Public perception of air pollution sources across Europe

Air pollution is one of the primary concerns of our society for its effect on human health and the environment. Among the policy measures that can be put in place to limit air pollutant emissions, end-of-pipe technologies and/or regulatory instruments may be implemented through legislative acts. Also, equally important are behavioural measures, requiring citizens’ active involvement. The success of any measure to limit pollutant emissions requires the acceptance by the citizens that, in turn, implies a correct perception of the main pollutant emission drivers. We present here the comparison between the public perception of air pollution sources and the real-world situation through a survey carried out in seven European countries and involving 16 101 respondents. Our study shows a dramatic underestimation of the contribution of the agri-food sector to air pollution. This result is common to all respondents in the seven countries examined and only to a small extent depends on gender, age and socio-economic status of the respondents.     

高烈度地震区隧道软硬围岩交接段刚柔并济抗减震技术研究*

为提高高烈度地震区隧道抗震性能，以某铁路隧道为研究背景，分析3种抗减震措施下隧道不同监测点隧道拱顶沉降、边墙收敛、衬砌结构PGA及最小安全系数，通过对比分析得到最优抗减震措施。结果表明:相比于工况1，工况2隧道拱顶沉降减小10.54%~81.10%，边墙收敛减小13.92%~78.77%，衬砌结构PGA减小31.42%~72.02%，最小安全系数增加18.04%~66.13%；相比于工况1，工况3结构拱顶沉降减小3.04%~18.02%，边墙收敛减小4.70%~32.00%，PGA增加13.95%~27.48%，最小安全系数增加7.49%~30.99%；工况4即“减震层+SFRC衬砌”刚柔并济法，相比于工况1，隧道拱顶沉降减小18.46%~83.98%，结构边墙收敛减小17.54%~85.47%，PGA减小30.00%~69.98%，最小安全系数增加47.95%~83.56%；4种工况抗减震性能由高到低依次为:工况4＞工况2＞工况3＞工况1。研究结果可为隧道软硬围岩交接段抗震设防提供理论参考。     

地表水环境遥感监测关键技术与系统

介绍了地表水环境遥感监测的关键技术与系统及其典型应用,其代表性机理模型和应用示范成果主要来自于中国科学院遥感与数字地球研究所的高光谱遥感团队在最近几年中取得的一些研究进展,主要包括建立了基于改进双峰法的水体分布自动化遥感提取方法,实现了简单、高效和高精度的水体提取；提出了大型湖泊长时序水量估算方法,并以青藏高原湖区为例,重建了典型湖泊面积、水位和水量序列；发展了基于“软分类”的典型内陆水体叶绿素a浓度反演方法,构建了基于生物光学模型的高度浑浊水体悬浮物浓度遥感反演半解析方法,提高了反演方法的区域和季节适用性；构建了基于水色指数的大范围湖库营养状态和透明度遥感监测方法,实现了全球大型湖库营养状态遥感监测,以及全国大型湖库透明度遥感监测；在此基础上,开发了地表水环境遥感监测系统,提高了水环境遥感监测效率,促进了卫星遥感在水环境监测中的高精度业务化应用。     

Critical review for the quantification of leachate production: Evaluation example for the “Oum Azza” public landfill in Rabat city,Morocco

The estimation of leachate quantities produced in landfills is necessary to dimension the treatment plants allowing to reduce the polluting load of these effluents and consequently avoid their negative impacts on the environment. Different leachate quantification methods were used in this study to assess the leachate volume produced at the Oum Azza landfill. The water balance method give comparable estimations of leachate production to the Ouled Berjal landfill ratio. The first method showed average values between 487 and 495 m³/day for 2015, 2018, and 2019, and at the same time, the second method gave values between 470 and 477 m³/day for the same years. In contrast, the World Bank ratio showed high values that vary between 2260 and 2295 m³/day for 2015, 2018, and 2019. The on-site data and the statistical analysis showed us that the World Bank ratio is not adapted for the estimation of the leachates produced in Oum Azza landfill, while the water balance and the ratio of Ouled Berjal landfill allowed to give comparable results to reality.     

A remote sensing tool for near real-time monitoring of harmful algal blooms and turbidity in reservoirs

Harmful algal blooms (HABs) diminish the utility of reservoirs for drinking water supply, irrigation, recreation, and ecosystem service provision. HABs decrease water quality and are a significant health concern in surface water bodies. Near real-time monitoring of HABs in reservoirs and small water bodies is essential to understand the dynamics of turbidity and HAB formation. This study uses satellite imagery to remotely sense chlorophyll-a concentrations (chl-a), phycocyanin concentrations, and turbidity in two reservoirs, the Grand Lake O′ the Cherokees and Hudson Reservoir, OK, USA, to develop a tool for near real-time monitoring of HABs. Landsat-8 and Sentinel-2 imagery from 2013 to 2017 and from 2015 to 2020 were used to train and test three different models that include multiple regression, support vector regression (SVR), and random forest regression (RFR). Performance was assessed by comparing the three models to estimate chl-a, phycocyanin, and turbidity. The results showed that RFR achieved the best performance, with R² values of 0.75, 0.82, and 0.79 for chl-a, turbidity, and phycocyanin, while multiple regression had R² values of 0.29, 0.51, and 0.46 and SVR had R² values of 0.58, 0.62, and 0.61 on the testing datasets, respectively. This paper examines the potential of the developed open-source satellite remote sensing tool for monitoring reservoirs in Oklahoma to assess spatial and temporal variations in surface water quality.     

Effect of ambient polycyclic aromatic hydrocarbons and nicotine on the structure of Aβ42 protein

● B[a]P, nicotine and phenanthrene molecules altered the secondary structure of Aβ₄₂. ● β-content of the peptide was significantly enhanced in the presence of the PAHs. ● Nicotine made stable cluster with Aβ₄₂ peptide via hydrogen bonds. ● Phenanthrene due to its small size, interfered with the Aβ₄₂ monomer more strongly. Recent studies have correlated the chronic impact of ambient environmental pollutants like polycyclic aromatic hydrocarbons (PAHs) with the progression of neurodegenerative disorders, either by using statistical data from various cities, or via tracking biomarkers during in-vivo experiments. Among different neurodegenerative disorders, PAHs are known to cause increased risk for Alzheimer’s disease, related to the development of amyloid beta (Aβ) peptide oligomers. However, the complex molecular interactions between peptide monomers and organic pollutants remains obscured. In this work, we performed an atomistic molecular dynamics study via GROMACS to investigate the structure of Aβ₄₂ peptide monomer in the presence of benzo[a]pyrene, nicotine, and phenanthrene. Interestingly the results revealed strong hydrophobic, and hydrogen-bond based interactions between Aβ peptides and these environmental pollutants that resulted in the formation of stable intermolecular clusters. The strong interactions affected the secondary structure of the Aβ₄₂ peptide in the presence of the organic pollutants, with almost 50 % decrease in the α-helix and 2 %–10 % increase in the β-sheets of the peptide. Overall, the undergoing changes in the secondary structure of the peptide monomer in the presence of the pollutants under the study indicates an enhanced formation of Aβ peptide oligomers, and consequent progression of Alzheimer’s disease.     

A new prediction method of industrial atmospheric pollutant emission intensity based on pollutant emission standard quantification

● Established a quantification method of pollutant emission standard. ● Predicted the SO₂ emission intensity of single coking enterprises in China. ● Evaluated the influence of pollutant discharge standard on prediction accuracy. ● Analyzed the SO₂ emissions of Chinese provincial and municipal coking enterprises. Industrial emissions are the main source of atmospheric pollutants in China. Accurate and reasonable prediction of the emission of atmospheric pollutants from single enterprise can determine the exact source of atmospheric pollutants and control atmospheric pollution precisely. Based on China’s coking enterprises in 2020, we proposed a quantitative method for pollutant emission standards and introduced the quantification results of pollutant emission standards (QRPES) into the construction of support vector regression (SVR) and random forest regression (RFR) prediction methods for SO₂ emission of coking enterprises in China. The results show that, affected by the types of coke ovens and regions, China’s current coking enterprises have implemented a total of 21 emission standards, with marked differences. After adding QRPES, it was found that the root mean squared error (RMSE) of SVR and RFR decreased from 0.055 kt/a and 0.059 kt/a to 0.045 kt/a and 0.039 kt/a, and theR² increased from 0.890 and 0.881 to 0.926 and 0.945, respectively. This shows that the QRPES can greatly improve the prediction accuracy, and the SO₂ emissions of each enterprise are highly correlated with the strictness of standards. The predicted result shows that 45% of SO₂ emissions from Chinese coking enterprises are concentrated in Shanxi, Shaanxi and Hebei provinces in central China. The method created in this paper fills in the blank of forecasting method of air pollutant emission intensity of single enterprise and is of great help to the accurate control of air pollutants.     

我国居住建筑室内PM_(2.5)研究现状及进展

分析了我国居住建筑室内PM_(2.5)污染水平,总结了现阶段PM_(2.5)的研究方法,主要包括理论分析法、数值模拟法和实验测试法。指出室外源是室内PM_(2.5)的主要污染来源,而室内烟草烟雾、烹饪及人员活动也会严重影响室内PM_(2.5)浓度。针对目前研究中存在的问题,提出了标定典型建筑在不同影响因素下的I/O比范围、研究家具和家电的颗粒物释放状况、加强农村室内外空气颗粒物污染调查等建议。     

固定源排污许可证监测管理制度研究

依靠排污许可证管理,固定源执行由行业排放标准为主正逐步过渡到"国家行业排放标准——单一源排放标准"双层排放标准,并以执行更全面和精准的单一源排放标准为主,对应的监测要求及考核方式更加多样化。对监测管理制度进行设计,明确固定源制定自行监测方案和守法监测的主体责任,厘清许可证核发部门、属地监测、执法部门的监管职责。系统设计"固定源制定并提交自行监测方案-核发部门审核-方案纳入排污许可证中成为规定-依规定自行监测和记录-固定源提交执行报告-监管部门审计式审核-执法监测和执法检查"的全过程管理机制,设计标准化的监管计划程序落实证后监管与执法监测,明晰监管部门的有限责任。     

天水市紫外吸收性气溶胶时空动态的遥感监测

采用OMI传感器的气溶胶产品,分析了2006—2015年中国西部城市天水市对流层紫外吸收性气溶胶的时空分布特征。结果表明:空间上,十年间天水市的吸收性气溶胶表现出从中部向周围依次减弱的南北向带状分布规律;季节变化呈现出秋冬季高于春夏季的规律;时间上,吸收性气溶胶指数(AI)从2006年的0.075增至2015年的0.506,年均值为0.28,年均增长率为57.5%;十年间出现2次阶段性增长和2次阶段性减小;AI年际变化与天水市地方总产值相关性为0.902,第一产业对其影响最大,第三产业影响最小。