Characteristics of aerosol types during large-scale transport of air pollution over the Yellow Sea region and at Cheongwon,Korea, in 2008

Episodes of large-scale transport of airborne dust and anthropogenic pollutant particles from different sources in the East Asian continent in 2008 were identified by National Oceanic and Atmospheric Administration satellite RGB (red, green, and blue)-composite images and the mass concentrations of ground level particulate matter. These particles were divided into dust, sea salt, smoke plume, and sulfate by an aerosol classification algorithm. To analyze the aerosol size distribution during large-scale transport of atmospheric aerosols, aerosol optical depth (AOD) and fine aerosol weighting (FW) of moderate imaging spectroradiometer aerosol products were used over the East Asian region. Six episodes of massive airborne dust particles, originating from sandstorms in northern China, Mongolia, and the Loess Plateau of China, were observed at Cheongwon. Classified dust aerosol types were distributed on a large-scale over the Yellow Sea region. The average PM10 and PM2.5 ratio to the total mass concentration TSP were 70% and 15%, respectively. However, the mass concentration of PM2.5 among TSP increased to as high as 23% in an episode where dust traveled in by way of an industrial area in eastern China. In the other five episodes of anthropogenic pollutant particles that flowed into the Korean Peninsula from eastern China, the anthropogenic pollutant particles were largely detected in the form of smoke over the Yellow Sea region. The average PM10 and PM2.5 ratios to TSP were 82% and 65%, respectively. The ratio of PM2.5 mass concentrations among TSP varied significantly depending on the origin and pathway of the airborne dust particles. The average AOD for the large-scale transport of anthropogenic pollutant particles in the East Asian region was measured to be 0.42 ± 0.17, which is higher in terms of the rate against atmospheric aerosols as compared with the AOD (0.36 ± 0.13) for airborne dust particles with sandstorms. In particular, the region ranging from eastern China, the Yellow Sea, and the Korean Peninsula to the Korea East Sea was characterized by high AOD distributions. In the episode of anthropogenic polluted aerosols, FW averaged 0.63 ± 0.16, a value higher than that in the episode of airborne dust particles (0.52 ± 0.13) with sandstorms, showing that fine anthropogenic pollutant particles contribute greatly to atmospheric aerosols in East Asia.     

Vulnerability of agro-ecological zones in India under the earth system climate model scenarios

India being a developing economy dependent on climate-sensitive sector like agriculture is highly vulnerable to impacts of global climate change. Vulnerability to climate change, however, differs spatially within the country owing to regional differences in exposure, sensitivity, and adaptive capacity. The study uses the Hadley Centre Global Environment Model version 2-Earth System (HadGEM-ES) climate projections to assess the dynamics in vulnerability across four climate change exposure scenarios developed using Representative Concentration Pathways (RCPs). The analysis was carried out at subnational (district) level; the results were interpreted and reported for their corresponding agro-ecological zones. Vulnerability of each district was quantified using indicators capturing climatic variability, ecological and demographic sensitivity, and socio-economic capacity. Our analysis further assigns probabilities to vulnerability classes of all the 579 districts falling under different agro-ecological zones. The results of the vulnerability profile show that Western plains, Northern plains, and central highlands of the arid and semi-arid agro-ecological zones are the most vulnerable regions in the current scenario (1950–2000). In the future scenario (2050), it extends along districts falling within Deccan plateau and Central (Malwa) highlands, lying in the arid and semi-arid zones, along with regions vulnerable in the current scenario, recording the highest vulnerability score across all exposure scenarios. These regions exhibit highest degree of variation in climatic parameters, ecological fragility, socio-economic marginality, and limited accessibility to resources, generating conditions of high vulnerability. The study emphasizes on the priority to take up adaptive management actions in the identified vulnerable districts to not only reduce risks of climate change, but also enhance their inherent capacity to withstand any future changes in climate. It provides a systematic approach to explicitly identify vulnerable regions, where regional planners and policy makers can build on existing adaptation decision-making by utilizing an interdisciplinary approach in the context of global change scenario.     

Impacts of climate variability and changes on domestic water use in the Yellow River Basin of China

We present a methodology for using a domestic water use time series that were obtained from Yellow River Conservancy Commission, together with the climatic records from the National Climate Center of China to evaluate the effects of climate variability on water use in the Yellow River Basin. A suit of seven Global Circulation Models (GCMs) were adopted to anticipate future climate patterns in the Yellow River. The historical records showed evidences of rises in temperature and subsequent rises in domestic water demand in the basin. For Upstream of Longyangxia region, the impact was the least, with only 0.0021?×?10⁸ m³ for a temperature increase of 1 °C; while for Longyangxia-Lanzhou region, domestic water use was found to increase to 0.18?×?10⁸ m³ when temperature increases 1 °C. Downstream of Huayuankou was the region with the most changes in temperature that gave the highest increase of 1.95?×?10⁸ m³ in domestic water demand for 1 °C of change of temperature. Downstream of Huayuankou was identified as the most vulnerable area, where domestic water demand increases nearly by 42.2 % with 1 °C increase of temperature. Judging from the trends of temperature range, we concluded that future temperature in Yellow River Basin has an increasing tendency. This could worsen the existing issues of domestic water demand and even more to trigger high competition among different water-using sectors.     

An Analysis of Spatial Clustering and Implications for Wildlife Management: A Burrowing Owl Example

Analysis tools that combine large spatial and temporal scales are necessary for efficient management of wildlife species, such as the burrowing owl (Athene cunicularia). We assessed the ability of Ripley’s K-function analysis integrated into a geographic information system (GIS) to determine changes in burrowing owl nest clustering over two years at NASA Ames Research Center. Specifically, we used these tools to detect changes in spatial and temporal nest clustering before, during, and after conducting management by mowing to maintain low vegetation height at nest burrows. We found that the scale and timing of owl nest clustering matched the scale and timing of our conservation management actions over a short time frame. While this study could not determine a causal link between mowing and nest clustering, we did find that Ripley’s K and GIS were effective in detecting owl nest clustering and show promise for future conservation uses.     

Energy use,blue water footprint,and greenhouse gas emissions for current food consumption patterns and dietary recommendations in the US

This article measures the changes in energy use, blue water footprint, and greenhouse gas (GHG) emissions associated with shifting from current US food consumption patterns to three dietary scenarios, which are based, in part, on the 2010 USDA Dietary Guidelines (US Department of Agriculture and US Department of Health and Human Services in Dietary Guidelines for Americans, 2010, 7th edn, US Government Printing Office, Washington, 2010). Amidst the current overweight and obesity epidemic in the USA, the Dietary Guidelines provide food and beverage recommendations that are intended to help individuals achieve and maintain healthy weight. The three dietary scenarios we examine include (1) reducing Caloric intake levels to achieve “normal” weight without shifting food mix, (2) switching current food mix to USDA recommended food patterns, without reducing Caloric intake, and (3) reducing Caloric intake levels and shifting current food mix to USDA recommended food patterns, which support healthy weight. This study finds that shifting from the current US diet to dietary Scenario 1 decreases energy use, blue water footprint, and GHG emissions by around 9 %, while shifting to dietary Scenario 2 increases energy use by 43 %, blue water footprint by 16 %, and GHG emissions by 11 %. Shifting to dietary Scenario 3, which accounts for both reduced Caloric intake and a shift to the USDA recommended food mix, increases energy use by 38 %, blue water footprint by 10 %, and GHG emissions by 6 %. These perhaps counterintuitive results are primarily due to USDA recommendations for greater Caloric intake of fruits, vegetables, dairy, and fish/seafood, which have relatively high resource use and emissions per Calorie.     

Drinking water risk assessment in practice: the case of Swedish drinking water producers at risk from floods

To achieve a safe and reliable drinking water supply, water producers need to manage a large range of risks regarding both water quality and quantity. A risk management approach where risks are systematically identified and handled in a preventive manner is promoted by the World Health Organization and supported by researchers and drinking water experts worldwide. Risk assessment is an important part of such a management approach, and a variety of tools for risk assessment are described in the literature. There is, however, little knowledge of how drinking water risk assessment is performed in practice, including which tools that are actually used. This study investigates the use of risk assessment tools, and the approach to risk management, on a local level in the Swedish water sector. It is based on interviews with key persons from a targeted selection of water producers. We find that the application of tools as well as the approach to risk assessment and management differs considerably between the water producers. The tools most frequently used are mainly the ones promoted or required by Swedish national organizations. Although many of the water producers have done some kind of risk assessment, most have not implemented a risk management approach. Furthermore, their knowledge of the concepts of risk and risk management is often limited. The largest challenge identified is to prioritize risk assessment, so that it is actually performed and then used as a basis for managing risk in a systematic way.     

An improvement selection methodology for key performance indicators

Key performance indicators (KPIs) are critical measures for determining the health of a manufacturing plant in relationship to the plant’s goals. In today’s competitive environment, manufacturers cannot be careless about their business; in fact, they must ensure that their KPIs are effective and use them to make improvements when necessary. This paper describes a method for suggesting improvements to a manufacturer’s KPIs, based on the results achieved from a workshop to score the KPI on a number of predefined criteria. The approach uses a prospect theory approach to weight the scoring. Different problem formulations were derived that allow for both recommendations for improvements and the recommendations for disinvestments to over-performing KPIs. The authors applied the developed approach to two workshop outputs, each from independent manufacturers, and the results highlighted the significant difference between the two manufacturers in terms of improvement priorities and KPI assessment. The optimal improvement suggestions were compared to those found through a fast heuristic. It was determined that given the underlying assumptions of the approach that the heuristic solutions were just as adequate as the optimal ones.     

Heat wave vulnerability and exposure mapping for Osaka City,Japan

Heat waves and heat-related stresses are increasing environmental concerns in urban areas. The impact of heat waves is dependent on the intensity and duration of each event and on underlying environmental and socio-demographic factors which influence population vulnerability. In order to develop effective adaptation strategies, it is important to develop a method to clearly identify the most vulnerable areas based on these factors. The purpose of this study is to develop and map a heat wave vulnerability index combined with heat exposure analysis to identify areas where interventions can be targeted. The vulnerability index was derived from a principle component analysis of eight key variables that influence heat wave vulnerability. Eight proxy measures of vulnerability were obtained from 2010 census and land-use data for the 1904 census districts of Osaka City. Three principle components explained >77 % of the variance (age, employment and education; social isolation; density and lack of green space). The components were combined and weighted to produce a vulnerability score for each census district. The vulnerability scores ranged from 0 to 106, were categorised into eight vulnerability levels and were overlaid with fine-scale air temperature observations. The resulting output identified the distribution of population vulnerability and exposure. This assessment of vulnerability, combining exposure and sensitivity components, can provide precedent for efficient, targeted action to be taken to reduce the impact of heat waves at present and under climate change.     

Think Global,Buy National: CSR,Cooperatives and Consumer Concerns in the Norwegian Food Value Chain

In a world where issues of food safety and food security are increasingly important, the social responsibility of central actors in the food chain—producers and the main grocery chains—becomes more pressing. As a response, these actors move from implicitly assuming social responsibilities implied in laws, regulations and ethical customs, towards explicitly expressing social responsibilities. In this paper, we discuss the ethical values relevant for the social responsibility of central food producers and retailers in Norway, one of the most subsidized and protected areas of food production in the world. How do the actors perceive and express their social responsibility, and—given their position in the local, national and global market—how should they handle these responsibilities? We analyze Tine and Nortura, two producers owned by farmer cooperatives with market regulator function, as well as Coop—a dominant grocery chain in Norway, with basis in the same public ownership model as the farmer-owned cooperative producers. While the complex roles of these key actors in the Norwegian food market have been criticized from several angles, we argue that these multifaceted roles put them in a good position to promote informed consumer choices in a globalized market.     

Choosing rewarding flowers; perceptual limitations and innate preferences influence decision making in bumblebees and honeybees

Flowers exhibit great intra-specific variation in the rewards they offer. At any one time, a significant proportion of flowers often contain little or no reward. Hence, foraging profitably for floral rewards is problematic and any ability to discriminate between flowers and avoid those that are less rewarding will confer great advantages. In this study, we examine discrimination by foraging bees among flowers of nasturtium, Tropaeolum majus. Bee visitors included carpenter bees, Xylocopa violacea, which were primary nectar robbers; honeybees, Apis mellifera, which either acted as secondary nectar robbers or gathered pollen legitimately and bumblebees, Bombus hortorum, which were the only bees able to gather nectar legitimately. Many flowers were damaged by phytophagous insects. Nectar volume was markedly lower in flowers with damaged petals (which were also likely to be older) and in flowers that had nectar-robbing holes. We test whether bees exhibit selectivity with regards to the individual flowers, which they approach and enter, and whether this selectivity enhances foraging efficiency. The flowers approached (within 2 cm) by A. mellifera and B. hortorum were non-random when compared to the floral population; both species selectively approached un-blemished flowers. They both approached more yellow flowers than would be expected by chance, presumably a reflection of innate colour preferences, for nectar standing crop did not vary according to flower colour. Bees were also more likely to accept (land on) un-blemished flowers. A. mellifera gathering nectar exhibited selectivity with regards to the presence of robbing holes, being more likely to land on robbed flowers (they are not able to feed on un-robbed flowers). That they frequently approached un-robbed flowers suggests that they are not able to detect robbing holes at long-range, so that foraging efficiency may be limited by visual acuity. Nevertheless, by using a combination of long-range and short-range selectivity, nectar-gathering A. mellifera and B. hortorum greatly increased the average reward from the flowers on which they landed (by 68% and 48%, respectively) compared to the average standing crop in the flower population. Overall, our results demonstrate that bees use obvious floral cues (colour and petal blemishes) at long-range, but can switch to using more subtle cues (robbing holes) at close range. They also make many mistakes and some cues used do not correlate with floral rewards.