The air quality in Beijing, especially its PM2.5 level, has become of increasing public concern because of its importance and sensitivity related to health risks. A set of monitored PM2.5 data from 31 stations, released for the first time by the Beijing Environmental Protection Bureau, covering 37 days during autumn 2012, was processed using spatial interpolation and overlay analysis. Following analyses of these data, a distribution map of cumulative exceedance days of PM2.5 and a temporal variation map of PM2.5 for Beijing have been drawn. Computational and analytical results show periodic and directional trends of PM2.5 spreading and congregating in space, which reveals the regulation of PM2.5 overexposure on a discontinuous medium-term scale. With regard to the cumulative effect of PM2.5 on the human body, the harm from lower intensity overexposure in the medium term, and higher overexposure in the short term, are both obvious. Therefore, data of population distribution were integrated into the aforementioned PM2.5 spatial spectrum map. A spatial statistical analysis revealed the patterns of PM2.5 gross exposure and exposure probability of residents in the Beijing urban area. The methods and conclusions of this research reveal relationships between long-term overexposure to PM2.5 and people living in high-exposure areas of Beijing, during the autumn of 2012.

This study presents an ArcGIS geoprocessing protocol for quickly processing large amounts of data from publicly available government sources to consider both water quality standards (WQS) and nonpoint pollution source (NPS) control, on a watershed-by-watershed basis to administratively predict locations where nonpoint source pollutants may contribute to the impairment of downstream waters and locations where nonpoint source pollutants are not expected to contribute to the impairment of downstream waters. This dissertation also presents an ArcGIS geoprocessing protocol to calculate the hydrological response time of a watershed and to predict the potential for soil erosion and nonpoint source pollutant movement on a landscape scale. The standardized methodologies employed by the protocol allow for its use in various geographic regions. The methodology has been performed on sites in Linn County and Boone County, Missouri, and produces results consistent with those expected from other widely accepted methods. These protocols were developed studying the movement of atrazine. but may be used for various nonpoint source pollutants that are water soluble, have an affinity to soil binding, and associated with a particular land use. All data and code are available in Mendeley Data (doi: 10.17632/wdjzftxyfd.1).

The data set contains:1. AHP Questionnaire, Estimated criteria weight and method of sensitivity analysis using GIS and one-factor at a time techniques.2. Figures of the study3. Raster data set fas ArcGIS GBD of the impact category maps and composite impact map4. Calculation of composite impact index

Filtered global GEBCO 2014 bathymetry/topography raster, intended for qmesh tutorials.

*From Ambient Air Quality Standards (GB 3095–2012) and Technical Regulation on Ambient Air Quality Index (HJ 633–2012, on trial) from the website of the Ministry of Environmental Protection, China (http://kjs.mep.gov.cn/hjbhbz/bzwb/dqhjbh/dqhjzlbz/201203/W020120410330232398521.pdf and http://kjs.mep.gov.cn/hjbhbz/bzwb/dqhjbh/jcgfffbz/201203/W020120410332725219541.pdf).

Gis Engineering And Environmental S Export Import Data. Follow the Eximpedia platform for HS code, importer-exporter records, and customs shipment details.

The 4 global maps of pyroxene-related spectral parameters derived from data coming from the VIR mapping spectrometer onboard NASA/Dawn acqusition campaing at Vesta.

The Air, Water, and Aquatic Environments (AWAE) research program is one of eight Science Program areas within the Rocky Mountain Research Station (RMRS). Our science develops core knowledge, methods, and technologies that enable effective watershed management in forests and grasslands, sustain biodiversity, and maintain healthy watershed conditions. We conduct basic and applied research on the effects of natural processes and human activities on watershed resources, including interactions between aquatic and terrestrial ecosystems. The knowledge we develop supports management, conservation, and restoration of terrestrial, riparian and aquatic ecosystems and provides for sustainable clean air and water quality in the Interior West. With capabilities in atmospheric sciences, soils, forest engineering, biogeochemistry, hydrology, plant physiology, aquatic ecology and limnology, conservation biology and fisheries, our scientists focus on two key research problems: Core watershed research quantifies the dynamics of hydrologic, geomorphic and biogeochemical processes in forests and rangelands at multiple scales and defines the biological processes and patterns that affect the distribution, resilience, and persistence of native aquatic, riparian and terrestrial species. Integrated, interdisciplinary research explores the effects of climate variability and climate change on forest, grassland and aquatic ecosystems. Resources in this dataset:Resource Title: Projects, Tools, and Data. File Name: Web Page, url: https://www.fs.fed.us/rm/boise/AWAE/projects.html Projects include Air Temperature Monitoring and Modeling, Biogeochemistry Lab in Colorado, Rangewide Bull Trout eDNA Project, Climate Shield Cold-Water Refuge Streams for Native Trout, Cutthroat trout-rainbow trout hybridization - data downloads and maps, Fire and Aquatic Ecosystems science, Fish and Cattle Grazing reports, Geomophic Road Analysis and Inventory Package (GRAIP) tool for erosion and sediment delivery to streams, GRAIP_Lite - Geomophic Road Analysis and Inventory Package (GRAIP) tool for erosion and sediment delivery to streams, IF3: Integrating Forests, Fish, and Fire, National forest climate change maps: Your guide to the future, National forest contributions to streamflow, The National Stream Internet network, people, data, GIS, analysis, techniques, NorWeST Stream Temperature Regional Database and Model, River Bathymetry Toolkit (RBT), Sediment Transport Data for Idaho, Nevada, Wyoming, Colorado, SnowEx, Stream Temperature Modeling and Monitoring, Spatial Statistical Modeling on Stream netowrks - tools and GIS downloads, Understanding Sculpin DNA - environmental DNA and morphological species differences, Understanding the diversity of Cottusin western North America, Valley Bottom Confinement GIS tools, Water Erosion Prediction Project (WEPP), Great Lakes WEPP Watershed Online GIS Interface, Western Division AFS - 2008 Bull Trout Symposium - Bull Trout and Climate Change, Western US Stream Flow Metric Dataset

The booming drainage design services market, projected to reach $15 billion in 2025 and grow at a 6% CAGR, is driven by urbanization and infrastructure development. Learn about key trends, regional insights, and leading companies shaping this vital sector. Explore market segmentation by application and drainage type.

Shapefiles furnished by the Environmental Engineering Firm (Modern Geosciences) for the clean up site on and around the Shingle Mountain (Blue Star Recycling ).

This line feature class represents levee centerlines for 93 Levee Maintenance Agencies/Reclamation Districts in the Sacramento-San Joaquin Delta. The centerline features contain levee geometry classification that indicates whether a levee segment meets the FEMA’s Hazard Mitigation Plan (HMP) or USACE’s Public Law 84-99 (PL8499) Delta levee standards. There are four categories used in the classification of the centerlines: HMP, Below HMP, Minimally Below HMP, and PL84-99. The classification and other data associated with these centerlines were produced as results of the Levee Geometry Assessment analysis performed by the California Department of Water Resources Delta Levees and Environmental Engineering Branch in 2012. The centerlines used in this analysis are part of the dataset produced from the Delta Levee Anatomy Mapping Project in 2011 through a contract between DWR and the Geographic Information Center at California State University, Chico.

The GIS-based Time model of Gothenburg aims to map the process of urban development in Gothenburg since 1960 and in particular to document the changes in the spatial form of the city - streets, buildings and plots - through time. Major steps have in recent decades been taken when it comes to understanding how cities work. Essential is the change from understanding cities as locations to understanding them as flows (Batty 2013)1. In principle this means that we need to understand locations (or places) as defined by flows (or different forms of traffic), rather than locations only served by flows. This implies that we need to understand the built form and spatial structure of cities as a system, that by shaping flows creates a series of places with very specific relations to all other places in the city, which also give them very specific performative potentials. It also implies the rather fascinating notion that what happens in one place is dependent on its relation to all other places (Hillier 1996)2. Hence, to understand the individual place, we need a model of the city as a whole. Extensive research in this direction has taken place in recent years, that has also spilled over to urban design practice, not least in Sweden, where the idea that to understand the part you need to understand the whole is starting to be established. With the GIS-based Time model for Gothenburg that we present here, we address the next challenge. Place is not only something defined by its spatial relation to all other places in its system, but also by its history, or its evolution over time. Since the built form of the city changes over time, often by cities growing but at times also by cities shrinking, the spatial relation between places changes over time. If cities tend to grow, and most often by extending their periphery, it means that most places get a more central location over time. If this is a general tendency, it does not mean that all places increase their centrality to an equal degree. Depending on the structure of the individual city’s spatial form, different places become more centrally located to different degrees as well as their relative distance to other places changes to different degrees. The even more fascinating notion then becomes apparent; places move over time! To capture, study and understand this, we need a "time model". The GIS-based time model of Gothenburg consists of: • 12 GIS-layers of the street network, from 1960 to 2015, in 5-year intervals • 12 GIS-layers of the buildings from 1960 to 2015, in 5-year intervals • 12 GIS- layers of the plots from1960 to 2015, in 5-year intervals In the GIS-based Time model, for every time-frame, the combination of the three fundamental components of spatial form, that is streets, plots and buildings, provides a consistent description of the built environment at that particular time. The evolution of three components can be studied individually, where one could for example analyze the changing patterns of street centrality over time by focusing on the street network; or, the densification processes by focusing on the buildings; or, the expansion of the city by way of occupying more buildable land, by focusing on plots. The combined snapshots of street centrality, density and land division can provide insightful observations about the spatial form of the city at each time-frame; for example, the patterns of spatial segregation, the distribution of urban density or the patterns of sprawl. The observation of how the interrelated layers of spatial form together evolved and transformed through time can provide a more complete image of the patterns of urban growth in the city. The Time model was created following the principles of the model of spatial form of the city, as developed by the Spatial Morphology Group (SMoG) at Chalmers University of Technology, within the three-year research project ‘International Spatial Morphology Lab (SMoL)’. The project is funded by Älvstranden Utveckling AB in the framework of a larger cooperation project called Fusion Point Gothenburg. The data is shared via SND to create a research infrastructure that is open to new study initiatives. 1. Batty, M. (2013), The New Science of Cities, Cambridge: MIT Press. 2. Hillier, B., (1996), Space Is the Machine. Cambridge: University of Cambridge

This data set defines both current and historic landfills/waste disposal storage sites for the State of Vermont. Historic landfills were identified with the publication of the Vermont Ground Water Pollution Source Inventory by the Agency of Environmental Conservation, Department of Water Resources and Environmental Engineering Water Quality Division, December 1980. Current landfill locations supplied by the Solid Waste Division of the Vermont Agency of Natural Resources, Department of Environmental Conservation.This dataset includes: active landfills - currently accepting waste, geo-located; closed landfills- ceased accepting waste and completed closure under solid waste regulations (post-1988), geo-located; historic landfills - ceased accepting waste prior to solid waste regulation implementation (pre-1988), locations obtained from a 1990 Vermont Groundwater Pollution Source Inventory completed by the Department of Waster Resources and Environmental Engineering Groundwater Management Section. The listing of historic landfills is likely incomplete.

This series of web pages presents site information for 63 Ground Control Points (GCP's) measured near Barrow, Alaska, during the summer of 2001 using Differential GPS. The GCP's were measured on the corners of buildings, ends of snowfences, base of telephone poles, and other features visible on small- to large-scale imagery. They are concentrated generally within 2 km of the Chukchi coast (coinciding with extent of the year 2000 air photos). The GCP's will help researchers and other scientists working in the area to establish precise geographic or UTM coordinates for field sites, and to assist with georectification of aerial photography and satellite imagery.

 The GCP's were measured as part of an ongoing research project, Alaska North
 Slope Climate Impact Assessment (ANSCIA), which is funded by the National
 Science Foundation's program on Human Dimensions of the Arctic System. This
 database is being made publicly available as part of our objectives for data
 sharing and outreach to both the scientific community and the public at large.

 [Summary provided by University of Colorado.]

Environmental Easements are required for remedial projects which rely upon one or more institutional and/or engineering controls. The Environmental Easement runs with the land in favor of the State, subject to the provisions of ECL Article 71, Title 36, and contains the use restriction(s) and/or any prohibition(s) on the use of land in a manner inconsistent with engineering controls. The placement of an Environmental Easement provides an effective and enforceable means of encouraging the reuse and redevelopment of a controlled property, at a level that has been determined to be safe for a specific use, while ensuring the performance of operation, maintenance, and/or monitoring requirements.For background information, see Finalizing Remedial Projects: Easements, Certificates Of Completion, And TemplatesFor layer information or to download layer, see Environmental EasementsDownload the metadata to learn more information about how the data was created and details about the attributes. Metadata Link

The booming Environmental Impact Assessment (EIA) market is projected to reach $32.11 billion by 2033, driven by stringent environmental regulations and the growing need for sustainable development. Explore market trends, key players, and regional insights in this comprehensive analysis.

A Cell-Based, Dynamic Flow Direction Model (DFD Model) for Water Balance Calculations Simulating Overland Runoff through Depressions Implemented using Python and GIS

Understanding the primary effects of anthropogenic activities and natural factors on river water quality is important in the study and efficient management of water resources. In this study, analysis of Variance (ANOVA), Principal component analysis (PCA), Pearson correlations, Multiple regression analysis (MRA) and Redundancy analysis (RDA) were applied as an integrated approach in a GIS environment to explore the temporal and spatial variations in river water quality and to estimate the influence of watershed land use, topography and socio-economic factors on river water quality based on 3 years of water quality monitoring data for the Cao-E River system. The statistical analysis revealed that TN, pH and temperature were generally higher in the rainy season, whereas BOD5, DO and turbidity were higher in the dry season. Spatial variations in river water quality were related to numerous anthropogenic and natural factors. Urban land use was found to be the most important explanatory variable for BOD5, CODMn, TN, DN, NH4+-N, NO3−-N, DO, pH and TP. The animal husbandry output per capita was an important predictor of TP and turbidity, and the gross domestic product per capita largely determined spatial variations in EC. The remaining unexplained variance was related to other factors, such as topography. Our results suggested that pollution control of animal waste discharge in rural settlements, agricultural runoff in cropland, industrial production pollution and domestic pollution in urban and industrial areas were important within the Cao-E River basin. Moreover, the percentage of the total overall river water quality variance explained by an individual variable and/or all environmental variables (according to RDA) can assist in quantitatively identifying the primary factors that control pollution at the watershed scale.

Discover the booming Geology, Water & Soil Analysis Software market! This in-depth analysis reveals key trends, growth drivers, and regional market shares from 2019-2033, featuring insights into GIS, data analytics, and leading companies. Learn about market size, CAGR, and future projections.