Differential sensitivities of electricity consumption to global warming across regions of Argentina

The description of the relationship between temperature [T] and electricity consumption [EC)] is key to improving our understanding of a potential climate change amplification feedback and, thus, energy planning. We sought to characterize the relationship between the EC and daily T of different regi...

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Detalles Bibliográficos
Otros Autores: Propato, Tamara Sofía, Abelleyra, Diego de, Semmartin, María, Verón, Santiago Ramón
Formato: Artículo
Lenguaje:Inglés
Materias:
ARGENTINA
SHAPE
THRESHOLD TEMPERATURE
WARM TEMPERATURE REGIMES
COOL TEMPERATURE REGIMES
TIME SERIES ANALYSIS
TEMPERATURE SCENARIOS
Acceso en línea:http://ri.agro.uba.ar/files/intranet/articulo/2021propato.pdf
LINK AL EDITOR
Aporte de:Registro referencial: Solicitar el recurso aquí
Biblioteca Central (FAUBA) de Universidad de Buenos Aires
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245 0 0 |a Differential sensitivities of electricity consumption to global warming across regions of Argentina 
520 |a The description of the relationship between temperature [T] and electricity consumption [EC)] is key to improving our understanding of a potential climate change amplification feedback and, thus, energy planning. We sought to characterize the relationship between the EC and daily T of different regions of Argentina and use these historical relationships to estimate expected EC under T future scenarios. We used a time series approach to model EC, removing trends and seasonality and accounting for breaks and discontinuities. EC and T data were obtained from Argentine Wholesale Market Administrator Company and global databases, respectively. We evaluate the T-EC model for the period between 1997 and 2014 and two sub-periods: 1997-2001 and 2011-2014. We use modeled temperature projections for the 2027-2044 period based on the Representative Pathway Concentration 4.5 together with our region-specific T-EC models to predict changes in EC due to T changes. The shape of the T-EC relationships is quite stable between periods and regions but varies according to the temperature gradient. We find large increases in EC in warm days (from 40 to 126 Wh/cap/°C) and a region-specific response to cold days [from flat to steep responses]. The T at which EC was at minimum varies between 14 and 20 °C and increase in time as mean daily T also increase. Estimated temperature projections translate into an average increase factor of 7.2 in EC with contrasting relative importance between regions of Argentina. Results highlight potential sensitivity of EC to T in the developing countries. 
650 4 |2 Agrovoc  |9 26 
651 4 |a ARGENTINA  |9 74592 
653 |a SHAPE 
653 |a THRESHOLD TEMPERATURE 
653 |a WARM TEMPERATURE REGIMES 
653 |a COOL TEMPERATURE REGIMES 
653 |a TIME SERIES ANALYSIS 
653 |a TEMPERATURE SCENARIOS 
700 1 |a Propato, Tamara Sofía  |u Instituto Nacional de Tecnología Agropecuaria (INTA). Centro de Investigación de Recursos Naturales (CIRN). Instituto de Clima y Agua. Castelar - Hurlingham, Buenos Aires, Argentina.  |u CONICET. Buenos Aires, Argentina.  |u Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Métodos Cuantitativos y Sistemas de Información. Buenos Aires, Argentina.  |9 37861 
700 1 |a Abelleyra, Diego de  |u Instituto Nacional de Tecnología Agropecuaria (INTA). Centro de Investigación de Recursos Naturales (CIRN). Instituto de Clima y Agua. Castelar - Hurlingham, Buenos Aires, Argentina.  |u Universidad de Buenos Aires. Facultad de Agronomía. Escuela para Graduados. Buenos Aires, Argentina.  |9 11479 
700 1 |a Semmartin, María  |u CONICET. Buenos Aires, Argentina.  |u Universidad de Buenos Aires. Facultad de Agronomía. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura (IFEVA). Buenos Aires, Argentina.  |u CONICET – Universidad de Buenos Aires. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura (IFEVA). Buenos Aires, Argentina.  |9 7454 
700 1 |a Verón, Santiago Ramón  |u Instituto Nacional de Tecnología Agropecuaria (INTA). Centro de Investigación de Recursos Naturales (CIRN). Instituto de Clima y Agua. Castelar - Hurlingham, Buenos Aires, Argentina.  |u CONICET. Buenos Aires, Argentina.  |u Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Métodos Cuantitativos y Sistemas de Información. Buenos Aires, Argentina.  |9 11455 
773 |t Climatic Change  |g Vol.166, no.1-2 (2021), art.25, 18 p., tbls., grafs., mapas 
856 |q application/pdf  |f 2021propato  |i En reservorio  |u http://ri.agro.uba.ar/files/intranet/articulo/2021propato.pdf  |x ARTI202311 
856 |u http://www.springer.com/  |z LINK AL EDITOR 
942 |c ARTICULO 
942 |c ENLINEA 
976 |a AAG 

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