Emission reduction strategies to control tropospheric ozone: a multi-objective optimization approach

Electric vehicles (EVs) can play an important role in improving the European Union’s (EU)’s energy supply security, reducing the environmental impact of transport, and increasing EU competitiveness. The EU aims at fostering the synchronised deployment of EVs and necessary recharging infrastructure. There is currently a lack of studies in the literature for analysing the societal impacts of EV and infrastructure deployment at continental scale. In our paper, we analyse the likely impact of related plans of the EU member states (MSs). With the help of qualitative and quantitative analyses, we study the impact of plans on recharging infrastructure deployment, contributions to the EU climate and energy goals, air quality objectives, and reinforcement of the EU’s competitiveness and job creation. We soft-link a fleet impact model with a simplified source receptor relationship model, and propose a new model to calculate job impacts. The results overall show modest impacts by 2020, as most member states’ plans are not very ambitious. According to our analysis of the plans, a reduction of CO2 emissions by 0.4%, NOx emissions by 0.37%, and PM2.5 emissions by 0.44%, as well as a gross job creation of more than 8000 jobs will be achieved by 2020. The member state plans are very divergent. For countries with more ambitious targets up to 2020, such as Austria, France, Germany, and Luxemburg, the climate, energy, and air quality impacts are significant and show what would be achievable if the EU would increase its pace of EV and infrastructure deployment. We conclude that more ambitious efforts by the member states’ to deploy electric vehicles could accelerate the reduction of CO2 emissions and lead to less dependence on fossil oil-based fuels, along with air quality improvements, while at the same time creating new job opportunities in Europe. In regards to the ratio of publicly accessible recharging points (RPs) per EV, we conclude that member states have to come up with more ambitious targets for recharging point deployment, as the current plans will lead to only one recharging point per every 20 EVs by 2020 across the EU. This paper can serve as useful input to the further the planning of EV and recharging infrastructure deployment in the EU and elsewhere. Our study highlights that the different strategies that are followed in the EU member states can be a fertile ground to identify best practices. It remains a challenge to quantify how different support policies impact EV deployment. In terms of further research needs, we identify that more detailed studies are required to determine an appropriate level of infrastructure deployment, including fast chargers.

Sensitivity analysis to precursor emissions of multi-objective air quality control policies

Canada is now considering recommendations of the Federal-Provincial Working Group on Air Quality Objectives and Guidelines to adopt objectives for fine particulates that will be among the most stringent anywhere in the world and that may be technically unobtainable in the short term. No Canadian city would be in compliance at this time if these objectives were adopted. The fine particulate issue is also driving a fundamental change in the way that Canada harmonizes regulations on air pollution. In the United States, standards are set by the federal government for implementation by the states; the federal government has primacy. These standards are mandatory as a minimum level of control, although states may impose more stringent standards. By contrast, in the Canadian system the federal government does not have primacy and environmental protection at the local level is mandated to provincial governments. Canada has chosen to set guidelines negotiated between the federal government and representatives of provincial governments, in the expectation that these guidelines will influence the individual provinces to adopt similar standards. The role of guidelines, as opposed to standards, is to drive voluntary change and to influence public opinion. In the past, these guidelines were set to be more stringent than U.S. National Ambient Air Quality Standards and reflected the reality that urban air pollution levels in most large Canadian cities were generally lower than their U.S. counterparts. In 1997, a new process was initiated to bring the development of recommended air quality criteria into a more scientific formulation. National Ambient Air Quality Objectives will now be developed in a more transparent, accountable and science-based process. They will also be recommended rather than mandated but as objectives will carry the expectation that all jurisdictions in Canada will eventually harmonize their own standards to these norms. The first two objectives under this new process are fine particulates and ozone. For the purpose of this discussion, we shall confine our remarks to fine particulates. A large body of evidence was compiled into a report 1 that constituted the briefing document for a Stakeholder Consultation Workshop convened by the Atmospheric Environment Service of Environment Canada in December 1997. Included in this dossier was the report of the Federal Provincial Working Group recommending new air quality objectives for fine particulates. 2 The implication of these recommendations was staggering. Based on their reading of the available evidence, and driven primarily by estimates of lives saved through reductions in mortality associated with fine particulate levels in urban areas, the Federal Provincial Working Group recommended an objective for PM 10 of a 24hour average concentration of 40 µg/m 3 and for PM 2.5 of 20 µg/m 3 . This compares with the U.S. Environmental Protection Agency’s (EPA’s) previously proposed (now remanded) National Ambient Air Quality Standard of U.S. 24-hour averages of 150 and 65 µg/m 3 , respectively. Canada would have no equivalent to the previously proposed U.S. annual averages of 50 and 15 µg/m 3 , respectively, relying on the 24

Visibility is a perceptible indicator of air pollution, so it is hardly surprising that it has been used to promote the regulation of air pollutants. In Hong Kong, poor visibility associated with air pollution has been linked with changes in tourist choices and health outcomes. Much research is available to examine the early deterioration of visibility in the city, and especially its relation to particulate sulfate. The period 2004–2012 saw especially poor visibility in Hong Kong and coincided with a time when pollutant levels were high. There is a reasonable correlation (multiple r2 = 0.57) between the monthly hours of low visibility (<8 km) and PM10, NO2, SO2, and O3 concentrations from the late 1990s. Visibility can thus be justified as a route to perceiving air pollution. Over the last decade, visibility has improved and average pollutant concentrations have declined in Hong Kong. The changing health risk from individual pollutants parallels their concentration trends: the risk from NO2 and particulate matter at urban sites has declined, but there have been increases in the health risks from ozone as its concentrations have risen across the region, although this is dominated by concentration increases at more rural sites. Since 2004, the frequency of search terms such as visibility, air pollution, and haze on Google has decreased in line with improved visibility. Despite positive changes to Hong Kong’s air quality, typically, the media representation and public perception see the situation as growing more severe, possibly because attention focuses on the air quality objectives in Hong Kong being less stringent than World Health Organisation guidelines. Policymakers increasingly need to account for the perceptions of stakeholders and acknowledge that these are not necessarily bound to measurements from monitoring networks. Improvements in air quality are hard won, but conveying the nature of such improvements to the public can be an additional struggle.

BackgroundAir quality is monitored at a local level in the UK as part of the Local Air Quality Management (LAQM) system. If air quality objectives within an area are not achieved an Air Quality Management Area (AQMA) is declared and action plan developed. The efficacy of this system in reducing air pollution has increasingly come into question, however very little is known about its impact on health or health inequalities. We therefore investigated the effect of declaring an AQMA on emergency hospitalisations for respiratory conditions in the North West Coast region of England, and examined whether the effect differed between more compared to less deprived neighbourhoods.MethodsThis longitudinal controlled ecological study analysed neighbourhoods located within or touching the boundaries of AQMAs declared in the North West Coast region between 2006 and 2016. Each of these intervention neighbourhoods were matched with five control neighbourhoods which had never been located within/touching an AQMA boundary. Difference-in-differences methods were used to compare the change in hospitalisation rates in the intervention neighbourhoods to the change in hospitalisation rates in the matched control neighbourhoods, before and after the declaration of an AQMA.ResultsIn total, 108 intervention neighbourhoods and 540 control neighbourhoods were analysed over the period 2005–2017, giving a total sample size of 8424 neighbourhood-years. Emergency hospitalisations for respiratory conditions decreased in the intervention neighbourhoods by 158 per 100,000 per year [95% CI 90 to 227] after an AQMA was declared relative to the control neighbourhoods. There was a larger decrease in hospitalisation rates following the declaration of an AQMA in more compared to less income deprived neighbourhoods.ConclusionsOur results suggest the LAQM system has contributed to a reduction in emergency hospitalisations for respiratory conditions, and may represent an effective strategy to reduce inequalities in health. These findings highlight the importance of measuring the success of air quality policies not just in terms of air pollution but also in terms of population health.

Urban scale integrated assessment of options to reduce PM10 in London towards attainment of air quality objectives

The Regional Deterministic Air Quality Analysis (RDAQA) is a mapping of surface air pollutant concentration which combines numerical forecasts from the Regional Air Quality Deterministic Prediction System (RAQDPS) and hourly AQ observational data from monitoring surface networks over North America. These include Canadian measurement networks operated by the provinces, territories, and some municipalities and those networks covering the continental United States under the umbrella of EPA’s national AIRNow program. The model forecasts and observations are combined based on an optimal interpolation algorithm. The current RDAQA has a horizontal spatial resolution of 10 km and is issued every hour. It provides our best knowledge of the current state of the atmosphere for surface pollutant concentration for chemical species like: ozone, NO2, NO, SO2, PM2.5 , PM10. The RDAQA also provide a mapping of the Air Quality Health Index (AQHI) in quasi-real time and can be used by meteorologists in Environment Canada’s regional forecast offices to inform the public on a daily basis about the health risk associated to short term exposure to air pollution. The RDAQA products available over an extended period of time can also be used by Health Canada and health consortium partners to study how Air Quality and other multiple environmental factors are linked to a wide range of health outcomes. A description of the RDAQA will be presented as well as data access and future plans.

Abstract. This paper presents an exploratory study on the aerosol layer height (ALH) retrieval from the OMI 477 nm O2 − O2 spectral band. We have developed algorithms based on the multilayer perceptron (MLP) neural network (NN) approach and applied them to 3-year (2005–2007) OMI cloud-free scenes over north-east Asia, collocated with MODIS Aqua aerosol product. In addition to the importance of aerosol altitude for climate and air quality objectives, our long-term motivation is to evaluate the possibility of retrieving ALH for potential future improvements of trace gas retrievals (e.g. NO2, HCHO, SO2) from UV–visible air quality satellite measurements over scenes including high aerosol concentrations. This study presents a first step of this long-term objective and evaluates, from a statistic point of view, an ensemble of OMI ALH retrievals over a long time period of 3 years covering a large industrialized continental region. This ALH retrieval relies on the analysis of the O2 − O2 slant column density (SCD) and requires an accurate knowledge of the aerosol optical thickness, τ. Using MODIS Aqua τ(550 nm) as a prior information, absolute seasonal differences between the LIdar climatology of vertical Aerosol Structure for space-based lidar simulation (LIVAS) and average OMI ALH, over scenes with MODIS τ(550 nm) ≥ 1. 0, are in the range of 260–800 m (assuming single scattering albedo ω0 = 0. 95) and 180–310 m (assuming ω0 = 0. 9). OMI ALH retrievals depend on the assumed aerosol single scattering albedo (sensitivity up to 660 m) and the chosen surface albedo (variation less than 200 m between OMLER and MODIS black-sky albedo). Scenes with τ ≤ 0. 5 are expected to show too large biases due to the little impact of particles on the O2 − O2 SCD changes. In addition, NN algorithms also enable aerosol optical thickness retrieval by exploring the OMI reflectance in the continuum. Comparisons with collocated MODIS Aqua show agreements between −0. 02 ± 0. 45 and −0. 18 ± 0. 24, depending on the season. Improvements may be obtained from a better knowledge of the surface albedo and higher accuracy of the aerosol model. Following the previous work over ocean of Park et al.(2016), our study shows the first encouraging aerosol layer height retrieval results over land from satellite observations of the 477 nm O2 − O2 absorption spectral band.

The relationship between the emission of ozone precursors and the chemical production of tropospheric ozone (O3) in the Pearl River Delta Region (PRD) was studied using numerical simulation. The aim of this study was to examine the volatile organic compound (VOC)- or nitrogen oxide (NOx =NO+NO2)-limited conditions at present and when surface temperature is increasing due to global warming, thus to make recommendations for future ozone abatement policies for the PRD region. The model used for this application is the U.S. Environmental Protection Agency’s (EPA’s) third-generation air-quality modeling system; it consists of the mesoscale meteorological model MM5 and the chemical transport model named Community Multi-scale Air Quality (CMAQ). A series of sensitivity tests were conducted to assess the influence of VOC and NOx variations on ozone production. Tropical cyclone was shown to be one of the important synoptic weather patterns leading to ozone pollution. The simulations were based on a tropicalcyclone-related episode that occurred during 14–16 September 2004. The results show that, in the future, the control strategy for emissions should be tightened. To reduce the current level of ozone to meet the Hong Kong Environmental Protection Department (EPD) air-quality objective (hourly average of 120 ppb), emphasis should be put on restricting the increase of NOx emissions. Furthermore, for a wide range of possible changes in precursor emissions, temperature increase will increase the ozone peak in the PRD region; the areas affected by photochemical smog are growing wider, but the locations of the ozone plume are rather invariant.

Assessment and prediction of the impact of road transport on ambient concentrations of particulate matter PM10

Surrogate models to compute optimal air quality planning policies at a regional scale

Optimizing the utilization of harvested wood products for maximum greenhouse gas emission reduction in a bioeconomy: A multi-objective optimization approach

The use of modeling to support environmental authorities to plan air quality control policies is now quite widespread in different parts of Europe. At the sub-national level the most common way to face the problem is through the scenario analysis approach, using Chemical Transport Models to assess the impact of emission reductions on pollution concentrations. In this paper a multi-objective approach to define air quality policies is proposed. The considered objective function is a vector including an Air Quality Index and an Internal Costs Index. In this work the Air Quality Index (AQI) is the yearly mean PM10 concentration over the study domain. It is estimated processing source-receptor models linking emission and concentrations over the domain cells, taking into account nonlinear phenomena and using Artificial Neural Networks (ANNs). The ExternE methodology is then applied to estimate health impacts and external costs of optimal control policies up to 2020. The data used to identify the source-receptor models has been provided by a set of 10 simulations computed through the TCAM (Transport Chemical Aerosol) model. The Internal Cost Index (CI) describes the costs to implement a particular emission reduction policy. This index is computed by means of ANNs linking emission reductions and their relative implementation costs, for different CORINAIR macro sectors. Simulations with IIASA’s GAINS model have been used to calibrate the emission-to-cost model. The solutions of the decision problem represent cost-effective policies at the sectoral level. The methodology is applied to Northern Italy, one of the most polluted areas in Europe, to select optimal control policies up to 2020.KeywordsIntegrated assessment modelsMulti-objective problem

Multi-criteria analysis for PM10 planning

Assessment of the effect of meteorological and emission variations on winter PM2.5 over the North China Plain in the three-year action plan against air pollution in 2018–2020