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There are several toxic microalgae species known as Harmful algal bloom (HAB) causing serious effects to the environment and economy. Knowledge on these groups of marine micro-flora is scanty and several areas remain unexplored. The present study focuses on the analysis of microalgal diversity in the Malabar coastal areas at Southwest and Northeast monsoon. The diatoms, dinoflagellates and total microalgal population were analysed and quantified. Predominant species were identified. Physicochemical parameters of the seawater at different time intervals and Correlation between diatoms, dinoflagellates and total microalgae population with physicochemical parameters were identified. From the analysis, a total of 53 diatoms and 15 dinoflagellates were identified. The predominant species including toxic or harmful bloom-forming were found to be Dinophysis caudata, Noctiluca scintillans, Prorocentrum lima and Tripos furca. The total microalgae population varied from 18,592 cells/L to 7,832 cells/L in the months of April and December. Dinoflagellates were positively correlated with salinity (r = 0.848; p = 0.008), nitrite (r = 0.752; p = 0.032) and total phosphorous (r = 0.734, p = 0.038). Diatoms were positively correlated with temperature (r = 0.804; p = 0.016) and nitrate (r = 0.774, p = 0.024). Total microalgal density was positively correlated with temperature (r = 0.825; p = 0.012) and nitrate content (r = 0.811, p = 0.15).

This study is the first attempt to assess the presence of 16 priority polycyclic aromatic hydrocarbons (PAHs) enlisted by the US Environmental Protection Agency in PM2.5 and PM10 from industrial areas of Odisha State, India. During 2017–2018, bimonthly sampling of PM10 and PM2.5 was carried out for 24 h in the industrial and mining areas of Jharsuguda and Angul in Odisha during the pre-monsoon, monsoon, and post monsoon seasons. Highest mean concentration of ∑16PAHs in PM2.5 was observed during the post monsoon (170 ng/m3) period followed by pre-monsoon (48 ng/m3) and monsoon (16 ng/m 3) periods, respectively. A similar trend of ∑16PAHs was also observed in PM10 with higher levels observed during post monsoon (286 ng/m3) followed by pre-monsoon (81 ng/m3) and monsoon (27 ng/m3) seasons. Diagnostic ratios and principal component analysis suggested diesel, gasoline and coal combustion as the major contributors of atmospheric PAH pollution in Odisha. Back trajectory analysis revealed that PAH concentration was affected majorly by air masses originating from the northwest direction traversing through central India. Toxic equivalents ranged between 0.24 and 94.13 ng TEQ/m3. In our study, the incremental lifetime cancer risk ranged between 10–5 and 10–3, representing potential cancer risk.

Spatio-temporal evolution of soil moisture is a complex process and controlled by several factors including hydro-meteorological forcings. This study borrows a recently developed concept of temporal networks to capture the time-varying association between hydro-meteorological forcings and spatio-temporal evolution of soil moisture. Climate change and dynamic terrestrial environment cause slow but continuous change in the characteristics of hydro-meteorological forcings leading to variation in spatio-temporal distribution of soil moisture. Keeping this in the focus of the study, temporal networks based time-varying modelling framework is adapted for one-month to one-season (three-months) in advance prediction of monthly soil moisture for entire Indian mainland. Results indicate that the association among the hydro-meteorological forcings varies with both space and time. With the increase in prediction lead-time, the strength of association with the variables, such as pressure, wind and temperature, decreases and that with the variables like leaf area index remains informative. Among different seasons, the model shows superior performance for the monsoon and post monsoon periods. Next, the soil moisture based extremes are assessed by utilizing two deficit indices and two wetness indices. The model performance is highly satisfactory but varies over space and seasons, with a marginally better performance for the wetness indices. Overall, given the vast spatial extent of the Indian mainland, the proposed model performs robustly for almost all the climatic regions and may be promising for other parts of the world as well.

This study has been carried out to find the groundwater quality of Burdwan district of West Bengal during pre-monsoon and post-monsoon. For this, the data of physicochemical parameters have been collected from Central Pollution Control Board (CPCB) website for the pre-monsoon and post-monsoon season for the year 2017. It is found that during the post-monsoon season, the water quality of all the stations falls in the category of excellent, and during the pre-monsoon season, the water quality of most of the stations is good.

During 2019, in all 12 intense low pressure systems formed over the Indian Seas. These include; one Super cyclonic storm (KYARR), one extremely severe cyclonic storm (FANI), 4 very Severe Cyclonic Storms (VAYU, HIKAA, MAHA & BULBUL), 2 Cyclonic Storms (PABUK & PAWAN), 3 Deep Depressions and 1 Depression. Out of these 12 systems, 4 systems formed over the Bay of Bengal and 8 over the Arabian Sea. Arabian Sea remained exceptionally active in terms of cyclogenesis this year, especially in the post monsoon season. The season-wise distribution had been one cyclonic storm in winter, one in pre-monsoon season, 2 depressions and 2 very severe cyclonic storms during the monsoon season and 4 cyclonic storms and 3 depressions in Post monsoon season.

Drought is a natural hazard that has a significant effect on the socio-economic, agricultural, and environmental aspects of a region. The Marathwada division of Maharashtra state is infamous for recurring drought situations. Poor precipitation, lack of water storage, relatively high temperature in pre and post-monsoon seasons, and variable unfavorable weather conditions lead to drought in this region. Post-monsoon drought mainly occurs due to deficit rainfall and a sudden increase in temperature. This study represents the overall assessment of post-monsoon drought over Marathwada during October, November, and December for the period 2001 to 2017. Monsoon rainfall deficit results in post-monsoon drought in subsequent months. Detection and monitoring of drought over large areas are possible through remote sensing indices namely, Temperature Condition Index (TCI), Vegetation Condition Index (VCI), and Vegetation Health Index (VHI). VHI is the resultant index from temperature and vegetation indices, which helps to understand vegetation health. During the last 17 years, moderate to severe drought has been observed in two successive years of 2014 and 2015, where TCI, VCI, and VHI indices indicated these years as drought-prone years for the post-monsoon season. Particularly, Bid, Osmanabad, Latur, Nanded, and Parbhani districts suffered severe drought in these successive years. Whereas, all the other years except 2010 and 2017 experienced normal conditions to moderate drought in the Marathwada region. Due to erratic rainfall, it is necessary to plan water utilization and storage in Marathwada to overcome the recurrent drought experienced in the region. This may help agronomists and planners in better management of water resources, particularly for the agricultural sector.

Drought is a burning issue in India and hence needs serious attention of researchers to develop rigorous plan and management. Areas that belong to various plateaus, e.g., Chottanagpur plateau, Deccan plateau, etc., are mostly affected by drought in India. In the past decade, Purulia District of West Bengal, which belongs to northeast part of Chottanagpur plateau, faced severe drought several times. But the assessment of drought in this area was far from a decesive proclamation till date. In this research, an attempt was made to compare the Holt-Winter additive and Holt-Winter multiplicative model in simulation (at 1 month lead time) of meteorological drought (using Standardized Precipitation Index (SPI) of Purulia District, West Bengal, India. The additive model showed better performance than the multiplicative model with minimized Root Mean Squared Error (RMSE) and higher correlation coefficient value (R2). The spatial assessment drought at pre-monsoon, monsoon and post-monsoon phase indicated that severe drought had occurred in post monsoon and premonsoon phase at the eastern portions of the study area.

Aim: The experiment is aimed at quantifying the nitrogen requirement and identifying suitable hybrids and varieties of castor to be grown during post monsoon season on Alfisols in Telangana Study Design: Split plot design. Place and Duration of Study: Regional Agricultural Research Station, Professor Jayashankar Telangana State Agricultural University, Palem, Telangana state, India during post monsoon season of 2010-11 and 2011-12. Methodology: The study consisted of four N levels (0, 40, 80 kg and 120 kg N ha-1) in main plots and five cultivars (DCH-177, PCH-111, GCH-4, Haritha and 48-1)in sub plots. The growth parameters, yield attributes, seed yield, water use efficiency, economic returns, correlation and regression were studied. Results: The pooled data indicated that significantly taller plants with more no. of branchesplant-1, longer and effective spikes thus seed yield of castor were observed due to application of 80 kg Nha-1 and 120 kg Nha-1. However, application of 120 kg N ha-1 resulted in greater net returns (USD 1049 ha-1) and also returns per rupee invested (1.66). The results further showed that the castor hybrids PCH-111 (1900 kg/ha) and DCH-177 (1809 kg/ha) produced similar yield, but, both significantly outyielded over other cultivars. The performance of hybrids was superior to the varieties. A highly significant positive correlation was observed for seed yield with no. of branches/plant, total and effective spike length. Conclusion: The cultivation of castor hybrids either PCH-111 or DCH-177 under N supply of 120 kg N ha-1 would help to realize higher yields, water use efficiency and income from post monsoon season castor on Alfisols.

The standard weekly rainy days analysis of binomial distribution for monsoon season of Navsari on chi-square test on binomial distribution was found in SW 22 to 31, 33 and SW 35 to 39 and post monsoon in standard week (SW) 41 to 44 shows significant. The result also reveals that the monsoon season SW 32 and 34 and post monsoon season SW 40, 45, 46 and 47 revealed non-significant result. Analysis reveals the rainfall is not equally distributed during SW 32, 34, 40, 45, 16 and 47, so that the test of binomial distribution is a good fit. Monsoon season rainfall data of Navsari reveals that the normal distribution at 10, 20 and 30% probability levels for the month of June, July, August and September shows the possibility of increasing rainy days occurrence. The Navsari districts during post monsoon season rainfall of months of October and November reveals decreasing tendency. The binomial distribution fit only those standard weeks in which rainfall is not equally distributed. From above results observed that the rainfall distribution is not equally distributed so test of binomial distribution at above given standard week is a good fit. The data also shows that, decreasing tendency in rainfall was observed in district.

The present study on Performance evaluation of Sweetcorn with different levels of Irrigation and nitrogen through drip during post monsoon season at Rajendranagar, Hyderabad, India was conducted for two years at Maize Research Centre, Agricultural Research Institute (ARI), Rajendranagar, Hyderabad to assess the influence of different levels of irrigation and nitrogen on performance of sweetcorn hybrid. Randomized block design with factorial concept was used in the study and the experiment was replicated thrice. The treatments used were two factors. Factor I was five irrigation levels viz., I1: Drip irrigation at 60% E pan, I2: Drip irrigation at 80% E pan, I3: Drip irrigation at 100% E pan, I4:Drip irrigation at 120% E pan andI5: Surface irrigation at IW/CPE- 1.0 and Factor II was four nitrogen levels in kg ha-1 viz., N1: 120, N2: 160 N3: 200 N4: 240. Pooled mean of two years revealed that, drip irrigation with 120% E pan which was on par with 100% E pan showed significantly better crop performance in terms of growth characteristics like plant height, Leaf Area Index and dry matter production and both were superior to drip irrigation of 80 and 60% E pan as well as surface irrigation method. Among the yield attributes, cob girth and 100 seed weight were not influenced either with irrigation or nitrogen and their interaction. Cob length, number of seeds row-1, green cob and fodder yield were higher with drip irrigation of 120% E pan but were on par with 100% E pan. Among the different nitrogen levels, nitrogen at the rate of 240 kg ha-1recorded significantly higher growth parameters, yield attributes, green cob and fodder yield but it was on par with 200 kg ha-1 and both were superior over 160 and 120 kg N ha-1. Drip irrigation of 100% E pan and a nitrogen level of 200 kg ha-1 resulted in higher gross and net returns and benefit cost ratio compared to other irrigation and nitrogen treatments. From the study, drip irrigation of 100% E pan with 200 kg N ha-1is recommended for getting higher yields and net income in sweetcorn hybrid grown in Southern Agro climatic zone of Telangana, India.

Algae are organisms with size ranging from microscopic to hundred feet to large seaweeds. The present study focuseson the algal diversity in Pandalam area of Achankovil river, Kerala, India. Pilgrims of Sabarimala uses the water of Achankovil River for various sanitary purposes and there by waste dump in river may cause water pollution and related ecological problems.Water samples werecollected during the monsoon and post monsoon seasons in the early morning before increasing the intensity of sunlight. Phytoplanktonic forms were collected using plankton net.The analysis of physico-chemical parameters such as temperature, pH, salinity and productivity show a slight variation in mean value during the two seasons. The study reveals presence of forty one algal genera belongings to four algal classes.Theresults showed that parameters such as dissolved oxygen, carbon dioxide, total hardness and silicate indicatevariations with relation to seasons.The variations and distribution of phytoplankton and changes in physico-chemical parameters in freshwater helps to know the water quality of the river.

In statistical downscaling technique, regional or local information are derived by determining a statistical model which relates large-scale climate variables or predictors generated by Global Climate Models (GCMs) to regional and local variables or predictands. In this paper, the results of GCMs were statistically downscaled to produce future climate projections of mean temperature in the post-monsoon season (October and November), for the time periods 2021-2050 and 2071-2100 for Bangladesh. The future climate projections are based on the three emission scenarios RCP2.6, RCP4.5 and RCP8.5 provided by the fifth Coupled Model Intercomparison Project (CMIP5). This paper established a method to analyze GCMs for use in statistical downscaling and utilized fifteen GCMs. The GCMs were assessed based upon their performance in simulated past climate in Bangladesh and adjoining areas. Downscaling was undertaken by linking large scale climate variables, taken from the ERA-Interim (resolution 79 km) reanalysis temperature, a gridded data set incorporating observations and climate models, to local scale observations. Overall, all fifteen GCMs, via statistical downscaling, show that mean temperature of the post-monsoon season in Bangladesh will increase under future climate scenarios. Comparing the ensemble of future projections with the reference period (1981- 2010), the mean post-monsoon temperature in Bangladesh is projected for RCP8.5 showing warming by 0.310C in near future and 1.790C in far future. On the other hand, estimated warming is 0.390C in near future and 1.140C is far future for RCP4.5. Low emission scenarios RCP2.6, near future temperature is nearly same the far future temperature. Journal of Engineering Science 11(2), 2020, 27-35

A field experiment was conducted at Agro Climate Research Center, Rajendranagar, Hyderabad, India during post monsoon season of 2019-20 with an objective to optimize the nitrogen dose under varied degrees of water stress environment. The experiment was laid out in split plot design replicated thrice with three irrigation scheduling (60%DASM, 40%DASM and 20%DASM) as main plots and three nitrogen levels (90, 180 and 240 kg of nitrogen ha-1) as sub plots. The results indicated that, at 20% DASM, with increasing nitrogen dose from 90 to180 and further 240 kg ha-1, the plant height and biomass increased significantly. Whereas a significant response in terms of the LAI, number of grains row-1, grain and stover yields and nitrogen uptake by plant was observed up to 180 kg N ha-1.Under deficit soil moisture condition (60% DASM) the maximum plant height (141.5cm), LAI (2.93), biomass (222.3 g plant-1), number of grains row-1 (35.3) test weight (24.1 g), grain yield (4930 kg ha-1), stover yields (7996kg ha-1) and nitrogen uptake by plant was recorded with low nitrogen dose of 90 kg N ha-1 and all these parameters were decreased with increasing nitrogen dose. The concentration of nitrogen in leaf, stem and grain was more under deficit soil moisture condition (60% DASM) and was decreased with reliving plant water stress by scheduling irrigation at 40% DASM and 20% DASM. This investigation evidences the need of nitrogen optimization under varied degree of moisture availability. Under deficit irrigated situation, lower dose of nitrogen is sufficient for optimum yield. Whereas under sufficient water availability, the beneficial effect increased nitrogen levels can be exploited for higher grain yield in maize.

The relationship ( $$\varvec{Z} = \varvec{AR}^{\varvec{b}}$$ ) between radar reflectivity factor, $$\varvec{ Z }$$ and rainfall rate, $$\varvec{R }$$ is studied using the micro rain radar (MRR) observation located over Darjeeling (27.05° N, 88.26° E, 2194 m above the msl) in the foothills of the eastern Himalayan Mountains during Indian summer monsoon and post monsoon seasons (June–October) 2013. Observations from MRR are classified mainly into two types, stratiform and convective, based on the bright band and non-bright band signatures in the radar reflectivity, respectively. We have observed 12 and 7 cases for the stratiform convective rain events, respectively. In the present study MRR is operated mostly during low intensity rainfall rate (0.02–20 mm/h). During southwest monsoon season $$\varvec{Z} {-} \varvec{R }$$ relation for the stratiform and convective rainfall types are found to be $$\varvec{Z} = 272\varvec{R}^{1.78}$$ and $$\varvec{Z} = 192\varvec{R}^{1.54}$$ respectively. $$\varvec{Z} {-} \varvec{R }$$ relation for both stratiform and convective rain shows high temporal variation during different months of monsoon and post monsoon seasons. The coefficient $$\varvec{A}$$ varies between 225 and 289 for stratiform rain and between 153 and 235 for convective rain. The exponent $$\varvec{b}$$ varies between 1.4 and 2.1 for stratiform rain while between 1.2 and 1.8 for convective rain. Interestingly, we observed a distinct relation with smaller values of $$\varvec{A}$$ and $$\varvec{b}$$ for convective rain than stratiform rain over Darjeeling. The height dependence of $$\varvec{A}$$ and $$\varvec{b}$$ are also studied which is found to be very small up to ~ 1.5 km above the surface for both types of the precipitating systems.

Uranium is a naturally occurring radioactive element. The higher concentrations of U in waters can cause chemical as well as radiological toxicity. In the present study 48 water samples were collected from the drinking/ground water sources in Narsipatnam Revenue division of Visakhapatnam District of Andhra Pradesh during pre and post monsoon seasons. Distribution of U has been measured and consequent ingestion dose was assessed. The observed U values range from

Increase in rainfall means a bumper crop production and erratic monsoon means a bad production of crops resulting into the loss of country's economy. The average rainfall for the El Nino years (strong and moderate El Nino) was compared with the normal rainfall for the years 1981 to 2016 during the four different seasons. The percentage change in seasonal rainfall during the El Nino years compared to normal rainfall was also computed for the seasons in different districts. Results revealed that the average rainfall during the S-W monsoon season during the El Nino years was less than the normal rainfall in all the district of Eastern UP. The departure was maximum in Barabanki district by 9.0 percent and lowest departure (0.4%) was recorded in Jaunpur districts. The average summer season rainfall during El Nino years from March to May was less than the normal rainfall in Eastern U.P. Maximum departure (20.3 percent) was recorded in Gorakhpur district and minimum departure (0.2%) over normal rainfall was recorded in Ballia district. The average rainfall during winter season during El Nino years from January to February was less than the normal rainfall in all the districts of Eastern U.P., The maximum departure (17.5%) was recorded in Ghazipur district. The average rainfall during the post monsoon (October to December) during El Nino years was almost less than the normal rainfall in Eastern U.P. during the years with El Nino compared to normal rainfall. El Nino unambiguously serves as a signal of deficit rainfall for the Eastern U.P. during the south west monsoon season and if it does not happen, leads to deficit annual rainfall. Analysis of long term data suggests an inverse relationship between El Nino and SW monsoon rainfall. However, there is no one to one relationship as El Nino years have not always produced severe drought. The average annual rainfall or S-W monsoon season rainfall were less than normal rainfall during the years with El Nino.

Present work attempts to use an easily available remote data to measure the spacio-temporal variation in the infestation on dominant mangrove species along Thane Creek, India. Satellite imageries of Sentinel 2 were processed in ArcGIS using Wide Dynamic Range Index (WDRI) and Normalized Difference Water Index (NDWI) to delineate the healthy and infested vegetation of mangrove. Out of total 47.03 sq.km. area of forest, in the post monsoon season of 2019, around 30.75 sq.km. was observed to be affected that amounts to be nearly 66 percent. The results obtained were found to be satisfactory after ground truthing. Thus the periodic phenomenon, though not harmful for human or mangrove vegetation, marks its significant occurrence in the ecological calendar of the creek ecosystem.

Arid region of India shows vast variation in climate and vegetation during last two decades. In order to analysis impact of monsoonal patterns on the vegetation indices of the arid zone, a three years (2015–2017) temporal series Moderate Resolution Image Spectrometer (MODIS) data for Pre & Post Monsoon was used for computing Normalized Difference Vegetation Index (NDVI). The cloud-free NDVI time series data are used to study the relationship between the rainfall pattern and the vegetation changes in Jodhpur District. ENVI and ArcGIS image processing software are used to evaluate and monitor the vegetation for the pre-monsoon and post-monsoon seasons for three years. Enormous changes were observed during pre and post monsoon temporal analysis. This study shows that MODIS NDVI data is best suited for quick vegetation assessment in arid region.

Unsystematic dumping of municipal solid waste affects soil, water and air by generating leachate, which effects the environment and human health. Considering this, present study investigates the leachate pollution index (LPI) of Indian landfills using leachate characteristics already published and by calculating the physico-chemical characteristics of landfill leachate from Chandigarh, SAS Nagar and Panchkula cities. LPI is a grade system (ranging from 5 to 100), which represents the capacity of leachate to contaminate the ground water through subsoil. Calculation of LPI shows that most of the Indian landfills have higher LPI than the acceptable limit (7.378). The error involved in LPI calculation was also studied using tricity (Chandigarh, SAS Nagar and Panchkula) LPI data. Higher sub-index and lower sub-index parameters were considered for error analysis. According to the results, ignoring higher sub-index parameters increases the error 79.2%, 68.5% and 67.8% in Chandigarh, SAS Nagar and Panchkula respectively. Whereas, LPI of landfills decreases 5 in Chandigarh, 7 in SAS Nagar and 5 in Panchkula. Based on the current study, It was observed that LPI values of Chandigarh, Mohali and Panchkula during pre- monsoon were 33.18, 26.17 21.94 and during post monsoon were 25.5, 20.32 and 19.49 respectively. it can be inferred that landfill leachate in India has significant potential to contaminate the groundwater resources. Considering this, the study also discusses some suitable remedial measures to reduce the ground water pollution by landfill leachate and demands more policy intervention to reduce the environmental and human health impact of MSW landfills.

The emissions from agricultural activities significantly impact the air quality at local (rural) and regional scales. The study monitored the near real-time concentrations of emission from agrarian activities, i.e., particulate matter (PM10, PM2.5, PM1), traces gases and VOCs, along with meteorological parameters in a rural area of Indo-Gangetic Plains (IGP). As different agricultural activities take place simultaneously in the region, sampling period was divided into three phases based on regional agricultural activities as HB (harvesting-burning) period, BTS (burning-tillage-sowing) period and PFS (pesticide-fertilizer spray) period. The highest mean concentration (± standard deviation) of particulate matter, i.e., PM10, PM2.5, PM1 was observed during HB period as 151.0 ± 52.3, 94.7 ± 32.9 and 41.0 ± 16.3 μgm-3 followed by PFS as 121.7 ± 49.1, 87.8 ± 35.5 and 39.7 ± 15.7 μgm-3 and BTS period as 92.5 ± 38.8, 63.5 ± 28.4, 26.6 ± 10.9 μgm-3 respectively. The mean concentration of NO (8.4 ± 3.4 ppb), SO2 (5.8 ± 1.2 ppb), CO (0.9 ± 0.3 ppm), O3 (12.5 ± 3.3 ppb) was also highest during harvesting-burning period. In the burning-tillage-sowing period, the mean concentration of NO2 (31.0 ± 2.9 ppb), benzene (2.8 ± 0.6 μgm-3) and o-xylene (2.1 ± 0.3 μgm-3) were highest. The data of crop residue burning fires showed that during HB period, around 34,683 active fires were there in the region (state of Punjab), whereas, in studied district, the number of fire counts were 635. During the HB period, around 70% of the air masses were originated within a 500 km area, whereas during the BTS and PFS period, 75% and 86% of air masses were originated from 500 km region, respectively. The ratio of PM2.5/PM10 during study period ranged from 0.63 to 0.72 and was observed highest during PFS period. The current study investigated the influence of agricultural activities on air quality during post-monsoon season in a rural area of Indo-Gangetic Plains to understand the impact of these activities on air quality in the region and plan mitigation strategies.

In this study, we have coupled measurements, modeling, and remote sensing techniques to better delineate the source characteristics and variability of air pollutants in Delhi primarily during the post-monsoon season in 2019. We show a comparison of ambient PM2.5 (particulate matter having aerodynamic diameter ≤2.5 μm) levels and associated elements during the post-monsoon with those during a relatively clean season of monsoon (experiencing frequent wet precipitation). Air-mass back trajectories from Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model have been used to infer the possible source pathways of PM2.5 impacting at the receptor site in Delhi. The average concentrations of PM2.5 during monsoon (June–July) and post-monsoon (October–November) were 42.2 ± 15.5 μg m−3 (range: 22–73 μg m−3) and 121.4 ± 53.6 μg m−3 (range: 46–298 μg m−3), respectively. The PM2.5 samples were analyzed for heavy and trace elements (Si, S, Na, Mg, Al, Cl, Ca, K, Ti, V, Cr, Mn, Fe, Ni, Cu, Br, Rb, Zr, and Pb) using an Energy Dispersive X-ray Fluorescence (ED-XRF) technique and their concentrations have been used to carry out the source-apportionment utilizing principal component analysis (PCA) tool. The PCA analysis has identified three major sources of fine aerosols including contributions from the sources viz. vehicular emission, biomass burning, coal combustion, secondary aerosols formation, soil dust, solid-waste burning and industrial emission. The source involving biomass burning contributed largely to the PM2.5 in post-monsoon season through long-range transport of large-scale agriculture-residue burning emissions (occurring in the states of Punjab, Haryana, and western part of Uttar Pradesh). The industrial emissions include primarily, medium- and small-scale metal processing industries (e.g. steel sheet rolling) in Delhi-National Capital Region. Traces of emission from coal based thermal power plants and waste incineration have also been observed in this study.

Introduction: Impact of heat on health of workers goes unrecognized by the virtue of the indispensable fact that every individual has varied perception and tolerance capacity. The present study determine the physiological signs with perceived subjective responses under the thermal stress.Materials and Methods: The study was spread on open field stone quarry workers (N = 934) during the summer (May to June), post monsoon (September to October), and winter (December to January).Results: In the summer months, dry bulb temperature range from 36.1 to 43.2°C and the distribution of Wet Bulb Globe temperature (WBGT) outdoor values were outlier-prone than normal distribution indicated heat vulnerability. The environmental effect on weighted average skin temperature (Tsk) local segmental Tsk and deep body temperature (Tcr) were greater than the effects that might be attributed to work severity. The tolerance time level in summer months (65 ± 13 min at WBGT 35 ± 2.3°C) was less than in other two season. About 85% of workers in summer, 68% in post monsoon and 79% in winter recorded working heart rate greater than 90 beats/min. Physiological and subjective responses to heat stress indicated that during summer month the workers complained of excessive sweating (93.5%), feeling of thirst/dry mouth (88.7%), elevated Core temperature (Tcr) (58.7%) and decreased working capacity (75.6%). The observation found that around 14% workers were vulnerable to heat stress and the workers had no knowledge to mitigate the heat related illnesses.Discussion and Conclusions: The stone quarry work as compared to other outdoor workers have environmental adversaries which becomes confounding variables in the study of such occupations. There was significant difference (p < 0.001) as far as the physiological and thermoregulatory responses were concerned in three different months of investigation.

In the present study, we have measured Black Carbon (BC) mass concentration over Ahmedabad city during the year 2017 and 2018. The measurements of BC have been carried out at various locations of the city during winter, summer, and post monsoon seasons. The concentration of black carbon has been found high in industrial areas and traffic junctions. In 2017, the measured high black carbon concentration was 80.73 µg/m3 and in 2018, it has increased to 83.7 µg/m3. Delta C value generally indicates wood burning as a BC source and its value is up to 20.38 µg/m3 in Ahmedabad during 2017-18. This study is helpful to estimate the major hotspots of BC mass concentration over the city and we have tried to find the major contributors to BC emission.

A Mesoscale Convective System (MCS), consisting of three Super Cellsformed over South-east Indian, is assessed in detail with satellite and ground baseddata-sets. The MCS under investigation generated a total of Ten (10) upwardelectrical discharges (9 Sprites and 1 Gigantic Jet) commonly named as TransientLuminous Events (TLEs). The TLEs were recorded from TLE observation stationlocated at Allahabad, India. The event occurred in the Post-Monsoon period of 2013on October 7, during 15-23 UT hours. The MCS was spread over a region of 25000 sq.Kilometers. A lowest cloud top temperature value of -84.7 0 C was observed in themature stage of the MCS, during 2130 UT hours, and the cloud top altitude wasreaching 17.6 km. The coldest cloud top region was covering an average area of13000 sq. Km. The measured Convective Available Potential Energy (CAPE) value was606.9 J/kg at 00 UT on 7 th October which dropped to 211 J/kg at 00 UT on 8 thOctober. The mean lightning flash rate during the formation and maturity stages ofthe MCS was around 46.03 min -1 . During the entire lifespan of the thunderstorm,peak currents were found to be reaching ±400 kA. Such high electric currents,extreme cold temperature and towering altitudes of the convective complexes showhow much a MCS is dynamically active and the TLEs which it produced are known toelectrically connect the lower atmosphere to the upper space environment.

The National Capital Region (NCR) of India, Delhi, has experienced high post-monsoon pollution along with several peak pollution episodes in recent years. Diwali, the festival of lights, which is among the biggest festivals of India celebrated during the post-monsoon season, is also considered a pollution event associated as it is with the lighting of a large number of firecrackers. 2016 Diwali pollution episode continued for a week creating severe discomfort to residents of Delhi, prompting the judiciary to ban the sale and use of firecrackers in Delhi from 2017 onwards. The current study analyzes different sectoral and temporal emissions contribution to the 2016 post monsoonal pollution episode over Delhi using a fully coupled chemical transport model. The findings of the study indicate that aerosols produced from crop residue open burning at the northwestern states contributed more than 60% of the total simulated surface concentration during the period under study. Model experimental simulations show that despite emissions from within the city, what explains the severity of pollution over Delhi during the period under consideration is an additional pollution load emanating from these intense crop open burning sessions from nearby areas. Further, model simulations show that while Diwali emissions can elevate the pollution load over Delhi, the effects do not last beyond 48 h. It is found that the stagnation of the pollutants several days beyond the 2016 Diwali day was due to favorable meteorological conditions like low surface temperature, lower boundary layer height, and weak northwesterly winds. The study shows that in order to improve air quality in Delhi during the post-monsoon period, mitigation efforts should target the adjacent rural areas, especially when there is massive burning of crop residue in those areas., WRF-Chem; Megacity pollution; Delhi; Biomass burning; PM2.5; Aerosols; Atmosphere modelling; Atmospheric physics; Air quality; Environmental analysis; Environmental assessment; Environmental pollution

Background Dengue is rapidly expanding climate-sensitive mosquito-borne disease worldwide. Outbreaks of dengue occur in various parts of India as well but there is no tool to provide early warning. The current study was, therefore, undertaken to find out the link between El Niño, precipitation, and dengue cases, which could help in early preparedness for control of dengue. Methods Data on Oceanic Niño Index (ONI) was extracted from CPC-IRI (USA) while the data on monthly rainfall was procured from India Meteorological Department. Data on annual dengue cases was taken from the website of National Vector Borne Disease Control Programme (NVBDCP). Correlation analysis was used to analyse the relationship between seasonal positive ONI, rainfall index and dengue case index based on past 20 years’ state-level data. The dengue case index representing ‘relative deviation from mean’ was correlated to the 3 months average ONI. The computed r values of dengue case index and positive ONI were further interpreted using generated spatial correlation map. The short-term prediction of dengue probability map has been prepared based on phase-wise (El Niño, La Niña, and Neutral) 20 years averaged ONI. Results A high correlation between positive ONI and dengue incidence was found, particularly in the states of Arunachal Pradesh, Chhattisgarh, Haryana, Uttarakhand, Andaman and Nicobar Islands, Delhi, Daman and Diu. The states like Assam, Himachal Pradesh, Meghalaya, Manipur, Mizoram, Jammu & Kashmir, Uttar Pradesh, Orissa, and Andhra Pradesh shown negative correlation between summer El Niño and dengue incidence. Two - three month lag was found between monthly ‘rainfall index’ and dengue cases at local-scale analysis. Conclusion The generated map signifies the spatial correlation between positive ONI and dengue case index, indicating positive correlation in the central part, while negative correlation in some coastal, northern, and north-eastern part of India. The findings offer a tool for early preparedness for undertaking intervention measures against dengue by the national programme at state level. For further improvement of results, study at micro-scale district level for finding month-wise association with Indian Ocean Dipole and local weather variables is desired for better explanation of dengue outbreaks in the states with ‘no association’.

Remote Sensing is a very reliable and expeditious technique for assessment and mapping of surface waterlogged areas. In this study band ratio based NDWI index (Normalized Difference Water Index) was used for extracting water pixels from optical imageries. To overcome the limitation of false positives and cloud penetration associated with optical imageries waterlogged areas was also extracted using SAR (Synthetic Aperture Radar) images. Thresholding of NDWI for optical image and Sigma0 for SAR images was done using their respective histograms to distinguish water and terrestrial features. The total surface waterlogged areas in the district was calculated by integrating the results from both optical and SAR images. It was found that surface waterlogged areas varies temporally from pre-monsoon to post-monsoon period in Rohtak district, Haryana. The surface waterlogged area for pre monsoon period is around 9.7 km2 and for post monsoon period is 17.86 km2. The canal and surface drain network in the district was digitized using the high resolution Sentinel 2 MSS images. Since most of the canals in the area are unlined a buffer of 500 m either side of the canals and surface drains was considered to assess the impact of seepage and leakage from canals and surface drains. It was found that more than 50% of the total surface waterlogged areas fall within this buffer, clearly indicating the contribution of leakages from canals and surface drains on surface waterlogging.

Introduction: Detection of dengue virus infection as soon as possible is critical for management of dengue virus infected patients. Immuno-chromatographic (ICT) tests are easy, cost effective method for dengue virus antigen detection.The sensitivity and specificity of ICT should compare with a gold standard test like RT-PCR. Aim of this study was to compare two test methods (ICT and RT-PCR), observe dengue serotype and seasonal impact on dengue infection.Methodology & result: The patients of Ibn Sina Medical College Hospital from October 2015 to October 2017 were tested for dengue NS1 antigen by ICT method. Out of 3201 sample tested 32.39% were found positive and 89 of which were re-tested for RT-PCR for comparison. Eighty eight of 89 NS1 positive cases showed positive by RT-PCR method giving an accuracy of 98.87%. Among the RT-PCR positive cases 45 were further analyzed for serotype. DEN-1, DEN-2 or both DEN- 1 and DEN-2 were found in 21, 23 and 1cases respectively. No cases of DEN-3 or DEN-4 were detected.Conclusion: This study showed that easily available and cost effective dengue NS1 antigen detection method (ICT) is as effective as molecular test (RT-PCR). DEN-1 and DEN-2 serotype were prevalent during last few years in Bangladesh. Continuous monitoring of dengue virus serotype is important for prevention and control of sudden epidemic by other serotype. Alert to be more during post monsoon when the peak of dengue virus infection was observed.Bangladesh Journal of Medical Science Vol.17(4) 2018 p.669-673

Groundwater qualities of coastal aquifers in the Ottapidaram taluk of Thoothukudi district, Tamil Nadu have been extensively monitored in post monsoon seasons in 2014 to assess its suitability in relation to domestic and drinking uses in four regions (N-S-EW). 34 groundwater samples were analyzed for various physicochemical attributes like pH, electrical conductivity (EC), Total dissolved solid (TDS), Na, K, Ca, Mg, Cl, HCO3, CO3, SO4, NO3, PO4. Most of these parameters fall under not permissible limits. The western part of the study area is highly polluted from K, Cl, HCO3 due to industrial/agriculture activity. The southern part is less polluted compared to other region. Hydrogeochemical processes controlling the water chemistry (Gibbs) indicates that most of groundwater samples fall at rock-weathering supremacy zone. Geochemical processes and temporal variation in the groundwater in this area are influenced by evaporation processes, ion exchange and dissolution of minerals. Major cation and anion ionic interaction indicate that weathering reactions have an inconsequential role in the hydrochemical processes of the shallow groundwater system. As a result of the hydrogeochemical analysis, seawater intrusion, aquifer rock weathering, sewer leakage are the overriding factors that determine the major ionic composition. The appropriate management plan is necessary to preserve precious groundwater resources.

A long-term study was conducted to study the impact of integrated nutrient management on soil quality in post-monsoon sorghum (Sorghum bicolor) at Solapur in Maharashtra State in Western India unde...

Spatio-seasonal water presence frequency and water depth change is tried to identify in two manmade reservoirs (Massanjore dam and Tilpara barrage) over Mayurakshi river of Eastern India. These reservoirs use to supply water for hydroelectricity and irrigation services. Multi-temporal image base analysis in three phases (phase 1:1987–1999; phase 2: 2000–2006 and phase 3: 2007–2016) clearly depicted that (1) in case of Massanjore dam (67.4 km2) water presence area in pre-monsoon season is declined from 44.13 to 23.54 km2 in between phase 1 and 3. (2) In post monsoon season, same is declined from 63.37 to 37.57 km2. (3) In case of Tilpara reservoir, water presence area is declined from 3.61 to 2.20 km2 in pre monsoon season and 3.76–2.67 km2 during post monsoon season since phase 1–3. Both average and maximum NDWI scores indicating qualitative depth of water in pre and post monsoon seasons have declined over time with significant rate (R2 ranges from 0.42 to 0.58). All these indicate growing attenuation of water availability within reservoirs. This may invite hardship to the stakeholders depends on the reservoir and ecological set up of the reservoir.

A longitudinal study in under constructing Manholes (considered as mosquito breeding trap of the study area) in a newly constructing road in the ward number 35 was conducted in the post monsoon period of 2016. Four species of mosquito population were available in the stagnant water of temporary breeding sites. Among them Cx. quinquefasciatus was the dominant species (98.6%) followed by Cx. tritaeniorhynchus (0.5%), Ar. subalbatus (0.5%) and Cx. fuscocephala (0.4%). Though the breeding sites were temporary and stayed until finishing the construction, yet the results indicated the abundant population of available mosquitoes including status of key species in the urban area of the city corporation.Bangladesh J. Zool. 45(2): 139-148, 2017

The monthly, seasonal and annual trends for five climatic parameters, such as rainfall, rainy days, temperature, relative humidity and sunshine hours were analyzed for the period of 1980–2015. The objective of this study was to detect the long term trend of climatic parameters of the study area. The non-parametric Mann–Kendall test and Sen’s slope estimators methods were used to determine whether there was a positive or negative trend in weather data with their statistical significance. The study area is characterized by high rainfall, receives an annual average rainfall of 3005 ± 820 mm, with an inter-annual variation 27% but analysis of long-term trends in the annual rainfall indicates a decreasing trend (− 14.31 mm year−1) and annual rainy days also significantly decreased (− 0.63 days year−1). In terms of seasonal rainfall, the pre-monsoon and monsoon months exhibited non-significant declining trends, while post monsoon months marginally increased. The result showed significant (P

A monsoon flood often happens on a huge scale on the East Coast of Peninsular Malaysia and has an immediate impact on the community. This article explores the community reconstruction orientation of the victims of the disaster of a post-monsoon flood in Malaysia. The study was carried out using an exploratory case study design on nine flood victims in Pahang, Malaysia. These informants were chosen by using purposive sampling, and data were gathered using the interview and observation methods. This study found three forms of community reconstruction orientation: (1) self-orientation, (2) family orientation, and (3) community orientation. Each orientation can be observed in a context through a participation indicator element, such as priority and commitment; readiness, knowledge, and skill; and social routine. A reconstruction effort from all parties ought to consider these orientations to avoid negative effects on the community. Thus, this study suggests that a partnership approach should be applied in the future to carry out community reconstruction. However, the findings cannot be generalized since it was a preliminary study.