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

Atmosphere ◽  
2020 ◽  
Vol 11 (3) ◽  
pp. 239 ◽  
Author(s):  
Massimo Stafoggia ◽  
Christer Johansson ◽  
Paul Glantz ◽  
Matteo Renzi ◽  
Alexandra Shtein ◽  
...  
Keyword(s):  
Air Pollution ◽  
Particulate Matter ◽  
Random Forest ◽  
Nitrogen Dioxide ◽  
Spatial Resolution ◽  
Rural Areas ◽  
Temporal Distribution ◽  
Air Pollutant ◽  
Monitoring Networks ◽  
Pollution Effects

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.

scholarly journals Time Series Analysis of Climate and Air Pollution Factors Associated with Atmospheric Nitrogen Dioxide Concentration in Japan

2020 ◽  
Vol 17 (24) ◽  
pp. 9507
Author(s):  
Takeshi Miyama ◽  
Hiroshi Matsui ◽  
Kenichi Azuma ◽  
Chika Minejima ◽  
Yasuyuki Itano ◽  
...  
Keyword(s):  
Air Pollution ◽  
Time Series ◽  
Relative Humidity ◽  
Time Series Analysis ◽  
Nitrogen Dioxide ◽  
Rural Areas ◽  
Air Pollutant ◽  
Climate Conditions ◽  
Series Analysis ◽  
Urban Rural

Nitrogen dioxide (NO2) is an air pollutant discharged from combustion of human activities. Nitrous acid (HONO), measured as NO2, is thought to impact respiratory function more than NO2. HONO and NO2 have an equilibrium relationship, and their reaction is affected by climate conditions. This study was conducted to discuss the extent of HONO contained in NO2, depending on the level of urbanization. Whether climate conditions that promote HONO production enhanced the level of NO2 measured was investigated using time series analysis. Climate and outdoor air pollution data measured in April 2009–March 2017 in urban (Tokyo, Osaka, and Aichi) and rural (Yamanashi) areas in Japan were used for the analysis. Air temperature had a trend of negative associations with NO2, which might indicate the decomposition of HONO in the equilibrium between HONO and NO2. The associations of relative humidity with NO2 did not have consistent trends by prefecture: humidity only in Yamanashi was positively associated with NO2. In high relative humidity conditions, the equilibrium goes towards HONO production, which was observed in Yamanashi, suggesting the proportion of HONO in NO2 might be low/high in urban/rural areas.

Vicious Cycle of Economic Growth, Pm2.5 and COVID-19 Case of G7 Countries

2020 ◽  
Author(s):  
Rıdvan Karacan
Keyword(s):  
Economic Growth ◽  
Air Pollution ◽  
Particulate Matter ◽  
Fossil Fuels ◽  
Fine Particulate Matter ◽  
Panel Cointegration ◽  
Air Pollutant ◽  
Population Exposure ◽  
Causality Analysis ◽  
G7 Countries

<p>Today, production is carried out depending on fossil fuels. Fossil fuels pollute the air as they contain high levels of carbon. Many studies have been carried out on the economic costs of air pollution. However, in the present study, unlike the former ones, economic growth's relationship with the COVID-19 virus in addition to air pollution was examined. The COVID-19 virus, which was initially reported in Wuhan, China in December 2019 and affected the whole world, has caused many cases and deaths. Researchers have been going on studying how the virus is transmitted. Some of these studies suggest that the number of virus-related cases increases in regions with a high level of air pollution. Based on this fact, it is thought that air pollution will increase the number of COVID-19 cases in G7 Countries where industrial production is widespread. Therefore, the negative aspects of economic growth, which currently depends on fossil fuels, is tried to be revealed. The research was carried out for the period between 2000-2019. Panel cointegration test and panel causality analysis were used for the empirical analysis. Particulate matter known as PM2.5[1] was used as an indicator of air pollution. Consequently, a positive long-term relationship has been identified between PM2.5 and economic growth. This relationship also affects the number of COVID-19 cases.</p><p><br></p><p><br></p><p>[1] "Fine particulate matter (PM2.5) is an air pollutant that poses the greatest risk to health globally, affecting more people than any other pollutant (WHO, 2018). Chronic exposure to PM2.5 considerably increases the risk of respiratory and cardiovascular diseases in particular (WHO, 2018). For these reasons, population exposure to (outdoor or ambient) PM2.5 has been identified as an OECD Green Growth headline indicator" (OECD.Stat).</p>

scholarly journals Quantifying Air Pollutant Variations during COVID-19 Lockdown in a Capital City in Northwest China

Atmosphere ◽  
2021 ◽  
Vol 12 (6) ◽  
pp. 788
Author(s):  
Rong Feng ◽  
Hongmei Xu ◽  
Zexuan Wang ◽  
Yunxuan Gu ◽  
Zhe Liu ◽  
...  
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Rural Areas ◽  
Vehicle Emissions ◽  
Motor Vehicle ◽  
Northwest China ◽  
Air Pollutant ◽  
Capital City ◽  
Air Pollution Control ◽  
Motor Vehicle Emissions

In the context of the outbreak of coronavirus disease 2019 (COVID-19), strict lockdown policies were implemented to control nonessential human activities in Xi’an, northwest China, which greatly limited the spread of the pandemic and affected air quality. Compared with pre-lockdown, the air quality index and concentrations of PM2.5, PM10, SO2, and CO during the lockdown reduced, but the reductions were not very significant. NO2 levels exhibited the largest decrease (52%) during lockdown, owing to the remarkable decreased motor vehicle emissions. The highest K+ and lowest Ca2+ concentrations in PM2.5 samples could be attributed to the increase in household biomass fuel consumption in suburbs and rural areas around Xi’an and the decrease in human physical activities in Xi’an (e.g., human travel, vehicle emissions, construction activities), respectively, during the lockdown period. Secondary chemical reactions in the atmosphere increased in the lockdown period, as evidenced by the increased O3 level (increased by 160%) and OC/EC ratios in PM2.5 (increased by 26%), compared with pre-lockdown levels. The results, based on a natural experiment in this study, can be used as a reference for studying the formation and source of air pollution in Xi’an and provide evidence for establishing future long-term air pollution control policies.

scholarly journals Assessment of PM10 in Aurangabad City of Central India

2016 ◽  
Vol 5 (2) ◽  
pp. 61-74 ◽  
Author(s):  
Geetanjali Kaushik ◽  
Arvind Chel ◽  
Sangeeta Shinde ◽  
Ashish Gadekar
Keyword(s):  
Air Pollution ◽  
Particulate Matter ◽  
Fine Particulate Matter ◽  
Tall Buildings ◽  
Central India ◽  
Air Pollutant ◽  
Traffic Density ◽  
High Pollution ◽  
High Concentrations ◽  
The City

Almost 670 million people comprising 54.5% of our population reside in regions that do not meet the Indian NAAQS for fine particulate matter. Numerous studies have revealed a consistent correlation for particulate matter concentration with health than any other air pollutant. Aurangabad city a rapidly growing city with population of 1.5 million is home to five major industrial areas, the city is also known for its historical monuments which might also be adversely affected from air pollution. Therefore, this research aims at estimating PM10 concentrations at several locations across Aurangabad. The concentration of PM10 was highest at the Railway Station followed by Waluj (an industrial zone) and City chowk is the centre of the city which has high population, tall buildings, few open spaces which causes high congestion and does not allow the particulates to disperse. Other locations with high concentrations of PM are Mill corner, Harsul T-point, Kranti Chowk, Seven Hill, TV centre and Beed Bye pass. All these locations have narrow roads, high traffic density, poor road condition with pot holes and few crossing points which cause congestion and vehicle idling which are responsible for high pollution. Therefore, it is evident that air pollution is a serious issue in the city which may be further aggravated if it is not brought under control. Hence, strategies have to be adopted for combating the menace of air pollution.INTERNATIONAL JOURNAL OF ENVIRONMENTVolume-5, Issue-2, March-May 2016, Page :61-74

scholarly journals HTAP_v2.2: a mosaic of regional and global emission grid maps for 2008 and 2010 to study hemispheric transport of air pollution

2015 ◽  
Vol 15 (19) ◽  
pp. 11411-11432 ◽  
Author(s):  
G. Janssens-Maenhout ◽  
M. Crippa ◽  
D. Guizzardi ◽  
F. Dentener ◽  
M. Muntean ◽  
...  
Keyword(s):  
Air Pollution ◽  
Particulate Matter ◽  
Low Income ◽  
Regional Scale ◽  
Global Scale ◽  
Air Pollutant ◽  
Pollutant Emissions ◽  
Pollution Transport ◽  
Data Set ◽  
Per Capita

Abstract. The mandate of the Task Force Hemispheric Transport of Air Pollution (TF HTAP) under the Convention on Long-Range Transboundary Air Pollution (CLRTAP) is to improve the scientific understanding of the intercontinental air pollution transport, to quantify impacts on human health, vegetation and climate, to identify emission mitigation options across the regions of the Northern Hemisphere, and to guide future policies on these aspects. The harmonization and improvement of regional emission inventories is imperative to obtain consolidated estimates on the formation of global-scale air pollution. An emissions data set has been constructed using regional emission grid maps (annual and monthly) for SO2, NOx, CO, NMVOC, NH3, PM10, PM2.5, BC and OC for the years 2008 and 2010, with the purpose of providing consistent information to global and regional scale modelling efforts. This compilation of different regional gridded inventories – including that of the Environmental Protection Agency (EPA) for USA, the EPA and Environment Canada (for Canada), the European Monitoring and Evaluation Programme (EMEP) and Netherlands Organisation for Applied Scientific Research (TNO) for Europe, and the Model Inter-comparison Study for Asia (MICS-Asia III) for China, India and other Asian countries – was gap-filled with the emission grid maps of the Emissions Database for Global Atmospheric Research (EDGARv4.3) for the rest of the world (mainly South America, Africa, Russia and Oceania). Emissions from seven main categories of human activities (power, industry, residential, agriculture, ground transport, aviation and shipping) were estimated and spatially distributed on a common grid of 0.1° × 0.1° longitude-latitude, to yield monthly, global, sector-specific grid maps for each substance and year. The HTAP_v2.2 air pollutant grid maps are considered to combine latest available regional information within a complete global data set. The disaggregation by sectors, high spatial and temporal resolution and detailed information on the data sources and references used will provide the user the required transparency. Because HTAP_v2.2 contains primarily official and/or widely used regional emission grid maps, it can be recommended as a global baseline emission inventory, which is regionally accepted as a reference and from which different scenarios assessing emission reduction policies at a global scale could start. An analysis of country-specific implied emission factors shows a large difference between industrialised countries and developing countries for acidifying gaseous air pollutant emissions (SO2 and NOx) from the energy and industry sectors. This is not observed for the particulate matter emissions (PM10, PM2.5), which show large differences between countries in the residential sector instead. The per capita emissions of all world countries, classified from low to high income, reveal an increase in level and in variation for gaseous acidifying pollutants, but not for aerosols. For aerosols, an opposite trend is apparent with higher per capita emissions of particulate matter for low income countries.

scholarly journals COVID-19 lockdowns cause global air pollution declines

2020 ◽  
Vol 117 (32) ◽  
pp. 18984-18990 ◽  
Author(s):  
Zander S. Venter ◽  
Kristin Aunan ◽  
Sourangsu Chowdhury ◽  
Jos Lelieveld
Keyword(s):  
Air Pollution ◽  
Particulate Matter ◽  
Fine Particulate Matter ◽  
Ground Level ◽  
Air Pollutant ◽  
Pollutant Emissions ◽  
Economic Activities ◽  
Long Distance ◽  
Mobility Data ◽  
Fine Particulate

The lockdown response to coronavirus disease 2019 (COVID-19) has caused an unprecedented reduction in global economic and transport activity. We test the hypothesis that this has reduced tropospheric and ground-level air pollution concentrations, using satellite data and a network of >10,000 air quality stations. After accounting for the effects of meteorological variability, we find declines in the population-weighted concentration of ground-level nitrogen dioxide (NO2: 60% with 95% CI 48 to 72%), and fine particulate matter (PM2.5: 31%; 95% CI: 17 to 45%), with marginal increases in ozone (O3: 4%; 95% CI: −2 to 10%) in 34 countries during lockdown dates up until 15 May. Except for ozone, satellite measurements of the troposphere indicate much smaller reductions, highlighting the spatial variability of pollutant anomalies attributable to complex NOxchemistry and long-distance transport of fine particulate matter with a diameter less than 2.5 µm (PM2.5). By leveraging Google and Apple mobility data, we find empirical evidence for a link between global vehicle transportation declines and the reduction of ambient NO2exposure. While the state of global lockdown is not sustainable, these findings allude to the potential for mitigating public health risk by reducing “business as usual” air pollutant emissions from economic activities. Explore trends here:https://nina.earthengine.app/view/lockdown-pollution.

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