Nepal is a country of contrast, with varying altitude, climate and vegetation from the top of high mountains to the tropical forest in low lands. The terrestrial vegetation has rapidly been altered by climate change in Nepal. The spatial and temporal evolution of vegetation and its linkage to climatic variables were analyzed using the Normalized Difference Vegetation Index (NDVI) obtained from Advanced Very High Resolution Radiometer (AVHRR) sensors. A linear regression model and Sen’s slope method were used to estimate NDVI trends and the Pearson correlation between NDVI and climatic variable, i.e., temperature and precipitation were calculated to identify the role of climate in vegetation changes. The carbon dynamics were also measured using a biomass carbon density estimation model. Results showed that NDVI experienced an overall increasing trend in Nepal from 1982–2015. The NDVI significantly increased at the rate of 0.0008 year⁻¹ (p < 0.05) with seasonal variation of 0.0004 year⁻¹, p > 0.05; 0.0007 year⁻¹, p < 0.05; 0.0008 year⁻¹, p < 0.05 and 0.0007 year⁻¹, p > 0.05 in winter, pre-monsoon, monsoon and post-monsoon seasons, respectively. The NDVI relative change ratio (RCR) was 6.29% during last 34 years in Nepal. The correlation between NDVI and temperature was significantly positive (r = 0.36, p = 0.03), but there was a negative correlation with precipitation (r = −0.21, p = 0.28). Altogether, 82.20% of the study areas showed a positive correlation with temperature in which 34.97% was significant and 69.23% of the area had a negative correlation (16.35% significant, p < 0.05) with precipitation. In addition, NDVI-based carbon estimation showed that Nepal’s forest total carbon stock is 685.45 × 10⁶ t C (i.e., an average of 115.392 t C/ha) with an annual carbon sequestration rate of 0.10 t C/ha from 1982–2015. The results suggest that NDVI variation is more sensitive to temperature than precipitation and it is valuable to measure carbon dynamics in Nepal.

Precipitation is the most important variable in the climate system and the dominant driver of land surface hydrologic conditions. Rain gauge measurement provides precipitation estimates on the ground surface; however, these measurements are sparse, especially in the high-elevation areas of Nepal. Reanalysis datasets are the potential alternative for precipitation measurement, although it must be evaluated and validated before use. This study evaluates the performance of second-generation Modern-ERA Retrospective analysis for Research and Applications (MERRA-2) datasets with the 141-gauge observations from Nepal between 2000 and 2018 on monthly, seasonal, and annual timescales. Different statistical measures based on the Correlation Coefficient (R), Mean Bias (MB), Root-Mean-Square Error (RMSE), and Nash–Sutcliffe efficiency (NSE) were adopted to determine the performance of both MERRA-2 datasets. The results revealed that gauge calibrated (MERRA-C) underestimated, whereas model-only (MERRA-NC) overestimated the observed seasonal cycle of precipitation. However, both datasets were able to reproduce seasonal precipitation cycle with a high correlation (R ≥ 0.95), as revealed by observation. MERRA-C datasets showed a more consistent spatial performance (higher R-value) to the observed datasets than MERRA-NC, while MERRA-NC is more reasonable to estimate precipitation amount (lower MB) across the country. Both MERRA-2 datasets performed better in winter, post-monsoon, and pre-monsoon than in summer monsoon. Moreover, MERRA-NC overestimated the observed precipitation in mid and high-elevation areas, whereas MERRA-C severely underestimated at most of the stations throughout all seasons. Among both datasets, MERRA-C was only able to reproduce the observed elevation dependency pattern. Furthermore, uncertainties in MERRA-2 precipitation products mentioned above are still worthy of attention by data developers and users.

Identification of drought is essential for many environmental and agricultural applications. To further understand drought, this study presented spatial and temporal variations of drought based on satellite derived Vegetation Condition Index (VCI) on annual (Jan–Dec), seasonal monsoon (Jun–Nov) and pre-monsoon (Mar–May) scales from 1982–2015 in Nepal. The Vegetation Condition Index (VCI) obtained from NOAA, AVHRR (National Oceanic and Atmospheric Administration, Advanced Very High Resolution Radiometer) and climate data from meteorological stations were used. VCI was used to grade the drought, and the Mann–Kendall test and linear trend analysis were conducted to examine drought trends and the Pearson correlation between VCI and climatic factors (i.e., temperature and precipitation) was also acquired. The results identified that severe drought was identified in 1982, 1984, 1985 and 2000 on all time scales. However, VCI has increased at the rate of 1.14 yr⁻¹ (p = 0.04), 1.31 yr⁻¹ (p = 0.03) and 0.77 yr⁻¹ (p = 0.77) on the annual, seasonal monsoon and pre-monsoon scales, respectively. These increased VCIs indicated decreases in drought. However, spatially, increased trends of drought were also found in some regions in Nepal. For instance, northern areas mainly in the Trans-Himalayan regions identified severe drought. The foothills and the lowlands of Terai (southern Nepal) experienced normal VCI, i.e., no drought. Similarly, the Anomaly Vegetation Condition Index (AVCI) was mostly negative before 2000 which indicated deficient soil moisture. The exceedance probability analysis results on the annual time scale showed that there was a 20% chance of occurring severe drought (VCI ≤ 35%) and a 35% chance of occurring normal drought (35% ≤ VCI ≤ 50%) in Nepal. Drought was also linked with climates in which temperature on the annual and seasonal monsoon scales was significant and positively correlated with VCI. Drought occurrence and trends in Nepal need to be further studied for comprehensive information and understanding.

This paper reports the generation of cold plasma jet working under atmospheric pressure condition, for surface treatment of polymeric films. The discharge has been characterized by electrical and optical methods. The electrical property of the discharge has been studied by taking current-voltage wave forms using voltage and current probes. The production of argon plasma jet is done in atmospheric conditions which are relatively much cheaper, convenient, and safer to use. The atmospheric pressure plasma jet sustained in pure argon has been used to improve wettability of polypropylene (PP). Cold atmospheric pressure plasma jet (CAPPJ) has been generated by a high-voltage power supply (5.5 kV, 0-20 kV) at an operating frequency of 20 kHz. The surface properties of the controls and plasma-treated PP samples were characterized by contact angle measurement, surface free energy measurement, scanning electron microscopy, and the Fourier transform-infrared spectroscopy analysis.

Identification of high altitudinal vegetation dynamics using remote sensing is important because of the complex topography and environment in the Himalayas. Langtang National Park is the first Himalayan park in Nepal representing the best area to study vegetation change in the central Himalaya region because of the high altitudinal gradient and relatively less disturbed region. This study aimed at mapping vegetation in Langtang National Park and its treeline ecotone using Moderate Resolution Imaging Spectroradiometer (MODIS), Normalized Difference Vegetation Index (NDVI). Two treeline sites with an altitude of 3927 and 3802 meters above sea level (masl) were selected, and species density was measured during the field survey. The linear slope for each pixel and the Mann Kendall test to measure significant trends were used. The results showed that NDVI has significantly increased at the rate of 0.002 yr-1 in Langtang National Park and 0.003 yr-1 in treeline ecotone during 2000-2017. The average 68.73% equivalents to 1463 km2 of Langtang National Park are covered by vegetation. At the same time, 16.45% equivalents to 350.43 km2 are greening, and 0.25%, i.e., 5.43 km2 are found browning. In treeline ecotone, the vegetation is mostly occupied by grasses, shrublands and small trees where the NDVI was found from 0.1 to 0.5. The relative changes of NDVI in barren lands are negative and vegetative lands above 0.5 NDVI are positive between 2000 and 2017. The dominant treeline vegetation were Abies spectabilis, Rhododendron campanulatum, Betula utilis and Sorbus microphyla, with the vegetation density of 839.28 and 775 individuals per hectare in sites A and B, respectively. The higher average NDVI values, significantly increased NDVI, and higher density of vegetation in both A and B sites indicate that the vegetation in treeline ecotone is obtaining a good environment in the Himalayas of Nepal.