Assuring access to data for chemical evaluations

Background: A database for studies used for U.S. Environmental Protection Agency (EPA) pesticide and chemical reviews would be an excellent resource for increasing transparency and improving systematic assessments of pesticides and chemicals. There is increased demand for disclosure of raw data from studies used by the U.S. EPA in these reviews. Objectives: Because the Information Quality Act (IQA) of 2001 provides an avenue for request of raw data, we reviewed all IQA requests to the U.S. EPA in 2002–2012 and the U.S. EPA’s responses. We identified other mechanisms to access such data: public access databases, the Freedom of Information Act (FOIA), and reanalysis by a third party. Discussion: Only two IQA requests to the U.S. EPA were for raw data. Both of these were fulfilled under FOIA, not the IQA. Barriers to the U.S. EPA’s proactive collection of all such data include costs to the U.S. EPA and researchers, significant time burdens for researchers, and major regulatory delays. The U.S. EPA regulatory authority in this area is weak, especially for research conducted in the past, not funded by the U.S. government, and/or conducted abroad. The U.S. EPA is also constrained by industry confidential business information (CBI) claims for regulatory testing data under U.S. chemical and pesticide laws. The National Institutes of Health Clinical Trials database systematically collects statistical data about clinical trials but not raw data; this database may be a model for data from studies of chemicals and pesticides. Conclusions: A database that registers studies and obtains systematic sets of parameters and results would be more feasible than a system that attempts to make all raw data available proactively. Such a proposal would not obviate rights under the IQA to obtain raw data at a later point

The U.S. Environmental Protection Agency Particulate Matter Health Effects Research Centers Program: a midcourse report of status, progress, and plans.

In 1998 Congress mandated expanded U.S. Environmental Protection Agency (U.S. EPA) health effects research on ambient air particulate matter (PM) and a National Research Council (NRC) committee to provide research oversight. The U.S. EPA currently supports intramural and extramural PM research, including five academically based PM centers. The PM centers in their first 2.5 years have initiated research directed at critical issues identified by the NRC committee, including collaborative activities, and sponsored scientific workshops in key research areas. Through these activities, there is a better understanding of PM health effects and scientific uncertainties. Future PM centers research will focus on long-term effects associated with chronic PM exposures. This report provides a synopsis of accomplishments to date, short-term goals (during the next 2.5 years) and longer-term goals. It consists of six sections: biological mechanisms, acute effects, chronic effects, dosimetry, exposure assessment, and the specific attributes of a coordinated PM centers program

Assessing the distribution of volatile organic compounds using land use regression in Sarnia, "Chemical Valley", Ontario, Canada

<p>Abstract</p> <p>Background</p> <p>Land use regression (LUR) modelling is proposed as a promising approach to meet some of the challenges of assessing the intra-urban spatial variability of ambient air pollutants in urban and industrial settings. However, most of the LUR models to date have focused on nitrogen oxides and particulate matter. This study aimed at developing LUR models to predict BTEX (benzene, toluene, ethylbenzene, m/p-xylene and o-xylene) concentrations in Sarnia, 'Chemical Valley', Ontario, and model the intra-urban variability of BTEX compounds in the city for a community health study.</p> <p>Method</p> <p>Using Organic Vapour Monitors, pollutants were monitored at 39 locations across the city of Sarnia for 2 weeks in October 2005. LUR models were developed to generate predictor variables that best estimate BTEX concentrations.</p> <p>Results</p> <p>Industrial area, dwelling counts, and highways adequately explained most of the variability of BTEX concentrations (<it>R</it>²: 0.78 – 0.81). Correlations between measured BTEX compounds were high (> 0.75). Although most of the predictor variables (e.g. land use) were similar in all the models, their individual contributions to the models were different.</p> <p>Conclusion</p> <p>Yielding potentially different health effects than nitrogen oxides and particulate matter, modelling other air pollutants is essential for a better understanding of the link between air pollution and health. The LUR models developed in these analyses will be used for estimating outdoor exposure to BTEX for a larger community health study aimed at examining the determinants of health in Sarnia.</p