Prediction of Distribution and Intensity of Hydrocarbon Contamination using GIS

Contaminated industrial plots are commonplace in a modern society. Hydrocarbon contamination has a widespread effect on animals and plants depending on the urban ecosystems and their resources. Despite the history of petroleum use, the research band of the field has been relatively narrow and has concentrated on heavy metal contamination. The aim of the thesis is to create a simplified method to predict the distribution and intensity of hydrocarbon contaminations that could be utilised by people working in the related industry or by officials. The prediction of the distribution and intensity of hydrocarbon contamination in the soil using geographic information systems is studied using available public sector remediation reports. A total of 19 reports are inspected and information within them is transferred into a computer software. The major factor affecting hydrocarbon contamination values is the distance from a contamination point source. Results show there is a possibility to create a simplified prediction model based on a few available factors, such as the distance from the source and the field test results. The accuracy of such a model is sufficient for day-to-day based operations of the industry and officials. The study suggests that companies and officials working with hydrocarbon contaminated soil should implement in geographic information systems to the planning of contaminated environments. The study recommends greater emphasis on quality control to provide meaningful data for future studies.Pilaantuneet maa-alueet ovat yleinen ongelma nyky-yhteiskunnassa. Hiilivedyillä on haitallinen vaikutus kaupunkiekosysteemien luonnonvaroista riippuvaisiin eläimiin ja kasveihin. Polttonesteiden pitkään jatkuneesta käytöstä huolimatta pilaantuneiden maaalueiden tieteellinen tutkiminen on pääasiassa keskittynyt raskasmetallien haittavaikutusten tutkintaan. Tämän lopputyön tarkoitus on luoda yksinkertainen menetelmä hiilivedyillä pilaantuneiden maa-alueiden laajuuden sekä voimakkuuden ennustamiseen. Menetelmän tulee olla myös sellainen, että sitä voisivat käyttää sekä alalla toimivat yritykset että viranomaiset. Hiilivedyillä pilaantuneen maa-alueen laajuuden ja voimakkuuden ennustamista on tutkittu paikkatietojärjestelmän avulla. Aineistona käytettiin 19:ää julkisen sektorin tilaamaa kunnostusraporttia. Merkittävin hiilivetysaastumaan vaikuttava tekijä on etäisyys saastuman pistelähteestä. Tulokset osoittavat, että yksinkertaistettu ennustamismenetelmä on mahdollista luoda vain muutaman eri tekijän avulla. Menetelmän tarkkuus on tarpeeksi suuri, jotta sitä voidaan hyödyntää alan jokapäiväisessä työelämässä. Tutkimuksen perusteella suositellaan, että alalla toimivat yritykset sekä niitä valvovat viranomaiset käyttäisivät paikkatietojärjestelmiä suunnitellessaan hiilivedyillä pilaantuneiden maa-alueiden kunnostamista. Laadunvalvontaa tulisi kehittää enemmän siihen suuntaan,että syntyvä aineisto olisi käyttökelpoista tulevia tutkimuksia varten

Additional file 1: of The pan-genome of Lactobacillus reuteri strains originating from the pig gastrointestinal tract

Figure S1A and B.Plasmid profiles from strains of L. reuteri. Figure S2. IS element target site sequence logos from strain ATCC 53608. Figure S3A and B. L. reuteri pan-genomes displayed as frequency of orthologous gene clusters per number of genomes. Figure S4. Core and unique genes from 20 genome-sequenced strains of L. reuteri. Figure S5. Circular comparison of selected 13 genome-sequenced strains of L. reuteri. Figure S6. Conservation of putative surface proteins from ATCC 53608 with four other pig-derived strains. Figure S7. Comparison of accessory SecA2-SecY2 clusters from L. reuteri strains ATCC 53608 and 100-23. (PDF 1398 kb

Additional file 5: Table S4. of The pan-genome of Lactobacillus reuteri strains originating from the pig gastrointestinal tract

Composition of 10-aa repeats in pig strain SRRPs compared with the rat 100-23 SRRP. (XLSX 11 kb

Additional file 3: Table S2. of The pan-genome of Lactobacillus reuteri strains originating from the pig gastrointestinal tract

Predicted surface proteins from L. reuteri ATCC 53608. (XLSX 14 kb

Additional file 6: Table S5. of The pan-genome of Lactobacillus reuteri strains originating from the pig gastrointestinal tract

L. reuteri homologues of SecA2-SecY2 cluster-associated MucBP-containing pseudogene protein LRATCC53608_0902-_0904. (XLSX 11 kb

Additional file 13: Figure S6. of Optimisation of 16S rRNA gut microbiota profiling of extremely low birth weight infants

Primer alignment study of the most common bacterial taxa found in ELBW (P29F). a Representation of primers used in this study along the 16S bacterial rRNA gene. b Primer alignment study using 16S rRNA gene from Bifidobacterium bifidum CP 010412 (isolated from Infloran) and the most common bacterial taxa found in an ELBW infant (P29F) with supplementation (Staphylococcus epidermis NR_074995, Enterobacter cloacae CP012165 and Enterococcus faecalis CP014949). We also included two strains of Bifidobacterium as control samples (B.infantis M58738.1 and B.longum ATCC 156697) All sequences are represented in 5′-3’orientation using UPAC nucleotide code, where Y = C or T, R = A or G, K = G or T, M = A or C (PDF 299 kb

Additional file 4: Table S3. of The pan-genome of Lactobacillus reuteri strains originating from the pig gastrointestinal tract

Homologues of DUF1542 repeat-containing cell wall protein LRATCC53608_1774 in genome-sequenced strains of L. reuteri. (XLSX 12 kb

Additional file 12: Figure S3. of Optimisation of 16S rRNA gut microbiota profiling of extremely low birth weight infants

Shannon diversity index calculation of 16S rRNA gene sequencing data. Shannon diversity index was calculated using 16S rRNA bacterial community profiles for the three different 16S rRNA libraries tested in this study (27F-519R (region V1 + V2 + V3), 530F-926R (region V4 + V5) and 926F-1394R (region V6 + V7 + V8)). Sequencing data was analysed using the PE protocol. (PDF 16 kb

Adhesion of <i>L. johnsonii</i> strains to HT29 monolayers.

<p>Results are the mean of triplicate experiments with three replicates per experiment +/− standard deviation, figures above bars represent the p value calculated using an independent t-test with unequal variance, comparing each strain to the wild type.</p

<i>L. johnsonii eps</i> gene cluster analysis.

*<p>, hypothetical protein.</p