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[Characteristics and Source Apportionment of Atmospheric Volatile Organic Compounds in Zhengzhou During O3 Campaign Period]. [O3 活动期间郑州大气挥发性有机化合物的特征和来源分配]。
Huanjing Kexue/Environmental Science Pub Date : 2024-10-08 DOI: 10.13227/j.hjkx.202310136
Si Chen, Jing-Wei Ni, Yi-Jin Qi, Tian-Tian Ji, Ling-Ling Wang, Xiao-Na Shan, Shan-Ling Gong
{"title":"[Characteristics and Source Apportionment of Atmospheric Volatile Organic Compounds in Zhengzhou During O<sub>3</sub> Campaign Period].","authors":"Si Chen, Jing-Wei Ni, Yi-Jin Qi, Tian-Tian Ji, Ling-Ling Wang, Xiao-Na Shan, Shan-Ling Gong","doi":"10.13227/j.hjkx.202310136","DOIUrl":"https://doi.org/10.13227/j.hjkx.202310136","url":null,"abstract":"&lt;p&gt;&lt;p&gt;An online gas chromatograph (GC5000) was used to monitor the volatile organic compounds (VOCs) in the atmospheric environment of Zhengzhou City during the ozone campaign period from May to September of 2022. The relationship between O&lt;sub&gt;3&lt;/sub&gt; and its precursors as well as meteorology was analyzed and the pollution characteristics of VOCs during the O&lt;sub&gt;3&lt;/sub&gt; exceeding and non-exceeding the standard days were compared and explored. Different VOC activity evaluation methods of OFP and &lt;i&gt;L&lt;/i&gt;&lt;sub&gt;·OH&lt;/sub&gt; were utilized to compare and analyze the key active components and species and the ratio analysis (RA) and positive matrix factorization (PMF) analysis models were used to study the apportionment contribution of VOCs. The results showed that the O&lt;sub&gt;3&lt;/sub&gt; pollution in June and September in Zhengzhou was mainly due to the adverse meteorological conditions of high temperature and low humidity, strong radiation, and low wind speed, superimposed by the prominent concentrations of local VOCs and NO&lt;sub&gt;2&lt;/sub&gt;, resulting in frequently high and excessive O&lt;sub&gt;3&lt;/sub&gt; occurrences. The VOCs concentration in Zhengzhou during the campaign period was an average of (68.3 ± 18.4) μg·m&lt;sup&gt;-3&lt;/sup&gt;, whereas it was 75.7 μg·m&lt;sup&gt;-3&lt;/sup&gt; during O&lt;sub&gt;3&lt;/sub&gt; exceeding standard days and 13.4 μg·m&lt;sup&gt;-3&lt;/sup&gt; during O&lt;sub&gt;3&lt;/sub&gt; non-exceeding days, respectively. Among the VOC species, the OVOCs was 31.6%, accounting for the highest mass fraction, followed by halogenated hydrocarbon, alkane, and aromatic hydrocarbon, and the major species were ethane, &lt;i&gt;n&lt;/i&gt;-butane, dichloromethane, propane, isopentane, toluene, chloromethane, 1,2-dichloroethane, and acetylene. VOC diurnal variation indicated that the emission of VOC pollution sources in the morning, evening peak, and at night should be paid more attention. The contribution of VOCs to OFP during the campaign period was (130.5 ± 46.4) μg·m&lt;sup&gt;-3&lt;/sup&gt;, and the &lt;i&gt;L&lt;/i&gt;&lt;sub&gt;·OH&lt;/sub&gt; was (6.5 ± 2.9) s&lt;sup&gt;-1&lt;/sup&gt;, among which the top 15 species with high activity were primarily acetaldehyde, isoprene, ethylene, &lt;i&gt;m/p&lt;/i&gt;-xylene, toluene, hexal, isopentane, propanal, propylene, trans-2-butene, &lt;i&gt;etc&lt;/i&gt;. In particular, the contributions of acetaldehyde, isoprene, ethylene, and hexal species were prominent during the O&lt;sub&gt;3&lt;/sub&gt; exceeding days. Ratio analysis showed that the B/T ratio in Zhengzhou from May to September ranged from 0.05 to 5.3, with an average value of 1.1 ± 0.6, and the regional VOCs was mainly controlled by the aging air mass with possible long-distance transports. The analysis of the PMF model showed that the major pollution sources to VOC concentration in Zhengzhou were motor vehicle exhaust emission sources and industrial solvent and secondary conversion sources, contributing 25.6% and 25.8%, respectively. The contribution rates of solvent coating sources, oil and gas volatile sources, plant emission sources, industrial solvents, and secondary conversion sources durin","PeriodicalId":35937,"journal":{"name":"Huanjing Kexue/Environmental Science","volume":"45 10","pages":"5671-5686"},"PeriodicalIF":0.0,"publicationDate":"2024-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142509610","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}
引用次数: 0
[Characteristics of Soil Respiration and Organic Carbon Mineralization in Dryland Potato Fields Under Different Ridge-furrow Mulching Patterns]. [不同垄沟覆盖模式下旱地马铃薯田土壤呼吸和有机碳矿化的特征]。
Huanjing Kexue/Environmental Science Pub Date : 2024-10-08 DOI: 10.13227/j.hjkx.202310083
Dan Li, Xiao-Ming Ma, Jia Lei, Jie Yu, Yong-Jin Zhou, Chun-Hua Wu, Rong Li, Xian-Qing Hou
{"title":"[Characteristics of Soil Respiration and Organic Carbon Mineralization in Dryland Potato Fields Under Different Ridge-furrow Mulching Patterns].","authors":"Dan Li, Xiao-Ming Ma, Jia Lei, Jie Yu, Yong-Jin Zhou, Chun-Hua Wu, Rong Li, Xian-Qing Hou","doi":"10.13227/j.hjkx.202310083","DOIUrl":"https://doi.org/10.13227/j.hjkx.202310083","url":null,"abstract":"&lt;p&gt;&lt;p&gt;Exploring the response mechanism of soil respiration rate to hydrothermal factors and organic carbon mineralization under different ridge-furrow mulching modes is of high importance for the development of the regional carbon cycle and assessment of its ecological benefits. An experimental study was carried out in 2020 in a dry-crop potato field in the mountainous area of southern Ningxia by setting three furrow-ridge ratios [60 cm∶30 cm (R1), 60 cm∶45 cm (R2), and 60 cm∶60 cm (R3)] combined with three mulching modes [ridge covered with ordinary plastic film, furrow covered with straw (DJ), degradable water-permeable plastic film (DS), and no mulching (DB) in furrows, respectively]. The soil hydrothermal factors, respiration rate, organic carbon content, and mineralization characteristics of potatoes during the reproductive period under different mulching modes were investigated with plain mulching without mulching (CK) as the control. The results showed that different furrow-ridge ratios combined with the mulching mode could significantly increase the soil water storage capacity in the 0-60 cm layer, and the R3DJ treatment had a better effect, with a significant increase of 24.99% compared with that in CK. The R2 treatment had the best effect of increasing temperature during the whole life cycle of the potato. The DS treatment had the effect of increasing temperature, and the DJ treatment had the effect of decreasing temperature under different mulching materials. Different furrow and ridge cover patterns could significantly increase the average soil respiration rate during the reproductive period, and the R3DS treatment was the most significant among the different furrow and ridge cover patterns, with a significant increase of 24.71% compared with that in the CK treatment. The soil organic carbon content in the 0-20 cm and 20-40 cm layers at harvest time was higher in the R2 and R1 ridges, respectively, and higher in the DB and DS treatments for different mulching materials. The soil organic carbon mineralization rate declined rapidly in the early stage of cultivation and then slowly declined and leveled off in the middle and late stages, which was highest in the R3 treatment for the three types of ridge ratios and highest in the DS treatment for different mulching materials. The fitting equations of soil respiration rate with soil hydrothermal factors during the reproductive period revealed that the synergistic effect of soil hydrothermal dual factors on soil respiration was higher than that of a soil hydrothermal single factor and that the quadratic hydrothermal dual factors could well explain 86.4% to 99.9% of the soil respiration. Correlation analysis showed that the average soil respiration rate during the whole life span of the potato was highly significantly and positively correlated with the average soil temperature in the 0-25 cm layer and the average soil organic carbon mineralization rate in the 0-40 cm layer, and the soil tempe","PeriodicalId":35937,"journal":{"name":"Huanjing Kexue/Environmental Science","volume":"45 10","pages":"6038-6049"},"PeriodicalIF":0.0,"publicationDate":"2024-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142509613","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}
引用次数: 0
[Diversity and Functional Characteristics of Fungal Communities and Influencing Factors in Typical Paddy Fields of China]. [中国典型稻田真菌群落的多样性和功能特征及其影响因素]。
Huanjing Kexue/Environmental Science Pub Date : 2024-10-08 DOI: 10.13227/j.hjkx.202310031
Ting-E Ye, Mei-Fen Lin, Chao-Fan Yu, Yu-Jun Xiao, Li-Wen Cheng, Yi Zheng, Wei-Qi Wang
{"title":"[Diversity and Functional Characteristics of Fungal Communities and Influencing Factors in Typical Paddy Fields of China].","authors":"Ting-E Ye, Mei-Fen Lin, Chao-Fan Yu, Yu-Jun Xiao, Li-Wen Cheng, Yi Zheng, Wei-Qi Wang","doi":"10.13227/j.hjkx.202310031","DOIUrl":"https://doi.org/10.13227/j.hjkx.202310031","url":null,"abstract":"<p><p>To investigate the structure, diversity, and function of different paddy soil fungal communities and the factors affecting them in typical paddy cropping areas in China, five typical Chinese paddy soils were selected in this study, and the composition and diversity of soil fungal communities were comparatively analyzed using high-throughput sequencing technology and functionally predicted using the FUNGuild microecological tool. The results showed that: ① The fungal community diversity of soil samples from Heilongjiang (HLJ) was significantly lower than that of the other four regions (<i>P</i><0.05); the highest fungal community richness was found in paddy soils from Yunnan (YN), which was significantly higher than that of the other regions (<i>P</i><0.05); and the soil samples from Hainan (HN), Jiangxi (JX), and Shandong (SD) were relatively close to each other. The highest average relative abundance at the level of the five typical paddy phyla was Ascomycota, and the genus with the highest average relative abundance was <i>Tausonia</i>. ② Fungi had the largest proportion of saprophytic trophic types, and their corresponding environmental functions were stronger. ③ The species abundance of soil fungi was highly significantly correlated with soil TP, EC, and BD (<i>P</i><0.01), and redundancy analyses also showed that soil TP was the main driver of the fungal community as well as the saprophytic functional taxa. The above results showed that the soil fungal community diversity and structure varied greatly among samples, and the relative abundance of fungal genera was affected by soil physical and chemical properties and altered the fungal community structure in paddy fields. The development of this study will provide theoretical references for the sustainable management based on fungal diversity and function of paddy fields.</p>","PeriodicalId":35937,"journal":{"name":"Huanjing Kexue/Environmental Science","volume":"45 10","pages":"6068-6076"},"PeriodicalIF":0.0,"publicationDate":"2024-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142509627","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}
引用次数: 0
[Evolution Characteristics and Typical Pollution Episodes of PM2.5 and O3 Complex Pollution in Bozhou City from 2017 to 2022]. [2017-2022年亳州市PM2.5和O3复合污染演变特征及典型污染事件]。
Huanjing Kexue/Environmental Science Pub Date : 2024-10-08 DOI: 10.13227/j.hjkx.202311032
Ke Wu, Xue-Zhong Wang, Dan-Dan Zhang, Hua-Long Zhu, Yong-Xin Yan, Fan-Xiu Li, Zhen-Hai Wu, Zhen-Wei Zheng, Qi-Kai Gao
{"title":"[Evolution Characteristics and Typical Pollution Episodes of PM<sub>2.5</sub> and O<sub>3</sub> Complex Pollution in Bozhou City from 2017 to 2022].","authors":"Ke Wu, Xue-Zhong Wang, Dan-Dan Zhang, Hua-Long Zhu, Yong-Xin Yan, Fan-Xiu Li, Zhen-Hai Wu, Zhen-Wei Zheng, Qi-Kai Gao","doi":"10.13227/j.hjkx.202311032","DOIUrl":"https://doi.org/10.13227/j.hjkx.202311032","url":null,"abstract":"<p><p>In China, atmospheric pollution exhibits a complex pattern, with simultaneous exceedances of fine particulate matter (PM<sub>2.5</sub>) and ozone (O<sub>3</sub>) levels becoming evident. To understand the complex pollution characteristics and evolution patterns of PM<sub>2.5</sub> and O<sub>3</sub> in Bozhou City, various methods such as weather classification, analysis of typical pollution processes, and investigation of precursor sources were employed to explore the pollution and variations of PM<sub>2.5</sub> and O<sub>3</sub> in Bozhou City from 2017 to 2022 and subsequently analyze their causes and precursor sources. The results indicated that: ① PM<sub>2.5</sub>-O<sub>3</sub> complex pollution in Bozhou City mostly occurred under high-pressure weather conditions, with daytime high temperatures and low humidity promoting the formation of O<sub>3</sub> pollution, whereas nighttime high humidity and atmospheric oxidative conditions promoted the generation of secondary components such as nitrates and ammonium salts in PM<sub>2.5</sub>. ② During the pollution process, PM<sub>2.5</sub> in Bozhou City mainly originated from biomass burning, secondary generation, traffic pollution, coal combustion, and dust sources. Volatile organic compounds (VOCs) primarily emerged from plant sources, traffic pollution, oil and gas evaporation, solvent use, fossil fuel combustion, residential emissions, and industrial emissions. Biomass burning and traffic pollution made significant contributions to the pollution process. ③ Analysis of air mass trajectories and regional pollution situations indicated that the overlay of northern and southern air masses, along with local generation, were the main causes of the PM<sub>2.5</sub>-O<sub>3</sub> complex pollution in Bozhou from October 18th to 27th, 2022.</p>","PeriodicalId":35937,"journal":{"name":"Huanjing Kexue/Environmental Science","volume":"45 10","pages":"5715-5728"},"PeriodicalIF":0.0,"publicationDate":"2024-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142509644","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}
引用次数: 0
[Characteristics of Spatiotemporal Changes in China's Carbon Budget at Different Administrative Scales]. [不同行政尺度下中国碳预算的时空变化特征]。
Huanjing Kexue/Environmental Science Pub Date : 2024-10-08 DOI: 10.13227/j.hjkx.202311005
Hai-Yue Lu, Jiao-Jiao Qi, Yan-Lei Ye, Bei-Er Zhang, Jing-Lu Sun, Can-Can Yang, Ming-Wei Zhao
{"title":"[Characteristics of Spatiotemporal Changes in China's Carbon Budget at Different Administrative Scales].","authors":"Hai-Yue Lu, Jiao-Jiao Qi, Yan-Lei Ye, Bei-Er Zhang, Jing-Lu Sun, Can-Can Yang, Ming-Wei Zhao","doi":"10.13227/j.hjkx.202311005","DOIUrl":"https://doi.org/10.13227/j.hjkx.202311005","url":null,"abstract":"&lt;p&gt;&lt;p&gt;Currently, scientifically and reasonably specifying carbon emission reduction measures in the context of \"double carbon\" has become a common concern worldwide. China's administrative divisions have a notable impact on the formulation and implementation of relevant policies. Therefore the carbon emissions must be calculated accurately under China's administrative divisions at different scales. The spatiotemporal change characteristics of absorption and carbon emissions can provide scientific basis for the formulation of reasonable and differentiated carbon emission reduction policies in different administrative regions in China. To this end, this study used multi-source data such as remote sensing and statistics and integrated ecological models, statistics, and GIS space analysis and other methods to analyze the spatiotemporal dynamic change characteristics of carbon emissions and carbon absorption at different administrative scales (provinces, cities, and counties) in China. The results showed that: ① The total carbon absorption of vegetation in China continued to increase from 2000 to 2021 and the average value gradually increased. Differences were observed in spatiotemporal changes in carbon emissions at different administrative scales. The spatiotemporal changes at smaller scales were more evident. Carbon emissions showed obvious spatial differences of \"high in the north and low in the south, high in the east and low in the west.\" ② The spatiotemporal distribution of CPI at the administrative scale was similar to that of carbon emissions and the overall trend was increasing annually. The pressure of carbon emissions on carbon absorption gradually weakened from the east to the central and western regions. ③ Spatiotemporal hotspot analysis showed that the overall spatial distribution of cold and hot spots in China's carbon absorption was as follows: In the spatial pattern of \"hot in the east and cold in the west,\" the spatial distribution of cold and hot spots of carbon emissions showed agglomeration characteristics. The provincial scale was primarily oscillating hotspot whereas municipal and county scales were majorly continuous hot spots. Further results revealed that: ① Carbon absorption in different regions and periods in China showed significant variability, especially in the central and eastern regions. The possibility of offsetting carbon emissions by increasing carbon absorption remains. ② At the same scale, administrative regions (such as different provinces) and lower-level administrative regions at another scale (such as different cities in the same province) showed varying degrees of variability in carbon absorption and carbon emissions. Therefore, taking provincial administrative regions as an example for subsequent formulation considering carbon trading, emission reduction, and other policies, we should first consider the coordination of emissions between different cities in the province and then consider the coordination bet","PeriodicalId":35937,"journal":{"name":"Huanjing Kexue/Environmental Science","volume":"45 10","pages":"5601-5612"},"PeriodicalIF":0.0,"publicationDate":"2024-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142509615","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}
引用次数: 0
[Pollution Characteristics and Source Apportionment of Volatile Organic Compounds in Typical Solvent-using Industrial Parks in Beijing]. [北京典型溶剂使用工业园区挥发性有机化合物的污染特征和来源分配]。
Huanjing Kexue/Environmental Science Pub Date : 2024-10-08 DOI: 10.13227/j.hjkx.202310142
Rui Liu, Zhen Yao, Xiao-Hui Hua, Xiu-Rui Guo, Hai-Lin Wang, Feng Qi
{"title":"[Pollution Characteristics and Source Apportionment of Volatile Organic Compounds in Typical Solvent-using Industrial Parks in Beijing].","authors":"Rui Liu, Zhen Yao, Xiao-Hui Hua, Xiu-Rui Guo, Hai-Lin Wang, Feng Qi","doi":"10.13227/j.hjkx.202310142","DOIUrl":"https://doi.org/10.13227/j.hjkx.202310142","url":null,"abstract":"<p><p>The BCT-7800A PLUS VOC online monitor system was employed to measure ambient volatile organic compounds (VOCs) in a typical solvent-using industrial park in Beijing. From January to June 2023, the pollution characteristics, source apportionment, and ozone formation potential(OFP)of VOCs were studied, and the results of a comparative analysis were also discussed between heating and non-heating periods. The results indicated that VOC concentrations from January to June 2023 were (104.21 ± 91.31) μg·m<sup>-3</sup> on average. The concentrations of TVOCs under the influence of southerly and northerly winds were (214.18 ± 202.37) μg·m<sup>-3</sup> and (197.56 ± 188.3) μg·m<sup>-3</sup>, respectively. Alkanes were the species with the highest average concentration and proportion, respectively (45.53 ± 41.43) μg·m<sup>-3</sup>. The VOC concentration during the heating period was higher than those during the non-heating period, with values of (111.57 ± 83.96) μg·m<sup>-3</sup> and (87.92 ± 75.03) μg·m<sup>-3</sup>, respectively. Propane and ethane were the species with the highest average concentration during the heating period. Compared with those in the non-heating period, the average concentrations of three species (propane, ethane, and n-butane) in the top ten species increased during the heating period, with average concentrations increasing by 51.94%, 54.64%, and 26.32%, respectively. The source apportionment results based on the positive matrix factorization (PMF) model indicated that the major sources of VOCs in the park during the monitoring period were printing emission sources (4.95%), oil and gas evaporation sources (9.52%), fuel combustion sources (15.44%), traffic emissions sources (18.97%), electronic equipment manufacturing (24.59%), and industrial painting sources (26.52%). Therefore, industrial painting sources, electronic equipment manufacturing sources, and traffic emissions sources were the emission sources that the park should focus on controlling. Compared with those during non-heating periods; industrial painting, traffic emission, and fuel combustion sources contributed more during the heating period, with VOC concentrations increasing by 15.02%, 16.53%, and 24.98%, respectively. The average OFP of VOCs from May to June during the monitoring period was 198.51 μg·m<sup>-3</sup> and OVOCs, olefins, and aromatic hydrocarbons contributed the most to OFP, which were 47.41%, 22.15%, and 18.41%, respectively. The electronic equipment manufacturing source was the largest contributor to the summer OFP of the park and its contribution rate was 30.11%, which should be strengthened in the future.</p>","PeriodicalId":35937,"journal":{"name":"Huanjing Kexue/Environmental Science","volume":"45 10","pages":"5661-5670"},"PeriodicalIF":0.0,"publicationDate":"2024-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142509653","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}
引用次数: 0
[Spatiotemporal Evolution Characteristics and Influencing Factors of Industrial Carbon Emissions in the Yellow River Basin]. [黄河流域工业碳排放时空演变特征及影响因素]。
Huanjing Kexue/Environmental Science Pub Date : 2024-10-08 DOI: 10.13227/j.hjkx.202308258
Xi-Lian Wang, Li-Hang Qu
{"title":"[Spatiotemporal Evolution Characteristics and Influencing Factors of Industrial Carbon Emissions in the Yellow River Basin].","authors":"Xi-Lian Wang, Li-Hang Qu","doi":"10.13227/j.hjkx.202308258","DOIUrl":"https://doi.org/10.13227/j.hjkx.202308258","url":null,"abstract":"<p><p>Scientific assessment of industrial carbon emissions in the Yellow River Basin and identification of its influencing factors are of great importance for promoting green transformation, ecological protection, and high-quality development of the Yellow River Basin. Considering nine provinces in the Yellow River Basin as the research objects; using relevant data on industrial development and energy consumption in the Yellow River Basin from 2000 to 2019; and with the help of IPCC carbon emission measurement, spatial autocorrelation, and LMDI decomposition, the spatial and temporal evolution characteristics and influencing factors of carbon emissions from industries and industrial sectors in the Yellow River Basin were analyzed. Reasonable suggestions were put forward for reducing the carbon emissions from industries in the Yellow River Basin. The results showed that: ① From 2000 to 2019, industrial carbon emissions in the Yellow River Basin showed a fluctuating growth trend, with a decreasing growth rate. The spatial pattern changed from \"low in the upstream and high in the middle and downstream\" to \"high and low value distribution,\" and the spatial difference gradually expanded. ② The high carbon industry was the most important source of industrial carbon emissions in the Yellow River Basin, accounting for 96.35% of the carbon emissions between the industries with a continuous growth trend, which was a significant difference. The middle and low carbon industry carbon emissions and the total proportion was low, showing different fluctuations; nine provinces and nine industrial industries had significant spatial variability. ③ Energy structure intensity, economic scale, and population scale promoted the increase in industrial carbon emissions in the Yellow River Basin and energy consumption intensity had an inhibitory effect on the increase in carbon emissions. The economic scale effect was positive and significant, which offset the negative effect of energy consumption intensity. Spatial variability was observed in the contribution value of the influence effect of the factors affecting the carbon emissions of the industry in nine provinces.</p>","PeriodicalId":35937,"journal":{"name":"Huanjing Kexue/Environmental Science","volume":"45 10","pages":"5613-5623"},"PeriodicalIF":0.0,"publicationDate":"2024-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142509657","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}
引用次数: 0
[Influence of Typical Regional Land Use/Landscape Pattern on Water TN of the Upper Yellow River]. [典型区域土地利用/景观模式对黄河上游水 TN 的影响]。
Huanjing Kexue/Environmental Science Pub Date : 2024-10-08 DOI: 10.13227/j.hjkx.202310025
Tian-Hong Zhou, Si-Lin Su, Kai Ma, Sen Du, Hui-Juan Xin
{"title":"[Influence of Typical Regional Land Use/Landscape Pattern on Water TN of the Upper Yellow River].","authors":"Tian-Hong Zhou, Si-Lin Su, Kai Ma, Sen Du, Hui-Juan Xin","doi":"10.13227/j.hjkx.202310025","DOIUrl":"https://doi.org/10.13227/j.hjkx.202310025","url":null,"abstract":"<p><p>This study aimed to explore the relationship between land use landscape pattern and water quality in the upstream of the Gansu water conservation, water and soil erosion, and ecological fragile areas. Based on the land use data and water quality monitoring section in 2020 in the 200 m, 500 m, 1 km, 2 km, 50 km, and 10 km riparian buffer area, the single-factor index evaluation method, random forest regression model, and BP neural network were used to quantify the response relationship between land use and landscape pattern of the upper Yellow River in Gansu province and water quality index and to carry out the basin water quality prediction based on land use landscape index data. The results showed that: ① through the single-factor index method, the major indicators of the total nitrogen (TN) in July and September, dissolved oxygen (DO), permanganate index, ammonia nitrogen (NH<sub>4</sub><sup>+</sup> -N), total phosphorus (TP), and other surface indexes met the surface water environment class Ⅲ water quality standard. ② The random forest regression model was used to analyze the influence of land use and landscape index on TN, and the difference in TN in different typical areas was obtained. The land use types with the highest influence on the TN index in water conservation areas, soil and soil erosion areas, and ecological fragile areas were cultivated land, grassland, and construction land, respectively. ③ The BP neural network was used to predict the water quality index based on different typical areas of land use landscape index. The result of water conservation areas was good, the error rate between the predicted value and the actual value was below 10%, and the prediction accuracy was high. The study showed that water quality prediction based on land use and landscape index/water quality quantitative relationship model had a good water quality prediction effect.</p>","PeriodicalId":35937,"journal":{"name":"Huanjing Kexue/Environmental Science","volume":"45 10","pages":"5768-5776"},"PeriodicalIF":0.0,"publicationDate":"2024-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142509648","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}
引用次数: 0
[Spatial and Temporal Characteristics and Driving Force Analysis of Ecological Environmental Quality in Fengfeng Mining Area with Remote Sensing Ecological Index of PM2.5 Concentration]. [利用 PM2.5 浓度遥感生态指数分析峰峰矿区生态环境质量的时空特征及驱动力]。
Huanjing Kexue/Environmental Science Pub Date : 2024-10-08 DOI: 10.13227/j.hjkx.202311223
Jing-Han Zhang, Wei Zhang, An-Zhou Zhao, Li-Hui Sun
{"title":"[Spatial and Temporal Characteristics and Driving Force Analysis of Ecological Environmental Quality in Fengfeng Mining Area with Remote Sensing Ecological Index of PM<sub>2.5</sub> Concentration].","authors":"Jing-Han Zhang, Wei Zhang, An-Zhou Zhao, Li-Hui Sun","doi":"10.13227/j.hjkx.202311223","DOIUrl":"https://doi.org/10.13227/j.hjkx.202311223","url":null,"abstract":"<p><p>The Fengfeng mining area is an important coal-producing area in China and crucial environmental problems have been caused by large-scale exploitation of coal mines. The spatio-temporal evolution and driving factors of the ecological environment quality in this area must be explored for promoting the transformation of coal-based cities. Based on Landsat data of the Google earth engine (GEE) platform, this study constructed a new remote sensing-based ecological index (RSEInew) for the Fengfeng mining area from 2000 to 2020. The spatial and temporal evolution of RSEInew and its driving factors were evaluated by using trend analysis and geographic detector methods. The results showed that: ① From 2000 to 2020, the RSEInew of the Fengfeng mining area presented a fluctuating increasing trend (trend = 0.002 2), and the proportion of good and excellent ecological environmental quality showed an increasing trend, rising from 24.80% in 2000 to 65.54% in 2020. ② The change in the RSEInew grade indicated that the proportion of significant improvement (3 and 4) of ecological environment quality grade in the Fengfeng Mining area from 2000 to 2020 was 10.21%, which was mainly distributed in Hexun town and Yijing town in the northwest of the Fengfeng mining area. The proportion of significant degradation (-3 and -4) was only 1.58%, mainly scattered in Linshui town and Dashe town. ③ RSEInew values increased significantly during 2000-2020 in the area accounting for 18.29%, mainly distributed in the central and northern areas and the western fringe of the Fengfeng mining area. The significantly reduced area accounted for 9.25%, mainly concentrated in the eastern area of the Fengfeng mining area. The coefficient of variation results showed that the areas with high fluctuation of RSEInew were mainly concentrated in Pengcheng town and Linshui town in the middle and eastern Fengfeng mining area. ④ From the perspective of influencing factors, the average <i>q</i> value of land use type (X6) during 2000-2020 was 0.290, which was much higher than other factors. The <i>q</i> value of social and economic factors showed an increasing trend, indicating that the spatial distribution of ecological environment quality in this region was increasingly strongly influenced by human activities. The interaction results showed that land use change was the key factor influencing ecological environment quality in the Fengfeng mining area.</p>","PeriodicalId":35937,"journal":{"name":"Huanjing Kexue/Environmental Science","volume":"45 10","pages":"5900-5911"},"PeriodicalIF":0.0,"publicationDate":"2024-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142509635","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}
引用次数: 0
[Spatiotemporal Characterization and Driving Factors of Fine Particulate Matter and Its Chemical Components in the Huaihe River Basin]. [淮河流域细颗粒物及其化学成分的时空特征和驱动因素]。
Huanjing Kexue/Environmental Science Pub Date : 2024-10-08 DOI: 10.13227/j.hjkx.202312141
Xiao-Yong Liu, Ji-Qiang Niu, Hang Liu, Yi-Dan Zhang, Jun Yan, Jun-Hui Yan, Fang-Cheng Su
{"title":"[Spatiotemporal Characterization and Driving Factors of Fine Particulate Matter and Its Chemical Components in the Huaihe River Basin].","authors":"Xiao-Yong Liu, Ji-Qiang Niu, Hang Liu, Yi-Dan Zhang, Jun Yan, Jun-Hui Yan, Fang-Cheng Su","doi":"10.13227/j.hjkx.202312141","DOIUrl":"https://doi.org/10.13227/j.hjkx.202312141","url":null,"abstract":"<p><p>According to the data sets of fine particulate matter (PM<sub>2.5</sub>) and its components in 35 cities in the Huaihe River Basin from 2015 to 2021, the temporal and spatial distribution patterns of pollutants were analyzed. The influence of meteorological factors on PM<sub>2.5</sub> concentrations was examined using a random forest model. The original series of PM<sub>2.5</sub>, sulfate (SO<sub>4</sub><sup>2-</sup>), nitrate (NO<sub>3</sub><sup>-</sup>), ammonium salt (NH<sub>4</sub><sup>+</sup>), organic matter (OM), and black carbon (BC) were rebuilt using KZ (Kolmogorov-Zurbenko) filtering and multiple linear regression (MLR) to quantify the effects of meteorological conditions. The results demonstrated that from 2015 to 2021, the declining rates of PM<sub>2.5</sub>, SO<sub>4</sub><sup>2-</sup>, NO<sub>3</sub><sup>-</sup>, NH<sub>4</sub><sup>+</sup>, OM, and BC in the Huaihe River Basin were 4.71, 0.99, 1.05, 0.77, 1.01, and 0.19 μg·(m<sup>3</sup>·a)<sup>-1</sup>, respectively. The high mass concentrations of PM<sub>2.5</sub> and its components were concentrated in the central and western regions of the HRB, whereas those in coastal and southern cities were lower. The variance contributions of the short-term, seasonal, and long-term components of PM<sub>2.5</sub> to the original PM<sub>2.5</sub> sequences in 35 cities were 51.6%, 35.9%, and 7.0%, respectively. The PM<sub>2.5</sub> in coastal cities were more affected by the short-term components. The meteorological conditions were unfavorable for PM<sub>2.5</sub> reduction in the HRB from 2015 to 2018, whereas the meteorological conditions supported the PM<sub>2.5</sub> decrease from 2019 to 2021. From 2015 to 2021, the contribution rates of meteorological conditions to the long-term component reductions of PM<sub>2.5</sub>, SO<sub>4</sub><sup>2-</sup>, NO<sub>3</sub><sup>-</sup>, NH<sub>4</sub><sup>+</sup>, OM, and BC were 28.3%, 29.1%, 31.0%, 29.3%, 27.8%, and 28.6%, respectively. The contribution rates of meteorological conditions to the long-term PM<sub>2.5</sub> reduction were 43.4%, 25.6%, 25.5%, and 20.6% in the HRB cities in Anhui, Shandong, Jiangsu, and Henan Provinces, respectively. With the decrease in PM<sub>2.5</sub> concentration in the HRB, the sulfur oxidation rate (SOR) increased significantly, while the nitrogen oxide oxidation rate (NOR) changed little.</p>","PeriodicalId":35937,"journal":{"name":"Huanjing Kexue/Environmental Science","volume":"45 10","pages":"5650-5660"},"PeriodicalIF":0.0,"publicationDate":"2024-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142509638","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}
引用次数: 0
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