Browsing by Subject "Air pollution"
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Item Intercomparison of Mixing Layer Heights from the National Weather Service Ceilometer Test Sites and Collocated Radiosondes(American Meteorological Society, 2019-01-21) Hicks, Micheal; Demoz, Belay; Vermeesch, Kevin; Atkinson, DennisA network of automated weather stations (AWS) with ceilometers can be used to detect sky conditions, aerosol dispersion, and mixing layer heights, in addition to the routine surface meteorological parameters (temperature, pressure, humidity, etc.). Currently, a dense network of AWSs that observe all of these parameters does not exist in the United States even though networks of them with ceilometers exist. These networks normally use ceilometers for determining only sky conditions. Updating AWS networks to obtain those nonstandard observations with ceilometers, especially mixing layer height, across the United States would provide valuable information for validating and improving weather/climate forecast models. In this respect, an aerosol-based mixing layer height detection method, called the combined-hybrid method, is developed and evaluated for its uncertainty characteristics for application in the United States. Four years of ceilometer data from the National Weather Service Ceilometer Proof of Concept Project taken in temperate, maritime polar, and hot/arid climate regimes are utilized in this evaluation. Overall, the method proved to be a strong candidate for estimating mixing layer heights with ceilometer data, with averaged uncertainties of 237 ± 398 m in all tested climate regimes and 69 ± 250 m when excluding the hot/arid climate regime.Item Using Spiderwebs to Detect Spatial Differences in Metal Air Pollution(2021-01-01) Rastegar, Nava; Hawn, Chris; Mahmoudi, Dillon; Geography and Environmental Systems; Geography and Environmental SystemsLong term studies of air pollution have been limited to stationary monitoring conducted by government bodies or large research institutions. These official monitoring sites can only measure a limited area, and the data they collect is then spatially generalized. This leads to large gaps in knowledge, as air pollution can vary significantly over small areas. This spatial gap has led to air pollution becoming a major area of study for public science efforts. The development of small, low-cost air monitors has enabled individuals and communities to examine their own exposure at a fine scale and become better informed on their own health risks. However, no low-cost sensors yet exist for the measurement o heavy metals, so despite their known negative impact on health, heavy metals have rarely been a focus of study for informal monitoring. There is a need for low-cost air quality monitoring that can detect differences at fine-scale and over long periods of time. Spiderwebs have been used in several studies to test air quality, but never in a public science setting and not yet at the fine spatial scale this study proposes. Furthermore, their results have only been verified by brief comonitoring, rather than long-term air pollution monitoring and modeling. This study collected spiderwebs to detect heavy metal air pollution in two neighborhoods of Southwest Baltimore, an area with a history of air pollution and known heavy metal releasing facilities, along with one of the highest levels of respiratory illnesses in the city and state. Webs were also collected near the two chemical speciation monitors operated by Maryland Department of the Environment. These webs were then analyzed for metal concentration using an ICP-MS. Spiderwebs collected in Southwest Baltimore were able to detect fine scale spatial differences in metal pollution, but the relationship between these values and known sources of air pollution are still unclear.