Suchergebnisse

Despite the remarkable development in its fishery sector, the penetration rate of fishery insurance in China is considerably low. This paper examines the key factors that contribute to the poor performance of fishery insurance, in particular aquaculture insurance, in China. The double-bounded dichotomous choice contingent valuation method (DB DCCVM) is used to investigate fish farmers' willingness to pay (WTP) for an insurance program, based on a survey of 1280 fish farmers in three coastal cities in China. The results indicate that fish farmers' decisions on adoption of an insurance scheme depend on various factors, among which magnitude of loss, fish farmers' awareness toward insurance and their education all have a positive impact. However, income and farming years are more likely to have a negative effect. In addition, the mean WTP for aquaculture insurance is estimated to be CNY 579 (US$ 90.05) 2 per household, which is equivalent to 1.5% of fish farmers' mean annual income. These results provide several policy implications for not only the Chinese government but also researchers as well as insurance companies.

China's commitment to building the country into a maritime power has seen a rapid growth in its marine economy in recent years. In the meantime, increasing concern over environmental degradation and sustainability has made the government to shift attention from marine development to marine ecosystem protection by formulating more environmental policies. There has been a long-standing debate between traditional views and well-known Porter Hypothesis (PH) over the impact of environmental regulation on the competitiveness and efficiencies of firms and industries. Aiming to obtain empirical evidence of the possible impact, this paper uses the Super-Efficiency Slacks-Based Measure (SE-SBM) model to calculate economic efficiency considering undesired outputs and the system Generalized Moment Method (GMM) to examine the relationship between the two variables, using data from 11 provinces and cities in China's coastal areas. The results seem to support the presence of the PH in Chinese marine economy and show a U-shaped relationship between environmental regulation and economic efficiency. In addition, it is also found optimization of industrial structure can impose a positive effect on economic efficiency, while capital investment and science and technological innovations may have a negative effect. Based on these results, the paper puts forward some recommendations for policy makers.

During the COVID-19 pandemic lockdown, the number of people shopping online has increased worldwide, and New Zealand is no exception. To date, little is known about the online shopping behaviours of New Zealanders in a pandemic environment. This paper provides the first attempt by exploring the factors affecting online shopping frequency in New Zealand, a country widely regarded as a paragon of excellence for containing the COVID-19 pandemic. A Poisson regression model is utilized to analyze data collected through an online survey between July and November 2020. The empirical results show that people's online shopping frequency is positively affected by payment convenience, competitive pricing, living in the city, and the number of children. The perceived effectiveness of the government's action in combating COVID-19, having poor past online shopping experiences, and being married reduce online shopping frequency.

The China-Pakistan Economic Corridor (CPEC) project passes through the Karakoram Highway in northern Pakistan, which is one of the most hazardous regions of the world. The most common hazards in this region are landslides and debris flows, which result in loss of life and severe infrastructure damage every year. This study assessed geohazards (landslides and debris flows) and developed susceptibility maps by considering four standalone machine-learning and statistical approaches, namely, Logistic Regression (LR), Shannon Entropy (SE),Weights-of-Evidence (WoE), and Frequency Ratio (FR) models. To this end, geohazard inventories were prepared using remote sensing techniques with field observations and historical hazard datasets. The spatial relationship of thirteen conditioning factors, namely, slope (degree), distance to faults, geology, elevation, distance to rivers, slope aspect, distance to road, annual mean rainfall, normalized difference vegetation index, profile curvature, stream power index, topographic wetness index, and land cover, with hazard distribution was analyzed. The results showed that faults, slope angles, elevation, lithology, land cover, and mean annual rainfall play a key role in controlling the spatial distribution of geohazards in the study area. The final susceptibility maps were validated against ground truth points and by plotting Area Under the Receiver Operating Characteristic (AUROC) curves. According to the AUROC curves, the success rates of the LR, WoE, FR, and SE models were 85.30%, 76.00, 74.60%, and 71.40%, and their prediction rates were 83.10%, 75.00%, 73.50%, and 70.10%, respectively; these values show higher performance of LR over the other three models. Furthermore, 11.19%, 9.24%, 10.18%, 39.14%, and 30.25% of the areas corresponded to classes of very-high, high, moderate, low, and very-low susceptibility, respectively. The developed geohazard susceptibility map can be used by relevant government officials for the smooth implementation of the CPEC project at the regional scale.

City-level CO2 emissions inventories are foundational for supporting the EU's decarbonization goals. Inventories are essential for priority setting and for estimating impacts from the decarbonization transition. Here we present a new CO2 emissions inventory for 116,572 municipal and local government units in Europe. The inventory spatially disaggregates the national reported emissions, using 9 spatialization methods to distribute the 167 line items detailed in the UN's Common Reporting Framework. The novel contribution of this model is that results are provided per administrative jurisdiction at multiple administrative levels using a new spatialization approach. All data from this study is available along with an interactive map of results at

This study seeks to estimate how global supply chain relocates emissions of tropospheric ozone precursors and its impacts in shaping ozone formation. Here we show that goods produced in China for foreign markets lead to an increase of domestic non-methane volatile organic compounds (NMVOCs) emissions by 3.5 million tons in 2013; about 13% of the national total or, equivalent to half of emissions from European Union. Production for export increases concentration of NMVOCs (including some carcinogenic species) and peak ozone levels by 20-30% and 6-15% respectively, in the coastal areas. It contributes to an estimated 16,889 (3,839-30,663, 95% CI) premature deaths annually combining the effects of NMVOCs and ozone, but could be reduced by nearly 40% by closing the technology gap between China and EU. Export demand also alters the emission ratios between NMVOCs and nitrogen oxides and hence the ozone chemistry in the east and south coast.

This study seeks to estimate how global supply chain relocates emissions of tropospheric ozone precursors and its impacts in shaping ozone formation. Here we show that goods produced in China for foreign markets lead to an increase of domestic non-methane volatile organic compounds (NMVOCs) emissions by 3.5 million tons in 2013; about 13% of the national total or, equivalent to half of emissions from European Union. Production for export increases concentration of NMVOCs (including some carcinogenic species) and peak ozone levels by 20-30% and 6-15% respectively, in the coastal areas. It contributes to an estimated 16,889 (3,839-30,663, 95% CI) premature deaths annually combining the effects of NMVOCs and ozone, but could be reduced by nearly 40% by closing the technology gap between China and EU. Export demand also alters the emission ratios between NMVOCs and nitrogen oxides and hence the ozone chemistry in the east and south coast.

We are grateful to Hanne Nørgaard Nielsen, Christina Aaby Svendsen, Jacob Dyring Jensen, Birthe S. Rosenqvist Lund, Kate Vina Vibefeldt, Inge Marianne Hansen, Gunhild Larsen, Hanne Mordhorst, and Carsten Bidstrup for technical assistance. We also thank Jeffrey Edward Skiby for internal review. This study has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement no. 643476 (COMPARE), the World Health Organization, The Villum Foundation (VKR023052), and The Novo Nordisk Foundation (NNF16OC0021856: Global Surveillance of Antimicrobial Resistance). ; Altres ajuts: VF/VKR023052 ; Altres ajuts: GSAR/NNF16OC0021856 ; Antimicrobial resistance (AMR) is a serious threat to global public health, but obtaining representative data on AMR for healthy human populations is difficult. Here, we use metagenomic analysis of untreated sewage to characterize the bacterial resistome from 79 sites in 60 countries. We find systematic differences in abundance and diversity of AMR genes between Europe/North-America/Oceania and Africa/Asia/South-America. Antimicrobial use data and bacterial taxonomy only explains a minor part of the AMR variation that we observe. We find no evidence for cross-selection between antimicrobial classes, or for effect of air travel between sites. However, AMR gene abundance strongly correlates with socio-economic, health and environmental factors, which we use to predict AMR gene abundances in all countries in the world. Our findings suggest that global AMR gene diversity and abundance vary by region, and that improving sanitation and health could potentially limit the global burden of AMR. We propose metagenomic analysis of sewage as an ethically acceptable and economically feasible approach for continuous global surveillance and prediction of AMR.