Huanjing Kexue/Environmental Science最新文献

{"title":"[Effects of Altitude on Airborne Bacteria and Potential Pathogenic Bacteria： A Case of Shigatse of Xizang].","authors":"Pei-Qin Liu, Meng-Ke Gao, Jian-Qiang Su, Hu Li","doi":"10.13227/j.hjkx.202309061","DOIUrl":"https://doi.org/10.13227/j.hjkx.202309061","url":null,"abstract":"<p><p>Airborne microbes are affected by natural environmental factors and have become a global issue due to their potential threat to human health. To explore the effects of altitude on the communities of microbes and potential pathogenic bacteria, we sampled airborne microbes and soils at sites with different altitudes in Shigatse of Xizang. The results showed a significant difference in bacterial communities between air and soil and a decrease in the contribution of soil to airborne bacteria from the sites with a lower altitude to the sites with a higher altitude. The Chao1 indexes of airborne bacteria were significantly higher in the sites with a lower altitude compared to those with a higher altitude, and the bacterial Bray-Curtis distances between sites with a lower altitude were significantly lower than those between sites with a lower altitude and high altitude. These results indicated that altitude would affect the community patterns of airborne bacteria, and the transport of air would decrease the variations in airborne microbial communities between different sites. Proteobacteria, with 84%-91% of average abundance, predominated in the airborne bacterial communities, but different taxa were enriched in sites with different altitudes. For example, the genera of <i>Flavobacterium</i> and <i>Lactobacillus</i> were enriched in sites with a lower altitude and a higher altitude, respectively. A total of 78 potential bacterial pathogens were detected across all samples, and the relative abundance of them in bacterial communities ranged from 2.69% to 38.19%. These findings indicated that altitude would affect the community compositions of airborne bacteria and potential pathogenic bacteria and suggested the potential threat of airborne bacteria to human health. This study provided a scientific basis for better understanding the distributions of airborne microbes and for air quality improvement and disease prevention in China.</p>","PeriodicalId":35937,"journal":{"name":"Huanjing Kexue/Environmental Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142355655","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"[Prediction of PM₁₀ Concentration in Dry Bulk Ports Using a Combined Deep Learning Model Considering Feature Meteorological Factors].","authors":"Jin-Xing Shen, Qin-Xin Liu, Xue-Jun Feng","doi":"10.13227/j.hjkx.202310217","DOIUrl":"https://doi.org/10.13227/j.hjkx.202310217","url":null,"abstract":"<p><p>Accurate prediction of PM₁₀ concentration is important for effectively managing PM₁₀ exposure and mitigating health and economic risks posed to humans in dry bulk ports. However, accurately capturing the time-series nonlinear variation characteristics of PM₁₀ concentration is challenging owing to the specific intensity of port operation activities and the influence of meteorological factors. To address such challenges, a novel combined deep learning model （CLAF） was proposed, merging cascaded convolutional neural networks （CNN）, long short-term memory （LSTM）, and an attention mechanism （AM）. This integrated model aimed to forecast hourly PM₁₀ concentration in dry bulk ports. First, using the random forest characteristic importance algorithm, the distinct meteorological factors were identified among the selected five meteorological factors. These selected factors were incorporated into the prediction model along with the PM₁₀ concentration. Subsequently, the CNN layer was employed to extract high-dimensional time-varying features from the input variables, while the LSTM layer captured sequential features and long-term dependencies. In the AM layer, different weights were assigned to the output components of the LSTM layer to amplify the effects of important information. Finally, three evaluation metrics were applied to compare the performance of the CLAF model with three basic models and three commonly used prediction models. Real-case data was collected and used in this study. Comparison results demonstrated that considering the meteorological factors could improve the prediction accuracy and fitting performance of PM₁₀ concentration in ports. The CLAF model reduced the mean absolute error statistic by 13.92%-56.9%, decreased the mean square error statistic by 45.99%-81.02%, and improved the goodness-of-fit statistic by 3.2%-15.5%.</p>","PeriodicalId":35937,"journal":{"name":"Huanjing Kexue/Environmental Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142355667","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"[Predicting Ozone Concentration in Hangzhou with the Fusion Class Stacking Algorithm].","authors":"Hong-Zhao Dong, Hong-Mei Guo, Fang Ying","doi":"10.13227/j.hjkx.202310221","DOIUrl":"https://doi.org/10.13227/j.hjkx.202310221","url":null,"abstract":"<p><p>Aiming at the problem that the single machine learning model has low prediction accuracy of daily average ozone concentration, an ozone concentration prediction method based on the fusion class Stacking algorithm （FSOP） was proposed, which combined the statistical method ordinary least squares （OLS） with machine learning algorithms and improved the prediction accuracy of the ozone concentration prediction model by integrating the advantages of different learners. Based on the principle of the Stacking algorithm, the observation data of the daily maximum 8h ozone average concentration and meteorological reanalysis data in Hangzhou from January 2017 to December 2022 were used. Firstly, the specific ozone concentration prediction models based on the light gradient boosting machine （LightGBM） algorithm, long short-term memory model （LSTM）, and Informer model were established, respectively. Then, the prediction results of the above models were used as meta-features, and the OLS algorithm was used to obtain the prediction expression of ozone concentration to fit the observed ozone concentration. The results showed that the prediction accuracy of the model combined with the class Stacking algorithm was improved, and the fitting effect of ozone concentration was better. Among them, <i>R</i>², RMSE, and MAE were 0.84, 19.65 μg·m^-3, and 15.50 μg·m^-3, respectively, which improved the prediction accuracy by approximately 8% compared with that of the single machine learning model.</p>","PeriodicalId":35937,"journal":{"name":"Huanjing Kexue/Environmental Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142355666","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"[Spatiotemporal Characteristics and Influencing Factors of the Synergistic Effect of Pollution Reduction and Carbon Reduction in China].","authors":"Ya-Nan Wang, Bing-Xun Li, Yi-Xin Zhang, Ying Zhao, Cheng-Kai Miao, Jia-Qi An","doi":"10.13227/j.hjkx.202308108","DOIUrl":"https://doi.org/10.13227/j.hjkx.202308108","url":null,"abstract":"<p><p>Based on the use of the coupling coordination model to calculate the coupling coordination degree of carbon emission and pollutant control, the national, regional, and provincial spatiotemporal characteristics of the synergistic effect of pollution control and carbon emissions reduction in China were further analyzed, facilitating the crucial to identification of key areas. The fixed effects regression models and provincial panel data from 2006 to 2020 were used to explore factors contributing to better synergizing the reduction of pollution and carbon emissions in China. On this basis, the adjustment variable of R&D investment intensity was introduced, and the regulation effect model was constructed to further explore the influence mechanism of the synergistic effect of pollution reduction and carbon reduction. The results showed that： synergy exists between carbon emission reduction and the air pollution control system, the evolution of the synergistic effect of pollution reduction and carbon reduction in China presented an inverted \"U\"-shaped trend from 2006 to 2020, and there was spatial aggregation and a spatial spillover effect in pollution reduction and carbon reduction. The synergistic governance of carbon emission and pollutant control was still at a relatively low level. The carbon emission and air pollutant emission systems were still in an unstable and uncoordinated state. The results showed that： The degree of coordination of eastern China, central China, and western China decreased in turn. At the national level, energy consumption structure, per capita GDP, and the proportion of green investment were the main factors affecting the synergistic effect of pollution reduction and carbon. The heterogeneity of the influencing factors existed in the central, eastern, and western regions on industrial structure, energy consumption structure, energy utilization efficiency, per capita GDP, urbanization rate, the proportion of green investment, and transportation structure. The intensity of R&D played a significant moderating effect in the whole country, eastern, and central regions. However, no significant moderating effect was identified in the western region. In the eastern region, the urbanization rate, the proportion of green investment, and the transportation structure could not have a significant effect on the synergistic effect of pollution reduction and carbon reduction alone, and it must be coordinated with the intensity of R&D.</p>","PeriodicalId":35937,"journal":{"name":"Huanjing Kexue/Environmental Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142355685","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"[Simulation and Analysis of Ozone Pollution Process in Shijiazhuang Based on CMAQ-ISAM Model].","authors":"Ya-Xian Geng, Jing-Han Guo, Yu-Xuan Ge, Shu-Qiao Wang, Jing-Zhou Yuan, Ding-Chao Zhang, Xin Wang","doi":"10.13227/j.hjkx.202309132","DOIUrl":"https://doi.org/10.13227/j.hjkx.202309132","url":null,"abstract":"<p><p>In Shijiazhuang City, ozone （O₃） pollution occurs frequently in June every year. In June 2023, the average O₃ 8 h concentration （O₃-8h） pollution exceeded 80% of the days in the month, and O₃ was the primary pollutant, accounting for 100%. For an O₃ heavy pollution process from June 11 to 18, the air quality model WRF-CMAQ was used for simulation, and the average error data MFB and MFE were -10.47% and 17.96%, respectively, which was within the ideal error range. The CMAQ process analysis module was used to simulate the physical and chemical processes in Shijiazhuang City, and the dry deposition （DDEP） contribution concentration was -23.88 μg·m^-3, which was the main process of O₃ consumption, whereas the transport process （TRAN） was the main source of O₃, among which the contribution was more significant in vertical transport （VTRA）. At the same time, the source analysis module （ISAM） was used to analyze the O₃ contribution of local and surrounding areas in Shijiazhuang City. The results showed that the contribution rate of local industry sources in Shijiazhuang City was as follows： traffic source （12.54%） &gt; industrial source （6.94%） &gt; residential source （6.56%） &gt; power source （4.75%）. The long-distance transmission source （BCON） continued to be in the first place with a high contribution rate of 63.31%. In the heavy pollution period under stable weather, the contribution concentration of BCON in the D02 layer of the nested domain to Shijiazhuang City was lower than the sum of the marked area. Among the surrounding cities, Baoding City had the highest contribution rate under stable weather, accounting for 26.21%. In the late period, the contribution concentration of Xingtai City increased rapidly under the action of high-value southwest wind. To effectively reduce O₃ pollution, it is necessary to reduce emissions in the city and to control the upwind cities in advance, and the implementation of inter-regional joint prevention and control is the key.</p>","PeriodicalId":35937,"journal":{"name":"Huanjing Kexue/Environmental Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142355671","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"[Tempo-spatial Variations in Nitrogen and Phosphorus Loads in Jianli-Hankou Reach of the Middle Yangtze River During the Past 20 Years].","authors":"Yu Mao, Jun-Qiang Xia, Mei-Rong Zhou, Shan-Shan Deng","doi":"10.13227/j.hjkx.202309082","DOIUrl":"https://doi.org/10.13227/j.hjkx.202309082","url":null,"abstract":"&lt;p&gt;&lt;p&gt;Ammonia nitrogen （NH&lt;sub&gt;4&lt;/sub&gt;&lt;sup&gt;+&lt;/sup&gt;-N） and total phosphorus （TP） were the major control pollutants in the Yangtze River Basin. Based on measured data from 2003 to 2020, the temporal and spatial variations in concentrations and fluxes of NH&lt;sub&gt;4&lt;/sub&gt;&lt;sup&gt;+&lt;/sup&gt;-N and TP in the Jianli to Hankou （JL-HK） reach of the Middle Yangtze River were studied, and the impacts of flow-sediment factors, tributary inflows, and others on variations in NH&lt;sub&gt;4&lt;/sub&gt;&lt;sup&gt;+&lt;/sup&gt;-N and TP fluxes were discussed. The results showed that： ① In recent years, NH&lt;sub&gt;4&lt;/sub&gt;&lt;sup&gt;+&lt;/sup&gt;-N and TP concentrations in the mainstream have declined significantly, with annual NH&lt;sub&gt;4&lt;/sub&gt;&lt;sup&gt;+&lt;/sup&gt;-N and TP concentrations at each monitoring station in 2020 averagely decreasing by 41% and 34% compared to those in 2003, respectively. Spatially, NH&lt;sub&gt;4&lt;/sub&gt;&lt;sup&gt;+&lt;/sup&gt;-N and TP concentrations decreased and then increased along the mainstream. NH&lt;sub&gt;4&lt;/sub&gt;&lt;sup&gt;+&lt;/sup&gt;-N and TP concentrations of tributary inflows, which include the Dongting Lake and Han River, were generally lower than that of the mainstream. The multi-year average values of NH&lt;sub&gt;4&lt;/sub&gt;&lt;sup&gt;+&lt;/sup&gt;-N and TP concentrations were both averaged at 0.12 mg·L&lt;sup&gt;-1&lt;/sup&gt; in the mainstream and were averaged at 0.11 mg·L&lt;sup&gt;-1&lt;/sup&gt; and 0.09 mg·L&lt;sup&gt;-1&lt;/sup&gt; in the tributary inflows. ② The flux differences between the upper and lower sections net of tributary confluences showed that NH&lt;sub&gt;4&lt;/sub&gt;&lt;sup&gt;+&lt;/sup&gt;-N and TP fluxes were lost in the Jianli to Luoshan （JL-LS） sub-reach and increased in the Luoshan to Hankou （LS-HK） sub-reach in most years. NH&lt;sub&gt;4&lt;/sub&gt;&lt;sup&gt;+&lt;/sup&gt;-N and TP fluxes decreased in the JL-LS sub-reach, which was related to the lower NH&lt;sub&gt;4&lt;/sub&gt;&lt;sup&gt;+&lt;/sup&gt;-N and TP concentrations in lateral inflows, such as Dongting Lake, and thus lowered the NH&lt;sub&gt;4&lt;/sub&gt;&lt;sup&gt;+&lt;/sup&gt;-N and TP concentrations in the mainstream. The LS-HK sub-reach showed the opposite trends, and the water and sediment loads increased in this sub-reach. Across the whole JL-HK reach, TP flux as well as water and sediment loads were recharged along the reach, whereas NH&lt;sub&gt;4&lt;/sub&gt;&lt;sup&gt;+&lt;/sup&gt;-N flux was reduced greatly, which could be attributed to the pollution abatement conducted in the Yangtze River Basin, which mainly focused on NH&lt;sub&gt;4&lt;/sub&gt;&lt;sup&gt;+&lt;/sup&gt;-N. ③ The correlation analysis results showed that NH&lt;sub&gt;4&lt;/sub&gt;&lt;sup&gt;+&lt;/sup&gt;-N fluxes had the strongest correlation with NH&lt;sub&gt;4&lt;/sub&gt;&lt;sup&gt;+&lt;/sup&gt;-N concentrations but not significantly correlated with discharges and sediment transport rates, indicating that NH&lt;sub&gt;4&lt;/sub&gt;&lt;sup&gt;+&lt;/sup&gt;-N was mainly controlled by point source pollution in the study reach. TP fluxes had higher correlations with discharges and sediment transport rates in high flow level periods, and the correlations between TP fluxes and TP concentrations were better in low flow level periods, reflecting that point source pollution contributed more to TP in dry seasons compared to floo","PeriodicalId":35937,"journal":{"name":"Huanjing Kexue/Environmental Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142355704","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"[Spatial and Temporal Characteristics of Fractional Vegetation Cover and Its Response to Urbanization in Beijing].","authors":"Na-Na Shi, Yu Han, Qi Wang, Neng-Wen Xiao, Zhan-Jun Quan","doi":"10.13227/j.hjkx.202308265","DOIUrl":"https://doi.org/10.13227/j.hjkx.202308265","url":null,"abstract":"<p><p>Exploration of the spatiotemporal changes in fractional vegetation cover （FVC） and its response characteristics to urbanization is of great significance for urban ecological protection and planning in Beijing. This study analyzed the spatiotemporal characteristics of vegetation cover changes in Beijing from 2000 to 2020 using the Theil-Sen Median and Mann-Kendall methods based on a long-term time series vegetation cover dataset. Then, this study used the urbanization index as a key indicator of spatial urbanization and utilized the transect line and global grid analysis methods to investigate the response characteristics of FVC to different urbanization gradients. The results indicated that： ① FVC changes showed spatial and temporal heterogeneity. From 2000 to 2020, Beijing was predominantly covered by high vegetation, accounting for 65.22% of the total area, which was mainly distributed in ecological conservation areas consistent with the Jundu, Xishan, and Yaji Mountain ranges. The FVC presented an overall positive development trend, with a decreasing trend of areas with low FVC. The increase in FVC was significant （by 28.68%）, mainly distributed in ecological conservation areas and within a range of 10-12 km in concentric circles centered around Tiananmen Square. The urbanization index and FVC change rate were relatively high in Haidian District, Chaoyang District, Fengtai District, Shijingshan District, and Changping District. ② The artificial land surface in 2000, 2010, and 2020 was 9.69%, 13.64%, and 21.19%, respectively, with significant spatial agglomeration and strong spatial heterogeneity. During the urbanization process in Beijing, the increase in artificial land surface reached 11.5%, with the conversion from arable land to artificial land surface accounting for 53.83% of the total land use conversion area. ③ There was a significant negative correlation between FVC and the urbanization index, indicating that urbanization had a negative impact on regional FVC. However, as the urbanization process stabilized, this negative correlation tended to gradually weaken. Although the central urban areas were mainly characterized by low FVC, there was a significant increasing trend in the FVC, indicating a positive development in the FVC and an improvement in regional ecological quality, which was closely related to the governance of the mountain-water-forest-field-lake-grass-sand system. The results of the study can provide a basis for the development of vegetation restoration programs and ecological management measures in Beijing.</p>","PeriodicalId":35937,"journal":{"name":"Huanjing Kexue/Environmental Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142355680","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"[Effects of Nitrogen Addition on Soil Organic Carbon and Its Fractions in Karst Farmland and Forest Ecosystems of China Based on Meta-analysis].","authors":"Yu-Peng Yan, Bo-Han Zhang, Zhi-Dong Zhou, Yuan-Qi Chen","doi":"10.13227/j.hjkx.202309091","DOIUrl":"https://doi.org/10.13227/j.hjkx.202309091","url":null,"abstract":"&lt;p&gt;&lt;p&gt;In recent decades, with the intensification of human activities, atmospheric nitrogen （N） deposition has been increasing. N deposition affects carbon （C） cycling in terrestrial ecosystems, especially in fragile karst ecosystems. Karst ecosystems are considered to be an important C pool. To evaluate the impact of N deposition on soil organic C （SOC） and its fractions in karst ecosystems of China, we collected and collated 14 English literature published through the end of March 2023, yielding a total of 460 sets of experimental data. The meta-analysis examined the effect of N addition levels [low N: ≤50 kg·（hm&lt;sup&gt;2&lt;/sup&gt;·a）&lt;sup&gt;-1&lt;/sup&gt;, medium N: 50-100 kg·（hm&lt;sup&gt;2&lt;/sup&gt;·a）&lt;sup&gt;-1&lt;/sup&gt;, and high N: &gt;100 kg·（hm&lt;sup&gt;2&lt;/sup&gt;·a）&lt;sup&gt;-1&lt;/sup&gt;, in terms of N] on SOC and its fractions [particular organic C （POC）, readily oxidized organic C （ROC）, microbial biomass C （MBC）, and dissolved organic C （DOC）]. The results showed that N addition levels significantly affected the responses of farmland and forest soil SOC and their active fractions to N addition. Specifically, low and high N additions significantly increased SOC concentration in farmland ecosystems, whereas medium N addition significantly increased SOC concentration in forest ecosystems. In addition, soil active C fraction concentrations increased under high N addition in farmland ecosystems and under low and medium N addition in forest ecosystems. Without considering the level of N addition, N addition significantly enhanced soil organic matter （SOM） mineralization in both farmland and forest ecosystems and increased the SOC concentration in farmland ecosystems but not forest ecosystems. The responses of different active C fractions to N addition were diverse. In farmland ecosystems, the POC and ROC concentrations increased, but DOC did not change with N addition. In forest ecosystems, the DOC and POC concentrations increased, but there was no significant effect on MBC. Moreover, the response ratios （RR） of SOC and its fractions in different ecosystems to N addition were influenced by different environmental factors. In farmland ecosystems, the response ratio of SOC was related to the annual average temperature and soil pH. The response ratio of DOC was affected by the annual average temperature, mean annual precipitation, and N addition rate. The POC response ratio was related to the N addition rate. In forest ecosystems, the effects of N addition on the SOC response ratio were significantly altered by the annual average temperature, mean annual precipitation, and soil pH. However, the response ratios of DOC, POC, and MBC were not affected by the annual average temperature, mean annual precipitation, soil pH, and N addition rate. Consequently, these findings indicate that N addition could enhance soil SOC concentration and promote soil C sequestration in farmland and forest ecosystems in karst regions, but this effect relies on the level of N addition. This provides a scientific ba","PeriodicalId":35937,"journal":{"name":"Huanjing Kexue/Environmental Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142355643","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"[Impact and Mechanism of Medium and Small Flood Regulation in the Three Gorges Reservoir on the Phytoplankton in Tributary Bays].","authors":"Rui Li, Xian-Qiang Tang, Xin-Bo Liu, Wen-Zhong Chen, Dan-Yang Wang, Yu-Feng Ren","doi":"10.13227/j.hjkx.202310059","DOIUrl":"https://doi.org/10.13227/j.hjkx.202310059","url":null,"abstract":"<p><p>The regulation of small- and medium-sized floods （RSMF） has become the main mode of regulation in the flood season of the Three Gorges Reservoir （TGR）. To study the response of phytoplankton in the tributary bays of the TGR to the RSMF, a typical eutrophic tributary of the TGR, Xiangxi River, was investigated for the spatiotemporal distribution characteristics of phytoplankton and nutrients in the main and tributary streams from 2020 to 2021. The response characteristics of phytoplankton in the tributary bays to the RSMF were analyzed. The results indicated that during the RSMF, the chlorophyll a （Chl-a） in the water body of the Xiangxi River decreased with the increase in the water level in front of the dam, whereas during the reservoir impounding at the end of flood season, the concentration of Chl-a increased again. During the RSMF, the Chlorophyta and Diatoma were the main communities of planktonic algae in the Xiangxi River. The phytoplankton community changed with the RSMF. When the water level fluctuation increased, diatoms were the main species, whereas when the water level fluctuation was small, blue and green algae were the main species. The concentration of Chl-a was more sensitive to changes in TN concentration. When the flow velocity was &gt;0.25 m·s^-1 or the suspended sediment content was &gt;10 mg·L^-1, the concentration of Chl-a in the water was inhibited. After 2010, the typical outbreak time of algal blooms in the Xiangxi River Reservoir Bay shifted to the flood season, with only two non-flood season algal blooms. Further attention needs to be paid to the response of algal blooms in the reservoir to small- and medium-sized flood control during the flood season.</p>","PeriodicalId":35937,"journal":{"name":"Huanjing Kexue/Environmental Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142355647","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"[A Method for Fine Mapping of Carbon Emissions from Regional Land Use Change and Its Application].","authors":"Quan-Fang Wang, Yu-Han Jin, Pei Sun, Ying Xiao, Zhi-Hao Chen, Ze-Ru Lu, Heng-Shuo Liang","doi":"10.13227/j.hjkx.202309248","DOIUrl":"https://doi.org/10.13227/j.hjkx.202309248","url":null,"abstract":"<p><p>Land use changes are always patchy and widespread within a region, making it a challenge to identify the point-scale pressure of reducing carbon emissions from land use/cover change （LUCC）. The carbon emission observation index （CEOI） was thus proposed to conduct the point-scale comparability analysis, which was based on the unique net C flux effects of conversions between two different land use types. Then, the spatial-temporal characteristics of land use changes and the resulting pressure of reducing carbon emissions were studied in the Weihe River Basin of China, which adopted the LUCC data from 2000 to 2020 and models of the Markov transition matrix （MTM）, compound carbon emission coefficients （CEC） of various types of land use changes, and the CEOI-based classification method on point-scale pressure of reducing carbon emissions. The results showed that： ① The net C flux was from 3.551 Tg C （2000-2010） to 7.031 Tg C （2010-2020）, and the pressure of reducing carbon emissions from LUCC had been continuously increasing, which was mainly driven by the significant increase in change-spots with the super-strong ability to reduce carbon emissions. ② Due to contributions from change spots with carbon uptake ability, the amount of carbon released to the atmosphere was eliminated by approximately 19.21% over the period 2000-2020 and approximately 37.4% during 2000-2010. ③ Change spots on various pressure levels for reducing carbon emissions were distributed unevenly in the basin, with their gravity points in the previous 10 years （2010-2020） far away from those during 2000-2010. Additionally, the gravity points of change-spots with a strong ability to reduce carbon emissions from conversions of grassland into forestland moved northeastward from Tianshui City to Pingliang City, whereas the gravity points of other change-spots with different abilities to reduce carbon emissions were mostly northwestward to the north-central region with higher elevations from the Middle and Lower Reaches of the Weihe River Basin with low elevations.</p>","PeriodicalId":35937,"journal":{"name":"Huanjing Kexue/Environmental Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142355631","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}