The purpose of this thesis was to develop meteorological criteria for forecasting air quality for individual air monitoring locations across the state of New Hampshire. Daily 1-hour ozone and 24-hour averaged PM2.5 data were obtained from the New Hampshire Department of Environmental Services for nine air monitoring stations for the years 2002 to 2005. Three methods (the climatology, criteria, and linear regression methods as described by the EPA’s (Environmental Protection Agency) Guidelines for Developing an Air Quality (Ozone and PM2.5) Forecasting Program document) were used to develop a four year climatology, criteria table, and linear regression equations for each station and pollutant. Surface observations were retrieved from the Plymouth State University Weather Center archived meteograms. Several meteorological variables were used to explore their individual influence on ozone and PM2.5 concentrations for each monitoring site. Ozone and PM2.5 threshold values of 65 ppb and 15.5 μg/m3 were used (corresponding to the EPA’s "Moderate" category on the Air Quality Index). Meteorological variables were analyzed for values that would cause the pollutants to exceed their threshold concentrations. Criteria tables were created using the meteorological variables and the resulting values of those variables which would cause the pollutant concentration to exceed its threshold value. Linear regression equations were also generated to demonstrate relationships between meteorological variable values and pollutant concentrations. The criteria table and linear regression equations were tested on one station using data from the summer of 2006. The criteria tables and linear regression equations adequately performed in forecasting whether or not a pollutant would exceed its threshold value. Maximum surface temperature, 850 hPa temperature, 1800 UTC relative humidity and wind direction (1200 UTC and 1800 UTC) were found to perform the best for ozone. Maximum surface temperature, 850 hPa temperature, dewpoint temperature and wind direction (1200 UTC and 1800 UTC) performed the best for summer PM2.5. Many similarities and differences were found between the several stations for both pollutants. Location and meteorological conditions were shown to be influential factors in air quality forecasting for New Hampshire.