The Experts below are selected from a list of 20688 Experts worldwide ranked by ideXlab platform
Wei Ouyang - One of the best experts on this subject based on the ideXlab platform.
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Spatial and temporal trend of Chinese manure Nutrient Pollution and assimilation capacity of cropland and grassland
Environmental science and pollution research international, 2013Co-Authors: Wei Ouyang, Fanghua Hao, Xinfeng Wei, Haobo HuangAbstract:Dynamics of livestock and poultry manure Nutrient was analyzed at a provincial scale from 2002 to 2008. The Nutrient capacity of 18 kinds of croplands and grasslands to assimilate Nutrients was assessed in the same temporal–spatial scale. Manure nitrogen (N) had increased from 5.111 to 6.228 million tons (MT), while manure phosphorus (P) increased from 1.382 to 1.607 MT. Manure N and P share similar spatial patterns of yields, but proportion of specialized livestock husbandry and contribution of leading livestock categories (swine, cattle, cow, sheep, layer chicken, broiler chicken) were different. The Nutrients generated from dominant seven provinces took more than about half of total manure N in China. After subtracting the chemical fertilizers, there were some manure Nutrient capacities in western part of China. Risk analysis of manure Nutrient Pollution overload in eastern and southern parts of China was serious, which should restrict livestock's developments. Amount of chemical fertilizers applied should be reduced to make room for manure Nutrients. For the sake of greenhouse effects, the emission of methane (CH4) and nitrous oxide (NO x ) emissions in China is serious for the global change, thus merits further statistics and studies. The spatial and temporal pattern of Chinese manure Nutrient Pollution from livestock and the assimilation capacity of cropland and grassland can provide useful information for policy development on Chinese soil environment and livestock.
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long term vegetation landscape pattern with non point source Nutrient Pollution in upper stream of yellow river basin
Journal of Hydrology, 2010Co-Authors: Wei Ouyang, Andrew K Skidmore, A G Toxopeus, Fanghua HaoAbstract:Grassland, forest, and farmland are the dominant land covers in upper catchments of the Yellow River and their landscape status has direct connection with dynamics of non-point source (NPS) Pollution. Understanding the correlations between landscape variables and different formats of NPS Nutrients pollutants is a priority in order to assess pollutants loading and predicting the impact on surface water quality. The regional vegetative cover in 1977, 1996, 2000 and 2006 was determined by classifying historical multi-temporal Landsat imagery and clipping data from the National Landcover Database. The landscape pattern is expressed means of metrics such as patch density, edge density, fractal distribution index, all of which were calculated by FRAGSTATS. The soil and water assessment tool (SWAT) was used to analyze and visualize the fate of NPS nitrogen and phosphorus loads in diverse formats from different land cover types in different years. Statistical analysis indicated that the grassland landscapes played a major role in NPS Nutrient Pollution dynamics and grassland patch edges benefited Pollution control. However, the presence of more forest and farmland lead to more NPS nitrogen emissions. It was found that grassland areas reduced nitrogen loss and had a multi-function role in the Nutrient Pollution process. Farmland was the direct source of organic Nutrients, but did not have great impacts on sediment P and soluble N loadings. Forest areas contributed NPS Nutrients Pollution loading. The statistical models derived in this study can be used to estimate watershed NPS Nutrient Pollution losses. These equations can help identify Pollution sources and suggest appropriate and effective solutions for planing basin management practices.
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Temporal-spatial dynamics of vegetation variation on non-point source Nutrient Pollution.
Ecological Modelling, 2009Co-Authors: Wei Ouyang, Fanghua Hao, Xuelei Wang, Raghavan SrinivasanAbstract:The temporal-spatial interaction of land cover and non-point source (NPS) Nutrient Pollution were analyzed with the Soil and Water Assessment Tool (SWAT) to simulate the temporal-spatial features of NPS Nutrient loading in the upper stream of the Yellow River catchment. The corresponding land cover data variance was expressed by the normalized difference vegetation index (NDVI) that was calculated from MODIS images. It was noted that the temporal variation of land cover NDVI was significantly correlated with NPS Nutrient loading. The regression analysis indicated that vegetation not only detained NPS Nutrient Pollution transportation, but also contributed to sustainable loading. The temporal analysis also confirmed that regional NDVI was an effective index for monthly assessment of NPS nitrogen and phosphorus loading. The spatial variations of NPS Nutrient loading can be classified with land cover status. The high loadings of NPS nitrogen in high NDVI subbasins indicated that forestry and farmland are the main critical loss areas. Farmland contributed sustainable soluble N, but the loading of soluble and organic N from grassland subbasins was much lower. Most P loading came from the areas covered with dense grassland and forestry, which cannot directly discharge to local water bodies. However, some NPS phosphorus from suburban farmland can directly discharge into adjacent water bodies. The interactions among Nutrient loading, NDVI, and slope were also analyzed. This study confirmed that the integration of NPS modeling, geographic information systems, and remote sensing is needed to understand the interactive dynamics of NPS Nutrient loading. Understanding the temporal-spatial variation of NPS Nutrients and their correlations with land cover will help NPS Pollution prevention and water quality management efforts. Therefore, the proposed method for evaluating NPS Nutrient loading by land cover NDVI can be an effective tool for Pollution evaluation and watersheds planning.
D B Boorman - One of the best experts on this subject based on the ideXlab platform.
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which offers more scope to suppress river phytoplankton blooms reducing Nutrient Pollution or riparian shading
Science of The Total Environment, 2010Co-Authors: Mike Hutchins, Andrew C Johnson, Amelie Deflandrevlandas, Sean Comber, Paulette Posen, D B BoormanAbstract:River flow and quality data, including chlorophyll-a as a surrogate for river phytoplankton biomass, were collated for the River Ouse catchment in NE England, which according to established criteria is a largely unpolluted network. Against these data, a daily river quality model (QUESTOR) was setup and successfully tested. Following a review, a river quality classification scheme based on phytoplankton biomass was proposed. Based on climate change predictions the model indicated that a shift from present day oligotrophic/mesotrophic conditions to a mesotrophic/eutrophic system could occur by 2080. Management options were evaluated to mitigate against this predicted decline in quality. Reducing Nutrient Pollution was found to be less effective at suppressing phytoplankton growth than the less costly option of establishing riparian shading. In the Swale tributary, ongoing efforts to reduce phosphorus loads in sewage treatment works will only reduce peak (95th percentile) phytoplankton by 11%, whereas a reduction of 44% is possible if riparian tree cover is also implemented. Likewise, in the Ure, whilst reducing nitrate loads by curtailing agriculture in the headwaters may bring about a 10% reduction, riparian shading would instead reduce levels by 47%. Such modelling studies are somewhat limited by insufficient field data but offer a potentially very valuable tool to assess the most cost-effective methods of tackling effects of eutrophication.
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Which offers more scope to suppress river phytoplankton blooms: reducing Nutrient Pollution or riparian shading?
The Science of the total environment, 2010Co-Authors: Mike Hutchins, Andrew C Johnson, Sean Comber, Paulette Posen, Amelie Deflandre-vlandas, D B BoormanAbstract:River flow and quality data, including chlorophyll-a as a surrogate for river phytoplankton biomass, were collated for the River Ouse catchment in NE England, which according to established criteria is a largely unpolluted network. Against these data, a daily river quality model (QUESTOR) was setup and successfully tested. Following a review, a river quality classification scheme based on phytoplankton biomass was proposed. Based on climate change predictions the model indicated that a shift from present day oligotrophic/mesotrophic conditions to a mesotrophic/eutrophic system could occur by 2080. Management options were evaluated to mitigate against this predicted decline in quality. Reducing Nutrient Pollution was found to be less effective at suppressing phytoplankton growth than the less costly option of establishing riparian shading. In the Swale tributary, ongoing efforts to reduce phosphorus loads in sewage treatment works will only reduce peak (95th percentile) phytoplankton by 11%, whereas a reduction of 44% is possible if riparian tree cover is also implemented. Likewise, in the Ure, whilst reducing nitrate loads by curtailing agriculture in the headwaters may bring about a 10% reduction, riparian shading would instead reduce levels by 47%. Such modelling studies are somewhat limited by insufficient field data but offer a potentially very valuable tool to assess the most cost-effective methods of tackling effects of eutrophication.
Victor M. Zavala - One of the best experts on this subject based on the ideXlab platform.
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Valuing economic impact reductions of Nutrient Pollution from livestock waste
Resources conservation and recycling, 2021Co-Authors: Apoorva M. Sampat, Andrea L. Hicks, Gerardo J. Ruiz-mercado, Victor M. ZavalaAbstract:Abstract Nutrient Pollution from livestock waste impacts both fresh and marine coastal waters. Harmful algae blooms (HABs) are a common ecosystem-level response to such Pollution that is detrimental to both aquatic life and human health and that generates economic losses (e.g., property values and lost tourism). Waste treatment and management technologies are not well established practices due, in part, to the difficulty to attribute economic value to associated social and environmental impacts of Nutrient Pollution. In this work, we propose a computational framework to quantify the economic impacts of HABs. We demonstrate the advantage of quantifying these impacts through a case study on livestock waste management in the Upper Yahara watershed region (in the state of Wisconsin, USA). Our analysis reveals that every excess kilogram of phosphorus runoff from livestock waste results in total economic losses of 74.5 USD. Furthermore, we use a coordinated market analysis to demonstrate that this economic impact provides a strong enough incentive to activate a Nutrient management and valorization market that can help balance phosphorus within the study area. The proposed framework can help state, tribes, and federal regulatory agencies develop regulatory and non-regulatory policies to mitigate the impacts of Nutrient Pollution.
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Logistics Network Management of Livestock Waste for Spatiotemporal Control of Nutrient Pollution in Water Bodies.
ACS sustainable chemistry & engineering, 2019Co-Authors: Apoorva M Sampata, Gerardo J. Ruiz-mercado, Victor M. ZavalaAbstract:Nutrient Pollution is a widespread water quality problem, which originates from excess Nutrient runoff from agricultural land, improperly managed farming operations, and point sources such as waste...
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Spatio-Temporal Control of Nutrient Pollution from Organic Waste
Computer Aided Chemical Engineering, 2019Co-Authors: Gerardo J. Ruiz-mercado, Victor M. ZavalaAbstract:Abstract Better management of anthropogenic organic waste and other primary sources of Nutrient Pollution such as agricultural, municipal, and industrial waste, will reduce the human impact on the environment. Harmful algal blooms (HABs) are a major environmental impact from organic waste and Nutrient Pollution. HABs can pose severe threats to human health due to the release of dangerous toxins in fresh or marine water that can negatively affect public health, increase treatment costs for drinking water, and cause enormous economic loss in industries that depend on clean water. In this study, the effect of decisions made in the organic waste supply chain (SC) on reducing the potential for HABs is investigated by integrating three types of models: a SC optimization model, a Nutrient transport model, and an algae growth model. This contribution presents a comprehensive spatio-temporal management strategy for short-term HAB reduction by adjusting components in the SC, including technologies, logistics, Nutrient management plans (NMPs) or environmental costs, and seasonal waste storage planning. In addition, it is presented a case study of the Upper Yahara Watershed in the State of Wisconsin to illustrate the practicability of this modeling framework.
Fanghua Hao - One of the best experts on this subject based on the ideXlab platform.
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Spatial and temporal trend of Chinese manure Nutrient Pollution and assimilation capacity of cropland and grassland
Environmental science and pollution research international, 2013Co-Authors: Wei Ouyang, Fanghua Hao, Xinfeng Wei, Haobo HuangAbstract:Dynamics of livestock and poultry manure Nutrient was analyzed at a provincial scale from 2002 to 2008. The Nutrient capacity of 18 kinds of croplands and grasslands to assimilate Nutrients was assessed in the same temporal–spatial scale. Manure nitrogen (N) had increased from 5.111 to 6.228 million tons (MT), while manure phosphorus (P) increased from 1.382 to 1.607 MT. Manure N and P share similar spatial patterns of yields, but proportion of specialized livestock husbandry and contribution of leading livestock categories (swine, cattle, cow, sheep, layer chicken, broiler chicken) were different. The Nutrients generated from dominant seven provinces took more than about half of total manure N in China. After subtracting the chemical fertilizers, there were some manure Nutrient capacities in western part of China. Risk analysis of manure Nutrient Pollution overload in eastern and southern parts of China was serious, which should restrict livestock's developments. Amount of chemical fertilizers applied should be reduced to make room for manure Nutrients. For the sake of greenhouse effects, the emission of methane (CH4) and nitrous oxide (NO x ) emissions in China is serious for the global change, thus merits further statistics and studies. The spatial and temporal pattern of Chinese manure Nutrient Pollution from livestock and the assimilation capacity of cropland and grassland can provide useful information for policy development on Chinese soil environment and livestock.
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long term vegetation landscape pattern with non point source Nutrient Pollution in upper stream of yellow river basin
Journal of Hydrology, 2010Co-Authors: Wei Ouyang, Andrew K Skidmore, A G Toxopeus, Fanghua HaoAbstract:Grassland, forest, and farmland are the dominant land covers in upper catchments of the Yellow River and their landscape status has direct connection with dynamics of non-point source (NPS) Pollution. Understanding the correlations between landscape variables and different formats of NPS Nutrients pollutants is a priority in order to assess pollutants loading and predicting the impact on surface water quality. The regional vegetative cover in 1977, 1996, 2000 and 2006 was determined by classifying historical multi-temporal Landsat imagery and clipping data from the National Landcover Database. The landscape pattern is expressed means of metrics such as patch density, edge density, fractal distribution index, all of which were calculated by FRAGSTATS. The soil and water assessment tool (SWAT) was used to analyze and visualize the fate of NPS nitrogen and phosphorus loads in diverse formats from different land cover types in different years. Statistical analysis indicated that the grassland landscapes played a major role in NPS Nutrient Pollution dynamics and grassland patch edges benefited Pollution control. However, the presence of more forest and farmland lead to more NPS nitrogen emissions. It was found that grassland areas reduced nitrogen loss and had a multi-function role in the Nutrient Pollution process. Farmland was the direct source of organic Nutrients, but did not have great impacts on sediment P and soluble N loadings. Forest areas contributed NPS Nutrients Pollution loading. The statistical models derived in this study can be used to estimate watershed NPS Nutrient Pollution losses. These equations can help identify Pollution sources and suggest appropriate and effective solutions for planing basin management practices.
-
Temporal-spatial dynamics of vegetation variation on non-point source Nutrient Pollution.
Ecological Modelling, 2009Co-Authors: Wei Ouyang, Fanghua Hao, Xuelei Wang, Raghavan SrinivasanAbstract:The temporal-spatial interaction of land cover and non-point source (NPS) Nutrient Pollution were analyzed with the Soil and Water Assessment Tool (SWAT) to simulate the temporal-spatial features of NPS Nutrient loading in the upper stream of the Yellow River catchment. The corresponding land cover data variance was expressed by the normalized difference vegetation index (NDVI) that was calculated from MODIS images. It was noted that the temporal variation of land cover NDVI was significantly correlated with NPS Nutrient loading. The regression analysis indicated that vegetation not only detained NPS Nutrient Pollution transportation, but also contributed to sustainable loading. The temporal analysis also confirmed that regional NDVI was an effective index for monthly assessment of NPS nitrogen and phosphorus loading. The spatial variations of NPS Nutrient loading can be classified with land cover status. The high loadings of NPS nitrogen in high NDVI subbasins indicated that forestry and farmland are the main critical loss areas. Farmland contributed sustainable soluble N, but the loading of soluble and organic N from grassland subbasins was much lower. Most P loading came from the areas covered with dense grassland and forestry, which cannot directly discharge to local water bodies. However, some NPS phosphorus from suburban farmland can directly discharge into adjacent water bodies. The interactions among Nutrient loading, NDVI, and slope were also analyzed. This study confirmed that the integration of NPS modeling, geographic information systems, and remote sensing is needed to understand the interactive dynamics of NPS Nutrient loading. Understanding the temporal-spatial variation of NPS Nutrients and their correlations with land cover will help NPS Pollution prevention and water quality management efforts. Therefore, the proposed method for evaluating NPS Nutrient loading by land cover NDVI can be an effective tool for Pollution evaluation and watersheds planning.
Mike Hutchins - One of the best experts on this subject based on the ideXlab platform.
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which offers more scope to suppress river phytoplankton blooms reducing Nutrient Pollution or riparian shading
Science of The Total Environment, 2010Co-Authors: Mike Hutchins, Andrew C Johnson, Amelie Deflandrevlandas, Sean Comber, Paulette Posen, D B BoormanAbstract:River flow and quality data, including chlorophyll-a as a surrogate for river phytoplankton biomass, were collated for the River Ouse catchment in NE England, which according to established criteria is a largely unpolluted network. Against these data, a daily river quality model (QUESTOR) was setup and successfully tested. Following a review, a river quality classification scheme based on phytoplankton biomass was proposed. Based on climate change predictions the model indicated that a shift from present day oligotrophic/mesotrophic conditions to a mesotrophic/eutrophic system could occur by 2080. Management options were evaluated to mitigate against this predicted decline in quality. Reducing Nutrient Pollution was found to be less effective at suppressing phytoplankton growth than the less costly option of establishing riparian shading. In the Swale tributary, ongoing efforts to reduce phosphorus loads in sewage treatment works will only reduce peak (95th percentile) phytoplankton by 11%, whereas a reduction of 44% is possible if riparian tree cover is also implemented. Likewise, in the Ure, whilst reducing nitrate loads by curtailing agriculture in the headwaters may bring about a 10% reduction, riparian shading would instead reduce levels by 47%. Such modelling studies are somewhat limited by insufficient field data but offer a potentially very valuable tool to assess the most cost-effective methods of tackling effects of eutrophication.
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Which offers more scope to suppress river phytoplankton blooms: reducing Nutrient Pollution or riparian shading?
The Science of the total environment, 2010Co-Authors: Mike Hutchins, Andrew C Johnson, Sean Comber, Paulette Posen, Amelie Deflandre-vlandas, D B BoormanAbstract:River flow and quality data, including chlorophyll-a as a surrogate for river phytoplankton biomass, were collated for the River Ouse catchment in NE England, which according to established criteria is a largely unpolluted network. Against these data, a daily river quality model (QUESTOR) was setup and successfully tested. Following a review, a river quality classification scheme based on phytoplankton biomass was proposed. Based on climate change predictions the model indicated that a shift from present day oligotrophic/mesotrophic conditions to a mesotrophic/eutrophic system could occur by 2080. Management options were evaluated to mitigate against this predicted decline in quality. Reducing Nutrient Pollution was found to be less effective at suppressing phytoplankton growth than the less costly option of establishing riparian shading. In the Swale tributary, ongoing efforts to reduce phosphorus loads in sewage treatment works will only reduce peak (95th percentile) phytoplankton by 11%, whereas a reduction of 44% is possible if riparian tree cover is also implemented. Likewise, in the Ure, whilst reducing nitrate loads by curtailing agriculture in the headwaters may bring about a 10% reduction, riparian shading would instead reduce levels by 47%. Such modelling studies are somewhat limited by insufficient field data but offer a potentially very valuable tool to assess the most cost-effective methods of tackling effects of eutrophication.
