Korea Environment Institute

Nature is perceived and valued in starkly different and oftenconflicting ways. This paper presents the rationale for theinclusive valuation of nature's contributions to people (NCP) indecision making, as well as broad methodological steps fordoing so. While developed within the context of theIntergovernmental Platform on Biodiversity and Ecosystem Services (IPBES), this approach is more widely applicable toinitiatives at the knowledge?policy interface, which require apluralistic approach to recognizing the diversity of values. Weargue that transformative practices aiming at sustainablefutures would benefit from embracing such diversity, which require recognizing and addressing power relationships across stake holder groups that hold different values on human nature relations and NCP

Abstract Twenty-five years since foundational publications on valuing ecosystem services for human well-being 1,2 , addressing the global biodiversity crisis 3 still implies confronting barriers to incorporating nature’s diverse values into decision-making. These barriers include powerful interests supported by current norms and legal rules such as property rights, which determine whose values and which values of nature are acted on. A better understanding of how and why nature is (under)valued is more urgent than ever 4 . Notwithstanding agreements to incorporate nature’s values into actions, including the Kunming-Montreal Global Biodiversity Framework (GBF) 5 and the UN Sustainable Development Goals 6 , predominant environmental and development policies still prioritize a subset of values, particularly those linked to markets, and ignore other ways people relate to and benefit from nature 7 . Arguably, a ‘values crisis’ underpins the intertwined crises of biodiversity loss and climate change 8 , pandemic emergence 9 and socio-environmental injustices 10 . On the basis of more than 50,000 scientific publications, policy documents and Indigenous and local knowledge sources, the Intergovernmental Platform on Biodiversity and Ecosystem Services (IPBES) assessed knowledge on nature’s diverse values and valuation methods to gain insights into their role in policymaking and fuller integration into decisions 7,11 . Applying this evidence, combinations of values-centred approaches are proposed to improve valuation and address barriers to uptake, ultimately leveraging transformative changes towards more just (that is, fair treatment of people and nature, including inter- and intragenerational equity) and sustainable futures.

Relieving phosphorus loading is a key management tool for controlling Lake Erie eutrophication. During the 1960s and 1970s, increased phosphorus inputs degraded water quality and reduced central basin hypolimnetic oxygen levels which, in turn, eliminated thermal habitat vital to cold-water organisms and contributed to the extirpation of important benthic macroinvertebrate prey species for fishes. In response to load reductions initiated in 1972, Lake Erie responded quickly with reduced water-column phosphorus concentrations, phytoplankton biomass, and bottom-water hypoxia (dissolved oxygen < 2 mg/l). Since the mid-1990s, cyanobacteria blooms increased and extensive hypoxia and benthic algae returned. We synthesize recent research leading to guidance for addressing this re-eutrophication, with particular emphasis on central basin hypoxia. We document recent trends in key eutrophication-related properties, assess their likely ecological impacts, and develop load response curves to guide revised hypoxia-based loading targets called for in the 2012 Great Lakes Water Quality Agreement. Reducing central basin hypoxic area to levels observed in the early 1990s (ca. 2000 km2) requires cutting total phosphorus loads by 46% from the 2003–2011 average or reducing dissolved reactive phosphorus loads by 78% from the 2005–2011 average. Reductions to these levels are also protective of fish habitat. We provide potential approaches for achieving those new loading targets, and suggest that recent load reduction recommendations focused on western basin cyanobacteria blooms may not be sufficient to reduce central basin hypoxia to 2000 km2.

Since flood frequency increases with the impact of climate change, the damage that is emphasized on flood-risk maps is based on actual flooded area data; therefore, flood-susceptibility maps for the Seoul metropolitan area, for which random-forest and boosted-tree models are used in a geographic information system (GIS) environment, are created for this study. For the flood-susceptibility mapping, flooded-area, topography, geology, soil and land-use datasets were collected and entered into spatial datasets. From the spatial datasets, 12 factors were calculated and extracted as the input data for the models. The flooded area of 2010 was used to train the model, and the flooded area of 2011 was used for the validation. The importance of the factors of the flood-susceptibility maps was calculated and lastly, the maps were validated. As a result, the distance from the river, geology and digital elevation model showed a high importance among the factors. The random-forest model showed validation accuracies of 78.78% and 79.18% for the regression and classification algorithms, respectively, and boosted-tree model showed validation accuracies of 77.55% and 77.26% for the regression and classification algorithms, respectively. The flood-susceptibility maps provide meaningful information for decision-makers regarding the identification of priority areas for flood-mitigation management.

With the increased production and widespread use of multiwalled carbon nanotubes (MWCNTs), human and environmental exposure to MWCNTs is inevitably increasing. Therefore, this study monitored the possible exposure to MWCNT release in a carbon nanotube research laboratory. To estimate the potential exposure of researchers and evaluate the improvement of the workplace environment after the implementation of protective control measures, personal and area monitoring were conducted in an MWCNT research facility where the researchers handled unrefined materials. The number, composition, and aspect ratio of MWCNTs were measured using scanning transmission electron microscopy with an energy-dispersive x-ray analyzer. The gravimetric concentrations of total dust before any control measures ranged from 0.21 to 0.43 mg/m(3), then decreased to a nondetectable level after implementing the control measures. The number of MWCNTs in the samples obtained from the MWCNT blending laboratory ranged from 172.9 to 193.6 MWCNTs/cc before the control measures, and decreased to 0.018-0.05 MWCNTs/cc after the protective improvements. The real-time monitoring of aerosol particles provided a signature of the MWCNTs released from the blending equipment in laboratory C. In particular, the number size response of an aerodynamic particle sizer with a relatively high concentration in the range of 2 to 3 microm in aerodynamic diameter revealed the evidence of MWCNT exposure. The black carbon mass concentration also increased significantly during the MWCNT release process. Therefore, the present study suggests that the conventional industrial hygiene measures can significantly reduce exposure to airborne MWCNTs and other particulate materials in a nano research facility.

Abstract The main purpose of this study is to identify the major factors affecting groundwater quality by means of multivariate statistical analysis of the physico‐chemical compositions. Cluster analysis results show that the groundwater in the study area is classified into four groups (A, B, C and D), and factor analysis indicates that groundwater composition, 81·9% of the total variance of 17 variables, is mainly affected by three factors: seawater intrusion, microbial activity and chemical fertilizers. These results might be related to the geographical characteristics of the study area. The main influence on groundwater in groups B, C and D, which are close to the Yellow Sea and contain reclaimed areas, is the seawater intrusion by the present seawater, the trapped seawater, and microbial activity. Group A, however, has been used for agriculture for a long time, and thus groundwater in this group has been largely affected by chemical fertilizers. As groundwater flows from group A to group D according to its path, the governing factor of the groundwater quality gradually changes from chemical fertilizers to microbial activity and seawater intrusion. Copyright © 2004 John Wiley &amp; Sons, Ltd.

Recently there has been an increasing occurrence of flooded area in Korea. Most of these flooded area occurred roadside in the city or residential areas. For predictive flooded area susceptibility mapping, this study applied and verified probability model, the frequency ratio at Busan, Korea, using a Geographic Information System (GIS) and Statistical methods. Flooded areas were identified in the study area of field surveys, and maps of the topography, geology, landcover and green infrastructure were constructed to spatial database. Using this analysis results, part of urban planning can find ideal locations for GIS which are needed. This result expects that this planning framework can bring flood mitigation of city.

BACKGROUND: Previous studies have associated short-term air pollution exposure with depression. Although an animal study showed an association between long-term exposure to particulate matter ≤ 2.5 μm (PM2.5) and depression, epidemiological studies assessing the long-term association are scarce. OBJECTIVE: We aimed to determine the association between long-term PM2.5 exposure and major depressive disorder (MDD). METHODS: A total of 27,270 participants 15-79 years of age who maintained an address within the same districts in Seoul, Republic of Korea, throughout the entire study period (between 2002 and 2010) and without a previous MDD diagnosis were analyzed. We used three district-specific exposure indices as measures of long-term PM2.5 exposure. Cox proportional hazards models adjusted for potential confounding factors and measured at district and individual levels were constructed. We further conducted stratified analyses according to underlying chronic diseases such as diabetes mellitus, cardiovascular disease, and chronic obstructive pulmonary disease. RESULTS: The risk of MDD during the follow-up period (2008-2010) increased with an increase of 10 μg/m3 in PM2.5 in 2007 [hazard ratio (HR) = 1.44; 95% CI: 1.17, 1.78], PM2.5 between 2007 and 2010 (HR = 1.59; 95% CI: 1.02, 2.49), and 12-month moving average of PM2.5 until an event or censor (HR = 1.47; 95% CI: 1.14, 1.90). The association between long-term PM2.5 exposure and MDD was greater in participants with underlying chronic diseases than in participants without these diseases. CONCLUSION: Long-term PM2.5 exposure increased the risk of MDD among the general population. Individuals with underlying chronic diseases are more vulnerable to long-term PM2.5 exposure. CITATION: Kim KN, Lim YH, Bae HJ, Kim M, Jung K, Hong YC. 2016. Long-term fine particulate matter exposure and major depressive disorder in a community-based urban cohort. Environ Health Perspect 124:1547-1553; http://dx.doi.org/10.1289/EHP192.

Spatial visitation patterns and its features on nature-based tourism are difficult to assess using only a field-based survey, which is costly and labor intensive. However, understanding of a protected area's visitation status is critical, as it can strongly influence the sustainability of natural resources. Hence, it is important to identify ‘where people visit’ and ‘why people visit,’ to evaluate the features attractive to tourists. In this regard, we proposed and applied social big data to investigate nature-based tourism in an ASEAN Heritage Park. Overall, our research was able to effectively illustrate spatial patterns of visitation using 10 years of Flickr geo-tagged photographs. Hotspots of high visitation were identified, while revealing the local spatial impact of distributed attributes. This study offers insights into the applicability of social big data to protected-area management and its potential in reinforcing existing field-based participatory approaches.

Hexose and pentose cofermentation is regarded as one of the chief obstacles impeding economical conversion of lignocellulosic biomass to biofuels. Over time, successful application of traditional metabolic engineering strategy has produced yeast strains capable of utilizing the pentose sugars (especially xylose and arabinose) as sole carbon sources, yet major difficulties still remain for engineering simultaneous, exogenous sugar metabolism. Beyond catabolic pathways, the focus must shift towards non-traditional aspects of cellular engineering such as host molecular transport capability, catabolite sensing and stress response mechanisms. This review highlights the need for an approach termed 'panmetabolic engineering', a new paradigm for integrating new carbon sources into host metabolic pathways. This approach will concurrently optimize the interdependent processes of transport and metabolism using novel combinatorial techniques and global cellular engineering. As a result, panmetabolic engineering is a whole pathway approach emphasizing better pathways, reduced glucose-induced repression and increased product tolerance. In this paper, recent publications are reviewed in light of this approach and their potential to expand metabolic engineering tools. Collectively, traditional approaches and panmetabolic engineering enable the reprogramming of extant biological complexity and incorporation of exogenous carbon catabolism.

Adequate groundwater development for the rural population is essential because groundwater is an important source of drinking water and agricultural water. In this study, ensemble models of decision tree-based machine learning algorithms were used with geographic information system (GIS) to map and test groundwater yield potential in Yangpyeong-gun, South Korea. Groundwater control factors derived from remote sensing data were used for mapping, including nine topographic factors, two hydrological factors, forest type, soil material, land use, and two geological factors. A total of 53 well locations with both specific capacity (SPC) data and transmissivity (T) data were selected and randomly divided into two classes for model training (70%) and testing (30%). First, the frequency ratio (FR) was calculated for SPC and T, and then the boosted classification tree (BCT) method of the machine learning model was applied. In addition, an ensemble model, FR-BCT, was applied to generate and compare groundwater potential maps. Model performance was evaluated using the receiver operating characteristic (ROC) method. To test the model, the area under the ROC curve was calculated; the curve for the predicted dataset of SPC showed values of 80.48% and 87.75% for the BCT and FR-BCT models, respectively. The accuracy rates from T were 72.27% and 81.49% for the BCT and FR-BCT models, respectively. Both the BCT and FR-BCT models measured the contributions of individual groundwater control factors, which showed that soil was the most influential factor. The machine learning techniques used in this study showed effective modeling of groundwater potential in areas where data are relatively scarce. The results of this study may be used for sustainable development of groundwater resources by identifying areas of high groundwater potential.

The tissue distribution of silver (Ag) nanoparticles showed a dose-dependent accumulation of Ag in all the tissues examined, including testes, kidneys, liver, brain, lungs, and blood. However, a gender-related difference in the accumulation of Ag was noted in the kidneys, with a twofold higher concentration in female kidneys compared males after subacute exposure to Ag nanoparticles via inhalation or oral ingestion. To investigate the gender-specific accumulation of Ag nanoparticles in kidneys of Fischer 344 rats, detailed histopathological studies were conducted by Ag enhancement staining. Female rats showed a higher accumulation of Ag nanoparticles in all kidney regions, including cortex, outer medulla, and inner medulla. In particular, the glomerulus in the cortex contained a higher accumulation in females than males. The Ag nanoparticles were also preferentially accumulated in the basement membranes of the renal tubules in the cortex, middle and terminal parts of the inner medulla, and outer medulla. In addition, Ag nanoparticles were detected in the cytoplasm and nuclei of interstitial cells in the inner medulla of the kidney.

Seven CNT (carbon nanotube) handling workplaces were investigated for exposure assessment. Personal sampling, area sampling, and real-time monitoring using an SMPS (scanning mobility particle sizer), dust monitor, and aethalometer were performed to characterize the mass exposure, particle size distribution, and particle number exposure. No workplace was found to exceed the current ACGIH (American Conference of Governmental Industrial Hygienists) TLVs (threshold limit values) and OELs (occupational exposure levels) set by the Korean Ministry of Labor for carbon black (3.5 mg/m(3)), PNOS (particles not otherwise specified; 3 mg/m(3)), and asbestos (0.1 fiber/cc). Nanoparticles and fine particles were most frequently released after opening the CVD (chemical vapor deposition) cover, followed by catalyst preparation. Other work processes that prompted nanoparticle release included spraying, CNT preparation, ultrasonic dispersion, wafer heating, and opening the water bath cover. All these operation processes could be effectively controlled with the implementation of exposure mitigation, such as engineering control, except at one workplace where only natural ventilation was used.

We assess the impact of transport of pollution from midlatitudes on the abundance of ozone in the Arctic in summer 2006 using the GEOS‐Chem global chemical transport model and its adjoint. We find that although the impact of midlatitude emissions on ozone abundances in the Arctic is at a maximum in fall and winter, in July transport from North America, Asia, and Europe together contributed about 25% of surface ozone abundances in the Arctic. Throughout the summer, the dominant source of ozone in the Arctic troposphere was photochemical production within the Arctic, which accounted for more than 50% of the ozone in the Arctic boundary layer and as much as 30%–40% of the ozone in the middle troposphere. An adjoint sensitivity analysis of the impact of NO x emissions on ozone at Alert shows that on synoptic time scales in both the lower and middle troposphere, ozone abundances are more sensitive to emissions between 50°N and 70°N, with important influences from anthropogenic, biomass burning, soil, and lightning sources. Although local surface NO x emissions contribute to ozone formation, transport of NO x in the form of peroxyacetyl nitrate (PAN) from outside the Arctic and from the upper troposphere also contributed to ozone production in the lower troposphere. We find that in late May and June the release of NO x from PAN decomposition accounted for 93% and 55% of ozone production at the Arctic surface, respectively.

Abstract. Together with emissions of air pollutants and precursors, meteorological conditions play important roles in local air quality through accumulation or ventilation, regional transport, and atmospheric chemistry. In this study, we extensively investigated multi-timescale meteorological effects on the urban air pollution using the long-term measurements data of PM10, SO2, NO2, CO, and O3 and meteorological variables over the period of 1999–2016 in Seoul, South Korea. The long-term air quality data were decomposed into trend-free short-term components and long-term trends by the Kolmogorov–Zurbenko filter, and the effects of meteorology and emissions were quantitatively isolated using a multiple linear regression with meteorological variables. In terms of short-term variability, intercorrelations among the pollutants and meteorological variables and composite analysis of synoptic meteorological fields exhibited that the warm and stagnant conditions in the migratory high-pressure system are related to the high PM10 and primary pollutant, while the strong irradiance and low NO2 by high winds at the rear of a cyclone are related to the high O3. In terms of long-term trends, decrease in PM10 (−1.75 µg m−3 yr−1) and increase in O3 (+0.88 ppb yr−1) in Seoul were largely contributed by the meteorology-related trends (−0.94 µg m−3 yr−1 for PM10 and +0.47 ppb yr−1 for O3), which were attributable to the subregional-scale wind speed increase. Comparisons with estimated local emissions and socioeconomic indices like gross domestic product (GDP) growth and fuel consumptions indicate probable influences of the 2008 global economic recession as well as the enforced regulations from the mid-2000s on the emission-related trends of PM10 and other primary pollutants. Change rates of local emissions and the transport term of long-term components calculated by the tracer continuity equation revealed a decrease in contributions of local emissions to the primary pollutants including PM10 and an increase in contributions of local secondary productions to O3. The present results not only reveal an important role of synoptic meteorological conditions on the episodic air pollution events but also give insights into the practical effects of environmental policies and regulations on the long-term air pollution trends. As a complementary approach to the chemical transport modeling, this study will provide a scientific background for developing and improving effective air quality management strategy in Seoul and its metropolitan area.

A bottom-up emissions inventory is one of the most important data sets needed to understand air quality (AQ) and climate change (CC). Several emission inventories have been developed for Asia, including Transport and Chemical Evolution over the Pacific (TRACE-P), Regional Emission Inventory in Asia (REAS), and Inter-Continental Chemical Transport Experiment (INTEX) and, while these have been used successfully for many international studies, they have limitations including restricted amounts of information on pollutant types and low levels of transparency with respect to the polluting sectors or fuel types involved. To address these shortcomings, we developed: (1) a base-year, bottom-up anthropogenic emissions inventory for Asia, using the most current parameters and international frameworks (i.e., the Greenhouse gas—Air pollution INteractions and Synergies (GAINS) model); and (2) a base-year, natural emissions inventory for biogenic and biomass burning. For (1), we focused mainly on China, South Korea, and Japan; however, we also covered emission inventories for other regions in Asia using data covering recent energy/industry statistics, emission factors, and control technology penetration. The emissions inventory (Comprehensive Regional Emissions inventory for Atmospheric Transport Experiment (CREATE)) covers 54 fuel classes, 201 subsectors, and 13 pollutants, namely SO2, NOx, CO, non-methane volatile organic compounds (NMVOC), NH3, OC, BC, PM10, PM2.5, CO2, CH4, N2O, and Hg. For the base-year natural emissions inventory, the Model of Emissions of Gases and Aerosols from Nature (MEGAN) and BlueSky-Asia frameworks were used to estimate biogenic and biomass burning emissions, respectively. Since the CREATE emission inventory was designed/developed using international climate change/air quality (CC/AQ) assessment frameworks, such as GAINS, and has been fully connected with the most comprehensive emissions modeling systems—such as the US Environmental Protection Agency (EPA) Chemical Manufacturing Area Source (CMAS) system—it can be used to support various climate and AQ integrated modeling studies, both now and in the future.

As most of the forest fires in South Korea are related to human activity, socio-economic factors are critical in estimating their probability. To estimate and analyze how human activity is influencing forest fire probability, this study considered not only environmental factors such as precipitation, elevation, topographic wetness index, and forest type, but also socio-economic factors such as population density and distance from urban area. The machine learning Maximum Entropy (Maxent) and Random Forest models were used to predict and analyze the spatial distribution of forest fire probability in South Korea. The model performance was evaluated using the receiver operating characteristic (ROC) curve method, and models’ outputs were compared based on the area under the ROC curve (AUC). In addition, a multi-temporal analysis was conducted to determine the relationships between forest fire probability and socio-economic or environmental changes from the 1980s to the 2000s. The analysis revealed that the spatial distribution was concentrated in or around cities, and the probability had a strong correlation with variables related to human activity and accessibility over the decades. The AUC values for validation were higher in the Random Forest result compared to the Maxent result throughout the decades. Our findings can be useful for developing preventive measures for forest fire risk reduction considering socio-economic development and environmental conditions.

OBJECTIVE: Many people are exposed to perfluoroalkyl substances (PFASs) because these substances are widely used as industrial products. Although epidemiological studies suggest that PFASs can disrupt thyroid hormones, the association between PFAS exposure and thyroid function remains inconclusive. Therefore, we performed a comprehensive meta-analysis to investigate the association between PFASs exposure and thyroid hormones. METHODS: We searched medical literature databases for articles on the association between PFASs-perfluorooctanesulfonic acid (PFOS), perfluorooctanoic acid (PFOA), and perfluorohexane sulfonic acid (PFHxS)-and thyroid hormone levels in adults. Twelve articles were included in the meta-analysis, and the pooled z values were calculated with correlation or regression coefficients. RESULTS: The blood PFOS concentration was positively correlated with free T4. The pooled z value was 0.05 (95% confidence interval (CI): 0.03, 0.08). PFOS was negatively correlated with total T4 and total T3 when excluding outlier studies. In a subgroup analysis stratified by mean PFOS concentration, PFOS was observed to be positively associated with free T4 and TSH and negatively associated with total T3 in the intermediate concentration group (8-16 ng/mL). PFOA concentration was negatively correlated with total T4 (z value, -0.06; 95% CI: -0.09, -0.03) after omitting one outlier study. PFHxS also showed a negative correlation with total T4 (z value, -0.04; 95% CI: -0.07, -0.01). A subgroup analysis of pregnant women showed that there was no association between PFASs and thyroid hormones. CONCLUSIONS: Our meta-analysis suggests that PFASs are negatively associated with total T4, and their effect can be different depending on the PFAS concentration.

Artificial structures installed in rivers can change the natural physical, physiochemical, and biological characteristics of the rivers. Coliform bacteria are important water quality indicators, related to human health. This study investigated the relationship between coliform bacteria and water quality factors at eight weir stations constructed in the Nakdong River, a major river in South Korea. Fifteen water quality factors were analyzed at these sites from 2012 to 2016 using correlation and multiple regression analyses. The results for all stations confirmed the analytical validity, with high adjusted R2 values of approximately 0.6 and 0.8 on average for total and fecal coliforms, respectively. The results showed influential water quality factors affecting the concentration of coliform bacteria at weir stations. Specifically, total coliforms were mostly affected by organic matter and fecal coliforms were mostly affected by phosphate phosphorus and suspended solids. Rainfall was the most influential factor affecting both coliforms. Further, both coliforms were negatively affected by organic matter below the Dalseong weir in the mid- to downstream area of the Nakdong River. A positive relationship with phosphate phosphorus was indicated at all weir stations. To the authors’ knowledge, this kind of study has never been attempted so far. Thus, the study results can provide important information on influential water quality factors related to coliform bacteria, especially in the Nakdong River, creating a foundation for future water quality management.

This article describes the relationship between the design features of green infrastructure and the benefits of multifunctionality. To do so, it examines the descriptive linkages between 12 design features and nine benefits using 447 project case studies from the American Society of Landscape Architects. Multiple benefits of green infrastructure were found in 65% of the projects, regardless of the number of applied design features. The major green infrastructure design features with multiple benefits were: bioretention areas, permeable pavements, grassed swales, rainwater harvesting, rain gardens, and curb cuts. The major benefits of applied design features were: enhanced economic capacity, educational opportunities, improvements to the built environment, and enhanced environmental soundness. The findings show that the multiple benefits of green infrastructure’s multifunctionality can be inferred in many current cases. Knowing the relationship between design features and their benefits for green infrastructure would facilitate selecting optimal design features to achieve specific goals and planning outcomes. For communities that require a range of complex benefits, a multifunctionality-based green infrastructure will advance highly acceptable climate change adaptation measures.