CARBON STORAGE IN HUNAN PROVINCE: MONITORING, MODELING, AND MANAGEMENT STRATEGIES FOR CLIMATE CHANGE MITIGATION

Carbon and nitrogen footprint of double rice production in Southern China

Response of spatiotemporal variability in soil pH and associated influencing factors to land use change in a red soil hilly region in southern China

The effects of increasing sea surface temperature (SST) and aerosol loading in a drought region in Southern China are studied using aerosol optical depth (AOD), low-level cloud cover (LCC), visibility, and precipitation from observed surface data; wind, temperature, specific humidity, and geopotential height from the NCEP–NCAR reanalysis fields; and SST from the NOAA archive data. The results show a warming of the SST in the South China Sea and the Indian Ocean, and a strengthening of the West Pacific Subtropical High (WPSH) in the early summer during the last 40 yr, with the high pressure system extending farther westward over the continent in Southern China. Because the early summer average temperature contrast between the land and ocean decreased, the southwesterly monsoon from the ocean onto mainland China weakened and a surface horizontal wind divergence anomaly occurred over Southern China stabilizing the boundary layer. Thus, less moisture was transported to Southern China, causing a drying trend. Despite this, surface observations show that AOD and LCC have increased, while visibility has decreased. Precipitation has decreased in this region in the early summer, consistent with both the second aerosol indirect effect (reduction in precipitation efficiency caused by the more numerous and smaller cloud droplets) and dynamically induced changes from convective to more stratiform clouds. The second aerosol indirect effect and increases in SST and greenhouse gases (GHG) were simulated separately with the ECHAM4 general circulation model (GCM). The GCM results suggest that both effects contribute to the changes in LCC and precipitation in the drought region in Southern China. The flooding trend in Eastern China, however, is more likely caused by strengthened convective precipitation associated with increases in SST and GHG.

Decomposition analysis of factors affecting carbon dioxide emissions across provinces in China

Current status, spatial features, health risks, and potential driving factors of soil heavy metal pollution in China at province level

A survey of aflatoxin M1 of raw cow milk in China during the four seasons from 2013 to 2015

Facing increasingly severe environmental problems, as the largest developing country, achieving regional carbon emission reduction is the performance of China's fulfillment of the responsibility of a big government and the key to the smooth realization of the global carbon emission reduction goal. Since China's carbon emission data is updated slowly, in order to better formulate the corresponding emission reduction strategy, it is necessary to propose a more accurate carbon emission prediction model on the basis of fully analyzing the characteristics of carbon emissions at the provincial and regional levels. Given this, this paper first calculated the carbon emissions of eight economic regions in China from 2005 to 2019 according to relevant statistical data. Secondly, with the help of kernel density function, Theil index and decoupling index, the dynamic evolution characteristics of regional carbon emissions are discussed. Finally, an improved particle swarm optimization radial basis function (IPSO-RBF) neural network model is established to compare the simulation and prediction models of China's carbon emissions. The results show significant differences in carbon emissions in different regions, and the differences between high-value and low-value areas show an apparent expansion trend. The inter-regional carbon emission difference is the main factor in the overall carbon emission difference. The economic region in the middle Yellow River (ERMRYR) has the most considerable contribution to the national carbon emission difference, and the main contributors affecting the overall carbon emission difference in different regions are different. The number of regions with strong decoupling between carbon emissions and economic development is increasing in time series. The results of the carbon emission prediction model can be seen that IPSO-RBF neural network model optimizes the radial basis function (RBF) neural network, making the prediction result in a minor error and higher accuracy. Therefore, when exploring the path of carbon emission reduction in different regions in the future, the IPSO-RBF neural network model is more suitable for predicting carbon emissions and other relevant indicators, laying a foundation for putting forward more scientific and practical emission reduction plans.

Mosquito-borne diseases have wreaked havoc on human health, with consequences dramatically increasing in recent years. The incidence of mosquito-borne diseases is closely linked to the locations that are chosen for urban development. The aim of this study was to provide characteristics of mosquito breeding sites in northern and southern China and to document the most important arbovirus vectors found in the study area, the evidence generated here is critical for early prevention and control inter ventions. This research involved a random selection of various sites across four provinces, spanning both the northern and southern regions of China. The dwellings and accessible water storage containers in these sites were investigated to detect the presence of immature mosquitoes. Samples were then collected, mosquitoes were nurtured to adulthood, and the species that were present were identified. A total of 1 249 samples were collected during this survey of the mosquito breeding sites. A total of 80 samples were processed using the Chelex method to extract mosquito DNA from all the samples. The ITS2 gene fragment was then amplified by PCR and sequenced. A subsequent BLAST comparison allowed the identification of the mosquito species, and MEGA11 software was used for phylogenetic analysis. The results showed that there were four species of mosquitoes, including Aedes albopictus, Culex quinquefasciatus, Lutzia fuscanus and Armigeres subalbatus. The primary mosquito breeding grounds in the four provinces of China consisted of storm drains, discarded containers, garbage bins, and areas with standing water. Still-water environments, such as rice fields were the primary breeding locations in the southern cities. In contrast, in the northern regions, most breeding occurred at construction sites, and in similar water-prone areas. The most prevalent mosquitoes in the four provinces of China were of the genus Aedes, with a significant number originating from Fujian Province, China. This information sheds light on the migration patterns of mosquitoes and significantly enhances community-based protection measures and mobilization efforts.

China's provincial carbon emission driving factors analysis and scenario forecasting

Emissions from the non-ferrous metal industry are a major source of carbon emissions in China. Understanding the decoupling of carbon emissions from the non-ferrous metal industry and its influencing factors is crucial for China to achieve its "double carbon" goal. Here, we applied the Tapio decoupling model to measure the decoupling status and developmental trends of carbon output and emissions of the non-ferrous metal industry in China. The panel interaction fixed effects model is used to empirically analyze the influencing factors of carbon emissions in China's non-ferrous metal industry. The results show that carbon emissions from China's non-ferrous metal industry have experienced three main states: strong decoupling, growth connection, and negative growth decoupling. The carbon emissions of the non-ferrous metal industry in some eastern and central provinces from 2000 to 2004 were in a negative decoupling state. Most provinces in the western and central regions were either in a strong or weak decoupling state based on the developmental trend of the decoupling state of carbon emissions. However, from 2015 to 2019, the decoupling status of carbon emissions in most provinces in western and central China had a significantly negative, weakly negative, or a negative growth decoupling status. Energy structure, energy intensity, cost, and non-ferrous metal production all have a positive driving effect on carbon emissions in the non-ferrous metal industry. Production had a mitigating effect on carbon emissions in the non-ferrous metal industry between 2010-2014 in the eastern region of China. From the results of our study, we propose policy recommendations to promote a strong decoupling of carbon emissions from the non-ferrous metal industry by improving energy structure, reducing energy intensity, and optimizing production capacity.

ABSTRACTIn this paper, an objective identification technique for regional extreme events (OITREE) is used to identify regional drought events (RDEs) in southern China based on the daily precipitation dataset of 342 stations from 1961 to 2012. Generally RDEs in southern China occur over an entire year, with high frequencies from January to April and peak frequencies in February and March. The spatial distributions of frequency and intensity of RDEs are consistent, with high frequencies of more than 60 and the annual average number of drought days being more than 30 in most regions of southern China east of 105 ° E. The trend distributions of the frequency and intensity of RDEs in southern China are similar, with increasing trends in most western regions and decreasing trends in most eastern regions. The decreasing trends of RDEs in most eastern regions were mainly affected by the weakening of East Asia summer moonsoon (EASM) from the 1960s to the 1990s, which resulted in the summer main rain belts in eastern China moving from North China to southern China and caused the precipitation increasing in eastern regions of southern China from the 1960s to the 1990s. While the increasing trends of RDEs in most western regions were not only affected by the EASM, but also associated with the weakening of the India‐Burma Trough (IBT) that caused less wet air transport to Southwest China and the decrease of precipitation in western regions of southern China.

BackgroundBisalbuminemia is a hereditary and/or acquired abnormality characterized by a double albumin (ALB) band on serum protein electrophoresis. However, there have been no epidemiological investigations of ALB variants in Chinese populations.MethodsThis retrospective study examined 71,963 unrelated subjects from five provinces in southern China. ALB variants were screened by cellulose acetate electrophoresis at pH 8.6 and ALB mutations were confirmed by polymerase chain reaction-DNA sequencing.ResultsThe average incidence of inherited bisalbuminemia in the southern Chinese population was 0.0264% (19/71,963). Thirteen cases showed slow and six showed fast genetic variants on cellulose acetate electrophoresis. Four kinds of ALB variants were identified: proalbumin Lille (p.Arg23His), ALB Castel di Sangro (p.Lys560Glu), ALB Fukuoka-1 (p.Asp587Asn), and a novel ALB Wuxi (p.Lys562Glu). The gene frequency of ALB variants in the Wuxi region (0.126%, 13/10,297) was significantly higher than in other regions in southern China, and 90.9% (10/11) of cases of proalbumin Lille were also found in the Wuxi region.ConclusionsThis study provides the first report of the detailed prevalence and molecular characterization of ALB variants in southern China. Compared with other areas of China, Wuxi had a different pattern of ALB variants and a high prevalence of proalbumin Lille.

China can be regarded as a group of disparate economies, so the responsibilities of reduction have to be decided by considering different development stages over the provinces as well as reaching fairness of allocation. This study analyzed factors that influenced carbon dioxide emission changes due to energy-related consumption of 30 mainland provinces in China from 2005 to 2011, which was to promote carbon emission reduction and allocate carbon emission allowance. First, the Logarithmic Mean Divisia Index (LMDI) technique was adopted to decompose the changes in carbon emissions at the provincial level into five effects that were carbon coefficient, energy structure, energy intensity, economic output and population-scale effect. Next, according to the LMDI decomposition results, the overall contributions of various decomposition factors were calculated and applied to distribute carbon emission allowance over 30 provinces in China in 2020. The total effects of economic output, population-scale effect and energy structure on carbon emissions were positive, whereas the overall effect of energy intensity was negative. The allocation of carbon emission allowance can facilitate decision makers to reconsider the emission reduction targets and some related policies.

A provincial lateral carbon emissions compensation plan in China based on carbon budget perspective.

Decoupling relationship between economic output and carbon emission in the Chinese construction industry