Optimal air quality policies and health: a multi-objective nonlinear approach

Relvas, Hélder; Miranda, Ana Isabel; Carnevale, Claudio; Maffeis, Giuseppe; Turrini, Enrico; Volta, Marialuisa

doi:10.1007/s11356-017-8895-7

Cited by 32 publications

(16 citation statements)

References 20 publications

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“…One notable difference is the higher respiratory diseases hospitalisation in this dust event (161) compared to fire event (24). There are a number of air quality management plan such as Action for Air in NSW or various air quality plans in many places in the world using tools such as the Regional Integrated Assessment Tool (RIAT+) to deal with anthropogenic emission [59]. However, the ability to improve the prediction or forecast of events such as dust storms can significantly increase the accuracy and ability to assess the health impact on exposed population and hence can allow the policy makers in environment and health organisation to formulate and implement procedures to minimize the exposure and associated health impact when dust storm events are forecasted.…”

Section: Discussionmentioning

confidence: 99%

Dust Transport from Inland Australia and its Impact on Air Quality and Health on the Eastern Coast of Australia during the February 2019 Dust Storm.

Aragnou¹,

Watt²,

H.³

et al. 2020

Preprint

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Dust storms originating from Central Australia and western New South Wales frequently cause high particles concentration at many sites across New South Wales, both inland and along the coast. This study focussed on a dust storm event in February 2019 which affect air quality across the state as detected at many ambient monitoring stations in the Department of Planning, Industry and Environment (DPIE) air quality monitoring network. The WRF-Chem (Weather Research and Forecast Model – Chemistry) model is used to study the formation, dispersion and transport of dust across the state of New South Wales (NSW, Australia). Wildfires also happened in northern NSW at the same time of the dust storm in February 2019, and their emissions are taken into account in WRF-Chem model by using Fire Inventory from NCAR (FINN) as emission input. The model performance is evaluated and is shown to predict fairly accurate the PM2.5 and PM10 concentration as compared to observation. The predicted PM2.5 concentration over New South Wales during 5 days from 11 to 15 February 2019 is then used to estimate the impact of the February 2019 dust storm event on three health endpoints namely mortality, respiratory and cardiac diseases hospitalisation rates. The results show that even though as the daily average of PM2.5 over some parts of the state, especially in western and north western NSW near the centre of the dust storm and wild fires, are very high (over 900 µg/m3), the population exposure is low due to the sparse population. The top five Statistical Area Level 4 regions with the most impact in term of mortality, respiratory diseases hospitalisation and cardiac disease hospitalisation are Far West and Orana, Newcastle and Lake Macquarie, New England and North West, Sydney – Inner South West and either Central Coast (mortality) or Sydney – Parramatta (respiratory diseases hospitalisation) or Sydney – Inner West (cardiac diseases hospitalisation). Generally, the health impact is similar in order of magnitude to that caused by biomass burnings events from wildfires or from hazardous reduction burnings (HRBs) near populous centres such as in Sydney in May 2016. One notable difference is the higher respiratory diseases hospitalisation for this dust event (161) compared to fire event (24).

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Section: Discussionmentioning

confidence: 99%

Dust Transport from Inland Australia and its Impact on Air Quality and Health on the Eastern Coast of Australia during the February 2019 Dust Storm.

Aragnou¹,

Watt²,

H.³

et al. 2020

Preprint

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“…Using this approach, a set of abatement measures is first defined by a panel of experts and stakeholders, and its impact is then assessed through the application of a chemical and transport model, with the possibility of modifying the proposed set of measures if they are deemed unsatisfactory under certain viewpoints. (2) The optimization approach includes the multi-objective analysis [14][15][16][17], a cost-benefit analysis [18]; [19], and a cost-effective analysis [20][21][22]. This means that a set of objectives must be defined a priori by a panel of experts and stakeholders, and an automatic algorithm will then determine the set of efficient measures to be implemented.…”

Section: Air Quality Plans: the European State Of The Artmentioning

confidence: 99%

Assessing the Economic and Environmental Sustainability of a Regional Air Quality Plan

Carnevale

Ferrari²,

Guariso

et al. 2018

Sustainability

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Air quality plans must be demonstrated to be economically sustainable and environmentally effective. This paper presents a full cost–benefit and environmental analysis of a large regional air quality plan involving several different actions covering a large spectrum of fields, from domestic heating to passenger and freight transport, from electricity generation to agriculture. The impact of each action is analyzed looking at the possible energy savings, greenhouse gases (GHG) emission reductions, the improvement in air quality, and the consequent decrease in external costs, namely the reduced impact on population health. The analysis is performed by applying a flexible and fast computer tool (RIAT+) that allows for a rapid simulation of different pollutant emission scenario, to assess different air quality indices (AQIs) over a regional scale domain. The results show that, in most cases, the economic savings exceed the implementation costs and thus that these actions can be introduced in air quality plans for the domain under study. The reduced health and climate costs, though relevant in absolute terms, are, in general, only a fraction of the economic benefits of energy savings. This is not true for the measures acting on improvements in electricity generation, since a reduction in power plant emissions (generally with high stacks, far from populated areas) does not significantly impact the air quality inside the region. A shift in energy production to renewable sources can instead provide noticeable effects on GHG emissions. This research raises some interesting and general questions about the adequacy of the methodologies applied to attribute costs (and benefits) to actions, improving a variety of sectors that are different from the one in which the measures are applied here.

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“…In the last decades, a number of decision-support systems has been developed [4] in order to help regional and local authorities to reach this objective. Even if in literature there is plenty of support systems developed to define long term plans for the pollutant exposure reduction [5][6][7][8], the formalization and implementation of decision support systems to develop short term plan is still in its infancy. The core of these systems formalization and development is the air quality forecasting model, needed to accurately reproduce the dynamics of the phenomena related to the formation, accumulation and removal of pollutants in the atmosphere.…”

Section: Introductionmentioning

confidence: 99%

Application of Data Fusion Techniques to Improve Air Quality Forecast: A Case Study in the Northern Italy

Carnevale¹,

Angelis²,

Finzi³

et al. 2020

Atmosphere

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Deterministic air quality forecasting models play a key role for regional and local authorities, being key tools to ensure that timely information about actual or near future exceedances of pollutant threshold values are provided to the public, as stated by the EU directive (2008/50/EC). One of the main problems of these models is that they usually underestimate some important pollutants, like PM10, especially in high-concentration areas. For this reason, the forecast of critical episodes (i.e., exceedance of 50 μ g/m 3 for PM10 concentration daily threshold) has low accuracy. To overcome this issue, several computationally fast techniques have been implemented in the last decade. In this work, two computational fast techniques are introduced, implemented and evaluated. The techniques are based on the off-line correction of the chemical transport model output in the forecasting window, estimated by means of the measurement data up to the beginning of the forecast. In particular, the techniques are based on the estimation of the correction performed as a linear combination of the corrections computed for the days when the measurements are available. The resulting system has been applied to the Lombardy region case (Northern Italy) for daily PM10 forecasting with good results.

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Optimal air quality policies and health: a multi-objective nonlinear approach

Cited by 32 publications

References 20 publications

Dust Transport from Inland Australia and its Impact on Air Quality and Health on the Eastern Coast of Australia during the February 2019 Dust Storm.

Dust Transport from Inland Australia and its Impact on Air Quality and Health on the Eastern Coast of Australia during the February 2019 Dust Storm.

Assessing the Economic and Environmental Sustainability of a Regional Air Quality Plan

Application of Data Fusion Techniques to Improve Air Quality Forecast: A Case Study in the Northern Italy

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