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In response to the recent development of ear corn feeding systems and the shortage of bulking agents for manure composting in the Hokkaido region, the plausibility of using corn stover (a residue of ear corn harvesting) as an alternative bulking agent for dairy manure composting was tested. The temperature profile, quality of the final product, and greenhouse gas emissions were evaluated and compared with the values obtained from manure that used wheat straw, a typical bulking agent. A sufficiently high temperature profile (>70°C) and active organic matter degradation were achieved by mixing in corn stover. After active organic matter degradation for 8 weeks, CO2 production was significantly lower and the stable final products were obtained. The total solids level increased significantly, to 48.8–50.4%, while the C/N ratio dropped significantly, from 19.9–21.8 to 11.2–12.8. Methane emission from the corn-stover-based pile was 0.36% of initial volatile solids, while nitrous oxide emission was 0.58% of initial N, proving that the use of corn stover can mitigate greenhouse gas emission and that its mitigating effect was comparable to those of other bulking agents. Together, the results showed that the use of corn stover can be a suitable alternative bulking agent for dairy manure composting and can serve as part of an ecologically friendly and “circular” method of dairy farming.

There are large amounts of waste activated sludge (WAS) and kitchen waste (KW) produced every year in China. It has been confirmed that anaerobic co-digestion is an effective method to solve this problem. The targets of the present study were optimizing the digestive performances and clearing of the mechanism of bentonite addition by adding bentonite into digestive system. Group M (WAS: KW = 1:2, based on VS) presented higher cumulative methane yield (CMY), where the CMY increased from 19.8 to 36.3 mL/g VS with the bentonite dosage from 0 to 2 g/g VS. After bentonite addition, the lag phase of every digester presented an obvious decrease from 15.1 to 1.4 d. Furthermore, and the moderating effects on microbial community by bentonite. The addition of bentonite improved methane production, and it can also reduce the lag phase of methane production in co-digestion. What's more, bentonite addition increased the speed of pH recovery from 4.2-4.8 to normal level (7.0-8.0) and thus enhanced the system stability. The conclusion of this study can be used to guide practical engineering.

An electrochemically activated solution (ECAS), generated by electrolysis of a dilute sodium chloride solution in a four-chamber electrolytic cell (Ecas4), was tested as a sanitising aerosol in eliminating bacteria from the environment of a weaning room vacated 24-48h earlier, at a continuous flow pig farm. An ultrasonic humidifier was used to fill the environment with a fog (droplets with diameters of 1–5 μm) containing 0.25 ppm of hypochlorous acid. The weaning room was fogged for 3 min at 30 min intervals during five hours of aerosol disinfection. An innovative sample treatment with propidium monoazide dye in conjunction with cyclonic air sampling was optimised and adapted for discerning live/dead bacteria in subsequent molecular quantification steps. Without fogging, total bacterial load ranged from 5.06 ± 0.04 to 5.75 ± 0.04 Log10 CFU/m3. After the first hour of fogging, a 78% total bacterial reduction was observed, which further increased to > 97% after the second hour, > 99.4% after the third and 99.8% after the fourth hour, finally resulting in a 99.99% reduction from the farm environment over five hours. Unlike the current formaldehyde spray disinfection protocol, which requires a long empty period because of its hazardous properties, this economically viable and environmentally friendly disinfection protocol may significantly lower downtime. Moreover, ECAS fogging can be easily adapted to a variety of applications, including the elimination of pathogens from livestock farm air environment for disease prevention, as well as decontamination after disease outbreaks. Refereed/Peer-reviewed

This study aimed to establish a new methodology for upgrading biomass quality using low-temperature (below 100 degrees C) oxidation to achieve simultaneous drying and decomposition. Sterilized manure (63% wet basis) was heated at 90 degrees C for 49 days under an oxidative environment. The obtained solid and moisture reduction curves indicated that drying and decomposition proceeded simultaneously. The biomass was decomposed by oxidation with the release of water, carbon dioxide, and volatile fatty acids such as acetic acid. The oxidation process stopped when the biomass was dehydrated, indicating that the water originally present in the biomass governed the process. Elemental and calorific analyses revealed no remarkable increase in carbon content or increased heating value, and a slight decrease in oxygen content. Although the severity of the process was insufficient to produce an optimum solid fuel due to the low temperature used, the process would enable the stabilization of waste biomass with low energy consumption such as using waste heat.

Sugarcane bagasse is a vast lignocellulosic byproduct generated in the industry with ~50% humidity (1 kg dry matter associated with 1 kg water). Although the presence of water brings deleterious consequences for combustion, storage and sugar extraction, the location of water in fresh bagasse remains unknown. In this work, we use synchrotron X-ray microtomography for non-invasive 3D imaging of fresh bagasse particles, which allows the visualization of intraparticle water. The sclerified fiber cells in the sheaths surrounding xylem vessels are often found full of water. We suggest this can be juice preserved from the native stalks as many sclerified fibers seem to keep their structural integrity despite the mechanical action during sugarcane crushing. The microtomograms of fresh bagasse also shows mineral particles adhered to biomass surfaces, with adhesion presumably favored by the presence of water. In summary, this work unveils the location of water in fresh bagasse, solving an old mystery of sugarcane technology.

Although there are a variety of commercially available biological and chemical treatments for removal of hydrogen sulfide (H2S) from biogas, managing biogas H2S remains a significant challenge for agricultural digesters where labor and operational funds are very limited compared to municipal and industrial digesters. The objectives of this study were to evaluate headspace aeration for reducing H2S levels in low cost plug flow digesters and to characterize the relationship between the liquid surface area and H2S oxidation rates. Experiments with replicate field scale plug flow digesters showed that H2S levels decreased from 3500 ppmv to

Background The progress of green credit in China is accelerating, but its development is uneven and insufficient in different regions. And whether the issuance of green credit can effectively promote the improvement of the environment and economy is not well understood. Objective Previous research has found that green credit promotes economic growth through improvement of the industrial structure and green technological innovation. However, these studies have not considered the positive externality of environmental improvement even though environmental improvement and economic growth are requirements of the sustainable development concept. Methods We use the chain-mediated model to estimate the impact of green credit issuance on the economic growth of different provinces since the large-scale implementation of green credit in China with data from 2008 to 2016. Results and conclusion This paper shows that the issuance of green credit can improve labor supply rather than labor productivity through the improvement of air quality to achieve regional economic growth. Such a chain-mediated path is different from the economic growth caused by industrial structural adjustment and green technology innovation. At the national level, every 1% increase in green credit issuance relative to industrial loans will increase the per capita gross domestic product (GDP) by approximately 4.6 yuan, or 0.012%, through air quality and labor supply, accounting for 2.875% of the total effect. Heterogeneity analysis indicates that due to regional industrial structure differences and diminishing marginal effects, the impact of green credit is stronger in the western region than in the eastern and central regions. For every 1% increase in the proportion of green credit issuance relative to industrial loans, the per capita GDP growth achieved through the chain-mediated path is approximately 30.17 yuan in the western region, approximately 6.6 times greater than that at the national level. Within a 95% confidence interval of 5000 bootstrap samples, this path is found to be true, and the chain-mediated effect accounts for approximately 12.96% of the total indirect effect. Limitations The limitation of this paper is the measurement of green credit. Although green credit has a large volume, it remains underdeveloped, and there is a lack of perfect indicators. Most existing studies have adopted only alternative or reverse indicators to measure the issuance of green credit. For example, this paper takes the interest expenditure of six high-energy-consuming enterprises as the reverse indicator, which may to a certain extent lead to the overestimation of the issuance of green credit and its impact on the environment and economy. Future research can accurately explore the performance of green credit on the basis of its mature development.

A growing level of environmental awareness in societies has led to an increased interest in the odor nuisance. Residents’ complaints have ultimately revealed the need to develop adequate research methods that would ensure objective measurements, thus shedding more light on this complex problem. One of the possible ways to conduct an objective odor assessment is to use a sensory panel in the tests. This paper presents the procedure for selecting and training the sensory analysis team especially for the purposes of odor nuisance testing. Several useful suggestions for conducting studies that involve a sensory panel are also provided. This in turn can prove a useful tool, supplementing the EN 13725 standard within the scope of building and convening a sensory panel. In this paper a performance comparison of two sensory panels is also discussed: one that received a basic training of 20h, solely based on the guidelines of the EN 13725 standard and another, whose members completed an extended training of 60h, based on the standards and guidelines used in the field of sensory analysis. It has been shown that acquiring more knowledge and developing certain competences in the field of sensory analysis may contribute to an increase in the overall and individual precision of determinations as adequate sensory training improves the panel’s performance.

A study was conducted to assess the efficacy of ozone gas in inactivating spores of both Bacillus anthracis and Bacillus subtilis inoculated onto six building materials (glass, wood, carpet, laminate, galvanized metal, and wallboard paper). Testing conditions consisted of ozone gas concentrations ranging from 7,000-12,000 parts per million (ppm), contact times from 4 to 12 h, and two relative humidity (RH) levels of 75 and 85%. Results showed that increasing the ozone concentration, contact time, and RH generally increased decontamination efficacy. The materials in which the highest decontamination efficacy was achieved for B. anthracis spores were wallboard paper, carpet, and wood with ≥ 6 log10 reduction (LR) occurring with 9,800 ppm ozone, 85% RH, for 6 h. The laminate and galvanized metal materials were generally more difficult to decontaminate, requiring 12,000 ppm ozone, 85% RH, and 9-12 h contact time to achieve ≥6 LR of B. anthracis. Lastly, overall, there were no significant differences in decontamination efficacy between the two species.

To better understand the agricultural resources and environmental problems of the provinces along The Belt and Road in China, it is critical to investigate their agricultural carbon emission efficiency and evolutionary trends. Based on the panel data of 18 key provinces and cities between 2006 and 2015, this paper evaluated the agricultural carbon emission efficiency with the data envelopment analysis–Malmquist model and further explored their dynamic evolutionary trends. There were several main findings. First, the efficiency levels of agricultural carbon emissions showed significant regional differentiation among the areas, with that along the 21st-Century Maritime Silk Road being much higher than that along the Silk Road Economic Belt. Second, technical efficiency was the key factor that restricted the improvement of the comprehensive efficiency of agricultural carbon. Third, most provinces invested in too many redundant and unreasonably allocated resources, showing a trend of diminishing returns to scale. Last, According to dynamic evolution analysis, the total productivity still demonstrated a diminishing trend. This paper provides some suggestions for effectively improve the efficiency of agricultural carbon emissions in China, such as optimize the agricultural industrial structure, increasing the investment of carbon emission reduction technology, and implementing a carbon emission quota clearing system. This paper contributes to the improvement of the environment in China.

The paper presents a mapping tool aiming to identify and minimise potential conflicts between onshore wind energy development and wildlife conservation in Lithuania. It merges current information on the distribution, conservation status and sensitivity of birds and bats to wind power with an integrated evaluation of wind resources (modelled wind speed), special planning status and technical perspectives of wind energy development. The paper includes assessment of the selected wildlife species which were described as sensitive to wind power (69 breeding and 43 migratory bird species and 17 bat species bats in the country). Used species level information allowed the precise identification of sensitive territories and might be used to mitigate negative wind farm effects using special measures based on species behavior. Finally, we delivered overlaps as possible conflicts among the most promising wind farm areas and the areas with high sensitivity in relation to bird and bat distribution. These overlaps point to the required attention and relevant decisions that are needed to ensure sustainable development of wind energy throughout the country. We suggest this tool for initial determination of appropriate areas for wind energy development in the country and as supplement to Environmental Impact Assessment.

Eco-cities have witnessed rapid growth in these years worldwide. As the Eco-cities entering operation stage gradually, more and more researchers have found that users (who are living or working in the Eco-cities) satisfaction is one of the most important factors to determine the success or failure of Eco-cities. Therefore, it is very important to investigate the user demands to attract more citizens willing to live or work in the Eco-cities, which will make the development of Eco-cities more sustainable and solid. The recent researches on user demands investigation and analysis in the Eco-cities mainly focused on understanding the user need itself, yet lack of research on the relationship between the user demand and user satisfaction. This paper initially introduced the Kano model analysis method to the research field of user demands in Eco-city, to explore the relationship between the user demand and user satisfaction. After proposing user demands library in Eco-city (including Land use, Ecological environment, Green building, Energy utilization, etc.), the user demands classification and importance analysis methods of Eco-city were proposed based on Kano model. The questionnaire survey for users of two Eco-cities in China as case study was conducted, consisted of user demand items questionnaire based on the Kano model and a questionnaire on the importance of the user demand items. By utilizing the integration of quantitative analysis methods based on the Kano model and Analytic Hierarchy Process (AHP) method, the final ranking of user demands importance was obtained. Comparing with the existing literatures in terms of user demands research for Eco-city, the user demands analysis method based on Kano model of this paper, is able to reveal the influence degree of user satisfaction towards the facilities and services provided in the Eco-city. The user demands analysis method can be used for other researchers worldwide to investigate and quantitively analyze user demands according to their local development situation and preference of Eco-city. The user demands analysis results obtained through this method, can benefit different stages of Eco-city.

Dengue is an arbovirus affecting global populations. Frequent outbreaks occur, especially in equatorial cities such as Singapore, where year-round tropical climate, large daily influx of travelers and population density provide the ideal conditions for dengue to transmit. Little work has, however, quantified the peaks of dengue outbreaks, when health systems are likely to be most stretched. Nor have methods been developed to infer differences in exogenous factors which lead to the rise and fall of dengue case counts across extreme and non-extreme periods. In this paper, we developed time varying extreme mixture (tvEM) methods to account for the temporal dependence of dengue case counts across extreme and non-extreme periods. This approach permits inference of differences in climatic forcing across non-extreme and extreme periods of dengue case counts, quantification of their temporal dependence as well as estimation of thresholds with associated uncertainties to determine dengue case count extremities. Using tvEM, we found no evidence that weather affects dengue case counts in the near term for non-extreme periods, but that it has non-linear and mixed signals in influencing dengue through tvEM parameters in the extreme periods. Using the most appropriate tvEM specification, we found that a threshold at the 70th (95% credible interval 41.1, 83.8) quantile is optimal, with extreme events of 526.6, 1052.2 and 1183.6 weekly case counts expected at return periods of 5, 50 and 75 years. Weather parameters at a 1% scaled increase was found to decrease the long-run expected case counts, but larger increases would lead to a drastic expected rise from the baseline correspondingly. The tvEM approach can provide valuable inference on the extremes of time series, which in the case of infectious disease notifications, allows public health officials to understand the likely scale of outbreaks in the long run., Author summary Dengue is an arbovirus affecting populations across much of the globe. Frequent outbreaks occur, especially in equatorial cities such as Singapore, where the year-round tropical climate, large daily influx of travelers and population density provide the ideal conditions for dengue transmission. Little work has however quantified the peaks of dengue outbreaks, when health systems are likely to be most stretched. Nor have methods been developed to infer differences in exogenous factors which lead to the rise and fall of dengue case counts across extreme and non extreme periods. In this paper, we developed time varying extreme mixture (tvEM) methods to account for the temporal dependence of dengue case counts across extreme and non-extreme periods. tvEM is able to infer differences in climatic forcing across non-extreme and extreme periods of dengue case counts, their temporal dependence as well as estimate suitable thresholds with associated uncertainties to determine dengue case count extremities. Using tvEM, we found no evidence that weather affects dengue case counts in the near term for non extreme periods, but has non-linear and mixed signals in influencing dengue through tvEM parameters in the extreme periods. Using the most appropriate tvEM specification, we found that a high percentile threshold is estimated, with dengue outbreak events far larger than currently observed to be expected in 5, 50 and 75 years. Weather parameters at a 1% scaled increase was found to decrease the long-run expected case counts, but larger increases would lead to a drastic expected rise from the baseline correspondingly. tvEM can provide valuable inference on the extremes of time series, which in the case of infectious disease data, allows public health officials to understand factors and the likely scale of infectious disease outbreaks in the long run.

The overflow of the flame plume from the window is the main cause of the vertical spread of the fire on the facade of the building. This paper considers the geometry of the window by taking measures to prevent the flame from propagating along the vertical wall. In this paper, a residential building is taken as an example to evaluate the flame plume characteristics through experimental tests and numerical simulations. The objective of the present study is to study the flame plume characteristics under the air blow on the outer window side of the building. The theoretical equations of the flame tilt angle, non-dimensional temperature and non-dimensional velocity are derived. A series of experimental tests were carried out in a reduced-scale building model corresponding to the changes of lateral blow ventilation velocity. Reduced scale numerical simulations were conducted to verify the experiments. Results showed that the flame tilt angle increases with ventilation velocity increases. Meanwhile, the experimental results were compared with the reduced-scale tests and numerical simulations. These showed a good agreement between experimental results and numerical simulations. All these findings provide theoretical basis for building fire prevention outside window.

Introduction In connection to food insecurity, adaptation of new techniques or alteration of regular behavior is executed that translates to coping strategies. This paper has used data from food security and nutrition surveillance project (FSNSP), which collects information from a nationally representative sample in Bangladesh on coping behaviors associated with household food insecurity. To complement the current understanding of different coping strategies implemented by the Bangladeshi households, the objective of this paper has been set to examine the demographic and socio-economic characteristics of the food insecure households which define their propensity towards adaptation of different types of coping strategies. Methodology FSNSP follows a repeated cross-sectional survey design. Information of 23,374 food insecure households available from February 2011 to November 2013 was selected for the analyses. Coping strategies were categorized as financial, food compromised and both. Multinomial logistic regression was employed to draw inference. Results Majority of the households were significantly more inclined to adopt both multiple financial and food compromisation coping strategies. Post-aman season, educational status of the household head and household women, occupation of the household’s main earner, household income, food insecurity status, asset, size and possession of agricultural land were found to be independently and significantly associated with adaptation of both financial and food compromisation coping strategies relative to only financial coping strategies. The relative risk ratio of adopting food compromisation coping relative to financial coping strategies when compared to mildly food insecure households, was 4.54 times higher for households with moderate food insecurity but 0.3 times lower when the households were severely food insecure. Whereas, households were 8.04 times and 4.98 times more likely to adopt both food compromisation and financial relative to only financial coping strategies if moderately and severely food insecure respectively when compared to being mildly food insecure. Conclusion Households suffering from moderate and severe food insecurity, are more likely to adopt both financial and food compromisation coping strategies.

Many countries have some kind of energy-system transformation either planned or ongoing for various reasons, such as to curb carbon emissions or to compensate for the phasing out of nuclear energy. One important component of these transformations is the overall reduction in energy demand. It is generally acknowledged that the domestic sector represents a large share of total energy consumption in many countries. Increased energy efficiency is one factor that reduces energy demand, but behavioral approaches (known as “sufficiency”) and their respective interventions also play important roles. In this paper, we address citizens’ heterogeneity regarding both their current behaviors and their willingness to realize their sufficiency potentials—that is, to reduce their energy consumption through behavioral change. We collaborated with three Swiss cities for this study. A survey conducted in the three cities yielded thematic sets of energy-consumption behavior that various groups of participants rated differently. Using this data, we identified four groups of participants with different patterns of both current behaviors and sufficiency potentials. The paper discusses intervention types and addresses citizens’ heterogeneity and behaviors from a city-based perspective., PLoS ONE, 12 (10), ISSN:1932-6203

One of the main manifestations of climate change will be increased rainfall variability. How to deal with this in agriculture will be a major societal challenge. In this paper we explore flexibility in land use, through deliberate seasonal adjustments in cropped area, as a specific strategy for coping with rainfall variability. Such adjustments are not incorporated in hydro-meteorological crop models commonly used for food security analyses. Our paper contributes to the literature by making a comprehensive model assessment of inter-annual variability in crop production, including both variations in crop yield and cropped area. The Ganges basin is used as a case study. First, we assessed the contribution of cropped area variability to overall variability in rice and wheat production by applying hierarchical partitioning on time-series of agricultural statistics. We then introduced cropped area as an endogenous decision variable in a hydro-economic optimization model (WaterWise), coupled to a hydrology-vegetation model (LPJmL), and analyzed to what extent its performance in the estimation of inter-annual variability in crop production improved. From the statistics, we found that in the period 1999-2009 seasonal adjustment in cropped area can explain almost 50% of variability in wheat production and 40% of variability in rice production in the Indian part of the Ganges basin. Our improved model was well capable of mimicking existing variability at different spatial aggregation levels, especially for wheat. The value of flexibility, i.e. the foregone costs of choosing not to crop in years when water is scarce, was quantified at 4% of gross margin of wheat in the Indian part of the Ganges basin and as high as 34% of gross margin of wheat in the drought-prone state of Rajasthan. We argue that flexibility in land use is an important coping strategy to rainfall variability in water stressed regions.

This paper presents an integrated hybrid optimization algorithm for training the radial basis function neural network (RBF NN). Training of neural networks is still a challenging exercise in machine learning domain. Traditional training algorithms in general suffer and trap in local optima and lead to premature convergence, which makes them ineffective when applied for datasets with diverse features. Training algorithms based on evolutionary computations are becoming popular due to their robust nature in overcoming the drawbacks of the traditional algorithms. Accordingly, this paper proposes a hybrid training procedure with differential search (DS) algorithm functionally integrated with the particle swarm optimization (PSO). To surmount the local trapping of the search procedure, a new population initialization scheme is proposed using Logistic chaotic sequence, which enhances the population diversity and aid the search capability. To demonstrate the effectiveness of the proposed RBF hybrid training algorithm, experimental analysis on publicly available 7 benchmark datasets are performed. Subsequently, experiments were conducted on a practical application case for wind speed prediction to expound the superiority of the proposed RBF training algorithm in terms of prediction accuracy.

In power systems, energy storage effectively improves the reliability of the system and smooths out the fluctuations of intermittent energy. However, the installed capacity value of energy storage cannot effectively measure the contribution of energy storage to the generator adequacy of power systems. To achieve a variety of purposes, several control strategies may be utilized in energy storage systems. The purpose of this paper is to study the influence of different energy storage control strategies on the generation adequacy. This paper presents the capacity value of energy storage to quantitatively estimate the contribution of energy storage on the generation adequacy. Four different control strategies are considered in the experimental method to study the capacity value of energy storage. Finally, the analysis of the influence factors on the capacity value under different control strategies is given.

International audience; There appears to be little doubt as to the existence of an intentional technological resolve to produce convergent tools during the Middle Palaeolithic. However, the use of these pieces as pointed tools is still subject to debate: i.e., handheld tool vs. hafted tool. Present-day technological analysis has begun to apply new methodologies in order to quantify shape variability and to decipher the role of the morphology of these pieces in relation to function; for instance, geometric morphometric analyses have recently been applied with successful results. This paper presents a study of this type of analysis on 37 convergent tools from level Ga of Payre site (France), dated to MIS 8-7. These pieces are non-standardized knapping products produced by discoidal and orthogonal core technologies. Moreover, macro-wear studies attest to various activities on diverse materials with no evidence of hafting or projectile use. The aim of this paper is to test the geometric morphometric approach on non-standardized artefacts applying the Elliptical Fourier analysis (EFA) to 3D contours and to assess the potential relationship between size and shape, technology and function. This study is innovative in that it is the first time that this method, considered to be a valuable complement for describing technological and functional attributes, is applied to 3D contours of lithic products. Our results show that this methodology ensures a very good degree of accuracy in describing shape variations of the sharp edges of technologically non-standardized convergent tools. EFA on 3D contours indicates variations in deviations of the outline along the third dimension (i.e., dorso-ventrally) and yields quantitative and insightful information on the actual shape variations of tools. Several statistically significant relationships are found between shape variation and use-wear attributes, though the results emphasize the large variability of the shape of the convergent tools, which, in general, does not show a strong direct association with technological features and function. This is in good agreement with the technological context of this chronological period, characterized by a wide diversity of non-standardized tools adapted to multipurpose functions for varied subsistence activities.

The body of science evaluating the potential impacts of unconventional natural gas development (UNGD) has grown significantly in recent years, although many data gaps remain. Still, a broad empirical understanding of the impacts is beginning to emerge amidst a swell of research. The present categorical assessment provides an overview of the peer-reviewed scientific literature from 2009–2015 as it relates to the potential impacts of UNGD on public health, water quality, and air quality. We have categorized all available original research during this time period in an attempt to understand the weight and direction of the scientific literature. Our results indicate that at least 685 papers have been published in peer-reviewed scientific journals that are relevant to assessing the impacts of UNGD. 84% of public health studies contain findings that indicate public health hazards, elevated risks, or adverse health outcomes; 69% of water quality studies contain findings that indicate potential, positive association, or actual incidence of water contamination; and 87% of air quality studies contain findings that indicate elevated air pollutant emissions and/or atmospheric concentrations. This paper demonstrates that the weight of the findings in the scientific literature indicates hazards and elevated risks to human health as well as possible adverse health outcomes associated with UNGD. There are limitations to this type of assessment and it is only intended to provide a snapshot of the scientific knowledge based on the available literature. However, this work can be used to identify themes that lie in or across studies, to prioritize future research, and to provide an empirical foundation for policy decisions.

This paper examines whether mega-events-initiated planning regulations improved air quality in Chinese cities and explores the driving forces of the enforcement of such regulations. Using the 2008 Beijing Olympics as an example, we find that mega-events serve as an opportunity for cities to combat air pollution. The 2008 Olympics prompted a handful of Chinese cities to cut pollution and sustain a blue sky: Cities with air quality regulated for the Olympics cut their Air Pollution Index by about 16 points during the Games, compared to non-regulated cities, and 60% of that effect remained four years after the event. These achievements are obtained through effective mobilization of city leaders by associating air quality with their political careers. This study reveals that 1) a mega-event may improve urban environmental quality beyond the host cities and the event period, and 2) successful implementation of environmental regulations hinges on incentivizing local leaders.

Cocoa is a plant with origins in northwestern South America with high relevance in the global economy. Evidence indicates that cocoa is sensitive to a dry climate, under which crop production is reduced. Projections for future climate change scenarios suggest a warmer and drier climate in the Amazon basin. In this paper, we quantify the potential effects in cocoa production due to its edaphoclimatic suitability changes to the Brazilian Amazon biome and account for regional differences in planning occupation territories. We modeled the suitability of cocoa’s geographical distribution using an ensemble of 10 correlative models that were run in the “biomod2” library and projected to two future climate scenarios (RCPs 4.5 and 8.5) by 2050. Combining information on climate and soil suitability and installed infrastructure in the macro-regions of the Brazilian Amazon. We defined a zoning system to indicate how cocoa production may respond to climate change according to the current and future suitability model. Our results suggest that a reduction in precipitation and an increase in temperature may promote a reduction in the suitability of cocoa production in the Brazilian Amazon biome. In addition of the areas suitable for cocoa plantation, we found a 37.05% and 73.15% decrease in the areas suitable for intensification and expansion zones under RCP 4.5 and 8.5, respectively, compared with the current scenario. We conclude that there may be a need to expand land to cocoa production in the future, or else it will be necessary to plant a cocoa variety resistant to new climatic conditions. Besides, we recommend procedures to combat illegal deforestation to prevent the most critical climate change scenarios from occurring.

A key challenge of environmental planning is to craft recommendations for future sustainable spatial development amid ubiquitous uncertainties. This paper aims to explore how different data uncertainties, usually unknown to the planner, may influence environmental planning recommendations. We apply a case study-based approach, in which we provide three illustrative examples of how data with different kinds and levels of uncertainty affect environmental assessments and, by that, the decision-support provided by environmental planning. The cases stem from different spatial levels in Germany and consider ‘Regional soil-based climate change mitigation’ in the region of Hannover, ‘State-wide habitat conservation siting’ in the federal state of Saxony-Anhalt, and ‘National renewable energy planning’. Based on the three examples, we discuss implications for planning practice and derive recommendations for further research. The three cases studies illustrate the substantial effects of data uncertainty on environmental assessments and planning recommendations derived from those results. We identify four problem constellations of dealing with data uncertainty in environmental planning that relate to the severeness of uncertainty impacts, the responsibility of the decision-maker, and the kinds of impacts that wrong decisions may have. We close with recommendations for further research, among others to develop robust and pragmatic methods for identifying the uncertainty levels in environmental data and assessment results.

Degradation in the polymeric insulators is caused due to the environmental stresses. The main aim of this paper is to explore the improved aging characteristics of hybrid samples by adding nano/micro silica in High Temperature Vulcanized Silicone Rubber (HTV-SiR) under long term accelerated aging conditions for 9000 hours. As HTV-SiR is unable to sustain environmental stresses for a long time, thus a long term accelerated aging behavior is an important phenomenon to be considered for field application. The aging characteristics of nano/micro filled HTV-SiR are analyzed by using techniques such as Scanning Electron Microscopy (SEM), Leakage Current (LC), Fourier Transform Infrared Microscopy (FTIR), Hydrophobicity Classification (HC), and breakdown strength for the aging time of 9000 hours. FTIR and leakage currents are measured after every cycle. All the co-filled samples revealed escalated aging characteristics as compared to the neat sample except the SN8 sample (8% nano-silica+20% micro-silica) after 9000 hours of aging. The highest loading of 6% and 8% nano-silica with 20% micro-silica do not contribute to the improved performance when compared with the neat and hybrid samples. However, from the critical experimental analysis, it is deduced that SN2 sample (2% nano-silica+20% micro-silica) is highly resistant to the long term accelerated aging conditions. SN2 has no cracks, lower loss percentages in the important FTIR absorption peaks, higher breakdown strength and superior HC after aging as compared to the unfilled and hybrid samples.

This study documents a rare case of mummified human remains from Japan, dating to the late Heian period, 12th Century AD. The remains have only been scientifically investigated once in 1950 so far. The results of this investigation were translated, analyzed, and interpreted using methods of the 21st century. The remains have been traditionally identified as the four ruling generations of the Ōshū Fujiwara clan, who built a cultural and economic center in Hiraizumi. Accordingly, this paper will first examine the historical and cultural significance of Hiraizumi and its ruling class before re-evaluating the findings of the 1950 investigation. This study is the first in the Western scientific literature to provide a comprehensive historical, cultural, and medical evaluation of these mummies.

Few studies have examined the effects of inbound overseas travelers and meteorological conditions on the shift in human respiratory syncytial virus (HRSV) season in Japan. This study aims to test whether the number of inbound overseas travelers and meteorological conditions are associated with the onset week of HRSV epidemic season. The estimation of onset week for 46 prefectures (except for Okinawa prefecture) in Japan for 4-year period (2014–2017) was obtained from previous papers based on the national surveillance data. We obtained data on the yearly number of inbound overseas travelers and meteorological (yearly mean temperature and relative humidity) conditions from Japan National Tourism Organization (JNTO) and Japan Meteorological Agency (JMA), respectively. Multi-level mixed-effects linear regression analysis showed that every 1 person (per 100,000 population) increase in number of overall inbound overseas travelers led to an earlier onset week of HRSV epidemic season in the year by 0.02 week (coefficient –0.02; P

In this paper, a new innovative type-2 fuzzy-based for microgrid (MG) islanding detection is proposed in the condition of uncertainties. Load and generation uncertainties are two main sources of uncertainties in microgrids (MGs). Regardless of the uncertainties, the results cannot be confirmed. The proposed controller detects islanding in the fastest time under different conditions, and the uncertainties in the system will not considerably affect the controller’s performance. The proposed method is simulated on the sample system and examined in different scenarios. Then, a comparison is made in different conditions and scenarios between the suggested method and some common methods that have been presented so far to demonstrate the ability of the proposed method for islanding detection.

This paper explores whether efficacy beliefs can alter the relationship between worry about climate change and personal energy-saving behaviors, controlling for climate change beliefs and socio-demographics. For this purpose, we used data from 23 countries that participated in the European Social Survey Round 8 (N = 44 387). Worry about climate change, personal efficacy, personal outcome expectancy, and collective outcome expectancy were each associated with personal energy-saving behaviors concerning either energy curtailment or energy efficiency. The results further show that outcome expectancies moderate the association between worry about climate change and both types of energy behaviors. Worry was more strongly related to energy curtailment behaviors among those with high levels of personal and collective outcome expectancy. A similar pattern was found for energy efficiency behaviors, which were more strongly predicted by worry about climate change when combined with high levels of collective outcome expectancy. These findings are relevant for climate change communication, especially informational campaigns aiming to lower overall household energy use. publishedVersion

Hand, foot and mouth (HFM) disease is a common childhood illness. The paper aims to capture the spatiotemporal characters, and investigate the influence factors of the HFM epidemic in 15 regions of Xinjiang province from 2008 to 2017, China. Descriptive statistical analysis shows that the children aged 0-5 years have a higher HFM incidence, mostly boys. The male-female ratio is 1.5:1. Through the scanning method, we obtain the first cluster high-risk areas. The cluster time is usually from May to August every year. A spatiotemporal model is proposed to analyze the impact of meteorological factors on HFM disease. Comparing with the spatial model, the model is more effective in terms of R2, AIC, deviation, and mean-square error. Among meteorological factors, the number of HFM cases generally increases with the intensity of rainfall. As the temperature increases, there are more HFM patients. Some regions are mostly influenced by wind speed. Further, another spatiotemporal model is introduced to investigate the relationship between HFM disease and socioeconomic factors. The results show that socioeconomic factors have significant influence on the disease. In most areas, the risk of HFM disease tends to rise with the increase of the gross domestic product, the ratios of urban population and tertiary industry. The incidence is closely related to the number of beds and population density in some regions. The higher the ratio of primary school, the lower the number of HFM cases. Based on the above analysis, it is the key measure to prevent and control the spread of the HFM epidemic in high-risk areas, and influence factors should not be ignored.

Icy bridge deck in winter has tremendous consequences for expressway traffic safety, which is closely related to the bridge pavement temperature. In this paper, the critical meteorological conditions of icy bridge deck were predicted by multiple linear regression and BP neural network respectively. Firstly, the main parameters affecting the bridge pavement temperature were determined by Pearson partial correlation analysis based on the three-year winter meteorological data of the traffic meteorological monitoring station on the bridge in Shandong province. Secondly, the bridge pavement temperature is selected as the dependent variable, while air temperature, wind speed, relative humidity, dew point temperature, wet bulb temperature and wind cold temperature were selected as independent variables, and the bridge pavement temperature prediction models of linear regression and 5-layer hidden layer classical BP neural network regression were established respectively based on whether the variables are linear or not. Finally, the prediction accuracy of the above models was compared by using the measured data. The results show that the linear regression model could be established only with air temperature, relative humidity and wind speed, owing to collinearity problem. Compared with multiple linear regression model, the predicted value of the BP neural network has a higher degree of fitting with the measured data, and the coefficient of determination reaches 0.7929. Using multiple linear regression and BP neural network, the critical meteorological conditions of bridge deck icing in winter can be effectively predicted even when the sample size is insufficient.

Estimating the contact angle of a virus infected saliva droplet is seen to be an important area of research as it presents an idea about the drying time of the respective droplet and in turn of the growth of the underlying pandemic. In this paper we extend the data presented by Balusamy, Banerjee and Sahu [“Lifetime of sessile saliva droplets in the context of SARS-CoV-2,” Int. J. Heat Mass Transf. 123, 105178 (2021)], where the contact angles are fitted using a newly proposed half-circular wrapped-exponential model, and a sequential confidence interval estimation approach is established which largely reduces both time and cost with regards to data collection.

Interpreting human behavioral patterns during the Middle Paleolithic in the Levant is crucial for better understanding the dispersals and evolution of Homo sapiens and their possible interactions with other hominin groups. Here, we reconstruct the technological behavior, focusing on the centripetal Levallois method at Nesher Ramla karst sinkhole, Israel. Nesher Ramla karst sinkhole is dated to the Marine Isotope stages (MIS) 6 and 5 and represents one of the oldest occurrences of the centripetal Levallois reduction strategy in the Near East. The Levallois centripetal technology is often seen as a marker of human dispersals and adaptations in the Middle Paleolithic/Middle Stone Age of Africa and the Near East. This technology is documented in East African sites as early as 300 kya and in the Levant as early as 130 kya. However, the degree of similarity between African and Levantine centripetal technology and whether it originates from the same source remain under debate. In this paper, we focus on describing the lithic organization at Unit III of Nesher Ramla (dated to MIS 5), which is dominated by the centripetal Levallois method in association with other reduction sequences. Both preferential and recurrent centripetal Levallois modes were used at the site to produce oval and rectangular flakes. Other minor reduction sequences include unidirectional convergent method for Levallois points production and a specific method for the manufacture of naturally backed knives. The lithic data from Unit III of Nesher Ramla is further used in inter-site comparisons suggesting that the mid-Middle Paleolithic sites in the Near East possess common technological characteristics, especially the use of the centripetal Levallois method as predominant reduction strategy. This trend differs from what is usually observed in Africa and Europe, where the centripetal Levallois method is modestly represented during MIS 5 and is accompanied by other, more dominant, reduction strategies.

Air pollution is a serious concern to people who want to engage in physical activities to improve and maintain their health. However, air quality data collected at the nearest monitoring site may not be the best source of information because the data may be incomplete (e.g., some pollutants are not monitored) or not representative. This paper puts forward a method that uses air quality data from a large area to derive a diurnal profile of air quality variation for that area and identify the time window in which the air quality is typically the best during a day. If people exercise in that time window then they can minimize their exposure to air pollution. Three years' worth of air quality data in five California counties were analyzed to identify the general pattern of diurnal variation of air quality. The analysis shows the pattern of air quality variation is very similar among those five counties which represent diverse geographical and meteorological conditions. The analysis further reveals that in California air quality is generally the best in early mornings; as such, people should exercise in the early morning if their daily schedule allows it. A similar analysis can be performed for other areas to help people choose the best time window to exercise.

Wheelchair castors fail frequently causing physical, social and economic consequences for wheelchair users. These failures occur in spite of established wheelchair test methods and regulations, suggesting that the existing tests may not be sufficient to screen poorly designed castors. An expert stakeholder group, convened by the International Society of Wheelchair Professionals (ISWP), noted castor failures as a high priority and recommended that a new castor testing system should be developed. In a previous study, the effect of shock exposure on castor durability was studied. The current paper extends the previous work and focuses on the development of a castor testing protocol based on shock, corrosion and abrasion exposure data collected in the community. The testing protocol was applied to 8 different castor models tested under four conditions: shock, corrosion + shock, abrasion + shock and abrasion + corrosion + shock. For each model, a total of n = 8 samples were evaluated across the four conditions. Results demonstrate that corrosion and abrasion reduced castor durability between 13% to 100% depending on the model. Importantly, the inclusion of corrosion and abrasion resulted in changes in the failure modes for 75% of the tested models and two-thirds of the altered failure modes are associated with increased risk of injury for wheelchair users. These results suggest that corrosion and abrasion present in the community reduce castor durability, thus supporting their inclusion in the castor testing protocol and potentially other wheelchair standards.

Southern African cities face several challenges including management of rapid urbanization, rising populations, expanding informal settlements; adequate water and other service provision, and a host of governance challenges. Climate change and variability add a compounding effect to this complex, multi stressor context. Addressing the complexity requires an understanding of urban ecosystems functioning and interactions amongst the built and natural environment (climate) and human systems. In this paper we argue that learning is essential for cities to be resilient to current and future challenges. We profile the Future Resilience for African CiTies And Lands (FRACTAL) project which contributed towards climate resilient development by providing relevant climate information for decision-making at the city regional scale in southern Africa. Following FRACTAL’s city-to-city learning approach of sharing good practices, knowledge and experiences framed around transdisciplinary research, the study cities of Harare, Lusaka, Windhoek and Durban conducted city learning exchange visits between 2017 and 2018. We used a mixed methods approach to collect and analyze historical climate and hydrological data and current socio-economic and development data among the cities. A qualitative, in-depth, case study comparative analysis was used to identify similarities and differences as well as lessons drawn from the learning process during the city exchanges and these were complimented by desktop studies. Results showed water scarcity, large informal settlements, reliance on external water and energy sources, inadequate protection of ecologically sensitive resources and service provision as some of the common complications in the cities. Several lessons and transferable practices learnt from the cities included effective water conservation and waste management and the use of public-private partnerships in Windhoek, community engagements in Durban and Lusaka while lessons on decisive leadership in dealing with informal settlements emanated from Harare’s limited informal settlements. Lastly, Durban’s Adaptation Charter and integrated climate planning provided lessons for biodiversity protection and mainstreaming climate change at city governance level. While we recognize that cities are context-specific we consider these good practices as being broadly transferable to other southern African cities. We conclude that social, experiential and structured learning can be an innovative way of multi-stakeholder engagement and a useful approach to increase city resilience planning across southern Africa and cities that face similar developmental challenges.

Hydrologic models such as the USEPA Stormwater Management Model (SWMM) are commonly used to assess the design and performance of green infrastructure (GI). To accurately represent GI performance models used in design need to be able to address both the hydrology/hydraulics of the catchment and the GI unsaturated (vadose) zone hydrology. While hydrologic models, such as SWMM, address the need for catchment hydrology/hydraulics, they often simplify the unsaturated zone hydrology. This paper presents a methodology utilizing existing components of SWMM to represent unsaturated zone hydrology in an accessible format that does not require adjustments to the SWMM source code. The methodology simulated the unsaturated soil water movement by considering flow caused by differences of soil matric head and flow caused by gravity between soil layers with finite depth/length. The flow flux related to the soil matric head is a function of soil water diffusivity (D) and the soil moisture gradient, where D can be represented by a pump curve in SWMM. The flow flux related to gravity was controlled by unsaturated hydraulic conductivity (K) only and was also simulated by a pump. The methodology was compared to another variably saturated model, HYDRUS, with theoretical soils (with single layers of sand, loam, silt, and clay, as well as dual-layer scenarios). Field data was used to compare the methodology to HYDRUS and the SWMM LID (Low Impact Development) module. In all comparisons the presented methodology and HYDRUS delivered similar results for the vadose zone response to a storm event, while the LID module of SWMM exhibited slower water movement. The results showed that under natural conditions, the approximation of the presented methodology yielded satisfactory results to simulate flow through the unsaturated vadose zone.

Indoor air quality monitoring as it relates to the domestic setting is an integral part of human exposure monitoring and health risk assessment. Hence there is a great need for easy to use, fast and economical indoor air quality sensors to monitor the volatile organic compound composition of the air which is known to be significantly perturbed by the various source emissions from activities in the home. To meet this need, paper-based colorimetric sensor arrays were deployed as volatile organic compound detectors in a field study aiming to understand which activities elicit responses from these sensor arrays in household settings. The sensor array itself is composed of pH indicators and aniline dyes that enable molecular recognition of carboxylic acids, amines and carbonyl-containing compounds. The sensor arrays were initially deployed in different rooms in a single household having different occupant activity types and levels. Sensor responses were shown to differ for different room settings on the basis of occupancy levels and the nature of the room emission sources. Sensor responses relating to specific activities such as cooking, cleaning, office work, etc were noted in the temporal response. Subsequently, the colorimetric sensor arrays were deployed in a broader study across 9 different households and, using multivariate analysis, the sensor responses were shown to correlate strongly with household occupant activity and year of house build. Overall, this study demonstrates the significant potential for this type of simple approach to indoor air pollution monitoring in residential environments.

Vulnerability to climate change is highly dynamic, varying between and within communities over different timescales. This paper draws upon complex adaptive systems thinking to develop an approach for capturing, understanding, and monitoring climate vulnerability in a case study from northern Canada, focusing on Inuit food systems. In the community of Ulukhaktok, Northwest Territories, we followed 10 hunters over a 2-year period, asking them to document their harvesting activities and discuss their lived experience of harvesting under changing environmental and societal conditions. GPS monitoring and participatory mapping sessions were used to document 23,996km of trails (n = 409), with conversational bi-weekly semi-structured interviews and secondary instrumental weather data used to contextualise climate change within a nexus of other socioeconomic, cultural, and political stressors that also affect harvesting. Our results demonstrate that climate change has considerable potential to affect harvesting activities, particularly when its impacts manifest as anomalous/extreme events. However, climate change impacts are not necessarily the most salient issues affecting harvesting on a day-to-day basis. Instead, factors relating to economics (particularly financial capital and the wage-based economy), social networks, and institutions are found to have a greater influence, either as standalone factors with cascading effects or when acting synchronously to augment the impacts of environmental change.

The importance of coastal upwelling systems is widely recognized. However, several aspects of the current and future behaviors of these systems remain uncertain. Fluctuations in temperature because of anthropogenic climate change are hypothesized to affect upwelling-favorable winds and coastal upwelling is expected to intensify across all Eastern Boundary Upwelling Systems. To better understand how upwelling may change in the future, it is necessary to develop a more rigorous method of quantifying this phenomenon. In this paper, we use SST data and wind data in a novel method of detecting upwelling signals and quantifying metrics of upwelling intensity, duration, and frequency at four sites within the Benguela Upwelling System. We found that indicators of upwelling are uniformly detected across five SST products for each of the four sites and that the duration of those signals is longer in SST products with higher spatial resolutions. Moreover, the high-resolution SST products are significantly more likely to display upwelling signals at 25 km away from the coast when signals were also detected at the coast. Our findings promote the viability of using SST and wind time series data to detect upwelling signals within coastal upwelling systems. We highlight the importance of high-resolution data products to improve the reliability of such estimates. This study represents an important step towards the development of an objective method for describing the behavior of coastal upwelling systems.

To improve the performance of wind sensors in the high velocity range, this paper proposes a wind measurement strategy for thermal wind velocity sensors that combines the constant power and constant temperature difference driving modes of the heating element. Based on the airflow distribution characteristics from fluid dynamics, sequential measurement and correction is proposed as a method of measuring wind direction. In addition, a wind velocity and direction measurement instrument was developed using the above-mentioned approaches. The test results showed that the proposed instrument can obtain large dynamic wind velocity measurements from 0 to 60 m/s. The wind velocity measurement accuracy was ±0.5 m/s in the common velocity range of 0–20 m/s and ±1 m/s in the high velocity range of 20–60 m/s. The wind direction accuracy was ±3° throughout the 360° range. The proposed approaches and instrument are not only practical but also capable of meeting the requirements of wide-range and large dynamic wind vector measurement applications.

On August 25 2017, an unprecedented influx of Rohingya refugees began from Rakhine State in Myanmar into Bangladesh’s district of Cox’s Bazar. The scale and acuteness of this humanitarian crisis was unprecedented and unique globally, requiring strong coordination of a multitude of actors. This paper reflects on the health sector coordination from August 2017 to October 2019, focusing on selected achievements and persisting challenges of the health sector strategic advisory group (HSSAG), and the health sector working groups including epidemiology and case management, sexual and reproductive health, community health, mental health and psychosocial support, and emergency preparedness. In the early days of the response, minimum service standards for primary health care were established, a fundamental initial step which enabled the standardization of services based on critical needs. Similarly, establishing standards for community health outreach was the backbone for capitalizing on this important health workforce. Novel approaches were adopted for infectious disease responses for acute watery diarrhoea and varicella, drawing on inter-sectoral collaborations. Sexual and reproductive health services were prioritized from the initial onset of the crisis and improvements in skilled delivery attendance, gender-based violence services, abortion care and family planning were recorded. Mental health service provision was strengthened through community-based approaches although integration of mental health programmes into primary health care has been limited by availability of specialist psychiatrists. Strong, collaborative and legitimate leadership by the health sector strategic advisory group, drawing on inter-sectoral collaborations and the technical expertise of the different technical working groups, were critical in the response and proved effective, despite the remaining challenges to be addressed. Anticipated reductions in funding as the crisis moves into protracted status threatens the achievements of the health sector in provision of health services to the Rohingya refugees.

Rapid technological development has revolutionized the industrial sector. Internet of Things (IoT) started to appear in many fields, such as health care and smart cities. A few years later, IoT was supported by industry, leading to what is called Industry 4.0. In this paper, a cloud-assisted fog-networking architecture is implemented in an IoT environment with a three-layer network. An efficient energy and completion time for dependent task computation offloading (ET-DTCO) algorithm is proposed, and it considers two quality-of-service (QoS) parameters: efficient energy and completion time offloading for dependent tasks in Industry 4.0. The proposed solution employs the Firefly algorithm to optimize the process of the selection-offloading computing mode and determine the optimal solution for performing tasks locally or offloaded to a fog or cloud considering the task dependency. Moreover, the proposed algorithm is compared with existing techniques. Simulation results proved that the proposed ET-DTCO algorithm outperforms other offloading algorithms in minimizing energy consumption and completion time while enhancing the overall efficiency of the system.

Due to high humidity, the ageing of room temperature vulcanized silicone rubber (RTV) has been a serious problem in Southwestern China. In order to solve the problem of RTV life prediction, the aging classification method was established by analyzing the microtopography of RTV samples in this paper. Besides, the comprehensive analysis of RTV element content, partial element content ratio, and major chemical groups of RTV samples in each aging level were conducted. It is found that as the ageing level increases, the element contents of C, Si, O, Al change accordingly and the ratio of C:Si drops from 2.39 to 1.54, and absorption peaks of the chemical groups of Si-(CH3)2, Si-O-Si, Si-CH3 and C-H in CH3 decrease. This work can enrich the investigation of RTV, and may provide useful reference for performance evaluation and replacement of RTV in substations.

It is estimated that about 1/4th of all greenhouse gas (GHG) emissions may be caused by the global food system. Reducing the GHG emissions from food production is a major challenge in the context of the projected growth of the world’s population, which is increasing demand for food. In this context, the goal should be to achieve the lowest possible emission intensity of the food production system, understood as the amount of GHG emissions per unit of output. The study aimed to calculate the emission intensity of food production systems and to specify its determinants based on a panel regression model for 14 countries, which accounted for more than 65% of food production in the world between 2000 and 2014. In this article, emission intensity is defined as the amount of GHG emissions per value of global output. Research on the determinants of GHG emissions related to food production is well documented in the literature; however, there is a lack of research on the determinants of the emission intensity ratio for food production. Hence, the original contribution of this paper is the analysis of the determinants of GHG emissions intensity of food production systems. The study found the decreased of emission intensity from an average of more than 0.68 kg of CO2 equivalent per USD 1 worth of food production global output in 2000 to less than 0.46 in 2014. The determinants of emission intensity decrease included the yield of cereals, the use of nitrogen fertilizers, the agriculture material intensity, the Human Development Index, and the share of fossil fuel energy consumption in total energy use. The determinants of growth of emission intensity of food production systems included GDP per capita, population density, nitrogen fertilizer production, utilized agriculture area, share of animal production, and energy use per capita.

When assessing the short term effect of air pollution on health outcomes, it is common practice to consider one pollutant at a time, due to their high correlation. Multi pollutant methods have been recently proposed, mainly consisting of collapsing the different pollutants into air quality indexes or clustering the pollutants and then evaluating the effect of each cluster on the health outcome. A major drawback of such approaches is that it is not possible to evaluate the health impact of each pollutant. In this paper we propose the use of the Bayesian hierarchical framework to deal with multi pollutant concentration in a two-component model: a pollutant model is specified to estimate the `true' concentration values for if your each pollutant and then such concentration is linked to the health outcomes in a time series perspective. Through a simulation study we evaluate the model performance and we apply the modelling framework to investigate the effect of six pollutants on cardiovascular mortality in Greater London in 2011-2012.

Wind energy is one of the most important renewable resources and plays a vital role in reducing carbon emission and solving global warming problem. Every country has made a corresponding energy policy to stimulate wind energy industry development based on wind energy production, consumption, and distribution. In this paper, we focus on forecasting wind energy consumption from a macro perspective. A novel power-driven fractional accumulated grey model (PFAGM) is proposed to solve the wind energy consumption prediction problem with historic annual consumption of the past ten years. PFAGM model optimizes the grey input of the classic fractional grey model with an exponential term of time. For boosting prediction performance, a heuristic intelligent algorithm WOA is used to search the optimal order of PFAGM model. Its linear parameters are estimated by using the least-square method. Then validation experiments on real-life data sets have been conducted to verify the superior prediction accuracy of PFAGM model compared with other three well-known grey models. Finally, the PFAGM model is applied to predict China's wind energy consumption in the next three years.

When the unmanned aerial vehicle (UAV) is used for aerial spraying, the downwash airflow generated by the UAV rotor will interact with the crop canopy and form a conical vortex shape in the crop plant. The size of the vortex will directly affect the outcome of the spraying operation. Six one-way spraying were performed by the UAV in a rice field with different but random flying altitude and velocities within the optimal operational range to form different vortex patterns. The spraying reagent was clear water, which was collected by water sensitive paper (WSP), and then the WSP was analyzed to study the droplets deposition effects in different vortex states. The results showed that the formation of the vortex significantly influenced the droplet deposition. To be specific, the droplet deposition amount in the obvious-vortex (OV) state was about 1.5 times of that in the small-scale (SV) vortex state, and 7 times of that in the non-vortex (NV) state. In the OV state, the droplets mainly deposited directly below and on both sides of the route. The deposition amount, coverage rate and droplet size increased from top to bottom of the crops with the deposition amount, coverage rate, and volume median diameter (VMD) ranging 0.204-0.470 μL/cm2, 3.31%-7.41%, and 306-367μm, respectively. In the SV state, droplets mainly deposited in the vortex area directly below the route. The deposition amount in the downwind direction was bigger than that in the upwind direction. The maximum of deposition amount, coverage rate and droplet size were found in the middle layer of the crops, the range are 0.177-0.334μL/cm2, 2.71%-5.30%, 295-370μm, respectively. In the NV state, the droplet mainly performed drifting motion, and the average droplet deposition amount in the downwind non-effective region was 29.4 times of that in the upwind non-effective region and 8.7 times of the effective vortex region directly below the route. The maximum of deposition amount, coverage rate and droplet size appeared in the upper layer of the crop, the range are 0.006-0.132μL/cm2, 0.17%-1.82%, 120-309μm, respectively, and almost no droplet deposited in the middle and lower part of the crop. The coefficient of variation (CV) of the droplet deposition amount was less than 40% in the state of obvious-vortex and small-scale vortex, and the worst penetration appeared in the non-vortex amounting to 65.97%. This work offers a basis for improving the spraying performance of UAV.

This paper investigates the correlation between climate, environment and human land use in the Westernmost Mediterranean on both sides of the Strait of Gibraltar during the Late Glacial. Using a multi-proxy approach on a sample of 300 sites from the Solutrean and Magdalenian of the Iberian Peninsula and from the Iberomaurusian in Morocco, we find evidence for significant changes in settlement patterns and site density after the Last Glacial Maximum. In Southern Iberia, during Heinrich Stadial 1, hyperarid zones expanded drastically from the south-eastern coast to the West through the Interior. This aridification process heavily affected Magdalenian settlement in the South and caused a strong decline of hunter-gatherer population. Southern Iberia during Heinrich Stadial 1 turned out to be a high-risk environment when compared to Northern Iberia. At the same time, the Late Iberomaurusian of Morocco, although considered to be situated in a high-risk environment as well, experiences an increase of sites and expansion of settlement area.

In this paper, we introduce a scalable machine learning approach accompanied by open-source software for identifying violent and peaceful forms of political protest participation using social media data. While violent political protests are statistically rare events, they often shape public perceptions of political and social movements. This is, in part, due to the extensive and disproportionate media coverage which violent protest participation receives relative to peaceful protest participation. In the past, when a small number of media conglomerates served as the primary information source for learning about political and social movements, viewership and advertiser demands encouraged news organizations to focus on violent forms of political protest participation. Consequently, much of our knowledge about political protest participation is derived from data collected about violent protests, while less is known about peaceful forms of protest. Since the early 2000s, the digital revolution shifted attention away from traditional news sources toward social media as a primary source of information about current events. This, along with developments in machine learning which allow us to collect and analyze data relevant to political participation, present us with unique opportunities to expand our knowledge of peaceful and violent forms of political protest participation through social media data.