models, measurement, particulates, PM 2.5, PM2.5, quantitative analysis, Texas (TX), continuous monitoring, air pollution, PM10, air modeling, ambient air monitoring, continuous emissions monitoring, modeling, human exposure, indoor/outdoor relationships, model, particle size, PM, quantification, measurement , mass balance model
Relevant Websites:

None.

Progress and Final Reports:
2001 Progress Report
Original Abstract


Main Center Abstract and Reports:
R828598    Gulf Coast HSRC (Lamar)

Subprojects under this Center: (EPA does not fund or establish subprojects; EPA awards and manages the overall grant for this center).
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The perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Conclusions drawn by the principal investigators have not been reviewed by the Agency.


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