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631.
A. V. M. Subba Rao Arun K. Shanker V. U. M. Rao V. Narsimha Rao A. K. Singh Pragyan Kumari C. B. Singh Praveen Kumar Verma P. Vijaya Kumar B. Bapuji Rao Rajkumar Dhakar M. A. Sarath Chandran C. V. Naidu J. L. Chaudhary Ch. Srinivasa Rao B. Venkateshwarlu 《Environmental Modeling and Assessment》2016,21(1):17-30
632.
L. Schultz P. Shah E. Giandomenico B. Chiera 《Environmental Modeling and Assessment》2016,21(2):169-179
Link Emissions Models estimate traffic-related air pollution emissions at the individual road link level and inform governmental policies for air quality management. The current South Australian Link Emissions Model (CLEM) assumes constant spatiotemporal traffic flow at a single fixed mean speed, a potential limitation as the variability of exhaust emissions with vehicle speed has been established in the literature.We extend CLEM to eliminate the assumption of constant traffic flow, through the derivation of mean Australian vehicle speed distributions for different road types. Specifically, we successfully model the vehicle speed profile data from the second National In-Service Emissions study using Nearest Neighbour Kernel Density Estimation. We propose a mean speed Distribution Link Emissions Model (DLEM) for exhaust emission estimation based on the derived mean speed distributions. DLEM is an augmented, enhanced version of CLEM, accommodating a range of vehicle speeds and road types. The performance of the extended model, DLEM, is analysed in comparison to the current model, CLEM, through a case study analysis of vehicle exhaust emissions on a typical arterial road in Adelaide, South Australia. Results indicate use of DLEM and, by extension, mean vehicle speed distributions, has a strong impact on emission estimation. In particular, the fixed speed model, CLEM, may be substantially underestimating exhaust emissions of carbon monoxide, non-methane volatile organic compounds and particulate matter less than 2.5 μm in diameter. These are common exhaust pollutants that have been extensively linked with adverse health effects including respiratory morbidity and premature mortality. 相似文献
633.
J. F. Jasonsmith B. C. T. Macdonald I. White 《Environmental monitoring and assessment》2017,189(4):188
Wybong Creek discharges salts into the agriculturally and industrially important Hunter River in New South Wales, Australia. Abrupt increases in salinity occur periodically in the mid-Wybong Creek catchment. In order to understand the processes which cause these abrupt increases, changes in surface and groundwater were investigated. It is shown that salinity increases can be attributed to highly discrete groundwater discharge directly into the river from below. Hourly electrical conductivity data measured in the river showed regular, diurnal electrical conductivity fluctuations of up to 350 μS cm?1. These fluctuations could not be attributed to barometric pressure, temperature, or evapotranspiration. Instead, a similar periodicity in surface water electrical conductivity and groundwater height in nearby groundwater wells was found. Fluctuations were of similar periodicity to the orthotides which cause fluctuations in surface water height and are induced by Earth tides. The geology in the mid-catchment area indicates conditions are optimal for Earth tides to impact groundwater. The reporting of orthotidal changes in water chemistry in this article is believed to be the first of its kind in the scientific literature, with the large fluctuations noted having important implications for water monitoring and management in the catchment. Further research investigating Earth-tide-induced phases of groundwater heights will better constrain the relationships between surface water chemistry and groundwater height. 相似文献
634.
H. W. Zhang Y. Q. Sun Y. Li X. D. Zhou X. Z. Tang P. Yi A. Murad S. Hussein D. Alshamsi A. Aldahan Z. B. Yu X. G. Chen V. d. P. MUGWANEZA 《Environmental monitoring and assessment》2017,189(8):411
Assessment of groundwater quality plays a significant role in the utilization of the scarce water resources globally and especially in arid regions. The increasing abstraction together with man-made contamination and seawater intrusion have strongly affected groundwater quality in the Arabia Peninsula, exemplified by the investigation given here from the United Arab Emirates, where the groundwater is seldom reviewed and assessed. In the aim of assessing current groundwater quality, we here present a comparison of chemical data linked to aquifers types. The results reveal that most of the investigated groundwater is not suitable for drinking, household, and agricultural purposes following the WHO permissible limits. Aquifer composition and climate have vital control on the water quality, with the carbonate aquifers contain the least potable water compared to the ophiolites and Quaternary clastics. Seawater intrusion along coastal regions has deteriorated the water quality and the phenomenon may become more intensive with future warming climate and rising sea level. 相似文献
635.
Kusum Komal Karati G. Vineetha N. V. Madhu P. Anil M. Dayana B. K. Shihab A. I. Muhsin C. Riyas T. V. Raveendran 《Environmental monitoring and assessment》2017,189(12):653
El Niño, an interannual climate event characterized by elevated oceanic temperature, is a prime threat for coral reef ecosystems worldwide, owing to their thermal threshold sensitivity. Phytoplankton plays a crucial role in the sustenance of reef trophodynamics. The cell size of the phytoplankton forms the “master morphological trait” with implications for growth, resource acquisition, and adaptability to nutrients. In the context of a strong El Niño prediction for 2015–2016, the present study was undertaken to evaluate the variations in the size-structured phytoplankton of Kavaratti reef waters, a major coral atoll along the southeast coast of India. The present study witnessed a remarkable change in the physicochemical environment of the reef water and massive coral bleaching with the progression of El Niño 2015–2016 from its peak to waning phase. The fluctuations observed in sea surface temperature, pH, and nutrient concentration of the reef water with the El Niño progression resulted in a remarkable shift in phytoplankton size structure, abundance, and community composition of the reef waters. Though low nutrient concentration of the waning phase resulted in lower phytoplankton biomass and abundance, the diazotroph Trichodesmium erythraeum predominated the reef waters, owing to its capability of the atmospheric nitrogen fixation and dissolved organic phosphate utilization. 相似文献
636.
A. M. Stellacci A. Castrignanò A. Troccoli B. Basso G. Buttafuoco 《Environmental monitoring and assessment》2016,188(3):199
Hyperspectral data can provide prediction of physical and chemical vegetation properties, but data handling, analysis, and interpretation still limit their use. In this study, different methods for selecting variables were compared for the analysis of on-the-ground hyperspectral signatures of wheat grown under a wide range of nitrogen supplies. Spectral signatures were recorded at the end of stem elongation, booting, and heading stages in 100 georeferenced locations, using a 512-channel portable spectroradiometer operating in the 325–1075-nm range. The following procedures were compared: (i) a heuristic combined approach including lambda-lambda R2 (LL R2) model, principal component analysis (PCA), and stepwise discriminant analysis (SDA); (ii) variable importance for projection (VIP) statistics derived from partial least square (PLS) regression (PLS-VIP); and (iii) multiple linear regression (MLR) analysis through maximum R-square improvement (MAXR) and stepwise algorithms. The discriminating capability of selected wavelengths was evaluated by canonical discriminant analysis. Leaf-nitrogen concentration was quantified on samples collected at the same locations and dates and used as response variable in regressive methods. The different methods resulted in differences in the number and position of the selected wavebands. Bands extracted through regressive methods were mostly related to response variable, as shown by the importance of the visible region for PLS and stepwise. Band selection techniques can be extremely useful not only to improve the power of predictive models but also for data interpretation or sensor design. 相似文献
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