How does natural resource dependence influence carbon emissions? The role of environmental regulation

Sustainable economic development and green recovery in the post-COVID-19 era in China requires consideration of natural resource dependence (NRD) and environmental regulation (ER) of CO2 emissions. Based on panel data covering 2008 and 2018 in China, this paper explores the impacts of NRD on carbon emissions and the moderating role of ER. In addition, the heterogeneity, asymmetry, and mediating mechanism are investigated in this study. Following are the main conclusions: (1) Decreasing the dependence on natural resources and strengthening ER can effectively cut down CO2 emissions, and the enhanced ER can reduce the contribution of NRD to CO2 emissions;(2) the positive influence of NRD on carbon emissions are consistent in various regions, while the influence of ER on CO2 emissions is negative in areas with high levels of NRD;(3) the reduced natural resources dependence can accelerate the carbon emissions reduction process indirectly by causing a reduction in China's total energy demand and coal consumption and accelerating the green technological innovation. The findings present several policy recommendations for achieving carbon emissions reduction.

[Analysis on cluster cases of COVID-19 in Tianjin].

Objective: To understand the characteristics of clusters of COVID-19 cases in Tianjin, and provide epidemiological evidence for the prevention and control of COVID-19. Methods: The data of all the COVID-19 cluster cases in Tianjin, reported by 22 February 2020, were collected to analyze the characteristics of different types of the clusters. Results: A total of 115 COVID-19 cases were reported in 33 clusters in Tianjin included 28 family clusters (71 cases), 1 work place cluster (10 cases), 3 transport vehicle clusters (8 cases) and 1 public place cluster (26 cases). Family clusters were caused by the cases from the working place or public place clusters. Numbers of secondary cases of family clusters was between 1 to 7, the median number was 2. The interval from onset to diagnosis for the first case was longer than those of other cases in the familial clusters (Z=-2.406, P=0.016). The median of incubation period of the public place clusters was 2 days. The intervals from onset to diagnosis were significant different among the family, working place and public place clusters (H=8.843, P=0.012), and also significant differences in onset time among the secondary cases (H=16.607, P=0.000). Conclusions: In the surveillance of COVID-19 epidemic, special attention should be paid to places where clustering are prone to occur, and the epidemiological investigation should be carried out timely to confirm the cluster. To prevent the transmission of COVID-19, the close contacts of the patients should be transferred to an assigned observation place on time for single room isolation. The awareness of COVID-19 prevention is low in some rural areas, reflected by many mass gathering activities and delayed medical care seeking after onset. It is necessary to strengthen the health education and take control measures in early period of epidemic.

[Epidemiological characteristics of confirmed COVID-19 cases in Tianjin].

Objective: To investigate the clinical and epidemiological characteristics of 135 confirmed cases of COVID-19 in Tianjin. Methods: The clinical and epidemiological data of 135 cases of COVID-19 in Tianjin were collected, and the data were analyzed with descriptive method. The factors influencing the severity of the illness were analyzed. Results: Among the 135 COVID-19 cases, 72 were males and 63 were females, the age of the cases was (48.62±16.83) years, and the case fatality rate was 2.22%. Local transmission caused 74.81% of the cases. A total of 33 clusters occurred, involving 85.92% of all COVID-19 cases. The median of the incubation period of COVID-19 was 6.50 days, the average generation interval was 5 days, and the household secondary transmission rate was 20.46%. Fever was the main symptom (78.63%), followed by cough (56.48%). Multivariate regression analysis indicated that age (OR=1.038, 95%CI: 1.010-1.167) and the number of chronic underlying diseases (OR=1.709, 95%CI: 1.052-2.777) were the risk factors of severe illness. Conclusions: Fever was the main symptom at the early phase of COVID-19 in Tianjin, and the local cluster cases accounted for high proportion in confirmed COVID-19 cases reported in Tianjin. Severe illness was prone to occur in people with old age and multi underlying diseases. Strict isolation of close contacts and intensive care of high-risk groups are the main measures to reduce the morbidity and case fatality of COVID-19.

[Epidemiological investigation on a cluster epidemic of COVID-19 in a collective workplace in Tianjin].

Objective: To investigate and analysis the epidemiological characteristics of a cluster epidemic of COIVD-19 in a collective workplace in Tianjin, evduate the prevention and control measures based on limited evidence and experience in early period of COVID-19 epidemic. Methods: Descriptive research method was used to describe the distribution and other epidemiological characteristics of the cluster cases of COVID-19. Results: Since the onset of the first index case on January 15, ten confirmed COVID-19 cases had occurred in the workplace, and the epidemic had spread from the workplace to 4 families, infecting 7 family members. The median age of 17 cases was 55 (19-79) years. All the 10 employee cases were males, and in the family cases, 3 were males and 4 were females. Of the employee cases, 8 worked in CW workshop and 2 worked in administrative office building. The median exposure-onset interval of all the cases was 4 days, and the median exposure-onset interval was 4.5 days in the employee cases and 4 days in the family cases. The median onset-medical care seeking interval was 4 days in the non-isolated cases, 2.5 days in the cases with home isolation after onset, and 0.5 day in the cases with home isolation before onset. Conclusions: The clustering of COVID-19 cases was observed in this workplace in Tianjin, which affected 4 families. In the early stage of the epidemic, accurate and rapid blocking and control measures can completely prevent the large-scale spread of COVID-19.