Temporal-spatial dynamics of vegetation variation on non-point source nutrient pollution

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.     

Eco-hydrological modelling in a highly regulated lowland catchment to find measures for improving water quality

Water quality modelling in the meso-scale Rhin catchment in the German federal state Brandenburg was done (1) to answer some specific questions concerning identification of point and diffuse sources of nutrient pollution in the catchment, (2) to assess the influences of possible climate and land use changes on water quantity and quality and (3) to evaluate potential measures to be done in order to achieve a “good ecological status” of the river and its lakes as required by the Water Framework Directive (WFD).The Rhin catchment is a typical highly regulated lowland river basin in Northern Germany. The regulations complicate water quantity and quality modelling in the catchment. The research was done by using the eco-hydrological model SWIM (Soil and Water Integrated Model), which simulates water and nutrient fluxes in soil and vegetation, as well as transport of water and nutrients to and within the river network. The modelling period was from 1981 until 2005. After calibrating the hydrological processes at different gauges within the basin with satisfactory results, water quality (nitrogen and phosphorus) modelling was done taking into account the emissions of different point sources (sewage treatment plants, etc.) and identifying the amount of diffuse pollution caused mainly by agriculture.For suggesting some feasible measures to improve water quality and to reduce diffuse pollution considering possible climate and land use changes, different reasonable scenarios were applied in consultation with the Environmental Agency of Brandenburg (LUA). The study revealed that the amount of water discharge has significant influence on the concentration of nutrients in the river network, and that nitrogen pollution, caused mainly by diffuse sources, could be notably reduced by application of agricultural measures, whereas the pollution by phosphorus could be diminished most effectively by the reduction of point source emissions.     

Application of a water quality model in the White Cart water catchment,Glasgow, UK

Water quality models of urban systems have previously focused on point source (sewerage system) inputs. Little attention has been given to diffuse inputs and research into diffuse pollution has been largely confined to agriculture sources. This paper reports on new research that is aimed at integrating diffuse inputs into an urban water quality model. An integrated model is introduced that is made up of four modules: hydrology, contaminant point sources, nutrient cycling and leaching. The hydrology module, T & T consists of a TOPMODEL (a TOPography-based hydrological MODEL), which simulates runoff from pervious areas and a two-tank model, which simulates runoff from impervious urban areas. Linked into the two-tank model, the contaminant point source module simulates the overflow from the sewerage system in heavy rain. The widely known SOILN (SOIL Nitrate model) is the basis of nitrogen cycle module. Finally, the leaching module consists of two functions: the production function and the transfer function. The production function is based on SLIM (Solute Leaching Intermediate Model) while the transfer function is based on the flushing hypothesis which postulates a relationship between contaminant concentrations in the receiving water course and the extent to which the catchment is saturated. This paper outlines the modelling methodology and the model structures that have been developed. An application of this model in the White Cart catchment (Glasgow) is also included.     

Pollution control and inputs to production

The primary concern of this paper is to identify the inputs required for air, water, and solid waste pollution abatement in the United States. Industry level data on pollution abatement expenditures in 1976 are decomposed into expenditures on various intermediate inputs and on two primary inputs—labor and capital. The 1971 input-output table is adjusted to reflect the input needs of pollution abatement technology. This revised direct input coefficients matrix is used to derive the gross output and primary input requirements of the 1971 final bill of goods.     

Effect of streambed bacteria release on E. coli concentrations: Monitoring and modeling with the modified SWAT

Streambed sediment has been attracting attention as a reservoir for bacteria, including pathogenic strains. Soil and Water Assessment Tool (SWAT) has been augmented with a bacteria transport subroutine in SWAT2005 in which bacteria die-off is the only in-stream process. The purpose of this study was to develop the partial model of sediment-associated bacteria transport in stream and to evaluate the potential significance of streambed Escherichia coli (E. coli) release and deposition within the SWAT microbial water quality simulations. Streambed E. coli release and deposition were simulated based on the sediment resuspension and deposition modules in SWAT. The modified SWAT was applied to the Little Cove Creek watershed, Pennsylvania, which has forestry and dairy pasture landuses. Temporal changes in sediment E. coli concentrations were derived from monitoring data rather than from a streambed bacteria population model. Sensitivity analyses and calibrations were separately conducted for both hydrologic and bacteria parameters. Hydrologic calibration characterized soils in the watershed as pervious and thus the surface runoff was only moderately contributing to the streamflow. However, the surface runoff carried large numbers of E. coli to the stream, and sediment resuspension contributed to the persistent concentration of E. coli in stream water. Although the uncertainty of E. coli concentrations in streambed sediments and from wildlife probably affected the performance of the modified SWAT model, this study qualitatively confirmed the significance of modeling E. coli release from streambed and deposition for the SWAT microbial water quality simulations. Further developments should include modeling dynamics of bacteria populations within streambeds.     

Trade''s Dynamic Solutions to Transboundary Pollution

This study develops a differential game to examine the effects of trade liberalization on transboundary water pollution. Water pollution is due to wastewater emissions from countries in a shared waterway along the U.S.–Mexico border with available data of pollution abatement costs, public health damages, and trade benefits. Noncooperative and cooperative games are examined with changes in trade policy and public health damages. Results show trade liberalization leads Mexico to curtail pollution in both games. Cooperation and trade liberalization limit emissions from both countries and curtail strategic behavior of the United States from Mexico's pollution control efforts in the noncooperative game.     

Efficient waste and pollution abatements for regions in Japan

This paper computes efficient industrial waste and air pollutants abatements for 47 regions in Japan for the period 1992–2002. The variable-returns-to-scale (VRS) data envelopment analysis (DEA) with a single output (real GDP) and seven inputs (labor, real public capital stock, real private capital stock, industrial waste, sulfur oxide, nitrogen oxide, and soot and dust) is used to compute target wastes of each region for each year. The efficient abatement ratios of each region in each year are obtained by comparing the actual to the target amount of a pollutant. Our major findings are: (1) Most regions in Japan have significant room to reduce their pollution since there is a wide gap between efficient and inefficient regions; (2) For each air pollutant, approximately 25–33% of Japan's prefectures can reduce their output by more than 50% without harming regional GDP, and approximately one-third of prefectures can reduce industrial waste more than 30%; (3) Hokkaido is the least efficient region for all years studied and for all waste and pollutants, and target abatement ratios there drastically worsened in the last two sample years; (4) Tokyo, Saitama, Yamanashi, Shiga, Nara, and Tottori are efficient with respect to each type of industrial waste and pollution throughout the study period; (5) many regions in the bottom quartile with respect to real per capita income have significant room to reduce their waste and pollution output; and (6) many regions where energy-intensive industries dominate produce excessive amounts of waste and air pollution compared to other regions.     

Efficient air pollution abatement for regions in China

This paper computes the efficient air pollution abatement ratios of 30 regions in China during the period 1996–2002. Three air emissions (SO₂, soot and dust) are considered. Data envelopment analysis (DEA) with a single output (real GDP) and five inputs (labour, real capital stock, SO₂, dust and soot emissions) is used to compute the target emissions of each region for each year. The efficient abatement ratios of each region in each year are then obtained by dividing the target emission by the actual emission of an air pollutant. Our major findings are: 1. The eastern area is the most efficient region with respect to SO₂, soot and dust emissions in every year during the research period. 2. The eastern, central and western areas have the lowest, medium and highest 1996–2002 average target abatement ratios of SO₂ (22.09%, 42.23% and 57.58%), soot (26.19%, 56.34% and 66.37%) and dust (15.20%, 29.09% and 40.59%), respectively. 3. These results are consistent with the Environmental Kuznets Curve (EKC) theory, whereby a more developed area will use environmental goods more efficiently than a less developed area. 4. Compared to dust emission, the average target abatement ratios for SO₂ and soot emissions (as direct outcomes of burning coal) are relatively much higher for all three areas.     

Robust technology policy against emission leakage: The case of upstream subsidies

Asymmetric regulation of a global pollutant between countries can alter the competitiveness of industries and lead to emissions leakage, which hampers countries’ welfare. In order to limit leakage, governments consider supporting domestic trade-exposed firms by subsidizing their investments in abatement technology. The suppliers of such technologies tend to be less than perfectly competitive, particularly when both emissions regulations and advanced technologies are new. In this context of twin market failures, we consider the relative effects and desirability of subsidies for abatement technology. We find a more robust recommendation for upstream subsidies than for downstream subsidies. Downstream subsidies tend to increase global abatement technology prices, reduce pollution abatement abroad and increase emission leakage. On the contrary, upstream subsidies reduce abatement technology prices, and hence also emissions leakage.     

The optimal pricing of pollution when enforcement is costly

We consider the pricing of a uniformly mixed pollutant with a model of optimal, possibly firm-specific, emissions taxes and their enforcement under incomplete information about firms’ abatement costs, enforcement costs, and pollution damage. We argue that optimality requires an enforcement strategy that induces full compliance by every firm, except possibly when a regulator can base the probabilities of detecting individual violations on observable correlates of violators’ actual emissions. Moreover, optimality requires discriminatory taxes, except when a regulator is unable to use observable firm-level characteristics to gain some information about the variation in firms’ abatement costs or monitoring costs.     

Sensitivity of the SWAT model to the soil and land use data parametrisation: a case study in the Thyle catchment,Belgium

The sensitivity of the distributed hydrological SWAT model to the pre-processing of soil and land use data was tested for modelling rainfall-runoff processes in the Thyle catchment in Belgium. To analyse this sensitivity, 32 different soil and land use parameterisation scheme were generated and evaluated. The soil input data sources were a generalised soil association map at a scale of 1:500,000, a detailed soil map at a scale of 1:25,000 and the soil profile analytical database AARDEWERK. These soil data were combined with a detailed and a generalised land use map. The results suggest that the SWAT model is extremely sensitive to the quality of the soil and land use data and the adopted pre-processing procedures of the geographically distributed data. The resolution and fragmentation of the original map objects are significantly affected by the internal aggregation procedures of the SWAT model. The catchment size threshold value (CSTV) is thereby a key parameter controlling the internal aggregation procedure in the model. It is shown that a parabolic function characterises the relationship between the CSTV and the hydrological modelling performance of the uncalibrated model, suggesting that optimal uncalibrated modelling results are not obtained when the CSTV is minimised. The hydrological response of the SWAT model to the calculated soil properties is significant. Therefore preference should be given to the calculation of the derived hydrologic soil properties prior to averaging of the profile data. Finally some general guidelines are suggested for parameterising soil and land use in the SWAT model application.     

SWAT模型在国内外非点源污染研究中的应用进展

模型模拟是定量估算非点源污染负荷的有效工具,也是对其进行规划、控制和管理的前提.近年来SWAT模型在国内外得到了快速的发展和应用,是目前全球评价大范围和环境变化条件下非点源污染问题的一个有效工具.简介SWAT模型的发展历程及原理,概述了SWAT模型目前在国内外的水文评价、污染物流失模拟、输人参数、土地利用及气候变化对水文响应的影响等方面的研究现状,并对SWAT模型的发展方向提出了建议,为模型的进一步完善与应用提供参考.结果显示,SWAT模型对水文评价(如径流量、泥沙量)可得到较好的模拟和预测结果,能够模拟污染物(如农药和化肥)在农田和河网中的迁移过程,模拟与分析土地利用/覆被变化及气候变化对水文过程的影响.模型参数的确定及其对地下水流与溶质运移的模拟是模型的主要问题,需要进一步研究与完善.     

Space-time modeling of environmental monitoring data

This study describes and applies statistical methods for space-time modeling of data from environmental monitoring programs, e.g., within areas such as climate change, air pollution and aquatic environment. Such data are often characterized by sparse sampling in both the temporal and spatial dimensions. In order to improve the amount of information on the physical system in question we suggest using statistical modeling methods for monitoring data. Model predictions combined with observations could be analyzed directly to assess the environmental state or as forcing functions for time series models and deterministic, hydrodynamic models. To illustrate the approach we applied the proposed modeling methods to data from the Danish and Swedish marine monitoring programs. Time series with a weekly resolution were predicted from observations of dissolved inorganic nitrogen (DIN) from the Kattegat basin (1993–1997). DIN observations were sparse, irregularly distributed and comprised approximately 10% of the generated time series.     

Implications of Intratropical Migration on Reserve Design: A Case Study Using Pharomachrus mocinno

As habitat loss continues, natural protected areas will become islands in human-modified landscapes; maintenance of functional communities and ecosystems will depend on properly designed protected areas. We demonstrate that incorporating regional habitat linkages that allow for seasonal migrations of intratropical resident species must be a major design criterion for establishing protected areas. Using radiotelemetry, we monitored the seasonal movements of one such migrant, the Resplendent Quetzal ( Pharomachrus mocinno ), a large, frugivorous bird, one of many tropical residents known to migrate altitudinally within Mesoamerica. Based on three years of data we determined that quetzals followed a complicated local migration that linked four montane life zones. Using this species as an indicator revealed that the configuration of the Monteverde reserve complex in the Tilaran Mountains in west-central Costa Rica lacked sufficient habitat distribution to conserve montane biodiversity. On the basis of these results, we propose that the three-step process proposed by Soulé and Simberloff (1986) for estimating minimum sizes of reserves be amended to include a fourth step: The critical habitats used throughout the annual cycles of target or keystone species must be identified and adequately protected. Natural protected areas can be considered adequately designed only when sufficient area with a full complement of ecologically linked habitats is included.     

Cars on crutches: How much abatement do smog check repairs actually provide?

Not as much abatement as has been presumed. Smog check programs aim to curb tailpipe emissions from in-use vehicles by requiring repairs whenever emissions, measured at regular time intervals, exceed a certain threshold. Using data from California, we estimate that on average 41% of the initial emissions abatement from repairs is lost by the time of the subsequent inspection, normally two years later. Our estimates imply that the cost per pound of pollution avoided is an order of magnitude greater for smog check repairs than alternative policies such as new-vehicle standards or emissions trading among industrial point sources.     

‘Optimal’ pollution abatement—whose benefits matter, and how much?

We examine the determinants of environmental regulatory activity (inspections and enforcement actions) and levels of air and water pollution for 409 US pulp and paper mills, using data for 1985–1997. We focus on the benefits to the surrounding population from pollution abatement. Plants with larger benefits emit less pollution, as do those with more kids and elders nearby. Plants in poor areas emit more pollution, though (surprisingly) we find less pollution in minority areas. Out-of-state neighbors seem to count less than in-state ones, although this effect diminishes if the bordering state's Congressional delegation is strongly pro-environment. We use ‘spatially lagged’ instrumental variables to control for the potential endogeneity of which individuals choose to locate near the plant. The results for regulatory activity are noticeably less significant than the emissions results.     

Environmental data management: The identification of outliers

Increased emphasis on pollution control and abatement has often necessitated development of large scale data bases. While sophisticated techniques have been developed and employed for data storage and manipulation, parallel developments in analyzing the accuracy and reliability of the data have been absent (see, for instance, the broad spectrum of requirements outlined in the Federal Water Pollution Control Act Amendments of 1972).This paper centers on the latter and sets out a procedure for data editing and “outlier” identification based on an application of discriminant analysis. A hypothetical example is included along with some suggested applications.     

Economical pollution control in warm climates by contact stabilization wastewater treatment

Water pollution abatement with economical solutions, for wastewater treatment plants design and operation, is a crucial problem, especially for economically developing countries. The purpose of this study is the evaluation of the contact stabilization process to achieve economical secondary treatment as well as partial nitrification under favorable temperature conditions. The examined variables are easily definable parameters of practical importance for any wastewater treatment plant. Based on full scale plants data, correlations between design or operation variables and plant performance or effluent quality are reported.     

Fully integrated approach: an alternative solution of coupling a GIS and diffuse pollution models

As a tool for management, query, visualization and analysis of spatially referred information, GIS has been recognized as a method to aid the modeling of diffuse pollution and visualize the results in a spatial context. A common question in integrating diffuse pollution models and GIS is to choose a suitable coupling approach, in which the feature of diffuse pollution models should be taken into account. In this paper, we report on our experience in coupling a distributed diffuse pollution model with a GIS. A prototype of fully integrated system is developed in this paper. This system has high flexibility, extendibility and great data management efficiency. Differences in applicability of loose coupling, tight coupling and fully integrated approaches are addressed. It is concluded that the fully integrated approach can avoid tanglesome data exchange and routine execution and more robust than loose and tight coupling approaches and is suitable for distributed diffuse pollution modes.     

Identification of pollution sources in rivers using a hydrodynamic diffusion wave model and improved Bayesian-Markov chain Monte Carlo algorithm

● A hydrodynamic-Bayesian inference model was developed for water pollution tracking. ● Model is not stuck in local optimal solutions for high-dimensional problem. ● Model can estimate source parameters accurately with known river water levels. ● Both sudden spill incident and normal sewage inputs into the river can be tracked. ● Model is superior to the traditional approaches based on the test cases. Water quality restoration in rivers requires identification of the locations and discharges of pollution sources, and a reliable mathematical model to accomplish this identification is essential. In this paper, an innovative framework is presented to inversely estimate pollution sources for both accident preparedness and normal management of the allowable pollutant discharge. The proposed model integrates the concepts of the hydrodynamic diffusion wave equation and an improved Bayesian-Markov chain Monte Carlo method (MCMC). The methodological framework is tested using a designed case of a sudden wastewater spill incident (i.e., source location, flow rate, and starting and ending times of the discharge) and a real case of multiple sewage inputs into a river (i.e., locations and daily flows of sewage sources). The proposed modeling based on the improved Bayesian-MCMC method can effectively solve high-dimensional search and optimization problems according to known river water levels at pre-set monitoring sites. It can adequately provide accurate source estimation parameters using only one simulation through exploration of the full parameter space. In comparison, the inverse models based on the popular random walk Metropolis (RWM) algorithm and microbial genetic algorithm (MGA) do not produce reliable estimates for the two scenarios even after multiple simulation runs, and they fall into locally optimal solutions. Since much more water level data are available than water quality data, the proposed approach also provides a cost-effective solution for identifying pollution sources in rivers with the support of high-frequency water level data, especially for rivers receiving significant sewage discharges.