The research focus of resource consumption and emissions from urban water services has, by and large, been restricted to what comes under the domain of the urban water utilities - the upstream sub-systems of water treatment and supply and the downstream sub-systems of wastewater collection, treatment and disposal. However, the material and energy flows necessitated by activities in the water demand sub-system (households, for instance) are by no means negligible. This paper studies the per-capita material and energy requirements, and the related emissions and life cycle environmental impacts, associated with water consumption in households of the city of Oslo for the year 2009. For example, the per-capita energy consumption in the household consumption phase, at 1.38 MWh per year, is eight times more than the corresponding consumption for the entire water-wastewater utility. All findings, taken together, clearly demonstrate the imperativeness of paying more attention to the demand-side management issues.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1080/09593330.2014.902504 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Water Quality and Land Use Shape Bacterial Communities Across 621 Canadian Lakes.
Environ Microbiol
January 2025
Groupe de Recherche Interuniversitaire en Limnologie (GRIL), Montréal, Canada.
Human activities such as agriculture and urban development are linked to water quality degradation. Canada represents a large and heterogeneous landscape of freshwater lakes, where variations in climate, geography and geology interact with land cover alteration to influence water quality differently across regions. In this study, we investigated the influence of water quality and land use on bacterial communities across 12 ecozones.
View Article and Find Full Text PDFRevisiting water resources management in the Mandara Mountains.
Heliyon
January 2025
Faculty of Science and Technology, Campus of Banekane, Université des Montagnes, P.O. Box 208, Bangangté, Cameroon.
This article evaluates the prospects for rainwater harvesting (RWH) as a means of optimizing water management in the Mandara Mountains. RWH is a small-scale water conservation approach for locally intercepting and storing rainfall before it enters the usual hydrologic cycle. This ancient practice has recently sustained lives in semiarid areas of the world (e.
View Article and Find Full Text PDFAssessment of tree-associated atypical myopathy risk factors in Acer pseudoplatanus (sycamore) seeds and leaves.
Equine Vet J
January 2025
Comparative Neuromuscular Diseases Laboratory, Department of Clinical Science and Services, The Royal Veterinary College, London, UK.
Background: Sycamore tree-derived hypoglycin A (HGA) toxin causes atypical myopathy (AM), an acute, equine pasture-associated rhabdomyolysis but incidence fluctuates.
Objectives: Investigate whether tree or environmental factors influence HGA concentration in sycamore material and are associated with AM relative risk.
Study Design: Retrospective and experimental prospective study.
Impacts of irrigation expansion on moist-heat stress based on IRRMIP results.
Nat Commun
January 2025
Department of Water and Climate, Vrije Universiteit Brussel, Brussels, Belgium.
Irrigation rapidly expanded during the 20 century, affecting climate via water, energy, and biogeochemical changes. Previous assessments of these effects predominantly relied on a single Earth System Model, and therefore suffered from structural model uncertainties. Here we quantify the impacts of historical irrigation expansion on climate by analysing simulation results from six Earth system models participating in the Irrigation Model Intercomparison Project (IRRMIP).
View Article and Find Full Text PDFLong-term reconstructed vegetation index dataset in China from fused MODIS and Landsat data.
Sci Data
January 2025
Institute of Carbon Neutrality, Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, Peking University, Beijing, 100091, China.
The vegetation index is a key satellite-based variable used to monitor global vegetation distribution and growth. However, existing vegetation index datasets face limitations in achieving both high spatial and temporal resolution, restricting their application potential. This study revised a machine learning spatiotemporal fusion model (InENVI) to produce a high-resolution NDVI dataset with 8-day temporal and 30 m spatial resolution, covering China from 2001 to 2020.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!