Search Results (2)

Crude oil exploration and transportation have led to significant soil contamination in nearby communities, yet seasonal and depth-related variations remain poorly understood. This study assessed physicochemical properties, potentially toxic elements, and polycyclic aromatic hydrocarbons in surface (0–15 cm) and subsurface (15–30 cm) soils from the Ibaa community and its pipeline Right of Way (ROW) in Rivers State, Nigeria. Samples were collected during wet and dry seasons from five locations, and analyses were conducted using standard methods. Results showed that soil temperature ranged from 27.5 to 31.2 °C, reflecting natural environmental conditions, while nitrate concentrations (1.23–3.45 mg/kg) and moisture content (14.3–23.9%) were within acceptable WHO limits. The pH values (4.61–5.72) suggested acidic conditions, particularly in the unremediated areas. Total Organic Carbon exceeded 3%, with a maximum of 6.23% recorded in the wet season, suggesting persistent hydrocarbon contamination. Phosphorus levels (2.65–6.02 mg/kg) were below the 15 mg/kg threshold. Notably, As (4.93 mg/kg) and Cd (1.67 mg/kg) concentrations exceeded the permissible WHO limits. Positive correlations were observed between As–Cd (r = 0.79), Cd–Cu (r = 0.85), and Pb–Cu (r = 0.64). Principal Component Analysis identified four components for physicochemical parameters (81.9% variance) and two for metals (82.6% variance), suggesting crude oil combustion and vehicular emissions as dominant pollution sources. Pb also correlated significantly with total PAHs in the dry season (r = 0.54, p < 0.05). The study highlights the influence of season and depth on contaminant behavior and emphasizes the urgent need for remediation and monitoring to mitigate ecological and public health risks. Full article

The Advanced Himawari Imager (AHI) aboard the Himawari-8, a new generation of geostationary meteorological satellite, has high-frequency observation, which allows it to effectively capture atmospheric variations. In this paper, we have proposed an Improved Bi-angle Aerosol optical depth (AOD) retrieval Algorithm (IBAA) from AHI data. The algorithm ignores the aerosol effect at 2.3 μm and assumes that the aerosol optical depth does not change within one hour. According to the property that the reflectivity ratio K of two observations at 2.3 μm does not change with wavelength, we constructed the equation for two observations of AHI 0.47 μm band. Then Particle Swarm Optimization (PSO) was used to solve the nonlinear equation. The algorithm was applied to the AHI observations over the Chinese mainland (80°–135°E, 15°–60°N) between April and June 2019 and hourly AOD at 0.47 μm was retrieved. We validated IBAA AOD against the Aerosol Robotic Network (AERONET) sites observation, including surrounding regions as well as the Chinese mainland, and compared it with the AHI L3 V030 hourly AOD product. Validation with AERONET of 2079 matching points shows a correlation coefficient R = 0.82, root-mean-square error RMSE = 0.27, and more than 62% AOD retrieval results within the expected error of ±(0.05 + 0.2 × AOD_AERONET). Although IBAA does not perform very well in the case of coarse-particle aerosols, the comparison and validation demonstrate it can estimate AHI AOD with good accuracy and wide coverage over land on the whole. Full article