This paper explores long-run and causal effects of financial development, real growth, urbanization, gross capital formation and energy consumption on CO2 emissions in Thailand by utilizing recent econometric techniques. The study employs ARDL technique to examine the long and short run interconnection between CO2 emissions and the regressors. Furthermore, we employ the FMOLS, DOLS and CCR as a robustness check to the ARDL long-run estimator. The study use time-series data spanning from 1971 to 2016. The study also utilizes the wavelet coherence technique to collect information on the association and causal interrelationship among these economic variables at different frequencies and timeframes in Thailand. The study objectives are structured to answer the following questions: (a) does the selected macroeconomic indicators impact CO2 emissions in Thailand? (b) if so, why? Findings reveal; (i) Negative and insignificant link between CO2 emissions and urbanization. (ii) GDP growth affects CO2 emissions positively. (iii) The interconnection between CO2 emissions and energy usage is positive. (iv) Gross capital formation impact CO2 emissions positively. (v) Positive interconnection exists between financial development and CO2 emissions in Thailand. Additionally, the wavelet coherence result provides a supportive evidence for the ARDL long run result. Based on these findings, policy directions were suggested.

Though, the attention of researchers on exploring the impact of economic policy uncertainty on carbon emissions is on increase, however, the impact of different types of economic policy uncertainty remains unexplored. Thus, this study investigates the impact of different types of economic policy uncertainty on carbon emissions in Japan. A monthly data from 1987M1 to 2019M12 was used, while the FMOLS, DOLS, CCR and ARDL estimators were employed for examining the cointegration among the variables, as well as the long- and short-run relationship between types of economic policy uncertainty and carbon emissions. The study findings revealed a long-run cointegration among energy consumption, per capita income, fiscal, exchange rate, monetary, and trade policy uncertainties and carbon emissions. Moreover, this study found energy consumption, exchange rate, monetary, and trade policy uncertainties to contribute significantly to the increase of carbon emissions in Japan. Finally, this study suggests that environmental policy makers in Japan should take into account the economic policy uncertainty so as to promote robust information for climate policy that will be targeted at ameliorating the carbon emissions in Japan.

Nitrogen (N) is an essential nutrient but may become a pollution source in the environment when the N concentration exceeds a certain threshold for humans and nature. Nitrate is a major N species in river water with notable spatial and temporal variations under the influences of natural factors and anthropogenic N inputs. We analyzed the relationship between riverine N (focusing on nitrate) concentration and various factors (land use, climate, basin topography, atmospheric N deposition, agricultural N sources and human-derived N) in 104 rivers located throughout the Japanese Archipelago except small remote islands. We aimed to better understand processes and mechanisms to explain the spatial and temporal changes in riverine nitrate concentration. A publicly available river water quality database observed in the 1980s (1980–1989) and 2000s (2000–2009) was used. This study is the first to evaluate the long-term scale of 20 years in the latter half of Japan's economic growth period at the national level. A geographic information system (GIS) was employed to determine average values of each variable collected from multiple sources of statistical data. We then performed regression analysis and structural equation modeling (SEM) for each period. The forestland area influenced by the basin topography, climate (i.e., air temperature) and other land uses (i.e., farmland and urban area) played a major role in decreasing nitrate concentrations in both the 1980s and 2000s. Atmospheric N deposition (especially N oxides) and agricultural N sources (fertilizer and manure) were also significant variables regarding the spatial variations in riverine nitrate concentrations. The SEM results suggested that human-derived N (via food consumption) intensified by demographic shifts during the 2000s increased riverine nitrate concentrations over other variables within the context of spatial variation. These findings facilitate better decision making regarding land use, agricultural practices, pollution control and individual behaviors toward a sustainable society.

Freshwater ecosystems are negatively impacted by various pollutants, from agricultural, urban and industrial wastewater, with metals being one of the largest concerns. Moreover, freshwater ecosystems are often affected by alien species introductions that can modify habitats and trophic relationships. Accordingly, the threat posed by metals interacts with those by alien species, since the latter can accumulate and transfer these substances across the food web to higher trophic levels. How metals transfer within such communities is little studied. We analysed the concentration of 14 metals/metalloids (Al, As, Cd, Co, Cr, Cu, Fe, Hg, Mg, Mn, Ni, Pb, Se, Zn, hereafter ‘metal(s)’) of eight fish and three crustacean species co-existing in the Arno River (Central Italy), most of which were alien. To assess the pathway of contaminants within the community, we coupled metal analysis with carbon and nitrogen stable isotope analysis derived from the same specimens. Crustaceans showed higher metal concentration than fish, except for Cd, Hg and Se that were higher in fish. We found evidence of trophic transfer for six metals (Cd, Cr, Hg, Mg, Se, Zn). Additionally, ontogenetic differences and differences among various fish tissues (muscle, liver, and gills) were found in metals concentration. Considerable biomagnification along the trophic chain was found for Hg, while other metals were found to biodilute. Using stable isotopes and Hg as a third diet tracer, we refined the estimations of consumed preys in the diet previously reconstructed with stable isotope mixing models. Alien species reach high biomass and can both survive to and accumulate high pollutants concentrations, potentially posing a risk for their predators and humans. A combined effect of environmental filtering and increased competition may potentially contribute to the disappearance of native species with lower tolerances.

Decades of intensive discharge from industrial activities into coastal systems has resulted in the accumulation of a variety of persistent organic pollutants (POPs) in marine waters and sediments, having detrimental impacts on aquatic ecosystems and the resident biota. POPs are among the most hazardous chemicals originating from industrial activities due to their biotoxicity and resistance to environmental degradation. Bacterial communities are known to break down many of these aromatic compounds, and different members of naturally occurring bacterial consortia have been described to work in syntrophic association to thrive in heavily contaminated waters and sediments, making them potential candidates as bioindicators of environmental pollution. In this study environmental, sampling was combined with chemical analysis of pollutants and high-resolution sequencing of bacterial communities using Next Generation Sequencing molecular biology tools. The aim of the present study was to describe the bacterial communities from marine sediments containing high loads of POPs and to identify relevant members of the resident microbial communities that may act as bioindicators of contamination. Marine sediments were collected from a coastal bay area of the Baltic Sea historically influenced by intense industrial activity, including metal smelting, oil processing, and pulp and paper production. Different types of POPs were detected at high concentrations. Fiberbank sediments, resulting from historic paper industry activity, were found to harbour a clearly distinct bacterial community including a number of bacterial taxa capable of cellulolytic and dechlorination activities. Our findings indicate that specific members of the bacterial communities thrive under increasing levels of POPs in marine sediments, and that the abundances of certain taxa correlate with specific POPs (or groups), which could potentially be employed in monitoring, status assessment and environmental management purposes.

Polychlorinated biphenyls (PCBs) are one of the most refractory organic environmental pollutants that ubiquitous existence in nature. Due to the polymorphism of their metabolic pathway and corresponding downstream metabolites, PCBs’ toxicities are complicated and need extended investigation. In the present study, we discovered a novel regulatory mechanism of PCB quinone metabolite-driven programmed cell death (PCD), namely, necroptosis. We first confirmed that PCB quinone induces cancerous HeLa and MDA-MB-231 cells necroptosis via the phosphorylation of mixed lineage kinase domain-like MLKL (p-MLKL). Then, we found that PCB quinone-stimulated p-MLKL enhances exosome biogenesis and secretion. Exosome interacts with p-MLKL and releases p-MLKL to the outside of the cell, and ultimately alleviating PCB quinone-induced necroptosis. The inhibition of exosome secretion by GW4869 significantly elevated necroptotic level, indicating the establishment of a short negative feedback loop of MLKL-exosome secretion upon PCB quinone challenge. Since exosome-mediated signaling showed great implications in various human diseases, this work may provide a new mechanism for PCBs-associated toxicity.

Crude oil pollution is a global environmental concern since it persists in the environment longer than most conventional carbon sources. In December 2014, the hyper-arid Evrona Nature Reserve, Israel, experienced large-scale contamination when crude oil spilled. The overarching goal of the study was to investigate the possible changes, caused by an accidental crude oil spill, in the leaf reflectance and biochemical composition of four natural habitat desert shrubs. The specific objectives were (1) to monitor the biochemical properties of dominant shrub species in the polluted and control areas; (2) to study the long-term consequences of the contamination; (3) to provide information that will assist in planning rehabilitation actions; and (4) to explore the feasibility of vegetation indices (VIs), along with the machine learning (ML) technique, for detecting stressed shrubs based on the full spectral range. Four measurement campaigns were conducted in 2018 and 2019. Along with the various stress indicators, field spectral measurements were performed in the range of 350–2500 nm. A regression analysis to examine the relation of leaf reflectance to biochemical contents was carried out, to reveal the relevant wavelengths in which polluted and control plants differ. Vegetation indices applied in previous studies were found to be less sensitive for indirect detection of long-term oil contamination. A novel spectral index, based on indicative spectral bands, named the “normalized blue-green stress index” (NBGSI), was established. The NBGSI distinguished significantly between shrubs located in the polluted and in the control areas. The NBGSI showed a strong linear correlation with pheophytin a. Machine learning classification algorithms obtained high overall prediction accuracy in distinguishing between shrubs located in the oil-polluted and the control sites, indicating internal component differences. The findings of this study demonstrate the efficacy of indirect and non-destructive spectral tools for detecting and monitoring oil pollution stress in shrubs.

In this report, we investigated the accumulation of heavy metals in the lizard Microlophus atacamensis, in three coastal areas of the Atacama Desert, northern Chile. We captured reptiles in a non-intervened area (Parque Nacional Pan de Azúcar, PAZ), an area of mining impact (Caleta Palitos, PAL) and an active industrial zone (Puerto de Caldera, CAL). Our methods included a non-lethal sampling of reptiles’ tails obtained by autotomy and a few sacrificed animals to perform a stomach contents analysis. The concentrations of lead, copper, nickel, zinc and cadmium were measured by atomic absorption spectrophotometry in both soil and prey and compared to those recorded in the lizards’ tails. Data obtained from lizard tails captured in PAL showed significantly high concentrations of Pb, Cu, Ni, and Zn compared to the other two sites PAZ and CAL. We did not find statistically significant differences among PAZ, PAL and CAL soils, probably due to the similar geological composition of the sites. However, the regional background values for Pb indicate contamination or at least metal enrichment in soils of the three sites, for Cu the global background values indicate contamination for the three sites, and for Cd both the regional and global backgroud values show high values. The analysis of the stomach content showed differences in the food sources of the lizards among the sites studied. The concentration of heavy metal in lizard tissues versus prey delivered values of the Trophic Transfer Factor higher than one (1), suggesting that food may be a primary source of metals in the tissues of M. atacamensis. Calculations of the Bioaccumulation Factor (BAF) and the Ecological Risk (IR) resulted in values higher than one (1) indicating the relevance of this process in the sites studied. In this article, we report relationships between environmental contaminants, mainly putative preys, and concentrations found in lizard tails, which is more substantial in areas with historical heavy metal contamination such as PAL where the non-lethal technique developed in this research suggests a process of metal bioaccumulation in M. atacamensis.

Arsenic (As) is a ubiquitous metalloid that is highly toxic to all living organisms. When grown in As-contaminated soils, plants may accumulate significant amounts of As in the grains or edible shoot parts which then enter a food chain. Plant growth and development per se are also both affected by arsenic. These effects are traditionally attributed to As-induced accumulation of reactive oxygen species (ROS) and a consequent lipid peroxidation and damage to cellular membranes. However, this view is oversimplified, as As exposure have a major impact on many metabolic processes in plants, including availability of essential nutrients, photosynthesis, carbohydrate metabolism, lipid metabolism, protein metabolism, and sulfur metabolism. This review is aimed to fill this gap in the knowledge. In addition, the molecular basis of arsenic uptake and transport in plants and prospects of creating low As-accumulating crop species, for both agricultural productivity and food safety, are discussed.