The Characteristics of Tropospheric Ozone Seasonality Observed from Ozone Soundings at Pohang, Korea

This paper presents the first analysis of vertical ozone sounding measurements over Pohang, Korea. The main focus is to analyze the seasonal variation of vertical ozone profiles and determine the mechanisms controlling ozone seasonality. The maxima ozone at the surface and in the free troposphere are observed in May and June, respectively. In comparison with the ozone seasonality at Oki (near sea level) and Happo (altitude of 1840 m) in Japan, which are located at the same latitude as of Pohang, we have found that the time of the ozone maximum at the Japanese sites is always a month earlier than at Pohang. Analysis of the wind flow at the surface shows that the wind shifts from westerly to southerly in May over Japan, but in June over Pohang. However, this wind shift above boundary layer occurs a month later. This wind shift results in significantly smaller amounts of ozone because the southerly wind brings clean wet tropical air. It has been suggested that the spring ozone maximum in the lower troposphere is due to polluted air transported from China. However, an enhanced ozone amount over the free troposphere in June appears to have a different origin. A tongue-like structure in the time-height cross-section of ozone concentrations, which starts from the stratosphere and extends to the middle troposphere, suggests that the ozone enhancement occurs due to a gradual migration of ozone from the stratosphere. The high frequency of dry air with elevated ozone concentrations in the upper troposphere in June suggests that the air is transported from the stratosphere. HYSPLIT trajectory analysis supports the hypothesis that enhanced ozone in the free troposphere is not likely due to transport from sources of anthropogenic activity.     

Assessment of Wastewater Reuse Effects on Nutrient Loads from Paddy Field Using Field-Scale Water Quality Model

CREAMS-PADDY, a modified version of the field-scale CREAMS model, simulates the hydrologic, sediment, and nutrient cycles in paddy fields. The CREAMS-PADDY model was applied to estimate the effects of using wastewater for irrigation on nutrient loads from paddy fields in Republic of Korea. The model was calibrated and validated using data from two rice paddy fields. The coefficient of determination between observed and simulated total nitrogen and total phosphorus were 0.92 and 0.57, respectively, for the calibration period and 0.84 and 0.73 for the validation period. Simulations showed that when using wastewater for irrigation, the total nitrogen loads increased by 210% and total phosphorus by 1,270% when compared with conventional water irrigation. The total nitrogen and total phosphorus concentration in the ponded water increased by 254 and 534%, respectively, when compared with conventional water irrigation. The effect of reducing N and P fertilizer application rates by 10, 30, and 50% on nutrient loads exiting a paddy field were also simulated using the validated CREAMS-PADDY model. These simulations indicated that total phosphorus loads from the paddy were reduced only slightly by reducing the fertilizer, while total nitrogen loads were reduced by as much as 8.8, 16.6, and 24.4% when N ferlitizer rates were reduced by 10, 30, and 50%, respectively. An erratum to this article can be found at     

Modeling of road traffic noise and estimated human exposure in Fulton County, Georgia, USA

Environmental noise is a major source of public complaints. Noise in the community causes physical and socio-economic effects and has been shown to be related to adverse health impacts. Noise, however, has not been actively researched in the United States compared with the European Union countries in recent years. In this research, we aimed at modeling road traffic noise and analyzing human exposure in Fulton County, Georgia, United States. We modeled road traffic noise levels using the United States Department of Transportation Federal Highway Administration Traffic Noise Model implemented in SoundPLAN?. After analyzing noise levels with raster, vector and fa?ade maps, we estimated human exposure to high noise levels. Accurate digital elevation models and building heights were derived from Light Detection And Ranging survey datasets and building footprint boundaries. Traffic datasets were collected from the Georgia Department of Transportation and the Atlanta Regional Commission. Noise level simulation was performed with 62 computers in a distributed computing environment. Finally, the noise-exposed population was calculated using geographic information system techniques. Results show that 48% of the total county population [N=870,166 residents] is potentially exposed to 55 dB(A) or higher noise levels during daytime. About 9% of the population is potentially exposed to 67 dB(A) or higher noises. At nighttime, 32% of the population is expected to be exposed to noise levels higher than 50 dB(A). This research shows that large-scale traffic noise estimation is possible with the help of various organizations. We believe that this research is a significant stepping stone for analyzing community health associated with noise exposures in the United States.     

The impact of heavy metal pollution gradients in sediments on benthic macrofauna at population and community levels

The effect of sediment pollution on benthos was investigated in the vicinity of a large sewage treatment outflow at Incheon North Harbor, Korea. Animal size, vertical distribution and standard community parameters were analyzed along a 3 km transect line (n = 7). Univariate parameters showed a general trend of increasing species diversity with increasing distance from the pollution source. Multi-dimensional scaling analysis led to the clear separation of 3 locational groups, supporting gradient-dependent faunal composition. The innermost location was dominated by small sub-surface dwellers while the outer locations by large mid to deep burrowers. Looking for the size-frequency distribution, most abundance species (Heteromastus filiformis) showed the presence of larger size animals with increasing proximity to the pollution source. Meanwhile, species-specific vertical distributions, regardless of the pollution gradient, indicated that such shifts were due to species replacement resulting from a higher tolerance to pollutants over some species.     

Food waste impact on municipal solid waste angle of internal friction

The impact of food waste content on the municipal solid waste (MSW) friction angle was studied. Using reconstituted fresh MSW specimens with different food waste content (0%, 40%, 58%, and 80%), 48 small-scale (100-mm-diameter) direct shear tests and 12 large-scale (430 mm × 430 mm) direct shear tests were performed. A stress-controlled large-scale direct shear test device allowing approximately 170-mm sample horizontal displacement was designed and used. At both testing scales, the mobilized internal friction angle of MSW decreased considerably as food waste content increased. As food waste content increased from 0% to 40% and from 40% to 80%, the mobilized internal friction angles (estimated using the mobilized peak (ultimate) shear strengths of the small-scale direct shear tests) decreased from 39° to 31° and from 31° to 7°, respectively, while those of large-scale tests decreased from 36° to 26° and from 26° to 15°, respectively. Most friction angle measurements produced in this study fell within the range of those previously reported for MSW.     

Distribution of perfluorochemicals between sera and milk from the same mothers and implications for prenatal and postnatal exposures

The levels of six perfluorocarboxylates (PFCAs), four perfloroalkylsulfonates (PFASs), and one sulfonamide were measured in paired samples of maternal serum, umbilical cord serum, and breast milk. The maternal and cord sera were strongly correlated with each other for all measured compounds (r > 0.5 and p < 0.01). Nevertheless, there was a significant difference in compound composition profile between the two sera matrices, with a more depletion of the longer chain compounds in cord serum. The transfer efficiency values from maternal to cord serum (TF_CS/MS) decreased by 70% with each increasing unit of -CF₂ chain within a PFCA group, and for perfluorooctanesulfonate (PFOS), by a half compared to perfluorooctanoate (PFOA). In contrast to the strong correlation in concentrations between the two sera matrices, the pattern of compounds in breast milk differed considerably with those in sera. Accordingly, compound- and matrix-specific transfer must be considered when assessing prenatal and postnatal exposure.     

Predicting Debris Yield From Burned Watersheds: Comparison of Statistical and Artificial Neural Network Models1

Abstract: Alluvial fans in southern California are continuously being developed for residential, industrial, commercial, and agricultural purposes. Development and alteration of alluvial fans often require consideration of mud and debris flows from burned mountain watersheds. Accurate prediction of sediment (hyper‐concentrated sediment or debris) yield is essential for the design, operation, and maintenance of debris basins to safeguard properly the general population. This paper presents results based on a statistical model and Artificial Neural Network (ANN) models. The models predict sediment yield caused by storms following wildfire events in burned mountainous watersheds. Both sediment yield prediction models have been developed for use in relatively small watersheds (50‐800 ha) in the greater Los Angeles area. The statistical model was developed using multiple regression analysis on sediment yield data collected from 1938 to 1983. Following the multiple regression analysis, a method for multi‐sequence sediment yield prediction under burned watershed conditions was developed. The statistical model was then calibrated based on 17 years of sediment yield, fire, and precipitation data collected between 1984 and 2000. The present study also evaluated ANN models created to predict the sediment yields. The training of the ANN models utilized single storm event data generated for the 17‐year period between 1984 and 2000 as the training input data. Training patterns and neural network architectures were varied to further study the ANN performance. Results from these models were compared with the available field data obtained from several debris basins within Los Angeles County. Both predictive models were then applied for hind‐casting the sediment prediction of several post 2000 events. Both the statistical and ANN models yield remarkably consistent results when compared with the measured field data. The results show that these models are very useful tools for predicting sediment yield sequences. The results can be used for scheduling cleanout operation of debris basins. It can be of great help in the planning of emergency response for burned areas to minimize the damage to properties and lives.     

Investigating the real-world emission characteristics of light-duty gasoline vehicles and their relationship to local socioeconomic conditions in three communities in Los Angeles,California

This paper discusses results from a vehicular emissions research study of over 350 vehicles conducted in three communities in Los Angeles, CA, in 2010 using vehicle chase measurements. The study explores the real-world emission behavior of light-duty gasoline vehicles, characterizes real-world super-emitters in the different regions, and investigates the relationship of on-road vehicle emissions with the socioeconomic status (SES) of the region. The study found that in comparison to a 2007 earlier study in a neighboring community, vehicle emissions for all measured pollutants had experienced a significant reduction over the years, with oxides of nitrogen (NO_X) and black carbon (BC) emissions showing the largest reductions. Mean emission factors of the sampled vehicles in low-SES communities were roughly 2–3 times higher for NO_X, BC, carbon monoxide, and ultrafine particles, and 4–11 times greater for fine particulate matter (PM_2.5) than for vehicles in the high-SES neighborhood. Further analysis indicated that the emission factors of vehicles within a technology group were also higher in low-SES communities compared to similar vehicles in the high-SES community, suggesting that vehicle age alone did not explain the higher vehicular emission in low-SES communities.

Evaluation of the emission factor distribution found that emissions from 12% of the sampled vehicles were greater than five times the mean from all of the sampled fleet, and these vehicles were consequently categorized as “real-world super-emitters.” Low-SES communities had approximately twice as many super-emitters for most of the pollutants as compared to the high-SES community. Vehicle emissions calculated using model-year-specific average fuel consumption assumptions suggested that approximately 5% of the sampled vehicles accounted for nearly half of the total CO, PM_2.5, and UFP emissions, and 15% of the vehicles were responsible for more than half of the total NO_X and BC emissions from the vehicles sampled during the study.

Implications: This study evaluated the real-world emission behavior and super-emitter distribution of light-duty gasoline vehicles in California, and investigated the relationship of on-road vehicle emissions with local socioeconomic conditions. The study observed a significant reduction in vehicle emissions for all measured pollutants when compared to an earlier study in Wilmington, CA, and found a higher prevalence of high-emitting vehicles in low-socioeconomic-status communities. As overall fleet emissions decrease from stringent vehicle emission regulations, a small fraction of the fleet may contribute to a disproportionate share of the overall on-road vehicle emissions. Therefore, this work will have important implications for improving air quality and public health, especially in low-SES communities.