In this study, artificial neural networks (ANNs) and adaptive neuro-fuzzy inference system (ANFIS) were used to estimate shear stress distribution in streams. The methods were applied to the 145 field data gauged from four different sites on the Sarimsakli and Sosun streams in Turkey. The accuracy of the applied models was compared with the multiple-linear regression (MLR). The results showed that the ANNs and ANFIS models performed better than the MLR model in modeling shear stress distribution. The root mean square errors (RMSE) and mean absolute errors (MAE) of the MLR model were reduced by 47% and 50% using ANFIS model in estimating shear stress distribution in the test period, respectively. It is found that the best ANFIS model with RMSE of 3.85, MAE of 2.85 and determination coefficient (R2) of 0.921 in test period is superior to the MLR model with RMSE of 7.30, MAE of 5.75 and R2 of 0.794 in estimation of shear stress distribution, respectively.
{"title":"Modeling shear stress distribution in natural small streams by soft computing methods","authors":"Onur Genç, O. Kisi, M. Ardiclioglu","doi":"10.15233/GFZ.2016.33.11","DOIUrl":"https://doi.org/10.15233/GFZ.2016.33.11","url":null,"abstract":"In this study, artificial neural networks (ANNs) and adaptive neuro-fuzzy inference system (ANFIS) were used to estimate shear stress distribution in streams. The methods were applied to the 145 field data gauged from four different sites on the Sarimsakli and Sosun streams in Turkey. The accuracy of the applied models was compared with the multiple-linear regression (MLR). The results showed that the ANNs and ANFIS models performed better than the MLR model in modeling shear stress distribution. The root mean square errors (RMSE) and mean absolute errors (MAE) of the MLR model were reduced by 47% and 50% using ANFIS model in estimating shear stress distribution in the test period, respectively. It is found that the best ANFIS model with RMSE of 3.85, MAE of 2.85 and determination coefficient (R2) of 0.921 in test period is superior to the MLR model with RMSE of 7.30, MAE of 5.75 and R2 of 0.794 in estimation of shear stress distribution, respectively.","PeriodicalId":50419,"journal":{"name":"Geofizika","volume":"33 1","pages":"137-156"},"PeriodicalIF":1.0,"publicationDate":"2016-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67352422","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"In Memory of Prof. Dr. Dragan Hadžievski","authors":"D. Herak, M. Herak","doi":"10.15233/GFZ.2016.33.2","DOIUrl":"https://doi.org/10.15233/GFZ.2016.33.2","url":null,"abstract":"","PeriodicalId":50419,"journal":{"name":"Geofizika","volume":"33 1","pages":"113-114"},"PeriodicalIF":1.0,"publicationDate":"2016-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67352521","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The seismic radiation patterns associated with probing the earth’s subsurface are essentially anisotropic due to its ubiquitous stratified structure. This anisotropy seriously complicates formation imaging and data acquisition. This is most salient for deep-water subsalt reservoirs. Traditionally, point scatterers with isotropic radiation patterns are used in migration imaging, but in the survey design problem, these might lead to design errors caused by receivers being placed in poor locations with respect to the radiation pattern of the scattering structure. Here, we extend a framework which accounts for anisotropy in the scattered radiation for optimal geophysical survey design purposes. The propagation medium is assumed to be attenuative. The locally dipping interfaces are modeled as a discrete set of finite-size planar scattering elements. The general elastodynamic expressions for the sensitivity kernels, i.e., the vectors which mathematically represent the candidate observations, in the presence of the scattering elements are provided. The size of each element controls the width of its radiation pattern, which may in turn be used to characterize the uncertainty on the dip angle, thus complementing the information provided by the model-parameter uncertainties and ultimately leading to better geophysical survey designs.
{"title":"Accounting for seismic radiation anisotropy in Bayesian survey designs","authors":"M. Khodja, M. Prange, H. Djikpesse","doi":"10.15233/GFZ.2016.33.1","DOIUrl":"https://doi.org/10.15233/GFZ.2016.33.1","url":null,"abstract":"The seismic radiation patterns associated with probing the earth’s subsurface are essentially anisotropic due to its ubiquitous stratified structure. This anisotropy seriously complicates formation imaging and data acquisition. This is most salient for deep-water subsalt reservoirs. Traditionally, point scatterers with isotropic radiation patterns are used in migration imaging, but in the survey design problem, these might lead to design errors caused by receivers being placed in poor locations with respect to the radiation pattern of the scattering structure. Here, we extend a framework which accounts for anisotropy in the scattered radiation for optimal geophysical survey design purposes. The propagation medium is assumed to be attenuative. The locally dipping interfaces are modeled as a discrete set of finite-size planar scattering elements. The general elastodynamic expressions for the sensitivity kernels, i.e., the vectors which mathematically represent the candidate observations, in the presence of the scattering elements are provided. The size of each element controls the width of its radiation pattern, which may in turn be used to characterize the uncertainty on the dip angle, thus complementing the information provided by the model-parameter uncertainties and ultimately leading to better geophysical survey designs.","PeriodicalId":50419,"journal":{"name":"Geofizika","volume":"33 1","pages":"79-99"},"PeriodicalIF":1.0,"publicationDate":"2016-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67352666","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
D. Mahalakshmi, A. Paul, D. Dutta, M. Ali, V. Dadhwal, R. S. Reddy, C. Jha, J. R. Sharma
In this study, net surface radiation (Rn) was estimated using artificial neural network (ANN) and Linear Model (LM). Then, estimated Rn with both the models (ANN and LM) were compared with measured Rn from eddy covariance (EC) flux tower. The routinely measured meteorological variables namely air temperature, relative humidity and wind velocity were used as input to the ANN and global solar radiation as input to the LM. All the input data are from the EC flux tower. Sensitivity analysis of ANN with all the meteorological variables is carried out by excluding one by one meteorological variable. The validation results demonstrated that, ANN and LM estimated Rn values were in good agreement with the measured values, with root mean square error (RMSE) varying between 21.63 W/m2 and 34.94 W/m2, mean absolute error (MAE) between 17.93 W/m2 and 22.28 W/m2 and coefficient of residual mass (CRM) between –0.007 and –0.04 respectively. Further we have computed modelling efficiency (0.97 for ANN and 0.99 for LM) and coefficient of determination (R2 = 0.97 for ANN and 0.99 for LM) for both the models. Even though both the models could predict Rn successfully, ANN was better in terms of minimum number of routinely measured meteorological variables as input. The results of the ANN sensitivity analysis indicated that air temperatuere is the more important parameter followed by relative humidity, wind speed and wind direction.
{"title":"Estimation of net surface radiation using eddy flux tower data over a tropical mangrove forest of Sundarban, West Bengal","authors":"D. Mahalakshmi, A. Paul, D. Dutta, M. Ali, V. Dadhwal, R. S. Reddy, C. Jha, J. R. Sharma","doi":"10.15233/GFZ.2016.33.5","DOIUrl":"https://doi.org/10.15233/GFZ.2016.33.5","url":null,"abstract":"In this study, net surface radiation (Rn) was estimated using artificial neural network (ANN) and Linear Model (LM). Then, estimated Rn with both the models (ANN and LM) were compared with measured Rn from eddy covariance (EC) flux tower. The routinely measured meteorological variables namely air temperature, relative humidity and wind velocity were used as input to the ANN and global solar radiation as input to the LM. All the input data are from the EC flux tower. Sensitivity analysis of ANN with all the meteorological variables is carried out by excluding one by one meteorological variable. The validation results demonstrated that, ANN and LM estimated Rn values were in good agreement with the measured values, with root mean square error (RMSE) varying between 21.63 W/m2 and 34.94 W/m2, mean absolute error (MAE) between 17.93 W/m2 and 22.28 W/m2 and coefficient of residual mass (CRM) between –0.007 and –0.04 respectively. Further we have computed modelling efficiency (0.97 for ANN and 0.99 for LM) and coefficient of determination (R2 = 0.97 for ANN and 0.99 for LM) for both the models. Even though both the models could predict Rn successfully, ANN was better in terms of minimum number of routinely measured meteorological variables as input. The results of the ANN sensitivity analysis indicated that air temperatuere is the more important parameter followed by relative humidity, wind speed and wind direction.","PeriodicalId":50419,"journal":{"name":"Geofizika","volume":"1 1","pages":"1-14"},"PeriodicalIF":1.0,"publicationDate":"2016-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67353042","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Height (altitude) determination in geodesy is faced with problems that are directly attributed to the method of measurements and used geoid solutions. Due to the reliability of CROPOS as well as growing progress in geoid determination (increase of their external and internal accuracy), GNSS observations using CROPOS_VRS_HTRS96 VPPS service became most commonly used method of height determination in Croatian every day geodetic practice. This paper describes establishment of 33 GNSS/levelling points using CROPOS_VRS_HTRS96 VPPS service and geometric levelling at the area of the City of Zagreb. It also gives the analysis of the quality of performed GNSS observations, analysis and comparison of the geoid undulations from official geoid solutions of the Republic of Croatia, HRG2000 and HRG2009 with undulations obtained by GNSS/levelling for established GNSS/levelling points and brief overview of current state of vertical network of the City of Zagreb.
{"title":"Accuracy validation of official Croatian geoid solutions over the area of City of Zagreb","authors":"Daria Dragčević, Marko Pavasović, Tomislav Bašić","doi":"10.15233/GFZ.2016.33.9","DOIUrl":"https://doi.org/10.15233/GFZ.2016.33.9","url":null,"abstract":"Height (altitude) determination in geodesy is faced with problems that are directly attributed to the method of measurements and used geoid solutions. Due to the reliability of CROPOS as well as growing progress in geoid determination (increase of their external and internal accuracy), GNSS observations using CROPOS_VRS_HTRS96 VPPS service became most commonly used method of height determination in Croatian every day geodetic practice. This paper describes establishment of 33 GNSS/levelling points using CROPOS_VRS_HTRS96 VPPS service and geometric levelling at the area of the City of Zagreb. It also gives the analysis of the quality of performed GNSS observations, analysis and comparison of the geoid undulations from official geoid solutions of the Republic of Croatia, HRG2000 and HRG2009 with undulations obtained by GNSS/levelling for established GNSS/levelling points and brief overview of current state of vertical network of the City of Zagreb.","PeriodicalId":50419,"journal":{"name":"Geofizika","volume":"33 1","pages":"183-206"},"PeriodicalIF":1.0,"publicationDate":"2016-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67353163","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Mehrdad Jeihouni, R. Delirhasannia, S. K. Alavipanah, M. Shahabi, S. Samadianfard
Artificial intelligence (AI) systems have opened a new horizon to analyze water engineering and environmental problems in recent decades. In this study performances of ordinary kriging (OK) as a linear geostatistical estimator and two intelligent methods including artificial neural networks (ANN) and adaptive neuro-fuzzy inference system (ANFIS) are investigated. For this purpose, geographical coordinates of 120 observation wells that located in Tabriz plain, north-west of Iran, were defined as inputs and groundwater electrical conductivities (EC) were set as output of models. Eighty percent of data were randomly selected to train and develop mentioned models and twenty percent of data used for testing and validating. Finally, the outputs of models were compared with the corresponding measured values in observation wells. Results indicated that ANFIS model provided the best accuracy among models with the root mean squared error (RMSE) value of 1.69 dS.m and correlation coefficient (R) of 0.84. The RMSE values in ANN and OK were calculated 1.97 and 2.14 dS.m and the R values were determined 0.79 and 0.76, respectively. According to the results, the ANFIS method predicted EC precisely and can be advised for modeling groundwater salinity.
{"title":"Spatial analysis of groundwater electrical conductivity using ordinary kriging and artificial intelligence methods (Case study: Tabriz plain, Iran)","authors":"Mehrdad Jeihouni, R. Delirhasannia, S. K. Alavipanah, M. Shahabi, S. Samadianfard","doi":"10.15233/GFZ.2015.32.9","DOIUrl":"https://doi.org/10.15233/GFZ.2015.32.9","url":null,"abstract":"Artificial intelligence (AI) systems have opened a new horizon to analyze water engineering and environmental problems in recent decades. In this study performances of ordinary kriging (OK) as a linear geostatistical estimator and two intelligent methods including artificial neural networks (ANN) and adaptive neuro-fuzzy inference system (ANFIS) are investigated. For this purpose, geographical coordinates of 120 observation wells that located in Tabriz plain, north-west of Iran, were defined as inputs and groundwater electrical conductivities (EC) were set as output of models. Eighty percent of data were randomly selected to train and develop mentioned models and twenty percent of data used for testing and validating. Finally, the outputs of models were compared with the corresponding measured values in observation wells. Results indicated that ANFIS model provided the best accuracy among models with the root mean squared error (RMSE) value of 1.69 dS.m and correlation coefficient (R) of 0.84. The RMSE values in ANN and OK were calculated 1.97 and 2.14 dS.m and the R values were determined 0.79 and 0.76, respectively. According to the results, the ANFIS method predicted EC precisely and can be advised for modeling groundwater salinity.","PeriodicalId":50419,"journal":{"name":"Geofizika","volume":"32 1","pages":"192-208"},"PeriodicalIF":1.0,"publicationDate":"2015-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.15233/GFZ.2015.32.9","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67352559","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
T. Kumar, D. Murugan, K. Rajalakshmi, T. I. Manish
This paper presents fast and effective filtering techniques for image enhancement from remote sensing Indian remote sensing satellite P6 Liss IV remotely sensed data like Near-Infrared band. There are four filtering techniques used for image enhancement based on spatial domain filters and frequency domain filters such as median filter, wiener filter, bilateral filter and Gaussian homomorphic filter and selected noises salt and pepper and Gaussian noise used with filter. Selected images tested with each filter and based on PSNR performance metric value and best filtering technique identified from these filters. Finally, Gaussian homomorphic filtering technique is suitable for image enhancement of the Liss IV remotely sensed Near-Infrared band. Image enhancement technique is preprocessing for future work such as edge detection and image segmentation.
{"title":"Image enhancement and performance evaluation using various filters for IRS-P6 Satellite Liss IV remotely sensed data","authors":"T. Kumar, D. Murugan, K. Rajalakshmi, T. I. Manish","doi":"10.15233/GFZ.2015.32.11","DOIUrl":"https://doi.org/10.15233/GFZ.2015.32.11","url":null,"abstract":"This paper presents fast and effective filtering techniques for image enhancement from remote sensing Indian remote sensing satellite P6 Liss IV remotely sensed data like Near-Infrared band. There are four filtering techniques used for image enhancement based on spatial domain filters and frequency domain filters such as median filter, wiener filter, bilateral filter and Gaussian homomorphic filter and selected noises salt and pepper and Gaussian noise used with filter. Selected images tested with each filter and based on PSNR performance metric value and best filtering technique identified from these filters. Finally, Gaussian homomorphic filtering technique is suitable for image enhancement of the Liss IV remotely sensed Near-Infrared band. Image enhancement technique is preprocessing for future work such as edge detection and image segmentation.","PeriodicalId":50419,"journal":{"name":"Geofizika","volume":"32 1","pages":"179-189"},"PeriodicalIF":1.0,"publicationDate":"2015-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67352162","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
On 20 March 2015, we lost a teacher, colleague and dear friend, Dr. Inga Lisac. Inga was born in Novi Marof, northern Croatia, on 13 December 1930, as the only child of a lawyer, Pavao Lisac, and a nurse and social worker, Vlasta (nee Sabljak). Her mother, Vlasta, descended from the respectable Fleischer family, which contributed to the cultural and educational life of the town of Bjelovar throughout the 19th and the early 20th century (Lisac, 2007).
{"title":"In Memory of Dr. Inga Lisac, the first Editor-in-Chief of Geofizika (Novi Marof, 1930 – Zagreb, 2015)","authors":"Z. Klaic","doi":"10.15233/GFZ.2015.32.8","DOIUrl":"https://doi.org/10.15233/GFZ.2015.32.8","url":null,"abstract":"On 20 March 2015, we lost a teacher, colleague and dear friend, Dr. Inga Lisac. Inga was born in Novi Marof, northern Croatia, on 13 December 1930, as the only child of a lawyer, Pavao Lisac, and a nurse and social worker, Vlasta (nee Sabljak). Her mother, Vlasta, descended from the respectable Fleischer family, which contributed to the cultural and educational life of the town of Bjelovar throughout the 19th and the early 20th century (Lisac, 2007).","PeriodicalId":50419,"journal":{"name":"Geofizika","volume":"32 1","pages":"265-278"},"PeriodicalIF":1.0,"publicationDate":"2015-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67352487","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Based on relative height displacement grid models of the Earth’s crust, related to the territory of the Croatia, Slovenia and Bosnia and Herzegovina, which were created by modelling of the benchmark height data contained in levelling networks of the Austrian precise levelling (APN), and First (INVT) and Second (IINVT) levelling of high accuracy, possibility of creation of uniformly accelerated or decelerated motion model and uniform motion model of Earth’s crust is analyzed. Kinematic laws of straight-line benchmark height motion has been applied to the values of Earth’s crust height displacements that are associated with the nodes in the grid models of relative height displacements created between explicit epochs APN and INVT, and APN and IINVT. This application enabled determination of motion kinematic parameters associated with the grid nodes. Kinematic parameter’s determination, structuring and including in a separate grid models, in analogy to the relative height displacement grid models, along with definition of basic kinematic equations of uniformly accelerated or decelerated motion and uniform motion of Earth’s crust, allowed for the territory of the Croatia, Slovenia and Bosnia and Herzegovina kinematic models creation.
{"title":"Kinematic models of recent motion of the Earth's crust on the territory of Croatia, Slovenia and Bosnia and Herzegovina","authors":"N. Rožić","doi":"10.15233/GFZ.2015.32.10","DOIUrl":"https://doi.org/10.15233/GFZ.2015.32.10","url":null,"abstract":"Based on relative height displacement grid models of the Earth’s crust, related to the territory of the Croatia, Slovenia and Bosnia and Herzegovina, which were created by modelling of the benchmark height data contained in levelling networks of the Austrian precise levelling (APN), and First (INVT) and Second (IINVT) levelling of high accuracy, possibility of creation of uniformly accelerated or decelerated motion model and uniform motion model of Earth’s crust is analyzed. Kinematic laws of straight-line benchmark height motion has been applied to the values of Earth’s crust height displacements that are associated with the nodes in the grid models of relative height displacements created between explicit epochs APN and INVT, and APN and IINVT. This application enabled determination of motion kinematic parameters associated with the grid nodes. Kinematic parameter’s determination, structuring and including in a separate grid models, in analogy to the relative height displacement grid models, along with definition of basic kinematic equations of uniformly accelerated or decelerated motion and uniform motion of Earth’s crust, allowed for the territory of the Croatia, Slovenia and Bosnia and Herzegovina kinematic models creation.","PeriodicalId":50419,"journal":{"name":"Geofizika","volume":"32 1","pages":"209-236"},"PeriodicalIF":1.0,"publicationDate":"2015-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67351692","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We investigated the relationship between wintertime 1-min mean urban indoor particulate matter mass concentrations for particles with aerodynamic diameter of < 1 μm (PM1) and outdoor atmospheric conditions. Particle concentrations were measured by two light-scattering laser photometers. Aerosol monitors were placed in the ground and first floor corridors of an university building, with inlets at heights of 1.7 m above the floor. The building is located in residential area of Zagreb, Croatia. During the experiment usual student and employee activities were occurring within the building. Surface meteorological data were collected at a nearby outdoor location. Results show the dependence of indoor PM1 on outdoor meteorology, with the strongest responses to air temperature and relative humidity, whilst global radiation impacts were almost negligible. Response times varied from 1.2 hours (for relative humidity) to 2.7 days (for global radiation). Furthermore, elevated mean concentrations point to the 8–9 km distant industrial zone. Both, PM1 and meteorological data series exhibited semidiurnal, diurnal and the long-term (about 10–11 days and about 21 day) periodicity. The long-term periodicity of PM1 time series might be associated with Rossby waves. Possible association with Rossby waves needs to be investigated further.
{"title":"Influences of outdoor meteorological conditions on indoor wintertime short-term PM1 levels","authors":"Z. Klaic, S. Ollier, Karmen Babić, I. Bešlić","doi":"10.15233/GFZ.2015.32.12","DOIUrl":"https://doi.org/10.15233/GFZ.2015.32.12","url":null,"abstract":"We investigated the relationship between wintertime 1-min mean urban indoor particulate matter mass concentrations for particles with aerodynamic diameter of < 1 μm (PM1) and outdoor atmospheric conditions. Particle concentrations were measured by two light-scattering laser photometers. Aerosol monitors were placed in the ground and first floor corridors of an university building, with inlets at heights of 1.7 m above the floor. The building is located in residential area of Zagreb, Croatia. During the experiment usual student and employee activities were occurring within the building. Surface meteorological data were collected at a nearby outdoor location. Results show the dependence of indoor PM1 on outdoor meteorology, with the strongest responses to air temperature and relative humidity, whilst global radiation impacts were almost negligible. Response times varied from 1.2 hours (for relative humidity) to 2.7 days (for global radiation). Furthermore, elevated mean concentrations point to the 8–9 km distant industrial zone. Both, PM1 and meteorological data series exhibited semidiurnal, diurnal and the long-term (about 10–11 days and about 21 day) periodicity. The long-term periodicity of PM1 time series might be associated with Rossby waves. Possible association with Rossby waves needs to be investigated further.","PeriodicalId":50419,"journal":{"name":"Geofizika","volume":"32 1","pages":"237-264"},"PeriodicalIF":1.0,"publicationDate":"2015-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67352280","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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