Dataset Information

Variability on particulate matter and meteorology dataset during the hazy period in eastern region of Peninsular Malaysia.

ABSTRACT: This paper provides detail on sequence analysis of hazy days based on eight monitoring stations from three states (Kelantan, Terengganu and Pahang) in the eastern region of Peninsular Malaysia. The dataset comprises of 1502 daily mean hazy days that had been measured for a decade. The meteorology data namely wind speed, wind direction, air temperature, relative humidity and particulate matter (PM10) were used to comprehend the variability, and the relationship existed amongst variables. The final dataset consists of a summary descriptive analysis and a boxplot, where all five variables were involved, including the minimum, maximum, mean, 1st quartile, median, 3rd quartile and standard deviation are presented. Apart from descriptive analysis, the normality test and histogram were performed as well.

SUBMITTER: Ku Yusof KMK

PROVIDER: S-EPMC7013119 | biostudies-literature | 2020 Apr

REPOSITORIES: biostudies-literature

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Variability on particulate matter and meteorology dataset during the hazy period in eastern region of Peninsular Malaysia.

Ku Yusof Ku Mohd Kalkausar KMK Ismail Siti Sofo SS Azid Azman A Sani Muhamad Shirwan Abdullah MSA Isa Noorain Mohd NM Mohamat Zawawi Mohd Zulfahmie MZ

Data in brief 20200201

This paper provides detail on sequence analysis of hazy days based on eight monitoring stations from three states (Kelantan, Terengganu and Pahang) in the eastern region of Peninsular Malaysia. The dataset comprises of 1502 daily mean hazy days that had been measured for a decade. The meteorology data namely wind speed, wind direction, air temperature, relative humidity and particulate matter (PM<sub>10</sub>) were used to comprehend the variability, and the relationship existed amongst variable ...[more]

PMID: 32071985

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Project description:The structural variation of the bacterial community associated with particulate matter (PM) was assessed in an urban area of Beijing during hazy and nonhazy days. Sampling for different PM fractions (PM2.5 [<2.5 ?m], PM10 [<10 ?m], and total suspended particulate) was conducted using three portable air samplers from September 2014 to February 2015. The airborne bacterial community in these samples was analyzed using the Illumina MiSeq platform with bacterium-specific primers targeting the 16S rRNA gene. A total of 1,707,072 reads belonging to 6,009 operational taxonomic units were observed. The airborne bacterial community composition was significantly affected by PM fractions (R = 0.157, P < 0.01). In addition, the relative abundances of several genera significantly differed between samples with various haze levels; for example, Methylobacillus, Tumebacillus, and Desulfurispora spp. increased in heavy-haze days. Canonical correspondence analysis and permutation tests showed that temperature, SO2 concentration, relative humidity, PM10 concentration, and CO concentration were significant factors that associated with airborne bacterial community composition. Only six genera increased across PM10 samples (Dokdonella, Caenimonas, Geminicoccus, and Sphingopyxis) and PM2.5 samples (Cellulomonas and Rhizobacter), while a large number of taxa significantly increased in total suspended particulate samples, such as Paracoccus, Kocuria, and Sphingomonas Network analysis indicated that Paracoccus, Rubellimicrobium, Kocuria, and Arthrobacter were the key genera in the airborne PM samples. Overall, the findings presented here suggest that diverse airborne bacterial communities are associated with PM and provide further understanding of bacterial community structure in the atmosphere during hazy and nonhazy days.IMPORTANCE The results presented here represent an analysis of the airborne bacterial community associated with particulate matter (PM) and advance our understanding of the structural variation of these communities. We observed a shift in bacterial community composition with PM fractions but no significant difference with haze levels. This may be because the bacterial differences are obscured by high bacterial diversity in the atmosphere. However, we also observed that a few genera (such as Methylobacillus, Tumebacillus, and Desulfurispora) increased significantly on heavy-haze days. In addition, Paracoccus, Rubellimicrobium, Kocuria, and Arthrobacter were the key genera in the airborne PM samples. Accurate and real-time techniques, such as metagenomics and metatranscriptomics, should be developed for a future survey of the relationship of airborne bacteria and haze.

Project description:BACKGROUND:Over the past 50 years, Southeast Asia has suffered the greatest losses of biodiversity of any tropical region in the world. Malaysia is a biodiversity hotspot in the heart of Southeast Asia with roughly the same number of mammal species, three times the number of butterfly species, but only 4% of the land area of Australia. Consequently, in Malaysia, there is an urgent need for biodiversity monitoring and also public engagement with wildlife to raise awareness of biodiversity loss. Citizen science is "on the rise" globally and can make valuable contributions to long-term biodiversity monitoring, but perhaps more importantly, involving the general public in science projects can raise public awareness and promote engagement. Butterflies are often the focus of citizen science projects due to their charisma and familiarity and are particularly valuable "ambassadors" of biodiversity conservation for public outreach. NEW INFORMATION:Here we present the data from our citizen science project, the first "Peninsular Malaysia Butterfly Count". Participants were asked to go outdoors on June 6, 2015, and (non-lethally) sample butterfly legs for species identification through DNA barcoding. Fifty-seven citizens responded to our adverts and registered to take part in the butterfly count with many registering on behalf of groups. Collectively the participants sampled 220 butterfly legs from 26 mostly urban and suburban sampling localities. These included our university campus, a highschool, several public parks and private residences. On the basis of 192 usable DNA barcodes, 43 species were sampled by the participants. The most sampled species was Appias olferna, followed by Junonia orithya and Zizina otis. Twenty-two species were only sampled once, five were only sampled twice, and four were only sampled three times. Three DNA barcodes could not be assigned species names. The sampled butterflies revealed that widely distributed, cosmopolitan species, often those recently arrived to the peninsula or with documented "invasive" potential, dominated the habitat types sampled by the participants. Data from this first Butterfly Count helps establish a baseline from which we can monitor the patterns and changes in butterfly communities in Peninsular Malaysia.

Dataset Information

Variability on particulate matter and meteorology dataset during the hazy period in eastern region of Peninsular Malaysia.

Publications

Variability on particulate matter and meteorology dataset during the hazy period in eastern region of Peninsular Malaysia.

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