Impact of external industrial sources on the regional and local SO&lt;sub&gt;2&lt;/sub&gt; and O&lt;sub&gt;3&lt;/sub&gt; levels of the Mexico megacity

Abstract. The air quality of megacities can be influenced by external emission sources on both global and regional scales. At the same time their outflow emissions can exert an impact to the surrounding environment. The present study evaluates an SO2 peak observed on 24 March 2006 at the suburban supersite T1 and at ambient air quality monitoring stations located in the northern region of the Mexico City Metropolitan Area (MCMA) during the Megacity Initiative: Local and Global Research Observations (MILAGRO) field campaign. We found that this peak could be related to an important episodic emission event coming from Tizayuca region, northeast of the MCMA. Back-trajectory analyses suggest that the emission event started in the early morning at 04:00 LST and lasted for about 9 h. The estimated emission rate is about 2 kg s−1. To the best of our knowledge, sulfur dioxide emissions from the Tizayuca region have not been considered in previous studies. This finding suggests the possibility of "overlooked" emission sources in this region that could influence the air quality of the MCMA. This further motivated us to study the cement plants, including those in the state of Hidalgo and in the State of Mexico. It was found that they can contribute to the SO2 levels in the northeast (NE) region of the basin (about 42%), at the suburban supersite T1 (41%) and that at some monitoring stations their contribution can be even higher than the contribution from the Tula Industrial Complex (TIC). The contribution of the Tula Industrial Complex to regional ozone levels is estimated. The model suggests low contribution to the MCMA (1 to 4 ppb) and slightly higher contribution at the suburban T1 (6 ppb) and rural T2 (5 ppb) supersites. However, the contribution could be as high as 10 ppb in the upper northwest region of the basin and in the southwest and south-southeast regions of the state of Hidalgo. In addition, the results indicated that the ozone plume could also be transported to northwest Tlaxcala, eastern Hidalgo, and farther northeast of the State of Mexico, but with rather low values. A first estimate of the potential contribution from flaring activities to regional ozone levels is presented. Results suggest that up to 30% of the total regional ozone from TIC could be related to flaring activities. Finally, the influence on SO2 levels from technological changes in the existing refinery is briefly discussed. These changes are due to the upcoming construction of a new refinery in Tula. The combination of emission reductions in the power plant, the refinery and in local sources in the MCMA could result in higher reductions on the average SO2 concentration. Reductions in external sources tend to affect more the northern part of the basin (−16 to −46%), while reductions of urban sources in the megacity tend to diminish SO2 levels substantially in the central, southwest, and southeast regions (−31 to −50%).

Download Full-text

Impact of external industrial sources on the regional and local air quality of Mexico Megacity

Atmospheric Chemistry and Physics Discussions ◽

10.5194/acpd-13-26579-2013 ◽

2013 ◽

Vol 13 (10) ◽

pp. 26579-26625

Author(s):

V. H. Almanza ◽

L. T. Molina ◽

G. Li ◽

J. Fast ◽

G. Sosa

Keyword(s):

Air Quality ◽

Regional Scale ◽

Ambient Air ◽

The State ◽

Combustion Model ◽

Potential Contribution ◽

Industrial Complex ◽

Ozone Levels ◽

Monitoring Stations

Abstract. The air quality of megacities can be influenced by external emissions sources on both global and regional scale, and at the same time their outflow emissions can exert an important impact to the surrounding environment. The present study evaluates an SO2 peak observed on 24 March 2006 at the suburban supersite T1 and ambient air quality monitoring stations located in the north region of the Mexico City Metropolitan Area (MCMA) during MILAGRO campaign. We found that this peak could be related to an important episodic emission event from Tizayuca region, northeast of the MCMA. Back trajectories analyses suggest that the emission event started in the early morning at 04:00 LST and lasted for about 9 h. The estimated emission rate is noticeably high, about 2 kg s−1. This finding suggests the possibility of "overlooked" emission sources in this region that could influence the air quality of the MCMA. This further motivated us to study the cement plants, including those in the State of Hidalgo and in the State of Mexico, and we found that they can contribute in the NE region of the basin (about 41.7%), at the suburban supersite T1 (41.23%) and at some monitoring stations their contribution can be even higher than from the Tula Industrial Complex. The contribution of Tula Industrial Complex to regional ozone levels is estimated. The model suggests low contribution to the MCMA (1 ppb to 4 ppb) and slightly higher at the suburban T1 (6 ppb) and rural T2 (5 ppb) supersites. However, the contribution could be as high as 10 ppb in the upper northwest region of the basin and in the southwest and south-southeast regions of State of Hidalgo. In addition, a first estimate of the potential contribution from flaring activities to regional ozone levels is presented. Emission rates are estimated with a CFD combustion model. Results suggest that up to 30% of the total regional ozone from TIC could be related to flaring activities. Finally, the influence in SO2 levels from technological changes in the existing refinery is briefly discussed. These changes are due to the upcoming construction of a new refinery in Tula. The combination of emission reductions in the power plant, the refinery and in local sources in the MCMA could result in higher reductions on the average SO2 concentration. Reductions in external sources tend to affect more the northern part of the basin (−16.35% to −45.58%), whilst reductions of urban sources in the megacity tend to diminish SO2 levels substantially in the central, southwest, and southeast regions (−30.71% to −49.75%).

Download Full-text

Air Quality Assessment in the State of Kuwait during 2012 to 2017

Atmosphere ◽

10.3390/atmos12060678 ◽

2021 ◽

Vol 12 (6) ◽

pp. 678

Author(s):

Adeeba Al-Hurban ◽

Sawsan Khader ◽

Ahmad Alsaber ◽

Jiazhu Pan

Keyword(s):

Air Pollution ◽

Air Quality ◽

Meteorological Factors ◽

Ambient Air ◽

The State ◽

Ambient Air Pollution ◽

Northeast Monsoon ◽

Residential Areas ◽

Industrial Areas ◽

The State Of Kuwait

This study aimed to examine the trend of ambient air pollution (i.e., ozone (O3), nitrogen monoxide (NO), nitrogen dioxide (NO2), nitrogen oxides (NOx), sulfur dioxide (SO2), carbon monoxide (CO), benzene (C6H6) and particulate matter with an aerodynamic diameter smaller than 10 microns (PM10), and non-methane hydrocarbons (NMHCs) at 10 monitoring stations located in the main residential and industrial areas in the State of Kuwait over 6 years (2012–2017). We found that the SO2 level in industrial areas (0.065 ppm) exceeded the allowable range of SO2 in residential areas (0.030 ppm). Air pollution variables were defined by the Environmental Public Authority of Kuwait (K-EPA). In this study, integrated statistical analysis was performed to compare an established air pollution database to Kuwait Ambient Air Quality Guidelines and to determine the association between pollutants and meteorological factors. All pollutants were positively correlated, with the exception of most pollutants and PM10 and O3. Meteorological factors, i.e., the ambient temperature, wind speed and humidity, were also significantly associated with the above pollutants. Spatial distribution mapping indicated that the PM10 level remained high during the southwest monsoon (the hot and dry season), while the CO level was high during the northeast monsoon (the wet season). The NO2 and O3 levels were high during the first intermonsoon season.

Download Full-text

Impact of COVID-19 induced lockdown and unlock down phases on the ambient air quality of Delhi, capital city of India

Urban Climate ◽

10.1016/j.uclim.2021.100945 ◽

2021 ◽

pp. 100945

Author(s):

Mayank Pandey ◽

M.P. George ◽

R.K. Gupta ◽

Deepak Gusain ◽

Atul Dwivedi

Keyword(s):

Air Quality ◽

Ambient Air ◽

Capital City ◽

Ambient Air Quality

Download Full-text

Ambient Air Quality Classification by Grey Wolf Optimizer Based Support Vector Machine

Journal of Environmental and Public Health ◽

10.1155/2017/3131083 ◽

2017 ◽

Vol 2017 ◽

pp. 1-12 ◽

Cited By ~ 13

Author(s):

Akash Saxena ◽

Shalini Shekhawat

Keyword(s):

Support Vector Machine ◽

Air Quality ◽

Industrial Development ◽

Learning Algorithm ◽

Ambient Air ◽

Support Vector ◽

Grey Wolf Optimizer ◽

Mathematical Framework ◽

Primary Concern

With the development of society along with an escalating population, the concerns regarding public health have cropped up. The quality of air becomes primary concern regarding constant increase in the number of vehicles and industrial development. With this concern, several indices have been proposed to indicate the pollutant concentrations. In this paper, we present a mathematical framework to formulate a Cumulative Index (CI) on the basis of an individual concentration of four major pollutants (SO2, NO2, PM2.5, and PM10). Further, a supervised learning algorithm based classifier is proposed. This classifier employs support vector machine (SVM) to classify air quality into two types, that is, good or harmful. The potential inputs for this classifier are the calculated values of CIs. The efficacy of the classifier is tested on the real data of three locations: Kolkata, Delhi, and Bhopal. It is observed that the classifier performs well to classify the quality of air.

Download Full-text

Ambient Air Quality Assessment with Particular Reference to Particulates in Western part of Jharia Coalfield, India

Current World Environment ◽

10.12944/cwe.10.2.18 ◽

2015 ◽

Vol 10 (2) ◽

pp. 523-528 ◽

Cited By ~ 2

Author(s):

Gurdeep Singh ◽

Amarjeet Singh

Keyword(s):

Air Quality ◽

Power Plants ◽

Environmental Parameters ◽

Ambient Air ◽

Primary Energy ◽

Underground Mines ◽

Opencast Mining ◽

Ambient Air Quality ◽

Jharia Coalfield

India is in the list of fastest growing countries of the world. India's energy needs are also increasing due to population and industrial growth for improving quality of living style. In India, coal is major input infrastructure industries for example Power plants, Steel plants and Cement industries. India’s 52% of primary energy is coal dependent1. 66% of India's power generation depends upon coal production1. Jharia Coalfield (JCF) is falling in the Lower Gondwana Coalfields of India. The area of the JCF is about 450 km2. It is important for the major supply of precious coking coal required for steel plants in India. It is located in Dhanbad district of Jharkhand state of India, The latitude is 23° 39' to 23° 48' N and longitude is 86° 11' to 86° 27' E for the Jharia coalfield. Based on environmental parameters, all the 103 mines of BCCL have been grouped under 17 Clusters. A cluster consists of a group of mines with mine lease boundary lying in close vicinity and includes-Operating mines, Abandoned/ closed mines and proposed projects.The focused study area is in the western part of the Jharia coalfield is named as Cluster XV group of mines of BCCL consists of four mines, Kharkharee Colliery (UG), Dharmaband Colliery (UG), Madhuband Colliery (UG) and Phularitand Colliery (UG) .The present study was carried out with the objective to measure the ambient air quality of the study area with reference to particulate matter (SPM, PM10 & PM2.5). Ambient air monitoring results have shown that the observe air quality were found within the limit prescribed by MoEF / CPCB. It may due to Underground mines as there are pollution causing lesser activities involved in the UG mining process compared to opencast mining. Implementation of Master plan for Jharia coalfields for environmental management has also improve the air quality in the area10,11.

Download Full-text

Assessment of ambient air pollution in the Waterberg Priority Area 2012-2015

Clean Air Journal ◽

10.17159/2410-972x/2016/v26n1a9 ◽

2016 ◽

Vol 26 (1) ◽

pp. 21-28 ◽

Cited By ~ 2

Author(s):

G.T. Feig ◽

S. Naidoo ◽

N. Ncgukana

Keyword(s):

Air Quality ◽

Monitoring Network ◽

Ambient Air ◽

Ambient Air Pollution ◽

Local Source ◽

Ambient Air Quality ◽

Priority Area ◽

Hourly Data ◽

Ambient Concentrations ◽

Monitoring Stations

The Waterberg Priority Area ambient air quality monitoring network was established in 2012 to monitor the ambient air quality in the Waterberg Air Quality Priority Area. Three monitoring stations were established in Lephalale, Thabazimbi and Mokopane. The monitoring stations measure the concentrations of PM10, PM2.5, SO2, NOx, CO, O3, BTEX and meteorological parameters. Hourly data for a 31 month period (October 2012-April 2015) was obtained from the South African Air Quality Information System (SAAQIS) and analysed to assess patterns in atmospheric concentrations, including seasonal and diurnal patterns of the ambient concentrations and to assess the impacts that such reported pollution concentration may have. Local source regions for SO2, PM10, PM2.5 and O3 were identified and trends in the recorded concentrations are discussed.

Download Full-text

Ambient Air Quality Monitoring Studies in Four Specific Location of Tamilnadu, India

International Research Journal of Multidisciplinary Technovation ◽

10.34256/irjmtcon96 ◽

2019 ◽

pp. 677-683

Author(s):

Mageshkumar P ◽

Ramesh S ◽

Angu Senthil K

Keyword(s):

Air Quality ◽

Quality Index ◽

High Volume ◽

Ambient Air ◽

Quality Parameters ◽

Air Quality Index ◽

Gaseous Pollutants ◽

Ambient Air Quality ◽

Air Sampler

A comprehensive study on the air quality was carried out in four locations namely, Tiruchengode Bus Stand, K.S.R College Campus, Pallipalayam Bus Stop and Erode Government Hospital to assess the prevailing quality of air. Ambient air sampling was carried out in four locations using a high volume air sampler and the mass concentrations of PM10, PM2.5, SO2, NOX and CO were measured. The analyzed quality parameters were compared with the values suggested by National Ambient Air Quality Standards (NAAQS). Air quality index was also calculated for the gaseous pollutants and for Particulate Matters. It was found that PM10 concentration exceeds the threshold limits in all the measured locations. The higher vehicular density is one of the main reasons for the higher concentrations of these gaseous pollutants. The air quality index results show that the selected locations come under moderate air pollution.

Download Full-text