Sources of the seasonal-trend behaviour and periodicity modulation of 7Be air concentration in the atmospheric surface layer observed in southeastern Spain

Chham, E.; Milena-Pérez, A.; Piñero-García, F.; Hernández-Ceballos, M.A.; Orza, J.A.G.; Brattich, Erika; Bardouni, T. El; Ferro-Garcı́a, M.A.

doi:10.1016/j.atmosenv.2019.06.011

Cited by 14 publications

(12 citation statements)

References 56 publications

(70 reference statements)

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“…The activity concentrations of 7 Be in the aerosols samples range from 7.3 to 0.35 mBq/m 3 , with a mean of 3.20 ± 1.12 mBq/m 3 , where the uncertainty is given as the sample standard deviation. This mean value coincides with the one presented in a previous study in Bilbao, 3.02 ± 1.02 mBq/m 3 [22] and is coherent with those provided at similar latitudes, such as Granada (4.86 mBq/m 3 ) [28], Lisbon (4.0 ± 2.0 mBq/m 3 ) [15].…”

Section: Be Time Series Characterizationsupporting

confidence: 92%

“…During the 10 years analyzed in the present study, weekly 7 Be activity concentrations exhibited large variability (Figure 3a). In previous studies [28], this strong variability is partially explained by The analysis of 7 Be activity data on a monthly basis (Figure 7b) helps to understand the differences between seasons. On average, the 7 Be concentration leaps in January and remains high until September, with a maximum in February and a secondary maximum during the months of July-August.…”

Section: Be Time Series Characterizationmentioning

confidence: 72%

“…During the 10 years analyzed in the present study, weekly 7 Be activity concentrations exhibited large variability (Figure 3a). In previous studies [28], this strong variability is partially explained by variations in atmospheric parameters, such as temperature, relative humidity, and precipitation. In the present analysis, to better understand the impact of these meteorological parameters on 7 Be activity concentrations, they have been grouped into six ranges, according to the boxplot graph presented in Figure 8a.…”

Section: Be Activity Concentrations and Their Correlation With Locamentioning

confidence: 83%

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Meteorological Factors Controlling 7Be Activity Concentrations in the Atmospheric Surface Layer in Northern Spain

et al. 2020

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This work presents the analysis of weekly 7Be activity concentrations in the air measured in Bilbao (northern Spain) by collecting aerosols in filters over a ten years period (2009–2018). 7Be level is in the 0.35–7.3 mBq/m3 range, with a mean of 3.20 ± 1.12 mBq/m3. The trend, cycle, seasonal and monthly variability are evaluated using time series analysis techniques. The results indicate the impact of sunspots (24th solar cycle) on interannual 7Be activity concentrations, and a significant seasonal and monthly variation, with maximum concentrations occurring in spring-summer and minimum in the winter. The correlation of different 7Be ranges with local meteorological parameters, such as precipitation, temperature, relative humidity, and pressure, is also addressed, with precipitation having the greatest impact on 7Be activity values. The analysis of synoptic airflows, by calculating the back-trajectory clusters, and local winds at surface level reveals the important influence of the arrival of slow northwest Atlantic flows and the development of breezes on reaching high 7Be activity concentrations in this area.

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Section: Be Time Series Characterizationsupporting

confidence: 92%

Section: Be Time Series Characterizationmentioning

confidence: 72%

“…During the 10 years analyzed in the present study, weekly 7 Be activity concentrations exhibited large variability (Figure 3a). In previous studies [28], this strong variability is partially explained by variations in atmospheric parameters, such as temperature, relative humidity, and precipitation. In the present analysis, to better understand the impact of these meteorological parameters on 7 Be activity concentrations, they have been grouped into six ranges, according to the boxplot graph presented in Figure 8a.…”

Section: Be Activity Concentrations and Their Correlation With Locamentioning

confidence: 83%

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Meteorological Factors Controlling 7Be Activity Concentrations in the Atmospheric Surface Layer in Northern Spain

et al. 2020

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“…To assess the quality of the used data, some traditional tests were used. Observations indicated that in the majority of studies (Chham et al 2019;Do and Cetin 2018;Shen et al 2011), Grubbs test (Grubbs and Beck 1972) was used to detect outliers in the time series. This test was hence selected for this purpose.…”

Section: Data Quality Controlmentioning

confidence: 99%

Spatio-Temporal Analysis of Heating and Cooling Degree-Days Over Iran

Sadeqi

Tabari

Dinpashoh

2021

Preprint

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Climate change affects the energy demand in different sectors of the society. To investigate this possible impact, in this research, temporal trends and change points in heating degree-days (HDD), cooling degree-days (CDD), and their simultaneous combination (HDD+CDD) were analysed for a 60-year period (1960-2019) in Iran. The results show that less than 20% of the study stations had significant trends (either upward or downward) in HDD time series, while more than 80% of the stations had significant increasing trends in CDD and HDD+CDD time series. Abrupt changes in HDD time series mostly occurred in the early 1980s, but those in CDD time series were mostly observed in the 1990s. The cooling energy demand in Iran has dramatically increased as CDD values have raised up from 690 ºC-days to 1010 ºC-days in the last 60 years. HDD, however, almost remained constant in the same period. The results suggest that if global warming continues with the current pace, cooling energy demand in the residential sector will considerably increase in the future, calling for a change in residential energy consumption policies.

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“…A time series is basically made up of three different components; namely the trend, the seasonal component, and the random error. Generally, a time series (Yt) is expressed as follows (Bianchi et al, 2019;Chham et al, 2019;Fan et al, 2003):…”

Section: Time Seriesmentioning

confidence: 99%

Analysis of CO2 and CH4 temporal patterns and the Valladolid urban plume influence over the upper Spanish plateau

Duque¹

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1.2. Resumen 5 2. Introduction 9 2.1. An overview 9 2.2. CO2 2.3. CH4 2.4. The importance of accurate CO2 and CH4 mixing ratio measurements 2.5. CIBA station characteristics 2.6. Time series 2.7. Valladolid urban plume analysis 2.8. Motivation of the study 3. Objectives 3.1. General objective 3.2. Specific objectives 4. Material and methods 4.1. Site description 4.2. Monitoring station 4.3. Instrumentation 4.4. Database 4.5. Software employed 4.6. Mathematical equations used 4.7. Statistical techniques 4.8. Graphical summary techniques 4.9. Validation methods 5. List of Original Contributions 6. Original Contributions 6.1. Harmonic function for describing CO2 and CH4 temporal patterns: Original Contribution I 6.2. Kernel functions for describing CO2 and CH4 temporal patterns: Original Contribution II 6.3. Local regression functions for describing CO2 and CH4 temporal patterns: Original Contribution III 101 6.4. Valladolid urban plume influence on the final CO2 and CH4 mixing ratios at CIBA: Original Contribution IV 115 7. General results 133 7.1. CO2 and CH4 temporal analysis 133 7.2. Back-trajectory analysis 136 II 7.3. Validation indicators 8. General discussion 8.1. Temporal pattern evolution 8.2. Mathematical equations for analysing temporal patterns 8.3. Valladolid urban plume analysis 9. Conclusions / Conclusiones 9.1. Conclusions 9.2. Conclusiones 10. References 11. Appendices 11.1. Acronyms 11.2. List of tables and figures 2.1.1.1. The Intergovernmental Panel on Climate Change (IPCC) In 1988 the World Meteorological Organization (WMO) and the United Nations EnvironmentProgram (UNEP) created the Intergovernmental Panel on Climate Change (IPCC) to analyse the problem of global climate change. The IPCC is a group open to all members of the United Nations and WMO (IPCC, 2020a). The function of the IPCC is not to conduct its own research but to analyse, in a comprehensive, objective, open and transparent way, the relevant scientific, technical and socioeconomic information required to understand the scientific elements involved in climate change caused by human activities, its possible repercussions and the possibilities of attenuation and/or adaptation (IPCC, 2020a). In addition, through their evaluations, the IPCC seeks to identify the strength of scientific agreement in different areas and indicates where further research is needed. The IPCC is made up of three different working In 2015, the 21 st Conference of the Parties (COP 21) of the United Nations Framework on Climate Change (UNFCCC) took place in Paris, ending with the adoption of the Paris Agreement by the 195 UNFCCC countries (Boffino et al., 2019). The Paris Agreement establishes the global framework for combating climate change from 2020, promoting a transition towards a low-emission economy in the fight against climate change (Boffino et al., 2019; Pauw et al., 2019). This agreement establishes a plan to reduce emissions of CO2 and other greenhouse gases, aiming to keep global temperature increases to below 2ºC relative to 2.3.1. The CH4 cycle A...

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Sources of the seasonal-trend behaviour and periodicity modulation of 7Be air concentration in the atmospheric surface layer observed in southeastern Spain

Cited by 14 publications

References 56 publications

Meteorological Factors Controlling 7Be Activity Concentrations in the Atmospheric Surface Layer in Northern Spain

Meteorological Factors Controlling 7Be Activity Concentrations in the Atmospheric Surface Layer in Northern Spain

Spatio-Temporal Analysis of Heating and Cooling Degree-Days Over Iran

Analysis of CO2 and CH4 temporal patterns and the Valladolid urban plume influence over the upper Spanish plateau

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