Southeast Asia experiences frequent fires in fuel-rich tropical peatlands, leading to extreme episodes of regional haze with high concentrations of fine particulate matter (PM2.5) impacting human health. In a study published recently, the first field measurements of PM2.5 emission factors for tropical peat fires showed larger emissions than from other fuel types. Here we report even higher PM2.5 emission factors, measured at newly ignited peat fires in Malaysia, suggesting that current estimates of fine particulate emissions from peat fires may be underestimated by a factor of 3 or more. In addition, we use both field and laboratory measurements of burning peat to provide the first mechanistic explanation for the high variability in PM2.5 emission factors, demonstrating that buildup of a surface ash layer causes the emissions of PM2.5 to decrease as the peat fire progresses. This finding implies that peat fires are more hazardous (in terms of aerosol emissions) when first ignited than when still burning many days later. Varying emission factors for PM2.5 also have implications for our ability to correctly model the climate and air quality impacts downwind of the peat fires. For modelers able to implement a time-varying emission factor, we recommend an emission factor for PM2.5 from newly ignited tropical peat fires of 58 g of PM2.5 per kilogram of dry fuel consumed (g/kg), reducing exponentially at a rate of 9%/day. If the age of the fire is unknown or only a single value may be used, we recommend an average value of 24 g/kg.
Growing plants in the gulf region can be challenging as it is mostly desert, and the climate is dry. A few species of plants have the capability to grow in such a climate. However, those plants are not suitable as a food source. The aim of this work is to design and construct an indoor automatic vertical hydroponic system that does not depend on the outside climate. The designed system is capable to grow common type of crops that can be used as a food source inside homes without the need of large space. The design of the system was made after studying different types of vertical hydroponic systems in terms of price, power consumption and suitability to be built as an indoor automated system. A microcontroller was working as a brain of the system, which communicates with different types of sensors to control all the system parameters and to minimize the human intervention. An open internet of things (IoT) platform was used to store and display the system parameters and graphical interface for remote access. The designed system is capable of maintaining healthy growing parameters for the plants with minimal input from the user. The functionality of the overall system was confirmed by evaluating the response from individual system components and monitoring them in the IoT platform. The system was consuming 120.59 and 230.59 kWh respectively without and with air conditioning control during peak summer, which is equivalent to the system running cost of 13.26 and 25.36 Qatari Riyal (QAR) respectively. This system was circulating around 104 k gallons of nutrient solution monthly however, only 8-10 L water was consumed by the system. This system offers real-time notifications to alert the hydroponic system user when the conditions are not favorable. So, the user can monitor several parameters without using laboratory instruments, which will allow to control the entire system remotely. Moreover, the system also provides a wide range of information, which could be essential for plant researchers and provides a greater understanding of how the key parameters of hydroponic system correlate with plant growth. The proposed platform can be used both for quantitatively optimizing the setup of the indoor farming and for automating some of the most labor-intensive maintenance activities. Moreover, such a monitoring system can also potentially be used for high-level decision making, once enough data will be collected. This work presents significant opportunities for the people who live in the gulf region to produce food as per their requirements.
Introduction: Most health advisories related to outdoor physical activity during haze are general in nature. The advisories normally advise everyone to reduce or limit prolonged exertion or heavy exertion without mentioning the acceptable duration for performing outdoor physical activity causing difficulty for public to decide to stop or cancel a particular outdoor or sport event. The aim of this paper is to determine the acceptable duration for performing outdoor physical activity pattern during haze based on API level.
Methods: Health risk assessment approach that comprises of hazard identification, exposure assessment, dose-response, and risk characterization steps was used to determine the potential inhaled dose and risk associated with performing the physical activity during haze. We have considered many factors that include time spent for physical activity patterns for Malaysian adult, age and physical intensity-specific inhalation rate (m3/min), and the indoor/outdoor ratio of PM10. A hypothetical exposure scenario of PM10 was created using the breakpoints of PM10 concentration for the calculation of respective API levels during haze.
Results: The association between physical activity pattern, API level and risk quotient were presented in the form of risk radar diagram. Based on the 50th percentile inhalation rate, all prolonged exertion and heavy exertion should be avoided when API reach >201 (very unhealthy) and >175 (unhealthy) respectively. Below the said API, the duration for performing prolonged exertion and heavy exertion should be reduced according to the API level. When API reaches 140, high intensity physical activity should be limited to < 90 minutes. A football match which requires 90 minutes, should be postponed of cancelled if API > 140. Whereas, for the same API level, prolonged exertion (moderate intensity physical activity) should be limited to 4 hours.
Conclusions: Reducing the physical activity is an effective strategy to lower the dose of inhaled pollutants and reduce the health risk during poor air quality. Based on the assessment, taking into account the uncertainty of risk assessment methodology, we proposed all prolonged exertion should be avoided when API reach very unhealthy status (>201). Below the said API level, outdoor physical activity should be reduced according to the level of API respectively. The recommendation is not applicable for the sensitive groups. The computed risk radar provide a valuable guide for the public to organize or considering postponing an outdoor event during haze.
Conventional air quality monitoring systems, such as gas analysers, are commonly used in many developed and developing countries to monitor air quality. However, these techniques have high costs associated with both installation and maintenance. One possible solution to complement these techniques is the application of low-cost air quality sensors (LAQSs), which have the potential to give higher spatial and temporal data of gas pollutants with high precision and accuracy. In this paper, we present DiracSense, a custom-made LAQS that monitors the gas pollutants ozone (O₃), nitrogen dioxide (NO₂), and carbon monoxide (CO). The aim of this study is to investigate its performance based on laboratory calibration and field experiments. Several model calibrations were developed to improve the accuracy and performance of the LAQS. Laboratory calibrations were carried out to determine the zero offset and sensitivities of each sensor. The results showed that the sensor performed with a highly linear correlation with the reference instrument with a response-time range from 0.5 to 1.7 min. The performance of several calibration models including a calibrated simple equation and supervised learning algorithms (adaptive neuro-fuzzy inference system or ANFIS and the multilayer feed-forward perceptron or MLP) were compared. The field calibration focused on O₃ measurements due to the lack of a reference instrument for CO and NO₂. Combinations of inputs were evaluated during the development of the supervised learning algorithm. The validation results demonstrated that the ANFIS model with four inputs (WE OX, AE OX, T, and NO₂) had the lowest error in terms of statistical performance and the highest correlation coefficients with respect to the reference instrument (0.8 < r < 0.95). These results suggest that the ANFIS model is promising as a calibration tool since it has the capability to improve the accuracy and performance of the low-cost electrochemical sensor.
Black Carbon (BC) deteriorates air quality and contributes to climate warming, yet its regionally- and seasonally-varying emission sources are poorly constrained. Here we employ natural abundance radiocarbon (14C) measurements of BC intercepted at a northern Malaysia regional receptor site, Bachok, to quantify the relative biomass vs. fossil source contributions of atmospheric BC, in a first year-round study for SE Asia (December 2015-December 2016). The annual average 14C signature suggests as large contributions from biomass burning as from fossil fuel combustion. This is similar to findings from analogous measurements at S Asian receptors sites (~50% biomass burning), while E Asia sites are dominated by fossil emission (~20% biomass burning). The 14C-based source fingerprinting of BC in the dry spring season in SE Asia signals an even more elevated biomass burning contribution (~70% or even higher), presumably from forest, shrub and agricultural fires. This is consistent with this period showing also elevated ratio of organic carbon to BC (up from ~5 to 30) and estimates of BC emissions from satellite fire data. Hence, the present study emphasizes the importance of mitigating dry season vegetation fires in SE Asia.
A stereological comparison has been made of the structure of the lungs of the adult female domestic fowl and its wild progenitor the Red Jungle Fowl. The volume of the lung per unit body weight of the domestic bird is between 20 and 33% smaller than that of the wild bird. The domestic fowl has partly compensated for this by increasing the surface area for gas exchange per unit volume of exchange tissue. However, the blood-gas tissue barrier is about 28% thicker in the domestic fowl than in the Red Jungle Fowl, and this has led to a 25% lower anatomical diffusing capacity for oxygen of the blood-gas tissue barrier per unit body weight in the domestic fowl. These structural characteristics may make the modern domestic fowl vulnerable to stress factors such as altitude, cold, heat or air pollution by predisposing to hypoxaemia and perhaps thence to ascites.
Exposure to hot and humid weather conditions will often lead to consuming a vast amount of electricity for cooling. Heating, ventilation, and air conditioning (HVAC) systems are customarily known as the largest consumers of energy in institutions and other facilities which raises the question regarding the impact of the weather conditions to the amount energy consumed. The academic building is a perfect example where a constant fixed daily operating characteristic is measured by the hour, aside from the occasional semester break. Therefore, it can be assumed that the daily HVAC services on an academic facility will operate on a fixed schedule each day, having a similar pattern all year round. This article aims to present an analysis on the relationship between typical weather data by implying the test reference year (TRY) and academic building electricity consumption in an academic building located at Durian Tunggal, Melaka. Typical weather data were generated in representing the weather data between 2010 and 2018 using the Finkelstein-Schafer statistic (F-S statistic) in addition to a data set of electricity consumption. Descriptive analysis and correlation matrix analysis were conducted using JASP software for two sets of sample data; Set A and Set B, with data points of 12 and 108, respectively. The result showed an alternate result with a positive correlation between 1)mean temperature-electricity consumption, and 2)mean rainfall-electricity consumption for data Set A, and a negative correlation between 1)mean temperature-electricity consumption and 2)mean rainfall-electricity consumption for data Set B.
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.
Unnecessary air conditioning for thermal comfort causeds energy over consumption. As air conditioning has become irreversible, one of the solutions is to run air conditioners at minimal energy without sacrificing the comfort of occupants in air conditioned space. The approach to thermal comfort is the key to successful thermal comfort research. Fanger's model has been adopted by ASHRAE and ISO standards but its universal applications have been debated. In recent decades, adaptive model that regards humans as adaptive beings has been accepted. The static and deterministic nature of Fanger's model has limited its application in hot, humid countries, such as Malaysia. This research aims to integrate the theories of Fanger and adaptive model into a new model which is applicable in Malaysia by taking the case in lecture halls. The new Fanger's Adaptive Model is established through normalization of the thermal sensation distribution obtained in thermal chamber by Fanger. The PMV range of 80% satisfaction has been widened to -1.3 to +1.3 which adopted the theories of adaptive model, where humans have the ability to adapt to environment. The research also includes field observations on Malaysian students clothing and activity levels in lecture halls. Previous field study results which proposed 25.3°C comfort temperature for lecture halls in Malaysia together with the field observation results were used to verify the new model. About 95% of PMV falls within the new range at this comfort temperature. It is proven that Fanger's model is semi-adaptive and probabilistic and the integration of Fanger's Adaptive Model is more accurate in predicting thermal comfort in hot and humid climate.
Malaysian Borneo has a lower population density and is an area known for its lush rainforests. However, changes in pollutant profiles are expected due to increasing urbanisation and commercial-industrial activities. This study aims to determine the variation of surface O3concentration recorded at seven selected stations in Malaysian Borneo. Hourly surface O3data covering the period 2002 to 2013, obtained from the Malaysian Department of Environment (DOE), were analysed using statistical methods. The results show that the concentrations of O3recorded in Malaysian Borneo during the study period were below the maximum Malaysian Air Quality Standard of 100ppbv. The hourly average and maximum O3concentrations of 31 and 92ppbv reported at Bintulu (S3) respectively were the highest among the O3concentrations recorded at the sampling stations. Further investigation on O3precursors show that sampling sites located near to local petrochemical industrial activities, such as Bintulu (S3) and Miri (S4), have higher NO2/NO ratios (between 3.21 and 5.67) compared to other stations. The normalised O3values recorded at all stations were higher during the weekend compared to weekdays (unlike its precursors) which suggests the influence of O3titration by NO during weekdays. The results also show that there are distinct seasonal variations in O3across Borneo. High surface O3concentrations were usually observed between August and September at all stations with the exception of station S7 on the east coast. Majority of the stations (except S1 and S6) have recorded increasing averaged maximum concentrations of surface O3over the analysed years. Increasing trends of NO2and decreasing trends of NO influence the yearly averaged maximum of O3especially at S3. This study also shows that variations of meteorological factors such as wind speed and direction, humidity and temperature influence the concentration of surface O3.
Natural ventilation is defined as the number of air exchanges per hour per unit floor area necessary
to reduce high indoor air temperature and humidity. In addition, it maintains the concentration of carbon dioxide. Natural ventilation is preferred in mechanical system as the ventilation opening is built into the greenhouse, with lower construction cost and no energy and maintenance inputs are required. A mathematical model to quantify natural ventilation rates was developed and verified in large-scale greenhouse structures. For this purpose, four Naturally Ventilated Tropical Greenhouse Structures were designed and constructed at the Malaysian Agricultural Research and Development Institute (MARDI). These were single, double, triple, and quadruple span structures with floor areas of 500 m2, 1000 m2, 1500 m2 and 2000 m2, respectively. This paper presents the validation of a mathematical model which was developed to quantify natural ventilation rates which are very crucial to reduce high in-house temperature built up in the tropics. Regression equations of natural ventilation against wind speed were found to be Φw = 0.0632V, Φw= 0.0395V, Φw= 0.0316Vand Φw=0.0276V for the single, double, triple and quadruple spans, respectively. Meanwhile, coefficients of determination showed strong relationships between ventilation rate and wind speed, with R2 = 0.9999 for all structures. Larger floor area was found to have higher in-house temperature than smaller ones. Ventilation rate inside the single-span structure was found to be higher compared to the multi-span structures, which increased linearly with the increasing wind speed at the eaves of structure.
Malaysia has good environmental laws to protect the outdoor environment and public health. However there are no laws governing indoor air quality (IAQ) and the knowledge among the public about its importance is also lacking. Environmental professionals think it is not a priority and this influences the policy decisions in the country. Therefore there is a need to create awareness by way of research, education and other promotional activities. What is much needed at this time is the establishment of standards for the conduct of risk assessment studies. To establish standards we need reliable data which can be used to develop appropriate guidelines for the purpose of mitigation and adaptation programmes. IAQ can have significant influence on health resulting in drop in productivity and economy of a country. It has been estimated that in the US, building related illnesses (BRI) symptoms have a relationship with decrease (3 to 5%) in work performance in an affected population resulting in an annual loss of US$60 billion in revenue. However, based on efficient management programmes they have also projected that the potential annual savings can be in the region of US$10 to 30 billion. This establishes that fact that good management programmes based on efficient guidelines is of economic value to a country and wellbeing of the population. The IMU has embarked on a research programme to collect the much-needed data for the framing of a good IAQ guideline for Malaysia.
The growing concern over the workers safety and health has lead many factories and organizations do the air monitoring to ensure the airborne at their workplace is safe for the worker’s health and complying the Occupational Safety and Health Act 1994 (Act 514). In this study, the monitoring covers an indoor air quality and chemical exposure to the workers in one of the power plant repair shop. A few workers from different sections namely blasting, welding, grinding, fitting and maintenance area were chosen to assist in the personal monitoring for 8 hours measurement. PM10 were measured at a few sampling points to collect dusts for 24 hours duration. The samples were brought back to the laboratory for gravimetric and SEM-EDAX analysis. The results were certainly exceed the limit for air quality, and many elements were detected such as Fe, Ni, Al, Si, Ca, K, Ba, S, Cr, Zn and Cl. The present of these elements shows that exposure to these particulate matters is quite risky and some measure needs to be taken for remedial action.
In this research, the biodiesel from WCO is used in order to reduce the exhaust emission and to investigate the
community perception regarding to the human health. Biodiesel production is conducted using trans-esterification
process with holding time of 2 hours, temperature of 60 oC and conventional frequency of 20 kHz and then followed
by washing process with holding time of 1 hours, temperature of 50 oC and the frequency of 5 kHz. Biodiesel can
reduce exhaust emission of NOx up to 55%, NO gas up to 57%, increase CO gas up to 25% and increase CO2 gas up
to 43.18% as compared to diesel fuel. In addition, biodiesel is achieve good responds from 35 respondents about the
biodiesel importance.
Indoor pollution increasingly becomes a public concern. These concerns are related to energy efficiency in a
building. There are various ways in which it can ensure energy conservation can be achieved, including superinsulation
and reduced fresh air exchange. As a result, indoor air becomes stagnant and odours, thereafter contaminants of air will
accumulate and will certainly disrupt human health. It is quite difficult to make people comfortable in a building with
consumption of energy-saving and human health guaranteed. Indoor plants are one of the alternative solutions that
have been studied since the last three decades. This paper intends to review the abilities of indoor plants to purify air,
and the ways used by previous researchers to prove that indoor plants can treat the air. In general, it can be stated that
indoor plants are able to absorb various types of volatile organic compounds (VOCs). An advantage of indoor plants
to cure air from carcinogen gas is greatly needed for human health. Therefore, studies on indoor plants to neutralize
the air are gaining attention. Enclosed space or chamber is often used by researchers to test the ability of indoor plants
absorb gaseous toxins in their study; because it is easy to handle and can quickly determine the absorption rate. In the
other hand, environmental factors such as temperature, humidity, and light are important to be taken into consideration
during the study. As a conclusion, it can be stated that the existence of indoor plants in a building is very reasonable,
because it can give positive impacts on human health and the total energy consumption.
The use of remote sensing in detecting aerosol or air pollution is not widely applied in Malaysia. The large area of coverage provided by remote sensing satellite may well be the solution to the lack of spatial coverage by the local ground air quality monitoring stations. This article discusses the application of remote sensing instruments in air quality monitoring of Malaysia. The remote sensing data is validated using ground truths either from local ground air monitoring stations or the Aerosol Robotic Network (AERONET). The correlation between remote sensing is relatively good with R from 0.5 to 0.9 depending on the satellite used. The correlation is much improved using the mixed effects algorithm applied on MODIS Aerosol Optical Depth (AOD) data. Accuracy of predicted air quality data by remote sensing is generally tested using the Root Mean Squared Error (RMSE) against the ground truths data. Besides the Geographic Information System (GIS) tools are used in manipulating the data from both remote sensing and ground stations so as to produce meaningful results such as spatio-temporal pattern mapping of air pollution. Overall the results showed that the application of remote sensing instruments in air quality monitoring in Malaysia is very useful and can be improved further.
Air pollution can be detected through rainwater composition. In this study, long-term measurements (2000-2014) of wet deposition were made to evaluate the physicochemical interaction and the potential sources of pollution due to changes of land use. The rainwater samples were obtained from an urban site in Kuala Lumpur and a highland-rural site in the middle of Peninsular Malaysia. The compositions of rainwater were obtained from the Malaysian Meteorological Department. The results showed that the urban site experienced more acidity in rainwater (avg=277mm, range of 13.8 to 841mm; pH=4.37) than the rural background site (avg=245mm, range of 2.90 to 598mm; pH=4.97) due to higher anthropogenic input of acid precursors. The enrichment factor (EF) analysis showed that at both sites, SO42-, Ca2+ and K+ were less sensitive to seawater but were greatly influenced by soil dust. NH4+ and Ca2+ can neutralise a larger fraction of the available acid ions in the rainwater at the urban and rural background sites. However, acidifying potential was dominant at urban site compared to rural site. Source-receptor relationship via positive matrix factorisation (PMF 5.0) revealed four similar major sources at both sites with a large variation of the contribution proportions. For urban, the major sources influence on the rainwater chemistry were in the order of secondary nitrates and sulfates>ammonium-rich/agricultural farming>soil components>marine sea salt and biomass burning, while at the background site the order was secondary nitrates and sulfates>marine sea salt and biomass burning=soil components>ammonia-rich/agricultural farming. The long-term trend showed that anthropogenic activities and land use changes have greatly altered the rainwater compositions in the urban environment while the seasonality strongly affected the contribution of sources in the background environment.
PM2.5 mass concentration and associated water-soluble ionic species in a sub-urban coastal area of Kuala Terengganu, Malaysia were investigated intermittently from year 2006 to 2009. A total of 78 weekly PM2.5 samples were analyzed. The mass concentration of PM2.5 exhibited annual, seasonal and diurnal variations. Temporal distributions of rainfall, sporadic haze episodes and local air flow (sea breeze circulation) were factors controlling PM2.5 mass variations in the study area. Although the PM2.5 concentrations were increased during haze episodes in 2006 (August and October) and2007 (October), their concentrations however, were still within the international guidelines. The average concentration of individual ions was in decreasing trend; SO42-> NH4+> K+> Na+> NO3-> Cl-> Ca2+. The concentrations of SO42- and NH4+ accounted for > 70% of the water-soluble aerosol mass. More than 80% of ionic species associated with PM2.5 are from non-marine sources. Major processes affecting the ionic composition of PM2.5 are biomass burning, crustal loading and sea spray. Air quality mitigation strategies should focus on anthropogenic activities emitting SO2, which promotes aerosol SO42- formation.
Open-cut coal mining can seriously disturb and reshape natural landscapes which results in a range of impacts on local ecosystems and the services they provide. To address the negative impacts of disturbance, progressive rehabilitation is commonly advocated. However, there is little research focusing on how these impacts affect ecosystem services within mine sites and changes over time. The aim of this study was to assess the cumulative impacts of mining disturbance and rehabilitation on ecosystem services through mapping and quantifying changes at multiple spatial and temporal scales. Four ecosystem services including carbon sequestration, air quality regulation, soil conservation and water yield were assessed in 1989, 1997, 2005 and 2013. Disturbance and rehabilitation was mapped using LandTrendr algorithm with Landsat. We mapped spatial patterns and pixel values for each ecosystem service with corresponding model and the landscape changes were analyzed with landscape metrics. In addition, we assessed synergies and trade-offs using Spearman's correlation coefficient for different landscape classes and scales. The results showed that carbon sequestration, air quality regulation and water yield services were both positively and negatively affected by vegetation cover changes due to mined land disturbance and rehabilitation, while soil conservation service were mainly influenced by topographic changes. There were strong interactions between carbon sequestration, air quality regulation and water yield, which were steady among different spatial scales and landscape types. Soil conservation correlations were weak and changed substantially due to differences of spatial scales and landscape types. Although there are limitations associated with data accessibility, this study provides a new research method for mapping impacts of mining on ecosystem services, which offer spatially explicit information for decision-makers and environmental regulators to carry out feasible policies, balancing mining development with ecosystem services provision.