Pre-monsoon Research Articles

Seasonal variation of mountain-valley wind circulation and surface layer parameters over the mountainous terrain of the northeastern region of India

Mountainous topography and solar elevation angle have a significant influence on the wind circulation and energy exchange over a complex region. Here, the seasonal variation of mountain-valley wind circulation (MVWC) and surface layer parameters have been presented over a hilly station of northeastern India. For the study, quick-response sonic anemometer data have been utilized. The solar elevation angle varies from 85° to 43° in different seasons and controls the MVWC over the terrain. MVWC was dominated in winter (WN), pre-monsoon (PM), and post-monsoon (PMN) seasons, while the synoptic wind predominates the wind direction over the terrain in monsoon (MN). In WN and PM, nighttime heat transmission from the atmosphere to the ground was −10 to −20 W m−2, while the minimum in MN and PMN was −3 to −7 W m−2. The net seasonal daily mean sensible heat flux (H) values from the surface to the atmosphere were 42 W m−2, 58 W m−2, 35 W m−2, and 34 W m−2 in WN, PM, MN, and PMN. In MN, the average daytime temperature was 8 °C, 0.5 °C, and 3 °C higher and at night was 9.5 °C, 2 °C, and 4.5 °C higher than the WN, PM, and PMN. In WN, PM, and PMN, the momentum flux had a higher value of about 2 to 3 h after the maximum value in H was attained at the 6-m and 10-m levels. The daytime turbulence kinetic energy was higher by 99%, 56%, 72%, and 93% than the nighttime during WN, PM, MN, and PMN.

Metal Contamination of Groundwater Sources in the Environs of a Tropical Estuary in South India.

The study was conducted to evaluate the metal pollution of groundwater sources in the residential areas in the surroundings of Kadinamkulam estuary, South India using the Heavy metal Pollution Index (HPI). For the study, forty one groundwater samples were collected during pre monsoon season from the dug wells of two gramapanchayaths and the concentration of heavy metals Cd, Cu, Zn, Cr, Pb and Fe were estimated and HPI was determined. Results of HPI show that 16.66% of groundwater sources in Azhoor and 21.73% in Kadinamkulam gramapanchayaths are in the low category and the remaining wells are classified in the high and medium category. The correlation analysis revealed that the sources of metals in groundwater in the study area are the leachates from the Kadinamkulam estuary, agricultural activities and solid wastes dumped in the nearby residential area. So the present study points out the metal pollution causes the degradation of the quality of groundwater which isthedrinking water source of these gramapanchayaths.

Monitoring of river health using aquatic insects: A study on Jatinga River, North East India

A biomonitoring study of River Jatinga located in south Assam, north east In-dia was conducted for the first time. The study aimed to evaluate water quality of the river in different stretches using aquatic in-sect as bioindicators. Insect samples were collected from selected sites of mid-stream and downstream of the river during monsoon- post monsoon, 2018 and winter- pre monsoon, 2019. A total of 25 families of aquatic insects recorded from 8 orders; Gerridae was eudominant in midstream across all the seasons with highest percentage in win-ter. Hemiptera, the most di-verse group was represented by six families with highest relative abundance. The study found that although both the sites were repre-sented by same functional feeding groups, there were seasonal and spatial varia-tions in the families of in-sects and their percentage occurrences. All the biotic indices, BMWPTHAI, SIG-NAL2 scores, EPT % and HFBI have shown relatively better quality of water of the River Jatinga in the mid-stream than that in the downstream during mon-soon and post monsoon sea-sons. Presence/absence and abundance of certain insect groups can provide infor-mation about health of the river.

Vertical and spatial distribution of elevated aerosol layers obtained using long-term ground-based and space-borne lidar observations

In this study, long-term ground-based and space-borne lidar measurements are used to understand the vertical (surface to 30 km) and spatial distribution of aerosols. First, the vertical distribution of aerosol extinction (AE) covering from near surface to 30 km is provided by combining Micro Pulse Lidar and Mie lidar observations co-located over a tropical station Gadanki (13.5oN, 79.2oE), India. The presence of two elevated aerosol layers, one between 2 and 5 km (lower troposphere) and the other between 15 and 18 km (Upper Troposphere and Lower Stratosphere (UTLS)), are simultaneously observed during the Indian summer monsoon season. Second, the spatial extent of these elevated aerosol layers obtained using Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) measurements reveals the presence of the lower layer extending from Africa to South Asia during both pre–monsoon and monsoon seasons. However, the UTLS layer is confined from middle-east to the China Sea only during monsoon season, also known as Asian Tropopause Aerosol Layer (ATAL). Third, aerosol sub-types obtained for these elevated aerosol layers using CALIPSO measurements reveals the dominance of polluted dust (44.6%) whereas the occurrence frequency of polluted continental, dust and elevated smoke is ~19.6%, 20.7% and 13.1%, respectively, for the lower layer. However, the frequency of volcanic ash and sulfate aerosols is ~50.3% and 49.7%, respectively, for the UTLS layer. Depolarization ratio (color ratio) values varies between 0.21 and 0.34 (>0.6) in the lower layer while the values >0.15 (<0.6) are present in the UTLS layer during monsoon season revealing the influence of non-spherical and coarse mode particles in the lower layer while spherical and fine mode particles in the UTLS region over the site. This information is very much useful in estimating reliable radiative forcing due to these elevated aerosol layers on the background atmosphere involved in assessing their impact on the regional climate.

Assessment of Environmental Parameters in Pre- and Post-Monsoons at Chabahar Bay, Gulf of Oman

This study is the first investigation to assess the variations of physical and chemical characteristics and biodiversity of planktons in offshore water column and chlorophyll-a and b, during the two monsoons at Chabahar Bay, to evaluate the water quality. To this end, 27 surface water samples in pre-monsoon (May, 2012) and totally 60 surface and deep water samples in post-monsoon (December, 2012) were collected from 9 and 10 stations at depths between 3.8 to 13.6 m in Chabahar Bay, respectively. The results showed that water salinity and pH with low variations were relatively higher in post-monsoon. The averages of water alkalinity levels in pre- (2.42±0.02 mmol H+/kg) and post- (2.44±0.01 mmol kg-1) monsoons were comparable to that of oceanic surface water (2-2.5 mmol H+/kg). In this study, 66 phytoplankton genus and species belonging to 13 groups were identified in pre-monsoon. Results demonstrated that nutrients were at higher levels inside the Chabahar Bay. Moreover, the physicochemical parameters of water samples were investigated and compared with international standards and data from other marine ecosystems. The results indicated that the water quality falls within the stipulated range of acceptability and sampling area can be classified as a good, stable, and healthy aquatic ecosystem.

Fluorescent whitening agents in commercial detergent: A potential marker of emerging anthropogenic pollution in freshwater of Bangladesh

Fluorescence whitening agents (FWAs), popular optical brighteners, are extensively used in commercial detergents to increase brightening of washed products. This study characterizes FWA in commercial detergents and quantifies its residue in sewerage linked lakes and the Ganges River water using three dimensional excitation emission matrix (3DEEM) fluorescence and Parallel Factor (PARAFAC) analysis. Concentrations of FWA in commercial detergents were varied between 0.57–12.84 mg/g, which was 0.23–5.14 times higher than the usage guideline of FWA in commercial and household detergents. Most of the detergents used DSBP, but some low priced detergents might not be used any FWA. Photodecay method was used for FWA analysis to circumvent the interferences of natural organic matter (NOM) and it showed about 12–23 times and 2–8 times higher values than the detection limit in lakes and the Ganges River water, respectively. DSBP (4,4'-bis(2-sulfostyryl) biphenyl disodium salt) concentration was ranged between 4.7–10.42 μg/L and 0.4995–2.59 μg/L in lakes and the Ganges River water, respectively and DAS1 (Disodium 4,4’-bis[(4-anilino-6-morpholino-1,3,5-triazin-2-yl)amino]stilbene-2,2’-disulfonate) concentration was insufficient to detect due to its rapid signal reduction under photo-irradiation and also interferences of NOM during fluorescence measurement. FWA concentration in the Ganges River was higher in the monsoon than pre monsoon and post monsoon. Seasonal variability of FWAs in the Ganges River might be related to high terrestrial derived input of organic matter into the river channel during monsoon. This study confirmed the potential ability of 3DEEM–PARAFAC to monitor FWA in freshwater as an anthropogenic molecular marker.

Physico-chemical Analysis of Pravara River water and its Impact on Human Health in Sangamner Tahashil (Maharashtra)

Water samples were collected from five different stations during pre monsoon season in Sangamner tahasil, Ahmednagar district. Different physicochemical parameters were measured and the samples were also analysed. Physicochemical parameters included pH, temperature, total alkalinity, total dissolved solids, electrical conductance (EC) bicarbonate, calcium, magnesium, Sodium etc. The quality of water play an important role concern to human being .Water covers 71% of Earth’s surface and is vital for all known forms of life Only 2.5% of the Earth’s water is fresh water, and 98.8% of that water is in ice and groundwater. Natural water, whether in the atmosphere, on ground surface, or under the ground, always contains dissolved minerals and gases as a result of its interaction with the atmosphere, minerals in rocks, organic matter, and living organisms. Reservoirs are one of the most important water resources used for water supply and irrigation. The results obtained from chemical analysis were compared with three standards namely BIS, WHO and ISI. Effect of industrial waste, municipality sewage and agriculture runoff on the river water were investigated . It is found that this water body is not suitable for drinking .so possible remedial methods should be adopted for this water resource for improving its quality.

THE IMPACT OF SEASONAL CHANGES ON HEAVY MINERALS CONCENTRATION FROM A PART OF EAST COAST OF INDIA

Pre and post monsoonal changes in the environment have led to a noticeable variation in sediment characteristics, heavy mineral concentrations and their distribution. The current study aimed to find out the effect of seasonal fluctuations on the concentration of heavy minerals along the coast and the variations in sediment textures and distribution. The study has revealed the effect of seasons on the sediments supply and its distribution along coast in the study area. The total heavy minerals concentrations are more in post monsoon than in pre monsoon and the concentration also increases from south to north in parts of the study area because of seasonal circulation of currents from south to north along the shore. The micro textural study of the heavy mineral grains from different locations in the study area revealed the mechanical and chemical erosions on the grain surfaces.

Unsupervised learning techniques in groundwater quality assessment of Mewat region, Haryana, India

Unsupervised learning techniques such as principal component analysis (PCA), cluster analysis (CA) were applied to the groundwater data of Mewat region (Haryana, India) collected in the pre monsoon season to identify the geochemical processes controlling groundwater chemistry. Thirteen physicochemical parameters were analyzed and were found to be above the permissible limits. The order of cation and anion concentration were found to be Na+ > Mg2+ > Ca2+ > K+ and Cl− > $${\text{NO}}_{3}^{ - }$$ > $${\text{SO}}_{4}^{2 - }$$ > $${\text{HCO}}_{3}^{ - }$$ > $${\text{CO}}_{3}^{2 - }$$ . The dominance of Na+ and Cl− in groundwater chemistry showed the salinity factor in the groundwater. PCA applied to the data set reduced the dimensionality to four significant factors accounting 76.66% of the total variance in the data set. The first factor can be assigned to alkalinity which originates due to the dissolution of geological minerals into the groundwater, second factor is assigned to salinity (due to salt water intrusion) and hardness which is caused by weathering of sedimentary rocks and calcium bearing minerals and other factors originate as a result of industrial wastes, domestic wastes and wastes from agricultural activities. CA classified 30 sampling sites into three clusters with relatively low salinity region, high salinity and very high salinity regions based on similar water quality characteristics.

Assessment of groundwater quality for drinking purposes in Amaravathi river basin

Groundwater assessment has become a demanding issue due to the scarcity of freshwater. Heavy textile based industrialization in Amaravathi river basin has caused over exploitation, decline in water levels and deterioration of water quality. Pre and Post monsoon analysis of samples from 31 observation wells over the period of thirty years (1988-2017) revealed that pH (8.18-8.22), Ca (67.87-73.79 mg/L), SO4 (122.37-125.64 mg/L), HCO3 (226.36-243.85 mg/L) and F (0.31-0.42 mg/L) are within the admissible limits and EC (0.05-0.50 d Sm-1), TH (489.4-518.29 mg/L), TDS (1021-1022 mg/L), Cl (304.68-306.51 mg/L), NO3 (24.90-26.21 mg/L)and Mg (78.76-82.75 mg/L) exceeds the admissible limits for the entire basin during Pre and Post monsoon periods. The quality of groundwater is classified as excellent (<25), good (25-50), Poor (50-75) very poor (75-100) or unfit (>100) for human consumption based on the calculated Water Quality Index values (WQI). Hydro chemical assessment of groundwater quality for domestic and drinking utility were worked out using WQI and ranged from 8.1 to 56.8 during Pre monsoon and 9.0 to 66.7 during post monsoon periods, indicating the water quality of excellent to poor and excellent to very poor categories for potable purposes during pre and post monsoon respectively. Instantaneously some proportion of excellent water quality wells are shifted into good quality wells over three decades.

Effect of Improved Agronomic Approaches on Growth and Yield of Redgram [Cajanus cajan (L.) Millsp.] under Rainfed Ecosystem

Background: Redgram is an important food legume which is largely cultivated under rainfed condition. In India rainfed agriculture contributes 80% of the total pulses production and the projected requirement will be 39 million tons by 2050 which necessitates an annual growth rate of 2.2%. The productivity has to be increased from the present level of 834 kg ha-1 to 1200 kg ha-1. With adoption of suitable agronomic management strategies the productivity could be increased to meet our demand and achieve self sufficiency in production. Hence the current study was carried out to increase the productivity of redgram under rainfed condition.Methods: Field experiment was conducted in farmer’s field in Madurai district, Tamil Nadu during North East Monsoon season of 2019 to study the effect of improved agronomic manipulations on growth and yield of redgram under rainfed ecosystem. Agronomic management approaches viz., nipping of primary branches at 45 and 60 days after receipt of soaking rain, high density planting at 30 cm × 30 cm in addition to recommended spacing of 60 cm × 30 cm and foliar application of 1% PPFM spray were compared with farmer’s practice in the redgram variety Co (RG) 7. Pre monsoon sowing has been taken up and the rainfall received during the cropping period was 521.7 mm received in 31 rainy days.Result: The field experimental results revealed that adoption of agronomic manipulation at the appropriate stage of the crop has increased the productivity of redgram. Nipping of primary branches at 45th day of the crop significantly increased the total number of productive branches, number of pods plant-1 and recorded the maximum seed yield of 1512 kg ha-1 (72 per cent increase over farmer’s practice) under rainfed condition.

Ozone variability: Influence by its precursors and meteorological parameters- an investigation

Surface observations on trace gases such as ozone (O3), oxides of nitrogen (August 2014–May 2017) and carbon monoxide (January 2016–May 2017) were used to investigate O3 chemistry. Study shows O3 concentration is high during winter with a mean value of 35.54 ± 7.16 ppbv and low concentration in monsoon with a mean value of 12.70 ± 3.55 ppbv. Oxides of nitrogen (NOx = NO + NO2) concentrations are high during pre-monsoon followed by winter, post-monsoon and monsoon. Mean carbon monoxide (CO) concentrations were observed to be 201.21 ± 36.90 ppbv, 222.61 ± 37.31 ppbv, 170.14 ± 14.34 ppbv, 249.59 ± 52.03 ppbv respectively during winter, pre monsoon, monsoon and post-monsoon. Study suggests that irrespective of seasonal changes, strong correlation coefficients (0.97–0.99) were observed between O3 and air temperature. Solar radiation showed an observable influence on surface O3 concentrations in the lower troposphere. The rate of change of O3 concentration during morning and evening hours at the study site were 3.6 ppbv/h and −3.9 ppbv/h respectively characterizing the site as sub-urban category. The mass concentrations of black carbon (BC) measurements (January–February 2016) were also used to understand its influence on CO and O3 concentrations. The BC showed a strong positive correlation (0.90) with CO whereas strong negative correlation (0.90) with O3. Study also indicates a strong influence of atmospheric boundary layer height on O3 and BC concentrations. Study revealed that emissions from crop residue burning during winter and forest fire during pre-monsoon have significant influence on enhancing CO concentrations at study site.

Heavy metals Assessment of Temple Ponds in Kanchipuram, Tamil Nadu, India

Heavy metals are a major environmental pollutant, they are slow, non-degradable material it affects the aquatic ecosystem. Heavy metal pollutant molecules arrive the pond water through anthropogenic activities, domestic waste, hospital wastes and temple wastes. The investigation was designed to study the seasonal spreading of specific heavy metals Iron (Fe), Copper (Cu), Lead (Pb), Arsenic (As) and Zinc (Zn)) in pond water. Seventeen pond water samples were collected during pre- monsoon (March 2017) and post monsoon (January 2018) period. The concentration of Iron in the pre monsoon greater than class A limit. The concentration of other prescribed heavy metal was less than central pollution control board standards in both the season. Hence pond water having a negligible amount of heavy metal pollution. This environmental observing and valuation research useful for managing and planning for the protection of pond.

Modelling groundwater level fluctuations in urban areas using artificial neural network

Rapid increase in urban areas due to rise in population and industrialization has increased the demand for water resources. Further, the changing land use pattern due to urban development is affecting the groundwater recharge. So, forecasting groundwater has become the basic condition for efficient groundwater resource development. The technique of Artificial Neural Networks (ANN) which has ability to model the complex water resources problems is used. ANN is a mathematical model which mimics the working of nerve cells. It is capable of recognizing the relationship between the input and output without understanding the physical connection between them. In this study, an ANN model was used to predict the pre and post monsoon groundwater fluctuation at the Tikri Kalan observation well situated in the West Delhi, India. The model comprises of three layers feed forward network trained with Levenberg-Marquardt (LM) algorithm and activated with log sigmoid function. Four different architectural networks are formulated and the optimum one is identified on the performance of statistical indices. The architecture of 3-15-1 is found to be generating the best results and can be employed in urban areas for forecasting groundwater fluctuation and managing water resources effectively.

Heavy metal analysis of groundwater of Thirukoviloor, Villuppuram, Tamil Nadu, India

Groundwater samples were collected from different localities in and around Thirukoviloor area, near Thenpennai River, Villuppuram District, Tamil Nadu during pre monsoon, monsoon and post monsoon respectively. A total of eight ground water Samples were collected and analyzed for heavy metals such as zinc, chromium, copper and iron using Atomic Absorption Spectrophotometer (AAS). The analytical data was compared with the guidelines prescribed by WHO. The Calculated values HPI 39.6. The result shows that the water quality of the study area is good and suitable for drinking purpose. The heavy metal contamination may due to the discharge of waste, industrial and municipal wastewater, disposal of solid waste by land filling and other anthropogenic influences in this region.

Spatio-temporal distribution of INSAT-3D AOD derived particulate matter concentration over India

Ground observations over 60–80 sites in India during 2014–18 reveal that Particulate Matter (PM) concentration exceeded National Ambient Air Quality Standard (NAAQS) by 1.5–2.5 times during Pre-Monsoon (PrM), Post-Monsoon (PoM) and Winter (Win) seasons only. Geographically Weighted Regression technique was employed to estimate PM2.5 and PM10 incorporating Aerosol Optical Depth (AOD) measured from geostationary orbit by Indian National Satellite (INSAT-3D) and ERA-INTERIM derived meteorological parameters. INSAT-3DAOD was well correlated with ground measured AOD (R2 > 0.75). Estimated PM found higher during PrM (PM2.5: 103.16 ± 31.39 μg m−3, PM10: 150.07 ± 43.13 μg m−3) than PoM (PM2.5: 58.72 ± 22.9 μg m−3, PM10: 127.17 ± 48.95 μg m−3) and Win (PM2.5: 71.02 ± 20.25 μg m−3, PM10: 96.86 ± 27.63 μg m−3). PM pollution was severe in West India (PM2.5: 87.44 ± 30.07 μg m−3, PM10: 148.13 ± 42.8 μg m−3), 1.2–1.5 times higher than least polluted North-East India. Spatial variability of PM distinctly discern the major prone areas that experience episodic events like dust (PM10 > 150 μg m−3) and biomass burning (PM2.5 >100 μg m−3). Overall country registered increase in AOD, PM10, PM2.5 by 52.34%, 36.23%, 36.58% respectively. Estimation accuracy produced by the model was satisfactory (R2 > 0.6; NMSE <0.25; −0.01 < FB < 0.09). The human footprint perceived by the PM2.5/PM10 ratio signifies that 60.95% PM10 is attributed to PM2.5 across the country and it was highest during Win (73.45%). The changes in spatial distribution of PM highlight that Indo-Gangetic Plain and coastal area in Southern India had undergone major industrialization, urban expansions which resulted in increase of PM2.5 by 50–125 μg m−3 during all seasons.

Assessment of atmospheric aerosols over Varanasi: Physical, optical and chemical properties and meteorological implications

The present paper reports the results derived from PM2.5 and PM10 concentrations during October 2016–May 2018 using MICROTOPS-II Sunphotometer and high volume samplers at Varanasi. Observed data were categorized and analyzed in order to understand the nature, source of origin and variability with seasons. Observations showed aerosol mass loading during the post-monsoon 2016 and winter 2017 as compared to the pre-monsoon 2018 values, which typically exceed national standard. The close relationships between PM2.5 and PM10 during post-monsoon (r = 0.571) and winter (r = 0.799) suggested that both type of particulates might have originated from the same source. Further, the PM2.5/PM10 indicated that the fine particles were dominantly present during the post-monsoon and winter season where as coarse particles were found dominant in the pre-monsoon season. The measured high values of aerosol optical depth (AOD) and angstrom exponent (AE) during post-monsoon and winter attributed to the accumulation of aerosols from sources and biomass/crop residue burning in the surrounding region and low dispersal due to shallow boundary layer and lower wind velocity. In contrast during pre-monsoon months the aerosols were accumulated as a mixture of transported from deserts and other far away regions including mineral from earth crust. The effect of meteorological parameters (temperature, wind speed and relative humidity) was also studied. Temperature did not show any relation during the pre monsoon when it was quite high, whereas during the winter months it showed negative trend with concentration. Wind showed negative correlation during the whole observation period. Relative humidity showed weak positive correlation during winter months for PM2.5 and PM10 where as PM2.5 did not show any relation during pre and post monsoon. PM10 showed weak negative relation during pre monsoon months. In order to understand elemental and ionic composition Scanning electron microscope (SEM) coupled with energy dispersive X-ray microanalyzer (EDX) analysis were done which showed dominant presence of C, F, O, Si, N, Na, K, Al, Ca and S. The following trend SO42− > NO3− > Na+> Ca2+> K+> Cl− > F− > Mg2+> Li+ was observed from the Ion chromatograph (IC) analysis. The source for these elements may have been different industrial activities, biomass burning and vehicular emissions. The results are useful for further planning of city developments and climate studies.

Water Quality Index for the Groundwater Analysis in Pedana Mandal, Krishna District, Andhra Pradesh, India

Water quality index is a mathematical method to applied for assess the water quality levels and for easy understand the water quality either in ground or surface water and using the standards, the present study was conducted in the pedana mandal groundwater quality for domestic and drinking purpose, there are 10 sampling stations were selected based on the more consumption and analyzed the physicochemical analysis in the pre monsoon season in 2019, the water quality parameters are pH, total hardness, Total dissolved solids, Calcium, Magnesium, Sulphtes, Chlorides, Fluorides and Iron, because each and every parameter is correlated to other parameter except iron and fluoride. The result reveals that average WQI value 428.02 is maximum and the value 137.24 is minimum in the study area, all water samples are high values and unfit for the drinking purpose, the values shows that 137.24 is poor water, the water is not suitable for direct consumption and required treatment before consumption.

Climatic Variation Water Quality Assessment of Selected Temple Ponds in Kanchipuram

Kanchipuram is the holiest city in Tamil Nadu, India. It has more number of Temple ponds, ponds having water has been selected for the study of climatic variations under physic chemical and biological parameters of water. The period of the study is pre monsoon march 2019 and post monsoon January 2020. The following parameters pH, electrical conductivity, dissolved oxygen, total dissolved solids, chlorides, sulphates, total hardness, calcium, magnesium, ammonical nitrogen, total nitrogen, total phosphate, total silica and biological parameter Total coliform count has been considered in the analysis. The results were linked with ISI-IS: 2296-1982 standards for surface water. The result shown that dissolved oxygen in all seventeen temple ponds has been greater than the standard limit in both the season. The remaining physico chemical, biological parameters were within the limit comparing with class B,C,D,E standard. Analysing the results the temple pond water appropriate in both the climate for bath, swim, fish culture, irrigation, etc. Climatic variation cannot cause the major changes in the pond water.

Assessment of heavy metals pollution in muscle of sole (Cynoglossus arel), spiny lobster (Panulirus homarus) and sediments in the northern coasts of the Oman Sea during pre and post monsoon

Concentrations of lead, copper, cadmium, and mercury were determined in sediments and two selected marine organisms (Cynoglossus arel and Panulirus homarus) collected from Jask Port, Darak Port, Pozm Port, Gulf of Chabahar and Gowatr Port in the north coasts of the Oman Sea during pre (spring) and post (autumn) monsoon in 2017. Heavy metals concentrations were determined by atomic absorption spectrophotometry. Results showed that there are statistically significant differences between studies concentrations in sediments during pre and post-monsoon at sample locations (p 0.05). In sediments and muscle of C. arel and P. homarus the trend in the mean metal concentrations was: Cu> Pb> Cd> Hg; Cu> Pb> Cd> Hg and Cu> Hg=Pb> Cd, respectively. Also, the trend in the mean metal concentrations in the samples was sediment > P. homarus> C. arel. However, paired t-test analysis for comparing heavy metal concentration in pre and post-monsoon showed only a significant difference for cadmium in the muscle of P. homarus (p<0.01). Totally, by comparing the results obtained from this study indicated that the accumulation of lead, copper, cadmium, and mercury in sediments and muscle C. arel and P. homarus at the Gulf of Chabahar and Jask Port is higher than other regions of the Iranian coasts along the Oman Sea which studied in current research.