Vogelclapp3529

Improving the green total-factor productivity (GTFP) is a key measure to coordinate industrial development and environmental protection in China. This study adopts the biennial Malmquist-Luenberger (BML) productivity index to estimate the GTFP change of China's 34 industrial subsectors covering the period 2005-2015. Subsequently, fixed-effect panel quantile regression is applied to analyze the heterogeneous effects of eight selected influencing factors on China's industrial GTFP change. The results show that China's overall industrial GTFP exhibited an increasing trend during the study period and varied greatly in different sub-sectors. Dexamethasone Moreover, technological innovation rather than efficiency promotion was the main contributor to the improvement of industrial GTFP in China. The impact of the scale structure (SS) was significantly positive across the quantiles and maintained a slightly downward trend. The impact of the property rights structure (PTS) was significantly negative and showed an increasing trend across the quantiles. The impact of the energy intensity (EI) slightly increased and was significantly negative at most quantiles. The energy consumption structure (ECS) exhibited an increasing trend and had a significantly negative effect at the middle quantiles. Technological innovation (TI) exerted a significantly positive effect and displayed a downward trend across the quantiles, and it was the most important factor to drive industrial GTFP growth. The "pollution halo" hypothesis and the Porter hypothesis were both verified with a certain range from the analysis of foreign direct investment (FDI) and environmental regulation (ER), as well as the interaction between ER and TI. Our results stress the importance of the heterogeneous effects of these influencing factors on different quantile subsectors when formulating the related measures and policies.Following the outbreak of Severe Acute Respiratory Syndrome CoronaVirus 2 (SARS-CoV-2) last December 2019 in China, Italy was the first European country to be severely affected, with the first local case diagnosed on 20 February 2020. The virus spread quickly, particularly in the North of Italy, with three regions (Lombardy, Veneto and Emilia-Romagna) being the most severely affected. These three regions accounted for >80% of SARS-CoV-2 positive cases when the tight lockdown was established (March 8). These regions include one of Europe's areas of heaviest air pollution, the Po valley. Air pollution has been recently proposed as a possible risk factor of SARS-CoV-2 infection, due to its adverse effect on immunity and to the possibility that polluted air may even carry the virus. We investigated the association between air pollution and subsequent spread of the SARS-CoV-2 infection within these regions. We collected NO2 tropospheric levels using satellite data available at the European Space Agency before the lockdown. Using a multivariable restricted cubic spline regression model, we compared NO2 levels with SARS-CoV-2 infection prevalence rate at different time points after the lockdown, namely March 8, 22 and April 5, in the 28 provinces of Lombardy, Veneto and Emilia-Romagna. We found little association of NO2 levels with SARS-CoV-2 prevalence up to about 130 μmol/m2, while a positive association was evident at higher levels at each time point. Notwithstanding the limitations of the use of aggregated data, these findings lend some support to the hypothesis that high levels of air pollution may favor the spread of the SARS-CoV-2 infection.The accumulation of anthropogenic chemical substances in aquatic organisms is an immensely important issue from the point of view of environmental protection. In the context of the increasing number and variety of compounds that may potentially enter the environment, there is a need for efficient and reliable solutions to assess the risks. However, the classic approach of testing with fish or other animals is not sufficient. Due to very high costs, significant time and labour intensity, as well as ethical concerns, in vivo methods need to be replaced by new laboratory-based tools. So far, many models have been developed to estimate the bioconcentration potential of chemicals. However, most of them are not sufficiently reliable and their predictions are based on limited input data, often obtained with doubtful quality. The octanol-water partition coefficient is still often used as the main laboratory tool for estimating bioconcentration. However, according to current knowledge, this method can lead to very unreliable results, both for neutral species and, above all, for ionic compounds. It is therefore essential to start using new, more advanced and credible solutions on a large scale. Over the last years, many in vitro methods have been newly developed or improved, allowing for a much more adequate estimation of the bioconcentration potential. Therefore, the aim of this work was to review the most recent laboratory methods for assessing the bioconcentration potential and to evaluate their applicability in further research.Antibiotic resistance represents the greatest challenge to healthcare systems around the world. As antibiotic resistance genes (ARGs) are shed in faeces, many studies have focused on how wastewater effluent contributes to ARG pollution in rivers. However, small urban streams and bathing waters not impacted by treated wastewater have received little attention though they may be important reservoirs of ARGs. The main objective of this study was to assess the extent to which ARG and faecal pollution impact small urban streams and bathing waters and to determine if there is a relationship between these contaminants. For one year, bi-monthly water samples were collected from two urban streams and Dublin city's three designated bathing waters. The Liffey Estuary, that receives treated wastewater, was also sampled. The sul1, tet(O), qnrS, blaTEM, blaSHV and blaCTX-M ARGs were quantified. E. coli and intestinal enterococci levels were determined and the source of faecal pollution (human, dog, gull) quantified by microbial source tracking. Our results show that the Liffey Estuary, the urban streams and the bathing waters are highly impacted by ARGs and human faeces. There were clear correlations between all of the studied faecal indicators and ARGs in the Liffey Estuary. In the urban streams relationships were observed for only some of the ARGs and faecal indicators, which is likely a result of non-continuous sewage leaks and overflows to the streams. Similarly, only some ARGs correlated with faecal indicators in the urban bathing waters. The source of ARGs in the bathing waters is likely to be multifaceted as we detected sporadic dog and gull faecal markers. This study demonstrates that small urban streams and bathing waters are reservoirs of ARGs and that they may pose a previously unrecognised public health risk as they have the potential to transmit enteric pathogens and antibiotic resistance determinants.Rice production systems are the largest anthropogenic wetlands on earth and feed more than half of the world's population. However, they are also a major source of global anthropogenic greenhouse gas (GHG) emissions. Several agronomic strategies have been proposed to improve water-use efficiency and reduce GHG emissions. The aim of this study was to evaluate the impact of water-saving irrigation (alternate wetting and drying (AWD) vs. soil water potential (SWP)), contrasting land establishment (puddling vs. reduced tillage) and fertiliser application methods (broadcast vs. liquid fertilisation) on water-use efficiency, GHG emissions and rice yield. The experiment was laid out in a randomised complete block design with eight treatments (all combinations of the three factors) and four replicates. AWD combined with broadcasting fertilisation was superior to SWP in terms of maintaining yield. However, seasonal nitrous oxide (N2O) emissions were significantly reduced by 64% and 66% in the Broadcast-SWP and Liquid reduce water use, N loss via N2O emissions, and CH4 emissions.Improving energy efficiency and building a low-carbon economy are the important ways to resolve the current contradiction between economic growth and the environment in China. In this paper, we use the super-efficiency Slack-Based Measure model (super-efficiency SBM model) to measure the energy efficiency of 30 provinces in China, and then conduct Empirical Orthogonal Function (EOF) to analyze its spatial-temporal evolution. Moreover, we use the Geographically and Temporally Weighted Regression (GTWR) to analyze the spatial-temporal heterogeneity of its driving factors. The results show that (i) during the sample period, China's energy efficiency shows a rapidly upward trend, accompanied by the gradually strengthening spatial pattern of the "eastern>central>western"; (ii) the spatial pattern of the "southern>northern" exhibited by the annual growth rate of energy efficiency experienced a process of weakening first and then gradually strengthening; (iii) the influencing effects of market openness, relative energy price and industry structure on energy efficiency have no significant heterogeneity as a whole; (iv) the effects of environmental regulation intensity, the marketization level, the technical level, energy consumption structure and economic development level have significant spatial heterogeneity, and the effects of energy conservation and emission reduction policies has significant temporal heterogeneity.Persistent organic pollutants (POP) are toxic substances for wildlife and people. The Kemp's Ridley sea turtle Lepidochelys kempii is an endangered species with limited distribution in the Gulf of Mexico (GM), a marine ecosystem that has been perturbed by a variety of anthropogenic activities. In this work, the concentrations of ten organochlorine pesticides (OP), eight polychlorinated biphenyls (PCB), and atrazine were determined in the plasma of Kemp's Ridley sea turtles that nest in Playa Rancho Nuevo Sanctuary, Tamaulipas, Mexico. Seventy-nine blood samples were collected from female turtles during the 2015-2016 nesting season. Samples were extracted with a focalized ultrasonic sound technique and analyzed through Gas Chromatography coupled to a Mass Spectrometer. POP with the highest percentage of detection were atrazine > PCB 52 > PCB 153 > DDE > alpha endosulfan > DDD > alpha HCH > DDT. There is no linear correlation between the detected POP levels in the Kemp's Ridley sea turtle plasma and its curve carapace length (CCL). When comparing 2015 and 2016 POP concentrations, there were statistically significant differences in atrazine (p less then 0.05, R2 = 0.069), PCB 52 (p less then 0.05, R2 = 0.0051) and ∑POP (p less then 0.05, R2 = 0.0001) and, no statistically significant differences in alpha endosulfan (p less then 0.05, R2 = 0.0294), DDE (p less then 0.05, R2 = 0.0315) and PCB 153 (p less then 0.05, R2 = 0.0036). The reported POP values of this work are one of the few registered for Kemp's Ridley sea turtle in the GM and the first for atrazine levels. These levels were higher than those reported for other sea turtle species from America, Africa, and Europe, which demonstrates a deteriorated health status of the GM marine ecosystem.