Air pollutant levels are 12 times higher than guidelines in Varanasi,India. Sources and transfer

Air quality in an urban atmosphere is regulated by both local and distant emission sources. For air quality management in urban areas, identification of sources and their relationships with local meteorology and air pollutants are essential. The critical condition of air quality in Indo-Gangetic plain is well known, but lack of data on both local and distant emission sources limits the scope of improving air quality in this region. Concentrations of particulate matter of size lower than 10 μm (PM₁₀) were assessed in the highly urbanized Varanasi city situated in middle Indo-Gangetic plain of India from 2014 to 2017, to identify the distant air pollution sources based on trajectory statistical models and local sources by conditional bivariate probability function. Modifying effects of meteorology and air pollutants on PM₁₀ were also explored. Mean PM₁₀ concentration for the study period was 244.8 ± 135.8 μg m^?3, which was 12 times higher than the WHO annual guideline. Several distinct sources of traffic as the major source of PM₁₀ were identified in the city. Trajectory statistical models like cluster analysis, potential source contribution function and concentration-weighted trajectory showed significant contributions from north-west and eastern directions in the transport of polluted air masses to the city. Dew point, wind speed, temperature and ventilation coefficient are the major factors in PM₁₀ formation and dispersion.     

High reduction of ozone and particulate matter during the 2016 G-20 summit in Hangzhou by forced emission controls of industry and traffic

Many regions in China experience air pollution episodes because of the rapid urbanization and industrialization over the past decades. Here we analyzed the effect of emission controls implemented during the G-20 2016 Hangzhou summit on air quality. Emission controls included a forced closure of highly polluting industries, and limiting traffic and construction emissions in the cities and surroundings. Particles with aerodynamic diameter lower than 2.5 μm (PM_2.5) and ozone (O₃) were measured. We also simulated air quality using a forecast system consisting of the two-way coupled Weather Research and Forecast and Community Multi-scale Air Quality (WRF-CMAQ) model. Results show PM_2.5 and ozone levels in Hangzhou during the G-20 Summit were considerably lower than previous to the G-20 Summit. The predicted concentrations of ozone were reduced by 25.4%, whereas the predicted concentrations of PM_2.5 were reduced by 56%.     

Improved characterisation of inorganic components in airborne particulate matter

We set up a microanalytical procedure for non-volatile ions by ion chromatography (IC) and for elements by energy-dispersive X-ray fluorescence (ED-XRF) and inductively coupled plasma optical emission spectroscopy (ICP-OES). We analysed NO₃, SO₄, NH₄, Na, Mg, Ca, Fe, S, Zn, As, Cd, Cu, Mn, Ni, Pb, Sb, Se, Ti, and V. The use of complementary techniques yields reliable data for both trace and crustal elements, overcoming the analytical restrictions characteristic of the individual techniques. Some elements determined by two or by all three techniques can be used as data quality markers. The application of the procedure to a short PM_2.5 monitoring campaign is also described, aimed to the identification of fireworks tracers.     

Numerical simulations of the effect of building configurations and wind direction on fine particulate matters dispersion in a street canyon

To explore the effect of traffic emissions on air quality within street canyon, the wind flow and pollutant dispersion distribution in urban street canyons of different H/W, building gap and wind direction are studied and discussed by 3D computational fluid dynamics simulations. The largest PM_2.5 concentrations are 46.4, 37.5, 28.4 µg/m³ when x = ? 88, ? 19.3, ? 19.3 m in 1.5 m above the ground level and the ratio of H/W is 1:1, 1:2 and 2:1, respectively. The flow around the top of the building and clearance flow between the buildings in street canyon influence by different H/W, which affected the diffusion of fine particulate matters. The largest PM_2.5 concentrations are 88.1, 31.6 and 33.7 µg/m³ when x = 148.0, ? 92.3 and ? 186.7 m above the ground level of 1.5 m height and the building gap of 0, 20 and 40%, respectively. The air flows are cut by the clearance in the street canyons, and present the segmental characteristics. The largest PM_2.5 concentrations are 10.6, 11.2 and 16.0 µg/m³ when x = 165.3 m, x = 58.0 and 1.5 m above the ground level of 1.5 m height and wind direction of the parallel to the street, perpendicular to the street and southwest, respectively. Modelled PM_2.5 concentrations are basic agreement with measured PM_2.5 concentrations for southwest wind direction. These results can help analyze the difussion of PM_2.5 concentration in street canyons and urban planning.

     

Trace elements in particulate matter of ambient air at petroleum filling stations

Size segregated suspended particulate matter (PM_2.5 and PM_10-2.5) in air at four major petroleum-filling stations in Ile-Ife, Nigeria, were monitored using double staged “Gent” stacked samplers to assess variations in mass loads and elemental concentrations of 25 elements. Na, Mg, Al, Si, P, S, Cl, K, Ca, Ti, V, Cr, Mn, Fe, Ni, Cu, Zn, Br, Rb, Sr, Zr, Cs, Ta, W, and Pb were determined in both fractions by external ion beam proton-induced X-ray emission technique. Enrichment factors and pollution indices were calculated and results revealed that most elements were anthropogenic in both fractions with concentrations exceeding the World Health Organization guideline standards.     

Air pollution-oriented ecological risk assessment in Xiamen city,China

Urban energy consumption is one of the most important causes of air pollution. Air pollution-oriented ecological risk assessment is of great significance to the promotion of urban environmental protection. This paper focuses on ecological risk in Xiamen city caused by air pollutant discharge from urban energy consumption. The Long-range Energy Alternatives Planning model was used to establish two scenarios of energy consumption in Xiamen city, and based on different scenarios, we estimated urban energy consumption and discharge quantity of air pollutant (DQAP). A box model and an expert scoring method were used to calculate the air pollution burden (APB) of SO₂, NO₂, CO, PM₁₀ and PM_2.5 and to obtain the probabilities of different air pollution loads. An ecological risk assessment model was developed and utilized to predict Xiamen city’s ecological risks in 2020. The results showed that under an energy-saving scenario, the ecological risks for PM_2.5, SO₂ and NO₂ are high, whereas the ecological risks for CO and PM₁₀ are low. Under a baseline scenario, the ecological risks for PM_2.5, SO₂ and NO₂ are moderate, whereas the ecological risks for CO and PM₁₀ are low. In addition, the APB of SO₂, NO₂, CO, and PM_2.5, but not of PM₁₀, is predicted to rise. In the simulation, energy generation from coal is the main source of air pollution. Although the DQAP from automobiles is not high, it is predicted to rise year-on-year. In summary, the ecological risk due to pollution in Xiamen city is high, and the main pollutants are SO₂, NO₂ and PM_2.5.     

Acute associations between air pollution on premature rupture of membranes in Hefei,China

Numerous studies had focused on the association between air pollution and health outcomes in recent years. However, little evidence is available on associations between air pollutants and premature rupture of membranes (PROM). Therefore, we performed time-series analysis to evaluate the association between PROM and air pollution. The daily average concentrations of PM_2.5, SO₂ and NO₂ were 54.58 μg/m³, 13.06 μg/m³ and 46.09 μg/m³, respectively, and daily maximum 8-h average O₃ concentration was 95.67 μg/m³. The strongest effects of SO₂, NO₂ and O₃ were found in lag4, lag06 and lag09, and an increase of 10 μg/m³ in SO₂, NO₂ and O₃ was corresponding to increase in incidence of PROM of 8.74% (95% CI 2.12–15.79%), 3.09% (95% CI 0.64–5.59%) and 1.68% (95% CI 0.28–3.09%), respectively. There were no significant effects of PM_2.5 on PROM. Season-specific analyses found that the effects of PM_2.5, SO₂ and O₃ on PROM were more obvious in cold season, but the statistically significant effect of NO₂ was observed in warm season. We also found the modifying effects by maternal age on PROM, and we found that the effects of SO₂ and NO₂ on PROM were higher among younger mothers (<?35 years) than advanced age mothers (≥?35 years); however,?≥?35 years group were more vulnerable to O₃ than?<?35 years group. This study indicates that air pollution exposure is an important risk factor for PROM and we wish this study could provide evidence to local government to take rigid approaches to control emissions of air pollutants.

     

Health risk of aerosols and toxic metals from incense and joss paper burning

We report for the first time the distribution and hazard potential of aerosol and metals resulting from joss paper burning. Burning joss paper and incense is a traditional custom in many Oriental countries. Large amounts of air pollutants, including particles, polycyclic aromatic hydrocarbons, toxic metals and other gaseous pollutants, are released into the environment during the burning stage. Many investigations have reported on the emission of pollutants from the incense burning. However, no work has been reported until now on the analysis of the released pollutants apart from polycyclic aromatic hydrocarbons. In this study, a micro-orifice uniform-deposit impactor and inductively coupled plasma optical emission spectrometry were, respectively, used to collect aerosols and characterize the toxic metals from joss paper burning. We studied two types of particulate matter (PM): PM_2.5 that are particles with a diameter smaller than 2.5 μm and PM₁₀ that are particles with a diameter smaller than 10 μm. PM_2.5 are the most potentially toxic particles. Our results showed that PM_2.5 are the major component of the pollutants and that the PM_2.5 to PM₁₀ ratio ranged from 62 to 99%. The metals Na, Ca, Mg, Al and K were the main species in the aerosol and in the bottom ash.     

World air particulate matter: sources,distribution and health effects

Particulate matter (PM) is both a major driver of climate change and a source of toxicity for health. In the upper atmosphere, particulate matter modifies the earth radiation budget, cloud formation and acts as a reaction center for air pollutants. In the lower atmosphere, particulate matter changes atmospheric visibility and alters biogeochemical cycles and meteorology. Most critical effects are observed in ambient air, where particulate matter degrades human health. Here we review the sources, spatial and temporal variability, and toxicity of PM₁₀, the particulate matter having particle sizes 10 micrometers or less in diameter, in world regions. For that we analyzed information from the world wide web and databases from government organizations after the year 2000. Findings show that PM₁₀ is a major risk in both developed and developing countries. This risk is more severe in Asian countries compared to Europe and USA, where decreasing trends are recorded during the last two decades. Meteorological factors modify particulate matter variations at local and regional levels. PM_2.5/PM₁₀ ratio provides information of particulate matter sources under different environment conditions. Crustal matter, road traffic and combustion of fuels are major sources of particulate matter pollution. Health studies indicate that long-term exposure to particulate matter has multiple health effects in people from all age groups. Identification of possible sources and their control with regular epidemiological monitoring could decrease the impact of particulate matter pollution.     

The effect of pollution on crime: Evidence from data on particulate matter and ozone

We estimate the effect of short-term air pollution exposure (PM_2.5 and ozone) on several categories of crime, with a particular emphasis on aggressive behavior. To identify this relationship, we combine detailed daily data on crime, air pollution, and weather for an eight-year period across the United States. Our primary identification strategy employs extremely high dimensional fixed effects and we perform a series of robustness checks to address confounding variation between temperature and air pollution. We find a robust positive effect of increased air pollution on violent crimes, and specifically assaults, but no relationship between increases in air pollution and property crimes. The effects are present in and out of the home, at levels well below Ambient Air Pollution Standards, and PM_2.5 effects are strongest at lower temperatures. The results suggest that a 10% reduction in daily PM_2.5 and ozone could save $1.4 billion in crime costs per year, a previously overlooked cost associated with pollution.     

Estimating the effects of meteorology on PM2.5 reduction during the 2008 Summer Olympic Games in Beijing, China

Particulate pollution was a critical challenge to the promise of good air quality during the 2008 Beijing Olympic Games, which took place from August 8th to 24th. To ensure good air quality for the Games, several temporary emission control measures were implemented in Beijing and surrounding areas. Ambient particulate matter concentration decreased significantly during the Olympic period; however, it is difficult to distinguish the effectiveness of those control measures since meteorology also affects ambient PM_2.5 concentration. In this work, a multiple linear regression model based on continuous field monitoring at a roadside site was conducted to evaluate the effects of meteorology and emission control measures on the reduction of PM_2.5 during the 2008 Olympic Games. The hourly data set was divided into two time periods, the no control period, June 22nd to July 4th, and the control period, July 28th to August 21st. The response variable was PM_2.5 and the meteorology covariates used in the model were hourly temperature, dew point temperature, wind speed and precipitation. Wind direction was not a significant predictor of PM_2.5 levels in either the control or the no control period. Using the meteorologically-based regression coefficients from the two time periods, meteorology was found to contribute to at least a 16% reduction in PM_2.5 levels in the roadside microenvironment; while the pollution control measures contributed to at least a 43% reduction in PM_2.5 levels.     

Indoor and outdoor air pollution and lung cancer in New Hampshire and Vermont

Indoor and outdoor air pollution is known to contribute to increased lung cancer incidence. This study is the first to address the contribution of home heating fuel and geographical course particulate matter (PM₁₀) concentrations to lung cancer rates in New Hampshire, USA. First, Pearson correlation analysis and geographically weighted regression were used to investigate spatial relationships between outdoor PM₁₀ and lung cancer rates. While the aforementioned analyses did not indicate a significant contribution of PM₁₀ to lung cancer in the state, there was a trend towards a significant association in the northern and southwestern regions of the state. Second, case-control data were used to estimate the contributions of indoor pollution and secondhand smoke to the risk of lung cancer with adjustment for confounders. Increased risk was found among those who used wood or coal to heat their homes for more than 10 winters before the age of 18, with a significant increase in risk per winter. Resulting data suggest that further investigation of the relationship between heating-related air pollution levels and lung cancer risk is needed.     

Ambient air particulates-bound metallic elements sources identifications during winter and summer at a Science Park

The ambient air particulates pollutants of total suspended particulates (TSP) and PM_2.5 were collected by using PS-1 and Wilbur PM_2.5 sampler, simultaneously during the year of 2015–2017 at a photoelectric factory in Science Park of central Taiwan. And those of the ambient air atmospheric metallic elements (Cr, Mn, Ni, Cu, Zn, Pb) concentrations which attached on the TSP and PM_2.5 were analyzed by using inductively coupled plasma optical emission spectrometer. In addition, identifying anthropogenic and natural pollutants sources were conducted by using the enrichment factor (EF) and principal component analysis (PCA) methods. The results indicated that the average TSP and PM_2.5 concentrations were ranked highest in winter season, while summer season was ranked lowest during the year of 2015–2016. In addition, the average highest metallic element concentrations were occurred in winter season for both TSP and PM_2.5 during the year of 2015–2016, while the average lowest metallic elements concentrations in TSP and PM_2.5 were also occurred in winter season during the year of 2016–2017. Moreover, the EF analysis results showed that the metallic element Zn came from anthropogenic emission source. As for metallic element Mn, the results showed that metallic element Mn was mainly attributed to natural emission in this study. Finally, the PCA results showed that metallic elements Cr, Zn and Pb were the dominant emissions metallic elements in this study. As for PM_2.5, the results showed that the metallic elements Cr, Cu and Pb were the dominant emissions metallic elements at this HPB sampling site.

     

Analysis and prediction of the influence of energy utilization on air quality in Beijing

This work evaluates the influence of energy consumption on the future air quality in Beijing, using 2000 as the base year and 2008 as the target year. It establishes the emission inventory of primary PM₁₀, SO₂ and NO_x related to energy utilization in eight areas of Beijing. The air quality model was adopted to simulate the temporal and spatial distribution of each pollutant concentration in the eight urban areas. Their emission, concentration distribution, and sectoral share responsibility rate were analyzed, and air quality in 2008 was predicted. The industrial sector contributed above 40% of primary PM₁₀ and SO₂ resulting from energy consumption, while vehicles accounted for about 65% of NO_x. According to the current policy and development trend, air quality in the eight urban areas could become better in 2008 when the average concentrations of primary PM₁₀, SO₂ and NO₂ related to energy utilization at each monitored site are predicted to be about 25, 50 and 51 μg/m³, respectively.     

Estimating the effect of air pollution on road safety using atmospheric temperature inversions

Does air quality influence road safety? We estimate the effect of increased air pollution on the number of road traffic accidents in the United Kingdom between 2009 and 2014. To address concerns of spurious correlation we exploit atmospheric temperature inversions as a source of plausibly exogenous variation in daily air pollution levels. We find an increase of 0.3–0.6% in the number of vehicles involved in accidents per day for each additional 1 μg/m³ of PM_2.5. The finding suggests that less safe roads may present a large and previously overlooked cost of air pollution. The results are robust to a number of specifications and across various sub-samples.     

Impact of energy structure adjustment on air quality: a case study in Beijing, China

Energy consumption is a major cause of air pollution in Beijing, and the adjustment of the energy structure is of strategic importance to the reduction of carbon intensity and the improvement of air quality. In this paper, we explored the future trend of energy structure adjustment in Beijing till 2020, designed five energy scenarios focusing on the fuel substitution in power plants and heating sectors, established emission inventories, and utilized the Mesoscale Modeling System Generation 5 (MM5) and the Models-3/Community Multiscale Air Quality Model (CMAQ) to evaluate the impact of these measures on air quality. By implementing this systematic energy structure adjustment, the emissions of PM₁₀, PM_2.5, SO₂, NO _x , and non-methane volatile organic compounds (NMVOCs) will decrease distinctly by 34.0%, 53.2%, 78.3%, 47.0%, and 30.6% respectively in the most coalintensive scenario of 2020 compared with 2005. Correspondingly, MM5-Models-3/CMAQ simulations indicate significant reduction in the concentrations of major pollutants, implying that energy structure adjustment can play an important role in improving Beijing??s air quality. By fuel substitution for power plants and heating boilers, PM₁₀, PM_2.5, SO₂, NO _x , and NMVOCs will be reduced further, but slightly by 1.7%, 4.5%, 11.4%, 13.5%, and 8.8% respectively in the least coal-intensive scenario. The air quality impacts of different scenarios in 2020 resemble each other, indicating that the potential of air quality improvement due to structure adjustment in power plants and heating sectors is limited. However, the CO₂ emission is 10.0% lower in the least coal-intensive scenario than in the most coal-intensive one, contributing to Beijing??s ambition to build a low carbon city. Except for energy structure adjustment, it is necessary to take further measures to ensure the attainment of air quality standards.     

Airborne fine particulate matter (PM2.5) at industrial,high- and low-density residential sites in a Nigerian megacity

Abstract

Airborne particulate matter PM_2.5 was collected in an industrial, a low-density, and a high-density residential area of Lagos from December 2010 to November 2011, and elemental composition was determined by proton-induced X-ray emission. Across the months, mass concentrations ranged from 13 to 237?µg?m^?3, exceeding the World Health Organization guideline value of 10?µg?m^?3. Data on 24 elements were obtained, with maximum values during Harmattan season months; source identification and apportionment studies by positive matrix factorization suggested that petroleum oil combustion (70%) was the major source of PM_2.5 and could pose a great hazard to Lagos receptors.     

Locating major PM10 source areas in Seoul using multivariate receptor modeling

Identifying the major sources contributing to air pollution is a problem of fundamental importance in developing effective air quality management plans. Multivariate receptor modeling aims to achieve this goal by unfolding the air pollution data into components associated with different sources based on factor analysis models. We analyze the PM₁₀ data obtained from 17 monitoring sites in Seoul to locate the major source regions using multivariate receptor modeling. The model uncertainty caused by the unknown number of sources and identifiability conditions is assessed by posterior probability of each model. The estimated source spatial profiles seem to be consistent with our prior expectation about the PM₁₀ sources in Seoul.     

Evaluation of the levels and sources of trace elements in urban particulate matter

An assessment of air quality of Belgrade, Serbia, was performed by determining the trace element content in airborne daily PM₁₀ and PM_2.5 samples collected from a central urban area. The ambient concentrations of Zn were the highest in PM_2.5 (1,998.0 ng m⁻³). Multivariate receptor modelling (principal component analysis and cluster analysis) has been applied to determine the contribution of different sources of specific metallic components in airborne particles. The obtained results showed that vehicle traffic and fossil fuel combustion in stationary objects were the main sources of trace metals in Belgrade urban aerosols.     

The effect of outdoor air pollutants and greenness on allergic rhinitis incidence rates: a cross-sectional study in Seoul,Korea

Air pollution poses a serious threat to human health in Asia. This study analyzes the association of air pollutants and greenness with incidence rates of allergic rhinitis in Seoul at the administrative district level to gain insight into district-level urban policies to improve public health. A spatial regression model is constructed to investigate the correlation between allergic rhinitis incidence rates and five air pollutants measured at 128 air pollution monitoring stations around Seoul: sulfur dioxide (SO₂), particulate matter less than 10 μm (PM₁₀), ozone (O₃), nitrogen dioxide (NO₂), and carbon monoxide (CO). The allergic rhinitis incidence data are derived from the National Health Insurance Service’s database that includes the number of allergic rhinitis-related clinic visits by the patients over 20 years of age and living in Seoul. A kriging geostatistical interpolation was used to estimate average air pollution level of 423 administrative districts. To assess pollen concentrations that can affect allergic rhinitis, the average normalized difference vegetation index (NDVI) is measured based on the urban greenness. The model, controlling for built environment and socio-economic attributes, identifies the possibility of a weak association between allergic rhinitis incidence rates and carbon monoxide levels. The NDVI value is negatively correlated with allergic rhinitis incidence rates, implying a complicated aspect in relation to the effect of urban greenness.