Dry reforming of methane to syngas: a potential alternative process for value added chemicals—a techno-economic perspective

During the past decade, there has been increasing global concern over the rise of anthropogenic CO₂ emission into the Earth’s atmosphere (J Air Waste Manage Assoc 53:645–715, 2003). The utilization of CO₂ to produce any valuable product is need of the hour. The production of syngas from CO₂ and CH₄ seems to be one of the promising alternatives in terms of industrial utilization, as it offers several advantages: (a) mitigation of CO₂, (b) transformation of natural gas and CO₂ into valuable syngas, and (c) producing syngas with H₂/CO ratio 1 which may further be used for the production of valuable petrochemicals (J Air Waste Manage Assoc 53:645–715, 2003). A conceptual design for the production of synthesis gas by dry reforming of methane is presented here. An economic assessment of this process with an integrated methanol production section as a case was conceptualized and compared with the conventional steam methane reforming route to produce methanol. The economic study indicated that dry reforming of natural gas/methane is a competitive process with lower operating and capital costs in comparison with steam reforming assuming negligible cost of CO₂ import.     

Wastewater reuse: modeling chloroform formation

The chloroform is a substance that presents a significant risk to or via the aquatic environment. Thus, the emissions, discharges and losses of this substance need to be controlled during wastewater disinfection for reclamation and reuse purposes. Due to its carcinogenetic potential, multiple studies have been carried out on drinking and surface/natural waters but less consideration has been directed to the wastewater disinfection. The focus of this work studied the formation of chloroform during chlorination in prepared waters or artificial matrices that intended to simulate wastewaters stored in landscape ponds for green areas irrigation. The relation between reaction time, chlorine dose, and chloroform formation and the variation of the dissolved organic carbon (DOC) content during the reaction was assessed. A two-variant model was proposed to simulate breakpoint chlorination practices (when chlorine dose is equal or lower than chlorine demand) and super chlorination techniques (when chlorine dose tends to surpass chlorine demand). The model was validated by the application of actual data from working conditions of six wastewater treatment plants located in Algarve, Portugal, including other data obtained in previous research studies that were not used in the model development, and by comparing the predicted values with real measured ones.     

Deep learning architecture for air quality predictions

With the rapid development of urbanization and industrialization, many developing countries are suffering from heavy air pollution. Governments and citizens have expressed increasing concern regarding air pollution because it affects human health and sustainable development worldwide. Current air quality prediction methods mainly use shallow models; however, these methods produce unsatisfactory results, which inspired us to investigate methods of predicting air quality based on deep architecture models. In this paper, a novel spatiotemporal deep learning (STDL)-based air quality prediction method that inherently considers spatial and temporal correlations is proposed. A stacked autoencoder (SAE) model is used to extract inherent air quality features, and it is trained in a greedy layer-wise manner. Compared with traditional time series prediction models, our model can predict the air quality of all stations simultaneously and shows the temporal stability in all seasons. Moreover, a comparison with the spatiotemporal artificial neural network (STANN), auto regression moving average (ARMA), and support vector regression (SVR) models demonstrates that the proposed method of performing air quality predictions has a superior performance.     

Increasing CACNA1C expression in placenta containing high Cd level: an implication of Cd toxicity

Cadmium (Cd) has known to produce many adverse effects on organs including placenta. Many essential transporters are involved in Cd transport pathways such as DMT-1, ZIP as well as L-VDCC. Fourteen pregnant women participated and were divided into two groups: high and low Cd-exposed (H-Cd, L-Cd) groups on the basis of their residential areas, Cd concentrations in the blood (B-Cd), urine (U-Cd), and placenta (P-Cd). The results showed that the B-Cd and U-Cd were significantly increased in H-Cd group (p < 0.05). Interestingly, the P-Cd in H-Cd group was elevated (p < 0.05) and positively related to their B-Cd and U-Cd values (p < 0.05). However, the mean cord blood Cd (C-Cd) concentration in H-Cd group was not significantly increased about 2.5-fold when comparing to L-Cd group. To determine the Cd accumulation in placental tissues, metallothionein-1A (MT-1A) and metallothionein-2A (MT-2A) expressions were used as biomarkers. The results revealed that mean MT-1A and MT-2A mRNAs and MT-1/2 proteins were up-regulated in H-Cd group (p < 0.05). In addition, the Ca channel alpha 1C (CACNA1C) mRNA and protein expressions were noticeably elevated in H-Cd group (p < 0.05). From these findings, we suggested that CACNA1C might be implicated in Cd transport in human placenta.     

Rapid metal extractability tests from polluted mining soils by ultrasound probe sonication and microwave-assisted extraction systems

Ultrasonic probe sonication (UPS) and microwave-assisted extraction (MAE) were used for rapid single extraction of Cd, Cr, Cu, Ni, Pb, and Zn from soils polluted by former mining activities (Mónica Mine, Bustarviejo, NW Madrid, Spain), using 0.01 mol L^?1 calcium chloride (CaCl₂), 0.43 mol L^?1 acetic acid (CH₃COOH), and 0.05 mol L^?1 ethylenediaminetetraacetic acid (EDTA) at pH 7 as extracting agents. The optimum extraction conditions by UPS consisted of an extraction time of 2 min for both CaCl₂ and EDTA extractions and 15 min for CH₃COOH extraction, at 30% ultrasound (US) amplitude, whereas in the case of MAE, they consisted of 5 min at 50 °C for both CaCl₂ and EDTA extractions and 15 min at 120 °C for CH₃COOH extraction. Extractable concentrations were determined by inductively coupled plasma atomic emission spectrometry (ICP-AES). The proposed methods were compared with a reduced version of the corresponding single extraction procedures proposed by the Standards, Measurements and Testing Programme (SM&T). The results obtained showed a great variability on extraction percentages, depending on the metal, the total concentration level and the soil sample, reaching high values in some areas. However, the correlation analysis showed that total concentration is the most relevant factor for element extractability in these soil samples. From the results obtained, the application of the accelerated extraction procedures, such as MAE and UPS, could be considered a useful approach to evaluate rapidly the extractability of the metals studied.     

Review of receptor modeling methods for source apportionment

Efforts have been made to relate measured concentrations of airborne constituents to their origins for more than 50 years. During this time interval, there have been developments in the measurement technology to gather highly time-resolved, detailed chemical compositional data. Similarly, the improvements in computers have permitted a parallel development of data analysis tools that permit the extraction of information from these data. There is now a substantial capability to provide useful insights into the sources of pollutants and their atmospheric processing that can help inform air quality management options. Efforts have been made to combine receptor and chemical transport models to provide improved apportionments. Tools are available to utilize limited numbers of known profiles with the ambient data to obtain more accurate apportionments for targeted sources. In addition, tools are in place to allow more advanced models to be fitted to the data based on conceptual models of the nature of the sources and the sampling/analytical approach. Each of the approaches has its strengths and weaknesses. However, the field as a whole suffers from a lack of measurements of source emission compositions. There has not been an active effort to develop source profiles for stationary sources for a long time, and with many significant sources built in developing countries, the lack of local profiles is a serious problem in effective source apportionment. The field is now relatively mature in terms of its methods and its ability to adapt to new measurement technologies, so that we can be assured of a high likelihood of extracting the maximal information from the collected data.

Implications: Efforts have been made over the past 50 years to use air quality data to estimate the influence of air pollution sources. These methods are now relatively mature and many are readily accessible through publically available software. This review examines the development of receptor models and the current state of the art in extracting source identification and apportionments from ambient air quality data.     

Assessing the vulnerability of rare plants using climate change velocity,habitat connectivity,and dispersal ability: a case study in Alberta,Canada

Climate change generally requires species to migrate northward or to higher elevation to maintain constant climate conditions, but migration requirement and migration capacity of individual species can vary greatly. Individual populations of species occupy different positions in the landscape that determine their required range shift to maintain similar climate, and likewise the migration capacity depends on habitat connectivity. Here, we demonstrate an approach to quantifying species vulnerabilities to climate change for 419 rare vascular plants in Alberta, Canada, based on a multivariate velocity of climate change metric, local habitat fragmentation, and migration capacity. Climate change velocities indicated that future migration requirements ranged from 1 to 5 km/year in topographically complex landscapes, such as the Alberta Foothills and Rocky Mountains. In contrast, migration requirements to maintain constant climate in relatively flat Boreal Plains, Parkland, and Grassland ranged from 4 to 8 km/year. Habitat fragmentation was also highest in these flat regions, particularly the Parkland Natural Region. Of the 419 rare vascular plants assessed, 36 were globally threatened (G1–G3 ranking). Three globally threatened species were ranked as extremely vulnerable and five species as highly vulnerable to the interactions among climate change velocity, habitat fragmentation, and migration capacity. Incorporating dispersal characteristics and habitat fragmentation with local patterns in climate change velocity improves the assessment of climate change threats to species and may be applied to guide monitoring efforts or conservation actions.     

Climatic changes and their impact on socio-economic sectors in the Bhutan Himalayas: an implementation strategy

This paper contributes to an enhanced understanding of present climatic conditions, observed climate trends and regional climate vulnerability of the Bhutan Himalayas. Bhutan’s complex, often high-altitude terrain and the severe impact of the Indian summer monsoon leads to a strong exposure of the countries’ key economic sectors (agriculture, forestry, hydropower generation and tourism) to climatic changes. Climate change also threatens Bhutan’s vast biodiversity and increases the likelihood of natural hazards (e.g. glacier lake outburst floods, flash floods, droughts and forest fires). A better understanding of Bhutan’s climate and its variability, as well as observed and possible climate impacts, will help in improving the handling of regional social, economic and ecologic challenges not limited to the Himalayas. Only a few climatological studies exist for the eastern Himalayas. They mainly focus on adaptation to immediate threats by glacier lake outbursts. In contrast, this paper (1) investigates the average spatial and inner-annual diversity of the air temperature regime of Bhutan, based on local meteorological observations, (2) discusses past temperature variability, based on global datasets, and (3) relates effects of observed warming to water availability, hydropower development, natural hazards, forests, biodiversity, agriculture, human health and tourism in the Bhutan Himalayas. Results indicate a large spatial and temporal temperature variability within Bhutan and considerably increasing temperatures especially over recent decades. Implications of regional climatic changes on various socio-economic sectors and possible adaptation efforts are discussed.     

Livelihood vulnerability approach to assessing climate change impacts on mixed agro-livestock smallholders around the Gandaki River Basin in Nepal

Climate change vulnerability depends upon various factors and differs between places, sectors and communities. People in developing countries whose subsistence livelihood depends mainly upon agriculture and livestock production are identified as particularly vulnerable. Nepal, where the majority of people are in a mixed agro-livestock system, is identified as the world’s fourth most vulnerable country to climate change. However, there is limited knowledge on how vulnerable mixed agro-livestock smallholders are and how their vulnerability differs across different ecological regions in Nepal. This study aims to test two vulnerability assessment indices, livelihood vulnerability index and IPCC vulnerability index, around the Gandaki River Basin of central Nepal. A total of 543 households practicing mixed agro-livestock were surveyed from three districts, namely Dhading, Syangja and Kapilvastu representing three major ecological zones: mountain, mid-hill and Terai (lowland). Data on socio-demographics, livelihood determinants, social networks, health, food and water security, natural disasters and climate variability were collected and combined into the indices. Both indices differed for mixed agro-livestock smallholders across the three districts, with Dhading scoring as the most vulnerable and Syangja the least. Substantial variation across the districts was observed in components, sub-components and three dimensions (exposure, sensitivity and adaptive capacity) of vulnerability. The findings help in designing site-specific intervention strategies to reduce vulnerability of mixed agro-livestock smallholders to climate change.     

A framework for understanding climate change impacts on coral reef social–ecological systems

Corals and coral-associated species are highly vulnerable to the emerging effects of global climate change. The widespread degradation of coral reefs, which will be accelerated by climate change, jeopardizes the goods and services that tropical nations derive from reef ecosystems. However, climate change impacts to reef social–ecological systems can also be bi-directional. For example, some climate impacts, such as storms and sea level rise, can directly impact societies, with repercussions for how they interact with the environment. This study identifies the multiple impact pathways within coral reef social–ecological systems arising from four key climatic drivers: increased sea surface temperature, severe tropical storms, sea level rise and ocean acidification. We develop a novel framework for investigating climate change impacts in social–ecological systems, which helps to highlight the diverse impacts that must be considered in order to develop a more complete understanding of the impacts of climate change, as well as developing appropriate management actions to mitigate climate change impacts on coral reef and people.