Showing papers on "Air pollutant concentrations published in 2020"

Worsening urban ozone pollution in China from 2013 to 2017 – Part 1: The complex and varying roles of meteorology

Abstract: . China has suffered from increasing levels of ozone pollution in urban areas despite the implementation of various stringent emission reduction measures since 2013. In this study, we conducted numerical experiments with an up-to-date regional chemical transport model to assess the contribution of the changes in meteorological conditions and anthropogenic emissions to the summer ozone level from 2013 to 2017 in various regions of China. The model can faithfully reproduce the observed meteorological parameters and air pollutant concentrations and capture the increasing trend in the surface maximum daily 8 h average (MDA8) ozone ( O3 ) from 2013 to 2017. The emission-control measures implemented by the government induced a decrease in MDA8 O3 levels in rural areas but an increase in urban areas. The meteorological influence on the ozone trend varied by region and by year and could be comparable to or even more significant than the impact of changes in anthropogenic emissions. Meteorological conditions can modulate the ozone concentration via direct (e.g., increasing reaction rates at higher temperatures) and indirect (e.g., increasing biogenic emissions at higher temperatures) effects. As an essential source of volatile organic compounds that contributes to ozone formation, the variation in biogenic emissions during summer varied across regions and was mainly affected by temperature. China's midlatitude areas (25 to 40 ∘ N) experienced a significant decrease in MDA8 O3 due to a decline in biogenic emissions, especially for the Yangtze River Delta and Sichuan Basin regions in 2014 and 2015. In contrast, in northern (north of 40 ∘ N) and southern (south of 25 ∘ N) China, higher temperatures after 2013 led to an increase in MDA8 O3 via an increase in biogenic emissions. We also assessed the individual effects of changes in temperature, specific humidity, wind field, planetary boundary layer height, clouds, and precipitation on ozone levels from 2013 to 2017. The results show that the wind field change made a significant contribution to the increase in surface ozone over many parts of China. The long-range transport of ozone and its precursors from outside the modeling domain also contributed to the increase in MDA8 O3 in China, especially on the Qinghai–Tibetan Plateau (an increase of 1 to 4 ppbv). Our study represents the most comprehensive and up-to-date analysis of the impact of changes in meteorology on ozone across China and highlights the importance of considering meteorological variations when assessing the effectiveness of emission control on changes in the ozone levels in recent years.

Historical and future changes in air pollutants from CMIP6 models

Abstract: . Poor air quality is currently responsible for large impacts on human health across the world. In addition, the air pollutants, ozone (O3) and particulate matter less than 2.5 microns in diameter (PM2.5), are also radiatively active in the atmosphere and can influence Earth’s climate. It is important to understand the effect of air quality and climate mitigation measures over the historical period and in different future scenarios to ascertain any impacts from air pollutants on both climate and human health. The 6th Coupled Model Intercomparison Project (CMIP6) presents an opportunity to analyse the change in air pollutants simulated by the current generation of climate and Earth system models that include a representation of chemistry and aerosols (particulate matter). The shared socio-economic pathways (SSPs) used within CMIP6 encompass a wide range of trajectories in precursor emissions and climate change, allowing for an improved analysis of future changes to air pollutants. Firstly, we conduct an evaluation of the available CMIP6 models against surface observations of O3 and PM2.5. CMIP6 models show a consistent overestimation of observed surface O3 concentrations across most regions and in most seasons, with a large diversity in simulated values over northern hemisphere continental regions. Conversely, observed surface PM2.5 concentrations are consistently underestimated by CMIP6 models, particularly for the northern hemisphere winter months, with the largest model diversity near natural emission source regions. Over the historical period (1850–2014) large increases in both surface O3 and PM2.5 are simulated by the CMIP6 models across all regions, particularly over the mid to late 20th Century when anthropogenic emissions increase markedly. Large regional historical changes are simulated for both pollutants, across East and South Asia, with an increase of up to 40 ppb for O3 and 12 µg m-3 for PM2.5. In future scenarios containing strong air quality and climate mitigation measures (ssp126), air pollutants are substantially reduced across all regions by up to 15 ppb for O3 and 12 µg m-3 for PM2.5. However, for scenarios that encompass weak action on mitigating climate and reducing air pollutant emissions (ssp370), increases of both surface O3 (up 10 ppb) and PM2.5 (up to 8 µg m-3) are simulated across most regions. Although, for regions like North America and Europe small reductions in PM2.5 are simulated in this scenario. A comparison of simulated regional changes in both surface O3 and PM2.5 from individual CMIP6 models highlights important differences due to the interaction of aerosols, chemistry, climate and natural emission sources within models. The prediction of regional air pollutant concentrations from the latest climate and Earth system models used within CMIP6 shows that the particular future trajectory of climate and air quality mitigation measures could have important consequences for regional air quality, human health and near-term climate. Differences between individual models emphasises the importance of understanding how future Earth system feedbacks influence natural emission sources.

Roadway tunnels: A critical review of air pollutant concentrations and vehicular emissions

Abstract: Air quality is a widespread problem with the presence of pollutants in indoor and outdoor environments that generate significant consequences for the population, ecosystems and exposed materials. Vehicular traffic is one of the main sources of air pollutants and, therefore, needs to be studied and analysed in detail. This review reported the results of studies conducted on tunnels, in particular for the measurement of concentrations and the definition of emission factors. The characteristics of the tunnels, available ventilation systems, type of vehicular traffic, and geographical distribution, in addition to concentrations and emission factors, are discussed. Light-duty vehicles are the most frequent category in the case studies. Between the fuels used, gasoline is by far the most widespread. Pollutant concentrations concentrations can reach very high levels. For example, atmospheric particulates (with an aerodynamic diameter of 10 µm) and nitrogen dioxide have also reached levels of 1490 µg/m3 and 4982 µg/m3, respectively.

Association between exposure to traffic-related air pollution and pediatric allergic diseases based on modeled air pollution concentrations and traffic measures in Seoul, Korea: a comparative analysis

Abstract: Pediatric allergic diseases are a major public health concern, and previous studies have suggested that exposure to traffic-related air pollution (TRAP) exposure is a risk factor. These studies have typically assessed TRAP exposure using traffic measures, such as distance to major roads, or by modeling air pollutant concentrations; however inconsistent associations with pediatric allergic diseases have often been found. Using road proximity and density, we previously found an association between TRAP and atopic eczema among approximately 15,000 children living in Seoul, Korea, heavily populated and highly polluted city in which traffic is a major emission source. We aimed to conduct a parallel analysis using modeled air pollution concentrations and thus examine the consistency of the association. Specifically, we examined the associations of individual-level annual-average concentrations of NO2, PM10, and PM2.5 with symptoms and diagnoses of three pediatric allergic diseases including asthma, allergic rhinitis, and atopic eczema. The study population included 14,614 children from the Seoul Atopy Friendly School Project Survey in Seoul, Korea, in 2010. To assess individual exposures to TRAP among these children, we predicted annual-average concentrations of NO2, PM10, and PM2.5 at the children’s home addresses in 2010 using universal kriging and land use regression models along with regulatory air quality monitoring data and geographic characteristics. Then, we estimated odds ratios (ORs) of the three allergic diseases for interquartile increases in air pollution concentrations after adjusting for individual risk factors in mixed effects logistic regression. Symptoms and diagnoses of atopic eczema symptoms showed an association with NO2 (OR = 1.07, 95% confidence interval = 1.02–1.13; 1.08, 1.03–1.14) and PM10 (1.06, 1.01–1.12; 1.07, 1.01–1.13). ORs of PM2.5 were positive but not statistically significant (1.01, 0.95–1.07; 1.04, 0.98–1.10). No association was found between asthma and allergic rhinitis, although PM2.5 showed a marginal association with allergic rhinitis. Our consistent findings regarding the association between TRAP and the prevalence of atopic eczema using traffic measures and surrogate air pollutants suggested the effect of TRAP on children’s health. Follow-up studies should elucidate the causal link, to support subsequent policy considerations and minimize adverse health effects in children.

Analysis of the Air Pollution Monitoring System in Ukraine

Abstract: In this chapter, the basic features of the functioning of the monitoring system of air pollution in Ukraine are considered. The process of implementing Directive 2008/50/EU in Ukrainian legislation, the requirements for monitoring various pollutants in the air (particulate matter (PM2.5, PM10), CO, SO2, NO2, O3) and the measures that Ukraine must take to implementation of the Directive are considered. The approaches to monitoring air pollution in Ukraine, the features of the Ukrainian air quality index—air pollution index are considered. The state of air pollution in different cities of Ukraine is analyzed, the most polluted cities and regions are determined in accordance with the air pollution index. Statistical studies on emissions into the air by stationary and mobile sources of pollution in Ukraine in 1990–2018 are carried out. In particular, the following pollutants were considered: SO2, NO2, CO, CO2, PAHs, Zn, Pb, Cu, Cr, Ni, Ar. It has been established that 5 cities in Ukraine generate emissions, which make up 40.2% of all emissions in the country. The main enterprises polluting the air in the largest cities are given. The process of measuring air pollutant concentrations as part of an air pollution monitoring system is considered. The optimal number of posts required for the implementation of the Directive has been determined. The features of monitoring air pollution in Kyiv are considered. The above-mentioned shortcomings of the air pollution monitoring system are shown and ways to eliminate them are proposed. A modern information-analytical system for monitoring air pollution is proposed.

Spatio-temporal regression kriging for modelling urban NO2 concentrations

Abstract: Recently developed urban air quality sensor networks are used to monitor air pollutant concentrations at a fine spatial and temporal resolution. The measurements are however limited to point suppor...

The effects of COVID-19 measures on air pollutant concentrations at urban and traffic sites in Istanbul

Abstract: Since December 2019, most countries have been working to stop the spread of SARS-CoV-2, the virus responsible for COVID-19 These measures, which include restricting movement, have environmental consequences This study assessed the impact of COVID-19 measures on air pollutant concentrations measured in urban areas and traffic stations on both the European and Asian sides of Istanbul during March 2020 Significant reductions in pollutants: 32–43% (PM10), 19–47% (PM2 5), 29–44% (NO2), 40–58% (CO) and 34–69% (SO2) were calculated The clearest reductions at the traffic stations were in NO2 which originates primarily from vehicle exhaust The reduction of NO2 at the traffic station on the European side was found higher comparing the Asian side The average concentrations of NO2, PM2 5, PM10 and CO during peak traffic hours were significantly (p <0 01) decreased under COVID-19 measures The results indicate that due to the measures taken in Istanbul and across Turkey and to control the spread of the virus, anthropogenic activities such as industry, vehicle traffic and sea transport have decreased, and consequently, air pollution has been significantly reduced These pollutant levels demonstrate the anthropogenic contribution to air pollution and can inform clean air actions in Istanbul and in others cities throughout the world © The Author(s)

A Random Forest Approach to Estimate Daily Particulate Matter, Nitrogen Dioxide, and Ozone at Fine Spatial Resolution in Sweden

Abstract: Air pollution is one of the leading causes of mortality worldwide. An accurate assessment of its spatial and temporal distribution is mandatory to conduct epidemiological studies able to estimate long-term (e.g., annual) and short-term (e.g., daily) health effects. While spatiotemporal models for particulate matter (PM) have been developed in several countries, estimates of daily nitrogen dioxide (NO2) and ozone (O3) concentrations at high spatial resolution are lacking, and no such models have been developed in Sweden. We collected data on daily air pollutant concentrations from routine monitoring networks over the period 2005–2016 and matched them with satellite data, dispersion models, meteorological parameters, and land-use variables. We developed a machine-learning approach, the random forest (RF), to estimate daily concentrations of PM10 (PM<10 microns), PM2.5 (PM<2.5 microns), PM2.5–10 (PM between 2.5 and 10 microns), NO2, and O3 for each squared kilometer of Sweden over the period 2005–2016. Our models were able to describe between 64% (PM10) and 78% (O3) of air pollutant variability in held-out observations, and between 37% (NO2) and 61% (O3) in held-out monitors, with no major differences across years and seasons and better performance in larger cities such as Stockholm. These estimates will allow to investigate air pollution effects across the whole of Sweden, including suburban and rural areas, previously neglected by epidemiological investigations.

Statistical analysis of atmospheric pollutant concentrations in parts of Imo State, Southeastern Nigeria

Abstract: This study was carried out to analyze the concentrations of some atmospheric pollutants in some parts of Imo State, southeastern Nigeria using statistical techniques. In the present study, PM10, NO2, SO2, CO, VOC and H2S in some parts of Imo State Southeastern Nigeria were analyzed to determine their presence, concentrations and possible sources of emission. This study also tried to establish possible relationship between pollutants spatial variation and dispersion with industrial and anthropogenic activities within the study area. The study area includes Egbema, Orlu, Okigwe and Orlu areas of Imo State, Nigeria. Air quality data was collected three times a day (morning, afternoon and evening) using the Gasman Air Monitors which was specifically used for SO2, NO2 and CO measurements, the Haze-dust Particulate Monitor 10 µm was used for PM10 data acquisition. Similarly, the Aeroqual Gas Monitor Model 300 was used for H2S measurement while the Ibrid MX6 Gas Monitor was used for VOC measurement. Results of the study revealed that the mean PM10 and CO levels in the locations exceeded the 24 h limit of 150 µg/m3 and 35 ppm of the United States National Ambient Air Quality Standards (US NAAQS) respectively. In addition, the mean concentrations of NO2 was above the annual limit of 0.053 ppm as prescribed by US NAAAQS, while the mean values of SO2 were within the annual and 1–hour limits of 0.5 ppm and 0.075 ppm respectively as stipulated by the US NAAQS. Whereas significant concentrations of H2S were not detected in the various locations, elevated concentration of VOC were recorded within Egbema area indicating possible influence from gas flaring and other crude oil related activities. The ANOVA and Box and Whisker plots revealed remarkable variations of the air pollutant concentrations in the study area. In addition, while the Hierarchical Cluster Analysis (HCA) grouped the pollutants into one major group, Principal Component Analysis (PCA) further grouped them into one coherent component indicating similar source of emission. The findings of this study therefore showed the need for regular air quality monitoring of the area to forestall adverse environmental problems.

Development of Weighting Scheme for Indoor Air Quality Model Using a Multi-Attribute Decision Making Method

Abstract: When planning the energy demand of ventilation, proper consideration should be given to the possible scenarios of indoor air quality and pollutant concentrations. The purpose of the present research is to create a practical method of prioritising indoor air pollutants, considering technical, economical and health aspects, in the Indoor Air Quality model (IAQ). In order to find the global weights for the combined IAQindex model sub-elements (in practice, air pollutant concentrations), the Multi-Criteria Decision Making (MCDM) approach is used. The authors have approached the problem of a weighting scheme in a model such as the complex model of the IAQ related to making decisions with many criteria and with the Multi-Attribute Decision Making MADM approach (specifically MCDM). The basis of the MADM method is a decision matrix constructed rationally by the authors, which includes six attributes: actual indoor air carbon dioxide concentration, total volatile organic compounds (TVOCs) and formaldehyde HCHO concentration, and their anthropogenic and construction product emissions to the indoor environment. The decision model of IAQindex includes five alternatives (possible situations), and the combination of pollutant concentration attributes with additional emission attributes is related to the indoor environment under specific situation. For defining the weights of criteria, the authors provide objective approaches: (i) entropy-based approach considering measuring the amount of information, and (ii) CRITIC, a statistic-based approach. The value of the presented method, i.e., the determination of global weights for IAQ components, is shown as a practical application to determine IAQ and the Indoor Environmental Quality (IEQ) index for an office building used as a case study.

Spatiotemporal variations and contributing factors of air pollutant concentrations in Malaysia during movement control order due to pandemic COVID-19

Abstract: The restriction of daily and economic-related activities due to COVID-19 pandemic via lockdown order has been reported to improve air quality This study evaluated temporal and spatial variations of four major air pollutant concentrations across Malaysia before (March 4, 2020–March 17, 2020) and during the implementation of different phases of Movement Control Order (MCO) (March 18, 2020–May 12, 2020) from 65 official regulatory air quality stations Results showed that restriction in daily and economic activities has remarkably reduced the air quality in all sub-urban, urban, and industrial settings with relatively small contributions from meteorological conditions Overall, compared to before MCO, average concentrations of PM2 5, CO, and NO2 reduced by 23 1%, 21 74%, and 54 0%, respectively, while that of SO2 was constant The highest reduction of PM2 5, CO, and NO2 were observed in stations located in urban setting, where 63% stations showed significant reduction (p <0 05) for PM2 5 and CO, while all stations showed significant reduction in NO2 concentrations It was also revealed that 70 5% stations recorded lower concentrations of PM2 5 during MCO compared to before MCO, despite that high numbers of local hotspots were observed simultaneously from NASA’s Moderate Resolution Imaging Spectroradiometer (MODIS) Spatial analysis showed that the northern part of Peninsular had the highest significant reduction of PM2 5, while the highest of NO2 and CO reduction were found in stations located in the central region All pollutants exhibit similar diurnal trends when compared between pre-and during MCO although significant lower readings were observed during MCO This study gives confidence to regulatory body;the enforcement of strict air pollution prevention and control policies could help in reducing pollution © 2020, AAGR Aerosol and Air Quality Research All rights reserved