Satellite Observation of Spatio-temporal Variations in Nitrogen Dioxide over West Africa and Implications for Regional Air Quality

Background. Nitrogen dioxide (NO2) is known to affect human health, causing heart and cardiovascular diseases, and it has been shown that locations with long term NO2 pollution recorded a high number of fatalities due to the COVID-19 pandemic. There are no ground stations monitoring emissions of NO2 over West Africa. The present study aimed to use satellite observations to examine pollutant trends over this region. Objective. To examine the trend of NO2 over the entire West Africa sub region in relationship to contributions to environmental emissions using satellite-derived data. This enables the assessment of West Africa regional air pollution hot spots in relationship to enhancing atmospheric factors. The results from this study will also be useful guidance for setting air quality standards for air pollution controls to minimize health hazards. Methods. The present study examined thirteen years of average monthly values of nitrogen dioxide (NO2) to determine the spatio-temporal variation of this pollutant over West Africa. Satellite data for NO2 between 2005 and 2017 were used to determine the variation in pollution levels over West Africa. Correlations between NO2 and meteorological variables (wind speed, rainfall and air temperature) were obtained to explain the influence of West African weather on the region's pollution accumulation. Results. The present study observed that NO2 concentrations varied from place to place and from season to season. Nitrogen dioxide concentrations during the dry season were higher (sometimes 200% higher) than values observed in the wet season which ranged between 0.5 and 6×1015 molec/cm2. Nitrogen dioxide north-south oscillation during the course of a year is largely controlled by the inter-tropical discontinuity (ITD) zone as high concentrations of NO2 are found in the vicinity of the ITD where wind speeds and horizontal vorticity approaches zero. Correlation analysis between NO2 and some atmospheric variables indicated NO2 concentrations are well influenced by atmospheric variables showing bipolar signals depending on the season. An increasing trend of NO2 was also found over selected cities of the region. This indicated that regional air quality is gradually deteriorating. Conclusions. The implications of worsening regional air quality were examined in the light of the prevailing COVID-19 pandemic. The dominant atmospheric factor determining pollution episodes in the region is the inter-tropical discontinuity line which marks the meeting point between the two wind regimes over the region. Densely populated areas are characteristically prone to elevated pollution and have experienced high fatalities during the COVID-19 pandemic. Competing Interests. The authors declare no competing financial interests.

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Spatio-Temporal Variation of Particulate Matter(PM2.5) Concentrations and Its Health Impacts in a Mega City, Delhi in India

Environmental Health Insights ◽

10.1177/1178630218792861 ◽

2018 ◽

Vol 12 ◽

pp. 117863021879286 ◽

Cited By ~ 16

Author(s):

Amit Kumar Gorai ◽

Paul B Tchounwou ◽

SS Biswal ◽

Francis Tuluri

Keyword(s):

Particulate Matter ◽

Air Quality ◽

Environmental Protection Agency ◽

Quality Index ◽

Temporal Variations ◽

Air Quality Index ◽

Capital City ◽

Health Impacts ◽

Quality Level ◽

Spatio Temporal

Rising concentration of air pollution and its associated health effects is rapidly increasing in India, and Delhi, being the capital city, has drawn our attention in recent years. This study was designed to analyze the spatial and temporal variations of particulate matter (PM2.5) concentrations in a mega city, Delhi. The daily PM2.5 concentrations monitored by the Central Pollution Control Board (CPCB), New Delhi during November 2016 to October 2017 in different locations distributed in the region of the study were used for the analysis. The descriptive statistics indicate that the spatial mean of monthly average PM2.5 concentrations ranged from 45.92 μg m−3 to 278.77 μg m−3. The maximum and minimum spatial variance observed in the months of March and September, respectively. The study also analyzed the PM2.5 air quality index (PM2.5—Air Quality Index (AQI)) for assessing the health impacts in the study area. The AQI value was determined according to the U.S. Environmental Protection Agency (EPA) system. The result suggests that most of the area had the moderate to very unhealthy category of PM2.5-AQI and that leads to severe breathing discomfort for people residing in the area. It was observed that the air quality level was worst during winter months (October to January).

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TRAFFIC RELATED AIR POLLUTION AND REGIONAL AIR QUALITY ARE ASSOCIATED WITH AUTISM

ISEE Conference Abstracts ◽

10.1289/isee.2011.00925 ◽

2011 ◽

Vol 2011 (1) ◽

Author(s):

Heather E. Volk ◽

Frederick Lurmann ◽

Bryan Penfold ◽

Irva Hertz-Picciotto ◽

Rob McConnell

Keyword(s):

Air Pollution ◽

Air Quality ◽

Regional Air Quality

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Evaluation of observation-fused regional air quality model results for population air pollution exposure estimation

The Science of The Total Environment ◽

10.1016/j.scitotenv.2014.03.107 ◽

2014 ◽

Vol 485-486 ◽

pp. 563-574 ◽

Cited By ~ 46

Author(s):

Gang Chen ◽

Jingyi Li ◽

Qi Ying ◽

Seth Sherman ◽

Neil Perkins ◽

...

Keyword(s):

Air Pollution ◽

Air Quality ◽

Air Quality Model ◽

Quality Model ◽

Exposure Estimation ◽

Air Pollution Exposure ◽

Regional Air Quality ◽

Pollution Exposure

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On the long term impact of emissions from central European cities on regional air-quality

Atmospheric Chemistry and Physics Discussions ◽

10.5194/acpd-15-32101-2015 ◽

2015 ◽

Vol 15 (22) ◽

pp. 32101-32155 ◽

Cited By ~ 6

Author(s):

P. Huszar ◽

M. Belda ◽

T. Halenka

Keyword(s):

Air Pollution ◽

Air Quality ◽

Rural Areas ◽

Ozone Production ◽

Central European ◽

Large Cities ◽

European Cities ◽

Regional Air Quality ◽

Urban Emissions ◽

The Impact

Abstract. For the purpose of qualifying and quantifying the impact of urban emission from Central European cities on the present-day regional air-quality, the regional climate model RegCM4.2 was coupled with the chemistry transport model CAMx, including two-way interactions. A series of simulations was carried out for the 2001–2010 period either with all urban emissions included (base case) or without considering urban emissions. Further, the sensitivity of ozone production to urban emissions was examined by performing reduction experiments with −20 % emission perturbation of NOx and/or NMVOC. The validation of the modeling system's air-quality related outputs using AirBase and EMEP surface measurements showed satisfactory reproduction of the monthly variation for ozone (O3), nitrogen dioxide (NO2) and sulfur dioxide (SO2). In terms of hourly correlations, reasonable values are achieved for ozone (r around 0.5–0.8) and for NO2 (0.4–0.6), but SO2 is poorly or not correlated at all with measurements (r around 0.2–0.5). The modeled fine particulates (PM2.5) are usually underestimated, especially in winter, mainly due to underestimation of nitrates and carbonaceous aerosols. EC air-quality measures were chosen as metrics describing the cities emission impact on regional air pollution. Due to urban emissions, significant ozone titration occurs over cities while over rural areas remote from cities, ozone production is modeled, mainly in terms of number of exceedances and accumulated exceedances over the threshold of 40 ppbv. Urban NOx, SO2 and PM2.5 emissions also significantly contribute to concentrations in the cities themselves (up to 50–70 % for NOx and SO2, and up to 60 % for PM2.5), but the contribution is large over rural areas as well (10–20 %). Although air pollution over cities is largely determined by the local urban emissions, considerable (often a few tens of %) fraction of the concentration is attributable to other sources from rural areas and minor cities. Further, for the case of Prague (Czech Republic capital) it is shown that the inter-urban interference between large cities does not play an important role which means that the impact on a chosen city of emissions from all other large cities is very small. The emissions perturbation experiments showed that to achieve significant ozone reduction over cities in central Europe, the emission control strategies have to focus on the reduction of NMVOC, as reducing NOx, due to suppressed titration, leads often to increased O3. The influence over rural areas remote from cities is however always in favor of improved air-quality, i.e. both NOx and/or NMVOC reduction ends up in decreased ozone pollution, mainly in terms of exceedances.

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Temporal analysis of air pollutants in the most affected monsoon region

Indonesian Journal of Electrical Engineering and Computer Science ◽

10.11591/ijeecs.v23.i1.pp229-236 ◽

2021 ◽

Vol 23 (1) ◽

pp. 229

Author(s):

Omar Kairan ◽

Nur Nasehah Zainudin ◽

Nurul Hasya Mohd Hanafiah ◽

Nur Emylia Arissa Mohd Jafri ◽

Fukayhah Fatiha @Suhami ◽

...

Keyword(s):

Air Pollution ◽

Air Quality ◽

Air Pollutants ◽

Monsoon Season ◽

Secondary Data ◽

Ambient Air ◽

Temporal Analysis ◽

Quality Standard ◽

Temporal Variations ◽

Air Pollutant

Air pollution has become an issue at all rates in the world. In Malaysia, there is a system is known as air quality index (API) used to indicate the overall air quality in the country where the air pollutants include or the new ambient air quality standard are sulphur dioxide (SO2), nitrogen dioxide (NO2), carbon monoxide (CO), ozone (O3) and particulate matter with size less than 10 (PM10). The concentration levels of the air pollutants were said to be affected by the monsoon changes. Therefore, this study is conducted to examine the existence of temporal variations of each air pollutant then identify the differences of each air pollutants concentration in temporal variations. This study uses secondary data where data that has been retrieved from the Department of Environment (DOE) where it is data of air pollution specifically for Kota Bharu, kelantan records. Hierarchical agglomerative cluster analysis was conducted to group monthly air quality. As a conclusion, the study can conclude that the five air pollutants grouped into several different monthly clusters mostly representing the two main monsoon seasons. Mostly air pollutant varied accordingly towards the monsoon season. During the southwestern monsoon, air pollutant concentration tends to higher compare to the northeastern monsoon with mostly due to meteorological factors.

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Combination of data-driven models and interpolation technique to develop of PM10 map for Hanoi, Vietnam

Scientific Reports ◽

10.1038/s41598-020-75547-y ◽

2020 ◽

Vol 10 (1) ◽

Author(s):

Dung Anh Nguyen ◽

Son Hong Duong ◽

Phuong Anh Tran ◽

Hai Hoang Cao ◽

Bang Quoc Ho

Keyword(s):

Air Quality ◽

Goodness Of Fit ◽

Meteorological Factors ◽

Meteorological Data ◽

Central Area ◽

Temporal Variations ◽

Data Driven ◽

Rapid Urbanization ◽

Interpolation Technique ◽

Spatio Temporal

Abstract The degradation of air quality is the most concerned issue of our society due to its harmful impacts on human health, especially in cities with rapid urbanization and population growth like Hanoi, the capital of Vietnam. This study aims at developing a new approach that combines data-driven models and interpolation technique to develop the PM10 concentration maps from meteorological factors for the central area of Hanoi. Data-driven models that relate the PM10 concentration with the meteorological factors at the air quality monitoring stations in the study area were developed using the Multiple Linear Regression (MLR) and Artificial Neural Network (ANN) algorithms. Models’ performance comparison showed that ANN models yielded better goodness-of-fit indices than MLR models at all stations in the study area with average coefficient of correlation (r) and Nash–Sutcliffe Efficiency Index (NSE) of 0.51 and 0.34 for the former, and 0.7 and 0.49 for the latter. These indices indicates that the ANN-based data-driven models outperformed the MLR-based models. Thus, the ANN-based models and the Inverse Distance Weighting (IDW) interpolation technique were then combined for mapping the monthly PM10 concentration with a spatial resolution of 1 km from global meteorological data. With this combination, the PM10 concentration maps account for both local PM10 concentration and impacts of spatio-temporal variations of meteorological factors on the PM10 concentration. This study provides a promising method to predict the PM concentration with a high spatio-temporal resolution from meteorological data.

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Nitrogen dioxide and formaldehyde measurements from the GEOstationary Coastal and Air Pollution Events (GEO-CAPE) Airborne Simulator over Houston, Texas

Atmospheric Measurement Techniques ◽

10.5194/amt-11-5941-2018 ◽

2018 ◽

Vol 11 (11) ◽

pp. 5941-5964 ◽

Cited By ~ 15

Author(s):

Caroline R. Nowlan ◽

Xiong Liu ◽

Scott J. Janz ◽

Matthew G. Kowalewski ◽

Kelly Chance ◽

...

Keyword(s):

Air Pollution ◽

Air Quality ◽

Nitrogen Dioxide ◽

Near Infrared ◽

Scattered Light ◽

Trace Gas ◽

Satellite Mission ◽

Tropospheric No2 ◽

Pollution Events

Abstract. The GEOstationary Coastal and Air Pollution Events (GEO-CAPE) Airborne Simulator (GCAS) was developed in support of NASA's decadal survey GEO-CAPE geostationary satellite mission. GCAS is an airborne push-broom remote-sensing instrument, consisting of two channels which make hyperspectral measurements in the ultraviolet/visible (optimized for air quality observations) and the visible–near infrared (optimized for ocean color observations). The GCAS instrument participated in its first intensive field campaign during the Deriving Information on Surface Conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ) campaign in Texas in September 2013. During this campaign, the instrument flew on a King Air B-200 aircraft during 21 flights on 11 days to make air quality observations over Houston, Texas. We present GCAS trace gas retrievals of nitrogen dioxide (NO2) and formaldehyde (CH2O), and compare these results with trace gas columns derived from coincident in situ profile measurements of NO2 and CH2O made by instruments on a P-3B aircraft, and with NO2 observations from ground-based Pandora spectrometers operating in direct-sun and scattered light modes. GCAS tropospheric column measurements correlate well spatially and temporally with columns estimated from the P-3B measurements for both NO2 (r2=0.89) and CH2O (r2=0.54) and with Pandora direct-sun (r2=0.85) and scattered light (r2=0.94) observed NO2 columns. Coincident GCAS columns agree in magnitude with NO2 and CH2O P-3B-observed columns to within 10 % but are larger than scattered light Pandora tropospheric NO2 columns by 33 % and direct-sun Pandora NO2 columns by 50 %.

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Umfang und Grenzen der Luftreinhalteplanung

10.5771/9783828877023 ◽

2021 ◽

Author(s):

Denise Berger

Keyword(s):

Air Pollution ◽

Air Quality ◽

Nitrogen Dioxide ◽

Pollution Control ◽

Ambient Air ◽

Air Pollution Control ◽

Eu Law ◽

Ambient Air Quality ◽

Control Plan ◽

Limit Value

Since the rulings of the Federal Administrative Court (BVerwG) of 27 February 2018 on the Stuttgart and Düsseldorf air pollution control plans, diesel driving bans have become one of the best-known but also most controversial measures in the context of air pollution control planning. The reason for this is that the limit value for nitrogen dioxide, which is based on the requirements of the Ambient Air Quality Directive under EU law, is exceeded, particularly in conurbations. Taking into account the legal and administrative court requirements for the proportionality of traffic bans, the current challenges for the instrument of the air pollution control plan are shown and the implementation of planned measures in practice is examined on the basis of selected air pollution control plans.

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