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Airborne trace elements (TEs) present in atmospheric fine particulate matter (PM 2.5 ) exert notable threats to human health and ecosystems. To explore the impact of meteorological conditions on shaping the pollution characteristics of TEs and the associated health risks, we quantified the variations in pollution characteristics and health risks of TEs due to meteorological impacts using weather normalization and health risk assessment models, and analyzed the source-specific contributions and potential sources of primary TEs affecting health risks using source apportionment approaches at four sites in Shandong Province from September to December 2021. Our results indicated that TEs experience dual effects from meteorological conditions, with a tendency towards higher TE concentrations and related health risks during polluted period, while the opposite occurred during clean period. The total non-carcinogenic and carcinogenic risks of TEs during polluted period increased approximately by factors of 0.53-1.74 and 0.44-1.92, respectively. Selenium (Se), manganese (Mn), and lead (Pb) were found to be the most meteorologically influenced TEs, while chromium (Cr) and manganese (Mn) were identified as the dominant TEs posing health risks. Enhanced emissions of multiple sources for Cr and Mn were found during polluted period. Depending on specific wind speeds, industrialized and urbanized centers, as well as nearby road dusts, could be key sources for TEs. This study suggested that attentions should be paid to not only the TEs from primary emissions but also the meteorology impact on TEs especially during pollution episodes to reduce health risks in the future., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Personal exposure to air pollution is influenced by an individual's time-activity patterns, but data regarding personal exposure to air pollution among children populations is lacking. The objective of this study was to characterize personal exposure to both PM 2.5 and ultrafine particles (UFPs) using two portable real-time monitors, combined with GPS logging, and describe the relationship between these exposures across time and microenvironments among adolescents with asthma. Participants completed personal exposure monitoring for seven consecutive days and PM2.5 and UFP concentrations experienced in five microenvironments were determined using GPS location and mobility data. Average UFP and PM 2.5 exposure varied across microenvironments with the highest average UFP exposure concentrations observed in transit (10,910 ± 27,297 p/cc), though correlations between UFP and PM 2.5 concentrations in transit were low (0.24) and did not reach statistical significance (p > 0.05). We calculated exposure time ratios for each participant. Across participants, UFP exposures within the transit environment demonstrated the highest ratio (average exposure-time ratio = 1.91) though only 3 % of overall sampling time among all participants was monitored in transit (74/2840 h). We did not observe similar trends among PM 2.5 exposures. The correlations between UFP and PM 2.5 exposures varied throughout the day, with an overall correlation ranging from moderate to high among participants. Identifying microenvironments and activities where high exposure to PM occurs may offer potential targets for interventions to reduce overall exposures among sensitive groups., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

With 24 million inhabitants and 6.6 million vehicles on the roads, Karachi, Pakistan ranks among the world's most polluted cities due to high levels of fine particulate matter (PM 2.5 ). This study aims to investigate PM 2.5 mass, seasonal and temporal variability, chemical characterization, source apportionment, and health risk assessment at two urban sites in Karachi. Samples were analyzed using ion chromatography and dual-wavelength optical transmissometer for various inorganic components (anions, cations, and trace elements) and black carbon (BC). Several PM 2.5 pollution episodes were frequently observed, with annual mean concentrations at Kemari (140 ± 179 μg/m 3 ) and Malir (95 ± 40.9 μg/m 3 ) being significantly above the World Health Organization's guidelines of 5 μg/m 3 . Chemical composition at both sites exhibited seasonal variability, with higher pollution levels in winter and fall and lower concentrations in summer. The annual average BC concentrations were 4.86 ± 5.29 μg/m 3 and 4.52 ± 3.68 μg/m 3 , respectively. A Positive Matrix Factorization (PMF) analysis identified 5 factors, crustal, sea salt, vehicular exhaust, fossil-fuel combustion, and industrial emission. The health risk assessment indicated a higher number of deaths in colder seasons (fall and winter) at the Kemari (328,794 and 287,814) and Malir (228,406 and 165,737) sites and potential non-carcinogenic and carcinogenic risks to children from metals. The non-carcinogenic risk of PM 2.5 bound Pb, Fe, Zn, Mn, Cr, Cu and Ni via inhalation exposure were within the acceptable level (<1) for adults. However, potential non-carcinogenic and carcinogenic health risk posed by Pb and Cr through inhalation were observed for children. The findings exhibit critical levels of air pollution that exceed the safe limits in Karachi, posing significant health risks to children and sensitive groups. Our study underscores the urgent need for effective emission control strategies and policy interventions to mitigate these air pollution risks., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier B.V.)

A clean atmosphere should be provided as a right for human beings to live. The reality is that a significant proportion of the population is exposed to air pollution. This study presents an in-depth investigation into the spatio-temporal dynamics of PM 2.5 concentrations in Ankara, Türkiye, spanning over three years. With particular emphasis on the impact of COVID-19 lockdown measures and local air quality management strategies, data from eight air pollution monitoring stations were analyzed. The findings indicate a significant reduction in PM 2.5 levels during lockdown periods, with an average decrease of 18 % observed across the city. Implementing the Ankara Provincial Clean Air Action Plan further contributed to a 9.1 % decrease in PM 2.5 concentrations in 2021, followed by an additional 6.6 % decrease in 2022 compared to 2020. The spatial distribution of PM 2.5 concentrations reveals the influence of industrial and urban areas on pollution levels. Potential Source Contribution Function (PSCF) and Concentration-Weighted Trajectory (CWT) methods were employed to investigate the spatial and temporal variation of long-range transport source regions contributing to the PM 2.5 levels in Ankara. PSCF and CWT analyses revealed a decreasing trend in anthropogenic contribution to PM 2.5 from 2020 to 2022. The AirQ + model was employed to predict the long-term mortality rates attributable to PM 2.5 across different monitoring stations. Based on the estimations, all stations' average estimated attributable proportion is 9.8 % (3.3 %-27.8 %). The results depict varying trends in estimated mortality rates, emphasizing the importance of targeted interventions to mitigate the public health risks arising from exposure to polluted air. Overall, the results of this study show significant measures for the development of effective clean air quality strategies can effectively change the direction of the adverse impact of air pollution on public health., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

The impact of atmospheric pollution on the growth of European forest tree species, particularly European beech, Silver fir and Norway spruce, is examined in five mesic forests in the Czech Republic. Analyzing of basal area increment (BAI) patterns using linear mixed effect models reveals a complex interplay between atmospheric nitrogen (N) and sulphur (S) deposition, climatic variables and changing CO 2 concentrations. Beech BAI responds positively to N deposition (in tandem with air CO 2 concentration), with soil phosphorus (P) availability emerging as a significant factor influencing overall growth rates. Fir BAI, on the other hand, was particularly negatively influenced by S deposition, although recent growth acceleration suggests growth resilience in post-pollution period. This fir growth surge likely coincides with stimulation of P acquisition following the decline of acidic pollution. The consequence is the current highest productivity among the studied tree species. The growth dynamics of both conifers were closely linked to the stoichiometric imbalance of phosphorus in needles, indicating the possible sensitivity of exogenous controls on nutrient uptake. Furthermore, spruce BAI was positively linked to calcium availability across sites. Despite enhanced water-use efficiency under elevated CO 2 , spruce growth is constrained by precipitation deficit and demonstrates weakening resilience to increasing growing season air temperatures. Overall, these findings underscore the intricate relationships between atmospheric pollution, nutrient availability, and climatic factors in shaping the growth dynamics of European forest ecosystems. Thus, incorporating biogeochemical context of nutrient availability is essential for realistic modelling of tree growth in a changing climate., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

The increase in the frequency and severity of global wildfires has been largely influenced by climate change and land use changes. From February 2 to 6, 2024, central Chile experienced its most devastating wildland-urban interface wildfire in history, severely impacting the Valparaíso region. This catastrophic event, which led to extensive forest destruction, the loss of thousands of homes, and over a hundred human fatalities, directly impacted the area surrounding the campus of Federico Santa María Technical University. In that period, an air quality monitoring campaign was set up on the campus to measure black carbon (BC) and particulate matter (PM) during the wildfire season. The monitoring station was located directly within the smoke plume, allowing for the collection of unprecedented air quality data. Extremely high concentrations of BC at 880 nm were reported during the wildfires, with a daily mean (±σ) of 14.83 ± 19.52 μg m -3 . Peak concentrations measured at 880 nm and 375 nm reached 812.89 μg m -3 and 1561.24 μg m -3 , respectively. The maximum daily mean BC concentrations at these wavelengths were 55 and 99 times higher, respectively, compared to the pre-event period. The mean Ångström absorbing coefficient during the event was 1.66, indicating biomass burning as the primary BC source, while the maximum BC/PM 2.5 ratio (at 375 nm) reached 57 %. From February 2 to 5, 2024, PM concentrations exceeded the Chilean air quality standard by 82 % and 198 % for coarse and fine particles, respectively. These levels are 4.7 and 6.0 times higher than the World Health Organization's recommendations. These elevated concentrations persisted for up to three days after the fire was extinguished. This study provides unique evidence of the rapid deterioration of regional air quality during a wildfire event using in situ measurements, serving as a stark reminder of the far-reaching consequences of a warming climate., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

The American continent is experiencing significant economic and industrial development driven by sustainability principles. In this context, discussions on improving energy consumption have become increasingly frequent and dynamic across various sectors of civil society, including the implementation of energy efficiency measures as advocated by the ISO 50001 energy management standard. However, there is a pressing need to investigate which socioeconomic aspects are responsible for the issuance of this certification in the Americas and how these factors relate to characteristic industrial emissions, especially particulate matter. This study aims to evaluate the socioeconomic factors influencing ISO 50001 standard issuance and how these adjusted factors correlate with particulate matter of 2.5 μm and 10 μm dimensions. To achieve this, machine learning techniques were employed, considering the complex nature and risk of data overfitting. Model fitting was performed through multiple lasso regression, and the relationship between the adjusted factors was examined through cross-correlation analysis. The analyses indicate a strong correlation of adjusted macroeconomic indicators, especially with PM 2.5 , suggesting an association with cardiorespiratory problems and methane-related origins. This work is of great relevance to academia as it proposes new concepts regarding the interaction between energy efficiency standards and particulate matter. For the industrial sector, the adjusted factors provide guidance for standard implementation while also helping to mitigate health issues. Additionally, for the government, these results can assist in formulating policies to address specific health problems related to this area., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

The prevalence in allergic diseases has increased considerably in the past decades. An important trigger of the symptoms of allergic rhinitis (hay fever) is the pollen of wind-pollinating plants. This pollen is developed by plants and is released into the air where it gets exposed to environmental influences and air pollution. We investigated the chemical changes to pollen that occur after release from the flower in a rural (Veluwe) and an urban (Amsterdam) site in the Netherlands using Fourier Transform Infrared (FTIR) spectroscopy. During the spring/summer of 2020 (during the COVID pandemic) the pollen of nine taxa (Alnus, Betula, Fagus, Fraxinus, Pinus, Plantago, Poaceae, Quercus and Salix) were collected directly from flowers and the air (using a mobile sampler). FTIR spectra were obtained for multiple individual pollen grains for each taxa. The spectra obtained from airborne pollen collected at the rural vs. urban sites did not show any statistical difference. This is possibly a result of a reduced difference in pollutant concentrations between the two sites due to the COVID-19-lockdown measures were in place. However, consistent differences in the FTIR spectra recovered from airborne vs. flower pollen were recorded for all pollen taxa. After the release from the flower the chemical composition of the pollen changed: (i) polysaccharides are converted to monosaccharides; (ii) protein concentration and/or nitration/oxidation level is altered; (iii) lipids are modified and/or reduced in concentration. These changes may alter the allergenicity of the pollen and suggest that further work on the allergenic nature of airborne pollen is required., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: WIlliam Gosling reports financial support was provided by the Netherlands Organisation for Scientific Research (NWO). If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

The objective of this study is to evaluate long-term changes in the level of exposure to NO 2 among the population living in the urban area of Naples (south Italy). This has been achieved by integrating data from the regional reference monitoring network with information collected during the citizen science initiative called 'NO 2 , NO grazie!' conducted in February 2020 and coordinated by the Non-Governmental Organisation 'Cittadini per l'aria'. This citizen science campaign was based on low-cost passive samplers (Palmes tubes), providing the ability to obtain unprecedented high-resolution NO 2 levels. Using a Land Use Random Forest (LURF), we extrapolated the experimental data obtained from the citizen science campaign and evaluated the changes in population exposure from 2013 to 2022 and the uncertainty associated with this assessment was quantified. The results indicate that a large proportion of the inhabitants of Naples are still exposed to high NO 2 concentrations, even if strict emission containment measures are enforced. The average levels remain higher than the new interim and air quality targets suggested by the World Health Organisation. The implementation of co-created citizen science projects, where NGO and citizens actively participate alongside scientists, can significantly improve the estimation and the interpretation of official reference data., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier B.V. All rights reserved.)

This study examines the influence of meteorological factors and air pollutants on the performance of automatic pollen monitoring devices, as part of the EUMETNET Autopollen COST ADOPT-intercomparison campaign held in Munich, Germany, during the 2021 pollen season. The campaign offered a unique opportunity to compare all automatic monitors available at the time, a Plair Rapid-E, a Hund-Wetzlar BAA500, an OPC Alphasense, a KH-3000 Yamatronics, three Swisens Polenos, a PollenSense APS, a FLIR IBAC2, a DMT WIBS-5, an Aerotape Sextant, to the average of four manual Hirst traps, under the same environmental conditions. The investigation aimed to elucidate how meteorological factors and air pollution impact particle capture and identification efficiency. The analysis showed coherent results for most devices regarding the correlation between environmental conditions and pollen concentrations. This reflects on one hand, a significant correlation between weather and airborne pollen concentration, and on the other hand the capability of devices to provide meaningful data under the conditions under which measurements were taken. However, correlation strength varied among devices, reflecting differences in design, algorithms, or sensors used. Additionally, it was observed that different algorithms applied to the same dataset resulted in different concentration outputs, highlighting the role of algorithm design in these systems (monitor + algorithm). Notably, no significant influence from air pollutants on the pollen concentrations was observed, suggesting that any potential difference in effect on the systems might require higher air pollution concentrations or more complex interactions. However, results from some monitors were affected to a minor degree by specific weather variables. Our findings suggest that the application of real-time devices in urban environments should focus on the associated algorithm that classifies pollen taxa. The impact of air pollution, although not to be excluded, is of secondary concern as long as the pollution levels are similar to a large European city like Munich., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Air pollution poses a significant threat to public health, while biogenic volatile organic compounds (BVOCs) play a crucial role in both aspects. However, the unclear relationship between BVOCs and air pollutants in the under-canopy space limits the accuracy of air pollution control and the exploitation of forest healthcare functions. To clarify the variation of BVOCs in forest therapy bases, and their impacts on ozone (O 3 ) and fine particulate matter (PM 2.5 ) at nose height, total VOCs (TVOCs) in the forest were collected during typical sunny days, while air pollutants and meteorological factors were observed simultaneously. The results showed that the branch-level emissions of P. tabuliformis were dominated by healthcare-effective monoterpenoids, with only α-pinene having relative air concentrations of over 5 % in forest air samples. The correlation between concentrations of under-canopy TVOCs and emission rates of BVOCs from P. tabuliformis was weak (p > 0.09) in all seasons. However, the correlation between concentrations of TVOCs and the concentrations of O 3 and PM 2.5 showed clear seasonal differences. In spring, TVOCs only showed a significant negative correlation with PM 2.5 in the forest (p < 0.01). In summer and autumn, TVOCs were significantly negatively correlated with both O 3 (p < 0.001) and PM 2.5 (p < 0.01). Specifically, the negative linear relationships were more pronounced for O 3 and oxygenated VOCs in autumn (R 2  = 0.40, p < 0.001) than for other relationships. The relationship between air pollutant concentrations inside and outside the forest also showed significant seasonal differences, generally characterized by a weaker correlation between them during seasons of strong emissions. Therefore, BVOCs in coniferous forests are health functions as they can provide healthcare effects and mitigate the concentration of air pollutants in the forest, and the establishment of forest therapy bases in rural areas with low NO x can be a sensible approach to promote good health, well-being, and sustainable development., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Since 2000, China has faced severe air pollution challenges，prompting the initiation of comprehensive emission control measures post-2013. The subsequent implementation of these measures has led to remarkable enhancements in air quality. This study aims to enhance our understanding of the long-term trends in fine particulate matter (PM 2.5 ) and gaseous pollutants of ozone (O 3 ) and nitrogen dioxide (NO 2 ) across China from 2000 to 2020. Utilizing the Community Multiscale Air Quality (CMAQ) model, we conducted a nationwide analysis of air quality, systematically quantifying model predictions against observations for pollutants. The CMAQ model effectively captured the trends of air pollutants, meeting recommended performance benchmarks. The findings reveal variations in pollutant concentrations, with initial increases in PM 2.5 followed by a decline after 2013. The proportion of the population living in high PM 2.5 concentrations (>75 μg/m 3 ) decreased to <5 % after 2015. However, during the period from 2017 to 2020, around 40 % of the population continued to live in regions that did not meet the criteria for Chinese air quality standards (35 μg/m 3 ). From 2000 to 2019, fewer than 20 % of the population met the WHO standard (100 μg/m 3 ) for MDA8 O 3 . In 2000, 77 % of the population met the NO 2 standard (<20 μg/m 3 ), a figure that declined to 60 % between 2005 and 2014, nearly reaching 70 % in 2020. This study offers a comprehensive analysis of the changes in pollutants and public exposure in 2000-2020. It serves as a foundational resource for future efforts in air pollution control and health research., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Marathon running significantly increases breathing volumes and, consequently, air pollution inhalation doses. This is of special concern for elite athletes who ventilate at very high rates. However, race organizers and sport governing bodies have little guidance to support events scheduling to protect runners. A key limitation is the lack of hyper-local, high temporal resolution air quality data representative of exposure along the racecourse. This work aimed to understand the air pollution exposures and dose inhaled by athletes, by means of a dynamic monitoring methodology designed for road races. Air quality monitors were deployed during three marathons, monitoring nitrogen dioxide (NO 2 ), ozone (O 3 ), particulate matter (PMx), air temperature, and relative humidity. One fixed monitor was installed at the Start/Finish line and one mobile monitor followed the women elite runner pack. The data from the fixed monitors, deployed prior the race, described daily air pollution trends. Mobile monitors in combination with heatmap analysis facilitated the hyper-local characterization of athletes' exposures and helped identify local hotspots (e.g., areas prone to PM resuspension) which should be preferably bypassed. The estimation of inhaled doses disaggregated by gender and ventilation showed that doses inhaled by last finishers may be equal or higher than those inhaled by first finishers for O 3 and PMx, due to longer exposures as well as the increase of these pollutants over time (e.g., 58.2 ± 9.6 and 72.1 ± 23.7 μg of PM 2.5 for first and last man during Rome marathon). Similarly, men received significantly higher doses than women due to their higher ventilation rate, with differences of 31-114 μg for NO 2 , 79-232 μg for O 3 , and 6-41 μg for PM x . Finally, the aggregated data obtained during the 4 week- period prior the marathon can support better race scheduling by the organizers and provide actionable information to mitigate air pollution impacts on athletes' health and performance., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Heavy metals (HMs) in PM 2.5 gain much attention for their toxicity and carcinogenic risk. This study evaluates the health risks of PM 2.5 -bound HMs, focusing on how meteorological conditions affect these risks against the backdrop of PM 2.5 reduction trends in China. By applying a receptor model with a meteorological normalization technique, followed by health risk assessment, this work reveals emission-driven changes in health risk of source-specific HMs in the outskirt of Tianjin during the implementation of China' second Clean Air Action (2018-2020). Sources of PM 2.5 -bound HMs were identified, with significant contributions from vehicular emissions (on average, 33.4 %), coal combustion (26.3 %), biomass burning (14.1 %), dust (11.7 %), industrial boilers (9.7 %), and shipping emission and sea salt (4.7 %). The source-specific emission-driven health risk can be enlarged or dwarfed by the changing meteorological conditions over time, demonstrating that the actual risks from these source emissions for a given time period may be higher or smaller than those estimated by traditional assessments. Meteorology contributed on average 56.1 % to the interannual changes in source-specific carcinogenic risk of HMs from 2018 to 2019, and 5.6 % from 2019 to 2020. For the source-specific noncarcinogenic risk changes, the contributions were 38.3 % and 46.4 % for the respective periods. Meteorology exerts a more profound impact on daily risk (short-term trends) than on annual risk (long-term trends). Such meteorological impacts differ among emission sources in both sign and magnitude. Reduced health risks of HMs were largely from targeted regulatory measures on sources. Therefore, the meteorological covariates should be considered to better evaluate the health benefits attributable to pollution control measures in health risk assessment frameworks., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Large marine vessels have historically used high-sulphur (S) residual fuel oil (RFO), with substantial airborne releases of sulphur dioxide (SO₂) and fine particulate matter (PM 2.5 ) enriched in vanadium (V), nickel (Ni) and other air pollutants. To address marine shipping air pollution, Canada and the United States have jointly implemented a North American Emissions Control Area (NA ECA) within which ships are regulated to use lower-sulphur marine fuel or equivalent SO 2 scrubbers (i.e., 3.5% maximum fuel S reduced to 1% S in 2012 and 0.1% S in 2015). To investigate the effects of these regulations on local air quality, we examined changes in air pollutant (SO₂, PM 2.5 , NO₂, O₃), and related PM 2.5 components (V, Ni, sulphate) concentrations over 2010-2016 at the Canadian port cities of Halifax, Vancouver, Victoria, Montreal, and Quebec City. SO 2 concentrations showed large statistically significant decreases at all sites (-28% to -83% mean hourly change), with the largest improvements in the coastal cities when the 0.1% fuel S regulation took effect. Statistically significant PM 2.5 but smaller fractional reductions were also observed (-7% to -37% mean hourly change), reflecting the importance of non-marine PM sources. RFO marker species V and Ni in PM 2.5 dramatically declined following regulation implementation, consistent with decreased RFO use likely indicating the switch to low-S distillate fuel oil rather than exhaust scrubbers for initial compliance. Significant changes in other pollutants with non-marine sources (NO 2 , O 3 ) were not contemporaneous with the regulatory timeline. The large SO 2 improvements in the port cities have reduced 1-h concentrations to <30 ppb, comparable to Canadian urban locations with few local SO 2 sources and likely reducing health risks to susceptible populations such as asthmatics and the elderly. Our findings indicate that the implementation of the NA ECA improved air quality at Canadian port cities immediately following the requirement for lower-S fuel. These air quality improvements suggest that large-scale international benefits can result from implementation of the 2020 global low-S marine fuel regulations., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Crown Copyright © 2021. Published by Elsevier B.V. All rights reserved.)

Since its first appearance in Wuhan, China at the end of 2019, the new coronavirus (COVID-19) has evolved a global pandemic within three months, with more than 4.3 million confirmed cases worldwide until mid-May 2020. As many countries around the world, Malaysia and other southeast Asian (SEA) countries have also enforced lockdown at different degrees to contain the spread of the disease, which has brought some positive effects on natural environment. Therefore, evaluating the reduction in anthropogenic emissions due to COVID-19 and the related governmental measures to restrict its expansion is crucial to assess its impacts on air pollution and economic growth. In this study, we used aerosol optical depth (AOD) observations from Himawari-8 satellite, along with tropospheric NO 2 column density from Aura-OMI over SEA, and ground-based pollution measurements at several stations across Malaysia, in order to quantify the changes in aerosol and air pollutants associated with the general shutdown of anthropogenic and industrial activities due to COVID-19. The lockdown has led to a notable decrease in AOD over SEA and in the pollution outflow over the oceanic regions, while a significant decrease (27% - 30%) in tropospheric NO 2 was observed over areas not affected by seasonal biomass burning. Especially in Malaysia, PM 10 , PM 2.5 , NO 2 , SO 2 , and CO concentrations have been decreased by 26-31%, 23-32%, 63-64%, 9-20%, and 25-31%, respectively, in the urban areas during the lockdown phase, compared to the same periods in 2018 and 2019. Notable reductions are also seen at industrial, suburban and rural sites across the country. Quantifying the reductions in major and health harmful air pollutants is crucial for health-related research and for air-quality and climate-change studies., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Covid-19 was first reported in Morocco on March 2, 2020. Since then, to prevent its propagation, the Moroccan government declared a state of health emergency. A set of rapid and strict countermeasures have taken, including locking down cities, limiting population's mobility and prohibiting almost all avoidable activities. In the present study, we attempted to evaluate the changes in levels of some air pollutants (mainly PM 10 , NO 2 and SO 2 ) in Salé city (North-Western Morocco) during the lockdown measures. In this context, a continuous measurement of PM 10 , SO 2 and NO 2 was carried before and during the Covid-19 lockdown period. As a consequence of the security measures and control actions undertaken, the emissions from vehicle exhaust and industrial production were significantly reduced, which contribute to the decrease in the concentrations of the studied pollutants. The obtained results showed that the difference between the concentrations recorded before and during the lockdown period were respectively 75%, 49% and 96% for PM 10 , SO 2 and NO 2 . PM 10 levels were much less reduced than NO 2 . The three-dimensional air mass backward trajectories, using the HYSPLIT model, demonstrated the benefits of PM 10 local emission reductions related to the lockdown were overwhelmed by the contribution of long-range transported aerosols outside areas. In addition, noteworthy differences in the air mass back trajectories and the meteorology between these two periods were evidenced., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier B.V. All rights reserved.)

The effect of lockdown due to coronavirus disease (COVID-19) pandemic on air pollution in four Southern European cities (Nice, Rome, Valencia and Turin) and Wuhan (China) was quantified, with a focus on ozone (O 3 ). Compared to the same period in 2017-2019, the daily O 3 mean concentrations increased at urban stations by 24% in Nice, 14% in Rome, 27% in Turin, 2.4% in Valencia and 36% in Wuhan during the lockdown in 2020. This increase in O 3 concentrations is mainly explained by an unprecedented reduction in NO x emissions leading to a lower O 3 titration by NO. Strong reductions in NO 2 mean concentrations were observed in all European cities, ~53% at urban stations, comparable to Wuhan (57%), and ~65% at traffic stations. NO declined even further, ~63% at urban stations and ~78% at traffic stations in Europe. Reductions in PM 2.5 and PM 10 at urban stations were overall much smaller both in magnitude and relative change in Europe (~8%) than in Wuhan (~42%). The PM reductions due to limiting transportation and fuel combustion in institutional and commercial buildings were partly offset by increases of PM emissions from the activities at home in some of the cities. The NO x concentrations during the lockdown were on average 49% lower than those at weekends of the previous years in all cities. The lockdown effect on O 3 production was ~10% higher than the weekend effect in Southern Europe and 38% higher in Wuhan, while for PM the lockdown had the same effect as weekends in Southern Europe (~6% of difference). This study highlights the challenge of reducing the formation of secondary pollutants such as O 3 even with strict measures to control primary pollutant emissions. These results are relevant for designing abatement policies of urban pollution., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier B.V. All rights reserved.)

The effectiveness and cost are always top factors for policy-makers to decide control measures and most measures had no pre-test before implementation. Due to the COVID-19 pandemic, human activities are largely restricted in many regions in India since mid-March of 2020, and it is a progressing experiment to testify effectiveness of restricted emissions. In this study, concentrations of six criteria pollutants, PM 10 , PM 2.5 , CO, NO 2 , ozone and SO 2 during March 16th to April 14th from 2017 to 2020 in 22 cities covering different regions of India were analysed. Overall, around 43, 31, 10, and 18% decreases in PM 2.5 , PM 10 , CO, and NO 2 in India were observed during lockdown period compared to previous years. While, there were 17% increase in O 3 and negligible changes in SO 2 . The air quality index (AQI) reduced by 44, 33, 29, 15 and 32% in north, south, east, central and western India, respectively. Correlation between cities especially in northern and eastern regions improved in 2020 compared to previous years, indicating more significant regional transport than previous years. The mean excessive risks of PM reduced by ~52% nationwide due to restricted activities in lockdown period. To eliminate the effects of possible favourable meteorology, the WRF-AERMOD model system was also applied in Delhi-NCR with actual meteorology during the lockdown period and an un-favourable event in early November of 2019 and results show that predicted PM 2.5 could increase by only 33% in unfavourable meteorology. This study gives confidence to the regulatory bodies that even during unfavourable meteorology, a significant improvement in air quality could be expected if strict execution of air quality control plans is implemented., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Nowadays, air pollution has a major impact on the environment and human health. Owen gauges allow the sampling of atmospheric depositions in polluted sites for further characterisation. This paper shows the study of the air particles of an old mining zone in Cartagena-La Unión (South-east of Spain) in order to quantify their potential risk on human health. There were 4 strategic sites monitored: the main mining tailing (Avenque), the urban area (La Unión), an agricultural zone (formerly mining) and a site in the Mediterranean coast. Physico-chemical and mineralogical characterisation was applied to atmospheric fallouts. The granulometry revealed a dust particle size around 15 μm, with the coarsest particles in the urban area and the thinnest at the tailing site. XRD analyses showed the presence of quartz, carbonates, sulphides and sulphates. Observations with SEM-EDX confirmed chemical spectra and allowed us to classify the particles into well-crystallised minerals and heterogeneous dusts. Total metal content determination was carried out by ICP-MS analyses and results showed Zn, Pb, As and Cd fluxes (respectively 2549, 1275, 68 and 7 μg·m -2 ·d -1 ) exceeding the limit values set by European legislations in the mining area. The fluxes of Zn, Pb and As also exceed these standards in the urban area whereas the coastal zone only exceeds the thresholds in the case of As. Inhalation health risk (defined by US EPA, 2009) was quantified in the sites using total and bioaccessible metal contents of the dusts. Risk calculations using total metal content considering a residential scenario showed acceptable risk for all sites except for the mining tailing which presented non-acceptable cancer and hazard risk mainly due to the total As and Pb contents. When considering the bioaccessible fraction of As and Pb, the risk diminished to acceptable values, demonstrating the overestimation produced when using total metal contents., (Copyright © 2019 Elsevier B.V. All rights reserved.)

Haze pollution has significant impacts on tourist perception and behaviour, including a sharp increase in risk perception and a decline in tourism experience quality. However, given the intervention of multiple factors, whether these impacts necessarily have a negative effect on the overall scale of regional tourism remains unknown. Hence, this paper explored the overall effect of haze pollution on domestic travel. Using 28 major cities in China as examples, we employed a two-way fixed effect panel model to investigate this issue. Combined with the comparisons between the results of different subgroups, including high cities, medium cities, low cities, outbreak cities and non-outbreak cities, this study found that there was no significant effect of haze concentration on domestic travel, but public awareness of haze pollution had a significant positive effect on that. Meanwhile, public awareness exerted a negative moderating effect of haze concentration and domestic travel. The findings are beneficial for understanding the new situation faced by the tourism industry, and several suggestions are provided for policy makers and travel agencies., (Copyright © 2019. Published by Elsevier B.V.)

Severe air pollution associated with the rapid urbanization is a pressing issue in China. Moreover, the public awareness of environmental protection in China is awakening, which poses enormous pressure on governments to enforce environmental regulations. The study of environmental problems from the public perspective plays a crucial role in effective environmental governance. The Baidu search engine is the China's largest search engine. The search index of haze based on Baidu search engine reflects the public concern on air quality in China. The aim of this study is to uncover important relationships between public concern and air quality monitoring data based on the case study of haze pollution crisis in China. The results indicate that: (1) the year 2013 is the turning point of the public concern on air quality in China; (2) according to daily data analysis, the search index of haze has increased progressively with increased PM 2.5 concentration with a time lag of 0-4 days and the lag time has a declining tendency from 2013 to 2017; (3) according to annual data analysis, the public concern showed a weak correlation with air quality and they showed an opposite temporal trend. However, when the long-term annual trend was removed, the strong positive correlation emerges between the fluctuation parts of the search index of haze and monitoring data of air quality. This indicates the public is more sensitive to the short-term fluctuation of air quality. The results of this paper provide statistical evidence on the evolution of public concern on air quality from 2013 to 2017. This study will help policy makers to better understand the patterns of the public's perception of environmental problems and consequently improve the government's capability to deal with these challenges., (Copyright © 2018 Elsevier B.V. All rights reserved.)

Based on the statistics data, this paper estimated the quantity of biomass resource, and then the distribution of emissions from its combu3stion and gasification was analyzed in Tibet in 2015. The main conclusions are as follows: (1) biomass energy is rich in Tibet and its geographical distribution and quantity mainly depends on the relationship between ecological zones and the climate conditions. Crop straw is mainly distributed in Xigazê, Lasha, Qamdo and Shannan with the total quantity of 3.29×10 6 t/year; while animal dung is mainly distributed in Nagqu, Qamdo and Xigazê with the total quantity of 1.69×10 7 t/year. For the acquirable quantity of crop straw and animal dung is 7.27×10 6 t/year, mainly distributed in Nagqu, Qamdo and Xigazê. (2) The energy production potential of crop straw and animal dung in Tibet for combustion (thermal efficiency: 22.5%), HLG (system efficiency: 28.75% based on our investigation) and VLG (system efficiency: 38.75%) is 2.56×10 10 J/year, 3.28×10 10 J/year and 4.42×10 10 J/year, respectively. (3) Compared to the household combustion, the reduction of SO 2 is 72% with HLG and 97% with VLG, and the NOx reduction is 79% with HLG, 96% with VLG and 72% with gasification-combustion case., (Copyright © 2018 Elsevier B.V. All rights reserved.)

As one of the most serious meteorological disasters in modern society, air pollution has received extensive attention from both citizens and decision-makers. With the complexity of pollution components and the uncertainty of prediction, it is both critical and challenging to construct an effective and practical early-warning system. In this paper, a novel hybrid air quality early-warning system for pollution contaminant monitoring and analysis was proposed. To improve the efficiency of the system, an advanced attribute selection method based on fuzzy evaluation and rough set theory was developed to select the main pollution contaminants for cities. Moreover, a hybrid model composed of the theory of "decomposition and ensemble", an extreme learning machine and an advanced heuristic algorithm was developed for pollution contaminant prediction; it provides deterministic and interval forecasting for tackling the uncertainty of future air quality. Daily pollution contaminants of six major cities in China were selected as a dataset to evaluate the practicality and effectiveness of the developed air quality early-warning system. The superior experimental performance determined by the values of several error indexes illustrated that the proposed early-warning system was of great effectiveness and efficiency., (Copyright © 2018 Elsevier B.V. All rights reserved.)

In this paper, the problem of predicting future concentrations of airborne pollen is solved through a computational intelligence data-driven approach. The proposed method is able to identify the most important variables among those considered by other authors (mainly recent pollen concentrations and weather parameters), without any prior assumptions about the phenological relevance of the variables. Furthermore, an inferential procedure based on non-parametric hypothesis testing is presented to provide statistical evidence of the results, which are coherent to the literature and outperform previous proposals in terms of accuracy. The study is built upon Poaceae airborne pollen concentrations recorded in seven different locations across the Spanish province of Madrid., (Copyright © 2016 Elsevier B.V. All rights reserved.)

With rapid industrialization and urbanization, China is facing a great challenge with regard to severe fog-haze pollutions, which were characterized by high fine particulate concentration level and visibility impairment. The control strategies for atmosphere pollutions in China were not only cutting-edge topics of atmospheric research, but also an urgent issue to be addressed by the Chinese government and the public. Focused on the core scientific issues of the haze and fog pollution, this paper reviews the main studies conducted in China, especially after 2010, including formation mechanisms, evolution features, and factors contributing to the fog-haze pollutions. Present policy and control strategies were synoptically discussed. The major challenges ahead will be stated and recommendations for future research directions are proposed at the end of this Review., (Copyright © 2016 Elsevier B.V. All rights reserved.)

Intra-urban assessment of air pollution exposure has become a priority study while international attention was attracted to PM2.5 pollution in China in recent years. Land Use Regression (LUR), which has previously been proved to be a feasible way to describe the relationship between land use and air pollution level in European and American cities, was employed in this paper to explain the correlations and spatial variations in Shanghai, China. PM2.5 and NO2 concentrations at 35-45 monitoring locations were selected as dependent variables, and a total of 44 built environmental factors were extracted as independent variables. Only five factors showed significant explanatory value for both PM2.5 and NO2 models: longitude, distance from monitors to the ocean, highway intensity, waterbody area, and industrial land area for PM2.5 model; residential area, distance to the coast, industrial area, urban district, and highway intensity for NO2 model. Respectively, both PM2.5 and NO2 showed anti-correlation with coastal proximity (an indicator of clean air dilution) and correlation with highway and industrial intensity (source indicators). NO2 also showed significant correlation with local indicators of population density (residential intensity and urban classification), while PM2.5 showed significant correlation with regional dilution (longitude as a indicator of distance from polluted neighbors and local water features). Both adjusted R squared values were strong with PM2.5 (0.88) being higher than NO2 (0.62). The LUR was then used to produce continuous concentration fields for NO2 and PM2.5 to illustrate the features and, potentially, for use by future studies. Comparison to PM2.5 studies in New York and Beijing show that Shanghai PM2.5 pollutant distribution was more sensitive to geographic location and proximity to neighboring regions., (Copyright © 2015. Published by Elsevier B.V.)

Nitrous oxide, carbon dioxide and methane are greenhouse gases (GHG) emitted from wastewater treatment that contribute to its carbon footprint. As a result of the increasing awareness of GHG emissions from wastewater treatment plants (WWTPs), new modelling, design, and operational tools have been developed to address and reduce GHG emissions at the plant-wide scale and beyond. This paper reviews the state-of-the-art and the recently developed tools used to understand and manage GHG emissions from WWTPs, and discusses open problems and research gaps. The literature review reveals that knowledge on the processes related to N2O formation, especially due to autotrophic biomass, is still incomplete. The literature review shows also that a plant-wide modelling approach that includes GHG is the best option for the understanding how to reduce the carbon footprint of WWTPs. Indeed, several studies have confirmed that a wide vision of the WWPTs has to be considered in order to make them more sustainable as possible. Mechanistic dynamic models were demonstrated as the most comprehensive and reliable tools for GHG assessment. Very few plant-wide GHG modelling studies have been applied to real WWTPs due to the huge difficulties related to data availability and the model complexity. For further improvement in GHG plant-wide modelling and to favour its use at large real scale, knowledge of the mechanisms involved in GHG formation and release, and data acquisition must be enhanced., (Copyright © 2016 Elsevier B.V. All rights reserved.)

Airborne pollen concentrations strongly correlate with flowering intensity of wind-pollinated species growing at and around monitoring sites. The pollen spectrum, and the variations in its composition and concentrations, is influenced by climatic features and by available nutritional resources but it is also determined by land use and its changes. The first factor influence is well known on aerobiological researches but the impact of land cover changes has been scarcely studied until now. This paper reports on a study carried out in Southern Spain (Córdoba city) examining airborne pollen trends over a 15-year period and it explores the possible links both to changes in land use and to climate variations. The Seasonal-Trend Decomposition procedure based on Loess (STL) which decomposes long-term data series into smaller seasonal component patterns was applied. Trends were compared with recorded changes in land use at varying distances from the city in order to determine their possible influence on pollen-count variations. The influence of climate-related factors was determined by means of non-parametric correlation analysis. The STL method proved highly effective for extracting trend components from pollen time series, because their features vary widely and can change quickly in a short term. Results revealed mixed trends depending on the taxa and reflecting fluctuations in land cover and/or climate. A significant rising trend in Olea pollen counts was observed, attributable both to the increasing olive-growing area but also to changes in temperature and rainfall. Poaceae pollen concentrations also increased, due largely to an expansion of heterogeneous agricultural areas and to an increase in pollen season length positively influenced by rainfall and temperature. By contrast, the significant declining trend observed for pollen from ruderal taxa, such as Amaranthaceae, Rumex, Plantago and Urticaceae, may be linked to changes in urban planning strategies with a higher building pressure., (Copyright © 2016. Published by Elsevier B.V.)

This paper presents a methodology for calculating exhaust emissions from on-road transport in cities with low-quality traffic data and outdated vehicle registries. The methodology consists of data collection approaches and emission calculation methods. For data collection, the paper suggests using video survey and parking lot survey methods developed for the International Vehicular Emissions model. Additional sources of information include data from the largest transportation companies, vehicle inspection stations, and official vehicle registries. The paper suggests using the European Computer Programme to Calculate Emissions from Road Transport (COPERT) 4 model to calculate emissions, especially in countries that implemented European emissions standards. If available, the local emission factors should be used instead of the default COPERT emission factors. The paper also suggests additional steps in the methodology to calculate emissions only from diesel vehicles. We applied this methodology to calculate black carbon emissions from diesel on-road vehicles in Murmansk, Russia. The results from Murmansk show that diesel vehicles emitted 11.7 tons of black carbon in 2014. The main factors determining the level of emissions are the structure of the vehicle fleet and the level of vehicle emission controls. Vehicles without controls emit about 55% of black carbon emissions., (Copyright © 2015 Elsevier B.V. All rights reserved.)

The present paper reports the analytical results of PAHs concentrations in ambient air obtained in the PM10 and gas-phase, from 2004 to 2014, in Porto, Portugal. As part of a monitoring programme conducted by IDAD - Institute of Environment and Development and supported by the regional municipal solid waste (MSW) management authorities, an extensive database of PAH concentrations in ambient air was collected in Porto's metropolitan area. During this period a total of 201 samples were collected in two sites classified as suburban. Analytical results showed a clear decreasing trend of total PAHs (∑PAH) and benzo[a]pyrene (BaP) levels during the period of study, especially in the first years of monitoring. The average annual concentrations of BaP were, throughout the monitoring period, lower than the target value for the annual average (1 ng m(-3)) defined in the European legislation. PAHs levels showed a strong seasonality, with higher concentrations values during the colder months. The winter/summer ratio of ∑PAH for the eleven years of study was 5, revealing the seasonal variation of PAHs in the studied area. The estimated toxic equivalency factors (TEFs) used to assess the contribution of the carcinogenic potential, confirmed a significant presence of the moderately active carcinogenic BaP and dibenz[ah]anthracene (DahA) in the samples collected in Porto. The ratio values of individual PAHs concentrations were used as diagnostic tool to identify the possible origin of PAH in the ambient air of Porto. Based on diagnostic ratios, it may be concluded that automobile traffic emissions, mainly related to diesel vehicles, were the major contribution of PAH levels in the ambient air, although some others contributions, such as coal and wood combustion, were identified., (Copyright © 2015 Elsevier B.V. All rights reserved.)

The greenhouse gases and black carbon emission inventory from IPCC key category Energy was accomplished for the Mezquital Valley, one of the most polluted regions in Mexico, as the Mexico City wastewater have been continuously used in agricultural irrigation for more than a hundred years. In addition, thermoelectric, refinery, cement and chemistry industries are concentrated in the southern part of the valley, near Mexico City. Several studies have reported air, soil, and water pollution data and its main sources for the region. Paradoxically, these sources contaminate the valley, but boosted its economic development. Nevertheless, no research has been done concerning GHG emissions, or climate change assessment. This paper reports inventories performed by the 1996 IPCC methodology for the baseline year 2005. Fuel consumption data were derived from priority sectors such as electricity generation, refineries, manufacturing & cement industries, transportation, and residential use. The total CO2 emission result was 13,894.9 Gg, which constituted three-quarters of Hidalgo statewide energy category. The principal CO2 sources were energy transformation (69%) and manufacturing (19%). Total black carbon emissions were estimated by a bottom-up method at 0.66 Gg. The principal contributor was on-road transportation (37%), followed by firewood residential consumption (26%) and cocked brick manufactures (22%). Non-CO2 gas emissions were also significant, particularly SO2 (255.9 Gg), which accounts for 80% of the whole Hidalgo State emissions. Results demonstrated the negative environmental impact on Mezquital Valley, caused by its role as a Megacity secondary fuel and electricity provider, as well as by the presence of several cement industries., (Copyright © 2015 Elsevier B.V. All rights reserved.)

As more municipalities and communities across developed world look towards implementing organic waste management programmes or upgrading existing ones, composting facilities are emerging as a popular choice. However, odour from these facilities continues to be one of the most important concerns in terms of cost & effective mitigation. This paper provides a technological and life cycle assessment of some of the different odour control technologies and treatment methods that can be implemented in organics processing facilities. The technological assessment compared biofilters, packed tower wet scrubbers, fine mist wet scrubbers, activated carbon adsorption, thermal oxidization, oxidization chemicals and masking agents. The technologies/treatment methods were evaluated and compared based on a variety of operational, usage and cost parameters. Based on the technological assessment it was found that, biofilters and packed bed wet scrubbers are the most applicable odour control technologies for use in organics processing faculties. A life cycle assessment was then done to compare the environmental impacts of the packed-bed wet scrubber system, organic (wood-chip media) bio-filter and inorganic (synthetic media) bio-filter systems. Twelve impact categories were assessed; cumulative energy demand (CED), climate change, human toxicity, photochemical oxidant formation, metal depletion, fossil depletion, terrestrial acidification, freshwater eutrophication, marine eutrophication, terrestrial eco-toxicity, freshwater eco-toxicity and marine eco-toxicity. The results showed that for all impact categories the synthetic media biofilter had the highest environmental impact, followed by the wood chip media bio-filter system. The packed-bed system had the lowest environmental impact for all categories., (Copyright © 2015 Elsevier B.V. All rights reserved.)

Epidemiological studies investigating relationships between environmental exposures from air pollution and health typically use residential addresses as a single point for exposure, while environmental exposures in transit, at work, school or other locations are largely ignored. Personal exposure monitors measure individuals' exposures over time; however, current personal monitors are intrusive and cannot be operated at a large scale over an extended period of time (e.g., for a continuous three months) and can be very costly. In addition, spatial locations typically cannot be identified when only personal monitors are used. In this paper, we piloted a study that applied momentary location tracking services supplied by smart phones to identify an individual's location in space-time for three consecutive months (April 28 to July 28, 2013) using available Wi-Fi networks. Individual exposures in space-time to the traffic-related pollutants Nitrogen Oxides (NOX) were estimated by superimposing an annual mean NOX concentration surface modeled using the Land Use Regression (LUR) modeling technique. Individual's exposures were assigned to stationary (including home, work and other stationary locations) and in-transit (including commute and other travel) locations. For the individual, whose home/work addresses were known and the commute route was fixed, it was found that 95.3% of the time, the individual could be accurately identified in space-time. The ambient concentration estimated at the home location was 21.01 ppb. When indoor/outdoor infiltration, indoor sources of air pollution and time spent outdoors were taken into consideration, the individual's cumulative exposures were 28.59 ppb and 96.49 ppb, assuming a respective indoor/outdoor ratio of 1.33 and 5.00. Integrating momentary location tracking services with fixed-site field monitoring, plus indoor-outdoor air exchange calibration, makes exposure assessment of a very large population over an extended time period feasible., (Copyright © 2014 Elsevier B.V. All rights reserved.)

Air-quality forecasting in urban areas is difficult because of the uncertainties in describing both the emission and meteorological fields. The use of incomplete information in the training phase restricts practical air-quality forecasting. In this paper, we propose a hybrid artificial neural network and a hybrid support vector machine, which effectively enhance the forecasting accuracy of an artificial neural network (ANN) and support vector machine (SVM) by revising the error term of the traditional methods. The hybrid methodology can be described in two stages. First, we applied the ANN or SVM forecasting system with historical data and exogenous parameters, such as meteorological variables. Then, the forecasting target was revised by the Taylor expansion forecasting model using the residual information of the error term in the previous stage. The innovation involved in this approach is that it sufficiently and validly utilizes the useful residual information on an incomplete input variable condition. The proposed method was evaluated by experiments using a 2-year dataset of daily PM₁₀ (particles with a diameter of 10 μm or less) concentrations and SO₂ (sulfur dioxide) concentrations from four air pollution monitoring stations located in Taiyuan, China. The theoretical analysis and experimental results demonstrated that the forecasting accuracy of the proposed model is very promising., (Copyright © 2014 Elsevier B.V. All rights reserved.)

Exposure to high concentrations of fine particulate matter (PM₂.₅) can cause serious health problems because PM₂.₅ contains microscopic solid or liquid droplets that are sufficiently small to be ingested deep into human lungs. Thus, daily prediction of PM₂.₅ levels is notably important for regulatory plans that inform the public and restrict social activities in advance when harmful episodes are foreseen. A hybrid EEMD-GRNN (ensemble empirical mode decomposition-general regression neural network) model based on data preprocessing and analysis is firstly proposed in this paper for one-day-ahead prediction of PM₂.₅ concentrations. The EEMD part is utilized to decompose original PM₂.₅ data into several intrinsic mode functions (IMFs), while the GRNN part is used for the prediction of each IMF. The hybrid EEMD-GRNN model is trained using input variables obtained from principal component regression (PCR) model to remove redundancy. These input variables accurately and succinctly reflect the relationships between PM₂.₅ and both air quality and meteorological data. The model is trained with data from January 1 to November 1, 2013 and is validated with data from November 2 to November 21, 2013 in Xi'an Province, China. The experimental results show that the developed hybrid EEMD-GRNN model outperforms a single GRNN model without EEMD, a multiple linear regression (MLR) model, a PCR model, and a traditional autoregressive integrated moving average (ARIMA) model. The hybrid model with fast and accurate results can be used to develop rapid air quality warning systems., (Copyright © 2014 Elsevier B.V. All rights reserved.)

This paper revisits the emission scenarios of the European Commission's 2005 Thematic Strategy on Air Pollution (TSAP) in light of today's knowledge. We review assumptions made in the past on the main drivers of emission changes, i.e., demographic trends, economic growth, changes in the energy intensity of GDP, fuel-switching, and application of dedicated emission control measures. Our analysis shows that for most of these drivers, actual trends have not matched initial expectations. Observed ammonia and sulfur emissions in European Union in 2010 were 10% to 20% lower than projected, while emissions of nitrogen oxides and particulate matter exceeded estimates by 8% to 15%. In general, a higher efficiency of dedicated emission controls compensated for a lower-than-expected decline in total energy consumption as well as a delay in the phase-out of coal. For 2020, updated projections anticipate lower sulfur and nitrogen oxide emissions than those under the 2005 baseline, whereby the degree to which these emissions are lower depends on what assumptions are made for emission controls and new vehicle standards. Projected levels of particulates are about 10% higher, while smaller differences emerge for other pollutants. New emission projections suggest that environmental targets established by the TSAP for the protection of human health, eutrophication and forest acidification will not be met without additional measures., (Copyright © 2014 Elsevier B.V. All rights reserved.)

The broad objective of this study was to develop CO2, PM, SOx, CO, NOx, VOC, NH3 and N2O emission inventory of organic and inorganic chemicals, mineral products, metallurgical, petroleum refining, wood products, food industries of Turkey for 2010 for both co]ntrolled and uncontrolled conditions. In this study, industries were investigated in 7 main categories and 53 sub-sectors and a representative number of pollutants per sub-sector were considered. Each industry was evaluated in terms of emitted emissions only from industrial processes, and fuel combustion activities were excluded (except cement industry). The study employed an approach designed in four stages; identification of key categories; activity data & emission factor search; emission factor analyzing; calculation of emissions. Emission factor analyzing required aggregate and firm analysis of sectors and sub-sectors and deeper insights into underlying specific production methods used in the industry to decide on the most representative emission factor. Industry specific abatement technologies were considered by using open-source documents and industry specific reports. Regarding results of this study, mineral industry and iron & steel industry were determined as important contributors of industrial emissions in Turkey in 2010. Respectively, organic chemicals, petroleum refining, and pulp & paper industries had serious contributions to Turkey's air pollutant emission inventory from industrial processes. The results showed that calculated CO2 emissions for year 2010 was 55,124,263 t, also other emissions were 48,853 t PM, 24,533 t SOx, 79,943 t NOx, 31,908 t VOC, 454 t NH3 and 2264 t N2O under controlled conditions., (Copyright © 2014 Elsevier B.V. All rights reserved.)

The CAQI or Common Air Quality Index was proposed to facilitate the comparison of air quality in European cities in real-time. There are many air quality indices in use in the world. All are somewhat different in concept and presentation and comparing air quality presentations of cities on the internet was virtually impossible. The CAQI and the accompanying website www.airqualitynow.eu and app were proposed to overcome this problem in Europe. This paper describes the logic of making an index, in particular the CAQI and its update with a grid for PM2.5. To assure a smooth transition to the new calculation scheme we studied the behaviour of the index before and after the changes. We used 2006 Airbase data from 31 urban background and 27 street stations all across Europe (that were monitoring PM2.5 in 2006). The CAQI characterises a city by a roadside and urban background situation. It also insists on a minimum number of pollutants to be included in the calculation. Both were deemed necessary to improve the basis for comparing one city to another. A sensitivity analysis demonstrates the comparative behaviour of the street and urban background stations and presents the sensitivity of the CAQI outcome to the pollutants included in its calculation., (© 2013.)

As part of a UK government funded research project to update the UK N2O inventory methodology, a systematic review of published nitrous oxide (N2O) emission factors was carried out of non-UK research, for future comparison and synthesis with the UK measurement based evidence base. The aim of the study is to assess how the UK IPCC default emission factor for N2O emissions derived from synthetic or organic fertiliser inputs (EF1) compares to international values reported in published literature. The availability of data for comparing and/or refining the UK IPCC default value and the possibility of analysing sufficient auxiliary data to propose a Tier 2 EF1 reporting strategy is evaluated. The review demonstrated a lack of consistency in reporting error bounds for fertiliser-derived EFs and N2O flux data with 8% and 44% of publications reporting EF and N2O flux error bounds respectively. There was also poor description of environmental (climate and soil) and experimental design auxiliary data. This is likely to be due to differences in study objectives, however potential improvements to soil parameter reporting are proposed. The review demonstrates that emission factors for agricultural-derived N2O emissions ranged -0.34% to 37% showing high variation compared to the UK Tier 1 IPCC EF1 default values of 1.25% (IPCC 1996) and 1% (IPPC 2006). However, the majority (83%) of EFs reported for UK-relevant soils fell within the UK IPCC EF1 uncertainty range of 0.03% to 3%. Residual maximum likelihood (REML) analysis of the data collated in the review showed that the type and rate of fertiliser N applied and soil type were significant factors influencing EFs reported. Country of emission, the length of the measurement period, the number of splits, the crop type, pH and SOC did not have a significant impact on N2O emissions. A subset of publications where sufficient data was reported for meta-analysis to be conducted was identified. Meta-analysis of effect sizes of 41 treatments demonstrated that the application of fertiliser has a significant effect on N2O emissions in comparison to control plots and that emission factors were significantly different to zero. However no significant relationships between the quantity of fertiliser applied and the effect size of the amount of N2O emitted from fertilised plots compared to control plots were found. Annual addition of fertiliser of 35 to 557 kg N/ha gave a mean increase in emissions of 2.02 ± 0.28 g N2O/ha/day compared to control treatments (p<0.01). Emission factors were significantly different from zero, with a mean emission factor estimated directly from the meta analysis of 0.17 ± 0.02%. This is lower than the IPCC 2006 Tier 1 EF1 value of 1% but falling within the uncertainty bound for the IPCC 2006 Tier 1 EF1 (0.03% to 3%). As only a small number of papers were viable for meta analysis to be conducted due to lack of reporting of the key controlling factors, the estimates of EF in this paper cannot include the true variability under conditions similar to the UK. Review-derived EFs of 0.34% to 37% and mean EF from meta-analysis of 0.17 ± 0.02% highlight variability in reporting EFs depending on the method applied and sample size. A protocol of systematic reporting of N2O emissions and key auxiliary parameters in publications across disciplines is proposed. If adopted this would strengthen the community to inform IPCC Tier 2 reporting development and reduce the uncertainty surrounding reported UK N2O emissions., (Copyright © 2014 Elsevier B.V. All rights reserved.)

This paper aims at presenting a dynamic indicator for life cycle assessment (LCA) measuring cumulative impacts over time of greenhouse gas (GHG) emissions from fertilizers used for wheat cultivation and production. Our approach offers a dynamic indicator of global warming potential (GWP), one of the most used indicator of environmental impacts (e.g. in the Kyoto Protocol). For a case study, the wheat production in France was selected and considered by using data from official sources about fertilizer consumption and production of wheat. We propose to assess GWP environmental impact based on LCA method. The system boundary is limited to the fertilizer production for 1 ton of wheat produced (functional unit) from 1910 to 2010. As applied to wheat production in France, traditional LCA shows a maximum GWP impact of 500 kg CO2-eq for 1 ton of wheat production, whereas the GWP impact of wheat production over time with our approach to dynamic LCA and its cumulative effects increases to 18,000 kg CO2-eq for 1 ton of wheat production. In this paper, only one substance and one impact assessment indicator are presented. However, the methodology can be generalized and improved by using different substances and indicators., (Copyright © 2014 Elsevier B.V. All rights reserved.)

This paper provides evidence that symmetry of CO2 concentration distribution may indicate sources or dispersive processes. Skewness was calculated by different procedures with CO2 measured at a rural site using a Picarro G1301 analyser over a two-year period. The usual skewness coefficient was considered together with fourteen robust estimators. A noticeable contrast was obtained between day and night, and skewness decreased linearly with the logarithm of the height. One coefficient was selected from its satisfactory relationship with the median concentration in daily evolution. Three analyses based on the kernel smoothing method were conducted with this coefficient to investigate its response to yearly and daily evolutions, wind direction, and wind speed. Left-skewed distributions were linked to thermal turbulence during midday, especially in spring-summer, or with high wind speeds. Almost symmetric distributions were associated with sources, such as the Valladolid City plume reinforced with spring emissions and the lack of emissions in summer in the remaining directions. Finally, right-skewed distributions were related to low wind speeds and stable stratification at night, furthered by strong emissions in spring. Skewness intervals were proposed and their average median concentrations were calculated such that the relationship between skewness and concentration depends on the analysis performed. Since some skewness coefficients may also be negative, they provide better information about sources or dispersive processes than concentration., (Copyright © 2014 Elsevier B.V. All rights reserved.)

The paper presents the application of a Lagrangian particle model to problems connected with safety in road transport. Numerical simulations were performed for a hypothetical case of smoke emission from a tanker fire in a built-up area. Propagation of smoke was analysed for three wind directions. A diagnostic model was used to determine the air velocity field, whereas the dispersion of pollutants was analysed by means of a Lagrangian particle model (Brzozowska, 2013). The Idrisi Andes geographic information system was used to provide data on landforms and on their aerodynamic roughness. The presented results of computations and their analysis exemplify a possible application of the Lagrangian particle model: evaluation of mean (averaged over time) concentrations of pollutants and their distribution in the considered area (especially important due to the protection of people, animals and plants) and simulation of the propagation of harmful compounds in time as well as performing computations for cases of the potential effects of road incidents., (Copyright © 2013 Elsevier B.V. All rights reserved.)

There is a high interest in quantifying temporal trends in surface ozone concentrations as they serve to quantify the impacts of the anthropogenic precursor reductions and to assess the effects of emission control strategies. In this paper ozone trends for nearly 2 decades (1993 to 2011) at both rural and urban sites have been analysed, using ground level ozone data from 5 urban and 15 rural sites, which are part of the UK AURN. This study analyses ozone trends at various percentiles, in addition to traditional mean trends using quantile regression, TheilSen function, and changepoint analysis. Ozone trends show significant variability at different statistical metrics (e.g., mean, median, maximum and selected quantiles). Maximum trends were negative, whereas median and mean trends were positive during the study period (1993-2011) at both rural and urban sites. Urban and rural trends show different rates of change and indicate that urban decrement (the difference in ozone concentration between rural and urban areas) has been decreasing over the period. Ozone trends were negative during the last 8 years (2004-2011), which could have been caused by the stabilisation of NOx concentration during this period. Furthermore, 3 changepoints were detected in the temporal trend using Pruned Exact Linear Time (PELT) search algorithm, which provides further insight into the ozone temporal trends., (Copyright © 2013 Elsevier B.V. All rights reserved.)

To fulfill the requirements of the 2008/50 Directive, which allows member states and regional authorities to use a combination of measurement and modeling to monitor air pollution concentration, a key approach to be properly developed and tested is the data assimilation one. In this paper, with a focus on regional domains, a comparison between optimal interpolation and Ensemble Kalman Filter is shown, to stress pros and drawbacks of the two techniques. These approaches can be used to implement a more accurate monitoring of the long-term pollution trends on a geographical domain, through an optimal combination of all the available sources of data. The two approaches are formalized and applied for a regional domain located in Northern Italy, where the PM10 level which is often higher than EU standard limits is measured., (Copyright © 2013 Elsevier B.V. All rights reserved.)

Preterm birth is one of the leading causes of perinatal mortality and is associated with long-term adverse health consequences for surviving infants. Preterm birth rates are rising worldwide, and no effective means for prevention currently exists. Air pollution exposure may be a significant cause of prematurity, but many published studies lack the individual, clinical data needed to elucidate possible biological mechanisms mediating these epidemiological associations. This paper presents the design of a prospective study now underway to evaluate those mechanisms in a cohort of pregnant women residing in Mexico City. We address how air quality may act together with other factors to induce systemic inflammation and influence the duration of pregnancy. Data collection includes: biomarkers relevant to inflammation in cervico-vaginal exudate and peripheral blood, along with full clinical information, pro-inflammatory cytokine gene polymorphisms and air pollution data to evaluate spatial and temporal variability in air pollution exposure. Samples are collected on a monthly basis and participants are followed for the duration of pregnancy. The data will be used to evaluate whether ambient air pollution is associated with preterm birth, controlling for other risk factors. We will evaluate which time windows during pregnancy are most influential in the air pollution and preterm birth association. In addition, the epidemiological study will be complemented with a parallel toxicology invitro study, in which monocytic cells will be exposed to air particle samples to evaluate the expression of biomarkers of inflammation., (Copyright © 2012 Elsevier B.V. All rights reserved.)

This paper explores technologies currently expanding the physical scope of air pollution monitoring and their potential contributions to the assessment of sustainable development. This potential lies largely in the ability of these technologies to address issues typically on the fringe of the air pollution agenda. Air pollution monitoring tends to be primarily focused on human health, and largely neglects other aspects of sustainable development. Sensor networks, with their relatively inexpensive monitoring nodes, allow for monitoring with finer spatiotemporal resolution. This resolution can support more conclusive studies of air pollution's effect on socio-ecological justice and human quality of life. Satellite observation of air pollution allows for wider geographical scope, and in doing so can facilitate studies of air pollution's effects on natural capital and ecosystem resilience. Many air pollution-related aspects of the sustainability of development in human systems are not being given their due attention. Opportunities exist for air pollution monitoring to attend more to these issues. Improvements to the resolution and scale of monitoring make these opportunities realizable., (Copyright © 2012 Elsevier B.V. All rights reserved.)

Quantifying human exposure to air pollutants is a challenging task. Ambient concentrations of air pollutants at potentially harmful levels are ubiquitous in urban areas and subject to high spatial and temporal variability. At the same time, every individual has unique activity-patterns. Exposure results from multifaceted relationships and interactions between environmental and human systems, adding complexity to the assessment process. Traditionally, approaches to quantify human exposure have relied on pollutant concentrations from fixed air quality network sites and static population distributions. New developments in sensor technology now enable us to monitor personal exposure to air pollutants directly while people are moving through their activity spaces and varying concentration fields. The literature review on which this paper is based on reflects recent developments in the assessment of human exposure to air pollution. This includes the discussion of methodologies and concepts, and the elaboration of approaches and study designs applied in the field. We identify shortcomings of current approaches and discuss future research needs. We close by proposing a novel conceptual model for the integrated assessment of human exposure to air pollutants taking into account latest technological capabilities and contextual information., (Copyright © 2012 Elsevier B.V. All rights reserved.)

Many studies demonstrate a strong relationship between air pollution and respiratory and cardiovascular diseases. For this reason, assessing air pollution, and conveying information about its possible adverse health effects, may encourage population and policy makers to reduce those activities increasing pollution levels. In this paper a relative index of variability, to be associated with the aggregate Air Quality Index (AQI) among pollutants proposed by Ruggieri and Plaia (2011), is developed in order to better investigate air pollution conditions for the whole area of a city/region. The most widely-used and up to date pollution indices, based mainly on AQI computed by the US Environmental Protection Agency (EPA) and often defined by the value of the pollutant with the highest (opportunely standardized) concentration on a given day, aim at warning the people for short term health impact. An aggregate AQI, taking into account the combined effects of all the considered pollutants, gives emphasis to possible chronic health effects and long term damages on environment caused by air pollution. The proposed index of variability adds precious information to the aggregate AQI, as it allows one to know whether the value assumed by the AQI is influenced by one or more pollutants. The two indices are jointly used on simulated data, considering different possible scenarios. Applications to real air pollution data are also reported. Before applying the two indices, the effects of different standardizations on data are evaluated from a theoretical point of view., (Copyright © 2010 Elsevier B.V. All rights reserved.)

A new method is presented which is designed to investigate whether laboratory test data used in the development of vehicle emission models adequately reflects emission distributions, and in particular the influence of high-emitting vehicles. The method includes the computation of a 'high-emitter' or 'emission distribution' correction factor for use in emission inventories. In order to make a valid comparison we control for a number of factors such as vehicle technology, measurement technique and driving conditions and use a variable called 'Pollution Index' (g/kg). Our investigation into one vehicle class has shown that laboratory and remote sensing data are substantially different for CO, HC and NO(x) emissions, both in terms of their distributions as well as in their mean and 99-percentile values. Given that the remote sensing data has larger mean values for these pollutants, the analysis suggests that high-emitting vehicles may not be adequately captured in the laboratory test data. The paper presents two different methods for the computation of weighted correction factors for use in emission inventories based on laboratory test data: one using mean values for six 'power bins' and one using multivariate regression functions. The computed correction factors are substantial leading to an increase for laboratory-based emission factors with a factor of 1.7-1.9 for CO, 1.3-1.6 for HC and 1.4-1.7 for NO(x) (actual value depending on the method). However, it also clear that there are points that require further examination before these correction factors should be applied. One important step will be to include a comparison with other types of validation studies such as tunnel studies and near-road air quality assessments to examine if these correction factors are confirmed. If so, we would recommend using the correction factors in emission inventories for motor vehicles., (Copyright © 2011 Elsevier B.V. All rights reserved.)