Long-Term Assessment of Air Quality and Identification of Aerosol Sources at Setúbal, Portugal

Understanding air pollution in urban areas is crucial to identify mitigation actions that may improve air quality and, consequently, minimize human exposure to air pollutants and their impact. This study aimed to assess the temporal evolution of the air quality in the city of Setúbal (Portugal) during a time period of 10 years (2003–2012), by evaluating seasonal trends of air pollutants (PM10, PM2.5, O3, NO, NO2 and NOx) measured in nine monitoring stations. In order to identify emission sources of particulate matter, PM2.5 and PM2.5–10 were characterized in two different areas (urban traffic and industrial) in winter and summer and, afterwards, source apportionment was performed by means of Positive Matrix Factorization. Overall, the air quality has been improving over the years with a decreasing trend of air pollutant concentration, with the exception of O3. Despite this improvement, levels of PM10, O3 and nitrogen oxides still do not fully comply with the requirements of European legislation, as well as with the guideline values of the World Health Organization (WHO). The main anthropogenic sources contributing to local PM levels were traffic, industry and wood burning, which should be addressed by specific mitigation measures in order to minimize their impact on the local air quality.

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Analysis of the Main Anthropogenic Sources’ Contribution to Pollutant Emissions in the Lazio Region, Italy

Applied Sciences ◽

10.3390/app11177936 ◽

2021 ◽

Vol 11 (17) ◽

pp. 7936

Author(s):

Gabriele Battista ◽

Emanuele de Lieto Vollaro ◽

Roberto de Lieto Vollaro

Keyword(s):

Air Quality ◽

Urban Areas ◽

Air Pollutants ◽

Global Climate ◽

Atmospheric Stability ◽

Air Pollutant ◽

Urban Traffic ◽

Pollutant Emissions ◽

Anthropogenic Sources ◽

Lazio Region

Most cities worldwide suffer from serious air-quality problems, which have received increasing attention in the past decade. The most probable reason for the air-quality problems is the urban population growth, combined with a change in land use due to increasing urban areas. The emission of air pollutants is caused by different anthropogenic processes which can be categorized into the sources of urban traffic, industry, and domestic heating. Dispersion and dilution of air pollutants are strongly influenced by meteorological conditions, especially by wind direction, wind speed, turbulence, and atmospheric stability. With an increasing number of people living in cities, there is the need to examine the correlation between air pollution, local climate, and the effects these changes have on global climate. New interdisciplinary research studies are needed to increase our understanding of the interactions among these aspects. The aim is to analyze the pollutant condition in Rome and the other provinces of the Lazio region with qualitative and quantitative analysis, in order to understand which are the main pollutant sources and what is the correlation of habits of the population on air pollutant emissions.

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Effect of Green Space Environment on Air Pollutants PM2.5, PM10, CO, O3, and Incidence and Mortality of SARS-CoV-2 in Highly Green and Less-Green Countries

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph182413151 ◽

2021 ◽

Vol 18 (24) ◽

pp. 13151

Author(s):

Sultan Ayoub Meo ◽

Faris Jamal Almutairi ◽

Abdulelah Adnan Abukhalaf ◽

Adnan Mahmood Usmani

Keyword(s):

Air Quality ◽

Urban Areas ◽

Air Pollutants ◽

Green Space ◽

Space Environment ◽

World Health ◽

Mean Values ◽

Environmental Performance Index ◽

Incidence And Mortality ◽

Health Organization

Worldwide, over half of the global population is living in urban areas. The metropolitan areas are highly populated and environmentally non-green regions on the planet. In green space regions, plants, grass, and green vegetation prevent soil erosion, absorb air pollutants, provide fresh and clean air, and minimize the burden of diseases. Presently, the entire world is facing a turmoil situation due to the COVID-19 pandemic. This study investigates the effect of the green space environment on air pollutants particulate matter PM2.5, PM10, carbon monoxide (CO), ozone (O3), incidence and mortality of Severe Acute Respiratory Syndrome Coronavirus (SARS-CoV-2) in environmentally highly green and less-green countries. We randomly selected 17 countries based on the Environmental Performance Index (EPI) data. The 60% of the EPI score is based on seven categories: “biodiversity and habitat, ecosystem, fisheries, climate change, pollution emissions, agriculture, and water resources”. However, 40% of the score is based on four categories: “air quality, sanitation and drinking water, heavy metals, and waste management”. The air pollutants and SARS-CoV-2 cases and deaths were recorded from 25 January 2020, to 11 July 2021. The air pollutants “PM2.5, PM10, CO, and O3” were recorded from the metrological websites, Air Quality Index-AQI, 2021. The COVID-19 daily cases and deaths were obtained from the World Health Organization. The result reveals that air pollutants mean values for PM2.5 110.73 ± 1.09 vs. 31.35 ± 0.29; PM10 80.43 ± 1.11 vs. 17.78 ± 0.15; CO 7.92 ± 0.14 vs. 2.35 ± 0.03 were significantly decreased (p < 0.0001) in environmentally highly green space countries compared to less-green countries. Moreover, SARS-CoV-2 cases 15,713.61 ± 702.42 vs. 3445.59 ± 108.09; and deaths 297.56 ± 11.27 vs. 72.54 ± 2.61 were also significantly decreased in highly green countries compared to less-green countries. The green environment positively impacts human wellbeing. The policymakers must implement policies to keep the living areas, surroundings, towns, and cities clean and green to minimize air pollution and combat the present pandemic of COVID-19.

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Historical and future changes in air pollutants from CMIP6 models

10.5194/acp-2019-1211 ◽

2020 ◽

Cited By ~ 4

Author(s):

Steven T. Turnock ◽

Robert J. Allen ◽

Martin Andrews ◽

Susanne E. Bauer ◽

Louisa Emmons ◽

...

Keyword(s):

Air Quality ◽

Human Health ◽

Air Pollutants ◽

Air Pollutant ◽

Mitigation Measures ◽

Climate Mitigation ◽

Historical Period ◽

Earth System ◽

Natural Emission ◽

Surface O3

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.

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Assessment of Air Pollution Aggravation during Straw Burning in Hubei, Central China

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph16081446 ◽

2019 ◽

Vol 16 (8) ◽

pp. 1446 ◽

Cited By ~ 1

Author(s):

Bo Zhu ◽

Yu Zhang ◽

Nan Chen ◽

Jihong Quan

Keyword(s):

Air Quality ◽

Air Pollutants ◽

Central China ◽

World Health ◽

Pollution Level ◽

Key Factor ◽

Regional Air Quality ◽

Straw Burning ◽

Health Organization ◽

Hourly Distribution

Crop straw burning frequently occurs in Central China, where agriculture is highly productive. We carried out a two-month observation on straw burning in Hubei Province from September 1 to October 31, 2015 to track the variations of air pollutants and comprehensively quantify their influence on regional air quality. Results showed that the concentration of suspended particles (particles smaller than 2.5 or 10 µm, i.e., PM2.5/PM10) and gas pollutants including ozone (O3), sulfur dioxide (SO2), nitrogen dioxide (NO2), and carbon monoxide (CO) was significantly enhanced with the increasing number of fire spots. The average daily concentrations of PM10, PM2.5 and O3 during the intensive burning period (from October 12 to 25) exceeded the daily limits published by the World Health Organization (WHO) by 101.8, 72.7 and 59.1 μg/m3, respectively. In the hourly distribution of pollutant concentration, PM10, PM2.5, O3, SO2, NO2 and CO were 63.49%, 46.29%, 65.56%, 64.40%, 48.57% and 13.49% higher during burning periods than during non-burning periods. Statistical results based on the air quality index (AQI) indicated that biomass burning was the key factor for the deterioration of local air quality, with a contribution ratio exceeding 41%. Additionally, the pollutants were more spatially homogeneous during the burning period than during the non-burning period. Straw burning not only worsened the local air quality but also raised the pollution level of surrounding regions due to the transport of air mass.

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Assessing the Immediate Effect of Covid-19 Lockdown on Air Quality: A Case Study of Delhi, India

Journal of Environmental Geography ◽

10.2478/jengeo-2020-0009 ◽

2020 ◽

Vol 13 (3-4) ◽

pp. 27-33

Author(s):

Ankit Sikarwar ◽

Ritu Rani

Keyword(s):

Air Pollution ◽

Air Quality ◽

Spatial Interpolation ◽

World Health ◽

Guideline Values ◽

Distance Weighting ◽

Health Organization ◽

The City ◽

Inverse Distance

Abstract In India, a nationwide lockdown due to COVID-19 has been implemented on 25 March 2020. The lockdown restrictions on more than 1.3 billion people have brought exceptional changes in the air quality all over the country. This study aims to analyze the levels of three major pollutants: particulate matter sized 2.5 μm (PM2.5) and 10 μm (PM10), and nitrogen dioxide (NO2) before and during the lockdown in Delhi, one of the world’s most polluted cities. The data for PM2.5, PM10, and NO2 concentrations are derived from 38 ground stations dispersed within the city. The spatial interpolation maps of pollutants for two times are generated using Inverse Distance Weighting (IDW) model. The results indicate decreasing levels of PM2.5, PM10, and NO2 concentrations in the city by 93%, 83%, and 70% from 25 February 2020 to 21 April 2020 respectively. It is found that one month before the lockdown the levels of air pollution in Delhi were critical and much higher than the guideline values set by the World Health Organization. The levels of air pollution became historically low after the lockdown. Considering the critically degraded air quality for decades and higher morbidity and mortality rate due to unhealthy air in Delhi, the improvement in air quality due to lockdown may result as a boon for the better health of the city’s population.

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Air Inequality: Global Divergence in Urban Fine Particulate Matter Trends

10.26434/chemrxiv.14671908 ◽

2021 ◽

Author(s):

Joshua Apte ◽

Sarah Seraj ◽

Sarah Chambliss ◽

Melanie Hammer ◽

Veronica Southerland ◽

...

Keyword(s):

Air Quality ◽

Urban Areas ◽

Urban Population ◽

Fine Particulate Matter ◽

Ground Level ◽

World Health ◽

Global Environmental ◽

Key Policy ◽

Health Organization

Fine particle air pollution (PM2.5) is the largest global environmental risk factor for ill-health and is implicated in >7% of all human deaths. Improved air quality is a key policy goal for cities, yet in-situ PM2.5 measurements are missing for >50% of the world’s urban population. Here, we apply satellite remote sensing to develop a 21-year time series of ground-level PM2.5 concentrations for the 4231 urban areas with populations >100,000 (2.9 billion people) from 1998 -2018. Globally, we find the most polluted cities are generally small (<1 million population) and lack PM2.5 monitors. Since 1998, we observe a growing divide in urban air quality between cities in lower and higher-income regions, with the PM2.5 disparity increasing by >50% (from 25 to 39 µg m-3) between the highest- and lowest income quartiles of world cities. Within Asia, a sharp divergence is underway, with sustained PM2.5 increases in South Asian cities (+48%) contrasted against dramatic improvements in Chinese cities (-40% since 2011). While 85% of the world’s urban population experiences PM2.5 higher than World Health Organization guidelines, urban PM2.5 concentrations are tightly linked to regional conditions, suggesting that city-level efforts alone may be insufficient to address this major health threat.

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Correlation Analysis between Land Use/Cover Change and Air Pollutants—A Case Study in Wuyishan City

Energies ◽

10.3390/en12132545 ◽

2019 ◽

Vol 12 (13) ◽

pp. 2545 ◽

Cited By ~ 2

Author(s):

Zhipeng Zhu ◽

Guangyu Wang ◽

Jianwen Dong

Keyword(s):

Land Use ◽

Air Quality ◽

Black Carbon ◽

Urban Areas ◽

Air Pollutants ◽

Pearson Correlation ◽

Water Area ◽

Air Pollutant ◽

Cultivated Land ◽

Bare Land

Land use changes have significantly altered the natural environment in which humans live. In urban areas, diminishing air quality poses a large threat to human health. In order to investigate the relationship between land use/cover change (LUCC) and air pollutants of Wuyishan City between 2014–2017, an integrated approach was used by combining remote sensing techniques with a landscape ecology methods. Annual, seasonal, and weekly mean values of air pollutant (SO2, NO2, CO, PM10, O3, PM2.5, black carbon) concentration and atmospheric visibility were calculated to develop a Pearson correlation between LUCC and air pollutants concentration. Results showed an increase in forested areas (1.79%) and water areas (15.89%), with a simultaneous reduction in cultivated land (6.47%), bare land (72.61%), and built-up land (16.03%) from 2014 to 2017. The transition matrix of land use types revealed that (i) forest expansion took place mainly at the expense of cultivated land (13.94%) and bare land (27.48%); and (ii) water area expansion took place mainly at the expense of cultivated land (1.29%) and forests (0.21%). In 2017, the proportion of days with AQI level I (94.52%) was higher than that in 2014 (88.77%). Additionally, the annual average visibility in 2017 (37.42 km) was higher than 2014 (27.46 km). The concentration of SO2, CO, O3, and black carbon was positively correlated with the cultivated land. The concentration of SO2, CO, and black carbon negatively correlated with the increase of forests. PM10, and PM2.5 is negatively correlated with the water area. Visibility was found to be positively correlated with forested area, and negatively correlated with cultivated land. The findings from this study represent a valuable gain in understanding of policies aimed at improving, safeguarding, and monitoring air quality. These results can be used to inform land-use planning decisions in a comprehensive way and could be a valuable tool for LUCC rational management strategies.

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Novel index to comprehensively evaluate air cleanliness: the Clean aIr Index (CII)

Geoscience Communication ◽

10.5194/gc-3-233-2020 ◽

2020 ◽

Vol 3 (2) ◽

pp. 233-247

Author(s):

Tomohiro O. Sato ◽

Takeshi Kuroda ◽

Yasuko Kasai

Keyword(s):

Air Quality ◽

Air Pollutants ◽

City Planning ◽

Air Pollutant ◽

World Health ◽

Observation System ◽

In Situ Observation ◽

Validation Data ◽

Air Index ◽

Clean Air

Abstract. Air quality on our planet has been changing in particular since the industrial revolution (1750s) because of anthropogenic emissions. It is becoming increasingly important to realize air cleanliness, since clean air is as valuable a resource as clean water. A global standard for quantifying the level of air cleanliness is swiftly required, and we defined a novel concept, namely the Clean aIr Index (CII). The CII is a simple index defined by the normalization of the amount of a set of individual air pollutants. A CII value of 1 indicates completely clean air (no air pollutants), and 0 indicates the presence of air pollutants that meet the numerical environmental criteria for the normalization. In this time, the air pollutants used in the CII were taken from the Air Quality Guidelines (AQG) set by the World Health Organization (WHO), namely O3, particulate matters, NO2, and SO2. We chose Japan as a study area to evaluate CII because of the following reasons: (i) accurate validation data, as the in situ observation sites of the Atmospheric Environmental Regional Observation System (AEROS) provide highly accurate values of air pollutant amounts, and (ii) fixed numerical criteria from the Japanese Environmental Quality Standards (JEQS) as directed by the Ministry of the Environment (MOE) of Japan. We quantified air cleanliness in terms of the CII for the all 1896 municipalities in Japan and used data from Seoul and Beijing to evaluate Japanese air cleanliness. The amount of each air pollutant was calculated using a model that combined the Weather Research and Forecasting (WRF) and Community Multiscale Air Quality (CMAQ) models for 1 April 2014 to 31 March 2017. The CII values calculated by the WRF–CMAQ model and the AEROS measurements showed good agreement. The mean of the correlation coefficient for the CII values of 498 municipalities where the AEROS measurements operated was 0.66±0.05, which was higher than that of the Air Quality Index (AQI) of 0.57±0.06. The CII values averaged for the study period were 0.67, 0.52, and 0.24 in Tokyo, Seoul, and Beijing, respectively; thus, the air in Tokyo was 1.5 and 2.3 times cleaner, i.e., lower amounts of air pollutants, than the air in Seoul and Beijing, respectively. The average CII value for the all Japanese municipalities was 0.72 over the study period. The extremely clean air, CII ≈0.90, occurred in the southern remote islands of Tokyo and to the west of the Pacific coast, i.e., Kochi, Mie, and Wakayama prefectures during summer, with the transport of clean air from the ocean. We presented the top 100 clean air cities in Japan as one example of an application of CII in society. We confirmed that the CII enabled the quantitative evaluation of air cleanliness. The CII can be useful and valuable in various scenarios such as encouraging sightseeing and migration, investment and insurance business, and city planning. The CII is a simple and fair index that can be applied to all nations.

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Implications of portable gasoline electricity generators on residential indoor air quality

Journal of Air Pollution and Health ◽

10.18502/japh.v5i3.5392 ◽

2021 ◽

Author(s):

Adinife Patrick Azodo ◽

Idama Omokaro ◽

Tochukwu Canice Mezue

Keyword(s):

Air Quality ◽

Indoor Air Quality ◽

Indoor Air ◽

Measurement Techniques ◽

Quality Parameters ◽

Air Pollutant ◽

World Health ◽

Mean Values ◽

Ogun State ◽

Health Organization

Introduction: Toxic gases emitted from electricity generating plants used for energy production process diffuse in the environment thereby causing environmental air pollution. The effect of the installation and usage of portable gasoline electricity generating plants at the balcony of different households on the indoor air quality was assessed in this study. Materials and methods: The data collected were the air quality chemical composition variables which include carbon-dioxide, formaldehyde, total volatile organic compounds, coarse (PM10), and fine (PM2.5) particulate matters at the indoor of the households in Abeokuta metropolis, Ogun state, Nigeria. Physical measurement techniques used for the data collection was through the instrumentation design of two air quality testers, models WP6910 and ZN-202S. The indoor air quality assessment followed the generator nighttime usage routine between the hours of 6:30 – 10:00 pm at a measurement height of 1.3 m and the center in the living rooms of the residences assessed. Results: The analysis of the data obtained showed that the mean values for each of the air quality parameters obtained during generator usages were significantly higher when compared to the indoor air quality parameters before generator usages at p<0.05. The air pollutant levels before and during generator usages were within the established safe standard air quality limit by the world health organization. Conclusion: However, for the installation of a portable electricity generator at the residents’ balcony, it is recommended that the generators should be adapted with an emission reduction device for the exhaust composition amelioration to avoid possible accumulation effect over time.

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