scholarly journals Source apportionment to support air quality planning: Strengths and weaknesses of existing approaches

2019 ◽  
Vol 130 ◽  
pp. 104825 ◽  
Author(s):  
P. Thunis ◽  
A. Clappier ◽  
L. Tarrason ◽  
C. Cuvelier ◽  
A. Monteiro ◽  
...  
Keyword(s):  
Air Quality ◽  
Source Apportionment ◽  
Quality Planning ◽  
Air Quality Planning

scholarly journals Source Apportionment and Integrated Assessment Modelling for Air Quality Planning

Electronics ◽  
2020 ◽  
Vol 9 (7) ◽  
pp. 1098
Author(s):  
Elena De Angelis ◽  
Claudio Carnevale ◽  
Enrico Turrini ◽  
Marialuisa Volta
Keyword(s):  
Air Quality ◽  
Source Apportionment ◽  
Integrated Assessment ◽  
Road Transport ◽  
Northern Italy ◽  
Optimization Approach ◽  
Quality Planning ◽  
Residential Heating ◽  
Integrated Assessment Modelling ◽  
Air Quality Planning

In Northern Italy a large fraction of the population is exposed to PM10 and PM2.5 concentrations that exceed the European limit values and the stricter WHO air quality guidelines. For this reason, in 2017 four Regions (Piemonte, Lombardia, Veneto, and Emilia Romagna) and the national Ministry of the Environment adopted a set of joint measures, namely the “Po Basin air quality plan”. The plan mainly tackles emission from road transport, residential heating, and agriculture. Air quality plans at regional and local scale are usually implemented defining a set of emission abatement measures, starting from experts’ knowledge. The aim of this work is to define a methodology that helps decision makers in air quality planning, combining two different approaches: Source-Apportionment techniques (SA) and Integrated Assessment Modelling (IAM). These techniques have been applied over a domain in Northern Italy to analyze the contribution of emission sources on PM10 concentration and to compute an optimal policy, obtained through a multi-objective optimization approach that minimizes both the PM10 yearly average concentration and the policy implementation costs. The results are compared to the Po Basin air quality plan impacts. The source-apportionment technique and the IAM optimization approach show intervention priorities in three main sectors: residential heating, agriculture, and road transport. The Po Basin air quality plan is effective in reducing PM10 concentrations, but not efficient, as a matter of fact the cost-effective policy at the same cost has a higher impact on air quality and on greenhouse gases emissions reduction.

An Agricultural Air Quality Planning Tool for Conservation Planners

2007 ◽  
Author(s):  
Greg Johnson ◽  
Greg Zwicke ◽  
Susan O'Neill ◽  
Roel Vining
Keyword(s):  
Air Quality ◽  
Planning Tool ◽  
Quality Planning ◽  
Air Quality Planning

The use of regional economic models in air quality planning

1995 ◽  
Vol 18 (1) ◽  
pp. 119-148 ◽  
Author(s):  
Teresa M. Lynch ◽  
Phil J. Marsosudiro ◽  
Mark G. Smith ◽  
E. Sue Kimbrough
Keyword(s):  
Air Quality ◽  
Economic Models ◽  
Regional Economic ◽  
Quality Planning ◽  
Air Quality Planning

scholarly journals Air Quality Planning and the Minimization of Negative Externalities

Resources ◽  
2019 ◽  
Vol 8 (1) ◽  
pp. 15 ◽  
Author(s):  
Marco Ravina ◽  
Deborah Panepinto ◽  
Mariachiara Zanetti
Keyword(s):  
Air Quality ◽  
Urban Areas ◽  
District Heating ◽  
Heating System ◽  
Negative Externalities ◽  
District Heating System ◽  
Quality Planning ◽  
Air Quality Planning ◽  
The Impact

The minimization of negative externalities is a key aspect in the development of a circular and sustainable economic model. At the local scale, especially in urban areas, externalities are generated by the adverse impacts of air pollution on human health. Local air quality policies and plans often lack of considerations and instruments for the quantification and evaluation of external health costs. Support for decision-makers is needed, in particular during the implementation stage of air quality plans. Modelling tools based on the impact pathway approach can provide such support. In this paper, the implementation of health impacts and externalities analysis in air quality planning is evaluated. The state of the art in European member states is reported, considering whether and how health effects have been included in the planning schemes. The air quality plan of the Piemonte region in Italy is then considered. A case study is analyzed to evaluate a plan action, i.e., the development of the district heating system in the city of Turin. The DIATI (Dipartimento di Ingegneria dell’Ambiente, del Territorio e delle Infrastrutture) Dispersion and Externalities Model (DIDEM model) is applied to detect the scenario with the highest external cost reduction. This methodology results are extensible and adaptable to other actions and measures, as well as other local policies in Europe. The use of health externalities should be encouraged and integrated into the present methodology supporting air quality planning. Efforts should be addressed to quantify and minimize the overall uncertainty of the process.

scholarly journals Source apportionment and sensitivity analysis: two methodologies with two different purposes

2017 ◽  
Vol 10 (11) ◽  
pp. 4245-4256 ◽  
Author(s):  
Alain Clappier ◽  
Claudio A. Belis ◽  
Denise Pernigotti ◽  
Philippe Thunis
Keyword(s):  
Sensitivity Analysis ◽  
Source Apportionment ◽  
Direct Method ◽  
Brute Force ◽  
Quality Planning ◽  
Source Contributions ◽  
Complex Models ◽  
Air Quality Planning ◽  
The Impact ◽  
The Relationship

Abstract. This work reviews the existing methodologies for source apportionment and sensitivity analysis to identify key differences and stress their implicit limitations. The emphasis is laid on the differences between source impacts (sensitivity analysis) and contributions (source apportionment) obtained by using four different methodologies: brute-force top-down, brute-force bottom-up, tagged species and decoupled direct method (DDM). A simple theoretical example to compare these approaches is used highlighting differences and potential implications for policy. When the relationships between concentration and emissions are linear, impacts and contributions are equivalent concepts. In this case, source apportionment and sensitivity analysis may be used indifferently for both air quality planning purposes and quantifying source contributions. However, this study demonstrates that when the relationship between emissions and concentrations is nonlinear, sensitivity approaches are not suitable to retrieve source contributions and source apportionment methods are not appropriate to evaluate the impact of abatement strategies. A quantification of the potential nonlinearities should therefore be the first step prior to source apportionment or planning applications, to prevent any limitations in their use. When nonlinearity is mild, these limitations may, however, be acceptable in the context of the other uncertainties inherent to complex models. Moreover, when using sensitivity analysis for planning, it is important to note that, under nonlinear circumstances, the calculated impacts will only provide information for the exact conditions (e.g. emission reduction share) that are simulated.

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