A robust simulation–optimization modeling system for effluent trading—a case study of nonpoint source pollution control

In this study, a robust simulation–optimization modeling system (RSOMS) is developed for supporting agricultural nonpoint source (NPS) effluent trading planning. The RSOMS can enhance effluent trading through incorporation of a distributed simulation model and an optimization model within its framework. The modeling system not only can handle uncertainties expressed as probability density functions and interval values but also deal with the variability of the second-stage costs that are above the expected level as well as capture the notion of risk under high-variability situations. A case study is conducted for mitigating agricultural NPS pollution with an effluent trading program in Xiangxi watershed. Compared with non-trading policy, trading scheme can successfully mitigate agricultural NPS pollution with an increased system benefit. Through trading scheme, [213.7, 288.8]?×?10³ kg of TN and [11.8, 30.2]?×?10³ kg of TP emissions from cropped area can be cut down during the planning horizon. The results can help identify desired effluent trading schemes for water quality management with the tradeoff between the system benefit and reliability being balanced and risk aversion being considered.     

Mass loads of dissolved and particulate mercury and other trace elements in the Mt. Amiata mining district,Southern Tuscany (Italy)

Total dissolved and particulate mercury (Hg), arsenic (As), and antimony (Sb) mass loads were estimated in different seasons (March and September 2011 and March 2012) in the Paglia River basin (PRB) (central Italy). The Paglia River drains the Mt. Amiata Hg district, one of the largest Hg-rich regions worldwide. Quantification of Hg, As, and Sb mass loads in this watershed allowed (1) identification of the contamination sources, (2) evaluation of the effects of Hg on the environment, and (3) determination of processes affecting Hg transport. The dominant source of Hg in the Paglia River is runoff from Hg mines in the Mt. Amiata region. The maximum Hg mass load was found to be related to runoff from the inactive Abbadia San Salvatore Mine (ASSM), and up to 30 g day^?1 of Hg, dominantly in the particulate form, was transported both in high and low flow conditions in 2011. In addition, enrichment factors (EFs) calculated for suspended particulate matter (SPM) were similar in different seasons indicating that water discharge controls the quantities of Hg transported in the PRB, and considerable Hg was transported in all seasons studied. Overall, as much as 11 kg of Hg are discharged annually in the PRB and this Hg is transported downstream to the Tiber River, and eventually to the Mediterranean Sea. Similar to Hg, maximum mass loads for As and Sb were found in March 2011, when as much as 190 g day^?1 each of As and Sb were measured from sites downstream from the ASSM. Therefore, the Paglia River represents a significant source of Hg, Sb, and As to the Mediterranean Sea.     

Comparative statistical study of hourly precipitation determined by radar-based Stage IV and ground-based methods in the North Central United States

Detailed hourly precipitation data are required for long-range modeling of dispersion and wet deposition of particulate matter and water-soluble pollutants using the CALPUFF model. In sparsely populated areas such as the north central United States, ground-based precipitation measurement stations may be too widely spaced to offer a complete and accurate spatial representation of hourly precipitation within a modeling domain. The availability of remotely sensed precipitation data by satellite and the National Weather Service array of next-generation radars (NEXRAD) deployed nationally provide an opportunity to improve on the paucity of data for these areas. Before adopting a new method of precipitation estimation in a modeling protocol, it should be compared with the ground-based precipitation measurements, which are currently relied upon for modeling purposes. This paper presents a statistical comparison between hourly precipitation measurements for the years 2006 through 2008 at 25 ground-based stations in the north central United States and radar-based precipitation measurements available from the National Center for Environmental Predictions (NCEP) as Stage IV data at the nearest grid cell to each selected precipitation station. It was found that the statistical agreement between the two methods depends strongly on whether the ground-based hourly precipitation is measured to within 0.1 in/hr or to within 0.01 in/hr. The results of the statistical comparison indicate that it would be more accurate to use gridded Stage IV precipitation data in a gridded dispersion model for a long-range simulation, than to rely on precipitation data interpolated between widely scattered rain gauges.

Implications:

The current reliance on ground-based rain gauges for precipitation events and hourly data for modeling of dispersion and wet deposition of particulate matter and water-soluble pollutants results in potentially large discontinuity in data coverage and the need to extrapolate data between monitoring stations. The use of radar-based precipitation data, which is available for the entire continental United States and nearby areas, would resolve these data gaps and provide a complete and accurate spatial representation of hourly precipitation within a large modeling domain.     

Optimization-Based Atmospheric Plume Source Identification

This work applies optimization and an Eulerian inversion approach presented by Bagtzoglou and Baun in 2005 in order to reconstruct contaminant plume time histories and to identify the likely source of atmospheric contamination using data from a real test site for the first time. Present-day distribution of an atmospheric contaminant plume as well as data points reflecting the plume history allow the reconstruction and provide the plume velocity, distribution, and probable source. The method was tested to a hypothetical case and with data from the Forest Atmosphere Transfer and Storage (FACTS) experiment in the Duke experimental forest site. In the scenarios presented herein, as well as in numerous cases tested for verification purposes, the model conserved mass, successfully located the peak of the plume, and managed to capture the motion of the plume well but underestimated the contaminant peak.     

Evaluating the capabilities of Aerosol-to-Liquid Particle Extraction System (ALPXS)/ICP-MS for monitoring trace metals in indoor air

This study investigates the application of the Aerosol-to-Liquid Particle Extraction System (ALPXS), which uses wet electrostatic precipitation to collect airborne particles, for multi-element indoor stationary monitoring. Optimum conditions are determined for capturing airborne particles for metal determination by inductively coupled plasma–mass spectrometry (ICP-MS), for measuring field blanks, and for calculating limits of detection (LOD) and quantification (LOQ). Due to the relatively high flow rate (300 L min^?1), a sampling duration of 1 hr to 2 hr was adequate to capture airborne particle-bound metals under the investigated experimental conditions. The performance of the ALPXS during a building renovation demonstrated signal-to-noise ratios appropriate for sampling airborne particles in environments with elevated metal concentrations, such as workplace settings. The ALPXS shows promise as a research tool for providing useful information on short-term variations (transient signals) and for trapping particles into aqueous solutions where needed for subsequent characterization. As the ALPXS does not provide size-specific samples, and its efficiency at different flow rates has yet to be quantified, the ALPXS would not replace standard filter-based protocols accepted for regulatory applications (e.g., exposure measurements), but rather would provide additional information if used in conjunction with filter based methods.

ImplicationsThis study investigates the capability of the Aerosol-to-Liquid Particle Extraction System (ALPXS) for stationary sampling of airborne metals in indoor workplace environments, with subsequent analysis by ICP-MS. The high flow rate (300 L/min) permits a short sampling duration (< 2 hr). Results indicated that the ALPXS was capable of monitoring short-term changes in metal emissions during a renovation activity. This portable instrument may prove to be advantageous in occupational settings as a qualitative indicator of elevated concentrations of airborne metals at short time scales.     

Once there was a river: a benefit–cost analysis of rehabilitation of the Jordan River

The Jordan River is among the world’s most famous and culturally and historically significant waterways. The lower stretch of the river, however, has been a victim of development in a water scarce region, with current flows less than 5 % of historical levels. Furthermore, as it functions as an international border in a region of conflict, access to the river and its potential as a tourist attraction has been limited. Recently, there have been numerous calls for rehabilitation of the river. This study presents a first estimate of the economic benefits of such rehabilitation and compares them to the estimated costs. Identical contingent valuation method surveys were administered in Israel, Jordan, and the Palestinian Authority. Evidence from this study shows that, despite the large opportunity costs of increasing environmental flows, rehabilitation of the lower Jordan would produce positive net economic benefits. This is true even though the study estimated only the benefits to local populations, and not to international tourists or those outside the region. Net benefits are maximized when taking a regional, as opposed to strictly national, approach.     

Model projected heat extremes and air pollution in the eastern Mediterranean and Middle East in the twenty-first century

The eastern Mediterranean and Middle East, a region with diverse socioeconomic and cultural identities, is exposed to strong climatic gradients between its temperate north and arid south. Model projections of the twenty-first century indicate increasing hot weather extremes and decreasing rainfall. We present model results, which suggest that across the Balkan Peninsula and Turkey climate change is particularly rapid, and especially summer temperatures are expected to increase strongly. Temperature rise can be amplified by the depletion of soil moisture, which limits evaporative cooling, prompted by the waning of large-scale weather systems that generate rain. Very hot summers that occurred only rarely in the recent past are projected to become common by the middle and the end of the century. Throughout the region, the annual number of heat wave days may increase drastically. Furthermore, conditions in the region are conducive for photochemical air pollution. Our model projections suggest strongly increasing ozone formation, a confounding health risk factor particularly in urban areas. This adds to the high concentrations of aerosol particles from natural (desert dust) and anthropogenic sources. The heat extremes may have strong impacts, especially in the Middle East where environmental stresses are plentiful.     

Adaptation options for marine industries and coastal communities using community structure and dynamics

Identifying effective adaptation strategies for coastal communities dependent on marine resources and impacted by climate change can be difficult due to the dynamic nature of marine ecosystems. The task is more difficult if current and predicted shifts in social and economic trends are considered. Information about social and economic change is often limited to qualitative data. A combination of qualitative and quantitative models provide the flexibility to allow the assessment of current and future ecological and socio-economic risks and can provide information on alternative adaptations. Here, we demonstrate how stakeholder input, qualitative models and Bayesian belief networks (BBNs) can provide semi-quantitative predictions, including uncertainty levels, for the assessment of climate and non-climate-driven change in a case study community. Issues are identified, including the need to increase the capacity of the community to cope with change. Adaptation strategies are identified that alter positive feedback cycles contributing to a continued decline in population, local employment and retail spending. For instance, the diversification of employment opportunities and the attraction of new residents of different ages would be beneficial in preventing further population decline. Some impacts of climate change can be combated through recreational bag or size limits and monitoring of popular range-shifted species that are currently unmanaged, to reduce the potential for excessive removal. Our results also demonstrate that combining BBNs and qualitative models can assist with the effective communication of information between stakeholders and researchers. Furthermore, the combination of techniques provides a dynamic, learning-based, semi-quantitative approach for the assessment of climate and socio-economic impacts and the identification of potential adaptation strategies.