Heavy metal pollution in sediments of the largest reservoir (Three Gorges Reservoir) in China: a review

The Three Gorges Dam in China is the world’s largest dam. Upon its completion in 2003, the Three Gorges Reservoir (TGR) became the largest reservoir in China and plays an important role in economic development and national drinking water safety. However, as a sink and source of heavy metals, there is a lack of continuous and comparative data on heavy metal pollution in sediments. This study reviewed all available literatures published on heavy metals in TGR sediments and further provided a comprehensive assessment of the pollution tendency of these heavy metals. The results showed that heavy metal concentrations in TGR sediments varied spatially and temporally. Temporal variations indicated that Hg in tributaries, as well as As, Cd, Cr, Cu, Ni, Pb, and Zn in the mainstream, exhibited a higher probability to exceed background values after the impoundment of TGR. Pollution assessments by contamination factor, geoaccumulation index, and potential ecological risk were similar. High Cd and Hg concentrations in both the mainstream and tributaries are a cause for much concern. However, sediment quality guidelines produced different results, as most previous studies adopted different sampling and measurement strategies. The data inconsistencies and lack of continuity regarding the reservoir confirm the need for a continuous monitoring network and the development of quality criteria relevant to the sediments of the TGR in the future.     

Development of the hybrid cells in series model to simulate ammonia nutrient pollutant transport along the Umgeni River

Discharge of organic waste results in high nutrient pollution of the water bodies which is a major menace to the environment. A high quantity of nutrients such as ammonia causes a reduction in the dissolved oxygen level and induces algal growth in the water bodies. Water quality models have been the tools to evaluate the rate at which streams can disperse the pollutants they receive. Many water quality models are flawed either because of their inadequacy to completely simulate the advection component of the pollutant transport, or because of the limited application of the models, due to inaccurate estimation of model parameters. The hybrid cell in series (HCIS) developed by Ghosh et al. (2004) has been able to overcome such difficulties associated with the mixing cell-based models. Thus, the current study focuses on developing an analytical solution for the pollutant transport of the ammonia concentration through the plug flow, the first and second well-mixed cells of the HCIS model. The HCIS model coupled with the first order kinetic equation for ammonia nutrient was developed to simulate the ammonia pollutant concentration in the water column. The ammonia concentration at various points along the river system was assessed by considering the effects of the transformation of ammonia to nitrite, the uptake of ammonia by the algae, the respiration rate of the algae and the input of benthic source to the ammonia concentration in the water column. The proposed model was tested using synthetic data, and the HCIS-NH₃ model simulations for spatial and temporal variation of ammonia pollutant transport were analysed. The simulated results of the HCIS-NH₃ model agreed with the Fickian-based advection-dispersion equation (ADE) for simulating ammonia concentration solved using an explicit finite difference scheme. The HCIS-NH₃ model also showed a good agreement with the observed data from the Umgeni River, except during rainy periods.     

Effect of ferrate on green algae removal

Green algae Cladophora aegagropila, present in cooling water of thermal power plants, causes many problems and complications, especially during summer. However, algae and its metabolites are rarely eliminated by common removal methods. In this work, the elimination efficiency of electrochemically prepared potassium ferrate(VI) on algae from cooling water was investigated. The influence of experimental parameters, such as Fe(VI) dosage, application time, pH of the system, temperature and hydrodynamics of the solution on removal efficiency, was optimized. This study demonstrates that algae C. aegagropila can be effectively removed from cooling water by ferrate. Application of ferrate(VI) at the optimized dosage and under the suitable conditions (temperature, pH) leads to 100% removal of green algae Cladophora from the system. Environmentally friendly reduction products (Fe(III)) and coagulation properties favour the application of ferrate for the treatment of water contaminated with studied microorganisms compared to other methods such as chlorination and use of permanganate, where harmful products are produced.

     

Value chain for next-generation biofuels: resilience and sustainability of the product life cycle

Multiple factors including climate change, price uncertainties, and geopolitical instability have prompted many industries to investigate the feasibility of replacing traditional petroleum-based fuels with biofuel alternatives. However, to make this transition successful, these new biofuels must be environmentally sustainable and the necessary support infrastructure must be in place to make the production, distribution, and storage of these biofuels technologically feasible and cost effective. Developing a value chain, spanning from feedstock production to distribution to end users, requires garnering buy-in from multiple stakeholders by demonstrating environmental, economic, and social benefits and incentives. Two critical factors are the environmental benefits achieved from the use of the biofuel technology and the degree of resilience of the value chain to emergent conditions to ensure steady supply to consumers. Moreover, different biofuel pathways have different costs, benefits, and risks which must be compared. In this paper, we describe how environmental sustainability can be modeled using life cycle assessment (LCA) and how the resilience of value chain initiatives can be modeled using a scenario-based decision model. We then describe how sustainability and resilience assessments can be integrated in an iterative, anticipatory LCA framework. These assessments can be used as the basis for a business case for various investments, as well as a means for promoting responsible innovations, with the aviation industry used as a case study.     

Technology and science: innovation at the International Symposium on Sustainable Systems and Technology

While science advances technology, it is also true that technology advances science. Thus, the two bodies of knowledge are increasingly recognized as interdependent. Nonetheless, recent advances in information communication technology (ICT), in particular, may have profound implications for the norms by which science is conducted. For example, treatment of data will increasingly be in terms of probability distributions, rather than as point estimates, because the cost of computation is now so low that more robust approaches to treatment of uncertainty are within the grasp of normal science. Perhaps more importantly, the techniques by which scientists collaborate, communicate, and curate science are undergoing a rare period of rapid change. The papers in this special section exemplify the evolution of the relationship between technology and science in these two important ways: (1) treatment of data uncertainties and (2) participation in novel methods of publication and review. The latter was fostered by the 2016 meeting of the International Symposium on Sustainable Systems and Technologies (ISSST), at which all of the papers in this special section were presented. This editorial summarizes some of the trends in ICT that are the subject of experimentation in ISSST and introduces the idea that scientific societies in the information age are more likely to take the form of a network than they are likely to look like the societies of the last several centuries.     

Simulated climate adaptation in stormwater systems: evaluating the efficiency of adaptation strategies

Adaptations in infrastructure may be necessitated by changes in temperature and precipitation patterns to avoid losses and maintain expected levels of service. A roster of adaptation strategies has emerged in the climate change literature, especially with regard to timing: anticipatory, concurrent, or reactive. Significant progress has been made in studying climate change adaptation decision making that incorporates uncertainty, but less work has examined how strategies interact with existing infrastructure characteristics to influence adaptability. We use a virtual testbed of highway drainage crossings configured with a selection of actual culvert emplacements in Colorado, USA, to examine the effect of adaptation strategy and culvert characteristics on cost efficiency and service level under varying rates of climate change. A meta-model approach with multinomial regression is used to compare the value of better climate change predictions with better knowledge of existing crossing characteristics. We find that, for a distributed system of infrastructural units like culverts, knowing more about existing characteristics can improve the efficacy of adaptation strategies more than better projections of climate change. Transportation departments choosing climate adaptation strategies often lack detailed data on culverts, and gathering that data could improve the efficiency of adaptation despite climate uncertainty.     

The development of a method to determine the burden of climate change on different health outcomes at a local scale: a case study in Osaka Prefecture,Japan

Climate change impacts human health in a variety of ways. Variables including the climate-related risk factor, the health outcome and location all determine the nature and extent of the impact. The existence of different pathways and endpoints presents a problem for quantifying and comparing impacts. Disability-adjusted life year (DALY) provides a common scale, whereby the impact of climate change on both acute and chronic health outcomes can be compared. This study presents a methodology to calculate the impact of climate change on human health at a local scale, using cardiovascular disease (CVD) and meteorological disaster-related injuries (DRIs) in Osaka Prefecture, Japan, as applied case studies. An additional very fine scale assessment of CVD conducted at the neighbourhood level to demonstrate the importance of conducting risk assessments at a local level. The comparative results calculated the impact of climate change in 2050 to be 16.866 DALY/100,000 population for CVD and 0.645 DALY/100,000 for meteorological DRIs. The actual impact of climate change by 2050 on CVD is judged to be higher, although the relative risk was projected to be lower (1.006, compared to 1.263 for meteorological DRIs). The fine scale assessment revealed the variations in the projected impact of climate change on CVD for all administrative zones in Osaka Prefecture. The range of impacts varied from 0 to 114.29 DALY/100,000. The results demonstrate the applicability of using DALY to quantify the impact of climate change on different health outcomes, using a transferable methodology, and provide information that enables evidence-based prioritisation of climate change adaptation strategies at a local scale.     

Optimizing angles of rooftop photovoltaics,ratios of solar to vegetated roof systems,and economic benefits,in Portland,Oregon, USA

This study analyzed insolation data to account for multiple scattering in calculating optimal tilt angles for stationary and seasonally moving photovoltaics on three different roof types in the US Pacific Northwest: vegetated roofs, white roofs, and dark roofs. Using these results, we modeled the energy savings for vegetated roofs and roofs covered in varying numbers of photovoltaic panels. We then calculated the net present value, internal rate of return, and other economic measures for all possible combinations of covering rooftops in mixes of photovoltaic arrays and vegetation, accounting for installation costs, proposed carbon taxes, stormwater management discounts, and other relevant factors. Our results quantify how, in the US Pacific Northwest and similar locations, photovoltaics produce higher returns on investment than do vegetated roofs for new buildings, while vegetated roofs produce better returns on investment than do photovoltaics for older buildings. This is important because in many areas, some buildings have photovoltaics when a vegetated roof would have been more cost and energy efficient, while other buildings have vegetated roofs when photovoltaics would have been more cost and energy efficient. Potential applications include modifying incentive programs and other policies to account properly for building age, use, and other relevant factors to ensure building owners make the most energy-efficient decisions between photovoltaic versus vegetated roof installation. Our research also demonstrates how positive returns on investment can be realized in the US Pacific Northwest and similar regions through vegetated roofs and photovoltaics provided they are each installed optimally.     

Trends and applications of multi-criteria decision analysis in environmental sciences: literature review

Approximately 3000 papers concerning multi-criteria decision analysis (MCDA) in the environmental field were identified through a series of queries in the Web of Science database and classified by MCDA method and environmental application using text mining in R. Stemming and stop word removal techniques were used to remove irrelevant text from the literature. Trends in MCDA methods (AHP/ANP, TOPSIS, outranking, MAUT/MAVT) associated with specific environmental applications (water, air, energy, natural resources, and waste management) or interventions/tools applications (stakeholders, strategies, sustainability, and GIS) were identified. The results show a linear growth in the share of MCDA papers in environmental science across all application areas. Furthermore, the results show that AHP/ANP and MAUT/MAVT are the most frequently mentioned MCDA methods in the literature. For environmental applications, the results showed that natural resource and waste management keywords were, respectively, the most and least commonly discussed applications within the MCDA papers. For intervention/tool applications, we found that keywords associated with ‘strategy’ and ‘GIS’ applications are, respectively, the most and least commonly discussed keywords within the MCDA papers. The authors found that MCDA method keywords were evenly distributed across the environmental and intervention/tool applications, indicating a lack of preference in the environmental field for use of specific MCDA methods. This paper demonstrates that text mining is an applicable tool to assess specific textual trends and patterns when analyzing larger bodies of MCDA literature.     

Characterization of summertime coarse particulate matter in the Desert Southwest—Arizona,USA

A year-long study was conducted in Pinal County, AZ, to characterize coarse (2.5 – 10 μm aerodynamic diameter, AD) and fine (< 2.5 μm AD) particulate matter (PMc and PMf, respectively) to further understand spatial and temporal variations in ambient PM concentrations and composition in rural, arid environments. Measurements of PMc and PMf mass, ions, elements, and carbon concentrations at one-in-six day resolution were obtained at three sites within the region. Results from the summer of 2009 and specifically the local monsoon period are presented.

The summer monsoon season (July – September) and associated rain and/or high wind events, has historically had the largest number of PM₁₀ NAAQS exceedances within a year. Rain events served to clean the atmosphere, decreasing PMc concentrations resulting in a more uniform spatial gradient among the sites. The monsoon period also is characterized by high wind events, increasing PMc mass concentrations, possibly due to increased local wind-driven soil erosion or transport. Two PM₁₀ NAAQS exceedances at the urban monitoring site were explained by high wind events and can likely be excluded from PM₁₀ compliance calculations as exceptional events. At the more rural Cowtown site, PM₁₀ NAAQS exceedances were more frequent, likely due to the impact from local dust sources.

PM mass concentrations at the Cowtown site were typically higher than at the Pinal County Housing and Casa Grande sites. Crustal material was equal to 52-63% of the PMc mass concentration on average. High concentrations of phosphate and organic carbon found at the rural Cowtown were associated with local cattle feeding operations. A relatively high correlation between PMc and PMf (R²?=?0.63) indicated that the lower tail of the coarse particle fraction often impacts the fine particle fraction, increasing the PMf concentrations. Therefore, reductions in PMc sources will likely also reduce PMf concentrations, which also are near the value of the 24-hr PM_2.5 NAAQS.

Implications: In the desert southwest, summer monsoons are often associated with above average PM₁₀ (<10 μm AD) mass concentrations. Competing influences of monsoon rain and wind events showed that rain suppresses ambient concentrations while high wind increase them. In this region, the PMc fraction dominates PM₁₀ and crustal sources contribute 52-63% to local PMc mass concentrations on average. Cattle feedlot emissions are also an important source and a unique chemical signature was identified for this source. Observations suggest monsoon wind events alone cannot explain PM₁₀ NAAQS exceedances, thus requiring these values to remain in compliance calculations rather than being removed as exceptional wind events.