In management of the Japanese scallop Mizuhopecten yessoensis culture, it is important to understand the phytoplankton bloom development in the coastal region of the Okhotsk Sea. Variations in food available to this benthic bivalve are a primary environmental factor affecting growth in nature. This paper determined the seasonal variability of Chlorophyll a (Chl a) at the scallop farming region in the Okhotsk Sea from 1998 to 2004 using satellite imageries. Satellite images were processed using default NASA coefficients and community-standard algorithms as implemented by Sea DAS. Spatial and temporal variation of Chl a was determined by EOF analysis. The Chl a concentration showed high seasonal and interannual variability. Peak of Chl a concentration occurred in spring followed by autumn and summer. This was evident in the Empirical Orthogonal Function (EOF) analysis. The spatial pattern of the first mode of EOF analysis of Chl a revealed intensified Chl a at the shelf and offshore areas in spring and autumn (51.8% of variance). The second mode explained 14.2% of the variance indicating enhancement of spring (April-May) Chl a pattern in the frontal area along the coast. Meanwhile, the third mode captured 9.0% of the variability demonstrating high Chl a extending seaward from the shelf area during late autumn. These seasonal variability of Chl a resulted from the variability in occurrences of physical processes associated with retreat of sea ice in spring, advection of Soya Warm Current in summer and intrusion of East Sakhalin Current in autumn.
Globally, around 1.3 billion tonnes of waste are generated annually, and solid waste management has thus become a major concern worldwide. There are projections of a 70% increase in waste generation from 2016 to 2050 owing to urbanization and the rapid growth of the global population. Estimates indicate that around 38,200 tonnes of waste are generated per day in Malaysia, and this volume of waste is significantly shortening the planned life spans of operating sanitary landfills in the country. Batu Pahat is a district in the state of Johor, Malaysia, with a relatively large population of 495,000 and with no record of an operational sanitary landfill. This study was conducted to identify and classify the most suitable sites for sanitary landfill developments in southern Peninsular Malaysia by means of the Analytical Hierarchy Process (AHP), which is recognized as a competent technique for multicriteria decision-making. The resulting landfill site suitability index map established 33.88 km2 of area coverage as very highly suitable for landfill development, while 353.86 km2 of area coverage was classified as unsuitable. Sites 1-6 were identified as the most suitable for landfill activities. Sites 1-5 are situated in agricultural land areas, while site 6 is in a forested land area; this implies public participation and the adoption of compensatory measures in the event of landfill development in these areas, given their socioeconomic importance. The six suitable sites are all at least 2000 m from rivers: 2000-3000 m for sites 1, 3, and 5 and > 3000 m for sites 2, 4, and 6. The six sites are all > 3000 m from fault zones and > 1000 m from flood-prone areas, meaning that occurrences such as fault movements and flooding will have minimal impact on the operational activities of landfills at these sites. The selection of sites 1-6 as very suitable for landfill development was associated with an overall accuracy rating of 93.33% and kappa coefficient score of 0.92 based on accuracy assessment analysis of all sites. This study will guide the actions of policymakers, city planners, and local authorities toward sustainable and environment-friendly landfill development and operation in Batu Pahat and other districts in the state of Johor.
Due to its effect on weather and its propensity to cause catastrophic incidents, climate change has garnered considerable global attention. Depending on the area, the effects of climate change may vary. Rainfall is among the most significant meteorological factors associated with climate change. In Malaysia, changes in rainfall distribution pattern have led to many floods and droughts events which lead to La Nina and El Nino where Johor is one of the states in southern part that usually affected. Thus, rainfall trend analysis is important to identify changes in rainfall pattern as it gives an initial overview for future analysis. This research aims to evaluate historical rainfall data of Johor between 1991 and 2020. Normality and homogeneity tests were used to ensure the quality of data followed by Mann-Kendall and Sen's slope analysis to determine rainfall trend as the rainfall data is not normally distributed (p > 0.05). Standardized precipitation anomaly, coefficient of variation, precipitation concentration index and rainfall anomaly index were used to identify rainfall variability and intensity while standard precipitation index was used to evaluate drought severity. The lowest annual rainfall recorded was 1725.07 mm in 2016 and the highest was 2993.19 mm in 2007. Annual rainfall and seasonal rainfall showed a declining trend although it is not statistically significant (p > 0.05). Results reveal that Johor experienced extreme wet and dry years, leading to drought and flood incidents. Major floods arose in 2006, 2007, 2008, 2010 and 2011 while driest years occurred in 1997, 1998 and 2016 which led to El Nino phenomenon. March and April were identified as the driest months among all. Thus, the findings from this study would assist researchers and decision-makers in the development of applicable adaptation and mitigation strategies to reduce climate change impact. It is recommended that more data analysis from more stations should be done in the future research study to obtain a clearer view and more comprehensive results.
Climate change and soil erosion are very associated with environmental defiance which affects the life sustainability of humans. However, the potency effects of both events in tropical regions are arduous to be estimated due to atmospheric conditions and unsustainable land use management. Therefore, several models can be used to predict the impacts of distinct climate scenarios on human and environmental relationships. In this study, we aimed to predict current and future soil erosion potential in the Chini Lake Basin, Malaysia under different Climate Model Intercomparison Project-6 (CMIP6) scenarios (e.g., SSP2.6, SSP4.5, and SSP8.5). Our results found the predicted mean soil erosion values for the baseline scenario (2019-2021) was around 50.42 t/ha year. The mining areas recorded the highest soil erosion values located in the southeastern part. The high future soil erosion values (36.15 t/ha year) were obtained for SSP4.5 during 2060-2080. Whilst, the lowest values (33.30 t/ha year) were obtained for SSP2.6 during 2040-2060. According to CMIP6, the future soil erosion potential in the study area would reduce by approximately 33.9% compared to the baseline year (2019-2021). The rainfall erosivity factor majorly affected soil erosion potential in the study area. The output of the study will contribute to achieving the United Nations' 2030 Agenda for Sustainable Development.