2004 Progress Report: Detection of a Recovery in Stratospheric and Total Ozone

EPA Grant Number: R829402C001
Subproject: this is subproject number 001 , established and managed by the Center Director under grant R829402
(EPA does not fund or establish subprojects; EPA awards and manages the overall grant for this center).

Center: Center for Integrating Statistical and Environmental Science
Center Director: Stein, Michael
Title: Detection of a Recovery in Stratospheric and Total Ozone
Investigators: Tiao, George , Guillas, Serge , Meng, Xiao-Li , Weatherhead, Betsy , Wuebbles, Donald J.
Current Investigators: Tiao, George , Fioletov, Vitali , Flynn, Lawrence , Guillas, Serge , Hayhoe, Katharine , Kerr, James , Meng, Xiao-Li , Miller, Alvin , Petropavlovskikh, Irina , Reinsel, Gregory , Weatherhead, Elizabeth , Wuebbles, Donald J. , Yang, Shi-Keng
Institution: University of Chicago , Georgia Institute of Technology , Harvard University , University of Colorado at Boulder , University of Illinois at Urbana-Champaign
Current Institution: University of Chicago , Environment Canada , Harvard University , National Oceanic and Atmospheric Administration , University of Colorado at Boulder , University of Illinois at Urbana-Champaign , University of Wisconsin - Madison
EPA Project Officer: Hahn, Intaek
Project Period: March 12, 2002 through March 11, 2007
Project Period Covered by this Report: March 12, 2004 through March 11, 2005
RFA: Environmental Statistics Center (2001) RFA Text |  Recipients Lists
Research Category: Environmental Statistics , Ecological Indicators/Assessment/Restoration , Health , Ecosystems , Air

Progress Summary:

Over the last 12 months, research has been conducted on the topics described below. We have continued to work with a team of scientists at the National Oceanic and Atmospheric Administration (NOAA)—notably Jim Miller and Ron Nagatani—and at the World Ozone and Ultraviolet Radiation Data Centre (WOUDC) in Canada on many aspects of the research.

It is extremely sad to note that one of our closest friends and colleagues, Gregory Reinsel, suddenly passed away in May. Greg was a giant in ozone trend analysis and had collaborated closely with a number of us on ozone trend research for more than two decades. He is sorely missed. A new principle investigator is Serge Guillas, who was a postdoctoral researcher on the project last year and has recently joined the faculty of the Georgia Institute of Technology. In our latest group meeting on October 21, 2004, Bella Maranion of the Global Programs Division, EPA, attended the meeting during which all the Center project topics were extensively reviewed and discussed. We expect that she will continue to actively participate in our group discussion meeting that has been held regularly about four times a year.

A. Trend Analysis of Total Ozone Data for Turnaround and Dynamical Contributions

We have performed a statistical trend analysis for monthly zonal average total ozone data from both the Total Ozone Mapping Spectrometer (TOMS) and the Solar Backscatter Ultraviolet (SBUV) satellite sources and ground-based instruments over the period 1978 to 2002 for detection of a “turnaround” in the previous downward trend behavior, and hence, for evidence for the beginning of an ozone recovery. In the statistical modeling, we also focus on accounting for the effects of various dynamical and circulation variations in the atmosphere, including Quasibiennial Oscillation (QBO), Arctic Oscillation (AO), Antarctic Oscillation (AAO), Eliassen–Palm (EP) flux, and solar cycle. A technical report on this topic has been completed and is under revision for publication in the Journal of Geophysical Research.

B. Trends and Solar and Arctic Oscillation Signals in Ozonesonde Data for Detection of Turnaround

For a trend analysis of profile ozone data, a statistical model that includes a linear trend beginning in 1970, together with a change in trend in about January 1996, is used to examine ozonesonde profile data for 13 ground stations over the period from 1970 to 2002. The solar flux, AO, and AAO indices are also included as explanatory variables in the statistical analysis. A technical report on this topic is near completion and will soon be submitted for publication.

C. A Statistical Evaluation of Total Ozone Trends Using a Chemistry and Transport Model (CTM)

In this work, we have proposed to model the ozone trend using results from a University of Illinois at Urbana-Champaign two-dimensional (UIUC 2-D) CTM of the global atmosphere. As part of the analysis, ozone observations from using a cohesive data set from the SBUV-SBUV/2 satellite system at northern mid-latitudes are considered in the spectral domain.

D. Statistical Diagnostics for Assessing and Improving Numerical Atmospheric Models

In this work, we have introduced a hybrid statistical CTM for total column ozone prediction, based on the UIUC 2-D CTM of the global atmosphere. A two-step diagnostic procedure is introduced for the model outputs in total ozone over the latitudes ranging from 60° South to 60° North to see if the model captures some typical patterns in the data. Details are given in a technical report, which has been submitted for publication.

E. Modeling Study on Past and Current Trends in Global Ozone

A series of atmospheric modeling studies, resulting in a Master’s Thesis for J. Xia at the University of Illinois, have been done. These studies focus on the heterogeneous processes affecting ozone over the polar regions, the analysis of past and current ozone variations, and the prediction of future ozone changes. Results from these studies were then used as input to various ozone trend research, including that described in sections C and D above. Details are given in J. Xia’s Master’s Thesis.

Results to Date

A. Trend Analysis of Total Ozone Data for Turnaround and Dynamical Contributions. The abstract of a paper completed on this topic is given below. The paper was published in the Journal of Geophysical Research.

Gregory C. Reinsel, Alvin J. Miller, Elizabeth C. Weatherhead, Lawrence E. Flynn, Ronald M. Nagatani, George C. Tiao, and Donald J. Wuebbles

Abstract. Statistical trend analyses have been performed for monthly zonal average total ozone data from both TOMS and SBUV satellite sources and ground-based instruments over the period 1978-2002 for detection of a ‘turnaround’ in the previous downward trend behavior and, hence, evidence for the beginning of an ozone recovery. Since other climatic and geophysical changes can impact ozone behavior and can influence the detection of turnaround and recovery, in the statistical modeling we also focus on accounting for ozone variations that may be ascribed to various physical and chemical influences. Thus we include in the statistical trend modeling and analysis the effects of various dynamical and circulation variations in the atmosphere, including those associated with the quasibiennial oscillation (QBO), Arctic oscillation (AO) and Antarctic oscillation (AAO), and Eliassen-Palm (EP) flux influences, as well as influences of solar cycle. A notable result of the analysis is that for latitude zones of 40E and above in both hemispheres, large positive and significant estimates of a change in trend (since 1996) are obtained (of the order of 1.5 to 3 DU per year). The dynamic index series, AO/AAO and EP flux, are found to have a substantial influence on total ozone for these higher latitudes, and significant influences of lesser magnitude are also found for lower latitudes. The feature of positive significant change in trend in total ozone over recent years, however, is obtained both without and with the dynamical index terms included in the statistical models.

B. Trends and Solar and Arctic Oscillation Signals in Ozonesonde Data for Detection of Turnaround. A summary of this work is given below. A paper is completed and will soon be submitted for publication.

Ronald M. Nagatani, Airong Cai, George Tiao, Alvin J. Miller, Irina Tropavlovskikh, Donald J. Wuebbles, Lawrence E. Flynn, Elizabeth C. Weatherhead, and Vitali Fioletov

A statistical model that includes a linear trend beginning in 1970, together with a change in trend in January 1996, is used to examine ozonesonde profile data for 13 stations from 1970 to 2002. This idea of trend change is the first being applied to ozonesonde data, although it has been previously applied to total ozone data. The solar flux and AO are also included as explanatory variables in the statistical model. We also investigate the effects of using and not using the correction factor in ozonesonde data, with the resulting analysis showing that the correction factor introduces a stronger negative trend in the data when all 13 stations are combined. A significant negative trend is observed in the ozonesonde data between 1970 and 1995, and a large and significant change in trend is observed in the ozonesonde data since 1996 at levels near 15 km, with the largest change occurring over the North American region. In addition, a large AO influence is observed also near 15 km, with the largest influences occurring over the European region.

C. A Statistical Evaluation of Total Ozone Trends Using a Chemical-Transport Model. A paper on this topic has been accepted for publication in the Journal of Geophysical Research. We provide a summary below.

Guillas, S., Stein, M. L., Wuebbles, D. J., and Xia. J.

This paper models the ozone trend using results from a UIUC 2-D chemical-transport model of the global atmosphere. As part of the analysis, ozone observations are considered in the spectral domain using a cohesive data set from the SBUV-SBUV/2 satellite system at northern mid-latitudes. In this study, we find that the new model is better at capturing the long range correlation of the data than assuming a linear trend. We also compare several statistical trend models, based either on a regression on a linear trend or on the Effective Equivalent Stratospheric Chlorine (EESC). Including a constant halocarbon emissions run of the UIUC 2-D model in the regression, the controlled EESC approach shows the best fit. The smallest future data length necessary to detect a recovery with a certain probability is obtained in this latter case. In particular, with a confidence level of 95% and a power for the test of 50%, it will take about 142 months from 2000 instead of 296 months for 40° to 50° North to detect a recovery. This represents a substantial improvement over the piecewise linear technique.

D. Statistical Diagnostics for Assessing and Improving Numerical Atmospheric Models. We provide a summary of this work, a paper of which is being considered for publication in the Journal of Geophysical Research.

Guillas, S., Tiao, G.C., Wuebbles, D.J., and Zubrow, A.

In this work, we introduce a hybrid statistical chemical-transport model for total column ozone prediction, based on the UIUC 2-­D chemical-transport model of the global atmosphere. We propose a general diagnostic procedure for the model outputs in total ozone over the latitudes ranging from 60° South to 60° North to see if the model captures some typical patterns in the data.

The method proceeds in two steps to avoid possible co-linearity. First, we regress the measurements given by a cohesive data set from the SBUV(/2) satellite system on the model outputs with an autoregressive noise component. Second, we regress the residuals of this first regression on the solar flux, the annual cycle, the AAO or AO, and the QBO. If the coefficients from this second regression are statistically significant, then they mean that the model did not simulate properly the pattern associated with these factors. Systematic anomalies of the model are then identified using data from 1979 to 1995 and are statistically corrected afterward. The 1996 to 2003 validation sample confirms that the combined approach yields appreciably better predictions than the direct UIUC 2-D outputs. The proposed two step procedure is computationally very simple and generally applicable to improve the predictive efficiency of numerical models.

E. Modeling Study on Past and Current Trends in Global Ozone

We now give a concise description of a series of atmospheric modeling studies, resulting in a Master’s Thesis for J. Xia at the University of Illinois. These studies focus on the heterogeneous processes affecting ozone over the polar regions, the analysis of past and current ozone variations, as well as the prediction of future ozone changes. Results from these studies were then used as input to various ozone trend research including that described in sections C and D above.

Polar stratospheric clouds (PSCs), an essential factor, play an extraordinarily important role in chemical ozone depletion in the lower stratosphere, especially over the polar area. The original 2-D model does not treat PSC so well, especially for the corresponding southern pole springtime ozone severe depletion, when compared with the observations. Thus, based on temperature probability distribution theory, a new PSC parameterization is set up by modifying the PSC parameterizations used in the three-dimensional (3-D) CTM developed for the National Aeronautics and Space Administration (NASA)’s Atmospheric Effects of Aviation Project (AEAP) by the Global Modeling Initiative (GMI) for use in our 2-D model. It proves to be an effective approach to improving the polar ozone treatment of the model and analyzing PSC’s role in polar ozone depletion and in the global ozone trend. However, the magnitude of the ozone depletion is still not large enough, especially for the southern pole area, as compared to the observations. Several other approaches are also discussed in the thesis in order to make a further improvement to the model PSC treatments in future work. By comparing the simulated ozone variation with the SBUV(/2) satellite and ground-based datasets, this study shows that the latest UIUC 2-D CTM can successfully track the total ozone changes of the Northern Hemisphere, Southern Hemisphere, and the entire globe in the past two decades (Figure 1). Furthermore, the modeled springtime “ozone holes” over the Arctic and Antarctica since 1980 have shown a very good agreement with the observations. As a result, the latest UIUC 2-D CTM appears to be a reliable tool for representing observed past trends in the stratospheric ozone.

Figure 1. The Comparison of Modeled Percent Ozone Change and Adjusted SBUV(/2) Observations

Figure 1. The Comparison of Modeled Percent Ozone Change and Adjusted SBUV(/2) Observations in 50° South to 50° North from 1980 to 2050.

Long-term changes in stratospheric ozone are related to the variations in tropospheric source gases, changes in solar radiation, volcanic effects, and stratospheric temperature temporal variations. A set of experiments has been designed to understand what the simulated combined response of stratospheric ozone is to the changes of these natural and anthropogenic stresses. These experiments have proved to be an effective way to assess the response of stratospheric ozone to these four driving forces, taking into account all four factors combined as well as each factor’s individual role in global and zonal ozone depletions due to their complicated interactions. As a conclusion, although changes in aerosols, trace gas emissions, solar irradiance, and stratospheric temperatures have all influenced ozone chemistry and the trends in global ozone change, anthropogenic gases appear to be the major driving force of long-term ozone change. Moreover, the treatment of global total ozone has been improved by updating the treatment for the driving forces.

The EESC, a variable that estimates the potential ozone depletion of source gases after they enter the lower stratosphere, has also been calculated by both the UIUC 2-D CTM and the simple box model. Since it is a factor that controls the long-term ozone change, the calculation of EESC in the model has improved the UIUC 2-D CTM as a forecasting tool in predicting future ozone recovery (Xia, 2004).

Potential Effects of Methane and Nitrous Oxide on the Recovery of Stratospheric Ozone. We now give a description of a series of scenario ozone recovery studies that have resulted in a Master’s Thesis by Yue Li at the University of Illinois. These scenario results form a basis for comparison with observed ozone trends in the future.

Assuming only halocarbons from human activities are affecting ozone and global compliance with the Montreal Protocol, the ozone layer is expected to recover by the middle of the 21st century. On the other hand, there are a number of other factors affecting ozone. Stratospheric ozone varies as a result of production and depletion mechanisms and transport processes around the earth. In addition, solar radiation changes due to 11-year solar cycles and aperiodic events such as volcano eruptions cause amounts of ozone to vary. However, the future ozone trends cannot be explained by only natural causes and halogen catalytic cycles. Further understanding of potential effects of other factors, particularly trace gases from human resources, is highly demanded. In this study, we considered a range of scenarios for future trace gas emissions developed by the Intergovernmental Panel on Climate Change (IPCC, 2001). See Figure 2 . We found that the future ozone recovery depends greatly on future emissions of two major green house gases (GHGs), methane (CH4) and nitrous oxide (N2O). For the six scenarios examined, total ozone increases with time during the first few decades. Some scenarios result in increasing ozone throughout the century, although not as rapid in the second half of the century as in the first. Most scenarios, except for the IPCC B1 scenario, achieve 1980 levels of ozone by around 2050. Several of these scenarios show ozone continuing to increase, beyond 1980 levels, in the last half of the century. A large latitudinal gradient in expected trends reveals a faster recovery in the Southern Hemisphere compared to that of the Northern Hemisphere. Some scenarios show declining levels of total ozone later in the century.

Figure 2. Percent Change in Annual Averaged Global Total Ozone

Figure 2. Percent Change in Annual Averaged Global Total Ozone Compared to 1980 Levels for Six IPCC Scenarios as Calculated by the UIUC 2D CTM.

The vertical profiles of ozone changes vary dramatically for different latitudes and time periods for different scenarios. However, the ozone altitude structure never returns to 1980 levels. This has important implications for climate change even when the total ozone does return to 1980 levels.

To illustrate the separate effects of N2O and CH4 that occur in the stratosphere, several new scenarios were made to contain invariant CH4 or N2O abundances. Model results show their contributions vary for different scenarios but have some general patterns. These studies found that the future levels of ozone will depend greatly on the relative increases in levels of methane and nitrous oxide, with increases in methane leading to ozone increases and increases in nitrous oxide leading to ozone decreases.

Reference:

Xia, J. Parameterization of heterogeneous processes and analysis of past, current and future ozone. M.S. Thesis, University of Illinois, Urbana-Champaign, 2004.

Future Activities:

For the next reporting period, we plan to concentrate our effort on the following topics.

A. Development of a Cohesive SBUV(/2) Satellite Total Ozone and Ozone Profile Data Set with Version 8 Algorithm

In June 2004, NASA and the National Environmental Satellite, Data, and Information Service (NESDIS) came out with a revised data set based on an algorithm that makes the ozone profile retrieval independent of the total ozone as well as including effects for satellite drift. Our colleagues in NOAA plan to redevelop a cohesive SBUV/(2) data set based on the new algorithm, and we will redo the comparisons with the 2-D model as well as the statistical “trend-change” analysis.

B. Examination of Tropospheric-Stratospheric Interaction for Decadal Variability

One significant question that continues to be the subject of considerable debate is the role of dynamics versus chemistry in accounting for the observed decadal variability in stratospheric ozone and temperature. Toward answering this question, we have included terms for the tropospheric AO along with the vertical energy EP flux and its divergence, both within the total ozone and the ozonesonde analysis, based upon 30 years (1968–1997) of National Centers for Environmental Prediction (NCEP)/ National Center for Atmospheric Research (NCAR) reanalysis data. The results, thus far, indicate a statistically significant association of the total ozone with these tropospheric dynamic terms, although the impact on the trend and trend-change is very slight. This work will be carried to completion using the Version 8 SBUV/2 data and a seasonal-trend model.

C. Development of a Trend-Quality Stratospheric Temperature Data Set

While we have made significant progress in developing a cohesive temperature data set, several issues remain. The first is that the Advanced Microwave Sounding Unit (AMSU) radiances in the stratosphere for channels 9–14 are very highly cross-correlated in time such that the statistical methodology has to be very rigorous. We will continue to investigate to make sure that the optimum approach is utilized. In addition, we will examine the algorithms employed in the polar areas to help resolve the substantial increase in error observed in the AMSU-Stratospheric Sounding Unit (SSU) continuity using the following approaches:

  1. We will re-examine the coefficients of the “X” channels that incorporate a variation with latitude.
  2. We will examine the comparisons with the AMSU: (a) using all channels; (b) using step-wise statistical regression; (c) examining the results based on all data including the annual cycle; and (d) re-examining the results using monthly anomalies.

For all data, a seasonal trend model will be examined and compared with available numerical model data.

D. Detection of a Recovery Using an Improved Numerical Mode

The UIUC 2-D CTM of the global atmosphere, with constant emissions, was used as a surrogate for the natural variation of ozone (Guillas, et al., 2004; see section C under Results to Date). The major findings were that it takes less time to detect a recovery by employing this method than by the classical piecewise linear statistical model. In particular, with a confidence level of 95 percent and a power for the test of 50 percent, it will take about 142 months from 2000, instead of 296 months, for 40° to 50° north to detect a recovery. Moreover, the UIUC 2-D model has some deficiencies, and a statistical technique has been developed to diagnose and correct the model (Guillas et al., 2006; see section C under Results to Date). A model with a better fit to the observations yields a shorter data length for the detection of a recovery, because the residual noise is diminished. Furthermore, starting in 1995—when a recovery is likely to start according to various assessments—enables us to make use of 8 years of data. Thus, reducing the data collection length necessary to detect a recovery from 12–18 years to 8 should allow us detect a recovery now.

However, there are several issues that should be investigated:

  1. Should the answer to the detection question be model free? If so, what preparatory diagnostic ought to be carried out on a numerical model in its constant emission version to qualify for being used as a basis for the trend? Some preliminary studies showed us that a model, in its scenario forced by real emissions, should not show an upward bias in the trend when compared to observations, since the constant emission scenario would be likely to present the same bias.
  2. Diagnosing that a recovery has occurred in this context means that the observations are on track with the model, according to the actual emissions scenario. Nevertheless, a “full recovery,” that is observations at their pre-1970’s levels, may never occur according to some numerical models coupled with climate change scenarios. A careful assessment of this topic can help us understand better the recovery in ozone. Indeed, strongly enforcing the Montreal protocol may yield a recovery—but not a full recovery—depending on the climatological conditions. However, the policy makers should be informed that their decisions have produced the desired outcome.

E. Statistical Diagnostics for Assessing and Improving Numerical Atmospheric Models

As pointed out in section D above, improving numerical atmospheric models can not only give us better predictions but also yield shorter data collection length for the detection of a recovery in total column ozone. The two-stage procedure (Guillas, et al., 2006; see section D under Results to Date), aimed at detecting and correcting model deficiencies, has been shown to be efficient. Moreover, the large computing time associated with these models, especially for 3-D models, makes quick statistical corrections very appealing. Furthermore, it appeared that the temperatures and winds input, either climatological, observed, or calculated, may have a great influence on the seasonal cycle and the trend.

We propose to investigate the following questions:

  1. Can we include in the diagnostics/correction study other variables than the monthly anomalies, the QBO, the AO/AAO, and the solar flux? Candidates include the aerosols and the EP Flux. What about the temperatures representation?
  2. If we want to measure the ability of the numerical atmospheric model to replicate the observed trends, how can we test for it? Indeed, testing for well-represented linear trends may not be accurate since neither the trends in the model nor the actual trends are linear. Moreover, if a downward trend is well represented in the model, is it the case for a symmetric upward trend?
  3. Some studies have shown that the nature of the influence of combined aerosols and the solar flux is non-linear with interactions. How can we improve our statistical test to adequately examine the possible deficiencies of the numerical model?
  4. If inputs of the numerical model trigger some anomalies, an adequately designed experiment could help the modelers to fix the inputs. Since there are many possibilities and the computing time is long, it may be fruitful to consider the use of statistical techniques, such as fractional factorial designs in fixing the inputs.
  5. In light of the growing interest in environmental data analysis in general, and in ozone recovery in particular, it may be useful to consider publishing a paper comparing different statistical techniques for detecting recovery and how outliers may influence the results. Such a paper is likely to attract a wide audience and provide important considerations for the scientific society. At the same time, it may also prove useful to hold a meeting to discuss issues relating to ozone recovery with the many researchers working in this field or interested in the results of this research. Members of this group have already begun discussions with some of the European researchers concerning a possible gathering.


Journal Articles on this Report : 4 Displayed | Download in RIS Format

Other subproject views: All 26 publications 4 publications in selected types All 4 journal articles
Other center views: All 115 publications 69 publications in selected types All 47 journal articles
Type Citation Sub Project Document Sources
Journal Article Guillas S, Stein ML, Wuebbles DJ, Xia J. Using chemistry transport modeling in statistical analysis of stratospheric ozone trends from observations. Journal of Geophysical Research 2004;109(D22303), doi:10.1029/2004JD005049. R829402C001 (2004)
R829402C001 (Final)
R829402C002 (2004)
  • Abstract: AGU Abstract
    Exit
  • Journal Article Guillas S, Tiao GC, Wuebbles DJ, Zubrow A. Statistical diagnostic and correction of a chemistry-transport model for the prediction of total column ozone. Atmospheric Chemistry and Physics 2006;6(2):525-537. R829402C001 (2004)
    R829402C001 (Final)
  • Abstract: Atmospheric Chemistry and Physics Abstract
    Exit
  • Other: Atmospheric Chemistry and Physics PDF
    Exit
  • Journal Article Miller AJ, Cai A, Tiao G, Wuebbles DJ, Flynn LE, Yang S-K, Weatherhead EC, Fioletov V, Petropavlovskikh I, Meng X-L, Guillas S, Nagatani RM, Reinsel GC. Examination of ozonesonde data for trends and trend changes incorporating solar and Arctic oscillation signals. Journal of Geophysical Research 2006;111(D13305), doi:10.1029/2005JD006684. R829402C001 (2004)
    R829402C001 (2006)
    R829402C001 (Final)
  • Abstract: AGU Abstract
    Exit
  • Journal Article Reinsel GC, Miller AJ, Weatherhead EC, Flynn LE, Nagatani RM, Tiao GC, Wuebbles DJ. Trend analysis of total ozone data for turnaround and dynamical contributions. Journal of Geophysical Research 2005;110(D16306), doi:10.1029/2004JD004662. R829402C001 (2004)
    R829402C001 (Final)
  • Abstract: AGU Abstract
    Exit
  • Supplemental Keywords:

    RFA, Economic, Social, & Behavioral Science Research Program, Health, Scientific Discipline, PHYSICAL ASPECTS, Air, Geographic Area, Ecosystem Protection/Environmental Exposure & Risk, particulate matter, Applied Math & Statistics, Ecosystem/Assessment/Indicators, Ecosystem Protection, Health Risk Assessment, climate change, Air Pollution Effects, Risk Assessments, Monitoring/Modeling, Ecological Effects - Environmental Exposure & Risk, Ecological Effects - Human Health, Environmental Monitoring, Physical Processes, decision-making, Environmental Statistics, Ecological Risk Assessment, Engineering, Chemistry, & Physics, Environmental Engineering, Atmosphere, EPA Region, Great Lakes, particulates, risk assessment, ecological effects, monitoring, health risk analysis, watersheds, policy making, ecological health, ozone , particulate, stratospheric ozone, ozone, risk management, computer models, exposure, air pollution, chemical transport modeling, chemical transport, trend monitoring, statistical models, human exposure, ecological risk, water, ecosystem health, environmental indicators, PM, regulations, ecological models, chemical transport models, Region 5, data models, air quality, human health risk, statistical methodology, stochastic models

    Relevant Websites:

    http://www.stat.uchicago.edu/~cises/ Exit

    Progress and Final Reports:

    Original Abstract
  • 2002 Progress Report
  • 2003
  • 2005
  • Final Report

  • Main Center Abstract and Reports:

    R829402    Center for Integrating Statistical and Environmental Science

    Subprojects under this Center: (EPA does not fund or establish subprojects; EPA awards and manages the overall grant for this center).
    R829402C001 Detection of a Recovery in Stratospheric and Total Ozone
    R829402C002 Integrating Numerical Models and Monitoring Data
    R829402C003 Air Quality and Reported Asthma Incidence in Illinois
    R829402C004 Quasi-Experimental Evidence on How Airborne Particulates Affect Human Health
    R829402C005 Model Choice Stochasticity, and Ecological Complexity
    R829402C006 Statistical Approaches to Detection and Downscaling of Climate Variability and Change