Browsing by Author "Zhang T"

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    Generalised Linear Modelling for Construction Waste Estimation in Residential Projects: Case Study in New Zealand
    (MDPI (Basel, Switzerland), 2024-02-27) Domingo N; Edirisinghe HM; Kahandawa R; Wedawatta G; Zhang T
    Construction waste is a global problem, including in New Zealand where it makes up 40–50% of landfill waste. Accurately measuring construction waste is crucial to reduce its impact on New Zealand’s landfills and meet carbon targets. Waste can be effectively managed if predicted correctly from the start of a project. Waste generation depends on factors such as geography, society, technology, and construction methods. This study focuses on developing a model specific to New Zealand to predict waste generation in residential buildings. By analysing data from 213 residential projects, the study identifies the design features that have the greatest influence on construction waste generation. A generalized linear model is constructed to correlate these design features with waste generation. The findings are valuable for construction stakeholders seeking to implement waste reduction strategies based on predicted waste quantities. This research serves as a starting point, and further investigation in this area is necessary.
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    Seasonal variation in soil and herbage CO2 efflux for a sheep-grazed alpine meadow on the north-east Qinghai-Tibetan Plateau and estimated net annual CO2 exchange
    (2/06/2022) Yuan H; Matthew C; He XZ; Sun Y; Liu Y; Zhang T; Gao X; Yan C; Chang S; Hou F
    The Qinghai-Tibetan Plateau is a vast geographic area currently subject to climate warming. Improved knowledge of the CO2 respiration dynamics of the Plateau alpine meadows and of the impact of grazing on CO2 fluxes is highly desirable. Such information will assist land use planning. We measured soil and vegetation CO2 efflux of alpine meadows using a closed chamber technique over diurnal cycles in winter, spring and summer. The annual, combined soil and plant respiration on ungrazed plots was 28.0 t CO2 ha-1 a-1, of which 3.7 t ha-1 a-1occurred in winter, when plant respiration was undetectable. This suggests winter respiration was driven mainly by microbial oxidation of soil organic matter. The winter respiration observed in this study was sufficient to offset the growing season CO2 sink reported for similar alpine meadows in other studies. Grazing increased herbage respiration in summer, presumably through stimulation of gross photosynthesis. From limited herbage production data, we estimate the sustainable yield of these meadows for grazing purposes to be about 500 kg herbage dry matter ha-1 a-1. Addition of photosynthesis data and understanding of factors affecting soil carbon sequestration to more precisely determine the CO2 balance of these grasslands is recommended.
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    The relationship between hair metabolites, air pollution exposure and gestational diabetes mellitus: A longitudinal study from pre-conception to third trimester.
    (Frontiers Media S.A., 2022-12-02) Chen X; Zhao X; Jones MB; Harper A; de Seymour JV; Yang Y; Xia Y; Zhang T; Qi H; Gulliver J; Cannon RD; Saffery R; Zhang H; Han T-L; Baker PN; Zhou N
    BACKGROUND: Gestational diabetes mellitus (GDM) is a metabolic condition defined as glucose intolerance with first presentation during pregnancy. Many studies suggest that environmental exposures, including air pollution, contribute to the pathogenesis of GDM. Although hair metabolite profiles have been shown to reflect pollution exposure, few studies have examined the link between environmental exposures, the maternal hair metabolome and GDM. The aim of this study was to investigate the longitudinal relationship (from pre-conception through to the third trimester) between air pollution exposure, the hair metabolome and GDM in a Chinese cohort. METHODS: A total of 1020 women enrolled in the Complex Lipids in Mothers and Babies (CLIMB) birth cohort were included in our study. Metabolites from maternal hair segments collected pre-conception, and in the first, second, and third trimesters were analysed using gas chromatography-mass spectrometry (GC-MS). Maternal exposure to air pollution was estimated by two methods, namely proximal and land use regression (LUR) models, using air quality data from the air quality monitoring station nearest to the participant's home. Logistic regression and mixed models were applied to investigate associations between the air pollution exposure data and the GDM associated metabolites. RESULTS: Of the 276 hair metabolites identified, the concentrations of fourteen were significantly different between GDM cases and non-GDM controls, including some amino acids and their derivatives, fatty acids, organic acids, and exogenous compounds. Three of the metabolites found in significantly lower concentrations in the hair of women with GDM (2-hydroxybutyric acid, citramalic acid, and myristic acid) were also negatively associated with daily average concentrations of PM2.5, PM10, SO2, NO2, CO and the exposure estimates of PM2.5 and NO2, and positively associated with O3. CONCLUSIONS: This study demonstrated that the maternal hair metabolome reflects the longitudinal metabolic changes that occur in response to environmental exposures and the development of GDM.