The air pollution in Jakarta has been recorded regularly; meanwhile, the information of atmospheric microplastics is still unknown. This study examines the characteristics (shape, size, and polymer) and deposition rate of atmospheric microplastics in Jakarta. The sample was obtained by putting a rain gauge for 12 months. All microplastic samples were analyzed for polymer using FT-IR. The lowest to the highest percentage of atmospheric microplastic based on shape were foam<fragment<fiber, meanwhile based on size were of 500–1000 μm < 300–500 μm. The detected polymers included polyester, polystyrene, polybutadiene, and polyethylene. The microplastics deposition rate ranged from 3 to 40 particles m⁻²d⁻¹, with an average of 15 particles m⁻²d⁻¹. The rainy season's deposition rate (23.422 particles m⁻²d⁻¹) was higher than the dry season (5.745 particles m⁻²d⁻¹). Our study proves that the atmospheric microplastic exists in Jakarta's air and needs to be considered to monitor by the government regularly.

The influence of a change from daily to weekly sampling of bulk precipitation on the obtained deposition values was studied with parallel sampling for 8 months at the station of Virolahti in 2004. Due to dry deposition, the deposition values of the whole period were found to be 5–70% higher from weekly sampling than from daily sampling, the biggest difference being for K+, Ca2+, Mg+ and Na+. The collection efficiencies of the summer sampler and the winter sampler compared to the standard rain gauge were studied from daily sampling in 1991–2003 and weekly sampling in 2004–2008. The performance was best in summer and in winter with rain samples (median value 85–88%), while the median value for daily snow samples was 72%. In winter, the total sum of precipitation collected in the daily sampler and the weekly sampler was 78% and 69%, respectively. The deficit in the weekly sampler in winter was concluded to be due to evaporation, while from the summer sampler no evaporation seemed to occur. Use of the precipitation amount measured by the standard rain gauge when calculating annual precipitation-weighted mean values gave higher mean concentrations than the use of the precipitation measured by the deposition sampler itself, the biggest difference of 8–11% being in the sea-salt ions Cl−, Mg+ and Na+. It was concluded that the concentration and deposition values measured by daily and weekly bulk sampling are incompatible, and should not be combined into the same time series.

Rainwater harvesting is an effective alternative practice, particularly within urban regions, during periods of water scarcity and dry weather. The collected water is mostly utilized for non-potable household purposes and irrigation. However, due to the increase in atmospheric pollutants, the quality of rainwater has gradually decreased. This atmospheric pollution can damage the climate, natural resources, biodiversity, and human health. In this study, the characteristics and physicochemical properties of rainfall were assessed using a qualitative approach. The three-year (2017–2019) data on rainfall in Peninsular Malaysia were analysed via multivariate techniques. The physicochemical properties of the rainfall yielded six significant factors, which encompassed 61.39% of the total variance as a result of industrialization, agriculture, transportation, and marine factors. The purity of rainfall index (PRI) was developed based on subjective factor scores of the six factors within three categories: good, moderate, and bad. Of the 23 variables measured, 17 were found to be the most significant, based on the classification matrix of 98.04%. Overall, three different groups of similarities that reflected the physicochemical characteristics were discovered among the rain gauge stations: cluster 1 (good PRI), cluster 2 (moderate PRI), and cluster 3 (bad PRI). These findings indicate that rainwater in Peninsular Malaysia was suitable for non-potable purposes.

In the present study, impact of precipitation disparity on groundwater level fluctuation was carried out in Vellore district, Tamil Nadu, India, using geospatial techniques. There are five rain gauge stations in the study area in which three rain gauge stations, namely Alangayam, Jolarpettai and Pernampet, receive more precipitation when compared with the average annual precipitation of Tamil Nadu state (920 mm). The other two stations, namely Madanur and Natrampalli, receive less than 920 mm of precipitation annually. The overall average annual precipitation of the study area is 913.6 mm. More than 100 mm precipitation is received in all the five rain gauge stations during southwest (SW) and northeast (NE) monsoon seasons. The maximum monthly precipitation is usually recorded during the month of November and the minimum precipitation is recorded during June. The post-monsoon precipitation is around 10.8 mm, which is almost negligible in the study area. The contribution of precipitation by various seasons is in the following sequence: Southwest monsoon > Northeast monsoon > Pre-monsoon > Post-monsoon. The spatial disparity study indicates that the intensity of average annual, pre-monsoon and post-monsoon precipitations increase towards west in the study area. The intensity of precipitation is more in the northern part during SW monsoon season, whereas the intensity is more in the southern part during NE monsoon season. The spatial disparity analysis of groundwater fluctuation shows that the depth of groundwater (below ground level) increases towards west during all the monsoon seasons. The minimum, mean and maximum depths of occurrence of groundwater in this region are, respectively, 1.6, 9.6 and 21.15 m. Declining trend in the regional groundwater level is observed from December to June because of less precipitation during non-monsoon season. However, the monsoon (both SW and NE monsoon) precipitation recharges the groundwater from June to December to reach the maximum in the month of December.

Drought is a major natural disaster that significantly impacts the susceptibility and flexibility of the ecosystem by changing vegetation phenology and productivity. This study aimed to investigate the impact of extreme climatic variation on vegetation phenology and productivity over the four sub-regions of China from 2000 to 2017. Daily rain gauge precipitation and air temperature datasets were used to estimate the trends, and to compute the standardized precipitation-evapotranspiration index (SPEI). Remote sensing–based Enhanced Vegetation Index (EVI) data from a moderate resolution imaging spectroradiometer (MODIS) was used to characterize vegetation phenology. The results revealed that (1) air temperature had significant increasing trends (P < 0.05) in all sub-regions. Precipitation showed a non-significant increasing trend in Northwest China (NWC) and insignificant decreasing trends in North China (NC), Qinghai Tibet area (QTA), and South China (SC). (2) Integrated enhanced vegetation index (iEVI) and SPEI variations depicted that 2011 and 2016 were the extremely driest and wettest years during 2000–2017. (3) Rapid changes were observed in the vegetation phenology and productivity between 2011 and 2016. In 2011, changes in the vegetation phenology with the length of the growing season (ΔLGS) = was − 14 ± 36 days. In 2016, the overall net effect changed at the onset and end of the growing season with ΔLGS of 34 ± 71 days. The change in iEVI per SPEI increased rapidly with a changing rate of 0.16 from arid (NWC, and QTA) to semi-arid (NWC, QTA and NC) and declined with a rate of − 0.04 from semi-humid (QTA, NC, and SC) to humid (SC) region. A higher association was observed between iEVI and SPEI as compared to iEVI and precipitation. Our finding exposed that north China is more sensitive to climatic variation.