Browsing by Subject "POLLUTION"

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  • Du, Wei; Dada, Lubna; Zhao, Jian; Chen, Xueshun; Dällenbach, Kaspar; Xie, Conghui; Wang, Weigang; He, Yao; Cai, Jing; Yao, Lei; Zhang, Yingjie; Wang, Qingqing; Xu, Weiqi; Wang, Yuying; Tang, Guiqian; Cheng, Xueling; Kokkonen, Tom V.; Zhou, Wei; Yan, Chao; Chu, Biwu; Zha, Qiaozhi; Hakala, Simo; Kurppa, Mona; Jarvi, Leena; Liu, Yongchun; Li, Zhanqing; Ge, Maofa; Fu, Pingqing; Nie, Wei; Bianchi, Federico; Petäjä, Tuukka; Paasonen, Pauli; Wang, Zifa; Worsnop, Douglas R.; Kerminen, Veli-Matti; Kulmala, Markku; Sun, Yele (2021)
    The role of new particle formation (NPF) events and their contribution to haze formation through subsequent growth in polluted megacities is still controversial. To improve the understanding of the sources, meteorological conditions, and chemistry behind air pollution, we performed simultaneous measurements of aerosol composition and particle number size distributions at ground level and at 260 m in central Beijing, China, during a total of 4 months in 2015-2017. Our measurements show a pronounced decoupling of gas-to-particle conversion between the two heights, leading to different haze processes in terms of particle size distributions and chemical compositions. The development of haze was initiated by the growth of freshly formed particles at both heights, whereas the more severe haze at ground level was connected directly to local primary particles and gaseous precursors leading to higher particle growth rates. The particle growth creates a feedback loop, in which a further development of haze increases the atmospheric stability, which in turn strengthens the persisting apparent decoupling between the two heights and increases the severity of haze at ground level. Moreover, we complemented our field observations with model analyses, which suggest that the growth of NPF-originated particles accounted up to similar to 60% of the accumulation mode particles in the Beijing-Tianjin-Hebei area during haze conditions. The results suggest that a reduction in anthropogenic gaseous precursors, suppressing particle growth, is a critical step for alleviating haze although the number concentration of freshly formed particles (3-40 nm) via NPF does not reduce after emission controls.
  • Sokhi, Ranjeet S.; Singh, Vikas; Querol, Xavier; Finardi, Sandro; Targino, Admir Creso; Andrade, Maria de Fatima; Pavlovic, Radenko; Garland, Rebecca M.; Massague, Jordi; Kong, Shaofei; Baklanov, Alexander; Ren, Lu; Tarasova, Oksana; Carmichael, Greg; Peuch, Vincent-Henri; Anand, Vrinda; Arbilla, Graciela; Badali, Kaitlin; Beig, Gufran; Carlos Belalcazar, Luis; Bolignano, Andrea; Brimblecombe, Peter; Camacho, Patricia; Casallas, Alejandro; Charland, Jean-Pierre; Choi, Jason; Chourdakis, Eleftherios; Coll, Isabelle; Collins, Marty; Cyrys, Josef; da Silva, Cleyton Martins; Di Giosa, Alessandro Domenico; Di Leo, Anna; Ferro, Camilo; Gavidia-Calderon, Mario; Gayen, Amiya; Ginzburg, Alexander; Godefroy, Fabrice; Alexandra Gonzalez, Yuri; Guevara-Luna, Marco; Haque, Sk Mafizul; Havenga, Henno; Herod, Dennis; Horrak, Urmas; Hussein, Tareq; Ibarra, Sergio; Jaimes, Monica; Kaasik, Marko; Kousa, Anu; Kukkonen, Jaakko; Kulmala, Markku; Kuula, Joel; Petäjä, Tuukka (2021)
    This global study, which has been coordinated by the World Meteorological Organization Global Atmospheric Watch (WMO/GAW) programme, aims to understand the behaviour of key air pollutant species during the COVID-19 pandemic period of exceptionally low emissions across the globe. We investigated the effects of the differences in both emissions and regional and local meteorology in 2020 compared with the period 2015-2019. By adopting a globally consistent approach, this comprehensive observational analysis focuses on changes in air quality in and around cities across the globe for the following air pollutants PM2.5, PM10, PMC (coarse fraction of PM), NO2, SO2, NOx, CO, O-3 and the total gaseous oxidant (O-X = NO2 + O-3) during the pre-lockdown, partial lockdown, full lockdown and two relaxation periods spanning from January to September 2020. The analysis is based on in situ ground-based air quality observations at over 540 traffic, background and rural stations, from 63 cities and covering 25 countries over seven geographical regions of the world. Anomalies in the air pollutant concentrations (increases or decreases during 2020 periods compared to equivalent 2015-2019 periods) were calculated and the possible effects of meteorological conditions were analysed by computing anomalies from ERA5 reanalyses and local observations for these periods. We observed a positive correlation between the reductions in NO2 and NOx concentrations and peoples' mobility for most cities. A correlation between PMC and mobility changes was also seen for some Asian and South American cities. A clear signal was not observed for other pollutants, suggesting that sources besides vehicular emissions also substantially contributed to the change in air quality. As a global and regional overview of the changes in ambient concentrations of key air quality species, we observed decreases of up to about 70% in mean NO2 and between 30% and 40% in mean PM2.5 concentrations over 2020 full lockdown compared to the same period in 2015-2019. However, PM2.5 exhibited complex signals, even within the same region, with increases in some Spanish cities, attributed mainly to the long-range transport of African dust and/or biomass burning (corroborated with the analysis of NO2/CO ratio). Some Chinese cities showed similar increases in PM2.5 during the lockdown periods, but in this case, it was likely due to secondary PM formation. Changes in O-3 concentrations were highly heterogeneous, with no overall change or small increases (as in the case of Europe), and positive anomalies of 25% and 30% in East Asia and South America, respectively, with Colombia showing the largest positive anomaly of similar to 70%. The SO2 anomalies were negative for 2020 compared to 2015-2019 (between similar to 25 to 60%) for all regions. For CO, negative anomalies were observed for all regions with the largest decrease for South America of up to similar to 40%. The NO2/CO ratio indicated that specific sites (such as those in Spanish cities) were affected by biomass burning plumes, which outweighed the NO2 decrease due to the general reduction in mobility (ratio of similar to 60%). Analysis of the total oxidant (OX = NO2 + O-3) showed that primary NO2 emissions at urban locations were greater than the O-3 production, whereas at background sites, O-X was mostly driven by the regional contributions rather than local NO2 and O-3 concentrations. The present study clearly highlights the importance of meteorology and episodic contributions (e.g., from dust, domestic, agricultural biomass burning and crop fertilizing) when analysing air quality in and around cities even during large emissions reductions. There is still the need to better understand how the chemical responses of secondary pollutants to emission change under complex meteorological conditions, along with climate change and socio-economic drivers may affect future air quality. The implications for regional and global policies are also significant, as our study clearly indicates that PM2.5 concentrations would not likely meet the World Health Organization guidelines in many parts of the world, despite the drastic reductions in mobility. Consequently, revisions of air quality regulation (e.g., the Gothenburg Protocol) with more ambitious targets that are specific to the different regions of the world may well be required.
  • Marin-Gomez, Oscar H.; MacGregor-Fors, Ian (2021)
    Urbanization drives changes in acoustic communication systems in some animal species. Noise and light pollution are among the main urban factors known to disrupt the timing and structure of avian singing behaviour. Despite our understanding of the ways in which urbanization can drive variations in avian acoustic communication, our ability to generalize the underlying causes of such variation and its consequences is still limited. Here, we reviewed the literature focused on the study of avian dawn choruses in urban settings at a global scale. Our findings reveal that avian dawn chorus research has focused on the impact of anthropogenic noise on dawn chorus traits (i.e. timing, peak, song output, song frequencies); relationships between light pollution and chorus timing; the effects of temperature, cloudiness, moonlight and natural light on chorus timing; relationships between nocturnal noise and light, and dawn chorus timing; the effects of chemical pollution and supplementary feeding on dawn chorus activity; and ecological patterns of dawn choruses in soundscapes across urban-non-urban gradients. We identified important knowledge gaps in the study of avian dawn choruses in urban settings and thus suggest future research directions, including frameworks (e.g. the urbanization intensity gradient) and consideration of a wider array of urban conditions and variables. Given the complexity of urban settings, we encourage further studies to address the role that all sources of pollution can have on avian acoustic communication at dawn. Additionally, a central question to resolve is whether the function of avian dawn choruses in urban areas differs, and if so how, from non-urban counterparts. Given that most research has been performed across Holarctic cities and towns, studies from tropical and subtropical regions are needed if we aim to understand the phenomenon globally. Finally, studies at the community- and soundscape-level across cities could advance understanding of the way in which urban birds use the acoustic space during the most critical singing time period, dawn.
  • Belis, C. A.; Karagulian, F.; Amato, F.; Almeida, M.; Artaxo, P.; Beddows, D. C. S.; Bernardoni, V.; Bove, M. C.; Carbone, S.; Cesari, D.; Contini, D.; Cuccia, E.; Diapouli, E.; Eleftheriadis, K.; Favez, O.; El Haddad, I.; Harrison, R. M.; Hellebust, S.; Hovorka, J.; Jang, E.; Jorquera, H.; Kammermeier, T.; Karl, M.; Lucarelli, F.; Mooibroek, D.; Nava, S.; Nojgaard, J. K.; Paatero, P.; Pandolfi, M.; Perrone, M. G.; Petit, J. E.; Pietrodangelo, A.; Pokorna, P.; Prati, P.; Prevot, A. S. H.; Quass, U.; Querol, X.; Saraga, D.; Sciare, J.; Sfetsos, A.; Valli, G.; Vecchi, R.; Vestenius, M.; Yubero, E.; Hopke, P. K. (2015)
    The performance and the uncertainty of receptor models (RMs) were assessed in intercomparison exercises employing real-world and synthetic input datasets. To that end, the results obtained by different practitioners using ten different RMs were compared with a reference. In order to explain the differences in the performances and uncertainties of the different approaches, the apportioned mass, the number of sources, the chemical profiles, the contribution-to-species and the time trends of the sources were all evaluated using the methodology described in Bells et al. (2015). In this study, 87% of the 344 source contribution estimates (SCEs) reported by participants in 47 different source apportionment model results met the 50% standard uncertainty quality objective established for the performance test. In addition, 68% of the SCE uncertainties reported in the results were coherent with the analytical uncertainties in the input data. The most used models, EPA-PMF v.3, PMF2 and EPA-CMB 8.2, presented quite satisfactory performances in the estimation of SCEs while unconstrained models, that do not account for the uncertainty in the input data (e.g. APCS and FA-MLRA), showed below average performance. Sources with well-defined chemical profiles and seasonal time trends, that make appreciable contributions (>10%), were those better quantified by the models while those with contributions to the PM mass close to 1% represented a challenge. The results of the assessment indicate that RMs are capable of estimating the contribution of the major pollution source categories over a given time window with a level of accuracy that is in line with the needs of air quality management. (C) 2015 The Authors. Published by Elsevier Ltd.
  • Demmler, Joanne C.; Gosztonyi, Ákos; Du, Yaxing; Leinonen, Matti; Ruotsalainen, Laura; Järvi , Leena; Ala-Mantila, Sanna (2021)
    Background Air pollution is one of the major environmental challenges cities worldwide face today. Planning healthy environments for all future populations, whilst considering the ongoing demand for urbanisation and provisions needed to combat climate change, remains a difficult task. Objective To combine artificial intelligence (AI), atmospheric and social sciences to provide urban planning solutions that optimise local air quality by applying novel methods and taking into consideration population structures and traffic flows. Methods We will use high-resolution spatial data and linked electronic population cohort for Helsinki Metropolitan Area (Finland) to model (a) population dynamics and urban inequality related to air pollution; (b) detailed aerosol dynamics, aerosol and gas-phase chemistry together with detailed flow characteristics; (c) high-resolution traffic flow addressing dynamical changes at the city environment, such as accidents, construction work and unexpected congestion. Finally, we will fuse the information resulting from these models into an optimal city planning model balancing air quality, comfort, accessibility and travelling efficiency.
  • Kotze, D. Johan; Kuoppamaki, Kirsi; Niemikapee, Juhamatti; Mesimaki, Marja; Vaurola, Ville; Lehvavirta, Susanna (2020)
    The proliferation of vegetated, or green roofs, warrant a revisit of the terminology used in order to efficiently, and without confusion, convey information among scientists, policy makers and practitioners. A Web of Science and Google Scholar search (from 1996 to 2018) showed a steady increase in green roof articles, reaching close to 300 per year in WOS and ca. 2500 in Google Scholar, with approximately 10-20%, and up to 40 % of all articles using the terms extensive and/or intensive, especially in recent years. We evaluated the use of these terms, including 'green roof, and 'intensive and extensive roof', found that they are used in confusing ways, and provide compelling evidence that there is a need for revising the terminology. Acknowledging that most, if not all, vegetated roofs are multifunctional, we propose a new classification system based on the roof's primary function(s) and vegetation, such as "stormwater meadow roof", "biodiversity meadow roof", "biodiversity forest roof", or even "multifunctional meadow roof". This new terminological sphere is not meant to be rigid, but should be allowed to evolve so that useful combinations survive the scrutiny of academia and practitioners, while less useful ones go extinct. A clear and standardized terminology will serve to avoid confusion, allow for generalizations and aid in the development of this rapidly-expanding field.
  • Petäjä, Tuukka; Ovaska, Aino; Fung, Pak Lun; Poutanen, Pyry; Yli-Ojanperä, Jaakko; Suikkola, Jari; Laakso, Mikko; Mäkelä, Taneli; Niemi, Jarkko V.; Keskinen, Jorma; Järvinen, Anssi; Kuula, Joel; Kurppa, Mona; Hussein, Tareq; Tarkoma, Sasu; Kulmala, Markku; Karppinen, Ari; Manninen, Hanna E.; Timonen, Hilkka (2021)
    Poor air quality influences the quality of life in the urban environment. The regulatory observation stations provide the backbone for the city administration to monitor urban air quality. Recently a suite of cost-effective air quality sensors has emerged to provide novel insights into the spatio-temporal variability of aerosol particles and trace gases. Particularly in low concentrations these sensors might suffer from issues related e.g., to high detection limits, concentration drifts and interdependency between the observed trace gases and environmental parameters. In this study we characterize the optical particle detector used in AQT530 (Vaisala Ltd.) air quality sensor in the laboratory. We perform a measurement campaign with a network of AQT530 sensors in Helsinki, Finland in 2020-2021 and present a long-term performance evaluation of five sensors for particulate (PM10, PM2.5) and gaseous (NO2, NO, CO, O-3) components during a half-year co-location study with reference instruments at an urban traffic site. Furthermore, short-term (3-5 weeks) co-location tests were performed for 25 sensors to provide sensor-specific correction equations for the fine-tuning of selected pollutants in the sensor network. We showcase the added value of the verified network of 25 sensor units to address the spatial variability of trace gases and aerosol mass concentrations in an urban environment. The analysis assesses road and harbor traffic monitoring, local construction dust monitoring, aerosol concentrations from fireworks, impact of sub-urban small scale wood combustion and detection of long-range transport episodes on a city scale. Our analysis illustrates that the calibrated network of Vaisala AQT530 air quality sensors provide new insights into the spatio-temporal variability of air pollution within the city. This information is beneficial to, for example, optimization of road dust and construction dust emission control as well as provides data to tackle air quality problems arising from traffic exhaust and localized wood combustion emissions in the residential areas.
  • Vari, Heli; Roslund, Marja; Oikarinen, Sami; Nurminen, Noora; Puhakka, Riikka; Parajuli, Anirudra; Grönroos, Mira; Siter, Nathan; Laitinen, Olli; Hyöty, Heikki; Rajaniemi, Juho; Rantalainen, Anna-Lea; Sinkkonen, Aki; The ADELE Research Group (2021)
    There is evidence that polycyclic aromatic hydrocarbons (PAHs) and human gut microbiota are associated with the modulation of endocrine signaling pathways. Independently, studies have found associations between air pollution, land cover and commensal microbiota. We are the first to estimate the interaction between land cover categories associated with air pollution or purification, PAH levels and endocrine signaling predicted from gut metagenome among urban and rural populations. The study participants were elderly people (65-79 years); 30 lived in rural and 32 in urban areas. Semi-Permeable Membrane devices were utilized to measure air PAH concentrations as they simulate the process of bioconcentration in the fatty tissues. Land cover categories were estimated using CORINE database and geographic information system. Functional orthologues for peroxisome proliferator-activated receptor (PPAR) pathway in endocrine system were analyzed from gut bacterial metagenome with Kyoto Encyclopaedia of Genes and Genomes. High coverage of broad-leaved and mixed forests around the homes were associated with decreased PAH levels in ambient air, while gut functional orthologues for PPAR pathway increased along with these forest types. The difference between urban and rural PAH concentrations was not notable. However, some rural measurements were higher than the urban average, which was due to the use of heavy equipment on active farms. The provision of air purification by forests might be an important determining factor in the context of endocrine disruption potential of PAHs. Particularly broad-leaved forests around homes may reduce PAH levels in ambient air and balance pollution-induced disturbances within commensal gut microbiota. (C) 2020 The Author(s). Published by Elsevier Ltd.
  • Zaidan, Martha A.; Wraith, Darren; Boor, Brandon E.; Hussein, Tareq (2019)
    Black carbon (BC) is an important component of particulate matter (PM) in urban environments. BC is typically emitted from gas and diesel engines, coal-fired power plants, and other sources that burn fossil fuel. In contrast to PM, BC measurements are not always available on a large scale due to the operational cost and complexity of the instrumentation. Therefore, it is advantageous to develop a mathematical model for estimating the quantity of BC in the air, termed a BC proxy, to enable widening of spatial air pollution mapping. This article presents the development of BC proxies based on a Bayesian framework using measurements of PM concentrations and size distributions from 10 to 10,000 nm from a recent mobile air pollution study across several areas of Jordan. Bayesian methods using informative priors can naturally prevent over-fitting in the modelling process and the methods generate a confidence interval around the prediction, thus the estimated BC concentration can be directly quantified and assessed. In particular, two types of models are developed based on their transparency and interpretability, referred to as white-box and black-box models. The proposed methods are tested on extensive data sets obtained from the measurement campaign in Jordan. In this study, black-box models perform slightly better due to their model complexity. Nevertheless, the results demonstrate that the performance of both models does not differ significantly. In practice, white-box models are relatively more convenient to be deployed, the methods are well understood by scientists, and the models can be used to better understand key relationships.
  • Tuomisto, Jouko; Airaksinen, Riikka; Pekkanen, Juha; Tukiainen, Erkki; Kiviranta, Hannu; Tuomisto, Jouni T. (2017)
    Soft-tissue sarcoma is one of the few specific tumors thought to be caused by polychlorinated dibenzo-pdioxins and dibenzofurans (PCDD/Fs) and specifically TCDD. Evidence is, however, based on questionnaire-based case-control studies, and on very few cancer cases in cohort studies at high occupational exposures to chlorophenols or chlorophenoxy acid herbicides with dioxin impurities. Recall bias has been suspected to influence the reporting of exposure, but this possibility has never been adequately put to test. In the present study 87 cancer patients and 308 controls answered a questionnaire asking their exposure to wood preservatives, fungicides and herbicides, and insecticides, and their PCDD/ F concentrations were also measured. After matching for age and area 67-69 sarcoma patients and 153156 controls were available for the study depending on the chemical group, 1-3 controls for each sarcoma patient. Sarcoma patients reported exposure to these chemicals significantly more often than controls did, odds ratios were 6.7 for wood preservatives (p = 0.02), 16 for fungicides and herbicides (p = 0.01), and 4.9 for insecticides (p = 0.06). There was no association, when the analysis was based on measured PCDD/ F concentrations (odds ratios close to 1). Although it is not possible to exclude the role of the main chemical as the cause with certainty, the results indicate that recall bias is very likely in previous studies. Thus the causality between contaminant PCDD/Fs and soft tissue sarcoma cannot be considered proven. (C) 2017 Elsevier B.V. All rights reserved.
  • Hari, Pertti Kaarlo Juhani; Petäjä, Tuukka Taneli; Bäck, Jaana Kaarina; Kerminen, Veli-Matti; Lappalainen, Hanna K; Vihma, Timo; Laurila, Tuomas; Viisanen, Yrjö; Vesala, Timo Veikko; Kulmala, Markku Tapio (2016)
    The global environment is changing rapidly due to anthropogenic emissions and actions. Such activities modify aerosol and greenhouse gas concentrations in the atmosphere, leading to regional and global climate change and affecting, e.g., food and fresh-water security, sustainable use of natural resources and even demography. Here we present a conceptual design of a global, hierarchical observation network that can provide tools and increased understanding to tackle the inter-connected environmental and societal challenges that we will face in the coming decades. The philosophy behind the conceptual design relies on physical conservation laws of mass, energy and momentum, as well as on concentration gradients that act as driving forces for the atmosphere-biosphere exchange. The network is composed of standard, flux and/or advanced and flagship stations, each of which having specific and identified tasks. Each ecosystem type on the globe has its own characteristic features that have to be taken into consideration. The hierarchical network as a whole is able to tackle problems related to large spatial scales, heterogeneity of ecosystems and their complexity. The most comprehensive observations are envisioned to occur in flagship stations, with which the process-level understanding can be expanded to continental and global scales together with advanced data analysis, Earth system modelling and satellite remote sensing. The denser network of the flux and standard stations allows application and up-scaling of the results obtained from flagship stations to the global level.
  • Bousquet, Jean; Anto, Josep M.; Haahtela, Tari; Jousilahti, Pekka; Erhola, Marina; Basagana, Xavier; Czarlewski, Wienczyslawa; Odemyr, Mikaela; Palkonen, Susanna; Sofiev, Mikael; Velasco, Cesar; Bedbrook, Anna; Delgado, Rodrigo; Kouznetsov, Rostislav; Mäkelä, Mika; Palamarchuk, Yuliia; Saarinen, Kimmo; Tommila, Erja; Valovirta, Erkka; Vasankari, Tuula; Zuberbier, Torsten; Annesi-Maesano, Isabella; Benveniste, Samuel; Mathieu-Dupas, Eve; Pepin, Jean-Louis; Picard, Robert; Zeng, Stephane; Ayache, Julia; Calves Venturos, Nuria; Micheli, Yann; Jullian-Desayes, Ingrid; Laune, Daniel (2020)
    In December 2019, a conference entitled "Europe That Protects: Safeguarding Our Planet, Safeguarding Our Health" was held in Helsinki. It was co-organized by the Finnish Institute for Health and Welfare, the Finnish Environment Institute and the European Commission, under the auspices of Finland's Presidency of the EU. As a side event, a symposium organized as the final POLLAR (Impact of air POLLution on Asthma and Rhinitis) meeting explored the digital transformation of health and care to sustain planetary health in airway diseases. The Finnish Allergy Programme collaborates with MASK (Mobile Airways Sentinel NetworK) and can be considered as a proof-of-concept to impact Planetary Health. The Good Practice of DG Sante (The Directorate-General for Health and Food Safety) on digitally-enabled, patient-centred care pathways is in line with the objectives of the Finnish Allergy Programme. The ARIACARE-Digital network has been deployed in 25 countries. It represents an example of the digital cross-border exchange of real-world data and experience with the aim to improve patient care. The integration of information technology tools for climate, weather, air pollution and aerobiology in mobile Health applications will enable the development of an alert system. Citizens will thus be informed about personal environmental threats, which may also be linked to indicators of Planetary Health and sustainability. The digital transformation of the public health policy was also proposed, following the experience of the Agency for Health Quality and Assessment of Catalonia (AQuAS).
  • Heikkinen, Liine; Äijälä, Mikko; Dällenbach, Kaspar; Chen, Gang; Garmash, Olga; Aliaga , Diego; Graeffe, Frans; Räty, Meri; Luoma, Krista; Aalto, Pasi; Kulmala, Markku; Petäjä, Tuukka; Worsnop, Douglas; Ehn, Mikael (2021)
    The Station for Measuring Ecosystem-Atmosphere Relations (SMEAR) II, located within the boreal forest of Finland, is a unique station in the world due to the wide range of long-term measurements tracking the Earth-atmosphere interface. In this study, we characterize the composition of organic aerosol (OA) at SMEAR II by quantifying its driving constituents. We utilize a multi-year data set of OA mass spectra measured in situ with an Aerosol Chemical Speciation Monitor (ACSM) at the station. To our knowledge, this mass spectral time series is the longest of its kind published to date. Similarly to other previously reported efforts in OA source apportionment from multi-seasonal or multi-annual data sets, we approached the OA characterization challenge through positive matrix factorization (PMF) using a rolling window approach. However, the existing methods for extracting minor OA components were found to be insufficient for our rather remote site. To overcome this issue, we tested a new statistical analysis framework. This included unsupervised feature extraction and classification stages to explore a large number of unconstrained PMF runs conducted on the measured OA mass spectra. Anchored by these results, we finally constructed a relaxed chemical mass balance (CMB) run that resolved different OA components from our observations. The presented combination of statistical tools provided a data-driven analysis methodology, which in our case achieved robust solutions with minimal subjectivity. Following the extensive statistical analyses, we were able to divide the 2012-2019 SMEAR II OA data (mass concentration interquartile range (IQR): 0.7, 1.3, and 2.6 mu gm(-3)) into three sub-categories - low-volatility oxygenated OA (LV-OOA), semi-volatile oxygenated OA (SV-OOA), and primary OA (POA) - proving that the tested methodology was able to provide results consistent with literature. LV-OOA was the most dominant OA type (organic mass fraction IQR: 49 %, 62 %, and 73 %). The seasonal cycle of LV-OOA was bimodal, with peaks both in summer and in February. We associated the wintertime LV-OOA with anthropogenic sources and assumed biogenic influence in LV-OOA formation in summer. Through a brief trajectory analysis, we estimated summertime natural LV-OOA formation of tens of ngm 3 h 1 over the boreal forest. SV-OOA was the second highest contributor to OA mass (organic mass fraction IQR: 19 %, 31 %, and 43 %). Due to SV-OOA's clear peak in summer, we estimate biogenic processes as the main drivers in its formation. Unlike for LV-OOA, the highest SV-OOA concentrations were detected in stable summertime nocturnal surface layers. Two nearby sawmills also played a significant role in SV-OOA production as also exemplified by previous studies at SMEAR II. POA, taken as a mix of two different OA types reported previously, hydrocarbon-like OA (HOA) and biomass burning OA (BBOA), made up a minimal OA mass fraction (IQR: 2 %, 6 %, and 13 %). Notably, the quantification of POA at SMEAR II using ACSM data was not possible following existing rolling PMF methodologies. Both POA organic mass fraction and mass concentration peaked in winter. Its appearance at SMEAR II was linked to strong southerly winds. Similar wind direction and speed dependence was not observed among other OA types. The high wind speeds probably enabled the POA transport to SMEAR II from faraway sources in a relatively fresh state. In the event of slower wind speeds, POA likely evaporated and/or aged into oxidized organic aerosol before detection. The POA organic mass fraction was significantly lower than reported by aerosol mass spectrometer (AMS) measurements 2 to 4 years prior to the ACSM measurements. While the co-located long-term measurements of black carbon supported the hypothesis of higher POA loadings prior to year 2012, it is also possible that short-term (POA) pollution plumes were averaged out due to the slow time resolution of the ACSM combined with the further 3 h data averaging needed to ensure good signal-to-noise ratios (SNRs). Despite the length of the ACSM data set, we did not focus on quantifying long-term trends of POA (nor other components) due to the high sensitivity of OA composition to meteorological anomalies, the occurrence of which is likely not normally distributed over the 8-year measurement period. Due to the unique and realistic seasonal cycles and meteorology dependences of the independent OA subtypes complemented by the reasonably low degree of unexplained OA variability, we believe that the presented data analysis approach performs well. Therefore, we hope that these results encourage also other researchers possessing several-yearlong time series of similar data to tackle the data analysis via similar semi- or unsupervised machine-learning approaches. This way the presented method could be further optimized and its usability explored and evaluated also in other environments.
  • Lappi, Pauli (2017)
    We study non-compliance in an emissions trading system in which firms may bank and borrow permits. We find a condition involving auditing probability that characterizes compliance and allows us to analyze the time paths of actual emissions, reported emissions and violations. We find two interesting time instants. At the first time instant, reported emissions begin to be lower than the actual emissions, and at the second time instant, the reported emissions become zero and the actual emissions become constant. The results indicate, among other things, that a given penalty scheme may fail to induce compliance over the whole planning interval, even though it achieves compliance over the initial stage.
  • Cai, Zongping; Sun, Yan; Deng, Yanghong; Zheng, Xiaojie; Sun, Shuiyu; Sinkkonen, Aki; Romantschuk, Martin (2022)
    This study compared electrokinetic (EK) remediation with and without interval power breaking in the removal of total and plant available cadmium (Cd) in the soil. Two laboratory experiments, i.e. EK remediation with interval power breaking (24-12 h power-on-off cycles) and conventional EK remediation (continuous power supply), with the same accumulated time (192 h) of power supply, were conducted to remove soil Cd. After the EK remediation with interval power breaking, the total Cd removal efficiency in the soil rose to 38%, in comparison to 28% after the conventional EK remediation. As for the plant available Cd, the removal efficiency was enhanced from 52 to 63%. Additionally, the electric current during the EK remediation and electric conductivity after the EK remediation were higher in the soil treated by interval power breaking, which indicated an enhanced desorption and/or migration of charged species. It further meant that the higher removal efficiency of soil Cd by interval power breaking could be related to the enhanced desorption and/or migration of Cd species. This study indicated that both conventional EK remediation and EK remediation with interval power breaking were effective methods to remove soil Cd but EK remediation with interval power breaking was more efficient.
  • Belinskij, Antti; Iho, Antti; Paloniitty née Korvela, Tiina; Soininen, Niko (2019)
    Animal agriculture is shifting toward larger farms and regional agglomerations in many countries. In step with this development, manure nutrients have started accumulating regionally, and are leading to increasing eutrophication problems. Nevertheless, the same trend may also prompt innovations in manure treatment. For example, Valio Ltd (the largest dairy processer in Finland) is planning a network of facilities that would remove water from manure, fraction the nutrients in it, and produce biogas from the excess methane. One of the main hurdles in developing this technology is that the current regulatory framework does not support a shift from diffuse loading, which is seen in the traditional application of manure on fields, to point-source loading; the regulations may even prevent such a change. This article analyzes a governance framework that addresses this dilemma in EU–Finland, and discusses how the governance described could curtail the nutrient loading of agriculture to waters. The approach is based on adaptive governance theory. We argue that traditional top–down regulation, which emphasizes food security, contains serious shortcomings when it comes to managing agricultural nutrient loading to waters, and that the current regulatory framework does not necessarily have the adaptive capacity to facilitate new, bottom–up solutions for manure treatment. Interestingly, the strict water quality requirements of the EU Water Framework Directive (2000/60/EC) open new windows of opportunity for such solutions, and thus for improving the overall sustainability of animal agriculture.
  • GBD 2019 Risk Factors (2020)
    Background Rigorous analysis of levels and trends in exposure to leading risk factors and quantification of their effect on human health are important to identify where public health is making progress and in which cases current efforts are inadequate. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 provides a standardised and comprehensive assessment of the magnitude of risk factor exposure, relative risk, and attributable burden of disease. Methods GBD 2019 estimated attributable mortality, years of life lost (YLLs), years of life lived with disability (YLDs), and disability-adjusted life-years (DALYs) for 87 risk factors and combinations of risk factors, at the global level, regionally, and for 204 countries and territories. GBD uses a hierarchical list of risk factors so that specific risk factors (eg, sodium intake), and related aggregates (eg, diet quality), are both evaluated. This method has six analytical steps. (1) We included 560 risk-outcome pairs that met criteria for convincing or probable evidence on the basis of research studies. 12 risk-outcome pairs included in GBD 2017 no longer met inclusion criteria and 47 risk-outcome pairs for risks already included in GBD 2017 were added based on new evidence. (2) Relative risks were estimated as a function of exposure based on published systematic reviews, 81 systematic reviews done for GBD 2019, and meta-regression. (3) Levels of exposure in each age-sex-location-year included in the study were estimated based on all available data sources using spatiotemporal Gaussian process regression, DisMod-MR 2.1, a Bayesian meta-regression method, or alternative methods. (4) We determined, from published trials or cohort studies, the level of exposure associated with minimum risk, called the theoretical minimum risk exposure level. (5) Attributable deaths, YLLs, YLDs, and DALYs were computed by multiplying population attributable fractions (PAFs) by the relevant outcome quantity for each age-sex-location-year. (6) PAFs and attributable burden for combinations of risk factors were estimated taking into account mediation of different risk factors through other risk factors. Across all six analytical steps, 30 652 distinct data sources were used in the analysis. Uncertainty in each step of the analysis was propagated into the final estimates of attributable burden. Exposure levels for dichotomous, polytomous, and continuous risk factors were summarised with use of the summary exposure value to facilitate comparisons over time, across location, and across risks. Because the entire time series from 1990 to 2019 has been re-estimated with use of consistent data and methods, these results supersede previously published GBD estimates of attributable burden. Findings The largest declines in risk exposure from 2010 to 2019 were among a set of risks that are strongly linked to social and economic development, including household air pollution; unsafe water, sanitation, and handwashing; and child growth failure. Global declines also occurred for tobacco smoking and lead exposure. The largest increases in risk exposure were for ambient particulate matter pollution, drug use, high fasting plasma glucose, and high body-mass index. In 2019, the leading Level 2 risk factor globally for attributable deaths was high systolic blood pressure, which accounted for 10.8 million (95% uncertainty interval [UI] 9.51-12.1) deaths (19.2% [16.9-21.3] of all deaths in 2019), followed by tobacco (smoked, second-hand, and chewing), which accounted for 8.71 million (8.12-9.31) deaths (15.4% [14.6-16.2] of all deaths in 2019). The leading Level 2 risk factor for attributable DALYs globally in 2019 was child and maternal malnutrition, which largely affects health in the youngest age groups and accounted for 295 million (253-350) DALYs (11.6% [10.3-13.1] of all global DALYs that year). The risk factor burden varied considerably in 2019 between age groups and locations. Among children aged 0-9 years, the three leading detailed risk factors for attributable DALYs were all related to malnutrition. Iron deficiency was the leading risk factor for those aged 10-24 years, alcohol use for those aged 25-49 years, and high systolic blood pressure for those aged 50-74 years and 75 years and older. Interpretation Overall, the record for reducing exposure to harmful risks over the past three decades is poor. Success with reducing smoking and lead exposure through regulatory policy might point the way for a stronger role for public policy on other risks in addition to continued efforts to provide information on risk factor harm to the general public. Copyright (C) 2020 The Author(s). Published by Elsevier Ltd.
  • Taka, Maija; Sillanpaa, Nora; Niemi, Tero; Warsta, Lassi; Kokkonen, Teemu; Setälä, Heikki (2022)
    Urban hydrology is characterized by increased runoff and various pollutant sources. We studied the spatio-temporal patterns of stormwater metal (Al, V, Cr, Mn, Fe, Cu, Zn, and Pb) concentrations and loads in five urbanized and one rural catchment in Southern Finland. The two-year continuous monitoring revealed a non-linear seasonal relationship between catchment urban intensity and metal export. For runoff, seasonal variation decreased with increasing imperviousness. The most urbanized catchments experienced greatest temporal variation in metal concentrations: the annual Cu and Zn loads in most of the studied urbanized catchments were up to 86 times higher compared to the rural site, whereas Fe loads in the urbanized catchments were only circa 29% of the rural load. Total metal levels were highest in the winter, whereas the winter peak of dissolved metal concentrations was less pronounced. The collection of catchment characteristics explained well the total metal concentrations, whereas for the dissolved concentrations the explanatory power was weaker. Our catchment-scale analysis revealed a mosaic of mainly diffuse pollutant sources and calls for catchment-scale management designs. As urban metal export occurred across seasons, solutions that operate also in cold conditions are needed.
  • Cai, Zongping; Sun, Yan; Deng, Yanghong; Zheng, Xiaojie; Sun, Shuiyu; Romantschuk, Martin; Sinkkonen, Aki (2021)
    Electrokinetic (EK) remediation has been widely studied at laboratory scales. However, field-scale research is far less. In this study, a 14-day EK remediation was carried out, in a field pilot (4 m2) test and a full-scale (200 m2) application for the first time, in a cadmium (Cd) contaminated paddy agricultural field near a mining area. A low voltage of 20 V was applied at both scales; voltage gradient was 20 V m & minus;1 and 4 V m & minus;1 at the pilot and full scales, respectively. Samples were taken from near the anode and cathode, and in the middle of the electric field, in the soil layers 0-10 cm, 10-20 cm, and 40-50 cm. After the EK remediation, a significant portion of the total Cd was removed in all the layers at the pilot scale, by 87%, 72%, and 54% from the top down, but only in the 0-10 cm layer at the full scale by 74%. As for the plant available (exchangeable and soluble) Cd, significant removal (64%) was only observed in the 0-10 cm layer at the pilot scale. The percentage reduction of the electrical conductivity and removal efficiency of the total Cd was higher near the anode than the cathode. The soil pH was elevated near the cathode but stayed below pH 6 due to the sufficient supply of lactic acid. After the EK remediation, the concentration of the total Cd dropped below the hazard threshold, i.e. 0.4 mg (kg dry wt soil)& minus;1 for agricultural paddy fields in China. A total energy of 2 kW & middot;h and 0.6 kW & middot;h was consumed at the pilot and full scales, respec-tively. This study showed a successful in situ EK remediation of Cd contaminated paddy agricultural soil, espe-cially in the surface layer, with low voltage and energy demand. (c) 2021 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
  • Fung, Pak Lun; Zaidan, Martha Arbayani; Niemi, Jarkko V.; Saukko, Erkka; Timonen, Hilkka; Kousa, Anu; Kuula, Joel; Rönkkö, Topi; Karppinen, Ari; Tarkoma, Sasu; Kulmala, Markku; Petäjä, Tuukka; Hussein, Tareq (2022)
    Lung-deposited surface area (LDSA) has been considered to be a better metric to explain nanoparticle toxicity instead of the commonly used particulate mass concentration. LDSA concentrations can be obtained either by direct measurements or by calculation based on the empirical lung deposition model and measurements of particle size distribution. However, the LDSA or size distribution measurements are neither compulsory nor regulated by the government. As a result, LDSA data are often scarce spatially and temporally. In light of this, we developed a novel statistical model, named the input-adaptive mixed-effects (IAME) model, to estimate LDSA based on other already existing measurements of air pollutant variables and meteorological conditions. During the measurement period in 2017–2018, we retrieved LDSA data measured by Pegasor AQ Urban and other variables at a street canyon (SC, average LDSA = 19.7 ± 11.3 µm2 cm−3) site and an urban background (UB, average LDSA = 11.2 ± 7.1 µm2 cm−3) site in Helsinki, Finland. For the continuous estimation of LDSA, the IAME model was automatised to select the best combination of input variables, including a maximum of three fixed effect variables and three time indictors as random effect variables. Altogether, 696 submodels were generated and ranked by the coefficient of determination (R2), mean absolute error (MAE) and centred root-mean-square difference (cRMSD) in order. At the SC site, the LDSA concentrations were best estimated by mass concentration of particle of diameters smaller than 2.5 µm (PM2.5), total particle number concentration (PNC) and black carbon (BC), all of which are closely connected with the vehicular emissions. At the UB site, the LDSA concentrations were found to be correlated with PM2.5, BC and carbon monoxide (CO). The accuracy of the overall model was better at the SC site (R2=0.80, MAE = 3.7 µm2 cm−3) than at the UB site (R2=0.77, MAE = 2.3 µm2 cm−3), plausibly because the LDSA source was more tightly controlled by the close-by vehicular emission source. The results also demonstrated that the additional adjustment by taking random effects into account improved the sensitivity and the accuracy of the fixed effect model. Due to its adaptive input selection and inclusion of random effects, IAME could fill up missing data or even serve as a network of virtual sensors to complement the measurements at reference stations.