High Population Exposure Research Articles

A systematic framework for assessing social vulnerability to flood for integrated flood risk management: A case study in Metro Manila, Philippines

Assessing social vulnerability to floods (SVF) is a crucial component of integrated flood risk management, especially in flood-prone regions such as Metro Manila in the Philippines. This study presents a holistic framework to assess SVF, based on susceptibility, exposure, and resilience factors while recognizing its multi-dimensional, multi-attribute, and context-dependent nature. The assessment was applied to three cities of Metro Manila: Marikina, Parañaque, and Manila. Indicators were systematically identified using deductive and hierarchical approaches, and factor indices were derived using a combined Simple Additive Weighting and Analytic Hierarchy Process, while the SVF index was estimated using the vulnerability relationship of the factors. The results exhibit a strong positive correlation with historical social flood damages and robustness across weight and normalization variations, with Marikina being the most vulnerable, followed by Parañaque and Manila. The city-level vulnerability profiles highlight salient determinants such as high population exposure in Parañaque, a relatively high population of susceptible social groups in Marikina, and significant disparity in flood control projects among the cities. Scenario analyses underscore the efficacy of flood countermeasures that reduce exposure and increase resilience. This study offers valuable insights and practical guidance for developing effective disaster reduction plans and policies in the study areas and similar regions by identifying disparities in vulnerability and understanding local conditions and drivers.

Spatial pattern assessment of dengue fever risk in subtropical urban environments: The case of Hong Kong

Dengue fever, a mosquito-borne fatal disease, brings a huge health burden in tropical regions. With global warming, rapid urbanization and the expansion of mosquitoes, dengue fever is expected to spread to many subtropical regions, leading to increased potential health risks on local populations. So far, limited studies assessed the dengue fever risk spatially for subtropical non-endemic regions hindering the development of related public health management. Therefore, we proposed a spatial hazard-exposure-vulnerability assessment framework for mapping the dengue fever risk in Hong Kong. Firstly, the spatial distribution of the habitat suitability for Aedes albopictus, the mosquito proxy for the dengue fever hazard, was predicted using a species distribution model (e.g., MaxEnt) relying on a list of variables related to local climate, urban morphology, and landscape metrics. Secondly, the spatial autocorrelation between high dengue hazard and high human population exposure in urban areas was measured. Finally, the dengue fever risk was assessed at community scale by integrating the results of vulnerability analysis basing on census data. This approach allowed the identification of 17 high-risk spots within Hong Kong. The landscape metrics about land utilities and vegetations, and urban morphological characteristics are the influential factors on the spatial distribution of dengue vector. In addition, the underlying factors behind each hot spot were investigated, and specific suggestions for dengue prevention were proposed accordingly. The findings provide a useful reference for developing local dengue fever risk prevention measures, with the proposed method easily exportable to other high-density cities within subtropical Asia and elsewhere.

Hysteresis and irreversibility of global extreme precipitation to anthropogenic CO2 emission

Understanding of extreme precipitation change in response to CO2 forcing and associated socioeconomic exposure is limited. In this study, a comprehensive analysis is conducted to explore the response of global extreme precipitation to CO2 forcing in terms of hysteresis and reversibility effect and associated population exposure. In this regard, climate outputs under two idealized CO2 scenarios such as ramp-up (RU; about +1% annually until quadrupling of present level) and ramp-down (RD; around −1% annually set back to present level) from Community Earth System Model version 1.2, and the projected population data from the five shared Socioeconomic Pathways (SSPs) are used. Extreme precipitation events are evaluated using the number of heavy precipitation days (R30 mm), maximum consecutive 5-day precipitation (Rx5day), and the precipitation of very wet days (R95pTOT) indices. Results show that the magnitude of extreme precipitation change and associated population exposure is higher in the CO2 reduction period (RD) than in RU. All the indices show substantial irreversible and hysteresis effects, ∼69% of the global land is expected to experience irreversible changes in extreme precipitation. Further, the hotspots of irreversibility (the region with irreversible change and a large hysteresis) will emerge in >20% of the global area. Spatially, strong hysteresis and irreversibility are particularly concentrated over global land monsoon regions. The leading exposure is estimated under SSP3 combined with both RU and RD periods. Under the SSP3-RD combination, the highest population exposure is estimated at ∼67.1% (globally averaged), and ∼72% (averaged over hotspots) higher than that of the present day. The exposed population is prominent in South Africa and Asia. Notably, the population change effect is the principal factor in global exposure change, while it is the climate change effect over the hotspots of irreversibility. These findings provide new insight into policymaking that only CO2 mitigation effort is not enough to cope with extreme precipitation, rather advanced adaptation planning is a must to have more socio-economic benefits.

High-resolution multi-scale air pollution system: Evaluation of modelling performance and emission control strategies

A high percentage of the world's population lives in areas where air pollutant concentrations exceed the World Health Organization guidelines. This work aims to develop and test, a high-resolution multi-scale air pollution modelling system by integrating a set of adequate tools. This system is able to provide detailed air pollutant concentrations in urban areas and support air quality management strategies through a better identification of different atmospheric processes. It also allows furthering the design and assessment of air pollution control measures for a specific area. To evaluate its performance and suitability, the system was applied to the Macau Special Administrative Region (SAR), China, one of the most densely populated areas on earth, during a winter period when this area is affected by high levels of Particulate Matter (PM). Although the developed system tends to underestimate the PM concentrations, it revealed a good performance in reproducing the temporal and spatial air pollution patterns. Several exceedances of the Chinese air quality standards were calculated and high population exposure to PM pollution was estimated. The tested urban atmospheric emission reduction scenarios have shown air quality improvements, indicating that emission reduction measures at urban level should focus on the domestic sector. However, it is crucial to implement joint pollution prevention strategies with neighbouring regions to improve the air quality in Macau SAR. The approach developed in this work can support policymakers in defining new strategies to reduce atmospheric pollution in urban areas.

Spatial and temporal heterogeneity of tropical cyclone precipitation over China from 1959 to 2018

Tropical cyclone precipitation (TCP) can cause serious floods and urban waterlogs as well as cause various secondary disasters, such as landslides and debris flows, which negatively affect human lives and the sustainable development of the economy. This study applied the prewhitening Mann-Kendall test, empirical orthogonal function, and continuous wavelet transform to investigate the long-term trend, spatiotemporal pattern, and periodicity of TCP at monthly, interannual, and interdecadal timescales over China. The recurrence risks of extreme TCP were analyzed using the return period estimation model. The results showed that 1) TCP displayed a significant increasing trend, especially in eastern China, inland areas, and Guangxi Province. The TCP periodicities were 2.5 and 4.9 years across all of China. However, TCP cycles had large discrepancies in the time and frequency domains in different subregions. 2) Monthly TCP demonstrated a decreasing trend in May and an increasing trend from June to October in all of China. The TCP in northeastern China and southern China tended to decrease in July and August, respectively. 3) TCP demonstrated a decreasing tendency from the 1960s–1980s followed by a rebounding trend in the 1990s–2010s. In addition, TCP showed a dipole mode in the 1970s and 2000s. 4) There was an increasing recurrence risk of extreme TCP in the Yangtze River Delta, Hainan Province, southeastern Guangxi Province, and southwestern Guangdong Province. It is therefore necessary to improve forecasting of extreme TCP events to improve risk management and prevention capacity of natural disasters, especially in regions with high population and economy exposure.

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) in Africa: Current Considerations and Future Projections.

The burden of severe Covid-19 has been relatively low in sib-Saharan Africa compared to Europe and the Americas. However, SARS-CoV-2 sero-prevalence data has demonstrated that there has been more widespread transmission than can be deduced from reported cases. This could be attributed to under reporting due to low testing capacity or high numbers of asymptomatic SARS-CoV-2 infection in communities. Recent data indicates that prior SARS-CoV-2 exposure is protective against reinfection and that vaccination of previously SARS-CoV-2 infected individuals induces robust cross-reactive antibody responses. Considering these data, calls for a need for a re-think of the COVID-19 vaccination strategy in sub-Saharan African settings with high SARSCoV-2 population exposure but limited available vaccine doses. A potential recommendation would be to prioritize rapid and widespread vaccination of the first dose, while waiting for more vaccines to become available.

Assessment of NO2 population exposure from 2005 to 2020 in China.

Nitrogen dioxide (NO2) is a major air pollutant with serious environmental and human health impacts. A random forest model was developed to estimate ground-level NO2 concentrations in China at a monthly time scale based on ground-level observed NO2 concentrations, tropospheric NO2 column concentration data from the Ozone Monitoring Instrument (OMI), and meteorological covariates (the MAE, RMSE, and R2 of the model were 4.16 µg/m3, 5.79 µg/m3, and 0.79, respectively, and the MAE, RMSE, and R2 of the cross-validation were 4.3 µg/m3, 5.82 µg/m3, and 0.77, respectively). On this basis, this article analyzed the spatial and temporal variation in NO2 population exposure in China from 2005 to 2020, which effectively filled the gap in the long-term NO2 population exposure assessment in China. NO2 population exposure over China has significant spatial aggregation, with high values mainly distributed in large urban clusters in the north, east, south, and provincial capitals in the west. The NO2 population exposure in China shows a continuous increasing trend before 2012 and a continuous decreasing trend after 2012. The change in NO2 population exposure in western and southern cities is more influenced by population density compared to northern cities. NO2 pollution in China has substantially improved from 2013 to 2020, but Urumqi, Lanzhou, and Chengdu still maintain high NO2 population exposure. In these cities, the Environmental Protection Agency (EPA) could reduce NO2 population exposure through more monitoring instruments and limiting factory emissions.

Overcoming challenges for implementing nature-based solutions in deltaic environments: insights from the Ganges-Brahmaputra delta in Bangladesh

The Ganges-Brahmaputra (GB) delta is one of the most disaster-prone areas in the world due to a combination of high population density and exposure to tropical cyclones, floods, salinity intrusion and other hazards. Due to the complexity of natural deltaic processes and human influence on these processes, structural solutions like embankments are inadequate on their own for effective hazard mitigation. This article examines nature-based solutions (NbSs) as a complementary or alternative approach to managing hazards in the GB delta. We investigate the potential of NbS as a complementary and sustainable method for mitigating the impacts of coastal disaster risks, mainly cyclones and flooding. Using the emerging framework of NbS principles, we evaluate three existing approaches: tidal river management, mangrove afforestation, and oyster reef cultivation, all of which are actively being used to help reduce the impacts of coastal hazards. We also identify major challenges (socioeconomic, biophysical, governance and policy) that need to be overcome to allow broader application of the existing approaches by incorporating the NbS principles. In addition to addressing GB delta-specific challenges, our findings provide more widely applicable insights into the challenges of implementing NbS in deltaic environments globally.

Environmental Risk Assessment Ascribed to Particulate Matter for Kota City, Rajasthan (India)

The present study analyses the current PM10 and PM2.5 pollution scenarios for Kota City (India) to evaluate human health and ecological environment risks associated with particulate matter pollution exposure. Particulate matter concentration revealed a falling trend during the research period, but PM10 and PM2.5 exceeded the Indian NAAQS and WHO standards. The dust ratio (PM10/PM2.5) has been increased over the years from 0.36 to 0.51. and continue to overgrow for Kota City, showing that fine particulates share more than 45% of total particulate matter. Kota exhibits a high exposure of population towards pollution compared to other megacities of the state. The ecological environment and health risk assessment showed the greater vulnerability of the people to potential risks caused by particulate matter as the risk level remained more than one throughout the research period. The exposure presents important conclusions to stakeholders and policymakers for the proper adoption of mitigation measures.

Effect of vehicle fleet composition and mobility on outdoor population exposure: A street resolution analysis in Paris

High concentrations of health-related pollutants are observed in streets, inducing high outdoor population exposure. The impact of reducing traffic emissions on urban air quality is often quantified using regional-scale chemical-transport models (CTMs), which are representative of background concentrations but fail to represent the high street concentrations. Local-scale models may be more suitable to represent them, but their use for outdoor exposure assessments is still limited, because they often neglect secondary species, use simplified methods to estimate background concentrations, and omit/underestimate non-exhaust emissions. Here the impact of realistic and ambitious tendencies of vehicle fleet renewal and mobility on outdoor population exposure is investigated using multi-scale simulations. They are capable of representing secondary species in urban background and streets (including the formation of secondary organic and inorganic aerosols), and use non-exhaust emissions determined with a recently revisited approach. The 10-year vehicle fleet renewal induces large decreases in population exposure to NO2, black carbon, PM10, PM2.5, and organics. These decreases are stronger than estimated using CTMs. Favouring recent diesel, petrol, or electric vehicles, as proposed here, induces similar decreases of outdoor population exposure to PM2.5. Promoting electric vehicles induces the highest decrease of exposure to NO2. Home-office practice enhances the decrease of pollutant concentrations, but it is less effective than vehicle fleet renewal. However, much more ambitious reductions of pollutant emissions are still needed to respect air-quality guidelines.

Population Exposure Changes to One Heat Wave and the Influencing Factors Using Mobile Phone Data—A Case Study of Zhuhai City, China

The frequent occurrence of extreme high temperature weather and heat waves has greatly affected human life. This paper analyzes population exposure and its influencing factors during a heat wave incident in Zhuhai from 6 to 12 September 2021 based on real-time mobile phone data and meteorological data. The results show that the most areas of Zhuhai are affected by high temperature during this heat wave incident. The hourly population exposure is directly proportional to hourly heat wave coverage. In terms of time dimension, the overall population exposure shows a trend of decreasing and then increasing. In terms of spatial dimensions, high population exposure is concentrated in areas such as primary and secondary schools, colleges and universities, office buildings, and residential areas. Low exposure is distributed in most of the mountainous areas along the southern coast. In addition, the leading factors that cause changes in population exposure in different periods of the heat wave cycle are different, which rely more on either climatic factors or population factors.

Influence of Terrestrial Precipitation on the Variability of Extreme Sea Levels along the Coast of Bangladesh

The coastal area of Bangladesh is highly vulnerable to extreme sea levels because of high population exposure in the low-lying deltaic coast. Since the area lies in the monsoon region, abundant precipitation and the resultant increase in river discharge have raised a flood risk for the coastal area. Although the effects of atmospheric forces have been investigated intensively, the influence of precipitation on extreme sea levels in this area remains unknown. In this study, the influence of precipitation on extreme sea levels for three different stations were investigated by multivariate regression using the meteorological drivers of precipitation, sea level pressure, and wind. The prediction of sea levels considering precipitation effects outperformed predictions without precipitation. The benefit of incorporating precipitation was greater at Cox’s Bazar than at Charchanga and Khepupara, reflecting the hilly landscape at Cox’s Bazar. The improved prediction skill was mainly confirmed during the monsoon season, when strong precipitation events occur. It was also revealed that the precipitation over the Bangladesh area is insensitive to the El Niño-Southern Oscillation and Indian Ocean Dipole mode. The precipitation over northern Bangladesh tended to be high in the year of a high sea surface temperature over the Bay of Bengal, which may have contributed to the variation in sea level. The findings suggest that the effect of precipitation plays an essential role in enhancing sea levels during many extreme events. Therefore, incorporating the effect of terrestrial precipitation is essential for the better prediction of extreme sea levels, which helps coastal management and reduction of hazards.

High health expenditures and low exposure of population to air pollution as critical factors that can reduce fatality rate in COVID-19 pandemic crisis: a global analysis

One of the problems hardly clarified in Coronavirus Disease 2019 (COVID-19) pandemic crisis is to identify factors associated with a lower mortality of COVID-19 between countries to design strategies to cope with future pandemics in society. The study here confronts this problem by developing a global analysis based on more than 160 countries. This paper proposes that Gross Domestic Product (GDP) per capita, healthcare spending and air pollution of nations are critical factors associated with fatality rate of COVID-19. The statistical evidence seems in general to support that countries with a low average COVID-19 fatality rate have high expenditures in health sector >7.5% of GDP, high health expenditures per capita >$2,300 and a lower exposure of population to days exceeding safe levels of particulate matter (PM2.5). Another relevant finding here is that these countries have lower case fatality rates (CFRs) of COVID-19, regardless a higher percentage of population aged more than 65 years. Overall, then, this study finds that an effective and proactive strategy to reduce the negative impact of future pandemics, driven by novel viral agents, has to be based on a planning of enhancement of healthcare sector and of environmental sustainability that can reduce fatality rate of infectious diseases in society.

A model for population exposure to PM2.5: Identification of determinants for high population exposure in Seoul

Outdoor concentrations of particulate matter with an aerodynamic diameter of <2.5 μm (PM2.5) are often used as a surrogate for population exposure to PM2.5 in epidemiological studies. However, people spend most of their daily activities indoors; therefore, the relationship between indoor and outdoor PM2.5 concentrations should be considered in the estimation of population exposure to PM2.5. In this study, a population exposure model was developed to predict seasonal population exposure to PM2.5 in Seoul, Korea. The input data for the population exposure model comprised 3984 time-location patterns, outdoor PM2.5 concentrations, and the microenvironment-to-outdoor PM2.5 concentrations in seven microenvironments. A probabilistic approach was used to develop the Korea simulation exposure model. The determinants for the population exposure group were identified using a multinomial logistic regression analysis. Population exposure to PM2.5 varied significantly among the three seasons (p < 0.01). The mean ± standard deviation of population exposures to PM2.5 was 21.3 ± 4.0 μg/m3 in summer, 9.8 ± 2.7 μg/m3 in autumn, and 29.9 ± 10.6 μg/m3 in winter. Exposure to PM2.5 higher than 35 μg/m3 mainly occurred in winter. Gender, age, working hours, and health condition were identified as significant determinants in the exposure groups. An “unhealthy” health condition was the most significant determinant. The high PM2.5 exposure group was characterized as a higher proportion of males of a lower age with longer working hours. The population exposure model for PM2.5 could be used to implement effective interventions and evaluate the effectiveness of control policies to reduce exposure.

Immune-Mediated Disease Flares or New-Onset Disease in 27 Subjects Following mRNA/DNA SARS-CoV-2 Vaccination.

Background: Infectious diseases and vaccines can occasionally cause new-onset or flare of immune-mediated diseases (IMDs). The adjuvanticity of the available SARS-CoV-2 vaccines is based on either TLR-7/8 or TLR-9 agonism, which is distinct from previous vaccines and is a common pathogenic mechanism in IMDs. Methods: We evaluated IMD flares or new disease onset within 28-days of SARS-CoV-2 vaccination at five large tertiary centres in countries with early vaccination adoption, three in Israel, one in UK, and one in USA. We assessed the pattern of disease expression in terms of autoimmune, autoinflammatory, or mixed disease phenotype and organ system affected. We also evaluated outcomes. Findings: 27 cases included 17 flares and 10 new onset IMDs. 23/27 received the BNT - 162b2 vaccine, 2/27 the mRNA-1273 and 2/27 the ChAdOx1 vaccines. The mean age was 54.4 ± 19.2 years and 55% of cases were female. Among the 27 cases, 21 (78%) had at least one underlying autoimmune/rheumatic disease prior the vaccination. Among those patients with a flare or activation, four episodes occurred after receiving the second-dose and in one patient they occurred both after the first and the second-dose. In those patients with a new onset disease, two occurred after the second-dose and in one patient occurred both after the first (new onset) and second-dose (flare). For either dose, IMDs occurred on average 4 days later. Of the cases, 20/27 (75%) were mild to moderate in severity. Over 80% of cases had excellent resolution of inflammatory features, mostly with the use of corticosteroid therapy. Other immune-mediated conditions included idiopathic pericarditis (n = 2), neurosarcoidosis with small fiber neuropathy (n = 1), demyelination (n = 1), and myasthenia gravis (n = 2). In 22 cases (81.5%), the insurgence of Adverse event following immunization (AEFI)/IMD could not be explained based on the drug received by the patient. In 23 cases (85.2%), AEFI development could not be explained based on the underlying disease/co-morbidities. Only in one case (3.7%), the timing window of the insurgence of the side effect was considered not compatible with the time from vaccine to flare. Interpretation: Despite the high population exposure in the regions served by these centers, IMDs flares or onset temporally-associated with SARS-CoV-2 vaccination appear rare. Most are moderate in severity and responsive to therapy although some severe flares occurred. Funding: none.

The Risk of the Population in a Changing Climate over the Tibetan Plateau, China: Integrating Hazard, Population Exposure and Vulnerability

As the “Third Pole” of the Earth, the Tibetan Plateau (TP) has been warming significantly, and the instability of extreme events related to climate and weather has enhanced exceptionally in recent decades. These changes have posed increasingly severe impacts on the population over the TP. So far, however, the impacts on the population have not been assessed systematically and comprehensively from the perspective of risk. In this paper, the hazard of climate change was assessed from a fresh look, not only considering extreme changes of air temperature, precipitation, and wind speed, but also their changes in mean and fluctuation, using daily meteorological data from 1961–2015. The population exposure and vulnerability to climate change were then evaluated using demographic data and considering population scale and structure. Finally, the population risk over the TP to climate change was quantitatively assessed within the framework of the Intergovernmental Panel on Climate Change (IPCC). The results showed that the climate change hazard was mainly at medium and heavy levels, in areas accounting for 64.60% of the total. The population exposure was relatively low; the land area at slight and light levels accounted for 83.94%, but high in the eastern edge area of the TP. The population vulnerability was mostly at medium and heavy levels, and the non-agricultural population rate was the key factor affecting the population vulnerability. Generally, the overall population risk over the TP was not very high: the number of counties with heavy and very heavy risk only accounted for 24.29%, and land area was less than 5%. However, more than 40% of the population was in high-risk areas, located in the eastern edge area of the TP. Population exposure was the decisive factor of the population risk to climate change, and high population exposure might lead to high risk. These findings were potentially valuable to improve cognition of risk, develop proactive risk mitigation strategies, and ensure sustainable development.

Ecological risks of geological disasters and the patterns of the urban agglomeration in the Fujian Delta region

Geological disasters not only hinder the ecological security guarantee in urban agglomerations, but also pose serious threat to the life and property of residents in the areas. The study establishes a “hazard-vulnerability-exposure” three-dimensional ecological risk assessment model, adopts an information value model to assess hazard, use landscape indices to analyze vulnerability and nighttime light data to indicate population exposure, and then quantitatively assesses the watershed-scale ecological risks of geological disasters and their patterns. The results show that ecological risks of geological disasters are mainly medium risks, presenting the trend of weakening from southeastern coastal areas to northwestern inland areas. The ecological risks exist in eight patterns in combination of the three dimensions of hazard, vulnerability and exposure. The elevation of 600–800 m, slope of 5 ~ 15°, aspect as southwest, NDVI of 0.4–0.6, lithology of metamorphic rocks, land use type as farmland, multi-year average precipitation of >1600 mm, distance to river of less than 200 m and distance to fault of less than 1000 m are the combination of greater likelihood of inducing geological disasters. Thestudyfindsthat ecological risks of geological disasters show the trend of high in the southeast and low in the northwest and are the highest under combination of the high vulnerability and high exposure pattern out of the eight patterns that are predominated by high population exposure. In addition, the study discovers the combination of greater likelihood of inducing geological disasters, and puts forward the prevention and control measures against geological disasters in the future.

Tsunami inundation hazard across Japan

Japan faces the world's highest tsunami hazard and risk due to its tectonic environment, high population density and exposure concentration along its coastlines. It is therefore of paramount interest to quantify and differentiate absolute and relative tsunami hazard and risk on a countrywide scale. We quantify tsunami hazard in terms of inundation depth for the entire Japanese coastline with a probabilistic tsunami hazard assessment utilizing the earthquake source information of the 2017 Japanese seismic hazard model. We simulate a stochastic event set for offshore earthquake sources and generate, for each single source with MW ≥ 7.5, non-uniform finite-fault slip models. We calculate elastic seafloor and landmass deformations that serve as initial conditions to high-resolution numerical modelling of tsunami wave propagation and coastal inundations by solving the non-linear shallow water equation. Variable land surface roughness based on land cover data is used to simulate accurate hydraulics of coastal inundation.We differentiate tsunami hazard by inundation depth hazard curves and inundation depth return period maps aggregated to city ward polygons as meaningful administrative boundaries. We find mega-thrust events on the subduction interfaces constituting the largest hazard. However, events down to MW = 7.5 can contribute to substantial hazard in several regions along the coast. In particular for city wards within the Tokyo bay area, we find that earthquakes occurring on the Sagami trough and not the largest mega-thrust events on the Nankai trough, contribute to the highest inundation hazard. Our results also illustrate that tsunami hazard on the western Japanese coast is not negligible.

Optimizing Emissions Reductions from the U.S. Power Sector for Climate and Health Benefits.

Improved air quality and human health are often discussed as "co-benefits" of mitigating climate change, yet they are rarely considered when designing or implementing climate policies. We analyze the implications of integrating health and climate when determining the best locations for replacing power plants with new wind, solar, or natural gas to meet a CO2 reduction target in the United States. We employ a capacity expansion model with integrated assessment of climate and health damages, comparing portfolios optimized for benefits to climate alone or both health and climate. The model estimates county-level health damages and accounts for uncertainty by using a range of air quality models (AP3, EASIUR, and InMAP) and concentration-response functions (American Cancer Society and Harvard Six Cities). We find that reducing CO2 by 30% yields $21-68 billion in annual health benefits, with an additional $9-36 billion possible when co-optimizing for climate and health benefits. Additional benefits accrue from prioritizing emissions reductions in counties with high population exposure. Total health benefits equal or exceed climate benefits across a wide range of modeling assumptions. Our results demonstrate the value of considering health in climate policy design and the need for interstate cooperation to achieve additional health benefits equitably.

Application of WRF Model for Vehicular Pollution Modelling Using AERMOD

Vehicular pollution is becoming significant in urban areas because of increasing population. This is at ground level, so it gives high population exposure. In this study, Chembur, which is the most polluted area in Mumbai city due to industrial and vehicular sources, is selected for vehicular pollution modeling using AMS/EPA Regulatory Model (AERMOD). Meteorological parameters, land use surface characteristics and source emission data are collected as required by AERMOD. The results of modelling depend upon reliability of input data and meteorological data has a vital role in the performance of the model. Generally, temporally and spatially interpolated meteorological data is used in modeling. This is generally collected from nearby meteorological station but this causes inaccuracy of the results. In this paper, the Weather Research and Forecasting (WRF) model has been used to generate onsite data on nine meteorological parameters. The modeling of six roads of Chembur has been performed using above meteorological data. This approach gives good results of traffic modeling. The results of AERMOD are compared with observed air quality which has contribution from all sources in the region and relative contribution of vehicular sources identified.