Cattle manure biochar and earthworm interactively affected CO2 and N2O emissions in agricultural and forest soils: Observation of a distinct difference

• Earthworms increase CO₂ and N₂O emissions in agricultural and forest soil. • 10% biochar suppresses CO₂ and N₂O emissions in forest soil. • Biochar interacted with earthworm to significant affect CO₂ and N₂O emissions. The application of manure-derived biochar offers an alternative to avoid the direct application of manure to soil causing greenhouse gas emission. Soil fauna, especially earthworms, can markedly stimulate carbon dioxide (CO₂) and nitrous oxide (N₂O) emissions from soil. This study therefore investigated the effect of cattle manure biochar (added at rates of 0, 2%, or 10%, coded as BC0, BC2 and BC10, respectively) application, with or without earthworm Aporrectodea turgida, on emissions of CO₂ and N₂O and changes of physic-chemical properties of agricultural and forest soils in a laboratory incubation experiment. The BC10 treatment significantly enhanced cumulative CO₂ emissions by 27.9% relative to the untreated control in the agricultural soil. On the contrary, the BC2 and BC10 treatments significantly reduced cumulative CO₂ emissions by 16.3%–61.1% and N₂O emissions by 92.9%–95.1% compared to the untreated control in the forest soil. The addition of earthworm alone significantly enhanced the cumulative CO₂ and N₂O fluxes in agricultural and forest soils. Cumulative CO₂ and N₂O fluxes were significantly increased when BC2 and BC10 were applied with earthworm in the agricultural soil, but were significantly reduced when BC10 was applied with earthworm in the forest soil. Our study demonstrated that biochar application interacted with earthworm to affect CO₂ and N₂O emissions, which were also dependent on the soil type involved. Our study suggests that manure biochar application rate and use of earthworm need to be carefully studied for specific soil types to maximize the climate change mitigation potential of such management practices.     

静力荷载作用下纤维材料增强路基性能的试验研究

分别采用现场铁路路基填料及掺量为0.3%的聚丙烯纤维改良填料构筑室内小型路基,通过对路基顶部施加不同的分级静载,对比研究两种不同填料对路基内应力分布规律和沉降变形特性的影响,进而判断纤维材料作为改良措施运用于路基沉降控制的可行性与有效性。试验结果表明:相对于现场填料路基,纤维改良措施加快了应力在路基中沿深度的扩散速度;应力加载至100 kPa时,两种填料路基的沉降变形规律相似,路基不同深度处的沉降随着基顶作用荷载的增加呈非线性增大;应力达到200 kPa时,纤维改良路基60 cm深度范围内的沉降曲线出现反转点,曲线形状近似拉长的s形;较于现场填料路基,纤维改良措施使基顶沉降分别减少了30.3%及35.4%;在高应力、大变形趋势条件下,纤维材料对路基沉降的控制效果会更好。     

The source and transport of bioaerosols in the air: A review

• Emission of microbe from local environments is a main source of bioaerosols. • Regional transport is another important source of the bioaerosols. • There are many factors affecting the diffusion and transport of bioaerosols. • Source identification method uncovers the contribution of sources of bioaerosols. Recent pandemic outbreak of the corona-virus disease 2019 (COVID-19) has raised widespread concerns about the importance of the bioaerosols. They are atmospheric aerosol particles of biological origins, mainly including bacteria, fungi, viruses, pollen, and cell debris. Bioaerosols can exert a substantial impact on ecosystems, climate change, air quality, and public health. Here, we review several relevant topics on bioaerosols, including sampling and detection techniques, characterization, effects on health and air quality, and control methods. However, very few studies have focused on the source apportionment and transport of bioaerosols. The knowledge of the sources and transport pathways of bioaerosols is essential for a comprehensive understanding of the role microorganisms play in the atmosphere and control the spread of epidemic diseases associated with them. Therefore, this review comprehensively summarizes the up to date progress on the source characteristics, source identification, and diffusion and transport process of bioaerosols. We intercompare three types of diffusion and transport models, with a special emphasis on a widely used mathematical model. This review also highlights the main factors affecting the source emission and transport process, such as biogeographic regions, land-use types, and environmental factors. Finally, this review outlines future perspectives on bioaerosols.     

2010～2019年雅鲁藏布江中游植被变化及其对气候因子的响应——以拉林铁路段为例

基于2010～2019年MOD13Q1/NDVI数据,结合研究区地形、1∶100万植被类型图和气象数据,采用趋势分析法、相关分析方法,探讨在气候变化背景下雅鲁藏布江拉林铁路段植被覆盖的时空演变规律及植被与气温、降水的相关性研究.结果 表明,2010～2019年研究区生长季NDVI值呈波动上升趋势,增速为0.2％/10a...     

压缩致密化阻燃木材的燃烧特性和成炭行为研究

为增强木材的阻燃性能,采用压缩致密化工艺制备致密化阻燃木材,并对其燃烧特性与成炭行为进行研究。结果表明：压缩致密化工艺能促进木材在燃烧过程中形成更多的芳香结构以增强炭层的致密性和隔热性,进而有效阻隔热量和氧气进入木材内部,使致密化木材表现出良好的阻燃性和自熄性。压缩致密化木材的阻燃和隔热性能与去木质化程度密切相关,并随去木质化程度的增加呈先提高后下降的趋势。经过24 h去木质素处理后的致密化木材的极限氧指数增加到39.5%并达到UL94 V-0级,总释放热和2 400 s背面平衡温度相比于未去木质素的致密化木材分别下降了25.8%和21.4%,表现出最佳的阻燃和隔热性能。     

露天矿山运输路面泡沫抑尘剂的配方优选及性能试验研究

为有效解决露天矿山运输路面的大量扬尘,针对现有抑尘剂存在的降解性差、成本较高、保水率差、除尘效率过低等问题,在对某露天矿山的扬尘进行表征分析的基础上,采用绿色表面活性剂烷基糖苷0.1%APG作为主剂、0.6%K12作为起泡剂、0.4%PAM作为稳泡剂、0.3%LAS作为润湿剂,通过测定泡沫的表面张力、泡沫体积、粉尘接触角、粉尘浸润深度确定各试剂的最佳质量分数,初步确定6个泡沫抑尘剂配方,选择保水率、抗风蚀性、抑尘效率作为性能指标,结果表明：配方为m(0.6%K12)∶m(0.1%APG)∶m(0.4%PAM)∶m(0.3%LAS)=1.05∶1∶0.6∶0.1的保水性、抗压强度、抗风蚀性均优于其他配方,全尘与呼吸性粉尘的抑尘效率分别高达87.11%,75.26%,经pH测试,符合绿色环保的要求。     

短链脂肪酸对太湖底泥多氯联苯微生物厌氧脱氯的影响

选取二氯联苯PCB5和PCB12、四氯联苯PCB64和PCB71、类二噁英五氯联苯PCB105和PCB114、六氯联苯PCB149和PCB153、七氯联苯PCB170,考察了添加7.5mmol/L乙酸和7.5mmol/L混合酸（乙酸：丙酸：丁酸=1：1：1）条件下,9种典型商业多氯联苯单体在太湖底泥厌氧微环境中24周内的脱氯降解情况.结果表明：乙酸和混合酸的添加均在一定程度上强化了多氯联苯的降解,多氯联苯总浓度降低速率由（0.276±0.023） mg/（kg·week）分别加快至（0.383±0.033）和（0.410±0.036） mg/（kg·week）;提高了部分脱氯路径的相对反应速率,特别是单侧氯取代的对位脱氯,但未改变脱氯微生物对多氯联苯降解底物的选择性及主要脱氯路径;进一步降低了体系类二噁英多氯联苯总毒性当量（TEQ）,24周降幅均在95%以上;乙酸和混合酸所起到的促进效果并无显著性差异.     

华南地区城市道路雨水径流对降雨特征的响应机制——以深圳市为例

合理设计道路面源污染控制设施(如低冲击开发设施)需要深入掌握被治理地区的径流污染特征及其影响因素。通过利用单变量与多变量数据分析相结合的方式对位处华南地区的深圳市道路雨水径流特性进行研究,结果表明道路雨水径流污染与降雨特征和污染物种类有着密切的关系。氮类污染物在小雨强所产生的降雨径流中浓度较高而颗粒物则相反,化学需氧量和磷随降雨特征变化相对较小。这说明不同的污染物种类呈现出对降雨特征不同的响应机制。因此在设计相关径流污染控制措施时,应该选择合适的降雨类型作为设计依据以满足对不同污染物的去除要求。     

全国污染物排放申报登记信息管理系统（SBMIS）在新疆的应用

１９９７年,我区利用全国排污申报登记信息管理系统完成了全区范围的污染物排放申报登记工作,在此基础上,我们对ＳＢＭＩＳ系统的功能及应用范围做了认真研究,分析了该系统在使用过程中存在的问题,展望了其应用前景。     

基于强化学习的城镇燃气事故信息抽取方法

为解决因城镇燃气事故调查报告标注样本缺乏,从而影响命名实体识别性能这一问题,提出基于BiLSTM-CRF+强化学习的燃气事故领域命名实体识别方法。首先在数据预处理阶段,采用基于文本结构的主旨段落抽取方法,识别事故调查报告的关键段落;其次在模型训练阶段,采用BiLSTM-CRF+强化学习模型,实现城镇燃气事故命名实体识别模型训练;最后利用城镇燃气事故调查报告作为试验数据进行验证。研究结果表明:经由强化学习模型降噪后,实体识别模型的综合评价指标提高5.76%,主旨段落识别方法相比Word2vec特征表示方法,使模型的综合评价指标提升7.17%。