Nurul Izma Mohammed

Greenhouse gas emissions estimation from proposed El Fukhary Landfill in the Gaza Strip

ABSTRACT Landfills throughout the world are contributing to the global warming problem. This is due to the existence of the most important greenhouse gases (GHG) in landfill gas (LFG); namely, methane (CH4) and carbon dioxide (CO2). The aim of this paper is quantifying the total potential emissions, as well as the variation in production with time of CH4 from a proposed landfill (El Fukhary landfill) in the Gaza Strip, Palestine. Two different methods were adopted in order to quantify the total potential CH4 emissions; the Default methodology based on the intergovernmental panel on climate change (IPCC) 1996 revised guidelines and the Landfill Gas Emissions model (LandGEM V3.02) provided by the United States Environmental Protection Agency (EPA). The second objective of the study has been accomplished using the Triangle gas production model. The results obtained from both Default and LandGEM methods were found to be nearly the same. For 25 years of disposing MSW, El Fukhary landfill expected to have potential CH4 emissions of 1.9542 ± 0.0037 ×109 m3. Triangle model showed that the peak production in term of CH4 would occur in 2043; 28 years beyond the open year. Moreover, the model shows that 50 % of the gas will be produced approximately at the middle of the total duration of gas production. Proper control of Methane emissions from El Fukhary landfill is highly suggested in order to reduce the harmful effects on the environment. Implications: Although, GHG emissions are extensively discussed in the developed countries throughout the world, it has gained little concern in the developing countries because they are forced most of the time to put environmental concerns at the end of their priority list. The paper shows that developing countries have to start recognizing their fault and change their way of dealing with environmental issues especially GHG emissions (mainly Methane and carbon dioxide). The authors estimated the potential methane emissions from a proposed central landfill that has been approved to be built in Palestine, a country that is classified as a developing country.

Air Quality Profile in an Enclosed Car Park

Complaints on poor air quality in an enclosed car park have been raised up among the public, which might cause serious health effects to the drivers, passengers, and labours who are working at the premises. Improper design of mechanical ventilation systems in a car park would result in a poor indoor environment. The exhaust emission of motor vehicle contains a variety of potentially harmful substances encompassing carbon monoxide, nitrogen oxides, sulphur dioxide, hydrocarbons, and fine particulates. In Kuala Lumpur, there is a great demand but a short supply of lands and building spaces. Thus, a large multi-storey underground car parks is a common solution for both, the government and developers. Although the health effects of the motor vehicle emissions and ambient air pollution are already known, but due to the nature of enclosed multi-storey car parks, these health risks are predicted to be intensified. Thus, it is crucial to investigate and evaluate the status of the air pollution in the enclosed car parks with emphasis on sulphur dioxide (SO2) and nitrogen dioxides (NO2). Samples were collected in one of the famous shopping malls in Kuala Lumpur using a GrayWolf Advanced Sense Direct Sense; Toxic Gas Test Meters from 8 am until 5 pm on weekdays and weekends. The results demonstrate that the concentrations of SO2 and NO2 on weekends is higher than weekdays. Besides, the concentrations for both weekdays and weekends have exceeded the standard limit set by the Malaysian Ambient Air Quality Guideline (MAAQG).

Evaluating the Influence of Meteorological Parameters on Ozone Concentration Levels

Over the years, anthropogenic activities have led to the increase in air pollution concentration levels in the atmosphere, this persistent increase in pollution levels can be influenced by meteorological parameters. These parameters assist in the formation and transportation of air pollutants in the atmosphere. Hence, this study aims at evaluating the association between meteorological parameters and air pollutants. The analysis was carried out using Ozone (O3), Particulate matter (PM10), Nitrogen dioxide (NO2), temperature, humidity, wind speed, and wind direction data from 2006 to 2010, from two industrial air quality monitoring stations. Stepwise regression (SR) analysis was used to assess the influence of meteorological parameters in accounting for the variability of O3 concentration levels. The SR analysis showed that meteorological parameters accounted for more than 50 % of O3 variability. It can be concluded that different relationship between meteorological parameters and O3 can exist in different locations in the same region.

Multivariate analysis of monsoon seasonal variation and prediction of particulate matter episode using regression and hybrid models

Prediction of particulate matter (PM10) episode in advance enables for better preparation to avert and reduce the impact of air pollution ahead of time. This is possible with proper understanding of air pollutants and the parameters that influence its pattern. Hence, this study analysed daily average PM10, temperature (T), humidity (H), wind speed and wind direction data for 5 years (2006–2010), from two industrial air quality monitoring stations. These data were used to evaluate the impact of meteorological parameters and PM10 in two peculiar seasons: south-west monsoon and north-east monsoon seasons, using principal component analysis (PCA). Subsequently, lognormal regression (LR), multiple linear regression (MLR) and principal component regression (PCR) methods were used to forecast next-day average PM10 concentration level. The PCA result (seasonal variability) showed that peculiar relationship exists between PM10 pollutants and meteorological parameters. For the prediction models, the three methods gave significant results in terms of performance indicators. However, PCR had better predictability, having a higher coefficient of determination (R2) and better performance indicator results than LR and MLR methods. The outcomes of this study signify that PCR models can be effectively used as a suitable format in predicting next-day average PM10 concentration levels.

Regression and multivariate models for predicting particulate matter concentration level

The devastating health effects of particulate matter (PM10) exposure by susceptible populace has made it necessary to evaluate PM10 pollution. Meteorological parameters and seasonal variation increases PM10 concentration levels, especially in areas that have multiple anthropogenic activities. Hence, stepwise regression (SR), multiple linear regression (MLR) and principal component regression (PCR) analyses were used to analyse daily average PM10 concentration levels. The analyses were carried out using daily average PM10 concentration, temperature, humidity, wind speed and wind direction data from 2006 to 2010. The data was from an industrial air quality monitoring station in Malaysia. The SR analysis established that meteorological parameters had less influence on PM10 concentration levels having coefficient of determination (R2) result from 23 to 29% based on seasoned and unseasoned analysis. While, the result of the prediction analysis showed that PCR models had a better R2 result than MLR methods. The results for the analyses based on both seasoned and unseasoned data established that MLR models had R2 result from 0.50 to 0.60. While, PCR models had R2 result from 0.66 to 0.89. In addition, the validation analysis using 2016 data also recognised that the PCR model outperformed the MLR model, with the PCR model for the seasoned analysis having the best result. These analyses will aid in achieving sustainable air quality management strategies.

A Field Study of Mould Growth for Institute Higher Education Library Buildings in Malaysia

This paper is part of a PhD field study that focuses on the importance of conducting a visual inspection and evaluation of the indoor climates in libraries. Libraries contain a large amount of stored books that require a stable relative humidity to guarantee its preservation. Mould can survive and grow when indoor relative humidity is high and fungus is present all the time in the air that we breathe. Recording data through visual inspection and field studies. Its recorded the indoor relative humidity, temperature and lighting to assess mould growth problems. The assessment technique for this paper is based on guidelines survey and literature review. Visual inspection found few symptoms of mould growth that related to the amount of moisture appeared when the relative humidity in the library increases. Finally, the recording data for temperature and relative humidity demonstrate the result show that the stable indoor climate in the library building.