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Abstract. The predictive analysis of natural disasters and their consequences is challenging because of uncertainties and incomplete data. The present article studies the use of variable fuzzy sets (VFS) and improved information diffusion method (IIDM) to construct a composite method. The proposed method aims to integrate multiple factors and quantification of uncertainties within a consistent system for catastrophic risk assessment. The fuzzy methodology is proposed in the area of flood disaster risk assessment to improve probability estimation. The purpose of the current study is to establish a fuzzy model to evaluate flood risk with incomplete data sets. The results of the example indicate that the methodology is effective and practical; thus, it has the potential to forecast the flood risk in flood risk management.

In the current global environmental problems, reducing CO2 emissions is an important goal and guide for countries all over the world in developing environmental and economic policies. It has become a global consensus to jointly promote greenhouse gas emission reduction. From 1970 to 2004, CO2 emissions increased yearly, accounting for 76% of the total emissions in 2004. According to the prediction of the International Energy Agency (IEA), the total global CO2 emission reached a record of 30 billion tons in 2010. In 2005, the Intergovernmental Panel on Climate Change (IPCC) specially recommended Carbon Capture and Storage (CCS) technology to achieve significant emission reduction of greenhouse gases. In 2007, the World Wide Fund for Nature (WWF) identified CCS as one of the six ways to deal with global climate change. The global climate conference in Cancun in 2010 incorporated CCS into the Clean Development Mechanism (CDM). The United States, Canada, the European Union, and other countries have taken CCS as an important part of future energy strategies and carbon emission reduction strategies and have formulated corresponding technology research plans that include Research and Development (R&D) and project demonstration. The NET-Zero Emissions (NZE) scenario proposed by the IEA for 2050 puts global CO2 capture at 1.7 gigatonnes per year in 2030 and 7.6 gigatonnes per year in 2050. Presently, CCS is a hot topic all around the world.

Carbon dioxide emissions from urban road traffic mainly come from automobile exhaust. However, the carbon dioxide emissions obtained by the instruments are unreliable due to time delay error. In order to improve the reliability of data, we propose a method to correct the measured vehicles' carbon dioxide emissions from instrument based on the CMEM model. Firstly, the synthetic time series of carbon dioxide emissions are simulated by CMEM model and GPS velocity data. Then, taking the simulation data as the control group, the time delay error of the measured carbon dioxide emissions can be estimated by the asynchronous correlation analysis, and the outliers can be automatically identified and corrected using the principle of DTW algorithm. Taking the taxi trajectory data of Wuhan as an example, the results show that (1) the correlation coefficient between the measured data and the control group data can be improved from 0.52 to 0.59 by mitigating the systematic time delay error. Furthermore, by adjusting the outliers which account for 4.73 % of the total data, the correlation coefficient can raise to 0.63, which suggests strong correlation. The construction of low carbon traffic has become the focus of the local government. In order to respond to the slogan of energy saving and emission reduction, the distribution of carbon emissions from motor vehicle exhaust emission was studied. So our corrected data can be used to make further air quality analysis.

Carbon dioxide emissions from urban road traffic mainly come from automobile exhaust. However, the carbon dioxide emissions obtained by the instruments are unreliable due to time delay error. In order to improve the reliability of data, we propose a method to correct the measured vehicles' carbon dioxide emissions from instrument based on the CMEM model. Firstly, the synthetic time series of carbon dioxide emissions are simulated by CMEM model and GPS velocity data. Then, taking the simulation data as the control group, the time delay error of the measured carbon dioxide emissions can be estimated by the asynchronous correlation analysis, and the outliers can be automatically identified and corrected using the principle of DTW algorithm. Taking the taxi trajectory data of Wuhan as an example, the results show that (1) the correlation coefficient between the measured data and the control group data can be improved from 0.52 to 0.59 by mitigating the systematic time delay error. Furthermore, by adjusting the outliers which account for 4.73 % of the total data, the correlation coefficient can raise to 0.63, which suggests strong correlation. The construction of low carbon traffic has become the focus of the local government. In order to respond to the slogan of energy saving and emission reduction, the distribution of carbon emissions from motor vehicle exhaust emission was studied. So our corrected data can be used to make further air quality analysis.

Abstract. We found the possible correlation between the precursory pattern of tidal triggering of earthquakes and the crustal heterogeneities, which is of particular importance to the researchers in earthquake prediction and earthquake hazard prevention. We investigated the connection between the tidal variations and earthquake occurrence in the Liyang, Wunansha, Cangshan, Wenan, Luquan and Yaoan regions of China. Most of the regions show a higher correlation with tidal triggering in several years preceding the large or destructive earthquakes compared to other times, indicating that the tidal triggering may inherently relate to the nucleation of the destructive earthquakes during this time. In addition, the analysis results indicate that the Liyang, Cangshan and Luquan regions, with stronger heterogeneity, show statistically significant effects of tidal triggering preceding the large or destructive earthquakes, while the Wunansha, Wenan and Yaoan regions, with relatively weak heterogeneity, show statistically insignificant effects of it, signifying that the precursory pattern of tidal triggering of earthquakes in these six regions is possibly related to the heterogeneities of the crustal rocks. The above results suggest that when people try to find the potential earthquake hazardous areas or make middle–long-term earthquake forecasting by means of precursory pattern of the tidal triggering, the crustal heterogeneity in these areas has to be taken into consideration for the purpose of increasing the prediction efficiency. If they do not consider the influence of crustal heterogeneity on the tidal triggering of earthquakes, the prediction efficiency might greatly decrease.

Research on congressional leadership has been dominated in recent decades by contextual interpretations that see leaders' behavior as best explained by the environment in which they seek to exercise leadership—particularly, the preference homogeneity and size of their party caucus. The role of agency is thus discounted, and leaders' personal characteristics and leadership styles are underplayed. Focusing specifically on the speakers of the U.S. House of Representatives from the first to the 110th Congress, we construct measures of each speaker's commitment to comity and leadership assertiveness. We find the scores reliable and then test the extent to which a speaker's style is the product of both political context and personal characteristics. Regression estimates on speakers' personal assertiveness scores provide robust support for a context-plus-personal characteristics explanation, whereas estimates of their comity scores show that speakers' personal backgrounds trump context.

Abstract. We present a new method for inverting coseismic slip distribution based on arc measurements of InSAR interferograms. The method only solves the integer ambiguities on the selected arcs so that the challenging task from global unwrapping of low coherence interferograms can be avoided. The simulated experiment results show that the new method recovered the given slip distribution well at different coherence quality levels. However, the conventional method with global interferogram unwrapping fails when the interferogram has some isolated areas. In addition, the new method is capable of using surface rupture offset data gathered in the field. We apply the proposed method to study the 2010 Yushu, China Ms 7.1 earthquake. Inclusion of field data can help to enhance the results of fault slip inversion. It derives a maximum slip of ∼3 m, larger than the published coseismic slip results on this event, but agreeing with the largest offset of 3.2 m from field investigation.

We employ a regression discontinuity (RD) design to estimate the impact of air pollution on house prices across a river that demarcates regions with and without coal-fired heating resulting from the Huai River Policy. This policy was decreed by the Chinese government in the 1950s and mandated the burning of coal for indoor heating at subsidised prices north of the Huai River. Employing quasi-experimental variation in particulate matter of 10 micrometres or less in aerodynamic diameter (PM10) generated by this arbitrary policy and a regression discontinuity (RD) design based on distance from Huai River, we estimate the local average treatment effect (LATE) to provide new evidence on the capitalisation of PM10 air pollution into house values. By using panel data covering 30 large cities on either side of the river for the period 2006–2015, we found that 1 µg/m3 (micrograms per cubic metre) reduction in average PM10 is associated with an approximately 1% increase in house prices. The results are robust to using parametric and nonparametric estimation methods, adjustment to a rich set of covariates, and using a subsample excluding first-tier cities.

China has developed a new oil crop, micro-endosperm ultra-high oil corn, approved by the government in 2011 and named Huajian No. 1 (HJ-1). This study analyzed the nutrients in HJ-1 cold-pressed whole-seed oil, their composition and contents in tocopherols, fatty acids, and phytosterols and compares them with those of seven selected vegetable oils. HJ-1 oil contained α-, β-, γ-, and δ-tocopherol, with contents of 433.25 ± 0.13, 26.27 ± 0.08, 570.69 ± 0.27, and 38.41 ± 0.005 mg/kg, respectively, the highest nutritional values among the vegetable oils studied, except for soybean and palm oils. Gas chromatography was used for fatty acid analysis and seven were detected, with the main ones being palmitic, oleic, and linoleic acids. In HJ-1, the ratio of oleic to linoleic acid was close to 1:1, and b-sitosterol, campesterol, and stigmasterol were present with contents of 254.20 ± 0.11, 108.91 ± 0.19, and 105.67 ± 0.58 mg/kg, respectively. ; China ha desarrollado un nuevo cultivo de aceite, el de micro-endospermo de maíz ultra alto, aprobado por el gobierno en 2011 y denominado Huajian No. 1 (HJ-1). Este estudio analizó los nutrientes en el aceite de semilla entera prensada en frío HJ-1: su composición y contenido de tocoferoles, ácidos grasos y fitoesteroles y los compara con los de siete aceites vegetales seleccionados. El aceite HJ-1 contenía α-, β-, γ-, y δ-tocoferol, con un contenido de 433,25 ± 0,13, 26,27 ± 0,08, 570,69 ± 0,27, y 38,41 ± 0,005 mg/kg, respectivamente, los valores nutricionales más altos entre los aceites vegetales estudiados, excepto aceites de soja y palma. La cromatografía de gases se utilizó para el análisis de ácidos grasos: se detectaron siete, los principales fueron los ácidos palmítico, oleico y linoleico. En HJ-1, la proporción de ácido oleico a linoleico fue cercana a 1:1, y β-sitosterol, campesterol y estigmasterol estaban presentes con contenidos de 254,20 ± 0,11, 108,91 ± 0,19 y 105,67 ± 0,58 mg/kg, respectivamente.

Recent studies have demonstrated that solar heat has a critical role to play in providing heat for industrial processes. In the present work, the thermal performance of a novel low profile concentrating solar thermal collector as a means to replace gas usage by mounting it on the rooftop of factories is investigated. The proposed collector incorporates an internal linear tracking system that concentrates beam radiation during a large part of a sunny day without external or rotational motion. The configuration presented here is suitable for an industrial metal process heating (drying and cleaning) application. In this paper, the annual behavior of the collector has been simulated for this application with TRNSYS (Transient System Simulation Tool) software in order to study its performance and economic feasibility. The annual solar fraction and economic metrics were used as selection criteria among design options (e.g. varying the solar array, storage tank sizes, and control methods). Assuming a constant thermal load of 260 kWh per day, the optimal total area of the collectors was calculated to be 200 m² for this application. Overall, the results show that, for the meteorological data of Sydney, the proposed concentrating collector can reach a solar fraction of 53%, while achieving positive economic returns. A preliminary economic analysis of this system indicates that a government subsidy of 50% of the capital equipment will reduce the payback period to 11 years. Due to the fact that solar-derived industrial heat production is an emerging market, further research and economies of scale could potentially be expected to drastically improve the economic viability of these types of systems going forward.