Air Pollution in 88 US Metropolitan Areas : Trends and Persistence

This paper analyses trends and persistence in air pollution levels in 88 US metropolitan areas using fractional integration methods. The results indicate that the differencing parameter d is higher than 0 in 38 of the series, which supports the hypothesis of long-memory behavior and implies that, al...

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Detalles Bibliográficos
Autores: Caporale, Guglielmo Maria, Carmona-González, Nieves, Carmona González, Nieves, Gil-Alana, Luis Alberiko, Gil Alana, Luis A., Romero-Rojo, María Fátima, Romero Rojo, María Fátima
Tipo de recurso: artículo
Fecha de publicación:2026
País:España
Institución:Universidad Francisco de Vitoria
Repositorio:DDFV. Repositorio Institucional de la Universidad Francisco de Vitoria
Idioma:inglés
OAI Identifier:oai:ddfv.ufv.es:10641/7858
Acceso en línea:https://hdl.handle.net/10641/7858
Access Level:acceso abierto
Palabra clave:air quality
fractional integration
long memory
seasonality
time trends
Fractional integration
Seasonality
Air quality
Time trends
Long memory
Environmental Science (miscellaneous)
Atmospheric Science
SDG 11 - Sustainable Cities and Communities
Descripción
Sumario:This paper analyses trends and persistence in air pollution levels in 88 US metropolitan areas using fractional integration methods. The results indicate that the differencing parameter d is higher than 0 in 38 of the series, which supports the hypothesis of long-memory behavior and implies that, although the effects of shocks are long-lived, they eventually die out. The highest degrees of persistence are found in the Fresno, Bakersfield, Bradenton and San Diego areas. On the whole, the gathered evidence indicates that regional differences in pollution levels are significant, with factors such as industrialisation history and extreme weather events playing a crucial role in their degree of persistence. This suggests that, in order to tackle pollution more effectively, federal environmental policies, such as the Clean Air Act, should be complemented by more targeted ones taking into account local characteristics.