Biomechanics Analysis of the Firefighters' Thorax Movement on Personal Protective Equipment during Lifting Task Using Inertial Measurement Unit Motion Capture.

Back injury is a common musculoskeletal injury reported among firefighters (FFs) due to their nature of work and personal protective equipment (PPE). The nature of the work associated with heavy lifting tasks increases FFs' risk of back injury. This study aimed to assess the biomechanics movement of FFs on personal protective equipment during a lifting task. A set of questionnaires was used to identify the prevalence of musculoskeletal pain experienced by FFs. Inertial measurement unit (IMU) motion capture was used in this study to record the body angle deviation and angular acceleration of FFs' thorax extension. The descriptive analysis was used to analyze the relationship between the FFs' age and body mass index with the FFs' thorax movement during the lifting task with PPE and without PPE. Sixty-three percent of FFs reported lower back pain during work, based on the musculoskeletal pain questionnaire. The biomechanics analysis of thorax angle deviation and angular acceleration has shown that using FFs PPE significantly causes restricted movement and limited mobility for the FFs. As regards human factors, the FFs' age influences the angle deviation while wearing PPE and FFs' BMI influences the angular acceleration without wearing PPE during the lifting activity.

Noise Exposure Assessment at a Secondary School in a City of Pulau Pinang, Malaysia.

Schools are considered sensitive areas to noise pollution. The objective of this study is to ascertain the sound level in schools with respect to different sampling time sessions and sampling points. Five sampling points, consisting of two classrooms (Classroom A and Classroom B), a canteen, a staffroom and a field, were chosen to obtain an overview of the noise level within the whole school in three different time sessions (morning, afternoon and evening), as well as 8-h continuous sampling in both classrooms and the staffroom. The average noise level (LAeq,10min) obtained in this school was found to be in the range of 48.8 dBA to 83.7 dBA, where most of the values exceeded the permissible maximum sound pressure level set by the Malaysian Department of Environment (DOE). Classroom B recorded the highest average noise level (LAeq,8h) of 77.9 dBA, which exceeded the maximum value set by the Department of Environment.

Physicochemical factors and their potential sources inferred from long-term rainfall measurements at an urban and a remote rural site in tropical areas.

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.

Source apportionment and health risk assessment among specific age groups during haze and non-haze episodes in Kuala Lumpur, Malaysia.

This study aims to determine PM2.5 concentrations and their composition during haze and non-haze episodes in Kuala Lumpur. In order to investigate the origin of the measured air masses, the Numerical Atmospheric-dispersion Modelling Environment (NAME) and Global Fire Assimilation System (GFAS) were applied. Source apportionment of PM2.5 was determined using Positive Matrix Factorization (PMF). The carcinogenic and non-carcinogenic health risks were estimated using the United State Environmental Protection Agency (USEPA) method. PM2.5 samples were collected from the centre of the city using a high-volume air sampler (HVS). The results showed that the mean PM2.5 concentrations collected during pre-haze, haze and post-haze periods were 24.5±12.0µgm-3, 72.3±38.0µgm-3 and 14.3±3.58µgm-3, respectively. The highest concentration of PM2.5 during haze episode was five times higher than World Health Organisation (WHO) guidelines. Inorganic compositions of PM2.5, including trace elements and water soluble ions were determined using inductively coupled plasma-mass spectrometry (ICP-MS) and ion chromatography (IC), respectively. The major trace elements identified were K, Al, Ca, Mg and Fe which accounted for approximately 93%, 91% and 92% of the overall metals' portions recorded during pre-haze, haze and post-haze periods, respectively. For water-soluble ions, secondary inorganic aerosols (SO42-, NO3- and NH4+) contributed around 12%, 43% and 16% of the overall PM2.5 mass during pre-haze, haze and post-haze periods, respectively. During haze periods, the predominant source identified using PMF was secondary inorganic aerosol (SIA) and biomass burning where the NAME simulations indicate the importance of fires in Sumatra, Indonesia. The main source during pre-haze and post-haze were mix SIA and road dust as well as mineral dust, respectively. The highest non-carcinogenic health risk during haze episode was estimated among the infant group (HI=1.06) while the highest carcinogenic health risk was estimated among the adult group (2.27×10-5).

Physicochemical factors and sources of particulate matter at residential urban environment in Kuala Lumpur.

Long-term measurements (2004-2011) of PM10 (particulate matter with an aerodynamic diameter <10 µm) and trace gases (carbon monoxide [CO], ozone [O3], nitrogen oxide [NO], oxides of nitrogen [NO(x)], nitrogen dioxide [NO2], sulfur dioxide [SO2], methane [CH4], nonmethane hydrocarbon [NMHC]) have been conducted to study the effect of physicochemical factors on the PM10 concentration. In addition, this study includes source apportionment of PM10 in Kuala Lumpur urban environment. An advanced principal component analysis (PCA) technique coupled with absolute principal component scores (APCS) and multiple linear regression (MLR) has been applied. The average annual concentration of PM10 for 8 yr is 51.3 ± 25.8 µg m⁻³, which exceeds the Recommended Malaysian Air Quality Guideline (RMAQG) and international guideline values. Detail analysis shows the dependency of PM10 on the linear changes of the motor vehicles in use and the amount of biomass burning, particularly from Sumatra, Indonesia, during southwesterly monsoon. The main sources of PM10 identified by PCA-APCS-MLR are traffic combustion (28%), ozone coupled with meteorological factors (20%), and wind-blown particles (1%). However, the apportionment procedure left 28.0 µg m⁻³, that is, 51% of PM10 undetermined.

Characterization and source apportionment of particle number concentration at a semi-urban tropical environment.

Principal component analysis (PCA) and correlation have been used to study the variability of particle mass and particle number concentrations (PNC) in a tropical semi-urban environment. PNC and mass concentration (diameter in the range of 0.25->32.0 µm) have been measured from 1 February to 26 February 2013 using an in situ Grimm aerosol sampler. We found that the 24-h average total suspended particulates (TSP), particulate matter ≤10 µm (PM10), particulate matter ≤2.5 µm (PM2.5) and particulate matter ≤1 µm (PM1) were 14.37 ± 4.43, 14.11 ± 4.39, 12.53 ± 4.13 and 10.53 ± 3.98 µg m(-3), respectively. PNC in the accumulation mode (<500 nm) was the most abundant (at about 99 %). Five principal components (PCs) resulted from the PCA analysis where PC1 (43.8 % variance) predominates with PNC in the fine and sub-microme tre range. PC2, PC3, PC4 and PC5 explain 16.5, 12.4, 6.0 and 5.6 % of the variance to address the coarse, coarser, accumulation and giant fraction of PNC, respectively. Our particle distribution results show good agreement with the moderate resolution imaging spectroradiometer (MODIS) distribution.

Source contribution of PM2.5 at different locations on the Malaysian Peninsula.

This study determined the source contribution of PM2.5 (particulate matter <2.5 µm) in air at three locations on the Malaysian Peninsula. PM2.5 samples were collected using a high volume sampler equipped with quartz filters. Ion chromatography was used to determine the ionic composition of the samples and inductively coupled plasma mass spectrometry was used to determine the concentrations of heavy metals. Principal component analysis with multilinear regressions were used to identify the possible sources of PM2.5. The range of PM2.5 was between 10 ± 3 and 30 ± 7 µg m(-3). Sulfate (SO4 (2-)) was the major ionic compound detected and zinc was found to dominate the heavy metals. Source apportionment analysis revealed that motor vehicle and soil dust dominated the composition of PM2.5 in the urban area. Domestic waste combustion dominated in the suburban area, while biomass burning dominated in the rural area.