Integrating atmospheric deposition, soil erosion and sewer transport models to assess the transfer of traffic-related pollutants in urban areas

2017 ◽  
Vol 96 ◽  
pp. 158-171 ◽  
Author(s):  
Yi Hong ◽  
Celine Bonhomme ◽  
Bastian Van den Bout ◽  
Victor Jetten ◽  
Ghassan Chebbo
Keyword(s):  
Soil Erosion ◽  
Atmospheric Deposition ◽  
Urban Areas ◽  
Transport Models

scholarly journals Correlating elements content in mosses collected in 2015 across Germany with spatially associated characteristics of sampling sites and their surroundings

2019 ◽  
Vol 31 (1) ◽  
Author(s):  
Stefan Nickel ◽  
Winfried Schröder
Keyword(s):  
Land Use ◽  
Population Density ◽  
Atmospheric Deposition ◽  
Vegetation Structure ◽  
Urban Areas ◽  
Explanatory Power ◽  
Spatial Density ◽  
Area Index ◽  
Explanatory Variables ◽  
Tree Layer

Abstract Background The aim of the study was a statistical evaluation of the statistical relevance of potentially explanatory variables (atmospheric deposition, meteorology, geology, soil, topography, sampling, vegetation structure, land-use density, population density, potential emission sources) correlated with the content of 12 heavy metals and nitrogen in mosses collected from 400 sites across Germany in 2015. Beyond correlation analysis, regression analysis was performed using two methods: random forest regression and multiple linear regression in connection with commonality analysis. Results The strongest predictor for the content of Cd, Cu, Ni, Pb, Zn and N in mosses was the sampled species. In 2015, the atmospheric deposition showed a lower predictive power compared to earlier campaigns. The mean precipitation (2013–2015) is a significant factor influencing the content of Cd, Pb and Zn in moss samples. Altitude (Cu, Hg and Ni) and slope (Cd) are the strongest topographical predictors. With regard to 14 vegetation structure measures studied, the distance to adjacent tree stands is the strongest predictor (Cd, Cu, Hg, Zn, N), followed by the tree layer height (Cd, Hg, Pb, N), the leaf area index (Cd, N, Zn), and finally the coverage of the tree layer (Ni, Cd, Hg). For forests, the spatial density in radii 100–300 km predominates as significant predictors for Cu, Hg, Ni and N. For the urban areas, there are element-specific different radii between 25 and 300 km (Cd, Cu, Ni, Pb, N) and for agricultural areas usually radii between 50 and 300 km, in which the respective land use is correlated with the element contents. The population density in the 50 and 100 km radius is a variable with high explanatory power for all elements except Hg and N. Conclusions For Europe-wide analyses, the population density and the proportion of different land-use classes up to 300 km around the moss sampling sites are recommended.

scholarly journals Ensemble forecasts of air quality in eastern China – Part 1: Model description and implementation of the MarcoPolo–Panda prediction system, version 1

2019 ◽  
Vol 12 (1) ◽  
pp. 33-67 ◽  
Author(s):  
Guy P. Brasseur ◽  
Ying Xie ◽  
Anna Katinka Petersen ◽  
Idir Bouarar ◽  
Johannes Flemming ◽  
...  
Keyword(s):  
Air Quality ◽  
Urban Areas ◽  
Eastern China ◽  
Model Description ◽  
Transport Models ◽  
Ensemble Forecasts ◽  
Chemical Transport Models ◽  
Systematic Biases ◽  
Forecasting System ◽  
The Mean

Abstract. An operational multi-model forecasting system for air quality including nine different chemical transport models has been developed and provides daily forecasts of ozone, nitrogen oxides, and particulate matter for the 37 largest urban areas of China (population higher than 3 million in 2010). These individual forecasts as well as the mean and median concentrations for the next 3 days are displayed on a publicly accessible website (http://www.marcopolo-panda.eu, last access: 7 December 2018). The paper describes the forecasting system and shows some selected illustrative examples of air quality predictions. It presents an intercomparison of the different forecasts performed during a given period of time (1–15 March 2017) and highlights recurrent differences between the model output as well as systematic biases that appear in the median concentration values. Pathways to improve the forecasts by the multi-model system are suggested.

scholarly journals Air TRITIA transport model

2018 ◽  
Vol 196 ◽  
pp. 04080
Author(s):  
Marek Drličiak ◽  
Ján Čelko
Keyword(s):  
Air Quality ◽  
Urban Areas ◽  
Spatial Information ◽  
Transport Model ◽  
Emission Model ◽  
Transport Models ◽  
Traffic Models ◽  
Main Input ◽  
The University ◽  
Information Database

The project AIRTRITIA has a uniform approach to the air pollution management system for functional urban areas in Tritia region. AIR TRITIA aims to increase air quality management capacities of public sector bodies through the development of a unified spatial information database, introducing new management and pollution prediction tools and air quality strategies. The article presents the transport model of Tritia region. The University of Žilina merged data from several traffic models to one on Tritia region. The traffic model will be the main input for the generalized emission model. The main topic of the article is a description of merging of the transport models. The detailed description is aimed to Žilina function area (FUA) in Slovakia.

scholarly journals Soil Erosion Assessment and Prediction in Urban Landscapes: A New G2 Model Approach

2021 ◽  
Vol 11 (9) ◽  
pp. 4154
Author(s):  
Siniša Polovina ◽  
Boris Radić ◽  
Ratko Ristić ◽  
Jovan Kovačević ◽  
Vukašin Milčanović ◽  
...  
Keyword(s):  
Soil Erosion ◽  
Land Cover ◽  
Urban Areas ◽  
Soil Loss ◽  
Soil Degradation ◽  
Machine Learning Techniques ◽  
Slight Reduction ◽  
Master Plan ◽  
Time Periods ◽  
The Impact

Soil erosion is a global problem that negatively affects the quality of the environment, the availability of natural resources, as well as the safety of inhabitants. Soil erosion threatens the functioning of urban areas, which was the reason for choosing the territory of the Master Plan of Belgrade (Serbia) as the research area. The calculation of soil erosion loss was analyzed using the G2 erosion model. The model belongs to a group of empirical models and is based on the synthesis of the equation from the Revised Universal Soil Loss Equation (RUSLE) and the Erosion Potential Method (EPM). The estimation of soil degradation was analyzed in two time periods (2001 and 2019), which represent the time boundaries of the management of the Master Plan of Belgrade. The novel approach used in this research is based on using the land cover inventory as a dynamic indicator of the urbanization process. Land cover was identified using remote sensing, machine learning techniques, and the random forest algorithm applied to multispectral satellite images of the Landsat mission in combination with spectral indices. Climatic parameters were analyzed on the basis of data from meteorological stations (first scenario, i.e., 2001), as well as on simulations of changes based on climate scenario RCP8.5 (representative concentration pathways) concerning the current condition of the land cover (second scenario). A comparative analysis of the two time periods identified a slight reduction in total soil loss. For the first period, the average soil loss value is 4.11 t·ha−1·y−1. The analysis of the second period revealed an average value of 3.63 t·ha−1·y−1. However, the increase in non-porous surfaces has led to a change in the focus of soil degradation. Increased average soil loss as one of the catalysts of torrential flood frequencies registered on natural and semi-natural areas were 43.29% and 16.14%, respectively. These results are a significant contribution to the study of soil erosion in urban conditions under the impact of climate change.

scholarly journals Study of Soil Erosian at a Site near Chemical Engineering Laboratory in UNIMAS

2013 ◽  
Vol 4 (2) ◽  
pp. 1-6
Author(s):  
Fizzahutiah Taha ◽  
Shenbaga R. Kaniraj
Keyword(s):  
Soil Erosion ◽  
Urban Areas ◽  
Soil Loss ◽  
Chemical Engineering ◽  
Environmental Concern ◽  
Control Measure ◽  
Soil Surface ◽  
Bare Soil ◽  
Erosion Risk ◽  
A Site

Soil erosion is one of the problems of environmental concern. Natural causes such as rainfall and human development activities are the two main factors that can cause soil erosion. In order to control soil erosion, especially in urban areas, the bare soil surface needs to be covered by plants as much as possible. Re-vegetation, the best permanent erosion control measure, might take time to be complete. Therefore, some suitable temporary measures should be applied to minimize the amount of soil loss. Topographical features and climate are among the factors that determine the amount of soil erosion. In order to control the rate of erosion, it is important to estimate the amount of soil loss. Universal Soil Loss Equation (USLE) is one of the approaches to estimate the rate of soil loss. In this study, the topographical features of a site prone to erosion within University Malaysia Sarawak (UNIMAS), were investigated by field survey. Laboratory experiments were carried out on soil samples collected from the site. Theparameters for use in USLE were evaluated. The soil loss at the site in 2011 was estimated as 52.85 t ha-1 and the soil erosion risk atthe site was categorized as moderately high. 

Quantitative assessment of gully erosion dynamics using a GIS implementation of Sidorchuks' DYNGUL model in Southern KwaZulu-Natal, South Africa

2020 ◽  
Author(s):  
adel omran ◽  
Dietrich Schroeder ◽  
Christian Sommer ◽  
Volker Hochschild ◽  
Aleksey Sidorchuk ◽  
...  
Keyword(s):  
South Africa ◽  
Soil Erosion ◽  
Urban Areas ◽  
Side Wall ◽  
Mass Conservation ◽  
Gully Erosion ◽  
Physical Parameters ◽  
Erosion Model ◽  
Erosion Processes ◽  
Kwazulu Natal

<p>Soil erosion is considered as one of the main threats affecting both rural and urban areas in many different parts all over the world. Therefore, increasing attention has been attributed to soil erosion in the last decades. This can also be documented by an increasing number of studies targeting soil erosion assessment using qualitative and quantitative models. However, gully erosion phenomena have been widely neglected in erosion modelling due to the nature and complexity of the related processes and hence, it is also more difficult to simulate, predict and to visualize its effects. Sidorchuk (1999) established a Fortran based dynamic erosion model called DYNGUL to describe the first quick stage of gully development, coinciding with the main changes in gully morphology; like changes in volume, area and elevation of the longitudinal profile. The DYNGUL model is based on the solution of the equations of mass conservation and gully bed deformation. The model of straight slope stability was used to predict gully side wall inclination and of the finite morphology of the gully. The objective of this contribution is to establish a GIS tool for a quantitative gully erosion assessment and to predict gully evolution over time. The tool will help: i) to cope with or mitigate gully erosion processes and ii) to plan measures to stabilize the landscape affected by gully erosion. Therefore, we developed a Python-based tool that can be applied in a GIS environment. The model was tested its performance and the sensitivity of physical parameters with data from a gully in the Drakensberg Mountains, KwaZulu-Natal, South Africa. The results of the gully erosion model showed that their sensitivity to lithological and hydrological factors is rather high.</p>

scholarly journals Estimation of soil erosion dynamics using remote sensing and swat in Kopaonik National Park, Serbia

2021 ◽  
Vol 71 (3) ◽  
pp. 231-247
Author(s):  
Ivan Potic ◽  
Nina Curcic ◽  
Milan Radovanovic ◽  
Gorica Stanojevic ◽  
Slavica Malinovic-Milicevic ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Soil Erosion ◽  
Surface Runoff ◽  
Urban Areas ◽  
National Park ◽  
Management Practices ◽  
Agricultural Land ◽  
Assessment Tool ◽  
Land Application ◽  
Mountain Areas

Soil erosion is a global environmental and economic problem that is significantly related to land-use changes. Over the last decades, several mountain areas in Serbia were exposed to strong human pressure caused by winter tourism development. The largest ski center in Serbia is situated on Kopaonik Mountain within the boundaries of Kopaonik National Park, where the conflict between economic and conservation goals is rapidly growing. In this study, we calculated the sedimentation and surface runoff in three sub-basins in the area of Kopaonik ski resort for two years (1984 and 2018) using the Soil and Water Assessment Tool (SWAT) and analyzed the changes that occurred during the observed period. The results show an increase in surface runoff and sediment yield in sub-basins 1 and 3 and a decrease in sub-basin 2. The analysis of land cover change shows an expansion of evergreen forests, appearance of barren soil and urban areas, reduction of mixed forests and pastures, and the appearance of deciduous forests. These findings indicate that in the area studied, the dominant processes are the development of tourism and natural revegetation of abandoned agricultural land. Application of remote sensing techniques and SWAT contributes to identifying and monitoring land degradation problems and improving conservation and management practices.

Agriculture and Soil Erosion

2007 ◽  
Author(s):  
Carol P. Harden ◽  
Glenn G. Hyman
Keyword(s):  
Soil Erosion ◽  
South America ◽  
International Development ◽  
Urban Areas ◽  
Amazon Basin ◽  
Physical Geography ◽  
Natural Environments ◽  
Post Colonial ◽  
Agricultural Trends ◽  
Preferred Species

People have manipulated the natural environments of South America for agricultural purposes for several millennia. While agriculture is strongly affected by the physical attributes of a place—soil, water, climate, biota, and topography—agriculture changes a landscape’s physical and biological characteristics and processes. Agriculture may involve short- and long-term conversion of forest to cropland and pasture, modification of topography and drainage, and the introduction and propagation of exotic species. Soil erosion, much of which is caused by agriculture, is a major concern in South America. This chapter introduces the patterns of agriculture in South America and examines agricultural trends. It then reviews the causes and consequences of soil erosion at continental to local scales, providing examples from research conducted across the continent. As population grows and demand for agricultural production increases, knowledge of the physical geography of soil erosion will be even more critical for the sustainability of agriculture in South America. Agriculture is broadly defined here to encompass annual and permanent crops, tree crops, and livestock. Agricultural patterns of South America today reflect great differences in the continent’s natural environments. They also reflect the influence of international and global markets, the impacts of national policies, and the imprints of preand post-colonial settlement patterns, preferred species, and cultural preferences. The wide range of climates in South America allows a great variety of temperate and tropical fruits, vegetables, and grains to flourish. Historically, the diverse agricultural capabilities of different parts of the continent have been fundamental influences in the development of pre- and post-colonial human habitation and economic patterns (U.S. Agency for International Development, 1993; see chapters 16 and 17). At the continental scale, agriculture occurs across almost all regions of South America. It is notably absent only in the Gran Chaco, rugged portions of the high Andes, and desert landscapes along the Pacific coast of northern Chile and southern Perú. In practice, there is little cropland in sparsely populated regions, especially in the Amazon basin, and in densely populated urban areas, even where the lands and climates of those places are capable of supporting agriculture.

Equidistance

2017 ◽  
pp. 129-150
Author(s):  
Guenter Emberger ◽  
Paul Pfaffenbichler
Keyword(s):  
Empirical Evidence ◽  
Urban Areas ◽  
Mode Choice ◽  
Policy Formulation ◽  
Transport Policy ◽  
Parking Space ◽  
Transport Models ◽  
Transport Planning ◽  
Space Instruments ◽  
Pricing Policies

The chapter will provide empirical evidence how parking organization (location, number and pricing policies of parking spaces in urban areas) influences the mode choice of transport system users. Following from that, the presently applied practice of parking space modelling within existing transport models will be presented and discussed critically. It will be shown which influence on transport demand the different parking space instruments have in existing 4-stage models (FSM) and where flaws and errors in the transport demand and mode choice estimation can occur. Finally, potential improvements how to overcome these afore mentioned shortcomings are presented and the impacts on future transport planning and transport policy formulation towards sustainability will be introduced.

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