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.     

Influence of sub-lethal crude oil concentration on growth,water relations and photosynthetic capacity of maize (Zea mays L.) plants

Environmental Science and Pollution Research - Maize tolerance potential to oil pollution was assessed by growing Zea mays in soil contaminated with varying levels of crude oil (0, 2.5 and...     

Constructed wetlands may lower inorganic nutrient inputs but enhance DOC loadings into a drinking water reservoir in North Wales

Environmental Science and Pollution Research - The objective of this study was to monitor a newly constructed wetland (CW) in north Wales, UK, to assess whether it contributes to an improvement in...     

Analysis of waste management issues arising from a field study evaluating decontamination of a biological agent from a building

The Bio-response Operational Testing and Evaluation (BOTE) Project was a cross-government effort designed to operationally test and evaluate a response to a biological incident (release of Bacillus anthracis [Ba] spores, the causative agent for anthrax) from initial public health and law enforcement response through environmental remediation. The BOTE Project was designed to address site remediation after the release of a Ba simulant, Bacillus atrophaeus spp. globigii (Bg), within a facility, drawing upon recent advances in the biological sampling and decontamination areas. A key component of response to a biological contamination incident is the proper management of wastes and residues, which is woven throughout all response activities. Waste is generated throughout the response and includes items like sampling media packaging materials, discarded personal protective equipment, items removed from the facility either prior to or following decontamination, aqueous waste streams, and materials generated through the application of decontamination technologies. The amount of residual contaminating agent will impact the available disposal pathways and waste management costs. Waste management is an integral part of the decontamination process and should be included through “Pre-Incident” response planning. Overall, the pH-adjusted bleach decontamination process generated the most waste from the decontamination efforts, and fumigation with chlorine dioxide generated the least waste. A majority of the solid waste generated during pH-adjusted bleach decontamination was the nonporous surfaces that were removed, bagged, decontaminated ex situ, and treated as waste. The waste during the two fumigation rounds of the BOTE Project was associated mainly with sampling activities. Waste management activities may represent a significant contribution to the overall cost of the response/recovery operation. This paper addresses the waste management activities for the BOTE field test.Implications: Management of waste is a critical element of activities dealing with remediation of buildings and outdoor areas following a biological contamination incident. Waste management must be integrated into the overall remediation process, along with sampling, decontamination, resource management, and other important response elements, rather than being a stand-alone activity. The results presented in this paper will provide decision makers and emergency planners at the federal/state/tribal/local level information that can be used to integrate waste management into an overall systems approach to planning and response activities.     

A context-intensive approach to imputation of missing values in data sets from networks of environmental monitors

Although networks of environmental monitors are constantly improving through advances in technology and management, instances of missing data still occur. Many methods of imputing values for missing data are available, but they are often difficult to use or produce unsatisfactory results. I-Bot (short for “Imputation Robot”) is a context-intensive approach to the imputation of missing data in data sets from networks of environmental monitors. I-Bot is easy to use and routinely produces imputed values that are highly reliable. I-Bot is described and demonstrated using more than 10 years of California data for daily maximum 8-hr ozone, 24-hr PM_2.5 (particulate matter with an aerodynamic diameter <2.5 μm), mid-day average surface temperature, and mid-day average wind speed. I-Bot performance is evaluated by imputing values for observed data as if they were missing, and then comparing the imputed values with the observed values. In many cases, I-Bot is able to impute values for long periods with missing data, such as a week, a month, a year, or even longer. Qualitative visual methods and standard quantitative metrics demonstrate the effectiveness of the I-Bot methodology.Implications: Many resources are expended every year to analyze and interpret data sets from networks of environmental monitors. A large fraction of those resources is used to cope with difficulties due to the presence of missing data. The I-Bot method of imputing values for such missing data may help convert incomplete data sets into virtually complete data sets that facilitate the analysis and reliable interpretation of vital environmental 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.