scholarly journals Soil gas radon mapping of Muzaffarabad city, Pakistan

2016 ◽  
Vol 31 (3) ◽  
pp. 291-298 ◽  
Author(s):  
Aleem Tareen ◽  
Muhammad Rafique ◽  
Kimberlee Kearfot ◽  
Muhammad Basharat ◽  
Bilal Shafique

Soil-based radon investigations are of value in correlating radon production and its transportation into buildings through the processes of convection and diffusion. Such studies can help in identifying land areas that pose special concerns. We present preliminary results of soil radon gas measurements at 60 different locations in an attempt to map out the geohazard zone of the city of Muzaffarabad. The seismic geohazard microzonation for the area includes five microzones based on different hazard parameters: a very high hazard zone, a high hazard zone, a moderate hazard zone, a low hazard zone, and a safe zone. Measurements were taken with an active radon monitoring system at the depths of 30, 40, 50, and 60 cm below the ground surface. The results obtained were explained by the lithology of the area. Average soil radon gas concentrations were correlated with the depth from the ground surface and indoor radon values for the study area. No significant correlation was found between soil radon gas and meteorological parameters, however soil radon gas increases as the depth from the surface of the ground grows. The results showed a linear relation between soil radon concentrations with depth from ground surface (R2 = 0.9577). The minimum soil radon concentration (68.5 Bq/m3) was found at a depth of 30 cm in the very high hazard zone, the maximum value (53.300 Bq/m3) at a depth of 60 cm in the seismically safe zone. Measured soil gas radon concentrations at depths of 30, 40, 50, and 60 cm were mapped for high, moderate, and low radon concentrations. Elevated soil radon gas concentrations were found in the safe zone, otherwise considered to be suitable for any type of construction.

Author(s):  
Mohammademad Adelikhah ◽  
Amin Shahrokhi ◽  
Morteza Imani ◽  
Stanislaw Chalupnik ◽  
Tibor Kovács

A comprehensive study was carried out to measure indoor radon/thoron concentrations in 78 dwellings and soil-gas radon in the city of Mashhad, Iran during two seasons, using two common radon monitoring devices (NRPB and RADUET). In the winter, indoor radon concentrations measured between 75 ± 11 to 376 ± 24 Bq·m−3 (mean: 150 ± 19 Bq m−3), whereas indoor thoron concentrations ranged from below the Lower Limit of Detection (LLD) to 166 ± 10 Bq·m−3 (mean: 66 ± 8 Bq m−3), while radon and thoron concentrations in summer fell between 50 ± 11 and 305 ± 24 Bq·m−3 (mean 115 ± 18 Bq m−3) and from below the LLD to 122 ± 10 Bq m−3 (mean 48 ± 6 Bq·m−3), respectively. The annual average effective dose was estimated to be 3.7 ± 0.5 mSv yr−1. The soil-gas radon concentrations fell within the range from 1.07 ± 0.28 to 8.02 ± 0.65 kBq·m−3 (mean 3.07 ± 1.09 kBq·m−3). Finally, indoor radon maps were generated by ArcGIS software over a grid of 1 × 1 km2 using three different interpolation techniques. In grid cells where no data was observed, the arithmetic mean was used to predict a mean indoor radon concentration. Accordingly, inverse distance weighting (IDW) was proven to be more suitable for predicting mean indoor radon concentrations due to the lower mean absolute error (MAE) and root mean square error (RMSE). Meanwhile, the radiation health risk due to the residential exposure to radon and indoor gamma radiation exposure was also assessed.


2013 ◽  
Vol 126 ◽  
pp. 165-171 ◽  
Author(s):  
Mutlu İçhedef ◽  
Müslim Murat Saç ◽  
Berkay Camgöz ◽  
Mustafa Bolca ◽  
Çoşkun Harmanşah

2018 ◽  
Vol 11 (9) ◽  
Author(s):  
Osman Günay ◽  
Müslim Murat Saç ◽  
Mutlu İçhedef ◽  
Caner Taşköprü

2021 ◽  
Author(s):  
Dawit Asmare Manderso

Abstract The main goal of this research was to perform a landslide hazard zonation and evaluation around Debre Markos town, North West Ethiopia, found about 300 km from the capital city Addis Ababa. To achieve the aim, a GIS-based probabilistic statistical technique was used to rate the governing factors, followed by geoprocessing in the GIS setting to produce the landslide hazard zonation map. In this research, eight internal causative and external triggering factors were selected: slope material (lithology and soil mass), elevation, aspect, slope, land use land cover, curvature, distance to fault, and distance to drainage. Data were collected from field mapping, secondary maps, and digital elevation models. Systematic and detailed fieldwork had been done for image interpretation and inventory mapping. Accordingly, the past landslides map of the research area was prepared. All influencing factors were statistically analyzed to determine their relationship to previous landslides. The results revealed that 17.15% (40.60 km2), 25.53% (60.45 km2), 28.04% (66.39 km2), 18.93% (44.83 km2), and 10.36% (24.54 km2) of the research area falls under no hazard, low hazard, moderate hazard, high hazard, and very high hazard respectively. The validation of the landslide hazard zonation map reveals that 1%, 2%, 3%, and 94% of past landslides fall in no hazard zone, low hazard, moderate hazard zone, and high hazard or very high hazard zones respectively. The validation of the landslide hazard zonation map thus, it has been adequately demonstrated that the adopted approach has produced acceptable results. The defined hazard zones can practically be utilized for land management and infrastructure construction in the study area.


Proceedings ◽  
2020 ◽  
Vol 67 (1) ◽  
pp. 7
Author(s):  
Ana Maria Carmen Ilie ◽  
Carmela Vaccaro

Cities are major contributors to greenhouse gas emissions (GHG) due to the high density of urbanization, numerous industrial centers, and intensive agricultural activities. This study focused on soil methane and radon gas measurements in the subsurface, as well as in the atmosphere. Measurements were conducted using new gas detection instrumentation and as low-cost devices for methane gas concentrations. Maximum soil radon gas concentration was observed to be approximately 1770 ± 582 Bq/m3 at a depth of 1 m below the ground surface. The soil comprised of 64.31% sand, 20.75% silt, and 14.94% clay, and 0.526 ppm of uranium. The maximum concentration of methane was about 0.06%, at a depth of 1 m into the soil, characterized by 83% sand, 8.96% silt, and 7.89% clay. Moreover, this study focused on a better understanding of the advantages and disadvantages of new soil gas detection technology. The results and findings of environmental data obtained from the soil gas survey were shared with the community, whose involvement was critical in the data acquisition process.


2010 ◽  
Vol 10 (6) ◽  
pp. 1221-1227 ◽  
Author(s):  
S. Mahajan ◽  
V. Walia ◽  
B. S. Bajwa ◽  
A. Kumar ◽  
S. Singh ◽  
...  

Abstract. The present research is aimed at accessing the relationship between variation in the soil gases radon (222Rn) and helium (4He) and recently developed fissures and other neotectonic features in Nurpur and Nadha areas of the NW Himalayas, India. Two soil-gas surveys were conducted on/near known faults to reconfirm their position using soil gas technique and to check their present activity. During these surveys, soil-gas samples were collected along traverses crossing the observed structures. The data analysis reveals that the concentrations of radon and helium along the Dehar lineament and the longitudinal profile (Profile D) are very high compared to any other thrust/lineament of the Nurpur area. The Nadha area shows high values of radon and helium concentrations along/near the Himalayan Frontal Fault (HFF) as compared to the adjoining areas. This indicates the presence of some buried fault/fault zone running parallel to the HFF, not exposed to the surface and not delineated by satellite data but is geochemically active and might be tectonically active too. Hence, soil helium and radon gas patterns have been combined with morphological and geological observations to supply useful constraints for deformation of tectonic environments.


2020 ◽  
Vol 326 (1) ◽  
pp. 1-9
Author(s):  
Bo Lei ◽  
Ziqi Cai ◽  
Changshou Hong ◽  
Guan Chen ◽  
Jintao Guo ◽  
...  

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