Effect of technology development on potential environmental impacts from heavy metals in waste smartphones

Technology development has brought beneficial changes in the functions of smartphones but has the potential to impact the environment due to the high generation of waste smartphones. Thus, this study evaluates and compares environmental impact potentials from metals in waste smartphones to figure out the effect of smartphone model replacements on hazardous waste, resource depletion, and toxicity potentials. The total threshold limit concentration (TTLC) analysis is used to determine whether the waste smartphones would be classified as hazardous waste, and the life-cycle impact assessment methods are used to evaluate resource depletion, cancer, non-cancer, and ecotoxicity potentials. The TTLC results showed that the smartphone technology development did not reduce hazardous waste potentials. The life-cycle impact assessment results showed that the technology development overall reduced resource depletion potential but increased toxicity potential. In addition, priority metals contributing to the potentials were identified to effectively manage their environmental impacts. This study can provide fundamental information for smartphone manufacturers, waste smartphone recyclers and disposers, and e-waste policymakers to circulate resources and to prevent environmental pollutions from hazardous and toxic materials.     

International trade causes large net economic losses in tropical countries via the destruction of ecosystem services

Despite the large implications of the use of tropical land for exports (“land absorption”) on ecosystem services (ES) and global biodiversity conservation, the magnitude of these externalities is not known. We quantify the net value of ES lost in tropical countries as a result of cropland, forestland and pastureland absorption for exports after deducting ES gains through imports (“land displacement”). We find that net ES gains occur only in 7 out of the 41 countries and regions considered. We estimate global annual net losses of over 1.7 x 10¹² international dollars (I$) (I$1.1 x 10¹² if carbon-related services are not considered). After deducting the benefits from agricultural, forest and livestock rents in land replacing tropical forests, the net annual losses are I$1.3 and I$0.7 x 10¹², respectively. The results highlight the large magnitude of tropical ES losses through international trade that are not compensated by the rents of land uses in absorbed land.

Electronic supplementary material

The online version of this article (doi:10.1007/s13280-016-0768-7) contains supplementary material, which is available to authorized users.     

Prediction of groundwater contamination with multivariate regression and probabilistic capture zones

Probabilistic capture zones are combined with a regression model and used as buffer zones around wells for Tobit regression analysis to predict contaminant concentration of groundwater in an agricultural region. A backward transport equation, which is a mathematical model based on the physical processes of solute transport, is used to delineate probabilistic capture zones. The probabilistic capture zone defines the area where contaminant discharge can have a direct influence, with pertinent probability, on the quality of groundwater pumped from a well. Tobit regression analysis is used to find the relationship between independent regression variables and a dependent variable, which is contaminant concentration in this study. The capture zone and the regression are combined into a model, and its applicability for prediction of nitrate concentration is tested in a small agricultural basin in Chuncheon, Korea, which is occupied mainly by vegetation fields, orchards, and small barns. Three cases of Model 1, Model 2, and Model 3 are compared in which buffer zones are circles, capture zones with probability over 0.1, and capture zones divided into sections with different probabilities, respectively. The resulting regression model describes nitrate concentration in terms of selected independent variables. When the concentrations are calculated with the model, the best fit with the observed concentrations was in Model 3. This result supports the applicability of the method proposed in this study to prediction of contaminant concentration of groundwater.     

Environmental indicators for communication of life cycle impact assessment results and their applications

Life cycle impact assessment (LCIA) is performed to quantitatively evaluate all environmental impacts from products, systems, processes and services. However, LCIA does not always provide valuable information for choosing among alternatives with different specifications, functionalities and lifetimes. The objectives of this study are (1) to propose environmental indicators to evaluate environmental efficiency and value qualitatively and quantitatively on the basis of analogies to financial and economic indicators, and (2) to present the application of the indicators. Incremental evaluation using a reference is employed to obtain the environmental indicators. The environmental efficiency indicators are conceptually based on the ratios of reduced environmental burdens returned to environmental burdens required: environmental return on investment, environmental payback period and environmental internal rate of return. The environmental value indicator is the sum of all reduced and required environmental burdens: i.e., environmental net present value. All the environmental indicators can be used to compare and rank the environmental efficiencies or values of alternatives. The environmental efficiency indicators can be applied to a new environmental labeling. The concept of eco-efficiency labeling is developed by combining the environmental efficiency indicators with financial indicators. A case study is performed to illustrate the necessity and importance of the environmental indicators. These environmental indicators can help easily communicate LCIA results in the field of environmental management.     

Composition and yields of secondary organic aerosol formed from OH radical-initiated reactions of linear alkenes in the presence of NOx: Modeling and measurements

The products and mechanism of secondary organic aerosol (SOA) formation from the OH radical-initiated reactions of linear alkenes in the presence of NO_x were investigated in an environmental chamber. The SOA consisted primarily of products formed through reactions initiated by OH radical addition to the CC double bond, including β-hydroxynitrates and dihydroxynitrates, as well as cyclic hemiacetals, dihydrofurans, and dimers formed from particle-phase reactions of dihydroxycarbonyls. 1,4-Hydroxynitrates formed through reactions initiated by H-atom abstraction also appeared to contribute. Product yields and OH radical and alkoxy radical rate constants taken from the literature or calculated using structure–reactivity methods were used to develop a quantitative chemical mechanism for these reactions. SOA yields were then calculated using this mechanism with gas-particle partitioning theory and estimated product vapor pressures for comparison with measured values. Calculated and measured SOA yields agreed very well at high carbon numbers when semi-volatile products were primarily in the particle phase, but diverged with decreasing carbon number to a degree that depended on the model treatment of dihydroxycarbonyls, which appeared to undergo reversible reactions in the particle phase. The results indicate that the chemical mechanism developed here provides an accurate representation of the gas-phase chemistry, but the utility of the SOA model depends on the partitioning regime. The results also demonstrate some of the advantages of studying simple aerosol-forming reactions in which the majority of products can be identified and quantified, in this case leading to insights into both gas- and particle-phase chemistry.     

Evaluation of kapok (Ceiba pentandra (L.) Gaertn.) as a natural hollow hydrophobic-oleophilic fibrous sorbent for oil spill cleanup

Oil sorption capacity and hydrophobic-oleophilic characteristics of an agricultural product, kapok (Ceiba pentandra), was thoroughly examined. The kapok fiber has a hollow structure with large lumen. Its performance was compared with that of a polypropylene (PP), a widely used commercial oil sorbent for oil spill cleanup. The oils investigated were diesel, hydraulic oil (AWS46), and engine oil (HD40). Reusability of the kapok after application to various oils was also evaluated. Both loose (at its natural state) and densely packed kapok assemblies were examined. Sorption capacities of the packed kapok assemblies were very much dependent on their packing densities. At 0.02gcm(-3), its oil sorption capacities were 36, 43 and 45gg(-1) for diesel, ASW46 and HD40, respectively. The values decreased to 7.9, 8.1 and 8.6gg(-1) at 0.09gcm(-3). Its sorption capacities for the three oils were significantly higher than those of PP. When the oil-saturated kapok assemblies were allowed to drain, they exhibited high oil retention ability, with less than 8% of the absorbed diesel and HD40, and 12% of the absorbed AWS46 lost even after 1h of dripping. When applied on oil-over-water baths, the kapok exhibited high selectivity for the oils over the water; almost all oils spilled could be removed with the kapok, leaving an invisible oil slick on water. After the 4th cycle of reuse, the reused kapok assembly only lost 30% of its virgin sorption capacity if packed at 0.02gcm(-3), and the loss in sorption capacity was much less at higher packing densities. The hydrophobic-oleophilic characteristics of the kapok fiber could be attributed to its waxy surface, while its large lumen contributed to its excellent oil absorbency and retention capacity.     

Multi-residues analysis of pre-emergence herbicides in fluvial sediments: application to the mid-Garonne River

Contamination of man and ecosystems by pesticides has become a major environmental concern. Whereas many studies exist on contamination from agriculture, the effects of urban sources are usually omitted. Fluvial sediment is a complex matrix of pollutants but little is known of its recent herbicide content. This study proposes a method for a fast and reliable analysis of herbicides by employing the accelerated solvent extractor (ASE). The aim of the study is to show the impact of a major town (Toulouse) on the herbicide content in the river. In this study, three herbicide families (i.e.s-triazine, substituted ureas and anilides) were analysed in fluvial sediment fractions at 11 sampling sites along the mid-Garonne River and its tributaries. River water contamination by herbicides is minor, except for at three sites located in urban areas. Among the herbicidal families studied, urban and suburban areas are distinguished from rural areas and were found to be the most contaminated sites during the study period, a winter low-water event. The herbicide content of the coarse sediment fractions is about one third of that found in the fine fractions and usually ignored. The distribution of pesticide concentrations across the whole range of particle sizes was investigated to clarify the role of plant remains on the significant accumulation in the coarse fractions.     

Assessment of water quality based on Landsat 8 operational land imager associated with human activities in Korea

Water pollution such as green algae blooms and eutrophication in freshwater fatally influences both water quality and human society. Water quality issues in the 4 major rivers in Korea, including the Nakdong, have recently become a major concern. For this reason, it is essential to monitor water quality parameters (WQPs) that have a widespread characteristic to ensure maintenance of an effective water management system. The possibility of utilizing remote sensing technology for monitoring water quality on a regional scale has been recently investigated. The main objective of this study is to evaluate potential applications of the Landsat 8 Operational Land Imager (OLI) for estimating water quality in the Nakdong River, Korea. Correlations between Landsat 8 bands and in situ measurements are determined, and water quality models are established for estimating suspended solids (SS), total nitrogen (TN), chlorophyll-a (Chl-a), and total phosphorus (TP). The results demonstrate that WQPs correlated well with band reflectance values from Landsat 8. Band 5 was reasonably correlated with all WQPs, particularly with SS (R?=??0.74) and Chl-a (R?=??0.71). This study constructed multiple regression equations for WQPs based on correlation analysis through band combination and band ratio. The spatial distribution of WQPs in the Nakdong River on October 27, 2013 and May 16, 2014 indicate that the river was nearly eutrophic from human activities. Based on the results, the Landsat 8 OLI may be an appropriate data for estimating and monitoring water quality parameters on a regional scale. However, further validation is required to support the findings of this study.     

A comparison of radiometric correction techniques in the evaluation of the relationship between LST and NDVI in Landsat imagery

Atmospheric corrections for multi-temporal optical satellite images are necessary, especially in change detection analyses, such as normalized difference vegetation index (NDVI) rationing. Abrupt change detection analysis using remote-sensing techniques requires radiometric congruity and atmospheric correction to monitor terrestrial surfaces over time. Two atmospheric correction methods were used for this study: relative radiometric normalization and the simplified method for atmospheric correction (SMAC) in the solar spectrum. A multi-temporal data set consisting of two sets of Landsat images from the period between 1991 and 2002 of Penang Island, Malaysia, was used to compare NDVI maps, which were generated using the proposed atmospheric correction methods. Land surface temperature (LST) was retrieved using ATCOR3_T in PCI Geomatica 10.1 image processing software. Linear regression analysis was utilized to analyze the relationship between NDVI and LST. This study reveals that both of the proposed atmospheric correction methods yielded high accuracy through examination of the linear correlation coefficients. To check for the accuracy of the equation obtained through linear regression analysis for every single satellite image, 20 points were randomly chosen. The results showed that the SMAC method yielded a constant value (in terms of error) to predict the NDVI value from linear regression analysis-derived equation. The errors (average) from both proposed atmospheric correction methods were less than 10%.