IEc Assessing the Mortality Burden of Air Pollution in Lima-Callao Final Report | May 14, 2021 prepared for: U.S. Environmental Protection Agency prepared by: Industrial Economics, Incorporated 2067 Massachusetts Avenue Cambridge, MA 02140 617/354-00074 TABLE OF CONTENTS ACKNOWLEDGEMENTS CHAPTER 1 | INTRODUCTION 1.1 Background 1-1 1.2 Analytic Overview 1-2 1.2.1 Research Objectives 1-2 1.2.2 Analytic Steps 1-3 1.3 Report Organization 1-3 CHAPTER 2 | SCENARIO DEVELOPMENT CHAPTER 3 | EMISSIONS ESTIMATION 3.1 Baseline Emissions Inventory 3-1 3.2 Accounting for Non-Compliance 3-3 3.3 Emissions Modeling Results 3-4 CHAPTER 4 | AIR QUALITY DATA AND MODELING 4.1 Air Quality Surfaces 4-1 4.1.1 Monitor Surfaces 4-1 4.1.2 Satellite Surfaces 4-3 4.1.3 Summary of Air Quality Surfaces 4-3 4.2 Air Quality Modeling 4-5 CHAPTER 5 | MORTALITY BURDEN ESTIMATION AND VALUATION 5.1 Overview of Approach 5-1 5.2 Data Inputs 5-2 5.2.1 Population 5-2 5.2.2 Baseline Mortality Incidence 5-2 5.2.3 Health Impacts Functions 5-2 5.2.4 Valuation 5-4 CHAPTER 6 | RESULTS 6.1 Total PM2.5 Attributable Mortality Burden 6-1 6.2 Transport Attributable PM2.5 Mortality Burden 6-2 6.3 PM2.5 Mortality Burden from Non-Compliant Vehicles 6-3 i CHAPTER 7 | SUMMARY OF FINDINGS 7.1 Summary of Findings 7-1 7.2 Uncertainties 7-2 7.3 Next Steps 7-3 REFERENCES APPENDICES Appendix A | Supplemental Emissions Estimation Results Appendix B | Satellite Measurements and Processing Appendix C | Health Impact Estimation Appendix D | District-Level Results ii ACKNOWLEDGEMENTS This report was prepared by Industrial Economics, Incorporated (IEc) for the U.S. Environmental Protection Agency (USEPA) Office of Air Quality Planning and Standards (OAQPS), under USEPA contract EP-D-14-032 as part of EPA’s Megacities Partnership program in Lima, Peru. Consistent with the Megacities Partnership approach to air quality management, this project was a collaborative effort between USEPA, IEc, and local partners at the Peruvian Ministry of Environment (MINAM). In particular, IEc acknowledges critical support from Luis Antonio Ibañez Guerrero, Katyuska Barja Paredes, and Guisselle Castillo Coila of MINAM, who provided key data sets, valuable local institutional knowledge, and helpful advice. We also thank USEPA staff including the Lima Megacities Project Manager Paul Almodóvar as well as a Richard Baldauf, Ali Kamal, and Ken Davidson for their input on the analysis and helpful feedback on earlier drafts of this report. iii CHAPTER 1 | INTRODUCTION The United States Environmental Protection Agency (USEPA) and the Ministry of the Environment of Peru (MINAM) are collaborating under the USEPA Megacities Partnership to: • Strengthen air quality management in the Lima-Callao region through policy development, community outreach, and stakeholder engagement; • Support air quality monitoring initiatives; and • Build technical capacity in Lima-Callao for scientific and economic analyses and communication planning in support of air quality management plan (AQMP) development. This report presents results from assessments of the current overall mortality burden attributable to concentrations of fine particulate matter (PM2.5) in the region. In addition to estimating total PM2.5-attributable health burden with respect to premature deaths, we employ emissions inventories and reduced-form air quality modeling techniques to analyze the burden attributable to concentrations of PM2.5 associated with emissions from on-road motor vehicles. We further evaluate the burden of a subset of these vehicles—those out of compliance with currently established emissions limits—and highlight the potential benefits associated with increased enforcement and expanded vehicle inspections and maintenance (I&M) programs. 1.1 BACKGROUND The Lima-Callao metropolitan region is home to approximately 10 million people, nearly one-third of Peru’s total population. This large and growing population is exposed to significant air pollutant concentrations due to emissions from sources such as motor vehicles. These exposures can be exacerbated by Lima-Callao’s meteorological conditions, primarily the Humboldt ocean current and the Andes Mountains to the east. The Humboldt ocean current carries cold water north from the tip of South America, which lowers atmospheric temperatures and prevents the formation of rain clouds (Thiel et al. 2007). The Humboldt ocean current is also responsible for persistent fog in Lima- Callao. The fog, combined with the obstruction of warmer and more humid air masses from the Amazon, by the Andes, results in frequent air inversions in Lima-Callao. These air inversions trap ambient pollutants at the surface level, causing pollutants to accumulate rather than disperse via coastal winds. As a result, Lima-Callao is ranked among the most polluted cities in Latin America by the World Health Organization (WHO, 2016). 1-1 Transportation sources are responsible for much of the region’s air pollution. Despite comprising one-third of the country’s population, Lima-Callao is home to roughly two- thirds of Peru’s vehicle fleet. In addition to the size of the vehicle fleet, its age plays a significant role in resulting air pollution (MINAM, 2018). According to surveys of registered vehicles from 2016-2019, approximately 34 percent of the on-road vehicles in Lima-Callao are greater than 15 years old. These older vehicles tend to have poor fuel economy and lack the emissions controls required of new vehicles. Based on emissions tests, MINAM partners note that many vehicles are non-compliant with national emissions standards; however, empirical estimates of non-compliance rates are currently limited. To address emissions from the transportation sector, the Government of Peru has passed several laws and regulations concerning emissions standards and vehicle inspection requirements. For example, in 2008, Peru established the National System of Technical Vehicle Inspection, which is responsible for inspecting and testing vehicles for safety and compliance with emissions standards. More recently, Peru adopted the Euro 4 vehicle emissions standards for all new vehicles and is considering implementing Euro 6 standards. Because of the slow rate of turnover in the vehicle fleet—as shown by the prevalence of old vehicles in circulation—additional measures may be needed to address the sector’s emissions. In this report, we provide insight into the potential magnitude of these on-road vehicle emissions and associated adverse health outcomes. 1.2 ANALYTIC OVERVIEW In this section, we summarize our analytic approach to estimating the mortality burden associated with PM2.5 concentrations in Lima-Callao. We first define our research objectives and then outline the analytic steps we follow in the remainder of the report. 1.2.1 RESEARCH OBJECTIVES In close consultation with MINAM and USEPA, we developed three research objectives addressed in this report. First, we aim to quantify and value the premature deaths associated with overall ambient PM2.5 concentrations in Lima-Callao. Second, we aim to quantify and value the premature deaths associated with emissions from Lima-Callao’s on-road vehicles, to better understand how vehicles contribute to the overall burden of premature deaths. Third, we aim to quantify and value the premature deaths associated with emissions from non-compliant vehicles in the Lima-Callao on-road vehicle fleet, to help MINAM understand the potential health gains from focusing on the non-compliance issue. For each research objective, we consider annual impacts using data that best characterize recent conditions for air quality, population, baseline health, and other relevant data. In Chapter 7, we highlight additional areas of future research that could complement this report. We hope that the analytical framework IEc applied in this analysis will serve as a useful guide for addressing these research topics, including estimating the benefits of specific transportation emissions control measures. 1-2 1.2.2 ANALYTIC STEPS Our methodology is comprised of five key steps: • Step 1: Scenario development. Define the research objectives and the spatial and temporal scale of our analyses. Specify conditions under a “business-as-usual” or “baseline” scenario and under a “regulatory” scenario in which the proposed regulation is implemented. Based on these scenario definitions, develop baseline and regulatory air quality surfaces. • Step 2: Emissions estimation. Develop or obtain emissions inventories for the transportation sector. Develop estimate of the fraction of non-compliant vehicles. Estimate the excess emissions associated with non-compliant vehicles in the Lima-Callao fleet. (Note: this step is not needed for assessing the total PM2.5- attributable mortality burden.) • Step 3: Air quality modeling. Obtain and process air quality data, such as satellite-based estimates and data from air quality monitors to characterize baseline conditions in Lima-Callao. Use air quality modeling methods to estimate the impact of vehicle emissions on ambient PM2.5 concentrations. • Step 4: Health impact estimation. Quantify premature deaths associated with PM2.5 concentrations using BenMAP-CE and relevant datasets, including population, air quality, baseline mortality incidence, and concentration-response relationships from the epidemiological literature. • Step 5: Valuation. Apply economic valuation estimates to quantified mortality values to characterize the PM2.5-attributable mortality burden in monetary terms. These steps are described in greater