A Novel Approach for Air Quality Inference and Prediction Based on DBU-LSTM

2019 ◽  
pp. 171-186
Author(s):  
Liang Ge ◽  
Aoli Zhou ◽  
Junling Liu ◽  
Hang Li
Keyword(s):  
Air Quality ◽  
Novel Approach

scholarly journals An integrated approach for the evaluation of technological hazard impacts on air quality: the case of the Val d'Agri oil/gas plant

2014 ◽  
Vol 2 (4) ◽  
pp. 2345-2376
Author(s):  
M. Calvello ◽  
F. Esposito ◽  
S. Trippetta
Keyword(s):  
Air Quality ◽  
Treatment Plant ◽  
Monitoring Network ◽  
Integrated Approach ◽  
Preliminary Evaluation ◽  
Air Quality Measurements ◽  
Novel Approach ◽  
Starting Point ◽  
Pre Treatment ◽  
Oil Gas

Abstract. The Val d'Agri area (southern Italy) hosts the biggest on-shore European reservoir and the largest oil/gas pre-treatment plant, named Centro Olio Val d'Agri (COVA), located in a rural/anthropized context. Several hazards are associated to this plant. These are mainly represented by possible impacts of the COVA atmospheric emissions on the local air quality and human health. This work uses a novel approach based on the integration of air quality measurements from the regional monitoring network, additional experimental measurements (i.e., sub-micrometric particulate matter – PM1 and Black Carbon – BC) and advanced statistical analyses to provide a preliminary evaluation of the Val d'Agri air quality state and give some indications of specific areas potentially affected by COVA hazards. Results show that the COVA plant emissions exert an impact especially on the air quality of the area closest to it. In this area several pollutants specifically related to the COVA combustion processes (i.e., nitrogen oxides, benzene and toluene) show the highest concentration values and significant correlations. The proposed approach represents a first step in the assessment of the risks associated to oil/gas exploration and pre-treatment activities and a starting point for the development of effective and exportable air quality monitoring strategies.

scholarly journals AIR QUALITY MONITORING AND DATA MANAGEMENT IN GERMANY – STATUS QUO AND SUGGESTIONS FOR IMPROVEMENT

2020 ◽  
Vol XLIV-4/W2-2020 ◽  
pp. 37-43
Author(s):  
L. Petry ◽  
H. Herold ◽  
G. Meinel ◽  
T. Meiers ◽  
I. Müller ◽  
...  
Keyword(s):  
Decision Making ◽  
Air Quality ◽  
Management Practices ◽  
System Development ◽  
Ground Level ◽  
Ground Level Ozone ◽  
Novel Approach ◽  
Depth Analysis ◽  
New Generation

Abstract. This paper proposes a novel approach to facilitate air quality aware decision making and to support planning actors to take effective measures for improving the air quality in cities and regions. Despite many improvements over the past decades, air pollutants such as particulate matter (PM), nitrogen dioxide (NO2) and ground-level ozone (O3) pose still one of the major risks to human health and the environment. Based on both a general analysis of the air quality situation and regulations in the EU and Germany as well as an in-depth analysis of local management practices requirements for better decision making are identified. The requirements are used to outline a system architecture following a co-design approach, i.e., besides scientific and industry partners, local experts and administrative actors are actively involved in the system development. Additionally, the outlined system incorporates two novel methodological strands: (1) it employs a deep neural network (DNN) based data analytics approach and (2) makes use of a new generation of satellite data, namely Sentinel-5 Precursor (Sentinel-5P). Hence, the system allows for providing areal and high-resolution (e.g., street-level) real-time and forecast (up to 48 hours) data to inform decision makers for taking appropriate short-term measures, and secondly, to simulate air quality under different planning options and long-term actions such as modified traffic flows and various urban layouts.

scholarly journals DESIGN AND RESULTS OF AN AI-BASED FORECASTING OF AIR POLLUTANTS FOR SMART CITIES

2021 ◽  
Vol VIII-4/W1-2021 ◽  
pp. 89-96
Author(s):  
L. Petry ◽  
T. Meiers ◽  
D. Reuschenberg ◽  
S. Mirzavand Borujeni ◽  
J. Arndt ◽  
...  
Keyword(s):  
Air Quality ◽  
Air Pollutants ◽  
Smart Cities ◽  
Meteorological Data ◽  
Weather Forecast ◽  
Ground Level ◽  
Urban Environments ◽  
Air Pollutant ◽  
Novel Approach

Abstract. This paper presents the design and the results of a novel approach to predict air pollutants in urban environments. The objective is to create an artificial intelligence (AI)-based system to support planning actors in taking effective and adequate short-term measures against unfavourable air quality situations. In general, air quality in European cities has improved over the past decades. Nevertheless, reductions of the air pollutants particulate matter (PM), nitrogen dioxide (NO2) and ground-level ozone (O3), in particular, are essential to ensure the quality of life and a healthy life in cities. To forecast these air pollutants for the next 48 hours, a sequence-to-sequence encoder-decoder model with a recurrent neural network (RNN) was implemented. The model was trained with historic in situ air pollutant measurements, traffic and meteorological data. An evaluation of the prediction results against historical data shows high accordance with in situ measurements and implicate the system’s applicability and its great potential for high quality forecasts of air pollutants in urban environments by including real time weather forecast data.

A Novel Approach to Design a Scalable Air Quality Monitoring System

2012 ◽  
Vol 7 (3) ◽  
pp. 37-54
Author(s):  
Ivaylo Atanasov ◽  
Ventsislav Trifonov ◽  
Kamelia Nikolova ◽  
Evelina Pencheva
Keyword(s):  
Air Quality ◽  
Value Added ◽  
Quality Data ◽  
Telemetry System ◽  
Application Layer ◽  
A Value ◽  
Novel Approach ◽  
Co2 Monitoring ◽  
Carbon Dioxide Co2 ◽  
Internet Of Things Technology

The research presents a novel approach to carbon dioxide (CO2) emissions monitoring and access to local air quality data. The approach applies the advanced Internet of things technology to design a mobile telemetry system for CO2 data collection and processing in order to be presented as a value-added application to mobile users. Based on requirements analysis, functional architecture for mobile telemetry system is proposed. The design aspects of mobile telemetry application layer protocol are studied. An approach to formal verification of protocol behavior is suggested. An information model that captures the basic concepts related to CO2 monitoring is proposed. Examples of ubiquitous access to CO2 measurements are described.

scholarly journals Assessment of parameters describing representativeness of air quality in-situ measurement sites

2010 ◽  
Vol 10 (8) ◽  
pp. 3561-3581 ◽  
Author(s):  
S. Henne ◽  
D. Brunner ◽  
D. Folini ◽  
S. Solberg ◽  
J. Klausen ◽  
...  
Keyword(s):  
Air Quality ◽  
Particle Dispersion ◽  
Surface Fluxes ◽  
Wind Fields ◽  
Mixing Ratios ◽  
Air Quality Measurements ◽  
Novel Approach ◽  
Variable Surface ◽  
Catchment Areas ◽  
Clustering Approach

Abstract. The atmospheric layer closest to the ground is strongly influenced by variable surface fluxes (emissions, surface deposition) and can therefore be very heterogeneous. In order to perform air quality measurements that are representative of a larger domain or a certain degree of pollution, observatories are placed away from population centres or within areas of specific population density. Sites are often categorised based on subjective criteria that are not uniformly applied by the atmospheric community within different administrative domains yielding an inconsistent global air quality picture. A novel approach for the assessment of parameters reflecting site representativeness is presented here, taking emissions, deposition and transport towards 34 sites covering Western and Central Europe into account. These parameters are directly inter-comparable among the sites and can be used to select sites that are, on average, more or less suitable for data assimilation and comparison with satellite and model data. Advection towards these sites was simulated by backward Lagrangian Particle Dispersion Modelling (LPDM) to determine the sites' average catchment areas for the year 2005 and advection times of 12, 24 and 48 h. Only variations caused by emissions and transport during these periods were considered assuming that these dominate the short-term variability of most but especially short lived trace gases. The derived parameters describing representativeness were compared between sites and a novel, uniform and observation-independent categorisation of the sites based on a clustering approach was established. Six groups of European background sites were identified ranging from generally remote to more polluted agglomeration sites. These six categories explained 50 to 80% of the inter-site variability of median mixing ratios and their standard deviation for NO2 and O3, while differences between group means of the longer-lived trace gas CO were insignificant. The derived annual catchment areas strongly depended on the applied LPDM and input wind fields, the catchment settings and the year of analysis. Nevertheless, the parameters describing representativeness showed considerably less variability than the catchment geometry, supporting the applicability of the derived station categorisation.

scholarly journals Corrigendum to "A novel downscaling technique for the linkage of global and regional air quality modeling" published in Atmos. Chem. Phys., 9, 9169–9185, 2009

2010 ◽  
Vol 10 (8) ◽  
pp. 4013-4031 ◽  
Author(s):  
Y. F. Lam ◽  
J. S. Fu
Keyword(s):  
Air Quality ◽  
Layer Structure ◽  
Atmospheric Model ◽  
Chem Phys ◽  
Regional Models ◽  
Global Atmospheric Model ◽  
Novel Approach ◽  
Vertical Variations ◽  
Regional Air Quality ◽  
Surface O3

Abstract. Recently, downscaling global atmospheric model outputs (GCTM) for the USEPA Community Multiscale Air Quality (CMAQ) Initial (IC) and Boundary Conditions (BC) have become practical because of the rapid growth of computational technologies that allow global simulations to be completed within a reasonable time. The traditional method of generating IC/BC by profile data has lost its advocates due to the weakness of the limited horizontal and vertical variations found on the gridded boundary layers. Theoretically, high quality GCTM IC/BC should yield a better result in CMAQ. Unfortunately, several researchers have found that the outputs from GCTM IC/BC are not necessarily better than profile IC/BC due to the excessive transport of O3 aloft in GCTM IC/BC. In this paper, we intend to investigate the effects of using profile IC/BC and global atmospheric model data. In addition, we are suggesting a novel approach to resolve the existing issue in downscaling. In the study, we utilized the GEOS-Chem model outputs to generate time-varied and layer-varied IC/BC for year 2002 with the implementation of tropopause determining algorithm in the downscaling process (i.e., based on chemical (O3) tropopause definition). The comparison between the implemented tropopause approach and the profile IC/BC approach is performed to demonstrate improvement of considering tropopause. It is observed that without using tropopause information in the downscaling process, unrealistic O3 concentrations are created at the upper layers of IC/BC. This phenomenon has caused over-prediction of surface O3 in CMAQ. In addition, the amount of over-prediction is greatly affected by temperature and latitudinal location of the study domain. With the implementation of the algorithm, we have successfully resolved the incompatibility issues in the vertical layer structure between global and regional chemistry models to yield better surface O3 predictions than profile IC/BC for both summer and winter conditions. At the same time, it improved the vertical O3 distribution of CMAQ outputs. It is strongly recommended that the tropopause information should be incorporated into any two-way coupled global and regional models, where the tropospheric regional model is used, to solve the vertical incompatibility that exists between global and regional models. We have discovered that the previously published paper was not the latest version of the manuscript we intended to use. Some corrections made during the second ACPD reviewing process were not incorporated in the text. As a result, the figure numbers (i.e., figure number below the graph) were not referenced correctly in the manuscript. Therefore, we have decided to re-publish this paper as a corrigendum.

scholarly journals Influence of a Biomass-Burning Event in PM2.5 Concentration and Air Quality: A Case Study in the Metropolitan Area of São Paulo

Sensors ◽  
2021 ◽  
Vol 21 (2) ◽  
pp. 425
Author(s):  
Gregori de Arruda Moreira ◽  
Izabel da Silva Andrade ◽  
Alexandre Cacheffo ◽  
Fábio Juliano da Silva Lopes ◽  
Alexandre Calzavara Yoshida ◽  
...  
Keyword(s):  
Air Quality ◽  
Biomass Burning ◽  
Metropolitan Area ◽  
Sao Paulo ◽  
Aerosol Layer ◽  
São Paulo ◽  
Air Masses ◽  
Novel Approach ◽  
Quality Classification ◽  
Entrainment Process

Severe biomass burning (BB) events have become increasingly common in South America in the last few years, mainly due to the high number of wildfires observed recently. Such incidents can negatively influence the air quality index associated with PM2.5 (particulate matter, which is harmful to human health). A study performed in the Metropolitan Area of São Paulo (MASP) took place on selected days of July 2019, evaluated the influence of a BB event on air quality. Use of combined remote sensing, a surface monitoring system and data modeling and enabled detection of the BB plume arrival (light detection and ranging (lidar) ratio of (50 ± 34) sr at 532 nm, and (72 ± 45) sr at 355 nm) and how it affected the Ångström exponent (>1.3), atmospheric optical depth (>0.7), PM2.5 concentrations (>25 µg.m−3), and air quality classification. The utilization of high-order statistical moments, obtained from elastic lidar, provided a new way to observe the entrainment process, allowing understanding of how a decoupled aerosol layer influences the local urban area. This new novel approach enables a lidar system to obtain the same results as a more complex set of instruments and verify how BB events contribute from air masses aloft towards near ground ones.

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