The Mobile Source Emissions Factor (MOBILE) model is a computer model developed by the U.S. Environmental Protection Agency (EPA) for estimating emissions from on-road motor vehicles. MOBILE is used in air-quality planning and regulation for estimating emissions of carbon monoxide (CO), volatile organic compounds (VOCs), and nitrogen oxides (NOx) and for predicting the effects of emissions-reduction programs. Because of its important role in air-quality management, the accuracy of MOBILE is critical. Possible consequences of inaccurately characterizing motor-vehicle emissions include the implementation of insufficient controls that endanger the environment and public health or the implementation of ineffective policies that impose excessive control costs. Billions of dollars per year in transportation funding are linked to air-quality attainment plans, which rely on estimates of mobile-source emissions. Transportation infrastructure decisions are also affected by emissions estimates from MOBILE. In response to a request from Congress, the National Research Council established the Committee to Review EPA's Mobile Source Emissions Factor (MOBILE) Model in October 1998. The committee was charged to evaluate MOBILE and to develop recommendations for improving the model.

Managing the nation's air quality is a complex undertaking, involving tens of thousands of people in regulating thousands of pollution sources. The authors identify what has worked and what has not, and they offer wide-ranging recommendations for setting future priorities, making difficult choices, and increasing innovation. This new book explores how to better integrate scientific advances and new technologies into the air quality management system. The volume reviews the three-decade history of governmental efforts toward cleaner air, discussing how air quality standards are set and results measured, the design and implementation of control strategies, regulatory processes and procedures, special issues with mobile pollution sources, and more. The book looks at efforts to spur social and behavioral changes that affect air quality, the effectiveness of market-based instruments for air quality regulation, and many other aspects of the issue. Rich in technical detail, this book will be of interest to all those engaged in air quality management: scientists, engineers, industrial managers, law makers, regulators, health officials, clean-air advocates, and concerned citizens.

"The combination of scientific and institutional integrity represented by this book is unusual. It should be a model for future endeavors to help quantify environmental risk as a basis for good decisionmaking." â€"William D. Ruckelshaus, from the foreword. This volume, prepared under the auspices of the Health Effects Institute, an independent research organization created and funded jointly by the Environmental Protection Agency and the automobile industry, brings together experts on atmospheric exposure and on the biological effects of toxic substances to examine what is knownâ€"and not knownâ€"about the human health risks of automotive emissions.

This book brings together the methods, models and formulae used for estimating air pollution concentrations in urban areas. From the ForewordThe visible effects of pollution in most cities in the developed countries have been reduced dramatically in the past thirty years. This has been achieved to a large extent by the replacement of most of the low-level sources, which burnt raw coal, by more modern appliances using gas, electricity or low-sulphur oil. The killer smog of 1952 could not be repeated unless there were to be a massive return to old-fashioned heating methods, due, for example, to excessive environmental constraints being applied to the more modern energy sources. It is important, therefore, to judge the impact of a new source in terms of its effect on the pattern of existing sources. One should also consider the environmental consequences of rejecting the new installation and examine the alternatives--that its product may either be denied to the community at large, produced elsewhere or produced using existing facilities. These facilities are probably less efficient and may therefore produce more pollution per unit of product than the new plant would. An objective, quantitative, urban-air-pollution model is clearly an essential component in such a decision-making process. Dr. Benarie has produced a distillation of existing modelling techniques which will, I hope, become the launching pad for many future models. As each city is unique, it will need its own tailor-made model, drawing on the best and the most appropriate techniques developed previously. Agreement with observations is the only real test of validity, because the physics and chemistry are so complicated that theoretical arguments are reduced to the role of assisting in the best formulation of the problem. Numerical precision must always rely on measurement. This is the approach that Dr. Benarie has adopted.--David J. Moore, Central Electricity Research Laboratires, Leatherhead, Surrey, UK.

The U.S. Environmental Protection Agency is concerned about fine particulate matter (also called as PM2.5 as the average particle size is less than 2.5 μm) pollution and its ill effects on public health. About 80 percent of the mobile-source PM2.5 emissions are released into the urban atmosphere through combustion of diesel fuel by trucks and are composed of road dust, smoke, and liquid droplets. To estimate the regional or local air quality impact of PM2.5 emissions and also to predict future PM2.5 concentrations, we often utilize atmospheric dispersion models. Application of such sophisticated dispersion models with finer details can provide us the comprehensive understanding of the air quality problem, including the quantitative effect of pollution sources. However, in the current practice the detailed truck specific pollution estimation is not easily possible due to unavailability of a modeling methodology with applied supporting data to predict the link-level hourly truck activity and corresponding emission inventory. In the first part of this dissertation, we have proposed a methodology for estimating the disaggregated link-level hourly truck activity based on advanced statistics in light of the AERMOD based dispersion/pollution modeling process. This new proposed truck model consists of following sub models: (a) The Spatial Regression and Optimization based Truck-demand (SROT) model is developed to predict truck travel demand matrices using the spatial regression model-output truck volumes at control locations in the study area. (b) The hourly distribution factor model to convert daily truck volumes to hourly truck volumes (c) The Highway Capacity Manual (HCM) based highway assignment model for assigning the hourly truck travel demand matrices. In the second part of dissertation, we have utilized the link-level hourly truck activity to predict the typical 24-hour and maximum 1-hr PM2.5 pollution in urban atmosphere. In this AERMOD based dispersion/pollution modeling process, the gridded hourly emission inventories are estimated based on bottom-up approach using link-level hourly truck activity and emission factors from MOVES model. The proposed framework is tested using the data for the Cincinnati urban area and for four different seasonal weekdays in the analysis year 2010. The comparison with default results has revealed that the proposed models anticipate higher PM2.5 emission contribution from the heavy duty trucks. The innovation of the current research will be reflective of the following aspects: (a) An enhanced comprehensive truck-related PM2.5 pollution modeling approach and also consistent estimation of heavy-duty trucks apportionment in urban air quality (b) More reliable estimation of spatial and temporal truck activity which takes care of peak hour congestion through application of advanced modeling techniques (c) The gridded emission inventory is better estimated as detailed truck activity and emission rates are used as part of the bottom-up approach (d) Better ground-truth prediction of PM2.5 hot-spots in the modeling area (e) A transferable methodology that can be useful in other regions in the Unites States.

Urban Transportation and Air Pollution synthesizes state-of-the-art methods on estimating near-road concentrations of roadway emissions. The book provides the information needed to make estimates using methods based on a minimal set of model inputs that can be applied by a wide range of users in many situations. Discussions include methods to estimate traffic emission under numerous urban driving conditions, the uncertainty of emission models, and the effects of road configurations, such as near-road solid barriers. Final sections present dispersion models that link traffic emissions with near road concentrations in urban environments. Addressing transportation-related environmental issues is extremely important as urban areas are constantly searching for ways to mitigate impacts from transportation sources. This book helps to explain dispersion models, a critical tool for estimating the impact of roadway emissions in cities. - Compiles and synthesizes the state-of-the-science methods for estimating roadway emissions - Demonstrates, with clear examples, how modeling methods reduce uncertainties in real-world problems - Emphasizes how local-scale, semi-empirical, steady-state modeling can be applied using only a small set of inputs - Offers an overview of the meteorology that governs air pollution dispersion in cities