A comprehensive approach for the evaluation and comparison of emission inventories in Madrid

Vedrenne, Michel; Borge, Rafael; Lumbreras, Julio; Rodríguez, María Encarnación; Paz, David de la; Pérez, J. L.; Andrés, Juan Manuel de; Quaassdorff, Christina Violetta

doi:10.1016/j.atmosenv.2016.09.020

Cited by 19 publications

(8 citation statements)

References 30 publications

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“…When smaller regions are modeled, it is easier to consider detailed information about the location of specific emission sources or to include information on fleet composition on specific streets. This can modify the emission inventories and subsequently the CTM results quite substantially (Vedrenne et al 2016).…”

Section: Horizontal Distributionmentioning

confidence: 99%

“…This flux is typically called "emission." Many studies have emphasized that a profound knowledge about how, where, and when substances are released ("emitted") into the atmosphere is crucial for the reliability of air quality predictions because transport and chemical transformation heavily depend on meteorological variables that also vary in space and time (see, e.g., Frost et al 2013;Fuzzi et al 2015;Bergström et al 2012;Denier van der Gon et al 2015;Fountoukis et al 2014;Im et al 2015;Kühlwein et al 2002;Vedrenne et al 2016). In addition, chemical reactions and adsorption, desorption, and coagulation processes depend on the presence of possible reaction or collision partners.…”

Section: Introductionmentioning

confidence: 99%

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Modeling emissions for three-dimensional atmospheric chemistry transport models

Matthias

Arndt

Aulinger

et al. 2018

Journal of the Air & Waste Management Association

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Emission data are probably the most important input for chemistry transport model (CTM) systems. They need to be provided in high spatial and temporal resolution and on a grid that is in agreement with the CTM grid. Simple methods to distribute the emissions in time and space need to be replaced by sophisticated emission models in order to improve the CTM results. New methods, e.g., for ammonia emissions, provide grid cell-dependent temporal profiles. In the future, large data fields from traffic observations or satellite observations could be used for more detailed emission data.

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Section: Horizontal Distributionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Modeling emissions for three-dimensional atmospheric chemistry transport models

Matthias

Arndt

Aulinger

et al. 2018

Journal of the Air & Waste Management Association

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“…In the words of Seika, the emission inventory (EI) is a comprehensive list of various types of air pollutants emitted by various sources of pollution in a given area within a given time interval [ 28 ]. EIs provide a description of the polluting activities that occur across a specific geographic domain and are widely used as input for air quality modeling for the assessment of compliance with environmental legislation [ 29 ]. Air pollution control requires complex environmental management, in which clear EIs are the basis for other research.…”

Section: The Current Status Of Pollution Researchmentioning

confidence: 99%

Air Pollution Forecasts: An Overview

Bai

Wang

et al. 2018

IJERPH

260

126

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Air pollution is defined as a phenomenon harmful to the ecological system and the normal conditions of human existence and development when some substances in the atmosphere exceed a certain concentration. In the face of increasingly serious environmental pollution problems, scholars have conducted a significant quantity of related research, and in those studies, the forecasting of air pollution has been of paramount importance. As a precaution, the air pollution forecast is the basis for taking effective pollution control measures, and accurate forecasting of air pollution has become an important task. Extensive research indicates that the methods of air pollution forecasting can be broadly divided into three classical categories: statistical forecasting methods, artificial intelligence methods, and numerical forecasting methods. More recently, some hybrid models have been proposed, which can improve the forecast accuracy. To provide a clear perspective on air pollution forecasting, this study reviews the theory and application of those forecasting models. In addition, based on a comparison of different forecasting methods, the advantages and disadvantages of some methods of forecasting are also provided. This study aims to provide an overview of air pollution forecasting methods for easy access and reference by researchers, which will be helpful in further studies.

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“…NO is derived from nitrogen (N 2 ) in high-temperature combustion processes, such as internal combustion engines and NO x emissions released from these engines contain over 90% of NO, which is relatively unstable, compared to oxygen (O 2 ) and N 2 (Dotse et al, 2016;Liu et al, 2018). The main fate of NO is to convert into NO 2 after reaction with ozone (O 3 ) in the ambient atmosphere (Derwent and Hertel, 1998;Vedrenne et al, 2016). NO x and NO are the secondary pollutants that require another reactant to change their form, therefore, the concentrations of these pollutants were lower, compared to that of PM 2.5 and NO 2 (Zawacki et al, 2018).…”

Section: Annual Trends Of Emissions and Relationship With Meteorologimentioning

confidence: 99%

Status of Air Quality with Potential Linkage to the Metrological Conditions in Three Major Cities of Pakistan

Hamid

Junaid

Ali

et al. 2019

American Journal of Environmental Sciences

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Environmental pollution being fatal for all living organisms is growing adversely due to excessive industrialization and urbanization. Vehicular emissions have aggravated the situation and pose detrimental effects on human health. In this study, the trend of ambient air quality was analyzed in the three metropolitan cities of Pakistan, including Karachi, Lahore and Islamabad for a period of three years (2008-2010). Air pollutants, such as NO, NO x , NO 2 and PM 2.5 were recorded usingmobile air quality monitoring stations in the target areas. Results from statistical analysis revealed PM 2.5 with highest levels in all the cities, albeit exceeded the World Health Organization (WHO) guideline limits. Spearman correlation revealed that the levels of air pollutants were negatively correlated with the temperature and rainfall, whereas positively correlated with the wind speed. Annual and seasonal variations in the concentrations of the air pollutants was also observed and the highest concentration was recorded in Karachi during the winter season that could be attributed to inversion phenomenon. In addition, the elevated vehicular emissions were observed in Lahore, implied comparatively high air pollution loads, comparison to those of Karachi and Islamabad. The widespread use of low-quality fuel, coupled with a dramatic expansion in the number of vehicles has led to significant air pollution problems, especially in Lahore and Karachi. Therefore, the efficient mass transit system and urban forests should be introduced to abate the ever-increasing levels of organic pollutants and improve the state of ambient air quality in the major cities of Pakistan.

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A comprehensive approach for the evaluation and comparison of emission inventories in Madrid

Cited by 19 publications

References 30 publications

Modeling emissions for three-dimensional atmospheric chemistry transport models

Modeling emissions for three-dimensional atmospheric chemistry transport models

Air Pollution Forecasts: An Overview

Status of Air Quality with Potential Linkage to the Metrological Conditions in Three Major Cities of Pakistan

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