Indian Institute of Tropical Meteorology, Ministry of Earth Sciences, Pune, 411008, India.
Divecha Centre for Climate Change, Indian Institute of Science, Bangalore, 560012, India.
Environ Sci Pollut Res Int. 2024 Aug;31(40):53304-53314. doi: 10.1007/s11356-024-34793-7. Epub 2024 Aug 26.
This study focuses on the chemical composition of cloud water (CW) and rainwater (RW) collected at Sinhagad, a high-altitude station (1450 m AMSL) located in the western region of India. The samples were collected during the monsoon over two years (2016-2017). The chemical analysis suggests that the concentration of total ionic constituents was three times higher in CW than in RW, except for NH (1.0) and HCO (0.6). Compared to RW, high concentrations of SO and NO were observed in CW. The weighted average RW pH (6.5 ± 0.3) was slightly more alkaline than CW pH (6.1 ± 0.5). This can be attributed to the high concentrations of neutralizing ions such as nss-Ca, nss-Mg, K, and NH, indicating the greater extent of wet scavenging during rainfall. These ions counteract the acidity generated by SO and NO. A high correlation between Ca, Na, K, NO, and SO makes it difficult to estimate the contribution of SO from different sources. Anthropogenic sulfur emissions and soil dust significantly influence the ionic composition of clouds and rain. Positive matrix factorization (PMF) was used to identify the contribution of different sources to the samples. In the CW, the extracted factors were cooking and vehicles, aging sea salt, agriculture, and dust. In RW, the factors were industries, cooking and vehicles, agriculture and dust, and aging sea salt. The findings of this study have significant implications for the monsoon build-up, ecosystems, agriculture, and climate change.
本研究聚焦于在印度西部地区一个高海拔站点（海拔 1450 米）辛哈加德收集的云（CW）和雨水（RW）的化学成分。这些样本是在两年的季风期间（2016-2017 年）采集的。化学分析表明，除了 NH（1.0）和 HCO（0.6）外，CW 中的总离子成分浓度是 RW 的三倍。与 RW 相比，CW 中 SO 和 NO 的浓度较高。RW 的加权平均 pH 值（6.5±0.3）略高于 CW 的 pH 值（6.1±0.5）。这可以归因于中和离子（如 nss-Ca、nss-Mg、K 和 NH）的高浓度，表明在降雨过程中湿清除的程度更大。这些离子抵消了 SO 和 NO 产生的酸度。Ca、Na、K、NO 和 SO 之间的高度相关性使得很难估计来自不同来源的 SO 的贡献。人为硫排放和土壤尘埃显著影响云和气溶胶的离子组成。正定矩阵因子分析（PMF）被用于识别不同来源对样品的贡献。在 CW 中，提取的因子有烹饪和车辆、老化海盐、农业和尘埃。在 RW 中，因子有工业、烹饪和车辆、农业和尘埃以及老化海盐。本研究的结果对季风的形成、生态系统、农业和气候变化具有重要意义。
