Determination of 15 phthalate esters in air by gas-phase and particle-phase simultaneous sampling

Based on previous research, the sampling and analysis methods for phthalate esters (PAEs) were improved by increasing the sampling flow of indoor air from 1 to 4 L/min, shortening the sampling duration from 8 to 2 hr. Meanwhile, through the optimization of chromatographic conditions, the concentrations of 9 additional PAE pollutants in indoor air were measured. The optimized chromatographic conditions required a similar amount of time for analysis as before, but gave high responsivity, the capability of simultaneously distinguishing 15 kinds of PAEs, and a high level of discrimination between individual sample peaks, as well as stable peak generation. The recovery rate of all gas-phase and particle-phase samples of the 15 kinds of PAEs ranged from 91.26% to 109.42%, meeting the quantitative analysis requirements for indoor and outdoor air sampling and analysis. For the first time, investigation of the concentration levels as well as characteristics of 15 kinds of PAEs in the indoor air from four different traffic micro-environments (private vehicles, busses, taxis and subways) was carried out, along with validation of the optimized sampling and analytical method. The results show that all the 9 additional PAEs could be detected at relatively high pollution levels in the indoor air from the four traffic micro-environments. As none of the pollution levels of the 15 kinds of PAEs in the indoor air from the 4 traffic micro-environments should be neglected, it is of great significance to increase the types of PAEs able to be detected in indoor air.     

Quantifying public health benefits of environmental strategy of PM2.5 air quality management in Beijing–Tianjin–Hebei region, China

In 2013,China issued "Air Pollution Prevention and Control Action Plan(Action Plan)" to improve air quality.To assess the benefits of this program in Beijing-Tianjin-Hebei(BTH)region,where the density of population and emissions vary greatly,we simulated the air quality benefit based on Ben MAP to satisfy the Action Plan.In this study,we estimate PM_(2.5) concentration using Voronoi spatial interpolation method on a grid with a spatial resolution of 1 × 1 km~2.Combined with the exposure-response function between PM_(2.5) concentration and health endpoints,health effects of PM_(2.5) exposure are analyzed.The economic loss is assessed by using the willingness to pay(WTP) method and human capital(HC) method.When the PM_(2.5) concentration falls by 25% in BTH and reached 60 μg/m~3 in Beijing,the avoiding deaths will be in the range of 3175 to 14051 based on different functions each year.Of the estimated mortality attributable to all causes,3117 annual deaths were due to lung cancer,1924 – 6318 annual deaths were due to cardiovascular,and343 – 1697 annual deaths were due to respiratory.Based on WTP,the estimated monetary values for the avoided cases of all cause mortality,cardiovascular mortality,respiratory mortality and lung cancer ranged from 1110 to 29632,673 to 13325,120 to 3579,1091 to 6574 million yuan,respectively.Based on HC,the corresponding values for the avoided cases of these four mortalities were 267 to 1178,161 to 529,29 to 143 and 261 million yuan,respectively.     

Predicting vehicle fuel consumption patterns using floating vehicle data

The status of energy consumption and air pollution in China is serious. It is important to analyze and predict the different fuel consumption of various types of vehicles under different influence factors. In order to fully describe the relationship between fuel consumption and the impact factors, massive amounts of floating vehicle data were used. The fuel consumption pattern and congestion pattern based on large samples of historical floating vehicle data were explored, drivers'' information and vehicles'' parameters from different group classification were probed, and the average velocity and average fuel consumption in the temporal dimension and spatial dimension were analyzed respectively. The fuel consumption forecasting model was established by using a Back Propagation Neural Network. Part of the sample set was used to train the forecasting model and the remaining part of the sample set was used as input to the forecasting model.     

闲置厌氧氨氧化微生物的启动及微生物分析

文章以闲置12个月的厌氧氨氧化生物膜填料重新启动厌氧氨氧化反应器,并对反应器的活性恢复情况、脱氮效果和微生物菌群结构开展研究。实验结果表明:在启动的200 d逐渐将进水氨氮、亚硝态氮浓度从50 mg/L提高到70 mg/L,水力停留时间从12 h缩短到4 h,后期氨氮去除率达80%以上,亚硝酸盐去除率达95%。170~200 d的稳定期中,平均去除负荷0.71±0.15 kg/(m~3·d)。另外,通过高通量测序技术对反应器中微生物群落变化情况进行了系统分析。启动过程中填料中污泥微生物浮霉菌门Planctomyctes的相对丰度从13.7%增长到了36.0%,成为优势菌群。     

烟草废弃物快速堆肥过程中重金属Cd形态变化特征

以烟草废弃物为原料,活性土壤为载体建立堆体,研究重金属镉的形态变化,及堆肥过程中的动态变化规律。结果表明,烟草废弃物与活性土壤混合能快速腐熟。堆肥总质量下降,重金属镉含量相对增加。重金属镉的铁锰氧化态比例增加19%,有机结合态比例在堆肥升温阶段增加,腐熟后有所下降。残渣态比例大幅度上升,增加达到5倍,且在腐熟阶段增幅最大。说明堆肥处理有利于降低重金属镉的活性。     

Evaluating the technical efficiencies of fishing vessels to achieve effective management of overexploited fisheries

Global marine capture fisheries are undergoing serious stress, with overfishing as one of the major problems. In order to mitigate the overexploitation of capture fisheries, government regulation or fisheries management is necessary. Among various management approaches, vessel quantity control is being widely employed. To achieve effective governance of fisheries, the technical efficiency (TE) issue needs to be considered in the implementation of vessel quantity control. Using the Pacific saury (Cololabis saira) stick-held dip net fishery in Japan as a case study, this paper estimated the TE of sampled fishing vessels and explored the possible factors affecting the gap in efficiency. This paper aims to provide suggestions for a better implementation of vessel quantity control in global Pacific saury fishery, and also to serve as an empirical example of integrating TE analysis into management of overexploited fisheries for achieving satisfactory effects. Results show the TE score of the sampled fishery averaged around 0.7 from 2009 to 2014, and factors concerning owners/skippers’ motivation such as vessel ownership and specialization, vessel tonnage as well as skippers’ age show positive effects on the TE. Our findings in the present work provide important strategies for mitigating overexploitation in fisheries. Conducting technical efficiency analysis of targeted fisheries is a vital issue to be considered for designing and realizing an effective implementation of fisheries management approaches. The large vessels and the enthusiasm of vessel owners/skippers need to be particularly addressed when vessel quantity limit is considered to mitigate the problem of overfishing.     

Assessment of inherent vulnerability of forests at landscape level: a case study from Western Ghats in India

Assessment of vulnerability is an important step in building long-term resilience in the forestry sector. The objective of this paper is to present a methodological approach to assess inherent vulnerability of forests at landscape level. The approach involves use of vulnerability indicators, the pairwise comparison method, and geographic information system (GIS) tools. We apply this approach to assess the inherent vulnerability of forests of the Western Ghats Karnataka (WGK) landscape, which is a part of the Western Ghats biodiversity hotspot in India. Four vulnerability indicators, namely biological richness, disturbance index, canopy cover, and slope, are selected. We find that forests in 30, 36, 19, and 15 % grid points in this region show low, medium, high, and very high inherent vulnerability, respectively. The forest showing high and very high inherent vulnerability are mostly dry deciduous forests and plantations located largely on the eastern side of the landscape. We also find that canopy cover is one of the key indicators that determine the inherent vulnerability of forests, and natural forests are inherently less vulnerable than man-made plantations. Spatial assessment of inherent vulnerability of forests at landscape level is particularly useful for developing strategies to build resilience to current stressors and climate change in future.     

Climate change implications for the nest site selection process and subsequent hatching success of a green turtle population

Sandy beach habitat where sea turtles nest will be affected by multiple climate change impacts. Before these impacts occur, knowledge of how nest site selection and hatching success vary with beach microhabitats is needed to inform managers on how to protect suitable habitats and prepare for scientifically valid mitigation measures at beaches around the world. At a highly successful green turtle (Chelonia mydas) rookery at Akumal, Quintana Roo, Mexico, we measured microhabitat characteristics along the beach crawl (rejected sites) and related nest site conditions (selected sites) to subsequent hatching success rates for 64 nesting events. To our knowledge, this is the first study to report environmental data along the nesting crawl for a green turtle population and the first to use natural breaks in the data to describe their preferred habitat ranges. Our results indicate that turtles were likely using a combination of cues to find nest sites, mainly higher elevations and lower sand surface temperatures (Kruskal-Wallis test, H?=?19.84, p?<?0.001; H?=?10.78, p?<?0.001). Hatching success was significantly and negatively correlated to sand temperature at cloaca depth (Spearman’s ρ?=??0.27, p?=?0.04). Indeed, the preferred range for cloaca sand temperatures at the nest site (26.3–27.5 °C) had significantly higher hatching success rates compared to the highest temperature range (Tukey HSD?=?0.47, p?=?0.05). Sand temperatures at various depths were intercorrelated, and surface and cloaca depth sand temperatures were correlated to air temperature (ρ?=?0.70, p?=?0.00; ρ?=?0.26, p?=?0.04). Therefore, rising air temperatures could alter sand temperature cues for suitable nest sites, preferred nest site ranges, and produce uneven sex ratios or lethal incubating temperatures. Elevation cues and preferred ranges (1.4–2.5 m) may also be affected by sea level rise, risking inundation of nests.     

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.     

Identification of structural breaks in the forest product markets: how sensitive are to changes in the Nordic region?

Forests play a fundamental role in the global carbon cycle and can be managed to mitigate greenhouse gas emissions and conserve or sequester carbon. Global policy and environmental changes can affect regional consumption of forest products, as well as inter-regional trade of forest goods and services. This study analyzes global and regional change impacts on the production, consumption and trade of forest products in two Nordic countries, Finland and Sweden. Annual data on removal and trade (1964–2012) for roundwood and sawnwood is used to identify structural breaks based on Chow tests. According to the analysis, the time period is divided into two periods: t1 (1964–1980) and t2 (1981–2012). In the first period, breaks occurred in 1975 and 1976 in the Finnish model and no break is found in the Swedish model. In the second period, we identify breaks in 1991 and 1992 for the Finnish model and in 2004, 2005 and 2006 for the Swedish model. Although our findings have broad empirical support, we do not identify any specific incident as a direct cause of the changes in the consumption and trade patterns of the two types of wood in these countries. The models and analysis presented here can serve as methodological tools for policymakers to better understand the effects of structural changes in the production of forest goods and services in the Nordic region and globally.