Development of an odor management plan for industrial stationary sources in an urban environment: A case study for Broward County, Florida

Objectionable odors remain at the top of air pollution complaints in urban areas such as Broward County that is subject to increasing residential and industrial developments. The odor complaints in Broward County escalated by 150 percent for the 2001 to 2004 period although the population increased by only 6 percent. It is estimated that in 2010 the population will increase to 2.5 million. Relying solely on enforcing the local odor ordinance is evidently not sufficient to manage the escalating odor complaint trends. An alternate approach similar to odor management plans (OMPs) that are successful in managing major malodor sources such as animal farms is required. ^ This study aims to develop and determine the feasibility of implementing a comprehensive odor management plan (COMP) for the entire Broward County. Unlike existing OMPs for single sources where the receptors (i.e. the complainants) are located beyond the boundary of the source, the COMP addresses a complex model of multiple sources and receptors coexisting within the boundary of the entire county. Each receptor is potentially subjected to malodor emissions from multiple sources within the county. Also, the quantity and quality of the source/receptor variables are continuously changing. ^ The results of this study show that it is feasible to develop a COMP that adopts a systematic procedure to: (1) Generate maps of existing odor complaint areas and malodor sources, (2) Identify potential odor sources (target sources) responsible for existing odor complaints, (3) Identify possible odor control strategies for target sources, (4) Determine the criteria for implementing odor control strategies, (5) Develop an odor complaint response protocol, and (6) Conduct odor impact analyses for new sources to prevent future odor related issues. Geographic Information System (GIS) is used to identify existing complaint areas. A COMP software that incorporates existing United States Environmental Protection Agency (EPA) air dispersion software is developed to determine the target sources, predict the likelihood of new complaints, and conduct odor impact analysis. The odor response protocol requires pre-planning field investigations and conducting surveys to optimize the local agency available resources while protecting the citizen's welfare, as required by the Clean Air Act. ^

Best Management Practices in Green Lodging Defined and Explained

Best management practices in green lodging are sustainable or “green” business strategies designed to enhance the lodging product from the perspective of owners, operators and guests. For guests, these practices should enhance their experience while for owners and operators, generate positive returns on investments. Best management practices in green lodging typically starts with a clear understanding of each lodging firm’s role in society, its impact on the environment and strategies developed to mitigate negative environmental externalities generated from the production of lodging goods and services. Negative externalities of hotel operations manifest themselves in energy and water usage, waste generation and air pollution. Hence, best management practices in green lodging are dynamic, cost effective, innovative, stakeholder driven and environmentally sound technical and behavioral solutions that attempt to ameliorate or eliminate the negative environmental externalities associated with lodging operations, while simultaneously generate positive returns on green investments. Thus, best management practices in green lodging should reduce lodging firms’ operating costs, increase guest satisfaction, reduce or eliminate the negative environmental impacts associated with hotel operations while simultaneously enhance business operations.

Best Management Practices in Green Lodging Defined and Explained

Best management practices in green lodging are sustainable or “green” business strategies designed to enhance the lodging product from the perspective of owners, operators and guests. For guests, these practices should enhance their experience while for owners and operators, generate positive returns on investments. Best management practices in green lodging typically starts with a clear understanding of each lodging firm’s role in society, its impact on the environment and strategies developed to mitigate negative environmental externalities generated from the production of lodging goods and services. Negative externalities of hotel operations manifest themselves in energy and water usage, waste generation and air pollution. Hence, best management practices in green lodging are dynamic, cost effective, innovative, stakeholder driven and environmentally sound technical and behavioral solutions that attempt to ameliorate or eliminate the negative environmental externalities associated with lodging operations, while simultaneously generate positive returns on green investments. Thus, best management practices in green lodging should reduce lodging firms’ operating costs, increase guest satisfaction, reduce or eliminate the negative environmental impacts associated with hotel operations while simultaneously enhance business operations.

Trends in Water Quality within the Broward County Portion of the Biscayne Aquifer

Continuous and reliable monitoring of contaminants in drinking water, which adversely affect human health, is the main goal of the Broward County Well Field Protection Program. In this study the individual monitoring station locations were used in a yearly and quarterly spatiotemporal Ordinary Kriging interpolation to create a raster network of contaminant detections. In the final analysis, the raster spatiotemporal nitrate concentration trends were overlaid with a pollution vulnerability index to determine if the concentrations are influenced by a set of independent variables. The pollution vulnerability factors are depth to water, recharge, aquifer media, soil, impact to vadose zone, and conductivity. The creation of the nitrate raster dataset had an average RMS Standardized error close to 1 at 0.98. The greatest frequency of detections and the highest concentrations are found in the months of April, May, June, July, August, and September. An average of 76.4% of the nitrate intersected with cells of the pollution vulnerability index over 100.