Changes in air pollution during COVID-19 lockdown in Spain: A multi-city study

The COVID-19 pandemic has escalated into one of the largest crises of the 21st Century. The new SARS-CoV-2 coronavirus, responsible for COVID-19, has spread rapidly all around the world. The Spanish Government was forced to declare a nationwide lockdown in view of the rapidly spreading virus and high mortality rate in the nation. This study investigated the impact of short-term lockdown during the period from March 15th to April 12th 2020 on the atmospheric levels of CO, SO₂, PM₁₀, O₃, and NO₂ over 11 representative Spanish cities. The possible influence of several meteorological factors (temperature, precipitation, wind, sunlight hours, minimum and maximum pressure) on the pollutants' levels were also considered. The results obtained show that the 4-week lockdown had significant impact on reducing the atmospheric levels of NO₂ in all cities except for the small city of Santander as well as CO, SO₂, and PM₁₀ in some cities, but resulted in increase of O₃ level.     

长江经济带典型矿业城市马鞍山市大气污染特征及颗粒物潜在源研究

本文利用2017-2020年监测数据对长江经济带典型矿业城市马鞍山市的主要大气污染物(PM2.5、PM10、SO2、CO和O3)进行了系统性分析.2017-2020年PM10和PM2.5的年均浓度分别为85.55、78.15、70.39、57.77 μg·m-3和50.44、45.21、43.36、36.30μg·m-...     

Significant contribution of secondary particulate matter to recurrent air pollution: Evidence from in situ observation in the most polluted city of Fen-Wei Plain of China

Particulate matter (PM) pollution in high emission regions will affect air quality, human health and climate change on both local and regional scales, and thus attract worldwide attention. In this study, a comprehensive study on PM_2.5 and its chemical composition were performed in Yuncheng (the most polluted city of Fen-Wei Plain of China) from November 28, 2020 to January 24, 2021. The average concentration of PM_2.5 was 87.8 ± 52.0 μg/m³, which were apparently lower than those observed during the same periods of past five years, attributable to the clean air action plan implemented in this region. NO₃⁻ and organic carbon (OC) were the dominant particulate components, which on average contributed 22.6% and 16.5% to PM_2.5, respectively. The fractions of NO₃⁻, NH₄⁺, OC and trace metals increased while those of crustal materials and elemental carbon decreased with the degradation of PM_2.5 pollution. Six types of PM_2.5 sources were identified by the PMF model, including secondary inorganic aerosol (35.3%), coal combustion (28.7%), vehicular emission (20.7%), electroplating industry (8.6%), smelt industry (3.9%) and dust (2.8%). Locations of each identified source were pinpointed based on conditional probability function, potential source contribution function and concentration weighted trajectory, which showed that the geographical distribution of the sources of PM_2.5 roughly agreed with the areas of high emission. Overall, this study provides valuable information on atmospheric pollution and deems beneficial for policymakers to take informed action to sustainably improve air quality in highly polluted region.     

PAHs pollution from traffic sources in air of Hangzhou, China: Trend and influencing factors

Introduction China is experiencing rapid economic and populationgrowth. The rapid growth and increasing fossil fuel energyconsumption have resulted in large amounts of pollutants suchas TSP, SO2, NOx and hydrocarbons to be emitted intoambient atmosphere. Nowadays, national routine monitor haspaid much attention to TSP, SO2 and NOx. Highconcentrations of SO2 and NOx can lead to an increase ofregional levels of acid deposition and tropospheric ozon, thu…     

2013—2015年北京污染频发期细颗粒物重污染成因与天气形势关系的研究

我国重污染呈现愈演愈烈态势,重污染事件在供暖季节（污染频发期）尤为频发.本文利用北京2013—2015年采暖期逐小时PM_2.5浓度数据、再分析资料、气团后向轨迹、气溶胶雷达数据以及探空数据综合分析了北京地区重污染状况,概括了重污染发生时常见的天气形势,探讨了重污染形成原因与天气形势的关系.研究结果表明：2013—2015年采暖期北京发生重污染（日均PM_2.5浓度大于150 μg·m^-3）的天数分别为36、28及35 d,即北京采暖期21.9%的天数受重污染天气影响.2月份重污染事件最为频发,发生频次为27.3%.北京发生重污染事件时,地面被高压控制时,高空500 hPa多东移的槽脊,当位于脊后槽前时,为上升运动,西南风,850 hPa多暖平流,西南风输送暖湿气流,湿度较大,地面偏南风,可能会存在污染物的输送;地面为低压控制时,500 hPa一般为稳定的西风气流或西北气流,低空850 hPa可能存在暖平流,地面常伴随弱的风场辐合,导致污染物累积;当地面为均压场时,高空500 hPa多为脊后槽前的形势,低空无明显冷暖平流,地面等压线稀疏或无等压线,静风天气.这3类结构引发的重污染天数分别占总重污染天数的47.3%、18.2%及34.5%.进一步分析重污染成因与天气形势关系表明：北京地面受高压系统控制时,污染时间持续最长,也最为频发（47.3%）,PM_2.5平均浓度最高可达258.8 μg·m^-3,且常伴随来自西南方向的污染物输送,北京上空1 km附近存在逆温和逆湿.对污染传输路径研究发现：主要存在3条输送通道,①天津-廊坊-北京、②沧州-廊坊-北京、③石家庄-保定-北京.鉴于目前数值模式对天气形势的预报较为成熟,本文对区域重污染过程与天气形势之间的关系研究,有助于为北京地区空气质量的精准预报预警提供科学支持.     

Air quality from a social perspective in four European metropolitan areas: Research hypothesis and evidence from the SEFIRA project

This paper analyses social constraints influencing air quality governance in four European Union (EU) countries. The comparative analysis carried out here is the outcome of the EU FP7 SEFIRA project. Starting from study of implemented measures the paper marks out the structure of double-delegation in policy-making for air quality governance; that is to say the delegation from the EU to national governments who further delegate to regional and local authorities the burden to put in place concrete measures. Therefore, our analysis has followed a multi-level approach considering all the territorial level down to the urban scale. In doing so, we found out commonalities in the strategies which have been followed by policy-makers. The comparison has been made possible through the analysis of operationalised categories such as Domain, Objectives and Modalities on air quality plans. The analysis went further: through interviews with selected key stakeholder the social constraints which may limit the choices made by institutions have been investigated. The -lack of- success in attaining EU requirements for the air quality cannot be considered only as the outcome of the −lack of- awareness of which may be the best practices or choices, rather as the result of complex entanglements of social forces. Indeed, one of the main outcomes of this explorative investigation has been the breakdown of such complexity into its social component in a comparative study. The paper finally points out the need to promote an integrated approach for air quality policy as a strategy for the design of new measures for the future.