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Human activities such as deforestation, farming, and uncontrolled construction have had a negative impact on mangrove areas in the Reserve. This paper explores how the mangrove area and space have changed since the establishment of the Dongzhaigang Mangrove Nature Reserve, as well as the relationship between this change and the community residents around the Reserve. Six remote sensing images, from 1976 to 2021, were used to obtain wetland data of different ages in the Dongzhaigang Mangrove Forest Nature Reserve in Haikou City. Using the transfer matrix, a questionnaire survey, and principal component analysis, we analyzed the changes in mangrove forests in protected areas and their relationship with surrounding communities over the past 45 years. The results show that: (1) From 1976 to 2021, the area of mangroves in the reserve has increased from 1,395.84 hm2 in 1976 to 1,589.28 hm2 in 2021, showing a trend of "suddenly slowing and rising" during this period, and the proportion of mangrove area has increased from 28.6% in 1976 to 32.6% in 2021, becoming the main wetland type. The largest decline (250 hm2) in the mangrove area was from 1976 to 1985. The largest growth occurred from 2005 to 2018, when the mangrove area increased by 190.08 hm2. (2) From 1976 to 2021, 91.77 hm2 of mangrove wetlands in the study area were converted into other wetlands, 10.71 hm2 were converted into non-wetlands, and 267.71 hm2 of other wetlands and 28.21 hm2 of non-wetlands were converted into mangrove wetlands. In the same period, the transfer targets of mangrove forests in the reserve were muddy beaches (34.32 hm2), rivers (25.81 hm2), marine aquaculture farms (21.06 hm2), other land (10.58 hm2) and flooded wetlands/interiors. Land flats (8.26 hm2); silt beaches (177.41 hm2), rivers (38.18 hm2), other land (28.21 hm2), deltas/sands/sand islands (22.15 hm2), flooding Wetlands/inland tidal flats (21.79 hm2), and paddy fields (6.34 hm2) are the most common areas transferred into mangroves. (3) Fishing income from surrounding community-dwelling individuals was significantly associated with farming, disfiguring forest-digging pond areas, conservation awareness, and mangrove area variation. The factor quality of fishing practices (cos2), values of fishing practices and income, months of fishing, fishing volume, and conservation attitude in the surrounding community residents accounted for more than 0.6 in the principal component analysis of area change of mangrove forests, where the factor quality of fishing practices and fishing income were more than 0.8. The decline in residential fishing frequency corresponds with the shift in household income sources, the occupational move from fishing to wage and service industries, the obvious increase in conservation awareness and the conservation attitude of residents, and the transformation of the mangrove area away from serious destruction to less fragmentation. The contributions of freshwater farms, resident population, number of secondary schools, and village to mangrove distance factors were all greater than 10 and negatively correlated with mangrove area change. Therefore, it is necessary to explore the relationship between mangroves and community residents to obtain a scientific reference for the utilization, protection, restoration, and management of mangroves in the Dongzhaigang Mangrove Nature Reserve.

Climate change in agriculture has important impacts on human life and health, so it is crucial to explore the process of carbon peaking in China's agricultural resource inputs and to provide data support for greenhouse gas (GHG) emission reduction in agriculture. The LMDI model and Tapio decoupling model were used in this study, and the interrelationship between carbon emissions from agricultural resource inputs and agricultural output was analyzed deeply. Meanwhile, global and local Moran's I indices were introduced to further analyze the degree of spatially significant correlation. The results showed that China's total agricultural carbon emissions from 2003 to 2021 showed an"inverted U-shaped"curve, indicating a first growth and then a downward trend, and reached a peak in 2015. Carbon emissions in east China have always been in the first place, followed by central China. However, the Northwest region, which has the lowest carbon emissions among the seven regions, has risen significantly to become the third largest source of agricultural carbon emissions by 2021. The use of fertilizers was the major factor contributing to agricultural carbon emissions, with an average annual contribution of 58%. while pesticides, agricultural films and diesel use were secondary factors. The global Moran' s I index showed significant spatial correlation in agricultural carbon emissions, but the degree of spatial aggregation gradually weakened over time. The local Moran' s I showed that the high-high aggregation was mainly concentrated in east China and central China. According to the results of the LMDI model, agricultural production efficiency, regional industrial structure, and the size of the agricultural labor force play an inhibitory role in the growth of agricultural carbon emissions, of which agricultural production efficiency is the main inhibitory factor, with an annual average emission reduction of 6.475 7 million tons. Agricultural industrial structure, the level of regional economic development, and the level of urbanization, on the other hand, promote the growth of agricultural carbon emissions, and the level of regional economic development is the main factor that promotes the growth of agricultural carbon emissions, with an annual average of about 8.91 million tons. The Tapio decoupling model showed that all regions achieved strong decoupling after 2016, and that agricultural economic growth was accompanied by a reduction in agricultural carbon emissions, which reached a desirable state, indicating that the effect of emission reduction after 2016 was significant. [ABSTRACT FROM AUTHOR]

The water quality of sources in the Huaihe River Basin significantly affects the lives and health of approximately 16.7% of China's population. Identifying and quantifying pollution sources and risks is essential for effective water resource management. This study utilized Monte Carlo simulations and Geodetector to assess water quality and eutrophication, as well as to evaluate the sources of heavy metals and the associated health risks for both adults and children. The results showed that eutrophication of water sources in Huaihe River was severe, with an overall EI value of 37.92; 67.8% of the water sources were classified as mesotrophic and 32.2% classified as eutrophic. Water quality and eutrophication levels in the southern mountainous regions were better than those in the densely populated northern areas. Adults were found to have a higher carcinogenic risk than children, whereas children faced a higher noncarcinogenic risk than adults. Cr presented the highest carcinogenic risk, affecting more than 99.8% of both adults and children at levels above 1 × 10−6 but not exceeding 1 × 10−4. The noncarcinogenic risk from metals did not surpass a level of 1, except for Pb. As was primarily influenced by agricultural activities and transportation, whereas Cd, Cr, and Pb were mainly affected by industrial activities, particularly in local textile industries such as knitting and clothing manufacturing. The analysis demonstrated that the influence of anthropogenic factors on heavy metal distribution was significantly enhanced by indirect natural factors. For example, the explanatory power of Precipitation and Road Network Density on As was 0.362 and 0.189, respectively, whereas their interaction had an explanatory power as high as 0.673. This study indicates that the geodetector method is effective in elucidating the factors influencing heavy metal distribution in water, thereby providing valuable insights into pollution sources in global drinking water. [ABSTRACT FROM AUTHOR]

Complex pollution with high aerosol and ozone concentrations has recently been occurring in several densely populated cities in China, raising concerns about the influence of meteorological factors, including synoptic circulation and local conditions. In this study, comprehensive analyses on the associations between PM2.5, PM10, and O3 and meteorological conditions were conducted based on observations from radar wind profiler, microwave radiometer, automatic weather station, and air quality monitoring sites in Beijing during the spring of 2019. The results showed that the boundary layer height and temperature inversion were negatively (positively) correlated with PM (O3) concentrations, modulating the degree of air pollution. Five identified synoptic patterns were derived using geopotential height data of the ERA5 reanalysis, among which Type 1, characterised by south-westerly prevailing winds with high pressure to the south, was considered to be associated with severe PM and O3 contamination. This indicates that air pollutants originating from southern regions exert a major influence on Beijing through the transportation effect. In addition, high temperature, relative humidity, and low wind velocity exacerbate pollution. Overall, this study provides significant information for understanding the vital roles played by meteorological elements at both the regional and local scales in regulating air contamination during spring in Beijing. [ABSTRACT FROM AUTHOR]