Variability and time series trend analysis of rainfall in the mid-hill sub humid zone: a case study of Nauni.

The spatiotemporal variability of rainfall, particularly in the context of climate change, has been imperative for examining the cropping patterns, farming sustainable crop production, and food security in rainfed areas. To that end, trend analysis was done to study the change in rainfall patterns in the mid-hills of Himachal Pradesh. The study investigated the historical rainfall data from 1971 to 2020 on a monthly, annual, seasonal, and decadal basis by using the variability analysis methods, viz., standard deviation (SD), coefficient of variance (CV), and transformed annual precipitation departure (Z). The trend analysis was also done by Mann-Kendall (MK) and Sen's slope estimator (SSE) test and linear regression model. The annual rainfall in the region was 1115.1 mm, which showed a decreasing trend (Z = - 0.79 mm/year). Based on the linear regression model, the decrease in annual rainfall was about - 2.28 mm/year. The monthly and seasonal variability of rainfall exhibited a sensitivity to change. The months of January, April, July, and September showed an increasing trend, whereas the rest of the other months showed a decreasing trend. The seasonal rainfall (summer, monsoon, and post-monsoon) showed a decreasing trend, whereas the winter season depicted an increasing trend. During the entire study period, 1988 recorded as the wettest year, with highest annual rainfall of about 2205.0 mm and monsoon rainfall of about 1653.0 mm. The highest annual (2205.0 mm) and monsoon (1653.0 mm) rainfall was recorded in the year 1988. The decadal analysis of the rainfall on an annual basis revealed a decrease in rainfall during the periods 1971-1980, 2001-2010, and 2011-2020 as compared to 1981-1990 and 1991-2000. The rainfall over the study region confirms the strength of the change in trend. Thus, the erratic rainfall pattern makes the cropping calendar shorter and affects the agricultural productivity.

Appraisal of regional haze event and its relationship with PM2.5 concentration, crop residue burning and meteorology in Chandigarh, India.

Air pollution affects not only the air quality in megacities but also in medium and small-sized cities due to rapid urbanization, industrialization, and other anthropogenic activities. From October 28, 2015 to November 3, 2015, the Indo-Gangetic Plains region, including Chandigarh encountered an episode of poor visibility during the daytime. The daily average PM2.5 concentration reached 191 µg/m3, and visibility reduced by ∼2.2 times in the Chandigarh region. PM2.5 concentration was found around 4 times higher than a non-haze day and more than 3 times higher than National Ambient Air Quality Standards for 24 h. A significant correlation between PM2.5 and CO (r: 0.87) during the haze period indicated similarity in their emission sources; which was attributed to the burning of solid organic matter. Further, satellite data and back-trajectory analysis of air masses showed large-scale rice stubble burning in the agricultural fields, adjoining to the city areas. The transboundary movement of air masses below 500 m and meteorological conditions played a major role in building the pollution load in the Chandigarh region. Moreover, the enhanced concentration of biomass burning tracers, i.e., organic carbon (∼3.8 times) and K+ ions (2∼ times) in PM2.5 and acetonitrile (∼2.3 times) in ambient air was observed during the haze event. The study demonstrates how regional emissions and meteorological conditions can affect the air quality in a city; which can be useful for proper planning and mitigation policies to minimize high air pollution episodes.

Mental health effects of climate change.

We all know that 2014 has been declared as the hottest year globally by the Meteorological department of United States of America. Climate change is a global challenge which is likely to affect the mankind in substantial ways. Not only climate change is expected to affect physical health, it is also likely to affect mental health. Increasing ambient temperatures is likely to increase rates of aggression and violent suicides, while prolonged droughts due to climate change can lead to more number of farmer suicides. Droughts otherwise can lead to impaired mental health and stress. Increased frequency of disasters with climate change can lead to posttraumatic stress disorder, adjustment disorder, and depression. Changes in climate and global warming may require population to migrate, which can lead to acculturation stress. It can also lead to increased rates of physical illnesses, which secondarily would be associated with psychological distress. The possible effects of mitigation measures on mental health are also discussed. The paper concludes with a discussion of what can and should be done to tackle the expected mental health issues consequent to climate change.