Wyniki wyszukiwania - Biblioteka Nauki

1

A comparison of soil CO2 efflux rate in young rubber plantation, oil palm plantation, recovering and primary forest ecosystems of Malaysia

100%

Mande H. K. , Abdullah A. M. , Aris A. Z. , Nuruddin A. A.

Polish Journal of Environmental Studies

|

2014

|

tom 23

|

nr 5

EN

Tropical deforestation and land conversion has been an environmental challenge over time and this is likely to have wide-reaching consequences for soil CO2 efflux. Such soil-carbon dynamic disturbances are critical in light of climate change, as tropical forests store almost 30% of global forest carbon. Soil CO2 efflux and environmental factors were determined in four different forest ecosystems of primary Dipterocarp forest, a 50-year-old recovering Dipterocarp forest, and a 5-year-old rubber and oil palm plantation using an automated soil CO2 chamber technique (Li-Cor 8100) with an in-built infrared gas analyzer. The forest sections are located within 1,800 m of each other while the plantation is 1,500 m away in the tropical lowland forest of Pasoh, Peninsular Malaysia. The aim was to determine the influence of environmental factors influencing soil CO2 efflux in relation to different forest ages and stand densities as a result of forest disturbance. Multiple regression analysis has been conducted on the relationship between soil CO2 and environmental factors. Soil CO2 efflux rate was found to range from 1.47-13.22 μmolCO2 m-2·s-1 (5.37 μmolCO2 m-2·s-1), 1.18-10 μmolCO2 m-2·s-1 (5.107 μmolCO2 m-2·s-1), 0.88-12.07 μmolCO2 m-2·s-1 (3.260 μmolCO2 m-2·s-1), and 2.33-7.89 μmolCO2 m-2·s-1 (4.678 μmolCO2 m-2·s-1) in the 50-year-old recovering forest, primary forest, oil palm plantation, and rubber plantation, respectively. Likewise, the highest forest biomass occurred in the primary forest and was followed by the 50-year-old recovering forest, rubber and oil palm plantation. Although the mean soil CO2 efflux rate did not differ significantly, differences were evident in the environmental factors such as soil temperature and moisture occurring at a range of 23 to 32°C and 15 to 35.56%, respectively, to influence soil CO2 efflux. The highest CO2 efflux rate was recorded in the 50-year-old recovering forest and followed by the primary forest, and rubber and oil palm plantation. The finding revealed a significant and strong correlation between soil CO2 efflux and soil temperature, moisture, and forest carbon input. Furthermore, the spatial variation in soil CO2 efflux was attributed to total above-ground biomass, below ground biomass, and forest carbon stock. We can conclude that the spatial variation in Soil CO2 efflux across the four different forest ecosystems is as a result of forest disturbance and land conversion triggering changes in environmental factors as well as forest carbon, thereby increasing microbial activity to emit soil CO2.

2

The relationship between daily maximum temperature and daily maximum ground level ozone concentration

88%

Abdullah A. M. , Ismail M. , Yuen F. S. , Abdullah S. , Elhadi R. E.

Polish Journal of Environmental Studies

|

2017

|

tom 26

|

nr 2

EN

Ground-level ozone is one of the dominant criteria pollutants that contribute to unhealthy days in ambient air measurements throughout Malaysia. In addition to VOCs and NOx, meteorological factors such as insolation and temperature influence the formation of ground-level ozone. For this reason, the relationship between daily maximum temperature and variation of ground-level ozone concentrations using 10 years of data (2000-10, excluding 2008) was scrutinized statistically at two stations representing urban and industrial areas in Terengganu State, Malaysia. We found that there is a positive linear correlation between maximum daily temperature and maximum daily ozone concentration with correlation coefficients of 0.684 and 0.605 for urban and industrial areas, respectively. Nevertheless, the long-term variation of daily maximum temperature and daily maximum ozone concentration for these two stations shows that the levels were higher in the industrial rather than the urban area. The results indicate that surrounding activities and temperature play vital roles in influencing ground-level ozone concentrations in Terengganu. Furthermore, ozone concentrations are highest for air masses characterized by dry, warm conditions during the southwest monsoon and are usually associated with the generation of haze episodes in the Malaysian Peninsula.

3

Source identification of heavy metals in particulate matter (PM10) in a Malaysian traffic area using multivariate techniques

75%

Elhadi R. E. , Abdullah A. M. , Abdullah A. H. , Ashaari Z. H. , Umar Kura N. , Gumel D. y. , Adamu A.

Polish Journal of Environmental Studies

|

2017

|

tom 26

|

nr 6

EN

This study was conducted to determine heavy metal concentrations in particulate matter (PM₁₀) and the source identification in the areas affected by traffic during the southwest monsoon from June to July 2014. Collection of the particulate samples was done at three sampling sites that have varying traffic densities (high, medium, and low). Samples were collected using a high-volume air sampler. Heavy metals in the particulate matter (PM₁₀) were assessed with inductively coupled plasma mass spectrometry. The results show that the mean concentrations of PM₁₀ for high-, medium-, and low-density traffic were found to be 207.63±7.82, 164.92±10.68, and 90.09±20.70 µg m⁻³, respectively. The concentrations in high- and mediumdensity areas were found to be significantly higher than 150 µg m⁻³ for 24 hrs as per Recommended Malaysian Air Quality Guidelines (RMAQG). The heavy metals found were dominated by Ba and Fe, followed by Cu > V> Zn > Pb > Mn > Cr> As > Ni >Cd > Co. A comparison of the concentrations of heavy metals with the United State Environmental Protection Agency (USEPA) and World Health Organization (WHO) guidelines revealed that As was higher than the standards in high- and medium-density areas. Cluster analysis (CA) and principal component analysis (PCA) were employed in the identification of the sources of metals for high-, medium-, and low-traffic densities. The CA identified three clusters for high-, medium-, and low-traffic densities, while PCA extracted four sources for high-, medium-, and low-traffic densities and the major pollution sources identified were vehicle exhaust emission, non-exhaust emission (brake and tire wear), and re-suspension dust.