000119599 001__ 119599 000119599 005__ 20240319080951.0 000119599 0247_ $$2doi$$a10.1016/j.physa.2021.126550 000119599 0248_ $$2sideral$$a127887 000119599 037__ $$aART-2022-127887 000119599 041__ $$aeng 000119599 100__ $$0(orcid)0000-0002-8816-5816$$aPeña, G.$$uUniversidad de Zaragoza 000119599 245__ $$aLog-growth rates of CO2: an empirical analysis 000119599 260__ $$c2022 000119599 5060_ $$aAccess copy available to the general public$$fUnrestricted 000119599 5203_ $$aWe study the parametric distribution of log-growth rates of CO2 and CO2 per capita emissions for 207 countries and territories taking data from 1994 to 2010. We define the log-growth rates for different duration periods, from one year apart to fifteen years apart. The considered probability distributions have been the following: the normal (N), the asymmetric double Laplace normal (adLN), the exponential tails normal (ETN) and a mixture of two normal (2N) or three normal (3N) distributions. The main result is that the best one is different depending on the period considered, in such a way that there is not a systematically dominant distribution. Thus, the behavior may change from one year to the next one, and possibly this is influenced by policy measures such as the Kyoto protocol or the Clean Development Mechanism. Moreover, a policy measure that can be derived from this paper is that some countries can still reduce their emissions of CO2 compared with others, as seen by the non-uniformity of the preferred probability distribution for each period. We also model a stochastic differential equation whose associated Fokker–Planck equation has as a solution the observed time-dependent probability density function. 000119599 536__ $$9info:eu-repo/grantAgreement/ES/AEI/PID2020-112773GB-I00$$9info:eu-repo/grantAgreement/ES/DGA/S39-20R 000119599 540__ $$9info:eu-repo/semantics/openAccess$$aby-nc-nd$$uhttp://creativecommons.org/licenses/by-nc-nd/3.0/es/ 000119599 590__ $$a3.3$$b2022 000119599 591__ $$aPHYSICS, MULTIDISCIPLINARY$$b31 / 85 = 0.365$$c2022$$dQ2$$eT2 000119599 594__ $$a7.5$$b2022 000119599 592__ $$a0.699$$b2022 000119599 593__ $$aCondensed Matter Physics$$c2022$$dQ2 000119599 593__ $$aStatistics and Probability$$c2022$$dQ2 000119599 593__ $$aStatistical and Nonlinear Physics$$c2022$$dQ2 000119599 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/acceptedVersion 000119599 700__ $$0(orcid)0000-0001-9728-668X$$aPuente-Ajovín, M.$$uUniversidad de Zaragoza 000119599 700__ $$0(orcid)0000-0003-2618-1535$$aRamos, A.$$uUniversidad de Zaragoza 000119599 700__ $$0(orcid)0000-0003-3725-0022$$aSanz-Gracia, F.$$uUniversidad de Zaragoza 000119599 7102_ $$14000$$2415$$aUniversidad de Zaragoza$$bDpto. Análisis Económico$$cÁrea Fund. Análisis Económico 000119599 773__ $$g588 (2022), 126550 [15 pp.]$$pPhysica, A$$tPhysica A: Statistical Mechanics and its Applications$$x0378-4371 000119599 8564_ $$s437994$$uhttps://zaguan.unizar.es/record/119599/files/texto_completo.pdf$$yPostprint 000119599 8564_ $$s2030022$$uhttps://zaguan.unizar.es/record/119599/files/texto_completo.jpg?subformat=icon$$xicon$$yPostprint 000119599 909CO $$ooai:zaguan.unizar.es:119599$$particulos$$pdriver 000119599 951__ $$a2024-03-18-13:07:53 000119599 980__ $$aARTICLE