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Indian cities, and the megacity of Delhi in particular, have suffered from high air pollution for years. Recent observations show that ambient concentrations of fine particulate matter (PM2.5) in Delhi strongly exceed the Indian national ambient air quality standards as well as the World Health Organization's interim target levels. At the same time, India is experiencing strong urbanization, and both Delhi's emissions as well as the exposed population are growing. Therefore the question arises how PM2.5concentrations will evolve in the future, and how they can be improved efficiently. In the past, typical responses of the Delhi government to high pollution episodes have been restrictions on motorized road traffic, on power plant operations and on construction activities. However, to design sustainable and efficient pollution mitigation measures, the contribution of different source sectors and spatial scales needs to be quantified. Here we combine the established emission calculation scheme of the Greenhouse Gas - Air Pollution Interactions and Synergies (GAINS) model with regional chemistry-transport model simulations (0.5◦resolution) as well as local particle dispersion (2×2km resolution) to arrive at a source attribution of ambient PM2.5in Delhi. Calculated concentrations compare well to observations. We find that roughly 60% of total population-weightedPM2.5originates from sources outside the national capital territory of Delhi itself. Consequently, mitigation strategies need to involve neighboring states and address the typical sources there. We discuss the likely evolution of ambient concentrations under different scenarios which assume either current emission control legislation, or application of a Clean Air Scenario foreseeing additional regulations in non-industrial sectors which are often overlooked, such as phase-out of solid fuel cook stoves, and road paving. Only in the case where the Clean Air Scenario is applied both in Delhi as well as in surrounding states, a strong reduction in ambient concentrations is envisaged which would bring PM2.5levels close to the WHO interim targets.

Indian cities, and the megacity of Delhi in particular, have suffered from high air pollution for years. Recent observations show that ambient concentrations of fine particulate matter (PM2.5) in Delhi strongly exceed the Indian national ambient air quality standards as well as the World Health Organization's interim target levels. At the same time, India is experiencing strong urbanization, and both Delhi's emissions as well as the exposed population are growing. Therefore the question arises how PM2.5concentrations will evolve in the future, and how they can be improved efficiently. In the past, typical responses of the Delhi government to high pollution episodes have been restrictions on motorized road traffic, on power plant operations and on construction activities. However, to design sustainable and efficient pollution mitigation measures, the contribution of different source sectors and spatial scales needs to be quantified. Here we combine the established emission calculation scheme of the Greenhouse Gas - Air Pollution Interactions and Synergies (GAINS) model with regional chemistry-transport model simulations (0.5◦resolution) as well as local particle dispersion (2×2km resolution) to arrive at a source attribution of ambient PM2.5in Delhi. Calculated concentrations compare well to observations. We find that roughly 60% of total population-weightedPM2.5originates from sources outside the national capital territory of Delhi itself. Consequently, mitigation strategies need to involve neighboring states and address the typical sources there. We discuss the likely evolution of ambient concentrations under different scenarios which assume either current emission control legislation, or application of a Clean Air Scenario foreseeing additional regulations in non-industrial sectors which are often overlooked, such as phase-out of solid fuel cook stoves, and road paving. Only in the case where the Clean Air Scenario is applied both in Delhi as well as in surrounding states, a strong reduction in ambient concentrations is envisaged which would bring PM2.5levels close to the WHO interim targets.

NO 2 concentrations at the street level are a major concern for urban air quality in Europe and have been regulated under the EU Thematic Strategy on Air Pollution. Despite the legal requirements, limit values are exceeded at many monitoring stations with little or no improvement in recent years. In order to assess the effects of future emission control regulations on roadside NO 2 concentrations, a downscaling module has been implemented in the GAINS integrated assessment model. The module follows a hybrid approach based on atmospheric dispersion calculations and observations from the AirBase European air quality database that are used to estimate site-specific parameters. Pollutant concentrations at every monitoring site with sufficient data coverage are disaggregated into contributions from regional background, urban increment, and local roadside increment. The future evolution of each contribution is assessed with a model of the appropriate scale: 28 × 28 km grid based on the EMEP Model for the regional background, 7 × 7 km urban increment based on the CHIMERE Chemistry Transport Model, and a chemical box model for the roadside increment. Thus, different emission scenarios and control options for long-range transport as well as regional and local emissions can be analysed. Observed concentrations and historical trends are well captured, in particular the differing NO 2 and total NO x = NO + NO 2 trends. Altogether, more than 1950 air quality monitoring stations in the EU are covered by the model, including more than 400 traffic stations and 70% of the critical stations. Together with its well-established bottom-up emission and dispersion calculation scheme, GAINS is thus able to bridge the scales from European-wide policies to impacts in street canyons. As an application of the model, we assess the evolution of attainment of NO 2 limit values under current legislation until 2030. Strong improvements are expected with the introduction of the Euro 6 emission standard for light duty vehicles; however, for some major European cities, further measures may be required, in particular if aiming to achieve compliance at an earlier time.

NO2 concentrations at the street level are a major concern for urban air quality in Europe and have been regulated under the EU Thematic Strategy on Air Pollution. Despite the legal requirements, limit values are exceeded at many monitoring stations with little or no improvement in recent years. In order to assess the effects of future emission control regulations on roadside NO2 concentrations, a downscaling module has been implemented in the GAINS integrated assessment model. The module follows a hybrid approach based on atmospheric dispersion calculations and observations from the AirBase European air quality database that are used to estimate site-specific parameters. Pollutant concentrations at every monitoring site with sufficient data coverage are disaggregated into contributions from regional background, urban increment, and local roadside increment. The future evolution of each contribution is assessed with a model of the appropriate scale: 28 x 28 km grid based on the EMEP Model for the regional background, 7 x 7 km urban increment based on the CHIMERE Chemistry Transport Model, and a chemical box model for the roadside increment. Thus, different emission scenarios and control options for long-range transport as well as regional and local emissions can be analysed. Observed concentrations and historical trends are well captured, in particular the differing NO2 and total NOx = NO + NO2 trends. Altogether, more than 1950 air quality monitoring stations in the EU are covered by the model, including more than 400 traffic stations and 70% of the critical stations. Together with its well-established bottom-up emission and dispersion calculation scheme, GAINS is thus able to bridge the scales from European-wide policies to impacts in street canyons. As an application of the model, we assess the evolution of attainment of NO2 limit values under current legislation until 2030. Strong improvements are expected with the introduction of the Euro 6 emission standard for light duty vehicles; however, for some major ...

NO2 concentrations at the street level are a major concern for urban air quality in Europe and have been regulated under the EU Thematic Strategy on Air Pollution. Despite the legal requirements, limit values are exceeded at many monitoring stations with little or no improvement in recent years. In order to assess the effects of future emission control regulations on roadside NO2 concentrations, a downscaling module has been implemented in the GAINS integrated assessment model. The module follows a hybrid approach based on atmospheric dispersion calculations and observations from the AirBase European air quality database that are used to estimate site-specific parameters. Pollutant concentrations at every monitoring site with sufficient data coverage are disaggregated into contributions from regional background, urban increment, and local roadside increment. The future evolution of each contribution is assessed with a model of the appropriate scale: 28 × 28 km grid based on the EMEP Model for the regional background, 7 × 7 km urban increment based on the CHIMERE Chemistry Transport Model, and a chemical box model for the roadside increment. Thus, different emission scenarios and control options for long-range transport as well as regional and local emissions can be analysed. Observed concentrations and historical trends are well captured, in particular the differing NO2 and total NOx = NO + NO2 trends. Altogether, more than 1950 air quality monitoring stations in the EU are covered by the model, including more than 400 traffic stations and 70% of the critical stations. Together with its well-established bottom-up emission and dispersion calculation scheme, GAINS is thus able to bridge the scales from European-wide policies to impacts in street canyons. As an application of the model, we assess the evolution of attainment of NO2 limit values under current legislation until 2030. Strong improvements are expected with the introduction of the Euro 6 emission standard for light duty vehicles; however, for some major European cities, further measures may be required, in particular if aiming to achieve compliance at an earlier time.

NO2 concentrations at the street level are a major concern for urban air quality in Europe and have been regulated under the EU Thematic Strategy on Air Pollution. Despite the legal requirements, limit values are exceeded at many monitoring stations with little or no improvement in recent years. In order to assess the effects of future emission control regulations on roadside NO2 concentrations, a downscaling module has been implemented in the GAINS integrated assessment model. The module follows a hybrid approach based on atmospheric dispersion calculations and observations from the AirBase European air quality database that are used to estimate site-specific parameters. Pollutant concentrations at every monitoring site with sufficient data coverage are disaggregated into contributions from regional background, urban increment, and local roadside increment. The future evolution of each contribution is assessed with a model of the appropriate scale: 28 x 28 km grid based on the EMEP Model for the regional background, 7 x 7 km urban increment based on the CHIMERE Chemistry Transport Model, and a chemical box model for the roadside increment. Thus, different emission scenarios and control options for long-range transport as well as regional and local emissions can be analysed. Observed concentrations and historical trends are well captured, in particular the differing NO2 and total NOx = NO + NO2 trends. Altogether, more than 1950 air quality monitoring stations in the EU are covered by the model, including more than 400 traffic stations and 70% of the critical stations. Together with its well-established bottom-up emission and dispersion calculation scheme, GAINS is thus able to bridge the scales from European-wide policies to impacts in street canyons. As an application of the model, we assess the evolution of attainment of NO2 limit values under current legislation until 2030. Strong improvements are expected with the introduction of the Euro 6 emission standard for light duty vehicles; however, for some major European cities, further measures may be required, in particular if aiming to achieve compliance at an earlier time.

Despite increasing emission controls, particulate matter (PM) has remained a critical issue for European air quality in recent years. The various sources of PM, both from primary particulate emissions as well as secondary formation from precursor gases, make this a complex problem to tackle. In order to allow for credible predictions of future concentrations under policy assumptions, a modelling approach is needed that considers all chemical processes and spatial dimensions involved, from long-range transport of pollution to local emissions in street canyons. Here we describe a modelling scheme which has been implemented in the GAINS integrated assessment model to assess compliance with PM 10 (PM with aerodynamic diameter <10 μm) limit values at individual air quality monitoring stations reporting to the AirBase database. The modelling approach relies on a combination of bottom up modelling of emissions, simplified atmospheric chemistry and dispersion calculations, and a traffic increment calculation wherever applicable. At each monitoring station fulfilling a few data coverage criteria, measured concentrations in the base year 2009 are explained to the extent possible and then modelled for the past and future. More than 1850 monitoring stations are covered, including more than 300 traffic stations and 80% of the stations which exceeded the EU air quality limit values in 2009. As a validation, we compare modelled trends in the period 2000–2008 to observations, which are well reproduced. The modelling scheme is applied here to quantify explicitly source contributions to ambient concentrations at several critical monitoring stations, displaying the differences in spatial origin and chemical composition of urban roadside PM 10 across Europe. Furthermore, we analyse the predicted evolution of PM 10 concentrations in the European Union until 2030 under different policy scenarios. Significant improvements in ambient PM 10 concentrations are expected assuming successful implementation of already agreed legislation; however, these will not be large enough to ensure attainment of PM 10 limit values in hot spot locations such as Southern Poland and major European cities. Remaining issues are largely eliminated in a scenario applying the best available emission control technologies to the maximal technically feasible extent.

Despite increasing emission controls, particulate matter (PM) has remained a critical issue for European air quality in recent years. The various sources of PM, both from primary particulate emissions as well as secondary formation from precursor gases, make this a complex problem to tackle. In order to allow for credible predictions of future concentrations under policy assumptions, a modelling approach is needed that considers all chemical processes and spatial dimensions involved, from long-range transport of pollution to local emissions in street canyons. Here we describe a modelling scheme which has been implemented in the GAINS integrated assessment model to assess compliance with PM10 (PM with aerodynamic diameter <10 um) limit values at individual air quality monitoring stations reporting to the AirBase database. The modelling approach relies on a combination of bottom up modelling of emissions, simplified atmospheric chemistry and dispersion calculations, and a traffic increment calculation wherever applicable. At each monitoring station fulfilling a few data coverage criteria, measured concentrations in the base year 2009 are explained to the extent possible and then modelled for the past and future. More than 1850 monitoring stations are covered, including more than 300 traffic stations and 80% of the stations which exceeded the EU air quality limit values in 2009. As a validation, we compare modelled trends in the period 2000-2008 to observations, which are well reproduced. The modelling scheme is applied here to quantify explicitly source contributions to ambient concentrations at several critical monitoring stations, displaying the differences in spatial origin and chemical composition of urban roadside PM10 across Europe. Furthermore, we analyse the predicted evolution of PM10 concentrations in the European Union until 2030 under different policy scenarios. Significant improvements in ambient PM10 concentrations are expected assuming successful implementation of already agreed legislation; however, these will not be large enough to ensure attainment of PM10 limit values in hot spot locations such as Southern Poland and major European cities. Remaining issues are largely eliminated in a scenario applying the best available emission control technologies to the maximal technically feasible extent.

Despite increasing emission controls, particulate matter (PM) has remained a critical issue for European air quality in recent years. The various sources of PM, both from primary particulate emissions as well as secondary formation from precursor gases, make this a complex problem to tackle. In order to allow for credible predictions of future concentrations under policy assumptions, a modelling approach is needed that considers all chemical processes and spatial dimensions involved, from long-range transport of pollution to local emissions in street canyons. Here we describe a modelling scheme which has been implemented in the GAINS integrated assessment model to assess compliance with PM10 (PM with aerodynamic diameter <10 um) limit values at individual air quality monitoring stations reporting to the AirBase database. The modelling approach relies on a combination of bottom up modelling of emissions, simplified atmospheric chemistry and dispersion calculations, and a traffic increment calculation wherever applicable. At each monitoring station fulfilling a few data coverage criteria, measured concentrations in the base year 2009 are explained to the extent possible and then modelled for the past and future. More than 1850 monitoring stations are covered, including more than 300 traffic stations and 80% of the stations which exceeded the EU air quality limit values in 2009. As a validation, we compare modelled trends in the period 2000-2008 to observations, which are well reproduced. The modelling scheme is applied here to quantify explicitly source contributions to ambient concentrations at several critical monitoring stations, displaying the differences in spatial origin and chemical composition of urban roadside PM10 across Europe. Furthermore, we analyse the predicted evolution of PM10 concentrations in the European Union until 2030 under different policy scenarios. Significant improvements in ambient PM10 concentrations are expected assuming successful implementation of already agreed legislation; however, these will not be large enough to ensure attainment of PM10 limit values in hot spot locations such as Southern Poland and major European cities. Remaining issues are largely eliminated in a scenario applying the best available emission control technologies to the maximal technically feasible extent.

Despite increasing emission controls, particulate matter (PM) has remained a critical issue for European air quality in recent years. The various sources of PM, both from primary particulate emissions as well as secondary formation from precursor gases, make this a complex problem to tackle. In order to allow for credible predictions of future concentrations under policy assumptions, a modelling approach is needed that considers all chemical processes and spatial dimensions involved, from long-range transport of pollution to local emissions in street canyons. Here we describe a modelling scheme which has been implemented in the GAINS integrated assessment model to assess compliance with PM10 (PM with aerodynamic diameter <10 μm) limit values at individual air quality monitoring stations reporting to the AirBase database. The modelling approach relies on a combination of bottom up modelling of emissions, simplified atmospheric chemistry and dispersion calculations, and a traffic increment calculation wherever applicable. At each monitoring station fulfilling a few data coverage criteria, measured concentrations in the base year 2009 are explained to the extent possible and then modelled for the past and future. More than 1850 monitoring stations are covered, including more than 300 traffic stations and 80% of the stations which exceeded the EU air quality limit values in 2009. As a validation, we compare modelled trends in the period 2000–2008 to observations, which are well reproduced. The modelling scheme is applied here to quantify explicitly source contributions to ambient concentrations at several critical monitoring stations, displaying the differences in spatial origin and chemical composition of urban roadside PM10 across Europe. Furthermore, we analyse the predicted evolution of PM10 concentrations in the European Union until 2030 under different policy scenarios. Significant improvements in ambient PM10 concentrations are expected assuming successful implementation of already agreed legislation; however, these will not be large enough to ensure attainment of PM10 limit values in hot spot locations such as Southern Poland and major European cities. Remaining issues are largely eliminated in a scenario applying the best available emission control technologies to the maximal technically feasible extent.

Despite increasing emission controls, particulate matter (PM) has remained a critical issue for European air quality in recent years. The various sources of PM, both from primary particulate emissions as well as secondary formation from precursor gases, make this a complex problem to tackle. In order to allow for credible predictions of future concentrations under policy assumptions, a modelling approach is needed that considers all chemical processes and spatial dimensions involved, from long-range transport of pollution to local emissions in street canyons. Here we describe a modelling scheme which has been implemented in the GAINS integrated assessment model to assess compliance with PM10 (PM with aerodynamic diameter < 10 mu m) limit values at individual air quality monitoring stations reporting to the Air-Base database. The modelling approach relies on a combination of bottom up modelling of emissions, simplified atmospheric chemistry and dispersion calculations, and a traffic increment calculation wherever applicable. At each monitoring station fulfilling a few data coverage criteria, measured concentrations in the base year 2009 are explained to the extent possible and then modelled for the past and future. More than 1850 monitoring stations are covered, including more than 300 traffic stations and 80% of the stations which exceeded the EU air quality limit values in 2009. As a validation, we compare modelled trends in the period 2000-2008 to observations, which are well reproduced. The modelling scheme is applied here to quantify explicitly source contributions to ambient concentrations at several critical monitoring stations, displaying the differences in spatial origin and chemical composition of urban roadside PM10 across Europe. Furthermore, we analyse the predicted evolution of PM10 concentrations in the European Union until 2030 under different policy scenarios. Significant improvements in ambient PM10 concentrations are expected assuming successful implementation of already agreed legislation; ...

Despite increasing emission controls, particulate matter (PM) has remained a critical issue for European air quality in recent years. The various sources of PM, both from primary particulate emissions as well as secondary formation from precursor gases, make this a complex problem to tackle. In order to allow for credible predictions of future concentrations under policy assumptions, a modelling approach is needed that considers all chemical processes and spatial dimensions involved, from long-range transport of pollution to local emissions in street canyons. Here we describe a modelling scheme which has been implemented in the GAINS integrated assessment model to assess compliance with PM10 (PM with aerodynamic diameter < 10 mu m) limit values at individual air quality monitoring stations reporting to the Air-Base database. The modelling approach relies on a combination of bottom up modelling of emissions, simplified atmospheric chemistry and dispersion calculations, and a traffic increment calculation wherever applicable. At each monitoring station fulfilling a few data coverage criteria, measured concentrations in the base year 2009 are explained to the extent possible and then modelled for the past and future. More than 1850 monitoring stations are covered, including more than 300 traffic stations and 80% of the stations which exceeded the EU air quality limit values in 2009. As a validation, we compare modelled trends in the period 2000-2008 to observations, which are well reproduced. The modelling scheme is applied here to quantify explicitly source contributions to ambient concentrations at several critical monitoring stations, displaying the differences in spatial origin and chemical composition of urban roadside PM10 across Europe. Furthermore, we analyse the predicted evolution of PM10 concentrations in the European Union until 2030 under different policy scenarios. Significant improvements in ambient PM10 concentrations are expected assuming successful implementation of already agreed legislation; however, these will not be large enough to ensure attainment of PM10 limit values in hot spot locations such as Southern Poland and major European cities. Remaining issues are largely eliminated in a scenario applying the best available emission control technologies to the maximal technically feasible extent.

This study explores the impacts of alternative emission control interventions for international shipping on the European Seas on relevant air pollutant emissions, examines their consequence on ambient air quality in Europe and the neighbouring regions, and explores the resulting improvements of human health. It estimates the costs of the various policy interventions, and compares them with monetized benefits on human health and other impacts. It is found that further controls of SO₂ emissions, e.g., through SO₂ emission control areas, could deliver rather fast benefits, and avoid by 2030 up to 4000 cases of premature deaths annually, and 8000 in 2050. In the longer run, by 2050, application of Tier III NOx standards could double the health benefits. Even when using the lower (most conservative) health valuation, all reduction measures examined in this report emerged as cost-effective, with monetized benefits exceeding emission control costs typically by a factor of 6 in 2030 and by a factor of 12 in 2050. Designation of the Mediterranean Sea as an Emission Control Area could by 2030 cut emissions of SO2 and NOx from international shipping by 80 and 20 percent, respectively, compared to current legislation. These additional emission reductions could avoid 4,100 cases of premature deaths in 2030 and more than 10,000 annual premature deaths in 2050. Even with the most conservative assumptions for health valuation, monetized benefits are on average 4.4 times higher than the costs in 2030 and 7.5 times higher in 2050.

This study explores the impacts of alternative emission control interventions for international shipping on the European Seas on relevant air pollutant emissions, examines their consequence on ambient air quality in Europe and the neighbouring regions, and explores the resulting improvements of human health. It estimates the costs of the various policy interventions, and compares them with monetized benefits on human health and other impacts. It is found that further controls of SO₂ emissions, e.g., through SO₂ emission control areas, could deliver rather fast benefits, and avoid by 2030 up to 4000 cases of premature deaths annually, and 8000 in 2050. In the longer run, by 2050, application of Tier III NOx standards could double the health benefits. Even when using the lower (most conservative) health valuation, all reduction measures examined in this report emerged as cost-effective, with monetized benefits exceeding emission control costs typically by a factor of 6 in 2030 and by a factor of 12 in 2050. Designation of the Mediterranean Sea as an Emission Control Area could by 2030 cut emissions of SO2 and NOx from international shipping by 80 and 20 percent, respectively, compared to current legislation. These additional emission reductions could avoid 4,100 cases of premature deaths in 2030 and more than 10,000 annual premature deaths in 2050. Even with the most conservative assumptions for health valuation, monetized benefits are on average 4.4 times higher than the costs in 2030 and 7.5 times higher in 2050.

The fast economic and population growth in India's urban areas and the limited control of pollution are causing public health problems and significant environmental degradation, including air, water, land and greenhouse gases, which undermines the potential for sustainable socioeconomic development of the country, particularly with impacts on the poor. To improve air quality and enhance economic and social development, the Government of India has issued a National Ambient Air Quality Standard (NAAQS) for annual average PM2.5 concentrations of 40 �g/m3. However, this standard is widely exceeded, and according to the World Health Organisation (WHO), India was home to 13 out of the 15 most polluted cities worldwide in terms of PM2.5 concentrations in 2016. This study explores pathways towards achieving the NAAQS in India in the context of the dynamics of social and economic development up to 2050. For this purpose, we employ two well-established scientific modelling tools that explore the socio-economic drivers of pollution (the GCAM model), in particular, energy consumption, and the GAINS model that explores effective policy interventions to reduce population exposure and health impacts. We estimate that in 2015 more than half of the Indian population, i.e. about 670 million people, was exposed to ambient PM2.5 concentrations that do not comply with India's NAAQS, and less than 1% enjoyed air quality conforming with the global WHO guideline value of 10 �g/m3. Without further political action, this figure is not expected to improve. While the existing emission control measures are effectively decoupling the trends of air pollutant emissions from economic growth, their impacts on ambient air quality are not directly visible since they are compensated by the rapid expansion of economic activities. The analysis reveals that advanced technical emission controls can deliver air quality improvements in India, but will not be sufficient to achieve the NAAQS everywhere. However, a package of development and decarbonization measures that are usually taken for other policy priorities can deliver significant co-benefits on air quality and achieve compliance with NAAQS for the vast majority of the population.