Effect of different black pepper crop ages on the availability of nitrogen, phosphorus, and potassium.

Black pepper cultivation at different land backgrounds and fertility can affect crop productivity. This study aims to determine soil-plant nutrients for three pepper farms based on crop ages and the correlation of selected physical and chemical properties. Samples were collected in Kapit, Bintulu, and Sri Aman and analyzed for physical and chemical properties. Soil nutrient in Bintulu (6 months old) has revealed higher soil pH (4.95) with higher Fe (0.21 g/kg) and N (1.33 g/kg) contents that is caused by burnt earth residue from the burning of secondary forest. Sri Aman (12 months old) showed greater TOC (3.34%), P (0.0032 g/kg), and K (0.10 g/kg) benefitted from a long year of cultivation and proper pre-establishment earlier. Nutrient removal is high in Bintulu for Fe, Mn, N, and K, while Sri Aman for P is due to early harvesting before its mature phase, whereby the increase in nutrient accumulation in leaves to support berries. Correlation has revealed the role of soil pH in governing the availability of TOC, P, and K. The increasing soil pH increases the availability of P and K. Hence, the availability of N, P, and K is affected by numerous reasons, such as pH and crop management

Changes in air quality during and after large scale social restriction periods in Jakarta city, Indonesia

COVID-19 outbreak has constrained human activities in Jakarta, Indonesia during the large-scale social restriction (LSSR) period. The objective of this study was to evaluate the changes in the spatial variation of air pollutants over Jakarta during and after the LSSR periods. This study used satellite retrievals such as OMI, AIRS, and MERRA-2 satellite data to assess spatial variations of NO2, CO, O3, SO2, and PM2.5 from May to June 2020 (during the LSSR period) and from July to August 2020 (after the LSSR period) over Jakarta. The satellite images were processed using GIS software to increase the clarity of the images. The relationship between air pollutants and meteorological data was analyzed using Pearson correlation. The results showed the levels of NO2, PM2.5, O3, and CO increased by 59.4%, 21.2%, 16.2%, and 1.0%, respectively, while SO2 decreased by 19.1% after the LSSR period. The temperature value was inversely correlated with PM2.5, NO2, and SO2 concentrations. Furthermore, the backward trajectory analysis revealed that air pollutants from outland areas such as the east and southeast carried more particulate matter and gases pollutants, which contributed to the air pollution during and after the LSSR periods. As a whole, the COVID-19 outbreak had bad impacts on human health, but the increase in air pollutants levels after loosening the LSSR policy could also lead to a higher risk of severe respiratory diseases. This study provides new insight into air pollutant distribution during and after LSSR periods and recommends an effective method of mitigating the air pollution issues in Jakarta

Effect of COVID-19 movement control order policy on water quality changes in Sungai Langat, Selangor, Malaysia within distinct land use areas

For the first time in the 21st century, many nations have been forced to conduct a lockdown that restricts their industrial, transportation, and social activities to avoid the extensive COVID-19 spread. Therefore, our study aimed to analyze the status of water quality that was measured by suspended particulate matter (SPM) in Sungai Langat, Selangor, Malaysia using the remote sensing technique. The study was concerned with rivers located in distinct land-use areas such as high-density urban, low-density urban, and agricultural areas. The study period included before and after movement control order (MCO) periods that occurred in February 2020 and February 2021, respectively. The SPM levels in each period were calculated using the remote sensing technique through Landsat-8 OLI images then they were analyzed using statistical analysis. The results of the remote sensing technique showed the highest decrease of SPM levels during the MCO period was observed in Sungai Langat within a high-density urban area (34.1%). Then, the SPM levels in all Sungai Langat raised significantly after the MCO period with the highest change at 31.6%. Rainfall and erosion factors had a significant impact on the SPM level through natural processes but the COVID-19 restriction had a direct impact on the SPM level due to the restriction of industrial and social activities. The suspended activities have made the lower emission compared with before the COVID-19 period in 2019

Clustering analysis of pm2.5 concentrations in the South Sumatra Province, Indonesia, using the merra-2 satellite application and hierarchical cluster method

The air quality monitoring system is the most prominent tool for monitoring air pollution levels, especially in areas where forest fires often occur. The South Sumatra Province of Indonesia is one of the greatest contributors to haze events in Indonesia due to peatlands fires. It does not sufficiently possess a ground monitoring system to cover rural areas, and thus, delayed actions can result in severe air pollution within this region. Therefore, the aim of this current study is to analyze the distribution and classification of PM2.5 observed from 2019 to 2021 within the South Sumatra Province, Indonesia. The acquisition of PM2.5 data was from the Merra-2 Satellite with a spatial resolution of 0.5˚ × 0.625˚ and an hourly interval. The hierarchical cluster analysis (HCA) was applied in this study for the clustering method. The result of the study revealed that the daily mean of PM2.5 levels varied from 5.9±0.01 to 21.3±0.03 μg/m3. The study area was classified into three classes: high pollution areas (HPA), moderate pollution areas (MPA) and low pollution areas (LPA), based on the HCA method. The average level of PM2.5 observed in HPA was notably higher, at 16.8±0.02 μg/m3, followed by MPA and LPA. Furthermore, this study indicated that the highest level of PM2.5 was found during 2019, with a severe haze event in the study area due to the intensive burning of forests, bush and peatlands. As a whole, the output of this study can be used by authorities for air quality management due to forest fire events in a certain area

Effect of cement additive and curing period on some engineering properties of treated peat soil

Peat soil is characterized by its high content of decomposed organic matter. Majority of areas occupied by peatland have been developed for agriculture sectors such as pineapple cultivation and oil palm. Due to its geotechnical drawback characteristics such as highly compressibility and low shear strength, peat soil is classified as problematic soils and unstable for engineering structures. Lack of suitable and expensive price of lands, peatland will be an alternative option for future development. Prior to construction works, stabilization of peat soil should be performed to enhance its engineering characteristics. This paper presents the effect of cement and curing period on engineering properties of the cement-treated peat soil. Some engineering variables were examined including the compaction behaviour, permeability and unconfined compressive strength (UCS). The Atterberg limit test was also carried out to examine the influence of cement addition on peat soil. The cement-treated peat soils were prepared by adding varying amount of ordinary Portland cement (OPC) ranging between 0% and 40% of dry weight of peat soil. In order to examine the effect of curing, the treated samples were dried at room temperature for three and seven days while for UCS tests samples were extended to 28 days prior to testings. The results showed that the liquid limit of treated soil decreased with the increase of cement content. Maximum dry density (MDD) increased while optimum moisture content (OMC) dropped with the increase in cement content. Permeability of treated soil decreased from 6.2×10-4 to 2.4×10-4 ms-1 as cement content increase from 0% to 40%. In contrast, the UCS tests indicated an increase in uncompressive strength with the increase in cement contents and curing period. The liquid limit and permeability were also altered as curing periods were extended from three to seven days. This study concluded that geotechnical properties of peat soil can be stabilized using ordinary cement and by modification of the curing periods

Impact of covid-19 pandemic on traffic volume and air quality in urban areas

The large transmission of COVID-19 has resulted in a deep impact on the surrounding urban environments, especially on air quality and traffic flows. The objective of this study was to analyze air pollutant concentrations (PM10, SO2, NO2, CO, and O3) and traffic volumes at five congested districts (Bundaran HI, Kelapa Gading, Jagakarsa, Lubang Buaya, and Kebon Jeruk) within Jakarta city impacted by the large-scale social restriction (LSSR) policy. Air quality data during three periods; before, during, and after the LSSR at five observed districts was obtained from the Department of Environment of Jakarta using the Air Quality Monitoring (AQMS) tool. While vehicle speed data were obtained from the waze data during the study period. In this study, air pollutant data during three periods; before, during, and after the LSSR were compared with vehicle speed and meteorological data using a statistical analysis. Results revealed the mean traffic volume at all five districts has greatly reduced by 19% from before to during the LSSR period. It was consistent with the mean PM10, NO2, CO, and SO2 concentrations which also dropped about 46%, 45%, 30%, and 23% respectively. In contrast, the concentrations of air pollutants significantly increased after the LSSR period. During the LSSR period, the traffic volume was negatively associated with the O3 concentration (r = −.86, p < .01), it was different with before the LSSR periods where the traffic volume associated with CO (r = .88, p < .01) and NO2 (r = .89, p < .01). The broad analysis of changes in air pollutants and traffic volumes can be used by the authorities to arrange a good air quality management and an effective way for current and future scenarios

Effect of COVID-19 Movement Control Order Policy on water quality changes in Sungai Langat, Selangor, Malaysia within distinct land use areas

For the first time in the 21st century, many nations have been forced to conduct a lockdown that restricts their industrial, transportation, and social activities to avoid the extensive COVID-19 spread. Therefore, our study aimed to analyze the status of water quality that was measured by suspended particulate matter (SPM) in Sungai Langat, Selangor, Malaysia using the remote sensing technique. The study was concerned with rivers located in distinct land-use areas such as high-density urban, low-density urban, and agricultural areas. The study period included before and after movement control order (MCO) periods that occurred in February 2020 and February 2021, respectively. The SPM levels in each period were calculated using the remote sensing technique through Landsat-8 OLI images then they were analyzed using statistical analysis. The results of the remote sensing technique showed the highest decrease of SPM levels during the MCO period was observed in Sungai Langat within a high-density urban area (34.1%). Then, the SPM levels in all Sungai Langat raised significantly after the MCO period with the highest change at 31.6%. Rainfall and erosion factors had a significant impact on the SPM level through natural processes but the COVID-19 restriction had a direct impact on the SPM level due to the restriction of industrial and social activities. The suspended activities have made the lower emission compared with before the COVID-19 period in 2019

Potential of Normalized Difference Vegetation Index for Mapping of Soft Clay Area in Paddy Fields of Kedah, Malaysia

Mapping of soft clay area in paddy fields uses remote sensing and GIS technique is the fastest way to obtain an accurate location of soft clay in a large scale area. It can be an alternative way to change conventional method like in-situ observation that is expensive and labor intensive. Therefore, this study aimed to investigate the normalized difference vegetation index (NDVI) to map soft clay area in paddy fields Kedah, Malaysia. To analyze soft clay area comprehensively, the study was carried out in three different periods; before paddy planting, after paddy planting and harvest. Ground-truth data of soft clay area was collected from study area during fieldwork activity and compared with NDVI values that produced from Landsat 8 image. Result of study showed NDVI map in period of before paddy planting could be a good indicator for mapping soft clay area because it gave a higher accuracy value than the other periods, with overall accuracy (85%) and kappa coefficient (0,84). Total area of soft clay from the highest value was showed in period of before paddy planting (1.856,97 ha), followed by after paddy planting (656,73 ha) and harvest (401,85 ha) periods, respectively

Soil erosion assessment in Tasik Chini Catchment using remote sensing and gis techniques

Over many years, forested land transformation into urban, agriculture and mining areas within Tasik Chini Catchment become more intense. These activities have negatively affected the catchment through soil erosion and increased the amount of sediments that deposited into the lake. Hence, the present study aimed to estimate soil erosion risk within Tasik Chini Catchment integrating the Revised Universal Soil Loss Equation (RUSLE) model and remotely sensed geospatial data. The multispectral imagery from LANDSAT 8 was used to provide up to date information on land cover within the catchment. The result shows the majority of Tasik Chini Catchment is classified at very low class ( 150 ton ha−1 yr−1) with total area of 120.04 ha (2.30%). Tasik Chini Catchment is very susceptible to soil erosion especially on northwest and southeast regions, where the main sources of soil loss come from the agricultural, new settlements and mining activities. To conclude, the estimation of soil erosion model using remotely sensed data can be used to build sustainable development strategy within Tasik Chini Catchment in the future

Agricultural Land Evaluation Using GIS-Based Matching Method in Highland Areas for Oil Palm Cultivation

Oil palm (Elaeis guineensis) is one of the commodity crops and is mostly found in tropical lands. This study aimed to analyze the current and potential land suitability for oil palm using the geographic information system (GIS) technique. The study was conducted in the Ranau District, Sabah State, Malaysia. Field activity was carried out to collect soil samples and land information in the study area. Land suitability was then assessed using the matching method and GIS software was employed to produce a land suitability map for oil palm. The results indicated that the current land suitability classes in the study area were highly suitable (S1) with a total area of 99,118 ha (27.4%); moderately suitable (S2) with 110,108 ha (30.4%); marginally suitable (S3) with 109,533 ha (30.2%); currently not suitable (N1) with 2,728 ha (0.7%) and permanently not suitable (N2) with 40,693 ha (11.3%). Meanwhile, the potential land suitability classes showed 198,206 ha (54.7%) for S1; 123,281 ha (34%) for S2 and 40,693 ha (11.3%) for N2. Suitable areas that could be planted with oil palm included the gently sloping flank and the low gradient slope margin. Availability of nutrients and work capability were the dominant limiting factors in the study area. The outputs of this study recommend that the Ranau District has the potential for oil palm although it still needs land improvements for sustainable oil palm cultivation