Inter Monsoon Research Articles

Seasonal Dynamics of Trichodesmium and Phytoplankton Communities in the Eastern Arabian Sea: Winter Vs Spring-inter monsoon

The filamentous marine cyanobacterium Trichodesmium forms extensive blooms in tropical seas, where it plays an important role in nitrogen fixation. This study investigated Trichodesmium-associated phytoplankton in the Eastern Arabian Sea (EAS) during bloom and nonbloom conditions. Trichodesmium blooms over the continental shelf primarily comprised of T. erythraeum and T. thiebautii during the Spring Inter Monsoon (SIM) and T. erythraeum during the Winter Monsoon (WM). T. erythreaum blooms have rarely been reported from the north-east Arabian Sea during WM. Trichomes comprised of 143-1552 cells during the WM, with filaments ranging from 1339 to 13163 µm in length. Non-diazotrophic groups like diatoms and dinoflagellates were associated with Trichodesmium during both seasons within the bloom waters. The study found a novel symbiotic relationship between the heterocystous diazotroph Richelia intracellularis and Nitzschia sicula during WM blooms. This research expands knowledge of lesser-known phytoplankton species and their associations in the EAS.

Temporal Variation of Water Quality in Nilwala River, Southern Province, Sri Lanka

This study intended to investigate the temporal variation of water quality of the Nilwala river in the Matara district and to determine how the changes in rainfall affect to river water quality. Water samples were collected monthly from March 2019 to October 2019 (considering the second Inter monsoon season and first inter-monsoon season) at eight locations along the main river. Water quality parameters such as chemical oxygen demand (COD), biological oxygen demand (BOD), pH, electrical conductivity, temperature, alkalinity, hardness, chloride, nitrate and phosphate were analyzed using APHA 23rd edition of standard methods for the examination of water and wastewater. Experimental results were statistically analyzed by Two-way ANOVA using Minitab 17. The pH, EC, temperature, alkalinity and nitrate concentration showed statistically significant differences among the months (p<0.001) and those showed statistically significant differences with monthly rainfall (p< 0.001). There is a statistically significant relationship between rainfall and month (p<0.001). There is a statistically significant relationship between rainfall and sampling location (p<0.001). The highest rainfall was recorded from august to November (2nd inter-monsoon season) and secondly from March to May (1st inter-monsoon season) was recorded. Conductivity, pH and temperature were decreased from March to June. This may due to 1st inter monsoon rainfall. Conductivity was increased during august-november. Flooding can increase conductivity when it washes salts and minerals from the soil into the water. Nitrate concentration in the majority of the locations was increased during march-may. Total alkalinity, pH and nitrate were increased from august to November. The temperature of river water at all locations decreased from august- November. In conclusion, the pH, EC, temperature, alkalinity and nitrate concentration showed statistically significant differences among each month. It may due to variation of rainfall. Upper part of Nilwala River had a higher rainfall than lower basin.
 Keywords: Conductivity, Nilwala River, pH, temporal variation, Water quality

Tropical coral reefs in Sri Lanka are threatened due to the fluctuation of seasonal and interannual sea surface temperature.

The thermal stress of oceans causes coral bleaching, which induces loss of life in coral reefs and makes them exposed to other threats which directly and indirectly affect millions of other species that inhabit the reef. However, studies focusing on how those thermal stresses affect Sri Lankan fringing reef ecosystems are scarce. Hence, the patterns of long-term and short-term fluctuations of sea surface temperature (SST) over the shallow reefs around the country were studied by separating them into different zones as the eastern coast (Passikudha, Kayankerni, Adukkuparu, Parrot Rock, and Pigeon Island), the southern coast (Beruwala Barbarian, Hikkaduwa, Unawatuna, Ahangama, Mirissa, Madiha, Polhena, and Devundara), and northern-northwestern coasts (Valiththoondal, Palk Bay, Mannar, Kalpitiya, Thalwila, and Uswatakeiyawa). The 1km Multiscale Ultrahigh Resolution (MUR) Level 4 SST dataset was used to analyze seasonal and interannual SST variability from 2005 to 2021. The data were correlated with the Indian Ocean Dipole (IOD), Ekman velocity, and wind stress curl. The annual, seasonal, and monthly variability of SST on different coasts is significantly different. Higher increasing trends of SST from 0.0324 to 0.0411 ℃/year are observed on different coasts, and most of the time higher positive anomalies are recorded after 2014. The First Inter Monsoon (IM-1) and the month of April are more critical since they reach the maximum SST, and the minimum is in the North West Monsoon (NWM) and January. Significant positive relationships are recorded between the Indian Ocean Dipole (IOD) index and the monthly average SST on different coasts, which was robust on the southern coast. Therefore, tropical coral reefs in Sri Lanka are severely threatened due elevation of SST by global warming and climate variability.

Rainfall and Streamflow Trends in the Upper <em>Maduru Oya</em> Sub-watershed in Sri Lanka: A Comparative Study Using Different Statistical Methods

Analysis of historical data on rainfall and streamflow provides useful information for water resources management in a river basin. The objective of this study was to assess the variations and trend analysis of rainfall and streamflow data in the upper Maduru Oya sub watershed in Sri Lanka during a 30 year period (1989 October to 2019 September) using daily rainfall data from two gauging locations (Padiyathalawa and Bibile) and daily average streamflow data from one gauging location (Padiyathalawa). Descriptive statistics were used to assess the variations. The Mann Kendal Trend Test (MK test) and Innovative Trend Analysis method (ITA) were used to analyze the trend, and Sen’s Slope Estimator was used to assess the magnitude of the trend. Based on the MK test, most of the rainfall trends obtained are in an increasing direction, and streamflow trends are in a decreasing direction. Rainfall trends found in Padiyathalawa are not statistically significant. Annual, First Inter Monsoon, March, and May time scales of rainfall showed significant upward trends at Bibile (p<0.1) while streamflow in January, April, and September showed significant negative trends (p<0.1) at Padiyathalawa. The results displayed by all three tests were in very good agreement for rainfall. ITA results showed similar trend types of 77%, 95% and 41% at Padiyathalawa and Bibile rainfall and streamflow, respectively. A significant positive (ρ<0.01) strong and lower correlation between the trend value of the ITA and the Z value of the MK test were found for rainfall and streamflow, respectively. Changes in rainfall are not sufficient to explain the observed trends in streamflow. Therefore, future research should be directed at the causal aspects of streamflow change in this watershed.

Seasonal variation of atmospheric Pb sources in Singapore - Elemental and lead isotopic compositions of PM10 as source tracer

Southeast Asia has become a hotspot of anthropogenic particulate matter (PM) emissions due to increased coal combustion, high-temperature industrial operations, vehicular traffic, and agricultural biomass burning. Lead (Pb), a criteria pollutant, bound to such PM can be hazardous when inhaled, even at extremely low concentrations. Precise and accurate source apportionment of atmospheric Pb is thus, critical in order to minimize its exposure. This study investigates the sources of atmospheric Pb in Singapore aerosol samples (PM10) using Pb isotopes and elemental composition as tracers of contamination sources. PM10 aerosol sampling was conducted over a period of 1 year from June 2017 to May 2018 to capture the seasonal variations in sources of atmospheric Pb. Elemental concentrations reveal particularly high enrichment factors for Pb, Cu, V, Ni and Zn, especially when under the influence of southwest (SW) and inter monsoon (IM) winds. Pb isotopic ratios across the three seasons (206/207Pb = 1.147˗1.150 and 208/207Pb = 2.420˗2.428) are not significantly different. The Pb isotopic signatures and V/Ni ratios for all three seasons overlap with those of gasoline, diesel and ship emissions. Moreover, V/Pb values of more than unity for SW and IM winds suggest influence of transboundary coal combustion emissions particularly from Indonesia. Consequently, using Pb isotopic fingerprints and elemental ratios, we find that the primary sources of atmospheric Pb are vehicular & ship emissions, heavy oil combustion, transboundary coal combustion emissions, waste incineration and recirculation of historic leaded gasoline.

A biogeographic assessment of phytoplankton richness and composition in the Andaman Archipelago and the potential links to anthropogenic and environmental impacts: A multivariate approach

We report here a year-round baseline assessment on phytoplankton diversity and abundance from the pristine coastal waters of the Andaman Islands (September 2011–October 2012). A total of 84 phytoplankton species belonging to 47 genera were recorded from the North to South Andaman Islands. The maximum number of phytoplankton diversity (84 species under 47 genera) was recorded during the northeast monsoon (NEM) at a highly urbanized coastal environment like South Andaman Islands, whereas the minimum diversity (53 species under 34 genera) was recorded during the inter-monsoon (IM) period at the less anthropogenic activity sites viz. North and Middle Andaman Islands. All over seasons, the community composition of phytoplankton was mostly dominated by diatoms (45%–87%) followed by dinoflagellates (11%–46%) and blue–green algae (1%–35%). Besides, the abundance of phytoplankton was recorded as a gradual decrease from South Andaman to North Andaman Islands. The Canonical Correspondence Analysis (CCA) revealed the impact of physicochemical variables on phytoplankton assemblages. Thus, the temperature, salinity, and nitrite were the major environmental variables that influenced phytoplankton assemblage and distribution in the coastal waters of the Andaman Islands. The Principal Component Analysis (PCA) showed a strong variability of phytoplankton diversity in the South Andaman Islands (PC1: 32.6–36.2% variance). In addition, the Metric-multidimensional Scaling analysis also showed the gradual species intensity in the South Andaman than the Middle and North Andaman Islands.

Seasonal variations of particle number concentration and its relationship with PM2.5 mass concentration in industrial-residential airshed

The smaller particles that dominate the particle number concentration (PNC) in the ambient air only contribute to a small percentage of particulate matter (PM) mass concentration although present in high particle number concentration. These small particles may be neglected upon assessing the health impacts of the PM. Hence, the knowledge on the particle number concentration size distribution deserves greater attention than the particulate mass concentration. This study investigates the measurement of the particle mass concentrations (PM2.5) and PNC of 0.27μm < Dp < 4.50μm during the southwest (SW), inter-monsoon (IM) and northeast (NE) monsoons in the industrial-residential airshed of Skudai, Johor Bahru, Malaysia. The PM2.5 mass concentrations and PNC were measured using a multi-channel GRIMM Environmental Dust Monitor (GRIMM EDM-SVC 365) equipped with a global positioning system. Diurnal variations, statistical analysis and regression plots were utilised from a six-month hourly data set to examine the patterns of the PNC size distributions and its relationships with the PM2.5 mass concentration. The overall mean PM2.5 mass concentration was 21.85μgm-3, with the 24h mean values of 26.80μgm-3, 26.08μgm-3 and 13.76μgm-3 for the SW, IM and NE monsoons, respectively. It was found that the hourly mean of PNC was recorded at the highest concentration during the SW monsoon (373.20 # cm-3). The particles in the accumulation mode (Dp < 1.0μm) were the prevalent form of the particle number concentration (94-98%). The scatter plots between the PM2.5 mass concentration and particle number size distribution showed that the PNC mode of 0.27 < Dp < 1.0μm has the highest correlation value of r2 = 0.87 due to the emission from the anthropogenic activities. The results of this study highlight the importance of the PNC measurement in the seasonal variations of the PM2.5 pollution, indicating the significance of the regional-scale emission control actions in the local air quality management.

Application of Standard Precipitation Index (SPI) to Assess Rainfall variability in a Major Agricultural Area in Dry Zone of Sri Lanka

Agriculture in the dry zone of Sri Lanka is highly constrained by the inadequacy of irrigation water. The small village tanks located in these areas help farmers to cultivate their lands during dry periods by storing rainwater. However, the rainfall variability has made a considerable threat to functioning of these tanks and in providing expected benefits to the farmers. The objective of this study was to assess the climatic variability using 30-year (1989 to 2018) daily rainfall data from six rain gauging locations (Anuradhapura, Mahagalkadawala, Hingurakgoda, MahaIlluppallama, Girithale and Diyabeduma) in a small tank dominated area in the Dry Zone. Standard Precipitation Index (SPI) was calculated to assess the temporal variability of dry and wet extremes. Mann Kendal Trend Test (MK test) was used to analyze the trend of SPI and Sen’s Slope Estimator to assess the magnitude of the trend. The results of Anuradhapura, Diyabeduma and Mahagalkadawala show significantly increasing trend of SPI 12/ annual rainfall. According to the SPI, there were increasing trends in First Inter Monsoon in Anuradhapura and MahaIlluppallama, which have resulted an increasing rainfall trend in Yala season. Additionally, there was an increasing trend in Second Inter-Monsoon in Anuradhapura. These changes highlight that there are extreme rainfall events occurring in some seasons without making a significant impact in the annual rainfall pattern of the area.

Soil moisture index estimation from landsat 8 images for prediction and monitoring landslide occurrences in Ulu Kelang, Selangor, Malaysia

Soil moisture is one of the contributing factors that accelerates soil erosion and landslide events due to the increase in pore pressure which eventually reduces the soil strength. For landslide prediction and monitoring purposes, large-scale measurement involves estimating the soil moisture. However, estimation of soil moisture usually involves point-based measurements at a particular site and time, which is difficult to capture the spatial and temporal soil moisture dynamics. This paper presents the estimation of the SMI using Landsat 8 images for prediction and monitoring of landslide events in Ulu Kelang, Selangor. The selected SMI map for dry, moist, and wet seasons are obtained from climatology rainfall analysis over 20-year periods (1998-2017). SMI is assessed based on remote sensing data which are land surface temperature (LST) and normalized difference vegetation index (NDVI) using GIS software. Overall results indicated that rainfall distribution is high during inter-monsoon (IM), followed by northeast monsoon (NEM) and southwest monsoon (SWM) season. High rainfall distribution is a direct contributor towards SMI condition. Results from simulation show that April 2017 is known to have the highest SMI estimation season and selected to be the best SMI mapping parameter to be applied for prediction and monitoring of landslide events.

Role of riverine inputs, low saline plume advection and mesoscale physical processes in structuring the Chlorophyll a distribution in the western Bay of Bengal during Fall Inter Monsoon

This study delineates the role of small and medium river inputs, Low Saline Plume Advection (LSPA) and eddies in hydrography alteration and Chlorophyll a (Chl. a) in the Western Bay of Bengal. Samples were collected across five transects viz: Hooghly (HO), Mahanadi (MN), Rushikulya (RK), Visakhapatnam (VSKP) and Godavari (GD) during Fall Intermonsoon. Each transect consists of 7 or 8 locations from inshore to offshore. LSPA propagates southward concordance with the East India Coastal Current (EICC) and its southward flow strengthened by a cold-core eddy. LSPA results in the intermittent low salinity in the cross-shore section of HO, MN and RK. Upper layer Chl. a is 2–3 folds higher in inshore and in LSP-influenced locations than in its adjacent stations. The present study identified Double Chlorophyll a Maxima (DoCM) in LSPA-influenced slope regions of MN and RK. DoCM is less known in the BoB. DoCM has both the Surface Chl. a Maxima (SCM) and Subsurface Chl. a Maxima (SSCM). SSCM layer is relatively shallow and intense in slope and offshore regions of MN and RK due to their closeness with cold-core eddy. The present study highlights that freshwater discharge from small and medium rivers impacts hydrobiology around 10–50 km from the shore depends on the magnitude of river influx. LSPA is away from the local inputs and impacts hydrobiology (>500 km) along the path. EICC and eddies together regulated the direction of LSPA. Existing eddies nature alters vertical hydrobiology in slope and offshore regions.

Diversity of Marine Eukaryotic Picophytoplankton Communities with Emphasis on Mamiellophyceae in Northwestern Philippines

Eukaryotic picophytoplankton (EPP) play vital roles in primary productivity and biogeochemical cycling in the marine environment. In this study, we explored the diversity of EPP communities in two different embayments and the shifts in their community structuring during monsoonal reversal in the northwestern Philippines. Water samples were collected weekly from late northeast (NE) monsoon to intermonsoon (IM) or summer periods (February–April 2019) in Bolinao, Pangasinan, and once in January in Masinloc, Zambales. EPP community profiling was done through targeted sequencing of the V4 region of the 18S rRNA gene. Grouping of samples based on physicochemical parameters was consistent with that of community beta diversity, suggesting strong clustering between late NE and IM periods. This exhibits short- term community shifts of EPPs possibly associated with the monsoonal transition. Specifically, overall EPP alpha diversity increased towards summer coupled with increased temperature and lower nutrient concentrations. NE monsoon samples from Bolinao and Masinloc were dominated by Chlorophyta and Stramenopiles, while Prymnesiophyta, Rhizaria, and Picozoa dominated the IM period samples in Bolinao. Specifically, the prasinophytes (Chlorophyta) Ostreococcus and Nannochloris distinguished the late NE communities of Masinloc and Bolinao, respectively. Phylogenetic analysis of dominant photosynthetic EPP further revealed the presence of Clades B5 and A1 of Micromonas, as well as Clades B and E of Ostreococcus. Tree topology of Ostreococcus diversity suggests the presence of a clade distinct from other established clades, possibly indicating novel diversity in the West Philippine Sea. This is the first report of these major picophytoplankton in Philippine waters, suggesting their significance and potential “hidden” diversity, which warrants further studies.

SEASONAL VARIATION OF PARTICLE NUMBER COUNT (PNC) AT THE COASTAL ENVIRONMENT IN PENINSULAR MALAYSIA USING BOOSTED REGRESSION TREES (BRTS)

The concentrations of airborne particulate matter (PM) is often measured as a mass concentration. However, the other way to express particulate matter is by using the Particle Number Count ([PNC]) concentrations. This study aims to analyse the seasonal variation of airborne particulate matter in terms of [PNC] by using R packages and the Boosted Regression Trees (BRTs) technique. The study was conducted at IOES, Universiti of Malaya in Bachok, Kelantan. The monitoring was important to understand the variability of seasonal effects due to different seasons. In this work, only the datasets for three seasons (Inter Monsoon, North East Monsoon and South-West Monsoon) were analysed involving 25,958 data. The air quality monitoring equipment involved was the particle counter Environment Dust Monitor GRIMM Model 180 and a weather station for recording the meteorological parameters. The data analysis was completed by using R software and its package for evaluating seasonal variability and providing the statistical analysis. The relationship between variables was studied by using the Boosted Regression Tree (BRT) technique. The interaction between independent variables towards the [PNC] in different seasons was discussed. The best setting result of BRT model evaluation R² is 0.22 (North-East Monsoon), 0.87 (Intern monsoon 1), and 0.59 for South West Monsoon which indicated that the model developed is acceptable except for NEM and intern monsoon seasons. Temperature (57 %) and wind direction (67%) were found to be the highest factor influenced by the formation of [PNC] concentrations in this area. Finally, good results indicated that BRT technique is an acceptable way to analysed air pollution data.

Tropical rainfall trend and stationarity analysis

Abstract Climate change is most likely to cause changes to the temporal and spatial variability of rainfall. A trend analysis to investigate the rainfall pattern can detect changes over temporal and spatial scales for a rainfall series. In this study, trend analysis using the Mann–Kendall test and Sen's slope estimator was conducted in the Kelantan River Basin, Malaysia. The Kwiatkowski–Phillips–Schmidt–Shin (KPSS) test was applied to evaluate the stationarity of the rainfall series. This basin annually faces onslaughts of varying year-end flooding conditions. The trend analysis was applied for monthly, seasonal and yearly rainfall series between 1989 and 2018. The temporal analysis results showed that both increasing and decreasing trends were detected for all rainfall series. The spatial analysis results indicated that the northern region of the Kelantan River Basin showed an increasing trend, whilst the southwest region showed a decreasing trend. It was found that almost all the rainfall series were stationary except at two rainfall stations during the Inter Monsoon 1, Inter Monsoon 2 and yearly rainfall series. Results obtained from this study can be used as reference for water resources planning and climate change assessment.

Chemical characteristics of rainwater in the tropical rainforest region in northwestern Borneo

A comprehensive study of the chemical composition of rainwater was carried out from October 2016 to September 2017 in the equatorial tropical rainforest region of northwestern Borneo. Monthly cumulative rainwater samples were collected from different locations in the Limbang River Basin (LRB) and were later categorized into seasonal samples representing northeast monsoon (NEM), southwest monsoon (SWM), and inter-monsoon (IM) periods. Physical parameters (pH, EC, TDS, DO, and turbidity), major ions (HCO3-, Cl-, Ca2+, Mg2+, Na+, and K+) and trace metals (Co, Ni, Cd, Fe, Mn, Pb, Zn, and Cu) were analyzed from collected rainwater samples. Rainwater is slightly alkaline with mean pH higher than 5.8. Chloride and bicarbonate are the most abundant ions, and the concentration of major ions in seasonal rainwater has shown slight variation which follows a descending order of HCO3-> Cl-> Na+ > Ca2+ > Mg2+ > K+ in NEM and Cl- > HCO3- > Na+ > Ca2+ > K+ > Mg2+ in SWM and Cl- > HCO3- > Na+ > Ca2+ > Mg2+ > K+ in IM period. Trace metals such as Fe and Ni have shown dominance in seasonal rainwater samples, and all the metals have shown variation in concentration in different seasons. Variation in chemical characteristic of seasonal rainwater samples identified through piper diagram indicates dominance of Ca2+-Mg2+-HCO3- and mixed Ca2+-Mg2+-Cl- facies during NEM, SWM, and IM periods. Statistical analysis of the results through two-way ANOVA and Pearson's correlation also indicates significant variation in physico-chemical characteristics. This suggests a variation in contributing sources during the monsoon seasons. Factor analysis confirmed the source variation by explaining the total variance of 79.80%, 90.72%, and 90.52% with three factor components in NEM, SWM, and IM rainwater samples with different loading of parameters. Enrichment factor analysis revealed a combined contribution of marine and crustal sources except K+ which was solely from crustal sources. Sample analysis of backward air mass trajectory supports all these findings by explaining seasonal variation in the source of pollutants reaching the study area. Overall, the results show that the chemical composition of seasonal rainwater samples in LRB was significantly influenced by natural as well as anthropogenic processes. These include (long-range and local) industrial activities, fossil fuel combustion, forest burning, transportation activities including road transport and shipping activities, and land-derived soil dust along with chemical constituents carried by seasonal wind.

Subsurface chlorophyll maxima in the North Eastern Arabian sea: Simulation on impact of warming

Abstract Stratified tropical oceanic systems are in general observed with Subsurface Chlorophyll Maxima (SCM), which was identified as light adaptation of shade-loving picophytoplankton groups. Apart from the light adaptation strategies of phytoplankton, the physical properties of water masses have significant role to hold the phytoplankton in particular layers. The present study gives theoretical explanation on the influence of fluid properties of water on the settling velocities of micro-nano phytoplankton groups, which contribute the SCM. The data and samples were collected from North Eastern Arabian Sea (NEAS) during March (Spring Inter Monsoon), by means of Bio-Argo floats, CTD and remote sensing. The analysis gives indications to the possible strengthening of SCM in the scenario of warming and enhanced stratification. The study conducted simulations using basic stoke’s equations on most abundant species of the area and found that the fluid density has a significant role in the settling of non-motile, suspended phytoplankton groups, irrespective of their cellular density. The simulations show strong decelerations at the same depths, in the upper part of the pycnocline but with varying settling velocity. A numerical expression derived based on curve fitting and multiple regression analysis substantiates the influence of vertical density on SCM. The sensitivity analysis (Global sensitivity Analysis) indicates warming trend in NEAS strengthening the stratification, which in turn influences the concentration in SCM and is capable of altering the primary production.

Seasonal Windstorm Pattern and Damages in Peninsular Malaysia 2018

Natural disasters cause damages, losses and social problems. Windstorm has been a major contributor to the losses and damages to the sustainability of human lives and built environment. The formation of seasonality in Southeast Asian countries are affected by the monsoon which brings large scale seasonal interchange of wind pattern. The trend of windstrom events is not properly recorded in any recent or previous studies.This paper analyses the windstorm pattern in Peninsular Malaysia. NCEP FNL Operational Model Global Tropospheric Analyses and Meteorological Operational (MeTOP) datasets were used to retrieve the wind speed and the direction during the study period. Both datasets show approximate value of wind pattern based on reported events. Southeast-monsoon (SM), Northeast-monsoon (NM) and Inter-monsoon (IM) impacts are considered in this study. The result exhibited the highest windstorm event was Southeast-monsoon, and the highest wind speed is from NS that is 5.96 m/s to 6.23 m/s. While the highest wind speed outside of peninsular that blows and impacts the land is from SM and the value calibrates in between 9.20 m/s to 10.96 m/s.

Long-Range Transport and Local Emission of Atmospheric PM2.5 in Southern Region of Peninsular Malaysia

The excessive inhalation of pollutant particles with aerodynamic diameters less than 2.5 µm (PM2.5) results in risking the human respiratory health. The aim of this study is to investigate the possible pathways of long range and local tranportation for PM2.5 sources. The route patterns are analyzed by using the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT 4.9) software during August 2017 to January 2018, covering three main monsoon seasons of Malaysia; southwest (SW), intermonsoon (IM) and northeast (NE) monsoon. This study represents the 72 h air mass backward trajectories in a mixed commercial-residential-industrial site of Skudai, Johor Bahru. The identified source origins are largely varied with different monsoon seasons and meteorological factors. The air-flow at different altitudes results in different effects, as the trajectory at height 500 m contributes to the greatest impact on the pollution level. The potential sources were generally from the Sumatera, Indonesia, during SW monsoon and China, during NE monsoon. The PM2.5 exceedance pattern in the Skudai area is also strongly influenced by the localized circulation, anthropogenic emission and dispersion characteristics. The increased levels of PM2.5 are predominantly contributed by the primary sources of vehicular emissions and industrial activities.

Spatial and statistical trend characteristics of rainfall erosivity (R) in upper catchment of Baram River, Borneo.

The upper catchment region of the Baram River in Sarawak (Malaysian Borneo) is undergoing severe land degradation due to soil erosion. Heavy rainfall with high erosive power has led to a number of soil erosion hotspots. The goal of the present study is to generate an understanding about the spatial characteristics of seasonal and annual rainfall erosivity (R), which not only control sediment delivery from the region but also determine the quantity of material potentially eroded. Mean annual rainfall and rainfall erosivity range from 2170 to 5167mm and 1632 to 5319MJmmha-1h-1year-1, respectively. Seasonal rainfall and rainfall erosivity range from 848 to 1872mm and 558 to 1883MJmmha-1h-1year-1 for the southwest (SW) monsoon, 902 to 2200mm and 664 to 2793MJmmha-1h-1year-1 for the northeast (NE) monsoon and 400 to 933mm and 331 to 1075MJmmha-1h-1year-1 during the inter-monsoon (IM) period. Linear regression, Spearman's Rho and Mann Kendall tests were applied.Considering the regional mean rainfall erosivity in the study area, all the methods show an overall non-significant decreasing trend (- 9.34, - 0.25 and - 0.30MJmmha-1h-1year-1, respectively for linear regression, Spearman's Rho and Mann Kendall tests). However, during SW monsoon and IM periods, rainfall erosivity showed a non-significant decreasing trend (- 25.45, - 0.52, - 0.40, and - 8.86, - 1.07, - 0.77MJmmha-1h-1year-1, respectively) whereas in NE, monsoon season erosivity showed a non-significant increasing trend (14.90, 1.59 and 1.60MJmmha-1h-1year-1, respectively). The mean erosivity density ranges from 0.77 to 1.38MJha-1h-1year-1 and shows decreasing trend. Spatial distribution pattern of erosivity density indicates significantly higher occurrence of erosive rainfall in the lower elevation portion of the study area. The spatial pattern of mean rainfall erosivity trends (linear, Spearman's Rho and Mann Kendall) suggests that the study area can be divided into two zones with increasing rainfall erosivity trends in the northern zone and decreasing trends in the southern zone. These results can be used to plan conservation measures to reduce sediment delivery from localized soil erosion hotspots.

Determination of the Sediment Contamination Level in Dangli Waters of Langkawi UNESCO Global Geopark, Kedah, Malaysia

Dangli Waters ecosystem is located at the north of Langkawi UNESCO Global Geopark. Apparently, this area is currently experiencing a significant deterioration of marine habitat. Therefore, 14 stations were set up in this study area to investigate the sediment for metal contents discharged into Dangli Waters using the ecological risk assessment. The sediment samples were collected during four seasons, namely South West Monsoon, First Inter Monsoon, North East Monsoon and Second Inter Monsoon. The spatial distribution pattern of heavy metals in sediment was properly determined as well as the seasonal variation of the contamination. From the results obtained, the average concentration of each heavy metal distributed in the surface sediment of Dangli Waters can be written in decreasing order as Fe>Cr>As>Co>Cd. From the observation, heavy metal concentrations of As was recorded the most higher profiles near to the cement plant production area. Meanwhile, for the pattern of seasonal changes, FIM season was defined as the season with higher concentrations of all metals in the surface sediment compared to other seasons. This is due to highly rainfall distribution and water runoff during this period, leading an increase of sediment deposition into the Dangli Waters. According to the contamination factor (Cf) for each metal, it was shown that some heavy metals such as As were at a risky level with the Cf value was higher than 6 (Cf >6). However, the degree of contamination (Cd) for each station was classified as moderate (7 ≤ Cd < 14), except for ST2 which showed a low degree of contamination.

Seasonal and spatial variation of surface current in the Pemba Channel, Tanzania.

The surface current speeds within the Pemba channel were examined using 24 years of drifter data received from the Global Drifter Program. This study aimed to uncover varying surface current in the Pemba Channel in different seasons. The results revealed the Pemba Channel experiences relatively higher median surface current speeds during the southeast (SE) monsoon season compared to the northeast (NE) and inter-monsoon (IN) periods. The strongest current speeds were confined in waters deeper than 200 meters between ~39.4°E and 39.7°E. These results prove that surface currents from the drifters can be used to uncover the patterns of surface circulation even in areas where in-situ measurements are scarce.