Church Rock Uranium Monitoring Project 2003-2007

The Church Rock Uranium Monitoring Project was initiated by Churchrock Chapter of the Navajo Nation in 2003 for the purposes of assessing environmental conditions in residential areas actually or potentially affected by abandoned uranium mines and building capacity to conduct community-based research and advocate for policies to address the long-term impacts of historic uranium development in the area. This report contains eighteen separate appendices, all of which are available as the downloadable supplementary files. There is an additional appendix for this report called Appendix III.C - Maps of Gamma Radiation Surveys Conducted by USEPA Scanner Van and Individual Surveyors Using Ludlum-19 Meters, October 2003 that we do not have. This research was completed money allocated during Round 1 of the Citizens’ Monitoring and Technical Assessment Fund (MTA Fund). Clark University was named conservator of these works. If you have any questions or concerns please contact us at [email protected]://commons.clarku.edu/churchrock/1000/thumbnail.jp

MODEL BASED ESTIMATION AND PREDICTION OF ATMOSPHERIC POLLUTANTS IN THE ENVIRONMENT

Air pollution in urban areas is mainly due to the intense use of motorized transport for travelling. To monitor the change in the concentration of pollutants in the atmosphere on a real time basis, we may use any control-theory engendered filter such as a Kalman filter, an Extended Kalman filter, an Unscented Kalman filter or a Particle filter, which are statistically based methods, that rely on some form of dynamic model of the changes in the concentration, are therefore suitable for monitoring concentrations of, Carbon monoxide (CO), Carbon dioxide (CO2), Nitric oxide (NO), unburnt hydrocarbons, Nitrogen dioxide (NO2) and other pollutants from cars and jet engines. In this study air quality monitoring data for years 2013 to 2017 (5 Years) was obtained from the website of Department for Environment, Food and Rural Affairs (DEFRA), UK. A formal statistical model that can be used to predict the dynamics of pollutants in the atmosphere or any other similar pollutant is not available and it is really necessary that such a model is developed based on the observed data. A simple second order model of this data was established using MATLAB. After that the concentrations of NO, Nitrogen dioxide (NO2) , Ozone and particulate matter (PM10) in the atmosphere at a particular location within London city, were estimated using different techniques namely, Least-squares estimation, Theil-Sen regression and an auto-regressive predictive filter known as the linear predictive coding (LPC) estimator. Based on the second order model, a Kalman filter was implemented to predict the concentration of the pollutants. Results obtained from these filters were compared with results of least-squares estimation method and Theil-Sen regression are similar and generally indicate a steady decline of the pollutant concentrations while the Kalman filter and LPC estimator predict a periodic reduction in the concentration of the same pollutants over the 5 year period

National air pollutant emission estimates /

Description based on: 1940-1985.Reports for , 1982- cumulative from 1940; , 1981 cumulative from 1970.Mode of access: Internet.Vols. for 1940-1986- produced by: Technical Support Division, National Air Data Branch