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Cover photo: Huy Hùng – TTXVN Cover design and layout: Hong Nguyen – Vuong Hoang Table of Contents Acknowledgements  ix Abbreviations  xi Executive Summary  xii Chapter 1: Improving Air Quality in Hanoi and its Surrounding Areas  1 1.1 Air Quality in Hanoi and the Surrounding Areas  3 1.2 Air Pollution Control Policy in Hanoi, Bac Ninh, and Hung Yen and Link with Climate Change Mitigation  7 1.3 The Draft Power Development Plan 8 and Vietnam’s Nationally Determined Contribution 2020 and Air Quality Co-benefits of Climate Actions  8 Chapter 2: Designing Scenarios to Estimate Air Quality  11 2.1 The GAINS Model  12 2.2 Data Sources and Cost Calculations  13 2.3 Stakeholder Consultations and Data Validations  14 2.4 Scenario Design  14 Chapter 3: Understanding How Air Quality Improvements Can be Made  17 3.1 Understanding the Current Situation  17 3.1.1 Emissions of PM2.5 Precursor Substances  18 3.1.2 Validation  21 3.1.3 PM2.5 Source Contributions for Hanoi, Bac Ninh, and Hung Yen in the GAINS Model  21 3.2 Future Air Quality  23 3.2.1 Socioeconomic Development Trends  23 3.2.2 The Policies before 2020 Scenario  23 3.2.3 The New Policies in Effect from 2021 Along with NDC 2020 Scenarios 26 3.2.4 The Cost-effective Scenario to Reach the NAAQS PM2.5 Target  31 3.3 Emissions Scenarios and their Population Exposure and Costs Impacts  32 3.3.1 Emissions  32 3.3.2 Population Exposure  33 3.3.3 Emissions Control Costs  34 3.4 Determining Cost Effectiveness through Marginal Abatement Cost Curves for Selected Key Air Quality Measures  35 Table of Contents i Chapter 4: Clean Air for Hanoi by 2030: What Will it Take?  39 4.1 Key Sector Interventions  40 4.2 A Coordinated Regional and National Mechanism is Needed for Air Quality Management  40 4.3 Enforcement is Key  41 4.4 Monitoring, Reporting, and Validation of Emissions Reductions and Climate Finance Mobilization  44 Appendix A: A Note on Data Collection  45 References  51 List of Boxes Box 1.1 World Bank’s Country Climate and Development Report (CCDR) for Vietnam  8 Box 3.1 The Maximum Technically Feasible Reduction Scenario  29 Box 4.1 Examples of air quality actions around the world  42 List of Figures Figure ES.1 Annual mean concentrations of PM2.5 in Hanoi since 2015  ix Figure ES.2 Ambient concentrations and population exposure to PM2.5 modelled for 2015 xi Figure ES.3 Population-weighted annual mean source contributions of PM2.5 concentrations in Hanoi, 2015  xii Figure ES.4 Impact of polices on air quality standards by 2020 in Hanoi, Bac Ninh, and Hung Yen  xiv Figure 1.1 Explanation of Air Quality Index 3 Figure 1.2 Annual mean concentrations of PM2.5 in Hanoi since 2015 4 Figure 1.3 Daily PM2.5 concentrations measured at the NCEM urban traffic station and at the urban background station in Hanoi in 2019-2020 6 ii Clean Air for Hanoi: What Will it Take? Figure 1.4 72-hour backward trajectories estimating air pollution in Hanoi on November 19, 2019 7 Figure 3.1 PM2.5 emission inventory for 2015 18 Figure 3.2 Emissions of PM2.5 precursors in Hanoi, Bac Ninh, and Hung Yen, estimated in this study for 2015  19 Figure 3.3 Ambient concentrations and population exposure to PM2.5 modelled for 2015  20 Figure 3.4 GAINS estimate of source apportion­ ment for Hanoi, 2015-2019  21 Figure 3.5 Population-weighted annual mean source contributions of PM2.5 concentrations in Hanoi, 2015 22 Figure 3.6 Population-weighted annual mean source contributions of PM2.5 concentrations in Bac Ninh and Hung Yen provinces, 2015 22 Figure 3.7 Ambient concentrations and population exposure to PM2.5 in the policies before 2020 case in 2030 for Hanoi, Bac Ninh, and Hung Yen 24 Figure 3.8 Source attributions to population-weighted PM2.5 concentrations in the policies before 2020 projection in 2030 25 Figure 3.9 Ambient concentrations and population exposure to PM2.5 in 2030 for the policy scenarios considered in the analysis for Hanoi, Bac Ninh, and Hung Yen 27 Figure 3.10 Source contributions for Hanoi in 2030 28 Figure B3.1 Ambient concentrations of PM2.5 and population exposed to PM2.5 with the application of MTFR in the three provinces in 2030  29 Figure 3.11 Sources of PM2.5 concentrations (population-weighted annual mean) in Hanoi in 2030 32 Figure 3.12 Distribution of population exposed to ambient PM2.5 in Hanoi, Bac Ninh, and Hung Yen in 2015 and emissions scenarios for 2030  34 Figure 3.13 Initial estimate of additional air pollution control costs to meet national standards 35 Figure 3.14 Marginal abatement cost curve for transportation in Hanoi outlook by 2030 36 Figure 3.15 Marginal abatement cost curve for the industrial sector in Hanoi outlook by 2030 37 Figure A.1 Summary of sampling process with relevant data collection methods in the craft village survey  47 List of Maps Map 2.1 Regions in Vietnam that were included in this study  13 Table of Contents iii List of Tables Table ES.1 Overview of scenarios analyzed for this study  xiv Table ES.2 Policy options to reduce PM2.5 emissions from key sectors  xix Table 1.1 WHO updated targets for PM2.5  3 Table 1.2 Standards for basic factors of ambient air (μg/m3)  5 Table 1.3 Projected emissions from coal-fired thermal power plants as in draft PDP8 – selected scenario (tonnes)  9 Table 2.1 Overview of scenarios analyzed for this study  15 Table 4.1 Policy options to reduce PM2.5 emissions from key sectors  41 Table B4.1.1 Policies that promote the e-mobility transition  43 iv Clean Air for Hanoi: What Will it Take? Acknowledgements Clean Air for Hanoi: What Will it Take? was prepared by a core team from the World Bank led by Katelijn van den Berg (Senior Environmental Specialist) and Thu Thi Le Nguyen (Senior Environmental Specialist). Financing from the World Bank-administered Pollution Management and Environmental Health (PMEH) Multi-Donor Trust Fund is gratefully acknowledged to support the preparation of this report. The team from the International Institute for Applied System Analysis (IIASA) provided support on air quality modelling. The team was led by Zbigniew Klimont and included Gregor Kiesewetter, Wolfgang Schöpp, Adriana Gómez-Sanabria, Peter Rafaj, Jens Borken-Kleefeld, Fabian Wagner, Pallav Purohit, Parul Srivastava, Binh Nguyen, Robert Sander, Laura Warnecke, and Chris Heyes. Support on AERMOD modelling was led by Hoang Xuan Co and Kim Van Chinh from the Research Center for Environmental Monitoring and Modelling in Vietnam. The RCEE-NIRAS team provided support on emission inventories and local costing was led by Nguyen Hoai Nam, Nguyen Thi Kim Oanh (Asian Institute of Technology, Thailand), and Nghiem Trung Dung and included Ly Bich Thuy, Le Thi Thanh Nhan, Le Tat Tu, Le Xuan Que, Nguyen Thanh Mai, Pham Thi Thu Thuy, and Kim Minh Thuy. The validation of the air quality model was done on the basis of one-year air quality monitoring and source apportionment work lead by the Finnish Meteorological Institute (FMI), where the work was led by Katja Lovén and included Ulla Makkonen and Mika Vestenius. It was done in collaboration with the Hanoi Environmental Protection Agency and the Northern Center of Environmental Monitoring (NCEM) under Environment Pollution Control Department during August 2019-July 2020. The team thanks the following colleagues and experts who reviewed this work and provided comments: Ernesto Sanchez-Triana (Lead Environmental Specialist), Yewande Aramide Awe (Senior Environmental Engineer), Dafei Huang (Senior Operations Officer), Muthukumara Mani (Lead Environmental Economist), and Stephen Ling (Lead Environmental Specialist). The team is grateful to Carolyn Turk (World Bank Country Director for Vietnam) for her comments and guidance. The team is also grateful to Dinh Thuy Quyen and Bui Thi Minh Phuong (Program Assistant) for logistical support. Acknowledgements v The report benefitted from discussions and consultation with different stakeholders in Vietnam, including Hanoi Department of Natural Resources and Environment, Hanoi Environmental Protection Agency, Bac Ninh Department of Natural Resources and Environment, Hung Yen Department of Natural Resources and Environment, Ministry of Natural Resources and Environment, academics, civil society organizations, private sector, and development partners. Editing and policy recommendation revisions were provided by Sanne Tikjoeb and Perinaz Bhada-Tata. Overall guidance was provided by Mona Sur (Practice Manager, Environment, Natural Resources and the Blue Economy Global Practice, EAP). vi Clean Air for Hanoi: What Will it Take? Abbreviations AERMOD American Meteorological MRV measurement, reporting and Society/United States verification Environmental Protection MTFR Maximum Technically Agency Regulatory Model Feasible Reduction AIT Asian Institute of Technology NAAQS national ambient air quality AQG air quality guideline standards AQI air quality index NCEM Northern Center of AQM air quality management Environmental Monitoring AUSC advanced ultra-supercritical NDC nationally determined BAU business-as-usual contribution BEV battery electric vehicle NER National Environmental Report CCDR Country Climate and Development Report NH3 ammonia CEMM Research Center for NO2 nitrogen dioxide Environmental Monitoring NOx nitrogen oxides and Modelling O3 ozone CO carbon monoxide O&M operation and maintenance CO2 carbon dioxide PDP7 Power Development Plan 7 DONRE Department of Natural PDP8 Power Development Plan 8 Resources and Environment PHEV plug-in hybrid vehicle EAP East Asia and the Pacific PM particulate matter EPA Environmental Protection PMEH Pollution Management and Agency Environmental Health EV electric vehicle PMF Positive Matrix Factorization FMI Finnish Meteorological SDG Sustainable Development Institute Goals GAINS Greenhouse gas-Air pollution SO2 sulfur dioxide Interactions and Synergies SOx sulfur oxides GDP gross domestic product SPM secondary PM GHG greenhouse gas TSP total suspended particles ICEV internal combustion engine UNFCCC United Nations Framework vehicle Convention on Climate IIASA International Institute for Change Applied Systems Analysis UNFPA United Nations Population km kilometer Fund m3 cubic meter USC ultra-supercritical MACC marginal abatement cost curve VOC volatile organic compounds MDTF Multi-Donor Trust Fund WHO World Health Organization MONRE Ministry of Natural Resources μg microgram and Environment Abbreviations vii Executive Summary Vietnam has achieved great progress in both economic growth and poverty reduction; nevertheless, this economic growth has come at the cost of increase in resource use resulting in negative externalities, such as air pollution. The deteriorating air quality has significantly impacted public health in some major cities in the country, including Hanoi, the capital of Vietnam. The current air quality situation in Hanoi and its neighboring provinces of Bac Ninh and Hung Yen necessitates urgent action to reduce pollution levels, and, consequently, population exposure to harmful particulate matter (PM2.5) concentrations. The measured annual mean concentrations are clearly above the national ambient air quality standards (NAAQS) of 25 µg/m³ and also exceed the World Health Organization global guideline value of 10 µg/m³ by a wide margin. Newly announced air quality-related policies, which will be in effect between 2021 and 2030, are an important step towards reducing air pollution levels but do not appear to be sufficient to protect public health in the medium-term, that is, until 2030. To explore management options available to policy makers in the near term, this study has developed new data and alternative scenarios analyzing the impact of various air quality measures and policies. Opportunities to achieve national standards across Hanoi and its surrounding areas were identified so as to provide input into policy discussions on an Air Quality Management (AQM) Plan for Hanoi and its surrounding provinces, as well as for Vietnam in general. ES.1 A Collaborative Effort The study has been implemented in a collaborative manner between several international and Vietnamese institutions including NIRAS (for emissions inventory and assessment of current and future air quality and climate policies and costing); the Research Center for Environmental Monitoring and Modelling (CEMM) together with the Asian Institute of Technology (AIT) for PM2.5 emissions inventory development and primary PM2.5 modelling using the AERMOD model; the Finnish Meteorological Institute (FMI) for PM2.5 monitoring and PMF receptor modelling1 for Hanoi; and the International Institute for Applied Systems Analysis (IIASA) for the application of the Greenhouse Gas-Air pollution Interactions and Synergies (GAINS) model to integrate collected data and inventory; assessment of PM2.5 1 Positive Matrix Factorization (PMF) Receptor modelling is the application of multivariate statistical methods to the identification and quantitative apportionment of air pollutants to their sources. viii Clean Air for Hanoi: What Will it Take? concentrations across the region and population exposure and development of emissions and mitigation scenarios. The GAINS model is a scientific tool to design cost-effective pollution control strategies. The model has been implemented and adapted to the specific conditions of Vietnam allowing for analysis of air pollution and mitigation scenarios. ES.2 Current Air Quality in Hanoi and its Surrounding Areas According to the National Environment Monitoring Report 2020, large cities in the North such as Hanoi had 30.5 percent poor urban air quality days out of the total number of monitoring days during the 2019 (MONRE 2021). Although there is growing evidence of unhealthy levels of PM and other pollutants in Hanoi, as shown in figure ES.1, the city currently lacks a standardized AQM system and AQM plan. Failure to introduce new policies will likely result in a significant worsening of air quality in the region in the coming years. More information regarding current air quality levels in Hanoi, Bac Ninh, and Hung Yen and the current policy scenario is provided in chapter 1. FIGURE ES.1 Annual mean concentrations of PM2.5 in Hanoi since 2015 60 2015 2016 2017 2019-20 Annual mean concentration of PM2.5 50 40 (μg/m3) 30 NAAQS for PM2.5 20 WHO Air Quality Guideline 10 0 US Embassy WHO (2016) This study MONER (2016) FMI (2021) Sources: FMI’s Source Apportionment Report (FMI 2021); MONRE’s National Environment Monitoring Report (MONRE 2016); US Embassy database; WHO’s Global Urban Ambient Air Pollution Database (WHO 2016). Note: This study used GAINS model calculation for the same two locations during a one-year period as FMI’s source apportionment measurements. The location of the US Embassy is at 7, Lang Ha Street, Hanoi, Vietnam. Executive Summary ix ES.3 Modelling Air Quality in the Greater Hanoi Region The GAINS model was used to assess the impact of various policy measures on air pollution and the mitigation of greenhouse gas (GHG) emissions as well as the interactions between policies. Various scenarios were considered, as summarized in table ES.1. Detailed descriptions of the model and the scenarios are available in chapter 2. TABLE ES.1 Overview of scenarios analyzed for this study Scenario Policies and measures included and status Geographical scope Policies before • Environmental policies, including emissions limits as defined in National, with 2020 current law. specific local • Key indicators related to national socio-economic development from policies of Hanoi, 2011 to 2020, including the high share of coal-fired power plants as Bac Ninh, and provided in PDP7. 2 Hung Yen • Enforcement of halting of open burning of waste and crop residue burning. • Energy efficiency program in manufacturing industries. New policies in • Key indicators related to national socio-economic development from Mainly national effect from 20213 2021 to 2025/2030. and Hanoi • Lower share of and improvements to efficiency of coal power plants policies as provided in draft PDP8. • Improved enforcement of environmental and emissions regulations, including a ban on open burning of waste and crop residue burning, higher energy efficiency standards, and tighter emissions limit values in manufacturing industries. New policies in • Additional policies to the ‘New policies in effect from 2021’ scenario, National policies effect from 2021 including the 2020 NDC. These include climate innovation and along with technologies/solutions introduced across sectors aiming at implementation reduction of GHG emissions. For example, further energy efficiency of NDC improvements in the power and industrial sectors, accelerated 2020 electrification of vehicle fleets, incentives for public transport, and reduced use of urea-based fertilizers. MTFR • Maximum applications of technical opportunities, mostly end-of- National policies (theoretically pipe or process modification measures, for which lowest attainable possible but very emissions factors are assumed, drawing on experiences in Asia. expensive) • It includes known limitations for application of measures and also considers current stocks and remaining lifetime but ignores cost constraints, focusing on maximum emissions reductions. Cost-efficient • Identifies a cost-effective portfolio of measures to achieve national National, with achievement ambient PM2.5 standards across the focus region. specific local of the national • GAINS model optimization is used. policies of Hanoi, standard for PM2.5 Bac Ninh, and Hung Yen 2 Key indicators include economic growth, population size, environmental standards, and GDP per capita, among others. 3 The report was prepared during 2019-2021. New policies in effect from 2021 are referred to those issued during that time or advanced in preparation, e.g. the draft Power Development Plan 8. x Clean Air for Hanoi: What Will it Take? ES.4 What the Results Show Based on the emissions estimates for 2015, ambient PM2.5 concentrations across the three provinces were estimated with the GAINS tool (figure ES.2). The analysis suggests wide- spread exceedances of Vietnam’s NAAQS for PM2.5 of 25 µg/m³. The analysis also suggests that the entire population of the greater Hanoi area was exposed to PM2.5 concentrations above NAAQS in 2015, and about 3.5 million people, equivalent to about 40 percent of population, were exposed to concentrations exceeding 45 µg/m3, which is nearly five times higher than the WHO’s air quality guideline of 10 µg/m³ (WHO, 2005) recommendation. In addition, the average annual PM2.5 concentrations measured in Hanoi during 2018-2020 were all higher by up to over a factor of two. FIGURE ES.2 Ambient concentrations and population exposure to PM2.5 modelled for 2015 a. Ambient concentrations b. Population exposure Total Hung Yen Bac Ninh PM2.5 (μg/m3) Hanoi 0 2 4 6 8 10 Million people exposed to PM2.5 < WHO guideline 10 μg/m3 10 – 15 μg/m3 15 – 25 μg/m3 25 – 35 μg/m3 35 – 45 μg/m3 > 45 μg/m3 Source: World Bank and IIASA Note: Panel a shows the annual mean concentrations in µg/m3 of PM2.5. Panel b shows the distribution of population exposure to ambient PM2.5 in the three provinces as well as the total population of the three provinces in 2015 based on the GAINS modelling carried out for this study. The results of this study also indicate that, despite the large size of Hanoi, only about one-third of PM2.5 in the ambient air originates from local sources, while the rest is transported from the Greater Hanoi/Red River Delta region, other provinces in Vietnam, and even other countries, international shipping, and natural sources (figure ES.3). Taking into consideration emissions of primary PM2.5 and its precursors from both local and surrounding domains, transportation sources contributed to about 25 percent of PM2.5 pollution in Hanoi; nearly 35 percent originated from industrial activities, including large power and industrial plants as well as craft villages; 10 percent from the residential sector (primarily cooking with biomass); another 20 percent from ammonia emissions from livestock farming and fertilizer application; about 7 percent from the open burning of agricultural waste, with the remainder from open burning of municipal solid waste. A similar picture is also observed for the other two provinces. For more details on the results of the modelling undertaken for this study, see chapter 3. Executive Summary xi FIGURE ES.3 Population-weighted annual mean source contributions of PM2.5 concentrations in Hanoi, 2015 PM2.5 (μg/m3) s es am n en i l no ta ce gio tri To gY ur Ha tn un l re so Vie un co ita l dH ra th r p e tu ou ca th an Na ds O oi inh an an cN rH th Ba he or rn Ot he Ot Source: World Bank and IIASA Note: The x-axis distinguishes the spatial origins of PM2.5. The y-axis indicates the amounts of PM2.5 originating from emissions of various economic sectors. ES.5 Hanoi Air Pollution in 2030: Will it get Better or Worse? Policies before 2020 will lead to further increases in PM concentrations across the region. Under the policies before 2020 scenario, average annual PM2.5 concentrations could reach nearly 60 μg/m3 in Hanoi and its surrounding provinces by 2030. The POLICIES BEFORE 2020 largest increase in ambient PM2.5 is expected to come from emissions in the power sector as economic growth fuels further demand for energy. The increasing role of coal in power production and the lack of stricter emissions limits will result in growing contributions of the power sector to estimated PM2.5 concentrations. Similarly, with population and economic growth, the contributions of agriculture and solid waste management to air pollution are expected to increase, especially without new legislation limiting open burning of solid waste. Existing transport regulations are barely expected to keep up with vehicle growth as the transport sector will continue to account for a quarter of PM2.5 concentrations in Hanoi. With current policies in place, by 2030 the entire pollution living in Hanoi, Bac Ninh, and Hung Yen will be exposed to air pollution levels more than five-to-six times the WHO recommended guideline (WHO, 2005). xii Clean Air for Hanoi: What Will it Take? New policies in effect from 20214 (excluding the 2022 NDC) are insufficient to NEW POLICIES IN EFFECT FROM reverse the trend of worsening air pollution. Even with new policies in place aimed at improving energy efficiency and strengthening enforcement of regulation, air pollution is expected to worsen. In 2030, more than 70 percent of the population in Hanoi will experience annual PM2.5 pollution levels above 45 µg/m3, nearly twice the level of NAAQS. The population in all three provinces would be exposed to air pollution twice the level of NAAQS. However, compared to the policies before 2020 2021 scenario, the new policies in effect from 2021 scenario would reduce the maximum observed annual average concentrations to below 50 µg/m3. Improvements will be mainly driven by a declining share of coal in power sector and increasing efficiency of remaining coal power plants and better enforcement of industrial emissions limits. It also requires increased enforcement on the ban of dumping and open burning of waste and agricultural crop residue. Further measures are needed to reverse the trend of deteriorating air pollution to bring Hanoi and its neighboring provinces closer to the national standards for ambient air quality. Co-benefits from climate action can improve air quality by 2030. The new policies in effect from 2021 along with the implementation of NDC 2020 scenario is expected NEW POLICIES IN EFFECT FROM to bring large qualitative change in air quality in the three provinces, resulting in almost a halving of PM2.5 concentrations in Hanoi compared to the policies before 2021 WITH NDC 2020 2020 scenario. Maximum concentrations would fall below 35 µg/m3 in most of the region, although only a small share of the population would enjoy concentrations within the NAAQS. The introduction of measures under the 2020 NDC, in addition to the new and planned policies, would reduce power sector emissions through further energy efficiency improvements and increases in renewable energy capacity. In the agricultural sector, the reduced use of urea fertilizer would bring significant reductions in ammonia emissions. Still, the typical range of annual average concentrations of PM2.5 would reach 25-35 µg/m3 with about 15 percent of the population, mostly in urbanized areas of Hanoi province would be exposed to levels above 35 µg/m3. Estimated concentrations of PM2.5 in Hanoi would need to be reduced further by 30 percent to reach NAAQS. The introduction of recently announced policies as well as climate- and SDG-motivated actions proposed in the 2020 NDC would result in improved air quality compared to the policies before 2020 scenario (figure ES.4), according to GAINS model analysis. Further air quality improvement is expected with the implementation of the recent 2022 NDC that target net zero GHG emission by 2050. 4 The report was prepared during 2019-2021. New policies in effect from 2021 are referred to those issued during that time or advanced in preparation, e.g. the draft Power Development Plan 8. Executive Summary xiii FIGURE ES.4 Impact of polices on air quality standards by 2020 in Hanoi, Bac Ninh, and Hung Yen Policies before 2020 scenario a. Ambient concentrations b. Population exposure Hung Yen Bac Ninh PM2.5 (μg/m3) Hanoi 0 1 2 3 4 5 6 7 8 9 Million people exposed to PM2.5 < WHO guideline 10 μg/m3 10 – 15 μg/m3 15 – 25 μg/m3 25 – 35 μg/m3 35 – 45 μg/m3 > 45 μg/m3 New policies in effect from 2021 scenario a. Ambient concentrations b. Population exposure Hung Yen Bac Ninh PM2.5 (μg/m3) Hanoi 0 1 2 3 4 5 6 7 8 9 Million people exposed to PM2.5 < WHO guideline 10 μg/m3 10 – 15 μg/m3 15 – 25 μg/m3 25 – 35 μg/m3 35 – 45 μg/m3 > 45 μg/m3 New policies in effect from 2021 with NDC 2020 scenario a. Ambient concentrations b. Population exposure Hung Yen Bac Ninh PM2.5 (μg/m3) Hanoi 0 1 2 3 4 5 6 7 8 9 Million people exposed to PM2.5 < WHO guideline 10 μg/m3 10 – 15 μg/m3 15 – 25 μg/m3 25 – 35 μg/m3 35 – 45 μg/m3 > 45 μg/m3 Source: World Bank and IIASA xiv Clean Air for Hanoi: What Will it Take? ES.6 Clean Air for Hanoi by 2030: What Will it Take? Given the range of human-induced air pollution sources that have been identified in the greater Hanoi area, a multi-sectoral and multi-province approach is needed to improve air quality. The GAINS model was used to determine what would be required to make air quality in the Hanoi region compliant with the NAAQS by 2030, which stipulates that the population- weighted annual mean concentration of PM2.5 should not exceed 25 μg/m3. Determining cost-effective measures requires balancing what is technically possible with what is financially achievable. Given the structure of emissions, the GAINS model in the optimization mode uses data on population distribution, atmospheric transport, and control cost differences across regions to identify a portfolio of cost-effective measures to comply with the NAAQS for PM2.5 across the three provinces. Interventions in the following sectors are required: energy, waste management, transport, and agriculture. The key interventions are summarized in table ES.2. TABLE ES.2 Policy options to reduce PM2.5 emissions from key sectors Sector Key Policy Options ENERGY Coal-fired power • Strengthen emission limit values for existing and new coal-fired power plants plants • Apply more efficient end-of-pipe filters • Flue gas desulphurization Craft villages • Reduce coal and biomass use in boilers and furnaces in craft villages INDUSTRY • Improve capture and removal of industrial process emissions, e.g., from the steel industry • Reduce coal use in industrial processes Biomass combustion • Introduce stricter emission limits on biomass combustion Cement production • Introduce stricter emission limits on cement production Brick kilns • Improve efficiency and introduce emissions standards • Reduce coal use Executive Summary xv TABLE ES.2 Policy options to reduce PM2.5 emissions from key sectors (cont.) Sector Key Policy Options TRANSPORT Dust control • Suppress road dust by paving more roads and wet cleaning urban areas • Requirements for dust control at construction sites Emission standards • Strengthen and monitor/enforce emission control standards for vehicles and for vehicles motorcycles Low-emission zones • Define and apply low-emission zones in designated central areas of the city High-emitting • Enforce a strict policy against high-emitting vehicles, including two-wheelers, vehicles eventually leading to total phase out of such vehicles Electrification of • Accelerate the electrification of vehicles and motorcycles, including with priority high vehicles emitting vehicles, buses, taxis and/or ride sharing firms. These can bring quick results as they are high emitting and/or a large share in the distances driven within cities. • Install charging stations and power infrastructure • Eventually lead to a total phase out of internal combustion engine vehicles (ICEV) Public transport • Promote the use of public transport AGRICULTURE Agricultural crop • Enforce a strict ban on agriculture residue burning and encourage better management residues of agricultural residues Nitrogen fertilizer • Replace urea with ammonium nitrate application • Ensure efficient application of urea fertilizer when used Livestock manure • Introduce low-emission covered storage for manure storage and biogas applications management • Ensure efficient application of manure WASTE MANAGEMENT Residential waste • Strictly enforce a ban on open burning of municipal solid waste, including by burning households Recycling • Improve waste collection, sorting, and recycling Landfill • Eliminate open burning of solid waste through bans management • Eliminate open dumpsites and dispose waste in sanitary landfills • Infrastructure to capture methane emissions from landfills, avoid organic waste to be disposed of in landfills and composted instead Targeting both air quality pollutants and greenhouse gases at the same time in the key polluting sectors of energy, industry, transportation, waste management, and agriculture can provide substantial co-benefits to both improving air quality while mitigating climate change. This will help Vietnam reduce emissions for better air quality by 2030, while at the same time achieving its commitments under its updated NDC. xvi Clean Air for Hanoi: What Will it Take? CHAPTER 1: Improving Air Quality in Hanoi and its Surrounding Areas As Vietnam continues to transition from a predominantly rural to a vibrant urban economy, it has made significant strides in economic growth and poverty reduction. Nevertheless, like other developing economies, this economic growth is coupled with an increase in the consumption of resources and other resultant negative externalities. More efforts in managing air pollution so far are expected to address public health problems, especially in some major cities and economic hubs. Ambient air pollution is a major contributor to human health and other living organisms, including in Hanoi, the capital of Vietnam and its second largest city. Chapter 1: Improving Air Quality in Hanoi and its Surrounding Areas 1 Between 2018 and 2020, the annual average values of PM10 and PM2.5 at all automatic air monitoring stations in Hanoi exceeded the national ambient air quality standard (NAAQS) values by up to over a factor of two times, with the highest values occurring in 2019. In large cities in the North such as Hanoi, the number of days in a year with poor and bad air quality index (AQI) account for about 30.5 percent of the total number of monitoring days, including days with very bad AQI ranging between 201 and 300 (MONRE 2021). Ambient air quality is a broad term used to describe air quality outdoors. Without effective countermeasures, air quality is expected to further deteriorate in the future because of growing levels of polluting activities, such as power generation, improper waste management, and industrial activities. For this work, the Vietnam Greenhouse Gas Air pollution Interactions and Synergies (GAINS) model has been developed in collaboration with the International Institute for Applied Systems Analysis (IIASA), drawing on GAINS model databases, especially for comparable countries in Asia. The model is available online at: https://gains.iiasa.ac.at/gains/VIE/index.login. The model uses source apportionment data from the laboratory analysis of pollution and emissions inventory data covering Hanoi, Bac Ninh, and Hung Yen provinces and emissions inventory for the region. The model includes complete source emissions coverage, which is detailed for the greater Hanoi area and updated emissions inventory in the regional and fine modelling domain. The GAINS analysis reveals that Hanoi’s air quality could deteriorate in the future as a consequence of the anticipated increase in economic activities. Effective improvements to Hanoi’s air quality also requires coordination with neighboring provinces, Bac Ninh and Hung Yen. A number of scenarios are studied, based on various policy assumptions, and for each scenario, the resultant PM2.5 concentration is determined, as PM2.5 is most damaging to health. This is described in more detail in chapter 2. Chapter 3 provides the results of the GAINS modelling, including impacts of alternative emissions control strategies, comparing their impacts on emissions, air quality, population exposure, and emissions control costs. Key findings and potential policy interventions for future improvements of Hanoi and its surrounding region are presented in chapter 4. 1.1 Air Quality in Hanoi and the Surrounding Areas Although there is growing evidence of unhealthy levels of PM and other pollutants in Hanoi, the city currently lacks a standardized AQM system and AQM plan. According to the National Environment Monitoring Report, Hanoi and its surrounding areas have poor urban air quality (MONRE 2021). The Air Quality Index (AQI) continues to be relatively high. The number of days in 2019 with poor and unhealthy AQI values accounted for 30.5 percent of the total number of days observed in the year, taking an average of AQM stations. There were days when the air quality declined to very bad threshold (AQI between 201-300), and even crossed an unprecedented level of 385. 2 Clean Air for Hanoi: What Will it Take? The WHO’s standard for ‘good’ air quality index is 50 or below, as shown in figure 1.1. As the AQI value increases, the worse—and, therefore, unhealthy—air pollution gets. In addition to the AQI, PM2.5 concentration is another important indicator of air pollution. PM2.5 refers to particles that have a diameter of 2.5 micrometers or less and remain suspended in the air for long durations. They are formed as a result of combustion of fossil fuels as well as chemical reactions that take place in the atmosphere. With regard to PM2.5, the WHO’s updated guidelines from 2021 state that annual average concentrations should not exceed 5 µg/m3, while 24-hour average exposures should not exceed 15 µg/m3 more than 3 to 4 days per year. Interim targets for PM2.5 for cities, regions, and countries that struggle with high levels of air pollution are also provided by the WHO and summarized in table 1.1. FIGURE 1.1 Explanation of Air Quality Index AQI value range Air Quality Color 0 - 50 Good Green 51 - 100 Average Yellow 101 - 150 Poor Orange 151 - 200 Bad Red 201 - 300 Very Bad Purple 301 - 500 Harmful Brown Source: VEA 2019 TABLE 1.1 WHO updated targets for PM2.5 Guideline/targets Annual average concentration 24-hour average exposure of PM2.5 (µg/m3) (µg/m3) Updated guideline 5 15 35 75 25 50 Interim targets 15 37.5 10 25 Source: WHO 2021 Chapter 1: Improving Air Quality in Hanoi and its Surrounding Areas 3 Given the existing state of poor air quality in Hanoi and the surrounding provinces, urgent action is necessary to reduce pollution levels and, consequently, population exposure to harmful PM2.5 concentrations. Measured annual mean concentrations are clearly above the NAAQS for PM2.5 of 25 µg/m³ and exceed the global guideline value of the WHO in 2005 (10 µg/m³) by a wide margin, as shown in figure 1.2. Failure to introduce new policies will likely result in a significant worsening of air quality in the region. Newly-announced policies such as the Vietnam NDC 2022, the National Socio-economic Development Strategy 2011-2020, the Draft Power Development Plan (PDP) 8, and new transport policies for Hanoi and the capital region are important steps in the right direction but appear insufficient to protect public health in the long term. To explore options available to policy makers in the near term, this study has developed new data and a set of alternative scenarios to analyze the impact of various potential measures and policies. Opportunities to achieve NAAQS across the region were identified and these could provide input to policy discussions on the development of an AQM Plan for Hanoi and the surrounding provinces as well as for Vietnam in general. FIGURE 1.2 Annual mean concentrations of PM2.5 in Hanoi since 2015 60 2015 2016 2017 2019-20 Annual mean concentration of PM2.5 50 40 (μg/m3) 30 NAAQS for PM2.5 20 WHO Air Quality Guideline 10 0 US Embassy WHO (2016) This study MONER (2016) FMI (2021) Sources: FMI’s Source Apportionment Report (FMI 2021); MONRE’s National Environment Monitoring Report (MONRE 2016); US Embassy database; WHO’s Global Urban Ambient Air Pollution Database (WHO 2016) Note: This study used GAINS model calculation for the same two locations during a one-year period as FMI’s source apportionment measurements. The location of the US Embassy is at 7, Lang Ha Street, Hanoi, Vietnam. 4 Clean Air for Hanoi: What Will it Take? Concentrations of sulfur dioxide (SO2) and carbon monoxide (CO), ground-level ozone (O3) and nitrogen dioxide (NO2) in urban areas generally stay within the NAAQS in 2021 as shown in table 1.2 (MONRE 2021). Local monitoring stations reveal an increase in NO2 pollution in high-traffic areas in large urban centers in Vietnam, including Hanoi (MONRE 2016). However, since 2016 the annual average NO2 has been within the national standard. TABLE 1.2 National Ambient Air Quality Standards for key air pollutants (μg/m3) No. Factor Average value Average value Average value Average value per hour per 8 hours per 24 hours per year 1 SO2 350 - 125 50 2 CO 30,000 10,000 - - 3 NO2 200 - 100 40 4 O3 200 120 - - 5 TSP 300 - 200 100 6 PM10 - - 150 50 7 PM2.5 - - 50 25 8 Lead - - 1.5 0.5 Source: MONRE 2013 Note: “-“ means not regulated. During the winter months, concentrations of PM2.5 tend to be exceptionally high due to meteorological conditions and stable atmospheric conditions, which limit the dispersion of pollutants. With prevailing winds from the north and north-east, Hanoi and its surrounding regions are also affected by air pollutants transported from northern provinces in Vietnam as well as long-range pollution transported from southern China. This is evident between the months of October and February, when the 24-hour limit value of 50 µg/m3 is regularly exceeded with very high peaks of 150-200 µg/m3 (figure 1.3). To test this hypothesis, backward trajectories were used to identify the region(s) from which air pollution was transported to Hanoi on a particular day. On November 19, 2019, the air masses came from the region to the north-east of Hanoi, carrying pollution from fires along their route, as seen in figure 1.4a, where the colored lines indicate the backward trajectory of the pollution Chapter 1: Improving Air Quality in Hanoi and its Surrounding Areas 5 recorded in Hanoi on that day. Fire maps were created based on satellite data, confirming that there were numerous fires burning that day in northern Vietnam and southern China. The fire map in figure 1.4b shows the active fires in red dots recorded on that particular day in northern Vietnam and in China. Figure 1.4c indicates the number of fires in yellow boxes. In the summer, pollution levels tend to typically be lower as rainfall washes away air pollution and southeasterly winds (that is, from the East Sea) prevail. Between May to August, PM2.5 concentrations are mostly below the Vietnamese 24-hour limit value (50 µg/m3) in Hanoi. FIGURE 1.3 Daily PM2.5 concentrations measured at the 556, Nguyễn Văn Cừ Street and at the urban background station in Hanoi in 2019-2020 250 NCEM PM2.5 mass (weighed) Hanoi EPA PM2.5 mass (weighed) Daily PM2.5 concentrations (µg/m3) 200 Hanoi EPA PM2.5 monitor 150 100 50 0 Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jul 2019 – 2020 Sources: Monitoring data from 556, Nguyễn Văn Cừ Street, Hanoi EPA, and FMI Note: The red line shows the Vietnamese national PM2.5 limit value for 24-hour average (50 µg/m3). In spring 2020, air quality was globally influenced by the COVID-19 pandemic restrictions. During the COVID-19 lockdown in Hanoi in March- April 2020, the concentrations of fine particles decreased at both measurement sites. Restrictions related to COVID-19 pandemic also affected the results of this study. The NCEM location represents an urban traffic air quality monitoring station and is located at the Northern Centre for Environmental Monitoring, 556 Nguyen Van Cu street, Long Bien District, Hanoi. The background air quality monitoring station is located at the Hanoi Environmental Protection Agency, 17 Luu Quang Vu street, Cau Giay District, Hanoi. 6 Clean Air for Hanoi: What Will it Take? FIGURE 1.4 72-hour backward trajectories estimating air pollution in Hanoi on November 19, 2019 a. Backward trajectories showing transport of b. Map showing number of active fires in air masses towards Hanoi Vietnam and China c. Map showing active fires in Vietnam and China Source: World Bank and FMI Note: The map in b shows active fires with red spots. In 3c, the number in the yellow box indicates the number of fires active in that location. Fire maps of the day were produced using satellite data. Backward trajectories were used to identify the potential source region for the air masses carrying pollution to Hanoi on November 19, 2019. 1.2 Air Pollution Control Policy in Hanoi, Bac Ninh, and Hung Yen and Link with Climate Change Mitigation The Law on Environmental Protection in Vietnam includes provisions for environmental protection of air quality. Particularly in urban areas, there are environmental protection regulations for sectors that generate high levels of air pollution, such as transportation, construction, and industrial activities. Chapter 1: Improving Air Quality in Hanoi and its Surrounding Areas 7 In 2016, the National Action Plan on Air Quality Management to 2020, with a Vision to 2025, was approved by the Prime Minister of Vietnam. Accordingly, urban air quality management practices have been improved by priority programs and projects. Particularly for Hanoi, the Ministry of Natural Resources and Environment has issued two technical regulations addressing air quality, tightening emission limit values for industrial sources in the city. More specifically, new standards address emissions of dust and inorganic substances from industrial sources including SO2, NOx, CO, etc.,. The city government has implemented air pollution controls such as removing beehive stoves and limiting the burning of straw and crop by-products after harvest. The city has also deployed activities such as spraying water to wash roads and thoroughly collecting garbage and dirt on roads. Climate change and air quality are closely related, and both have an impact on one another. Beyond health and ecosystem impacts, air pollutants contribute also to climate change. For example, while sulfur dioxide cools the atmosphere, black carbon (component of PM) contributes to warming. Moreover, air pollutants and greenhouse gases (GHGs) are often emitted from the same sources, such as coal-fired power plants and fossil fuel-powered vehicles, both of which are important sectors considered in this report. According to the WHO, air pollution in the main urban centers of Vietnam results in around 60,000 premature deaths per year. Measures to reduce GHGs and meet Vietnam’s NDC target would also abate air pollution, thus providing important co-benefits both ways. BOX 1.1 World Bank’s Country Climate and Development Report (CCDR) for Vietnam The World Bank’s recent Country Climate and Development Report (CCDR) for Vietnam—the first CCDR in the East Asia and Pacific Region—provides a decarbonizing pathway for Vietnam, particularly for the energy, agriculture, transport, and industrial processes sectors. These are the same sectors that emit harmful air pollutants, resulting in negative impacts on public health and labor productivity. Importantly, Vietnam’s decarbonization efforts can also advance its development objectives, such as reducing air pollution and improving public health. One of the top five policies in the CCDR that require immediate attention by the government and urgent investment in Vietnam includes a targeted air pollution reduction program in the Hanoi region to reach the WHO PM2.5 target by 2030 (World Bank 2022). 1.3 The Draft Power Development Plan 8 and Vietnam’s Nationally Determined Contribution 2020 and Air Quality Co-benefits of Climate Actions The draft PDP8 of Vietnam has been developed considering various environmental issues such as GHG emissions and industrial waste from coal-fired thermal power plants. According to the NDC updated in October 2022, GHG emissions by 2030 from the energy sector will reach 678 million tons of CO2 equivalent in the business-as-usual (BAU) scenario. The PDP8 draft in July 8 Clean Air for Hanoi: What Will it Take? 2022 estimates the power sector generation of CO2 emissions by 2045 to be 169 million tons in the low case and 175 million tons in the high case. However, with the anticipated increase in the capacity of coal-fired power plants by 2030, air quality is expected to be severely impacted due to a rapid growth in SO2, NOx, PM2.5 emissions, as indicated in table 1.3. TABLE 1.3 Projected emissions from coal-fired thermal power plants as in draft PDP8 – selected scenario (tonnes) Year 2020 2025 2030 2035 2040 2045 SOx 91,733 118,263 174,003 243,732 261,498 256,517 NOx 184,561 298,328 450,578 637,171 692,959 719,571 Dust (PM) 9,450 21,312 31,707 41,505 43,677 46,207 Source: PDP8 draft Note: Emissions from power plants are categorized as ‘dust’ as they comprise particulate matter of all sizes, not only PM2.5. One of the most affected regions in Vietnam is expected to be the Red River Delta region where several future coal-fired power plants are located and more being planned. Increasing emissions from power plants will affect strongly Hanoi and surrounding provinces, home to more than 23.2 million people.5 In order to prevent a worsening of air pollution in the future, it is important that the new policies require all new coal-fired power plants use ultra-supercritical (USC) or advanced ultra-supercritical (AUSC) technology, while phasing out old and low-efficiency power plants. Vietnam’s updated NDC to the UNFCCC in 2022 strengthens the country’s 2030 targets in terms of CO2 emissions reductions. According to the 2022 NDC, by 2030 Vietnam will reduce 15.8 percent of its total GHG emissions compared to the BAU scenario using 2014 as the base year, equivalent to 146.3 million tons of carbon dioxide equivalent (Mt CO2eq) using domestic financial resources. The 15.8 percent contribution could be increased to 43.5 percent (equivalent to 403.7 Mt CO2eq) with international support from bilateral and multilateral cooperation as well as implementation of mechanisms under the Paris Agreement (UNFCCC 2022).6 The 2022 NDC identifies certain domestic measures to achieve GHG mitigation targets that can have a significant improvement in air quality, such as: • Improving energy efficiency and savings, thus reducing energy consumption • Changing the fuel structure in industry and transportation sectors and shifting passenger and cargo transport models 5 Based on 2021 provincial statistics data for Hanoi, Bac Ninh, and Hung Yen. 6 The scenarios and calculations in this report are based on Vietnam's 2020 NDC. In the 2020 NDC, Vietnam targeted a reduction of 9 percent of total GHG emissions compared to the BAU scenario, equivalent to 83.9 Mt CO2eq. This 9 percent could be conditionally increased to 27 percent (equivalent to 250.7 Mt CO2eq) compared to the BAU, with additional international funding (UNFCCC 2020). Chapter 1: Improving Air Quality in Hanoi and its Surrounding Areas 9 • Improving effective exploitation of and increasing the proportion of new and renewable energy sources in energy production and consumption • Improving management of solid waste • Sustainable agricultural development At the UN Climate Change Conference in Glasgow in November 2021 (COP26), the Prime Minister made a commitment on an ambitious target of reducing emissions to net zero by 2050 (Climate Action Tracker n.d.). The 2022 NDC is in line with the net zero target committed by Vietnam at COP26. This is expected to have a local benefit of improving air quality for Hanoi. 10 Clean Air for Hanoi: What Will it Take? CHAPTER 2: Designing Scenarios to Estimate Air Quality This chapter details the methodology used to assess air quality in Hanoi and its surrounding areas of Bac Ninh and Hung Yen. The Greenhouse Gas-Air pollution Interactions and Synergies (GAINS) model was specifically developed and calibrated for the greater Hanoi area on the basis of a one-year PM2.5 monitoring campaign.7 This was done by developing a PM2.5 emissions 7 The GAINS model was validated against PM2.5 monitoring data collected by FMI, which showed an acceptable agreement between the two datasets. The specific measurements performed by FMI and the application of the PMF method to estimate source contributions to the measured PM2.5 constituents. This PMF method and model is the application of multivariate statistical methods to the identification and quantitative apportionment of air pollutants to their sources and created a dataset of air pollution sources to which results of the GAINS model could be compared. The GAINS model was able to reproduce the total PM2.5 mass as measured by FMI and the source apportionment analysis performed by FMI and GAINS show good agreement in terms of primary and secondary particulate matter. The link to the model is at https://gains.iiasa.ac.at/gains/VIE/index.login Chapter 2: Designing Scenarios to Estimate Air Quality 11 inventory that—for the first time—combined analyses of primary and secondary sources of PM2.5 for the Hanoi region. This chapter describes the model as well as the various policy scenarios that were designed to assess current and future air quality in the area. 2.1 The GAINS Model The GAINS model is a widely-applied tool globally to assess the impact of various policy measures on air pollution and the mitigation of greenhouse gas (GHG) emissions as well as the interactions between policies. The model calculates the emissions of air pollutants and GHGs based on international emissions inventories and statistics as well as inputs obtained from collaborating national expert teams. Emissions are estimated considering explicitly combustion, production, and applied pollutant reduction technologies. Details of the GAINS model are available in peer- reviewed literature and documentation from the online version of the model (Amann et al. 2011; IIASA n.d.). This integrated assessment model has been widely applied in policy analysis, including air quality and climate target negotiations across Europe and is now being implemented globally at regional, national, and provincial levels in east and south Asia, Africa, the Middle East, and South America. Given the use of this consistent framework across multiple regions, the GAINS model was chosen for use in northern Vietnam, and groups the provinces into five regions, which are then further considered in the analysis: A. Hanoi B. Bac Ninh province C. Hung Yen province D. The Greater Hanoi region and Red River Delta, that is, the Red River Delta and northern midland. This includes the provinces of Hai Duong, Bac Giang, Quang Ninh, Hai Phong, Thai Binh, Ha Nam, Nam Dinh, Ninh Binh, Thai Nguyen, Vinh Phuc, and Hoa Binh. E. The remaining areas of northern and north-central Vietnam, that is, the provinces of Son La, Yen Bai, Lao Cai, Lang Son, Thanh Hoa, and Nghe An. 12 Clean Air for Hanoi: What Will it Take? MAP 2.1 Regions in Vietnam that were included in this study Source: World Bank 2.2 Data Sources and Cost Calculations The estimated emissions in each province considered in the GAINS model are determined by activity data, emissions factors, and control strategies, which are updated with local information in the three provinces of Hanoi, Bac Ninh, and Hung Yen. For instance, local data related to power, industry, waste, transport, and agricultural activities as well as control efficiency data, are collected from the National Master Power Plan 7 and 8, Vietnam Energy Outlook Report (2020), Hanoi Environmental Protection Agency (Hanoi EPA), Hanoi Department of Industry and Trade, General Statistical Yearbooks, the Ministry of Natural Resources and Environment, and the Ministry of Industry and Trade. It should be noted that official data and information from Bac Ninh and Hung Yen local government departments were also collected. The model also used primary data collected from craft villages in the three provinces. Additionally, the work was supported by the collaboration with Vietnam Academy of Sciences and Technology (VAST) in the joint IIASA-VAST activity which has been documented in Amann et al. (2019)8. 8 The “Future air quality in Ha Noi and Northern Vietnam” report is available at https://previous.iiasa.ac.at/web/home/research/re- searchPrograms/air/news/181107_AQM_Vietnam.html Chapter 2: Designing Scenarios to Estimate Air Quality 13 Cost calculations were based on the methodology implemented in the GAINS model and only include costs of air pollution control technology. The costs were calculated using technology- specific unit costs, and local cost factors were also considered.9 2.3 Stakeholder Consultations and Data Validations Stakeholder consultations and data validation are crucial components of the GAINS model used in Vietnam. These are opportunities for outreach to larger audiences, particularly government agencies such as MONRE, Hanoi EPA, Bac Ninh EPA, and Hung Yen EPA, as well as to present the results of the study more effectively. The work was also supported by the collaboration with VAST under the joint IIASA-VAST activity mentioned above. Consultations on the methodology were carried out and results of the inventory and report results were shared with a wide spectrum of stakeholders through various stakeholder consultation workshops. These also served to promote the GAINS model as a suitable and reliable tool to deliver policy and investment measures at the provincial, national, and international levels of AQM planning. These events served to further coordinate the formal feedback process for the report, particularly as MONRE and DONRE inputs were crucial for the use of the collected data in the modelling work undertaken at IIASA, where the GAINS model is housed. Model implementation and consultation activities have been strongly supported by relevant government agencies of Hanoi, Bac Ninh, and Hung Yen, which provides a higher level of data credibility and reliability for GAINS modelers and analysis experts. 2.4 Scenario Design Three policy scenarios and two types of mitigation scenarios are constructed and analyzed for this study, therefore providing five scenarios in total, as described in table 2.1. The policies before 2020 scenario were developed to explore the interplay between pollution control policies and economic growth and their impacts on future air quality. This scenario assumes economic development trends as a business-as-usual case, following the national socio-economic development and implementation of the legislation on pollution controls. 9 Unit costs are annual costs that take into account annualized investments (using a 4 percent interest rate), as well as fixed and vari- able operation and maintenance (O&M) costs that take into account fuel prices, local wages, waste disposal costs, and other such costs. GAINS calculates emissions control costs from the perspective of a social planner, with a focus on resource costs of emissions controls to societies. While this perspective is different from that of private profit-oriented actors, it is the appropriate approach for decisions on the optimal allocation of societal resources. Costs are calculated based on international prices. Regional-specific circumstances (for example, the size distribution of plants, plant utilization, fuel quality, energy, and labor costs) lead to justifiable differences in actual costs at which a given technology removes pollution from different sources. What is not covered by the cost concept of the GAINS model is: (i) Any cost for actually implementing a measure (that is, transaction costs); (ii) Monitoring and en- forcement costs, such as regular vehicle or combustion inspections; (iii) Full accounting for changes in infrastructure and behavior, and (iv) Macro-economic feedbacks, for example, on prices, productivity, and substitution, either as a result of a shift in technology portfolio/electrification or behavioral change. 14 Clean Air for Hanoi: What Will it Take? TABLE 2.1 Overview of scenarios analyzed for this study Scenario Measures included Geographical scope Policies before • Environmental policies, including emissions limits as defined in National, with 2020 current law. specific local • Key indicators related to national socio-economic development from policies of 2011 to 2020, including the high share of coal-fired power plants as Hanoi, Bac provided in PDP7.10 Ninh, and Hung Yen • Enforcement of open burning of waste and crop residue burning. • Energy efficiency programs in manufacturing industries. New policies in • Key indicators related to national socio-economic development from Mainly national effect from 2021 2021 to 2025/2030. and Hanoi • Lower share of and improvements to efficiency of coal power plants policies as provided in draft PDP8. • Improved enforcement of environmental and emissions regulations, including a ban on open burning of waste and crop residue burning, higher energy efficiency standards, and tighter emissions limit values in manufacturing industries. New policies in • Additional policies to the ‘New policies in effect from 2021’ scenario, National effect from 2021 including the 2020 NDC. These include climate innovation and policies along with NDC technologies/solutions introduced across sectors aiming at 2020 reduction of GHG emissions. For example, further energy efficiency improvements in the power and industrial sectors, accelerated electrification of vehicle fleets, incentives for public transport, and reduced use of urea-based fertilizers. MTFR • Maximum applications of technical opportunities, mostly end-of- National (theoretically pipe or process modification measures, for which lowest attainable policies possible but very emissions factors are assumed, drawing on experiences in Asia. expensive) • It includes known limitations for application of measures and also considers current stocks and remaining lifetime but ignores cost constraints, focusing on maximum emissions reductions. Cost-efficient • Identifies a cost-effective portfolio of measures to achieve national National, with achievement ambient PM2.5 standards across the focus region. specific local of the national • GAINS model optimization is used. policies of standard for PM2.5 Hanoi, Bac Ninh, and Hung Yen Note: GHG = Greenhouse gas; MTFR = Maximum Technically Feasible Reductions; NDC = National Determined Contribution; PDP7 = Power Development Plan 7; PDP8 = Power Development Plan 8 The new policies in effect from 2021 scenario was created to examine newly-established policies or those coming into effect between 2021 and 2030, such as new master plans for cement, agriculture, iron/steel production with improvements to emissions standards, cleaner technology adoption, or activity level changes11. Examples of such policies include the National Socio-economic 10 Key indicators include economic growth, population size, environmental standards, and GDP per capita, among others. 11 The NDC 2022 and PDP8, with an expected increase in the share of renewable energy and reduced coal power plant usage by 2045, will contribute to improvements in air quality for Hanoi. Coal power plant capacity by 2030 is the same in both the PDP8 2021 draft (used to develop this report) and the 2022 draft. Chapter 2: Designing Scenarios to Estimate Air Quality 15 Development Strategy 2021-2030 and the draft National Master Power Plan 2016-2035 (PDP8). For road transportation, the most recent emissions standard in Vietnam that applies to newly registered cars is taken into consideration. The new policies in effect from 2021 scenario assumes no capacity additions for subcritical power plants after 2025, while future growth in coal use is driven by the use of advanced (supercritical and ultra-supercritical) power plants that have higher efficiencies.12 For industrial boilers and furnaces, efficiency improvements in some industries, such as cement and iron and steel production, are explicitly projected and follow the Ministry of Natural Resources and Environment (MONRE).13 There are new transportation policies for Hanoi and the capital region, such as higher shares of public buses, urban railway, and electric buses for passenger transport. The Hanoi People’s Committee will enforce waste treatment practices toward reducing landfilling and increase waste incineration and recycling, while a 100-percent ban on open burning of agricultural waste from 2021 have been applied.14 The new policies in effect from 2021 along with the implementation of NDC 2020 scenario provides the identified GHG mitigation measures endorsed by the Government of Vietnam in its 2020 NDC and submitted to the United Nations Framework Convention on Climate Change (UNFCCC). The 2022 NDC is the most recent commitment from Vietnam in combating climate change, where air quality co-benefits are reasonably clear. This scenario covers most of the key relevant sectors, such as energy, industry, agriculture, and waste management. The Maximum Technically Feasible Reduction (MTFR) case assumes further measures that rely primarily on technological solutions to reduce emissions, in line with examples widely adopted in many countries across the world.15 It should be noted that the new policies in effect from 2021 along with NDC 2020 + the MTFR scenario also assumes that the rest of Asia enters an ambitious policy pathway to achieve the sustainable development goals consistent with the Paris Agreement and the introduction of stringent air quality legislation. The latter would result in lower transboundary pollution. For this scenario, it is also assumed that the recent experience in applying high-efficiency control technologies in certain Asian countries is propagated across Asia, translating to lowest attainable emissions factors for respective technologies, that is, flue gas desulfurization, selective catalytic NOx reduction, and high efficiency dust removal technology. Lastly, cost-effective air quality management strategies for PM2.5 explore the potential to achieve the national ambient air quality standard (NAAQS) of 25 μg/m3 for most of the population across the three provinces of Hanoi, Bac Ninh, and Hung Yen as well as the Red River Delta region. The GAINS optimization model is used to identify a portfolio of cost-effective measures to achieve population-weighted NAAQS across the region. 12 It should be noted that there will be no changes to emissions controls for thermal power plants, which stay at the level of 200 mg/ Nm3 for dust and 500 mg/Nm3 for SO2. 13 For cement facilities on the tightened regulation on emissions as defined under the QCVN 23:2009/BTNMT and QCTĐHN 01:2014/ BTNMT in which the concentration of dust, SO2, and NOx are stipulated and tightened in future. 14 Hanoi People’s Committee’s Instruction No. 15/CT-UBND, dated September 18, 2020, to ban open burning of agricultural waste. 15 This scenario does not consider the potential benefits from further structural changes in the economy that affect the most polluting activities, such as the burning of coal and biomass, for example through energy conservation or substitution of fuels. Such measures offer significant potential for air quality improvements, in addition to their own benefits on other development objectives. 16 Clean Air for Hanoi: What Will it Take? CHAPTER 3: Understanding How Air Quality Improvements Can be Made 3.1 Understanding the Current Situation The key element of any air quality assessment is an emissions inventory for particular air pollutants. So far, the focus has been on ambient PM2.5 and, therefore, emissions inventories of primary PM2.5 and its precursors were developed for Hanoi, Bac Ninh, and Hung Yen. Activity data and local emissions factors have been implemented in the GAINS model together with national legislation prescribing either the use of a specific technology or emissions limit values for various air pollutants. Based on this, the GAINS model, supported by the calculations of the fine scale primary PM2.5 using AERMOD, has been used to estimate ambient concentrations of Chapter 3: Understanding How Air Quality Improvements Can be Made 17 PM2.5, and then compared to the available measurement data.16 Finally, the population exposure to PM2.5 in the three provinces was assessed. 3.1.1 Emissions of PM2.5 Precursor Substances In the first step, an emissions inventory for PM2.5 was developed for 2015, relying on published and collected statistical data, published emission factors representing local circumstances, and the new assessment of emissions from craft villages, crop residue burning, as well as transportation, including road dust (see Appendix A). The emissions inventory results shown in figure 3.1 provide the key emissions sources of PM2.5 in Hanoi, Bac Ninh, and Hung Yen. The most important sources of PM2.5 in Hanoi were industrial activities (29 percent), open burning of rice straw (26 percent), road dust (23 percent), and (mainly on-road) transportation (15 percent), with the remaining emissions originating from burning of waste by households and small businesses. The largest sources of PM2.5 in Bac Ninh were craft villages (29 percent) and open burning of crop residues (29 percent), followed by residential/commercial combustion (17 percent), road dust (16 percent), and transportation (7 percent). In Hung Yen, the largest source of PM2.5 was crop residue burning (32 percent) followed by residential/commercial combustion, road dust, industrial activities (each at approximately 20 percent), and transport (7 percent). FIGURE 3.1 PM2.5 emission inventory for 2015 30 PM2.5 emissions (thousand tons) Other 25 Municipal waste Crop residue burning 20 Road dust 15 Transport 10 Industry, excluding craft villages Craft villages 5 Household indoor burning 0 Power plants Hanoi Bac Ninh Hung Yen Province Source: World Bank, IIASA, NIRAS inventory for this study. Note: Household indoor burning includes gas appliances, wood or coal burning stoves, and fireplaces. 16 AERMOD is an integrated air quality model developed jointly by the American Meteorological Society and the US Environmental Protection Agency. It is used to estimate the impact of new and existing sources of air pollution on ambient levels at distances of less than 50 km. For this report, AERMOD model was implemented and run by the Center for Environmental Monitoring and Modelling (CEMM) based on the joint IIASA and CEMM work on data collection and development of inputs for modelling with AERMOD 18 Clean Air for Hanoi: What Will it Take? This air emissions inventory data was used to calibrate the GAINS model and a good match was achieved between the data collected for this study and the data available in the GAINS model from other public sources. The same activity data was also used to estimate emissions of other pollutants, such as NOx, SO2, and NH3, that are considered precursors of ambient PM2.5. Figure 3.2 shows total emissions for the three provinces from key sectors in 2015. FIGURE 3.2 Emissions of PM2.5 precursors in Hanoi, Bac Ninh, and Hung Yen, estimated in this study for 2015 Thousand tons SO2 NOx PM2.5 NH3 Source: World Bank, IIASA, CEMM, VAST, NIRAS for this study The modelling domain is larger than the three provinces and includes transport of air pollution from geographical areas in Vietnam as well as neighboring Asian countries. Industrial activities including craft villages, transportation, and agriculture are key sources of PM2.5 pollution within the three provinces.17 Owing to the successful implementation of policies promoting the use of gas for cooking, biomass use (and coal, in some regions) for cooking has been on the decline and does not represent a large share of emissions in the three regions. The high contribution of agriculture to PM2.5 emissions is related to agricultural sources of ammonia which create ‘secondary PM2.5, and significant amounts of organic agricultural residues, such as rice husks and biomass waste, burned in the fields in Hanoi, Bac Ninh, and Hung Yen (figure 3.2). 17 Since power generation is not relevant in the three provinces as the power plants, especially coal power plants are in the neighbor- ing provinces. Chapter 3: Understanding How Air Quality Improvements Can be Made 19 Based on these emissions estimates for 2015, ambient PM2.5 concentrations across the three provinces have been estimated with the GAINS tool (figure 3.3a). The highest annual average concentrations (over 50 µg/m³) are estimated for the central part of Hanoi city, including urban areas of the Hanoi city. This analysis suggests wide-spread exceedances of Vietnam’s national ambient air quality standard (NAAQS) for PM2.5 of 25 µg/m³. The population exposure distribution is of interest for air quality managers and policy makers who aim to monitor the current status and impact of pollution as well as develop future plans to reduce pollution and related impacts. For 2015, the model analysis suggests that the entire population of the greater Hanoi area was exposed to PM2.5 concentrations above NAAQS, and about 3.5 million people (primarily in the greater Hanoi area), equivalent to about 40 percent, were exposed to concentrations exceeding 45 µg/m3, which is nearly ten times higher than the WHO air quality guideline (AQG) recommendation (figure 3.3b). According to the recent National Environment Status Report for 2016-2020 developed by MONRE, air pollution in Hanoi during this period is higher than other cities. The average annual PM2.5 measured in Hanoi during 2018-2020 were all higher than the national standards by up to over a factor of two times. The highest level was recorded in 2019. This is consistent with project findings from the GAINS model. FIGURE 3.3 Ambient concentrations and population exposure to PM2.5 modelled for 2015 a. Ambient concentrations b. Population exposure measured Total Hung Yen Bac Ninh PM2.5 (μg/m3) Hanoi 0 2 4 6 8 10 Million people exposed to PM2.5 < WHO guideline 10 μg/m3 10 – 15 μg/m3 15 – 25 μg/m3 25 – 35 μg/m3 35 – 45 μg/m3 > 45 μg/m3 Source: World Bank and IIASA Note: Panel a shows the annual mean concentrations in µg/m3 of PM2.5. Panel b shows the distribution of population exposure to ambient PM2.5 in the three provinces as well as the total population of the three provinces in 2015 based on the GAINS modelling carried out for this study. 20 Clean Air for Hanoi: What Will it Take? 3.1.2 Validation A source apportionment analysis performed in GAINS also shows good agreement in terms of primary and secondary particulate matter, although GAINS has a slightly higher share of secondary PM as well as key sources from which ambient PM originates. Figure 3.4 shows the GAINS source apportionment for FIGURE 3.4 GAINS estimate of source Hanoi, indicating that about half of the PM apportionment for Hanoi, 2015-2019 mass is composed of secondary PM. 3.1.3 PM2.5 Source Contributions for Hanoi, Bac Ninh, and Hung Yen in the GAINS Model The results of this study indicate that, despite the large size of Hanoi, only about one-third of PM2.5 (total primary and secondary) in the ambient air originates from local sources, while the rest is transported from the Greater Hanoi/ Red River Delta region, other provinces Source: GAINS model in Vietnam, and even other countries, Note: At Hanoi EPA and 556, Nguyễn Văn Cừ Street. international shipping, and natural sources (figure 3.5). Taking into consideration emissions of primary PM2.5 and its precursors from both local and surrounding domains, transportation sources contributed to about 25 percent of PM2.5 pollution in Hanoi; nearly 35 percent originated from industrial activities, including large power and industrial plants as well as craft villages; 10 percent from the residential sector (primarily cooking with biomass); another 20 percent from ammonia emissions from livestock farming and fertilizer application; about 7 percent from the open burning of agricultural waste, with the remainder from open burning of municipal solid waste. Chapter 3: Understanding How Air Quality Improvements Can be Made 21 FIGURE 3.5 Population-weighted annual mean source contributions of PM2.5 concentrations in Hanoi, 2015 PM2.5 (μg/m3) s s am n en i l no ta ce rie gio To gY ur Ha tn nt re so Vie ou un al l rc dH ra pit th tu he ou ca an Na Ot ds oi inh an an cN rH th Ba he or rn Ot he Ot Source: GAINS model Note: The x-axis distinguishes the spatial origins of PM2.5. The y-axis indicates the amounts of PM2.5 originating from emissions of various economic sectors. A similar picture emerges for the other two provinces (figure 3.6). While these provinces experience slightly lower overall concentrations than those calculated for Hanoi province, the local contribution from the provinces represents no more than 25 percent of the observed concentrations, with most of the remainder originating from other regions in Vietnam, primarily northern Vietnam and about one-third of the remainder associated with long-range transport, that is, international sources, of air pollutants and natural origin. FIGURE 3.6 Population-weighted annual mean source contributions of PM2.5 concentrations in Bac Ninh and Hung Yen provinces, 2015 a. Bac Ninh province b. Hung Yen province PM2.5 (μg/m3) PM2.5 (μg/m3) co es an h V es Ha apit nam Hu n pr n e l co es an h V es Ha pita am nd gion pr h e ta l inc inc io Ye in ta rc tri rc ri To i a l reg n cN nt To Ot sou Ot sou ov ov n ng l re iet iet u u Ba a l l ra ra is is r r r H sout r H sout nd tu tu he he Th Th ca ia c Na Na oi oi no Ot and Ot and no th th he he or or rn rn he he Ot Ot Source: GAINS model Note: The x-axis distinguishes the spatial origin of PM2.5, and the y-axis indicates the amounts originating from emissions of the different economic sector. 22 Clean Air for Hanoi: What Will it Take? 3.2 Future Air Quality Future air quality in Vietnam will be determined by several factors such as the pace of economic development and the adoption and implementation of new regulations on emissions controls. The analysis undertaken for this study includes the impacts of various policy scenarios on ambient concentrations of PM2.5 and population exposure and further explores mitigation opportunities and their impacts. Specifically, the implementation of best available measures is used to design strategies to achieve the lowest attainable pollution levels for a given policy case. Finally, the research also considers the cost-effectiveness of meeting the national PM2.5 NAAQS. 3.2.1 Socioeconomic Development Trends Baseline projections in this study are based on targets including population, economic development, and energy consumption, and follow the projections provided in the National Socio-economic Development Plan Report. The Plan depicts an annual GDP growth of 6-7 percent per year between 2016 and 2020 (Nhan Dan 2020). Population projections are provided by the General Statistics Office and UNFPA, foreseeing an increase in urbanization rate up to 38- 40 percent by 2020. These projections were complemented by the Vietnam Energy/Renewable Energy Development Strategy to 2020 with vision to 2050 (Prime Minister 2007; Prime Minister 2015), the Vietnam Green Growth Strategy to 2030 with vision to 2050 (Prime Minister 2012), and sectoral development plans for agriculture, industry, and transportation. Regional distribution of economic growth is based on provincial developments plans. Overall, the projections assume an annual population growth in northern Vietnam of 1 percent per year, resulting in a 10.1 percent larger population in 2030 compared to that in 2020. At the same time, economic wealth (expressed as GDP per capita) is projected to grow by 6.5-7.0 percent per year. Transportation demand is assumed to follow the same trajectory. The economic projection is accompanied by an energy forecast that predicts a decline in energy intensity in Hanoi, Bac Ninh, and Hung Yen provinces, and an increase in energy intensity in the Greater Hanoi/Red River Delta region due to the migration of industrial activities to this region. The remainder of this section describes the projections for each policy scenario, outlined in table 2.1, up to 2030. 3.2.2 The Policies before 2020 Scenario Assuming that regional economic trends provided in the underlying energy projection are achieved and that the current policies are effectively implemented, ambient PM2.5 concentrations are expected to continue increasing in the region compared to current levels up to 2030. Computed maximum average concentrations of PM2.5 would increase from less than 50 µg/m³ Chapter 3: Understanding How Air Quality Improvements Can be Made 23 to nearly 60 µg/m³ (figure 3.7a), which is more than twice Vietnam’s NAAQS of 25 µg/m³ and would exceed the global WHO guideline value of 10 µg/m³ by a wide margin. FIGURE 3.7 Ambient concentrations and population exposure to PM2.5 in the policies before 2020 case in 2030 for Hanoi, Bac Ninh, and Hung Yen a. Ambient concentrations b. Population exposure Hung Yen Bac Ninh Hanoi PM2.5 (μg/m3) 0 1 2 3 4 5 6 7 8 9 Million people exposed to PM2.5 < WHO guideline 10 μg/m3 10 – 15 μg/m3 15 – 25 μg/m3 25 – 35 μg/m3 35 – 45 μg/m3 > 45 μg/m3 Source: GAINS model Population-weighted PM2.5 concentrations would rise across the region and lead to worsening air quality, exposing entire populations in the three provinces to levels well above the NAAQS of 25 µg/m³. A significant portion of the population would reside in areas where PM2.5 concentrations would be close to or above five times the WHO recommended guideline of 10 μg/m3 for PM2.5 (figure 3.7b). As emissions growth is expected to be similar in all three provinces, the spatial source apportionments do not change remarkably over time in relative terms. Compared to 2015, PM2.5 concentrations increase by about 10 µg/m³ reaching 50-60 µg/m³ in the capitals of the three provinces. The largest increase in ambient PM2.5 is expected to come from emissions from the power sector, owing to expected expansion in coal capacity without strengthening current emissions limits for PM, SO2, and NOx. The agricultural sector becomes increasingly important as a source of PM2.5 as there are no current policies targeting ammonia emissions. In addition, agricultural production is expected to keep growing (figure 3.8). 24 Clean Air for Hanoi: What Will it Take? FIGURE 3.8 Source attributions to population-weighted PM2.5 concentrations in the policies before 2020 projection in 2030 a. Hanoi b. Bac Ninh province PM2.5 (μg/m3) PM2.5 (μg/m3) s s m n en i l s es m ion n inh l no ta ta rce rie ce gio Ye na na tri To To gY Ha ur eg cN nt ou n ng re iet iet so u u un r Ba ls co o al al Hu hV hV l c dH ra ra pit pit er r ut ut nd tu tu he ca ca an h so so Na Na ia Ot Ot oi oi inh d d no an an an an Ha cN rH rH th th Ba he he or or rn rn Ot Ot he he Ot Ot c. Hung Yen province PM2.5 (μg/m3) s s m n oi n l ta rce rie gio Ye an na To nt ou ng dH re iet u ls co al Hu hV an ra pit er ut tu inh ca h so Na Ot cN oi d an an Ba rH th he or rn Ot he Ot Source: GAINS model Note: The graph shows the contributions to population weighted PM2.5 concentrations in the Hanoi, Bac Ninh, and Hung Yen province. The x-axis distinguishes the spatial origin of PM2.5, and the y-axis indicates the amounts originating from emissions of the different economic sectors. Chapter 3: Understanding How Air Quality Improvements Can be Made 25 3.2.3 The New Policies in Effect from 2021 Along with NDC 2020 Scenarios The introduction of the recently-announced policies as well as climate and SDG-motivated actions proposed in the 2020 NDC would result in improved air quality compared to the policies before 2020 scenario (figure 3.9), according to GAINS model analysis. New policies that have gone into effect from 2021 would reduce the maximum observed annual average PM2.5 concentrations to below 50 µg/m3, which are still very high. About 70 percent of the population in Hanoi province would experience PM2.5 levels above 45 µg/m3, while in Bac Ninh and Hung Yen provinces it would be about 30 percent of the population. Importantly, the entire population in the three provinces would be exposed to PM2.5 levels above 35 µg/m3. The new policies in effect from 2021 along with the implementation of NDC 2020 scenario brings significant qualitative changes, reducing maximum PM2.5 concentrations to below 35 µg/m3 in most of the targeted area; however, only small share of the population would enjoy concentrations within the NAAQS (figure 3.9c). Overall, the typical range of annual average PM2.5 concentrations is within 25-35 µg/m3, with about 15 percent of population, mostly in urban areas of Hanoi province, exposed to levels above 35 µg/m3. This preliminary analysis shows that with current economic growth assumptions, even implementation of proposed policies appears to be insufficient to reach wide compliance with NAAQS for PM2.5. It should be noted that the interpretation and implementation of the primarily national-level goals of the policies before 2020 scenario and the new policies in effect from 2021 along with NDC 2020 scenario carry uncertainties about how they would impact regional energy structure, transportation policy, agricultural activities, and so on. These national-level strategies could change the results of this scenario, potentially reducing exposure in some areas, but the overall recommendation is to consider further actions than those already announced. 26 Clean Air for Hanoi: What Will it Take? FIGURE 3.9 Ambient concentrations and population exposure to PM2.5 in 2030 for the policy scenarios considered in the analysis for Hanoi, Bac Ninh, and Hung Yen A. Policies before 2020 scenario a. Ambient concentrations b. Population exposure Hung Yen Bac Ninh PM2.5 (μg/m3) Hanoi 0 1 2 3 4 5 6 7 8 9 Million people exposed to PM2.5 < WHO guideline 10 μg/m3 10 – 15 μg/m3 15 – 25 μg/m3 25 – 35 μg/m3 35 – 45 μg/m3 > 45 μg/m3 B. New policies in effect from 2021 scenario a. Ambient concentrations b. Population exposure Hung Yen Bac Ninh PM2.5 (μg/m3) Hanoi 0 1 2 3 4 5 6 7 8 9 Million people exposed to PM2.5 < WHO guideline 10 μg/m3 10 – 15 μg/m3 15 – 25 μg/m3 25 – 35 μg/m3 35 – 45 μg/m3 > 45 μg/m3 C. New policies in effect from 2021 with NDC 2020 scenario a. Ambient concentrations b. Population exposure Hung Yen Bac Ninh PM2.5 (μg/m3) Hanoi 0 1 2 3 4 5 6 7 8 9 Million people exposed to PM2.5 < WHO guideline 10 μg/m3 10 – 15 μg/m3 15 – 25 μg/m3 25 – 35 μg/m3 35 – 45 μg/m3 > 45 μg/m3 Source: GAINS model Chapter 3: Understanding How Air Quality Improvements Can be Made 27 Figure 3.9 shows how the implementation of the new and NDC policies could modify PM2.5 concentrations for Hanoi and the surrounding regions. As indicated above, both the policies before 2020 scenario and the new policies in effect from 2021 along with NDC 2020 scenario result in declines in PM2.5 concentrations from nearly 60 µg/m3 in the policies before 2020 case to about 35 µg/m3 in the new policies + NDC 2020 scenario. Notable improvements to air quality are seen, with significant impacts from power sector policies in the NDC and strengthening emission limit standards in industry, as well as improvements in nitrogen use efficiency in the agricultural sector, and finally in waste management. A large proportion of the reductions are achieved through measures introduced outside of Hanoi province. For instance, there are no coal-fired power plants in Hanoi province, highlighting the importance of collaboration when developing the next AQM plan and related policy. The key conclusion from the analysis of these scenarios is that without additional measures, none of these scenarios would be sufficient on their own to meet the national PM2.5 standard; therefore, further actions are needed, which are analyzed in the next sections of this chapter. FIGURE 3.10 Source contributions for Hanoi in 2030 a. Policies before 2020 scenario b. New policies in effect from 2021 scenario PM2.5 (μg/m3) PM2.5 (μg/m3) s es am d H ion en i l s s am d H ion en i l no no ta ta rce rce rie tri To To gY gY g Ha g Ha tn tn nt ou ou n l re re e Vie ou ou un un i ls ls al hV a rc rc ra ra c N apit c N apit th ut tu tu he he ou an an so c c Na Na Ot Ot ds oi oi inh inh d an an an an rH rH th th Ba Ba he he or or rn rn Ot Ot he he Ot Ot c. New policies in effect from 2021 along with NDC 2020 scenario PM2.5 (μg/m3) s es am d H ion en i l Source: GAINS model no ta rce tri To gY g Ha tn ou n l re e ou un i ls hV Note: The graph shows the contributions to population- a rc ra c N apit ut tu he an so c Na weighted PM2.5 concentrations in the Hanoi EPA station. Ot oi inh d an an rH The x-axis distinguishes the spatial origin of PM2.5, and th Ba he or rn Ot the y-axis indicates the amounts originating from he Ot emissions of the different economic sectors. 28 Clean Air for Hanoi: What Will it Take? BOX 3.1 The Maximum Technically Feasible Reduction Scenario A possible scenario applying the maximum technically feasible measures consists of strengthening emission limit values or actions based on the assumption that the best available technologies to reduce emissions would be used and supported by more stringent management methods. Three maximum technically feasible reduction (MTFR) scenarios are established. The measures considered in the MTFR scenario would tighten emission limit values for large point sources for SO2, NOx, and PM/Total Suspended Particles (TSP, also known as dust). For mobile sources, tighter controls would be introduced for non-road mobile machinery, and emissions standards for road vehicles would progress to the Euro 6 level. Experiences from Europe are used to derive a set of measures reducing ammonia losses from agriculture, which include low-emission stables, enclosed storage of manure, efficient application of manure on land, as well as further reduced use of urea as fertilizer (or, alternatively, urea substitution or improved fertilizer application methods). In the waste management sector, measures include moving towards high rates of collection and recycling as well as proper operation of sanitary landfills with methane gas recovery. Finally, halving resuspended dust is also assumed by expanding the network of paved roads and introducing measures to suppress dust on the roads. Widespread implementation of low-emission technologies translates into very strong declines of emissions and improved air quality indicators. Taking the policies before 2020 scenario with MTFR, about 85 percent of population in the three provinces would be exposed to a level of PM2.5 compliant with NAAQS and no areas appear to have annual concentrations over 35 µg/m3 (figure B3.1). Combining the new policies in effect from 2021 scenario with MTFR would result in full compliance with PM2.5 NAAQS, and in some areas around 10 percent of the population would see PM2.5 concentrations below 15 µg/m3. In the final MTFR scenario, which combines NDC policies and assumes that similar policies are implemented in other parts of Asia, full compliance with PM2.5 NAAQS is achieved and PM2.5 concentrations for the entire population are below 15 µg/m3, including from natural sources. As a result, anthropogenic source contributions are below the AQG of WHO. FIGURE B3.1 Ambient concentrations of PM2.5 and population exposed to PM2.5 with the application of MTFR in the three provinces in 2030 Policies before 2020 + MTFR scenario a. Ambient concentrations b. Population exposure Hung Yen Bac Ninh PM2.5 (μg/m3) Hanoi 0 1 2 3 4 5 6 7 8 9 Million people exposed to PM2.5 < WHO guideline 10 μg/m3 10 – 15 μg/m3 15 – 25 μg/m3 25 – 35 μg/m3 35 – 45 μg/m3 > 45 μg/m3 Chapter 3: Understanding How Air Quality Improvements Can be Made 29 FIGURE B3.1 Ambient concentrations of PM2.5 and population exposed to PM2.5 with the application of MTFR in the three provinces in 2030 (cont.) New policies in effect from 2021 + MTFR scenario a. Ambient concentrations b. Population exposure Hung Yen Bac Ninh PM2.5 (μg/m3) Hanoi 0 1 2 3 4 5 6 7 8 9 Million people exposed to PM2.5 < WHO guideline 10 μg/m3 10 – 15 μg/m3 15 – 25 μg/m3 25 – 35 μg/m3 35 – 45 μg/m3 > 45 μg/m3 2020 NDC + MTFR scenario a. Ambient concentrations b. Population exposure Hung Yen Bac Ninh PM2.5 (μg/m3) Hanoi 0 1 2 3 4 5 6 7 8 9 Million people exposed to PM2.5 < WHO guideline 10 μg/m3 10 – 15 μg/m3 15 – 25 μg/m3 25 – 35 μg/m3 35 – 45 μg/m3 > 45 μg/m3 Source: GAINS model The analysis indicates that massive PM2.5 emissions reductions across all sectors and regions are needed to achieve the reductions.18 18 It is important to note that all MTFR scenarios assume implementation of measures across all provinces in Vietnam and, in the NDC scenario with MTFR, also for Asia. 30 Clean Air for Hanoi: What Will it Take? 3.2.4 The Cost-effective Scenario to Reach the NAAQS PM2.5 Target The GAINS model identified a portfolio of cost-effective measures across all provinces in Vietnam to comply with NAAQS for PM2.5 across the three provinces. In other words, the population- weighted PM2.5 annual mean concentration does not exceed 25 µg/m3 in the greater Hanoi area in the Cost-efficient achievement of the national standard for PM2.5 scenario described in Table 2.1. 2.1. This is also in line with the WHO’s interim target for 2030 of 25 µg/m3. In the optimization mode, the GAINS model uses data about the atmospheric transport, population distribution, and differences in control costs across the region. Exploring the full potential of emissions mitigation by applying proven technological measures across all sectors and pollutants (including precursors of secondary PM: SO2, NOx, and NH3) would allow the achievement of PM2.5 NAAQS across the entire region by 2030 (figure B3.1). But this would be accompanied by implementation and enforcement challenges as well as high costs (figure 3.12). Furthermore, the analysis indicates that even the most stringent emissions control measures, if restricted only to the Hanoi area (or another single province), will not be sufficient to effectively reach Vietnam’s PM2.5 NAAQS. Policies that focus on Hanoi province alone could reduce ambient levels of PM2.5 in 2030 by not more than 20 percent, down to about 48 µg/m³, which is still nearly twice the NAAQS. In this scenario, the majority of the pollution comes from outside Hanoi province, and hence coordinated action with neighboring provinces is indispensable for any effective improvements in air quality within Hanoi. To summarize, effective improvements in Hanoi’s air quality requires further action and it must necessarily be coordinated with neighboring provinces. Cost-effective measures, beyond the policies before 2020 scenario, include strengthening national emissions limits for PM2.5 and SO2 emissions from large combustion installations, including power plants that, together with industry, could contribute to over 30 percent of the achieved PM2.5 reductions, and nearly all of this potential is actually outside of Hanoi province. Key measures for these plants include flue gas desulfurization and high-efficiency dust filters. Other measures with significant potential include banning open burning of crop residues and addressing ammonia emissions from mineral and organic fertilizer manure, which is important locally as well as from regional sources in Vietnam, contributing to about 25 percent of total declines in PM2.5 concentrations. Finally, in the transportation sector, further tightening of standards for road (especially motorcycles) and non-road vehicles as well as incentives for public transport would play an important role further reducing PM2.5 concentrations by about 5 µg/m3. Chapter 3: Understanding How Air Quality Improvements Can be Made 31 FIGURE 3.11 Sources of PM2.5 concentrations (population-weighted annual mean) in Hanoi in 2030 60 60 a. Policies before 2020 scenario b. Cost-efficient achievement of the national standard 50 50 scenario for PM 2.5 ) (μg m3) PM2.5 (μg m3) 40 40 60 60 60 60 30 50 50 50 30 50 2.5 PM PM2.5 (μg m3) PM2.5 (μg m3) PM2.5 (μg m3) 40 40 40 40 3 20 20 PM2.5 (μg m 30 30 30 30 10 10 20 20 20 20 100 10 10 0 10 es es m dtnH ion i l s ies i a am ion oi l gi Yen en no ta ta ce an un am tna thrt er he rces urc u sl so ies tri l To To Vi ces tr Hu H n g Y Ot t o n u thu our on g p un am reg ng oi Ha n 0 0 0 0 n sun n H l r Yen ng th gi esl re n u i l ies et ou so e ur nt u on i i l ss at u r co th ur eo nl s am Hu Han n Tonoi l m Yeoi To i l l rV V u Hu n n no ta ta ta ta h inu re tirtia ric ietnce r c ce l s al o cahH tn o ou so rtrc Ye l d Ye ngan he ort the urra tna i o nd Viepgit h ita th To To i r r an reg Ha Ha ra ur V u i d so tal p ut n ap un c N api ung tan g e u anh a th care et he he rthd s ral e i c cou O asto c nie oa tu at HOath th o ther o erso o o aV c N n pi c a t al in ia c oi d H a t Na N N O r n h a Na O r o o an anh sod d tu e d d a th oi cn hec N d s n h h t an Ba Niin Ot tht ndan atn o Na t OtBa anHa N O not r Ha O r H nN h h ah or an n in c ac r n Hr i a cN he a BH re ro Ot B he eh rh r Ba Ba r on OO rO rn Ot er n O ee thh h Ot Ot O MunicipalMunicipal Agriculture Agriculture TransportTransport Industry Industry Residential Residential Power PowerCement Cement Soil dust, Soil dust, Municipal waste waste Agriculture Transport Residential Industry plant Power plant Cement seasaltSoil dust, seasalt waste plant seasalt Source: GAINS model Note: The x-axis distinguishes the spatial origin of PM2.5, the y-axis indicates the amounts originating from emissions of the different economic sectors. 3.3 Emissions Scenarios and their Population Exposure and Costs Impacts The policy intervention options discussed in previous sections result in varied emissions reductions of PM2.5 precursors across the various regions, which in turn, have different impacts on population exposure due to differences in climatic, meteorological, and topographic conditions as well as in population densities. The following sections provide a summary of emissions and total regional population exposure across all potential scenarios. 3.3.1 Emissions The various scenarios have different emissions trajectories as well as different mitigation potentials. The key features of various scenarios, in terms of emissions of primary PM and PM2.5 precursors, show the emissions trajectories over time (2015 vs 2030) as well as the key emissions mitigation potential arising from the policies embedded in the scenarios. Continuing enforcement of policies that enable clean energy access for cooking, regulate industrial emission standards, and ban crop burning would lead to reduced emissions of air pollutants. However, NOx emissions from transportation and ammonia are expected to increase over time. Additionally, since no new standards for power sector have been introduced, emissions in neighboring provinces will increase significantly as a result of growing coal-fired power plant 32 Clean Air for Hanoi: What Will it Take? capacity. The exception to this is the NDC scenario, where increases in renewable energy sources and supercritical plant capacity are expected to decrease emissions from the power sector as well as decrease ammonia emissions from the agricultural sector with the reduction in urea and improvements in nitrogen use efficiency. The policies before 2020 and new policies in effect from 2021 scenarios do not assume that emission limits for coal-fired power plants are strengthened; however, best available regulatory practices in Asia show that PM2.5, SO2, and NOx can be further reduced to attain very strict emission limit values. These emissions may be decreased by using more efficient PM filters, flue gas desulfurization, and selective catalytic reduction, resulting in significant air quality improvements as is shown in the MTFR scenario and in the cost optimization to achieve national standards scenario (figure 3.11). In summary, further emissions mitigation has been identified that would allow reduction of key air pollutant emissions by up to 85 percent by 2030, compared to the policies before 2020 scenario. 3.3.2 Population Exposure This section summarizes the impact on population exposure of the various scenarios analyzed for this study. Here, populations considered include those in the greater Hanoi area, which include Hanoi, Bac Ninh, and Hung Yen provinces. Even though policies currently exist to improve air quality, the air quality in Hanoi is expected to deteriorate in the future. The newly-announced polices are likely to bring improvements in terms of the population exposed to harmful air pollutants, but air quality in Hanoi, Bac Ninh, and Hung Yen is expected to remain out of compliance with national requirements. Taking into consideration the anticipated increase in economic activities, it is estimated that without additional policy measures, PM2.5 concentrations in Hanoi and neighboring provinces would increase further by 2030. This implies that almost the entire population in the three provinces would be exposed to poor air quality, exceeding the PM2.5 NAAQS and severely exceeding WHO guidelines for PM2.5 (see policies before 2020 and new policies in effect from 2021 scenario results in figure 3.9). Expanding the new policies in effect from 2021 scenario would result in considerable improvements but would still leave the majority of the population exposed to levels above 25 μg/m3. The recently-announced polices bring improvements in terms of population exposure but are far from compliance with NAAQS; therefore, most of the population suffers from the negative impacts of high air pollution. This could be mitigated only with the introduction of additional measures and would result in widespread compliance with NAAQS as well as significantly lower population expose to PM2.5 (figure 3.12). Identified emissions mitigation potential for primary PM2.5 and precursor gases of ambient PM2.5 allows the achievement of national standards. Figure 3.9 illustrates the population-weighted Chapter 3: Understanding How Air Quality Improvements Can be Made 33 exposure resulting from the application of the whole GAINS model portfolio of low emissions measures, which implies implementation of reductions as MTFR. While such scenario achieves the national standard across the whole region, it is associated with very high costs (figure 3.13). Employing GAINS model optimization allows the achievement of the standards at a fraction of the MTFR cost (figure 3.13). FIGURE 3.12 Distribution of population exposed to ambient PM2.5 in Hanoi, Bac Ninh, and Hung Yen in 2015 and emissions scenarios for 2030 < WHO guildline 10 µg/m3 10 - 15 µg/m3 15 - 25 µg/m3 25 - 35 µg/m3 35 - 45 µg/m3 > 45 µg/m3 MTFR Cost optimization scenario New policies in e ect from 2021 along with NDC 2020 MTFR Cost optimization scenario New policies in e ect from 2021 MTFR Cost optimization scenario Policies before 2020 2015 Population exposed to PM2.5 (millions) Source: GAINS model 3.3.3 Emissions Control Costs A preliminary cost analysis of analyzed scenarios on the basis of international costs as per the GAINS model reveals that the new policy and NDC scenarios that promote an increased share of renewable energy, more efficient coal-fired power plants, and effectively ban open burning of waste, results in ‘savings’, compared to the costs associated with the implementation of additional measures in the policies before 2020 scenario, in order to achieve compliance with the PM2.5 NAAQS of 25 µg/m3 (figure 3.13). Implementing the policies included in the 2020 NDC, as an extension of the new policies in effect from 2021 scenario, would play an important role in improving the cost efficiency of achieving PM2.5 NAAQS across the three provinces. 34 Clean Air for Hanoi: What Will it Take? FIGURE 3.13 Initial estimate of additional air pollution control costs to meet national standards as well as MTFR scenario Million Euros/year Policies before 2020 National standard (opt) Maximum reduction New policies in effect from 2021 National standard (opt) Maximum reduction New policies in effect from 2021 along with NDC 2020 National standard (opt) Maximum reduction Source: GAINS model Note: Figure shows the initial estimate of additional air pollution control costs (compared to the policies before 2020 scenario) for the cost-efficient achievement of PM2.5 NAAQS and for the under MTFR scenario. 3.4 Determining Cost Effectiveness through Marginal Abatement Cost Curves for Selected Key Air Quality Measures For selected key air quality measures, some example marginal abatement cost curves (MACC)19 on the basis of localized Vietnamese costs were prepared to analyze cost effectiveness of measures to reduce PM2.5, taking into account the following observations: 19 Marginal abatement cost curves are the costs that are either spent or saved per unit of reduced emissions (usually per ton) for a specific unit of time (normally per year). The formula for calculating MACC is: MACC = (Cns - Cbs)/GHG, where: • Cns: Total cost of implementing emission reduction measures in a unit of time • Cbs: Total cost of the base (business-as-usual) measure in a unit of time • GHG: The amount of emissions reductions when applying the measure in a unit of time MACC can be negative or positive. A negative MACC implies that when implementing an emissions reduction measure, the cost of implementation is less than the cost of the BAU activities. Chapter 3: Understanding How Air Quality Improvements Can be Made 35 For the Hanoi region, the highest abatement options for PM2.5 come from the transport sector. Within this sector, four measures are shown in figure 3.14. The measures include (i) Using electric motorbikes to replace conventional motorbikes; (ii) Electric vehicles fossil fuel- powered cars; (iii) Introduction of EURO 5 or EURO 6 vehicles; and (iv) Replacement of diesel buses with clean energy buses. Investment needs for this sector are estimated at €1.56 billion, including electrification of fossil fuel-powered and motor bikes and introduction of higher emissions standard from EURO 5 to EURO 6. FIGURE 3.14 Marginal abatement cost curve for transportation in Hanoi outlook by 2030 Replace diesel buses with clean energy buses 25,190 tons of PM2.5 €2,689,000/ ton of PM2.5 Introduce EURO 5 and 6 vehicles €16,000/ ton of PM2.5 834,211 tons of PM2.5 -€200/ton of PM2.5 -€390/ Replace fossil fuel-powered Replace fossil fuel-powered ton of PM2.5 scooters with e-scooters cars with EV cars Cumulative tons of PM2.5 Source: World Bank. In the MACC graph, the x-axis represents the marginal abatement cost curves of the measures and the y-axis shows the PM2.5 abatement potential. With the transport sector, the intervention of replacing fossil fuel power scooters with e-scoorters and fossil fuel-powered cars with EV cars brings about the largest decrease in the amount of PM2.5. In addition, the MACC is negative, for these measures. In general, replacing conventional vehicles with electric vehicles are optimal measures because large amounts of PM2.5 can be decreased. 36 Clean Air for Hanoi: What Will it Take? With regard to the measure that replaces conventional gasoline motorbikes with e-motorbikes, the assumption is that the number of motorbikes remains the same. This would result in the MACC being negative. The total costs of using an e-motorbike (including investment cost to purchase the vehicle, charging and repair costs) over the lifespan of an electric vehicle are lower than the total costs of using a conventional motorbike, factoring in the purchase cost, fuel costs, and repair costs. In the industrial sector, six mitigation measures were considered, in which (1) waste heat recovery for power generation, (2) waste heat recovery from paper drying, and (3) advanced high-efficiency filters to remove PM for stationary combustion are among the top abatement options, resulting in a reduction of about 533 tons of PM2.5 by 2030 (figure 3.15). Investment needs for this sector are estimated at €775.8 million. FIGURE 3.15 Marginal abatement cost curve for the industrial sector in Hanoi outlook by 2030 200 Upgrade calciner & preheater (ton PM2.5: 19) 150 100 Advanced high-efficiency filters Waste heat recovery for power generation (ton PM2.5: 170) to remove particulate matter Thousand Euros per ton of PM2.5 50 for stationary combustion 0 -50 -100 -150 Steam saving by trap management (ton PM2.5: 0) -200 -250 Flare gas recovery (ton PM2.5: 2) -300 Waste heat recovery from paper drying (ton PM2.5: 176) Cumulative tons of PM2.5 Source: World Bank The best emissions reduction measures of the six industry measures is waste heat recovery from paper drying. Annually, this measure has a PM2.5 abatement potential of 176.13 tons. Other measures that also have a negative MACC are steam saving by trap management and advanced high-efficiency filters to remove PM from stationary combustion. In addition, for the remaining two measures, although the MACCs are positive, when implemented, will also help reduce large emissions. Specifically, waste heat recovery for power generation can reduce 169.83 tons of PM2.5 annually in the three provinces. Chapter 3: Understanding How Air Quality Improvements Can be Made 37 The agricultural sector was not considered in this cost effectiveness analysis as key efforts such as ban of on-farm biomass burning in Hanoi region could bring significantly high abatement effects (2,800 tons of PM2.5 reduced in greater Hanoi region only) without large investment needs, with an outlook by 2030. 38 Clean Air for Hanoi: What Will it Take? CHAPTER 4: Clean Air for Hanoi by 2030: What Will it Take? Given the range of human-induced air pollution sources that have been identified in the greater Hanoi area, a multi-sectoral and a multi-province approach is needed to improve air quality. The GAINS model was used to determine what would be required to make air quality in the Hanoi region compliant with the national ambient air quality standard (NAAQS) by 2030, which stipulates that the population-weighted annual mean concentration of PM2.5 should not exceed 25 μg/m3. Determining cost-effective measures requires balancing what is technically possible with what is financially achievable. Given the structure of emissions, the GAINS model in the optimization mode uses data on population distribution, atmospheric transport, and control cost differences across regions to identify a portfolio of cost-effective measures to comply with the NAAQS for PM2.5 across the three provinces. Chapter 4: Clean Air for Hanoi by 2030: What Will it Take? 39 4.1 Key Sector Interventions The following are key air quality interventions recommended for implementation in Vietnam based on measured pollution levels, assessed population impacts, and policy effectiveness: 1. Energy sector: Further strengthening of emission limit values for power plants and industry, including a continual reduction of coal and biomass use in boilers and furnaces in craft villages. 2. Waste management sector: Developing sustainable waste management strategies to ensure the elimination of open burning of solid waste, such as higher collection rates, separation, and recycling, effectively enforcing the ban on open burning, and recovery of landfill gas, which has important co-benefits for climate change mitigation due to associated methane reductions. 3. Transport sector: Strengthening and enforcing emissions control standards for motorcycles, promoting public transport, accelerating electrification of vehicles, introducing measures to suppress road dust, all of which would achieve marked improvements in air quality and quality of life, especially in urban areas. 4. Agriculture sector: Addressing sources of ammonia from agriculture, which is an important part of the air quality management plan. So far, the agricultural sector in Vietnam has not been subject to strict regulations related to air pollution, but it is a growing source of particulate pollution as ammonia contributes to the formation of secondary particulate matter. Targeting both air quality pollutants and greenhouse gases at the same time in the key polluting sectors of energy, industry, transportation, and agriculture can provide substantial co-benefits to both improving air quality while mitigating climate change. This will help Vietnam reduce emissions for better air quality by 2030, while at the same time achieving its commitments under its updated NDC. 4.2 A Coordinated Regional and National Mechanism is Needed for Air Quality Management With much of the air pollution recorded in Hanoi, Bac Ninh, and Hung Yen originating outside the region, policy responses must be considered and coordinated at all levels—local, regional, and national. The analysis provided by the GAINS modelling for this study indicates that even the strictest emission control measures—if restricted to the Hanoi area or another single province—would fall short of meeting Vietnam’s requirements for air quality, that is, its NAAQS. Measures focused on Hanoi province alone could reduce ambient levels of PM2.5 in 2030 by a maximum of 20 percent 40 Clean Air for Hanoi: What Will it Take? down to about 48 μg/m³, which is still nearly twice the national ambient air quality standard. Therefore, for any significant improvements in air quality in Hanoi, Bac Ninh, and Hung Yen, coordinated action with bordering provinces is essential. This is particularly important in the energy and agricultural sectors, as emissions from these sectors, particularly, are transported long distances and contribute to high levels of air pollution in surrounding regions. Establishment of an inter-provincial coordination mechanism for air quality management is strongly recommended. 4.3 Enforcement is Key Strict enforcement of policies targeted at reducing PM2.5 emissions is key to achieving better air quality. Measures to reduce PM2.5 emissions must align private incentives with policy objectives. Policies must be designed with appropriate enforcement arrangements in mind, adopting a carrot and stick approach. Policy options for certain sectors, namely energy, industry, cement production, transportation, agriculture, and waste management, are summarized in table 4.1. TABLE 4.1 Policy options to reduce PM2.5 emissions from key sectors Sector Key Policy Options ENERGY Coal power plants • Strengthen emission limit values for existing and new coal-fired power plants • Apply more efficient end-of-pipe filters • Flue gas desulphurization Craft villages • Reduce coal and biomass use in boilers and furnaces in craft villages INDUSTRY • Improve capture and removal of industrial process emissions, e.g., from the steel industry • Reduce coal use in industrial processes Biomass combustion • Introduce stricter emission limits on biomass combustion Cement production • Introduce stricter emission limits on cement production Brick kilns • Improve efficiency and introduce emissions standards • Reduce coal use TRANSPORT Dust control • Suppress road dust by paving more roads and wet cleaning urban areas • Requirements for dust control at construction sites Emission standards for • Strengthen and monitor/enforce emission control standards for vehicles and vehicles motorcycles Low-emission zones • Define and apply low-emission zones in designated central areas of the city High-emitting vehicles • Enforce a strict policy against high-emitting vehicles, including two-wheelers, eventually leading to total phase out of such vehicles Chapter 4: Clean Air for Hanoi by 2030: What Will it Take? 41 TABLE 4.1 Policy options to reduce PM2.5 emissions from key sectors (cont.) Sector Key Policy Options Electrification of vehicles • Accelerate the electrification of vehicles and motorcycles, including with priority high emitting vehicles, buses, taxis and/or ride sharing firms. These can bring quick results as they are high emitting and/or a large share in the distances driven within cities. • Install charging stations and power infrastructure • Eventually lead to a total phase out of internal combustion engine vehicles (ICEV) Public transport • Promote the use of public transport AGRICULTURE Agricultural crop • Enforce a strict ban on agriculture residue burning and encourage better management residues of agricultural residues Nitrogen fertilizer • Replace urea with ammonium nitrate application • Ensure efficient application of urea fertilizer when used Livestock manure • Introduce low-emission covered storage for manure storage and biogas applications management • Ensure efficient application of manure WASTE MANAGEMENT Residential waste • Strictly enforce a ban on open burning of municipal solid waste, including by burning households Recycling • Improve waste collection, sorting, and recycling Landfill management • Eliminate open burning of solid waste through bans • Eliminate open dumpsites and dispose waste in sanitary landfills • Infrastructure to capture methane emissions from landfills, avoid organic waste to be disposed of in landfills and composted instead BOX 4.1 Examples of air quality actions around the world In the Hebei Air Quality Action Plan in China, cost-effective measures were agreed across all sectors and with substantial ear-marked fiscal budget from central and provincial governments. Between 2013 to 2017, air quality improved by 39 percent in Hebei and by 35.6 percent in Beijing due to the measures put in place. In addition, these measures resulted in the reduction of 4-6 million tons of CO2 emissions as a co-benefit. Specifically, there are numerous cost-effective measures in the transport sector, many of which have already been demonstrated to enable quick transformation and result in cleaner air. Other examples include: • Within the European Union, countries that have been actively promoting zero- and low-emitting cars, such as battery electric vehicles (BEVs) and plug-in hybrid vehicles (PHEVs), have significantly reduced their CO2 emissions. This has also resulted in other environmental benefits in these countries, such as reductions in NOx and PM emissions as a result of the uptake of electric vehicles (EVs). The effects of tax incentives that promote low-emitting conventional cars are less clear (EEA 2019). 42 Clean Air for Hanoi: What Will it Take? BOX 4.1 Examples of air quality actions around the world (cont.) • China leads the world in deployment of electric vehicles. At the end of June 2019, almost half of the electric cars and 99 percent of the electric buses in the world were in China. China also dominates global markets for low-speed electric vehicles and electric two-wheelers. Electric bicycles are omnipresent in China today and the number of EV charging stations is growing rapidly (Columbia University 2022). • Indonesia is aiming to put two million electric motorcycles on the road by 2025 by: (i) increasing the number of charging stations or increasing easy access to battery swap stations; (ii) ensuring the production of quality electric motorcycle batteries; and (iii) ensuring the quality of the motors found in electric motorcycles (Tyler 2022). • London introduced congestion charges in 2003 and low-emission zones with air quality improving 19 percent compared to 2016. More charging stations and ultra-low emissions zones will be put in place with EVs being exempt (Fortuna 2022). Examples of various policies that promote the e-mobility transition and examples are shown in the table B4.1.1 below. TABLE B4.1.1 Policies that promote the e-mobility transition Incentives/Mechanisms Challenge Example Supply incentives Innovation market failure; • Promote technology development and need to jump-start supply encourage manufacturers to bring more EVs to market Unpriced environmental • Reduce the cost of EVs to consumers to externalities; need to jump- make EVs price competitive with ICEVs20 start demand • Provide credit lines or leasing mechanisms Direct demand to facilitate purchase of EVs Consumers and municipalities incentives • Unlock access to carbon finance for charging are credit-constrained and infrastructure may be unable to access • Eventually have complete ban on ICEVs21 necessary finance Information market failures • Provide non-monetary inducements such as Indirect demand informing potential EV owners or making EV incentives operations more convenient Charging and power Network dependencies • Reduce EV owners’ anxiety about reliable infrastructure (chicken-and-egg problem) vehicle operations Unpriced environmental • Encourage bus operators, taxis, or ride Public, shared, and externalities; need to jump- sharing firms to shift to EVs as an efficient fleet operations way to mainstream the technology start demand 20 An overview of EV and EV charging incentives in Europe is available here: https://blog.wallbox.com/ev-incentives-europe-guide/. 21 EU will completely ban ICEVs by 2025. In California, a new regulation sets out a roadmap with various milestones. By 2026, 35 per- cent of all new cars would need to be either zero-emission or plug-in hybrid vehicles. That number increases to 68 percent in 2030 and 100 percent by 2035. In China, from 2035 the only new cars for sale will be ‘new energy’. Chapter 4: Clean Air for Hanoi by 2030: What Will it Take? 43 TABLE B4.1.1 Policies that promote the e-mobility transition (cont.) Incentives/Mechanisms Challenge Example Procurement and Small and fragmented • Increase bargaining power of consumers consolidation demand and attract commercial financing through mechanisms demand aggregation vehicles Avoid environmental • Ensure that the full environmental cost of Vehicle disposal externalities EVs is reflected in prices, even after their regulations useful lifespan Fiscal distortions in taxes and • Provide accurate price signals on the subsidies affecting electricity relative costs of different types of energy Energy pricing and liquid transportation fuel for transportation, capturing externalities efficiently Source: Briceno-Garmendia 2022 4.4 Monitoring, Reporting, and Validation of Emissions Reductions and Climate Finance Mobilization Monitoring, reporting, and validation (MRV) of emissions and emissions reductions are crucial to improve understanding of key sources of air pollution and impacts of policies and investments on emissions reductions. Such MRV systems are also of crucial importance for greenhouse gases (GHGs) and a necessity to mobilize climate finance. For GHGs, MRV refers to the multi-step process to measure the amount of emissions reduced by a specific mitigation activity over a period of time and report these findings to an accredited third party. The third party then verifies the report so that the results can be certified and carbon credits can be issued. Setting up a robust MRV system is key to unlocking climate financing and to achieving the commitments under Vietnam’s NDC. Since many sector measures reduce both air pollutants and GHGs, it can be worthwhile to establish an MRV system covering multiple pollutants, such as the European Industrial Emissions Portal.22 With the large amount of financing required for climate and air quality in order to achieve the goals and commitments, establishing robust MRV systems can mobilize the urgently-needed climate financing to make the required transition. 22 https://industry.eea.europa.eu/ 44 Clean Air for Hanoi: What Will it Take? Appendix A: A Note on Data Collection A.1 Energy Use and Industrial Activities Detailed provincial statistical data on energy use have been used, such as databases from local sources (for example, provincial Departments of Industry and Trade, local power development plans) and international organizations (for example, International Energy Agency statistics [IEA 2015] and World Steel Organization data [WSO 2018]) to populate the GAINS database with energy balances at a regional level. In order to allocate power plants and industrial energy use, all power plants and key industrial complex (including iron and steel, cement, pulp and paper, fertilizer manufacturing plants, and brick manufacturing) data were spatially identified and distributed to the regions considered in the GAINS-Vietnam model. Energy use and industrial activities are also characterized in the craft village survey conducted in 33 villages. Craft village data were scaled up to encompass all craft villages in Hanoi using relevant proxies, such as data on the number of households conducting production activities. Vietnam is currently undergoing an important transition in fuel use for cooking. Several national and regional programs support the reduction in the use of solid fuels (for example, coal, wood, agricultural residues) by promoting access to gas (that is, liquid petroleum gas). The distribution of fuel use and fuel types by region drew on data and information summarized in various national assessments (Hoang 2011; Accenture Development Partnership 2012). A.2 Road Transport Road traffic activity data were collected and estimated at the regional level for Hanoi, Bac Ninh, and Hung Yen provinces. Fuel consumption was estimated from the number of vehicles (GSO 2006, 2016) and average annual mileage and average fuel economy relied on local measurements (NILU, CAI-Asia, and CETIA 2015). The NILU, CAI-Asia, and CETIA (2015) study was also used to develop the split of total fuel used in cars between gasoline and diesel. That dataset was further validated and enhanced in the World Bank emissions inventory assignment where the RCEE-NIRAS team focused on the activity data collection and processed the number of vehicles and total annual vehicle‐kilometers travelled. Based on this information, total annual fuel consumption by fuel type and by vehicle category were calculated with the fuel Appendix A: A Note on Data Collection 45 consumption norm for each vehicle category and determined based on the fuel consumption measurement results published by the Vietnam Register and the data from the final report of the Hanoi Green Growth Action Plan (2020). In total, the regional estimates of fuel consumption developed within this project match well (within 2-3 percent) with the national statistical data for 2010 and 2015. A.3 Characterization of Craft Villages There are about 4,575 craft villages in Vietnam, of which 1,951 are recognized. Forty-seven craft villages are classified as seriously polluted in Vietnam, of which 34 are in the North and eight are in Hanoi (MONRE 2021). Businesses in these villages have greatly contributed to increased income and reduced poverty in rural areas. However, they have also caused severe environmental deterioration (MoNRE 2008a; Huy and Oanh 2017). The craft villages often waste resources and cause heavy air, water, and soil pollution, thus significantly contributing to environmental pollution in rural areas. The specific conditions and features of emissions sources in craft villages are likely to be only inadequately represented by international data (Huy and Oanh 2017). Air pollution in craft villages is mainly caused by coal burning and use of chemicals in production (MONRE 2021). At the same time, due to a lack of administrative capacity and human and financial resources, there remains a gap in the availability of data on craft villages for environmental impact analyses (Huy and Oanh 2017). Little quantitative data on activity statistics and characteristic emissions factors from the various operations exist in Vietnam, so that currently all emissions estimates for such sources draw on partial and rather dated assessments and, therefore, are highly uncertain. For the 2019-2020 assignment on emissions inventory, the RCEE-NIRAS team carried out a survey with 500 households in craft villages (figure A.1). The overall goal of conducting the survey was to collect necessary information on the level of activities, fuel use, and technology of production lines. The survey also collected data on solid waste and wastewater from the craft villages since an assessment of co-benefits to air quality from solid waste and wastewater management is important and could be undertaken with the GAINS model. The survey was conducted in 33 villages from May to June 2020, of which 23 villages are in Hanoi, 5 villages in Hung Yen, and 5 villages in Bac Ninh. The survey team interviewed 33 representatives of local authorities and 410 households, yielding a total of 443 respondents for the survey. Hanoi and its nearby provinces aim to improve the environmental performance of craft villages between 2021 and 2030. 46 Clean Air for Hanoi: What Will it Take? FIGURE A.1 Summary of sampling process with relevant data collection methods in the craft village survey Input from desk review All craft Pre- Judgmental Sub- Judgmental Sampled craft villages categorized Four groups categorized categories selection villages Input from Face-to-face online survey interview A.4 Solid Waste Management Historical activity data on industrial and municipal solid waste and wastewater generation, composition, collection rates, and management practices were derived from national statistics, official reports, and scientific articles (GSO 1995; MONRE 2008b; RCEE and Full Advantage 2009; MONRE 2010a; GSO 2011; MONRE 2011; World Bank 2013; Nguyen and Chi 2015; GSO 2016; MONRE 2016). Information related to the type of management of uncollected waste (scattered or openly burnt) carry larger uncertainty because such data is usually not included in the statistics, which focus more on the management of collected waste. Key indicators such as total generated municipal waste, collection percentage data for urban, rural, and the whole domain of the studied provinces, municipal waste composition, and amount of waste subjected to uncontrolled burning were collected, analyzed, and validated. One source of uncertainty of the obtained activity data is related to the assumption of the amount of uncontrolled/open burning of waste, which was taken as 50 percent of uncollected waste. In general, waste management is being improved in Vietnam, which emphasizes the requirements to reduce uncontrolled burning and increase rates of improved waste management practices. Appendix A: A Note on Data Collection 47 A.5 Agriculture In order to populate the regional databases in GAINS, historical data on livestock were collected from national and provincial statistics (GSO 2006, 2016) as well as from more detailed data for dairy cattle and poultry (MARD 2018). For mineral fertilizers, the International Fertilizer Association (IFA 2018) statistics for urea and other nitrogen fertilizers were used and distributed to the regions considered by GAINS based on the share of land area under cultivation by province (GSO 2006, 2016). Data on rice cultivation area and production were taken from regional statistics (GSO 2006, 2016). Data on other areas such as forests, activity-organic soils, grasslands, and soils were collected from the Vietnam Administration of Forestry (MARD), Green Growth Action Plan for Hanoi, Animal Husbandry Institute, and Ba Vi Animal Breeding Center. Large amounts of agricultural residues, primarily rice straw and husk, are generated in Vietnam, and are typically either openly burned in the fields or used as cooking fuel. Regional estimates of the volumes of residues burned in fields were derived from recent data and review assessments (Oanh et al. 2011; Hoang et al. 2013; Dinh et al. 2016; Oanh et al. 2018). 48 Clean Air for Hanoi: What Will it Take? Glossary Air quality index (AQI): A national, uniform index for reporting and forecasting daily air quality. It is used to report on common ambient air pollutants such as particle pollution (PM10 and PM2.5). AQI normally focuses on health effects that may be experienced within a few hours or days after breathing polluted air. Backward trajectory: Where long-range transport of air pollutants is an important factor in ambient air concentrations, backward trajectory models use weather models to predict how air masses have been transported over a preceding time period. Emission limit value: Refers to the permissible quantity or concentration of a substance that may be discharged into the air during a given period, which may not be exceeded during one or more periods of time. Emissions inventory: An emissions inventory estimates the quantity and types of pollutants that are emitted to the air each year from various sources, such as transport, energy, agriculture, industrial processes, solid waste management, and so on. Greenhouse Gas–Air Pollution Interactions and Synergies (GAINS): The GAINS model looks at air pollutants and greenhouse gases and assesses emission and pollution reduction strategies at least cost, and minimizes the negative effects of these emissions on human health, ecosystems, and climate change. It is used for policy analyses to assess emission reduction potentials. In the ‘scenario analysis’ mode, it follows emission pathways from sources to impacts, providing estimates of costs and environmental benefits of alternative emission control strategies. In the ‘optimization’ mode, it identifies where emissions can be reduced most cost effectively. Marginal abatement cost curve (MACC): A MACC graphically presents the costs or savings from a range of opportunities, alongside the volume of emissions that could be reduced if these opportunities are implemented. MACCs can be used to easily compare the financial costs and abatement benefits (that is, emissions reductions) of individual policy actions. Each opportunity is presented as a box above or below the horizontal axis. The width of the box indicates the potential volume of emissions reductions per year, expressed as tons of CO2-equivalent. National Ambient Air Quality Standards (NAAQS): NAAQS are national limits on atmospheric concentration of air pollutants, such as ozone (O3), atmospheric particulate matter, lead, carbon monoxide (CO), sulfur oxides (SOx), and nitrogen oxides (NOx). Glossary 49 Nationally determined contribution (NDC): The Paris Agreement requires each country to prepare and communicate its post-2020 climate actions, known as an NDC. An NDC describes the efforts by a country to reduce its national emissions and adapt to climate change impacts. NDCs are submitted every five years to the UNFCCC Secretariat. Particulate matter (PM): Particulate matter (also called particle pollution) is a mixture of microscopic solid particles and liquid droplets found in the air that can be inhaled and cause serious health problems. PM includes PM2.5 (fine particles with diameters generally 2.5 micrometers and smaller) and PM10 (particles with diameters generally 10 micrometers and smaller). Positive Matrix Factorization (PMF): PMF is a model developed by the US EPA that provides scientific support for the development and implementation of air and water quality standards. The model reduces the large number of variables in complex analytical data sets into more manageable combinations of source types and source contributions. Precursors: Precursors are chemicals that react to form particles in the atmosphere. In the case of PM2.5, its precursors are sulfur dioxide (SO2), nitrogen oxides (NOx), volatile organic compounds (VOCs), and ammonia (NH3). Secondary particulate matter: Particulate matter that is formed by chemical reactions of gases in the atmosphere. Major sources of secondary fine particles are power plants and some industrial processes, including oil refining and pulp and paper production. 50 Clean Air for Hanoi: What Will it Take? References Accenture Development Partnership. 2012. “Vietnam Market Assessment- Sector Mapping.” Global Alliance for Clean Cookstoves. Amann, M., Bertok, I., Borken-Kleefeld, J., Cofala, J., Heyes, C., Höglund-Isaksson, L., Klimont, Z., Nguyen, B., Posch M, Rafaj P, Sandler R, Schoepp W, Wagner F, Winiwarter W. (2011). Cost-effective control of air quality and greenhouse gases in Europe: Modeling and policy applications. Environmental Modelling & Software 10.1016/j.envsoft.2011.07.012. Amann, M., Klimont, Z., An Ha, T., Rafaj, P., Kiesewetter, G., Gomez Sanabria, A., Nguyen, B., Thi Thu, T.N., et al. (2019). Future air quality in Ha Noi and northern Vietnam. IIASA Research Report. Laxenburg, Austria: RR-19-003. https://previous.iiasa.ac.at/web/home/ research/researchPrograms/air/news/181107_AQM_Vietnam.html Briceno-Garmendia, Cecilia, W. Qiao, V. Foster. 2022. The Economics of Electric Vehicles for Passenger Transportation. Washington, DC: The World Bank. https://openknowledge. worldbank.org/handle/10986/38265. Climate Action Tracker. n.d. Viet Nam. Updated on September 20, 2022. https:// climateactiontracker.org/countries/vietnam/net-zero-targets/. Columbia University. 2022. Guide to Chinese Climate Policy – Electric Vehicles. SIPA Center on Global Energy Policy. https://chineseclimatepolicy.energypolicy.columbia.edu/en/electric- vehicles. Dinh, M.C., A.L. Hoang, and X.C., Hoang. 2016. “Calculation of Gas Emission from Rice Straw Open Burning in Ninh Binh Province for 2010-2015 Period and Proposal of Mitigation Solutions.” VNU Journal of Science: Earth and Environmental Sciences, 32, pp. 70–76. EEA. 2019. “Fiscal instruments favouring electric over conventional cars are greener.” Briefing. September 24. Copenhagen, Denmark: European Environment Agency. https://www.eea. europa.eu/publications/fiscal-instruments-favouring-electric-over. Fortuna, Carolyn. 2022. London, Transportation Fees, & EV Adoption — An Equation To Lower Air Pollution. October 13. CleanTechnica. https://cleantechnica.com/2022/10/13/london- transportation-fees-ev-adoption-an-equation-to-lower-air-pollution/. GSO (General Statistics Office). 1995. “Statistical Yearbook of Vietnam 1994.” Statistical Publishing House. Hanoi: General Statistics Office, Government of Vietnam. References 51 GSO (General Statistics Office). 2006. “Statistical Yearbook of Vietnam 2005.” Statistical Publishing House. Hanoi: General Statistics Office, Government of Vietnam. GSO (General Statistics Office). 2011. “Statistical Yearbook of Vietnam 2010.” Statistical Publishing House. Hanoi: General Statistics Office, Government of Vietnam. GSO (General Statistics Office). 2016. “Statistical Yearbook of Vietnam 2015.” Statistical Publishing House. Hanoi: General Statistics Office, Government of Vietnam. Hoang, A.L., T.T.H. Nguyen, and T.L. Le. 2013. “Estimated Gas Emission from Burning Rice Straw in Open Fields in Thai Binh Province.” Scientific Journal of Vietnam National University, 29, pp. 26–33. Hoang, V.T. 2011. “Survey on Cookstoves usage in Northern Vietnam.” SVN Vietnam. Huy, L.N. and N.T K. Oanh. 2017. “Assessment of national emissions of air pollutants and climate forcers from thermal power plants and industrial activities in Vietnam.” Atmospheric Pollution Research, 8(3), pp. 503-513. https://doi.org/10.1016/j.apr.2016.12.007. IEA (International Energy Agency). 2015. “Energy Statistics of Non-OECD Countries 2015.” Paris, France: International Energy Agency and Organisation for Economic Co-operation and Development. IFA (International Fertiliser Association). 2018. IFASTAT Databases. IIASA. n.d. GAINS Online - Reveal win-win policy interventions with GAINS-online. Laxenburg, Austria: International Institute for Applied Systems Analysis. https://gains.iiasa.ac.at/ models/index.html. Nguyen, M.L. and V.C.C. Chi. 2015. “Solid Waste Typology and Management in Hanoi.” IMV France, CIRAD and INRA. https://umr-selmet.cirad.fr/content/download/4052/29638/ version/3/file/IMV_REPORT_WASTETYPOLOGY_HANOI.pdf. MARD (Ministry of Agriculture and Rural Development). 2018. “Vietnam Livestock Production.” Ministry of Agriculture and Rural Development, Government of Vietnam. MOIT (Ministry of Industry & Trade). 2021. Draft Power Develpment Plan 8. MONRE (Ministry of Natural Resources and Environment). 2008a. “Vietnam Craft Village Environment.” Ministry of Natural Resources and Environment, Government of Vietnam. MONRE (Ministry of Natural Resources and Environment). 2008b. “National State of Environment Report 2008.” Ministry of Natural Resources and Environment, Government of Vietnam. MONRE (Ministry of Natural Resources and Environment). 2010a. “National State of Environment Report 2010.” Ministry of Natural Resources and Environment, Government of Vietnam. 52 Clean Air for Hanoi: What Will it Take? MONRE (Ministry of Natural Resources and Environment). 2011. “National State of Environment Report 2011.” Ministry of Natural Resources and Environment, Government of Vietnam. MONRE (Ministry of Natural Resources and Environment). 2013. Circular No. 32/2013/TT- BTNMT of the Ministry of Natural Resources and Environment on the Promulgation of National Technical Regulations on Environment. October 25. Ministry of Natural Resources and Environment, Government of Vietnam. MONRE (Ministry of Natural Resources and Environment). 2016. “National State of Environment Report 2016.” Ministry of Natural Resources and Environment, Government of Vietnam. MONRE (Ministry of Natural Resources and Environment). 2021. “National State of Environment Report 2021.” Ministry of Natural Resources and Environment, Government of Vietnam. MONRE (Ministry of Natural Resources and Environment). 2020. "Vietnam Nationally Determinded Contribution". Ministry of Natural Resources and Environment, Government of Vietnam. MONRE (Ministry of Natural Resources and Environment). 2022. "Vietnam Nationally Determinded Contribution". Ministry of Natural Resources and Environment, Government of Vietnam. Nhan Dan. 2020. “BÁO CÁO ĐÁNH GIÁ KẾT QUẢ THỰC HIỆN NHIỆM VỤ PHÁT TRIỂN KINH TẾ - XÃ HỘI 5 NĂM 2016 - 2020 VÀ PHƯƠNG HƯỚNG, NHIỆM VỤ PHÁT TRIỂN KINH TẾ - XÃ HỘI 5 NĂM 2021 – 2025.” October 20. https://nhandan.vn/bao- cao-danh-gia-ket-qua-thuc-hien-nhiem-vu-phat-trien-kinh-te-xa-hoi-5-nam-2016-2020- va-phuong-huong-nhiem-vu-phat-trien-kinh-te-xa-hoi-5-nam-2021-2025-post621157. html. NILU, CAI-Asia, and CETIA. 2015. “Developing Mobile Source Emission Inventory for Hanoi.” Final Report within the Hanoi Urban Transport Development Project. Norwegian Institute for Air Research, Clean Air Initiative for Asian Cities, and CETIA. Oanh, N.T.K., T.L. Bich, D. Tipayarom, B.R. Manadhar, P. Prapat, C.D. Simpson, and J.S. Liu. 2011. “Characterization of Particulate Matter Emission from Open Burning of Rice Straw.” Atmospheric Environment, 45(2), p. 493. https://doi.org/10.1016/j.atmosenv.2010.09.023. Oanh, N.T.K., D.A. Permadi, P.K. Hopke, K.R. Smith, N.P. Dong, and A.N. Dang. 2018. “Annual emissions of air toxics emitted from crop residue open burning in Southeast Asia over the period of 2010–2015.” Atmospheric Environment, 187, pp. 163-173. https://doi. org/10.1016/j.atmosenv.2018.05.061. Prime Minister (Vietnam). 2007. “Decision Approving Vietnam’s National Energy Development strategy up to 2020 with 2050 vision.” Hanoi, Vietnam. Prime Minister (Vietnam). 2012. “Decision approving the National Strategy on Green Growth.” Hanoi, Vietnam. References 53 Prime Minister (Vietnam). 2015. “Decision approving Vietnam’s Renewable Energy Development Strategy until 2030 with a Vision to 2050.” Hanoi, Vietnam. RCEE Energy and Environment JSC; Full Advantage Co., Ltd. 2009. Potential Climate Change Mitigation Opportunities in Waste Management Sector in Vietnam. Washington, DC: The World Bank. https://openknowledge.worldbank.org/handle/10986/28217. Tyler, Tim. 2022. Indonesia To Put 2 Million Electric Motorbikes On Road By 2025. October 26. CleanTechnica. https://cleantechnica.com/2022/10/26/indonesia-to-put-2-million- electric-motorbikes-on-road-by-2025/. UNFCCC. 2020. Vietnam Updated Nationally Determined Contribution 2020. https://unfccc.int/ sites/default/files/NDC/2022-06/Viet%20Nam_NDC_2020_Eng.pdf UNFCCC. 2022. Vietnam Updated Nationally Determined Contribution 2022. https://unfccc.int/ documents/622541. VEA (Vietnam Environment Administration). 2019. Decision Promulgating a Guide to Calculation and Publishing of Vietnam Air Quality Index (VN_AQI). No.: 1459/QD- TCMT. November 12. Ministry of Natural Resources and Environment, Government of Vietnam. WHO (World Health Organization). 2016. “WHO Global Urban Ambient Air Pollution Database (update 2016).” Geneva, Switzerland: World Health Organization. http://www.who.int/ phe/health_topics/outdoorair/databases/cities/en/. WHO (World Health Organization). 2021. “WHO global air quality guidelines – Particulate matter (PM2.5 and PM10), ozone, nitrogen dioxide, sulfur dioxide and carbon monoxide.” Geneva, Switzerland: World Health Organization. https://apps.who.int/iris/bitstream/han dle/10665/345329/9789240034228-eng.pdf. World Bank. 2013. “Vietnam Urban Wastewater Review.” Washington, DC: The World Bank. https://openknowledge.worldbank.org/handle/10986/18245. World Bank. 2020. “Implementation Completion and Results Report for Hebei Air Pollution Prevention and Control Program – Program-for-Results”. June 22. Loan number 8623- CN. https://documents1.worldbank.org/curated/en/746591593402580377/pdf/China- Hebei-Air-Pollution-Prevention-and-Control-Project.pdf. World Bank. 2022. Vietnam Country Climate and Development Report. CCDR Series. Washington, DC: The World Bank. https://openknowledge.worldbank.org/handle/10986/37618. WSO (World Steel Association). 2018. “Steel Statistical Yearbook 2018.” Belgium. 54 Clean Air for Hanoi: What Will it Take?