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.     

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%.     

Groundwater quality assessment in the urban-west region of Zanzibar Island

This paper highlights the levels of anions (nitrate, nitrite, sulfate, bromide, chloride, and fluoride) and cations (potassium, sodium, magnesium, and calcium) in selected springs and groundwater sources in the urban-west region of Zanzibar Island. The levels of total dissolved solids (TDS) and sodium adsorption ratio (SAR) were also studied. Thirty water samples were collected in December 2012 from various types of water sources, which included closed hand-dug wells (CHDW), open hand-dug wells (OHDW), springwater (SW), public bore wells (PBW), and bore wells owned by private individuals (BWP), and analyzed after filtration and sometimes dilution. The cations were analyzed using inductively coupled plasma-optical emission spectrometry (ICP-OES). The anions were analyzed by chemically suppressed ion chromatography (IC). The ranges of the levels of the investigated parameters were as follows: Na 13.68–3,656 mg L^?1, K 2.66–583 mg L^?1, Mg 0.63–131.10 mg L^?1, Ca 16.79–189.9 mg L^?1, Cl^? 8.61–4,340.97 mg L^?1, F^? 0–1.02 mg L^?1, Br^? 0–10.88 mg L^?1, NO₃ ^? 0.18–342.4 mg L^?1, NO₂ ^? 0–1.39, SO₄ ^2? 4.43–534.02 mg L^?1, TDS 7–6,380 mg L^?1, and SAR 0.63–50. Except fluoride, most of the studied parameters in the water samples had concentrations beyond the permissible limits of the World Health Organization (WHO). The elevated concentrations are a result of seepage of contaminated water from on-site septic tanks, pit latrines, landfill leachates, fertilizer applications, and domestic effluents. These results should alert domestic water stakeholders in Zanzibar to the urgent task of initiating a quick mitigation response to control these alarming water risks.     

Electrospun Protein Concentrate Fibers from Microalgae Residual Biomass

Currently there is a growing interest in developing novel bioproducts and biomaterials derived from renewable sources that can reduce the dependence on fossil fuel feedstock. In this study a protein concentrate from microalgae Botryococcus braunii residual biomass (MPC) from a biorefinery process was used as a biopolymer to develop ultrafine fibers by electrospinning. Experiments were designed to study the effect of different formulations of MPC, poly(ethylene oxide) and pH on morphology and diameter of fibers. The results indicated MPC fibers from acidic solutions prepared at pH 1 had smoother and smaller diameter than those fibers from alkaline solutions (pH 12). Moreover, under the conditions studied, it was conclude that pH and the concentration of MPC were the most significant factors in determining the diameter and morphology of the fibers obtained. Fourier transform infrared analysis showed there is a slight frequency shift for the secondary structure of MPC as induced by change in pH of the polymer solutions. Likely this change in the protein structure improved the physical chain entanglement in the polymer blend. The results of this work revealed a potential to develop fibers from MPC from residual biomass by a promising technique that may find many end-use applications.