Chemical characteristics of rainwater in the tropical rainforest region in northwestern Borneo

Sources, Ionic Composition and Acidic Properties of Bulk and Wet Atmospheric Deposition in the Eastern Middle Adriatic Region

Atmospheric bulk and wet deposition samples were collected simultaneously at the background coastal site in the Eastern Middle Adriatic region in order to assess the impact of major ions (Cl^-, NO₃^-, SO₄^2-, Na⁺, K⁺, NH₄⁺, Mg²⁺, Ca²⁺) on deposition acidity and distinguish the main sources. Higher ion levels were observed during the cold period, especially for Cl^-, Na⁺, Mg²⁺ and K⁺. Dust intrusion caused significant increases in levels of Ca²⁺, Mg²⁺ and K⁺, while open-fire events increased the levels of K⁺. Deposition acidity showed seasonal differences as well as the influence of dust intrusion. Low ionic balance ratios indicated acidic deposition properties and the presence of organic anions. The highest neutralization ability was found for Ca²⁺, Na⁺ and NH₄⁺. Several natural (marine, crustal) and anthropogenic sources were determined, as well as the formation of secondary aerosols. Wet deposition was characterized by higher contribution of sea salt fraction compared to bulk deposition and lower contribution of crustal fraction.

Land-Use Impact on Water Quality of the Opak Sub-Watershed, Yogyakarta, Indonesia

The integrated monitoring system of water quality is eminently reliant on water quality trend data. This study aims to obtain water quality patterns related to land-use change over a periodic observation in the Opak sub-watershed, Indonesia, both from a seasonal and spatial point of view. Landsat image data from 2013 to 2020 and water quality data comprising 25 parameters were compiled and analyzed. This study observed that land use remarkably correlated to water quality, especially the building area representing the dense population and various anthropogenic activities, to pollute the water sources. Three types of pollutant sources were identified using principal component analysis (PCA), including domestic, industrial, and agricultural activities, which all influenced the variance in river water quality. The use of spatiotemporal-based and multivariate analysis was to interpret water quality trend data, which can help the stakeholders to monitor pollution and take control in the Opak sub-watershed. The results investigated 17 out of 25 water quality parameters, which showed an increasing trend from upstream to downstream during the observation time. The concentration of biological oxygen demand over five days (BOD5), chemical oxygen demand (COD), nitrite, sulfide, phenol, phosphate, oil and grease, lead, Escherichia coli (E. coli), and total coli, surpassed the water quality standard through spatial analysis.

Seven-year study of monsoonal rainwater chemistry over the mid-Brahmaputra plain, India: assessment of trends and source regions of soluble ions

This work is a 7-year study of monsoonal rainwater chemistry (n = 302), over mid-Brahmaputra plain during 2012 to 2018. The samples were analyzed for major chemical parameters viz. pH, electrical conductivity (EC), and ions (SO₄^2-, NO₃^-, Br^-, Cl^-, F^-, Mg²⁺, Ca²⁺, K⁺, NH₄⁺, Na⁺, and Li⁺) to assess the chemistry. The mean pH of rainwater varied among the years, which was maximum in 2018 (6.18 ± 0.72) and minimum in the year 2014 (5.39 ± 0.54), and the variations were significant at p < 0.0001. Ridgeline plots were drawn to visualize interannual variations, which revealed that Ca²⁺ was the dominant cation in the early years, whereas NH₄⁺ prevailed in the latter years. Mann-Kendall analysis and Sen's slope statistical tests were employed, and it was found that all the ions showed positive S values indicating increasing trends. Enrichment factors (EF) of K⁺, SO₄^2-, and NO₃^- were found to be high with respect to both soil and seawater suggesting the influence of emissions from fossil fuel and biomass burning in the chemistry of rainwater. Principal component analysis (PCA) was applied to identify the sources of rain constituents, and five factors were obtained explaining crustal dust, biomass burning, fossil fuel combustion, agricultural emissions, and coal burning as possible sources. Airmass back trajectory clusters and Potential Source Contribution Function (PSCF) were computed by application of HYbrid Single-Particle Lagrangian Integrated Trajectory model to appreciate the terrestrial influence on the chemistry. The results indicated inputs from both local and regional dust and anthropogenic constituents that influenced the monsoonal rainwater chemistry over Brahmaputra Valley.