Health Impact Assessment Model Research Articles

Modeling Urban-Rural health disparities using a Taxi-Based mobile atmospheric monitoring system

The disparities of pollutant exposures and health burdens exists among regions. To capture the spatio-temporal variability of PM2.5 and analyze the inequity between urban and rural areas, this study developed a health impact assessment (HIA) model, which incorporates hyper-localized roadside PM2.5 concentration collected by a taxi-based mobile monitoring system. High-resolution pollutant concentrations, health risks, and PM2.5-related deaths were mapped to illustrate the spatio-temporal patterns among regions. The results showed that the average PM2.5 concentrations in some rural counties were higher than urban areas. 7.85%, 3.72%, 8.74%, and 0.97% of individuals were exposed to environment higher than the maximum concentration of central districts in winter, spring, summer, and autumn, respectively. The application of refined HIA model was discussed and grid cells with high risks of all-cause mortality, cardiovascular disease, respiratory disease, and lung cancer were identified. Establishing the comprehensive pollutant monitoring system facilitates targeted interventions and realization of health equity.

Improving consistency in estimating future health burdens from environmental risk factors: Case study for ambient air pollution

Future changes in exposure to risk factors should impact mortality rates and population. However, studies commonly use mortality rates and population projections developed exogenously to the health impact assessment model used to quantify future health burdens attributable to environmental risks that are therefore invariant to projected exposure levels. This impacts the robustness of many future health burden estimates for environmental risk factors. This work describes an alternative methodology that more consistently represents the interaction between risk factor exposure, population and mortality rates, using ambient particulate air pollution (PM2.5) as a case study. A demographic model is described that estimates future population based on projected births, mortality and migration. Mortality rates are disaggregated between the fraction due to PM2.5 exposure and other factors for a historic year, and projected independently. Accounting for feedbacks between future risk factor exposure and population and mortality rates can greatly affect estimated future attributable health burdens. The demographic model estimates much larger PM2.5-attributable health burdens with constant 2019 PM2.5 (∼10.8 million deaths in 2050) compared to a model using exogenous population and mortality rate projections (∼7.3 million), largely due to differences in mortality rate projection methods. Demographic model-projected PM2.5-attributable mortality can accumulate substantially over time. For example, ∼71 million more people are estimated to be alive in 2050 when WHO guidelines (5 µg m−3) are achieved compared to constant 2019 PM2.5 concentrations. Accounting for feedbacks is more important in applications with relatively high future PM2.5 concentrations, and relatively large changes in non-PM2.5 mortality rates.

Unpacking the factors contributing to changes in PM2.5-associated mortality in China from 2013 to 2019

From 2013 to 2019, a series of air pollution control actions significantly reduced PM2.5 pollution in China. Control actions included changes in activity levels, structural adjustment (SA) policy, energy and material saving (EMS) policy, and end-of-pipe (EOP) control in several sources, which have not been systematically studied in previous studies. Here, we integrate an emission inventory, a chemical transport model, a health impact assessment model, and a scenario analysis to quantify the contribution of each control action across a range of major emission sources to the changes in PM2.5 concentrations and associated mortality in China from 2013 to 2019. Assuming equal toxicity of PM2.5 from all the sources, we estimate that PM2.5-related mortality decreased from 2.52 (95 % confidence interval, 2.13–2.88) to 1.94 (1.62–2.24) million deaths. Anthropogenic emission reductions and declining baseline incidence rates significantly contributed to health benefits, but population aging partially offset their impact. Among the major sources, controls on power plants and industrial boilers were responsible for the highest reduction in PM2.5-related mortality (∼80 %), followed by industrial processes (∼40 %), residential combustion (∼40 %), and transportation (∼30 %). However, considering the potentially higher relative risks of power plant PM2.5, the adverse effects avoided by their control could be ∼2.4 times the current estimation. Our power plant sensitivity analyses indicate that future estimates of source-specific PM2.5 health effects should incorporate variations in individual source PM2.5 effect coefficients when available. As for the control actions, while activity levels increased for most sources, SA policy significantly reduced the emissions in residential combustion and industrial boilers, and EOP control dominated the contribution in health benefits in most sources except residential combustion. Considering the emission reduction potential by source and control actions in 2019, our results suggest that promoting clean energy in residential combustion and enforcing more stringent EOP control in the iron and steel industry should be prioritized in the future.

Health and economic benefits of heavy-duty diesel truck emission control policies in Beijing

PM2.5 emissions from heavy-duty diesel trucks (HDDTs) have a significant impact on air quality, human health, and climate change, and seriously threaten the UN Sustainable Development Goals. Globally, a series of emission control measures have been implemented to reduce pollution emissions from HDDTs. Current studies assessing the impact of these measures on air quality and human health have mainly used coarse-grained emission data as input to dispersion model, resulting in the inability to capture the spatiotemporal variability of pollutant concentrations and tending to increase the uncertainty of health impact assessment results. In this study, we quantified the impact of pollution control policies for HDDTs in Beijing on PM2.5 concentrations, human health, and economic losses by integrating policy scenario analysis, pollution dispersion simulation, public health impact and economic benefit assessment models, supported by high spatiotemporal resolution emission data from HDDTs. The results show that PM2.5 concentrations from HDDTs exhibit significant spatial aggregation characteristics, with the intensity of aggregation at night being about twice as high as that during the day. The emission hotspots are mainly concentrated in the sixth, fifth and fourth rings and major highways. Compared to the “business as usual” scenario in 2018, the current policy of updating the fuel standard to China VI and the emission standard to China 6 can reduce PM2.5 concentrations by 96.72%, thereby avoiding 612 premature deaths, which is equivalent to obtaining economic benefits of 1.65 billion CNY. This study further emphasizes the importance of high spatiotemporal resolution emission data during traffic dispersion modeling. The results can help improve the understanding of the effectiveness of emission reduction measures for HDDTs from a health benefit perspective.

School building energy efficiency and NO2 related risk of childhood asthma in England and Wales: Modelling study

BackgroundClimate change legislation will require dramatic increases in the energy efficiency of school buildings across the UK by 2050, which has the potential to affect air quality in schools. We assessed how different strategies for improving the energy efficiency of school buildings in England and Wales may affect asthma incidence and associated healthcare utilization costs in the future. MethodsIndoor concentrations of traffic-related NO2 were modelled inside school buildings representing 13 climate regions in England and Wales using a building physics school stock model. We used a health impact assessment model to quantify the resulting burden of childhood asthma incidence by combining regional health and population data with exposure-response functions from a recent high-quality systematic review/meta-analysis. We compared the effects of four energy efficiency interventions consisting of combinations of retrofit and operational strategies aiming to improve indoor air quality and thermal comfort on asthma incidence and associated hospitalization costs. ResultsThe highest childhood asthma incidence was found in the Thames Valley region (including London), in particular in older school buildings, while the lowest concentrations and health burdens were in the newest schools in Wales. Interventions consisting of only operational improvements or combinations of retrofit and operational strategies resulted in reductions in childhood asthma incidence (547 and 676 per annum regional average, respectively) and hospital utilization costs (£52,050 and £64,310 per annum regional average, respectively. Interventions that improved energy efficiency without operational measures resulted in higher childhood asthma incidence and hospital costs. ConclusionThe effect of school energy efficiency retrofit on NO2 exposure and asthma incidence in schoolchildren depends critically on the use of appropriate building operation strategies. The findings from this study make several contributions to fill the knowledge gap about the impact of retrofitting schools on exposure to air pollutants and their effects on children's health.

Non-negligible health risks caused by inhalation exposure to aldehydes and ketones during food waste treatments in megacity Shanghai

Aldehydes and ketones in urban air continue to receive regulatory and scientific attention for their environmental prevalence and potential health hazard. However, current knowledge of the health risks and losses caused by these pollutants in food waste (FW) treatment processes is still limited, especially under long-term exposure. Here, we presented the first comprehensive assessment of chronic exposure to 21 aldehydes and ketones in urban FW-air environments (e.g., storage site, mechanical dewatering, and composting) by coupling substantial measured data (383 samples) with Monte Carlo-based probabilistic health risk and impact assessment models. The results showed that acetaldehyde, acetone, 2-butanone and cyclohexanone were consistently the predominant pollutants, although the significant differences in pollution profiles across treatment sites and seasons (Adonis test, P < 0.001). According to the risk assessment results, the estimated cancer risk (CR; mean range: 1.6 × 10−5-1.12 × 10−4) and non-cancer risk (NCR; mean range: 2.98–22.7) triggered by aldehydes and ketones were both unacceptable in most cases (CR: 37.8%–99.3%; NCR: 54.2%–99.8%), and even reached the limit of concern to CR (1 × 10−4) in some exposure scenarios (6.18%–16.9%). Application of DALYs (disability adjusted life years) as a metric for predicting the damage suggested that exposure of workers to aldehydes and ketones over 20 years of working in FW-air environments could result in 0.02–0.14 DALYs per person. Acetaldehyde was the most harmful constituent of all targeted pollutants, which contributed to the vast majority of health risks (>88%) and losses (>90%). This study highlights aldehydes and ketones in FW treatments may be the critical pollutants to pose inhalation risks.

Source Contributions to PM2.5-Related Mortality and Costs: Evidence for Emission Allocation and Compensation Strategies in China

The emissions from various pollution sources were not proportional to their contributions to ambient PM2.5 concentrations and associated health burdens. That means even with the same total abatement targets, different abatement allocation strategies across emission sources can have distinct health benefits. Insufficient knowledge of various sources' contributions to health burdens in China, the country suffering substantial PM2.5-related deaths, hindered the government from seeking optimized abatement allocation strategies. In this context, we separated the contributions of 155 emission sources (31 provinces × 5 sectors) to PM2.5-related mortality across China in 2017 by coupling the Comprehensive Air Quality Model with Extensions (CAMx), Weather Research and Forecasting model (WRF), and health impact assessment model. We further identified the priority-control emission sources and quantified interprovincial ecological compensation volumes to alleviate inequality induced by emission allocation strategies. Results showed that PM2.5 pollution caused 899,443 excess deaths and around 127 billion USD costs in 2017. Approximately half of the deaths and costs were attributable to emissions from sources outside the boundary of the regions where the deaths occurred. Twenty-five out of 155 emission sources that contributed to the top 60% mortality burdens and had high marginal abatement efficiencies in China shall be the priority-control emission sources. A 1 μg/m3 decrease of PM2.5 concentration in regions where these key emission sources occur shall be compensated by 76-153 million USD in their receptor regions. Our study sheds light on the sources' contributions to mortality burdens and costs and provides scientific evidence for optimizing the emission allocation and compensation strategies in China. It also has wide implications for other countries suffering similar problems.

Present-day and future PM2.5 and O3-related global and regional premature mortality in the EVAv6.0 health impact assessment model

We used the EVAv6.0 system to estimate the present (2015) and future (2015–2050) global PM2.5 and O3-related premature mortalities, using simulated surface concentrations from the GISS-E2.1-G Earth system model. The PM2.5-related global premature mortality is estimated to be 4.3 and 4.4 million by the non-linear and linear models, respectively. Ischemic heart diseases are found to be the leading cause of PM2.5-related premature deaths, contributing by 35% globally. Both long-term and short-term O3-related premature deaths are estimated to be around 1 million, globally. Overall, PM2.5 and O3-related premature mortality leads to 5.3–5.4 million premature deaths, globally. The global burden of premature deaths is mainly driven by the Asian region, which in 2015 contributes by 75% of the total global premature deaths. An increase from 6.2% to 8% in the PM2.5 relative risk as recommended by the WHO leads to an increase of PM2.5-related premature mortality by 28%, to 5.7 million. Finally, bias correcting the simulated PM2.5 concentrations in 2015 leads to an increase of up to 73% in the global PM2.5-related premature mortality, leading to a total number of global premature deaths of up to 7.7 million, implying the necessity of bias correction to get more robust health burden estimates. PM2.5 and O3-related premature mortality in 2050 decreases by up to 57% and 18%, respectively, due to emission reductions alone. However, the projected increase and aging of the population leads to increases of premature mortality by up to a factor of 2, showing that the population exposed to air pollution is more important than the level of air pollutants, highlighting that the population dynamics should be considered when setting up health assessment systems.

Mutual effects of CO2 emission reduction and air pollution control policies in beijing-tianjin-hebei region

To meet the carbon neutrality target and Beautiful China goal, the co-control strategy of carbon emission and air pollution is crucial. The Beijing-Tianjin-Hebei region is a prominent cooperative development zone, which faces dual challenges of CO2 emission reduction and air pollution control. This study aims to find the co-benefit pathway for achieving both targets in Beijing-Tianjin-Hebei. Based on an innovative and integrated framework by linking the computable general equilibrium model, atmospheric environment analysis model and health impact assessment model, we analyze the mutual co-benefits of carbon reduction and air quality improvement by climate and environmental policies. The results show significant mutual effects of CO2 emission mitigation and air pollution reduction. From the regional view, air pollutants control and CO2 mitigation policies have a relatively higher synergistic emission reduction effect in Beijing and Tianjin than in Hebei. From the sector perspective, the energy supply and transport sectors have much higher co-effects with CO2 reduction, while climate change mitigation policies have the best co-effects with air pollution reduction in the energy supply and residential sectors. Moreover, the health benefits in the air pollution control scenario (6.0 BUSD) are higher than in the decarbonization scenario (5.7 BUSD). In addition, climate mitigation policies could have tremendous synergistic air pollution reductions, even the health benefits (5.7 BUSD) may be insufficient to offset the cost (18.7 BUSD) of climate policy in the current situation. In order to better achieve the dual climate and air quality targets at lower costs, two types of policies should be better coordinated in the decision-making process.

Quantifying the multiple environmental, health, and economic benefits from the electrification of the Delhi public transport bus fleet, estimating a district-wise near roadway avoided PM2.5 exposure

This study investigates the co-benefits from the utilization of the battery-electric bus (BEB) fleet in the Delhi public transportation system as a part of the Delhi electric vehicles policy 2020. To this aim, an integrated quantitative assessment framework is developed to estimate the expected environmental, health, and economic co-benefits from replacing the currently existing public bus fleet with the new BEBs in Delhi. First, the model estimates the avoided emissions from deploying the BEB fleet, using a detailed battery energy simulation model, considering the impact of the battery capacity loss on the annual operational time (hours of service) of the BEB. The annual operational time of the BEB is greatly affected by its battery degradation, which results in time lost due to charging the battery. This indicates that the annual passenger-kilometer (PKM) delivered by the BEB is less than the regular bus, under the same traveling condition. Second, considering fine particles (PM2.5) as the most health-harming pollutant, the model calculates the near roadway avoided PM2.5 exposure in the selected traffic zones of 11 major districts of Delhi, using a Gaussian dispersion model. Third, the near roadway avoided PM2.5 exposure is further used in a health impact assessment model, which considers concentration-response functions for several diseases to evaluate the public health benefits from introducing the BEB fleet in Delhi. The research findings indicate that, the utilization of the new BEB fleet leads to a 74.67% reduction in the total pollutant emissions from the existing bus fleet in Delhi. The results of the integrated co-benefits assessment reveal a significant reduction in PM2.5 emissions (44 t/y), leading to avoidance of mortality (1370 cases) and respiratory diseases related hospital admissions (2808 cases), respectively, and an annual savings of about USD 383 million from the avoided mortality and morbidity cases in Delhi.

Projecting the Suicide Burden of Climate Change in the United States.

We quantify and monetize changes in suicide incidence across the conterminous United States (U.S.) in response to increasing levels of warming. We develop an integrated health impact assessment model using binned and linear specifications of temperature‐suicide relationship estimates from Mullins and White (2019), in combination with monthly age‐ and sex‐specific baseline suicide incidence rates, projections of six climate models, and population projections at the conterminous U.S. county scale. We evaluate the difference in the annual number of suicides in the U.S. corresponding to 1–6°C of warming compared to 1986–2005 average temperatures (mean U.S. temperatures) and compute 2015 population attributable fractions (PAFs). We use the U.S. Environmental Protection Agency’s Value of a Statistical Life to estimate the economic value of avoiding these mortality impacts. Assuming the 2015 population size, warming of 1–6°C could result in an annual increase of 283–1,660 additional suicide cases, corresponding to a PAF of 0.7%–4.1%. The annual economic value of avoiding these impacts is $2 billion–$3 billion (2015 U.S. dollars, 3% discount rate, and 2015 income level). Estimates based on linear temperature‐suicide relationship specifications are 7% larger than those based on binned temperature specifications. Accounting for displacement decreases estimates by 17%, while accounting for precipitation decreases estimates by 7%. Population growth between 2015 and the future warming degree arrival year increases estimates by 15%–38%. Further research is needed to quantify and monetize other climate‐related mental health outcomes (e.g., anxiety and depression) and to characterize these risks in socially vulnerable populations.

Present-Day and Future Pm2.5 and O3-Related Global and Regional Premature Mortality in the Evav6.0 Health Impact Assessment Model

Present-Day and Future Pm2.5 and O3-Related Global and Regional Premature Mortality in the Evav6.0 Health Impact Assessment Model

Reduced-complexity air quality intervention modeling over China: the development of InMAPv1.6.1-China and a comparison with CMAQv5.2

Abstract. This paper presents the first development and evaluation of a reduced-complexity air quality model for China. In this study, the reduced-complexity Intervention Model for Air Pollution over China (InMAP-China) is developed by linking a regional air quality model, a reduced-complexity air quality model, an emission inventory database for China, and a health impact assessment model to rapidly estimate the air quality and health impacts of emission sources in China. The modeling system is applied over mainland China for 2017 under various emission scenarios. A comprehensive model evaluation is conducted by comparison against conventional Community Multiscale Air Quality (CMAQ) modeling system simulations and ground-based observations. We found that InMAP-China satisfactorily predicted total PM2.5 concentrations in terms of statistical performance. Compared with the observed PM2.5 concentrations, the mean bias (MB), normalized mean bias (NMB) and correlations of the total PM2.5 concentrations are −8.1 µg m−3, −18 % and 0.6, respectively. The statistical performance is considered to be satisfactory for a reduced-complexity air quality model and remains consistent with that evaluated in the USA. The underestimation of total PM2.5 concentrations was mainly caused by its composition, primary PM2.5. In terms of the ability to quantify source contributions of PM2.5 concentrations, InMAP-China presents similar results to those based on the CMAQ model, with variation mainly caused by the different treatment of secondary inorganic aerosols in the two models. Focusing on the health impacts, the annual PM2.5-related premature mortality estimated using InMAP-China in 2017 was 1.92 million, which was 250 000 deaths lower than estimated based on CMAQ simulations as a result of the underestimation of PM2.5 concentrations. This work presents a version of the reduced-complexity air quality model over China that provides a powerful tool to rapidly assess the air quality and health impacts associated with control policy and to quantify the source contribution attributable to many emission sources.

Heat-related mortality under climate change and the impact of adaptation through air conditioning: A case study from Thessaloniki, Greece

Climate change is expected to increase heat-related mortality across the world. Health Impact Assessment (HIA) studies are used to quantify the impact of higher temperatures, taking into account the effect of population adaptation. Although air-conditioning (AC) is one of the main drivers of technological adaptation to heat, the health impacts associated with AC-induced air pollution have not been examined in detail. This study uses the city of Thessaloniki, Greece as a case study and aims to estimate the future heat-related mortality, the residential cooling demand, and the adaptation trade-off between averted heat-related and increased air pollution cardiorespiratory mortality. Using temperature and population projections under different Coupled Model Intercomparison Project Phase 6 (CIMP6) Shared Socioeconomic Pathways scenarios (SSPs), a HIA model was developed for the future heat and air pollution cardiorespiratory mortality. Counterfactual scenarios of either black carbon (BC) or natural gas (NG) being the fuel source for electricity generation were included in the HIA. The results indicate that the heat-related cardiorespiratory mortality in Thessaloniki will increase and the excess of annual heat-related deaths in 2080–2099 will range from 2.4 (95% CI: 0.0–20.9) under SSP1-2.6 to 433.7 (95% CI: 66.9–1070) under SSP5-8.5. Population adaptation will attenuate the heat-related mortality, although the latter may be counterbalanced by the higher air pollution-related mortality due to increased AC, especially under moderate SSP scenarios and coal-fired power plants. Future studies examining the health effects of warmer temperatures need to account for the impact of both adaptation and increased penetration and use of AC.

The Development of a Rapid Health Impact Assessment Model for Songkhla Special Economic Zone (SEZ) Policy in Southern Thailand.

Background:Rapid Health Impact Assessment (Rapid HIA) for Special Economic Zone (SEZ) has not been undertaken in Thailand. We aimed to develop a Rapid HIA model for policymaking by using Songkhla SEZ as a study model.Methods:Four-stage of the research and development based on HIA process were used: 1) drafting the model using literature reviews and focus group discussions, 2) collecting additional information from 24 stakeholders, and conducting an in-depth interview with six informants, 3) verifying the model by drawing agreements on the model from 17 related agencies and experts, and 4) confirming the validity of the final model using seven experts. The study were conducted from Jan 2018 to Feb 2019. Content analysis and constant comparison were used to analyze the data.Results:A four-step assessment model was obtained. They included public screening, scoping, assessing, and reviewing and influencing. Public screening is deduced from a meeting with organizations and related personnel. Public scoping is an outcome of literature reviewing and meeting with stakeholders and academics. The assessment step focuses on secondary data from related agencies and a participatory workshop with stakeholders and academics. Finally, a meeting with stakeholders and academics, including internet broadcasting, is the reviewing and influencing process.Conclusion:This Rapid HIA model was specifically developed for SEZ policy. Reviewing and influencing steps were combined, whereas the monitoring and evaluation step was removed for further operations. This model depends on the official appointment of the steering committee. HIA practitioners should be experienced academics from higher educational institutions.

The long-term impact of restricting cycling and walking during high air pollution days on all-cause mortality: Health impact Assessment study

Regular active commuting, such as cycling and walking to and from the workplace, is associated with lower all-cause mortality through increased physical activity (PA). However, active commuting may increase intake of fine particles (PM2.5), causing negative health effects. The purpose of this study is to estimate the combined risk of PA and air pollution for all-cause mortality among active commuters who, on days with high PM2.5 levels, switch to commuting by public transportation or work from home. Towards this purpose, we developed a Health Impact Assessment model for six cities (Helsinki, London, Sao Paulo, Warsaw, Beijing, New Delhi) using daily, city-specific PM2.5 concentrations. For each city we estimated combined Relative Risk (RR) due to all-cause mortality for the PA benefits and PM2.5 risks with different thresholds concentrations. Everyday cycling to work resulted in annual all-cause mortality risk reductions ranging from 28 averted deaths per 1000 cyclists (95% confidence interval (CI): 20–38) in Sao Paolo to 12 averted deaths per 1000 cyclists (95% CI: 5–19) in Beijing. Similarly, for everyday walking, the reductions in annual all-cause mortality ranged from 23 averted deaths per 1000 pedestrians (95 CI: 16–31) in Sao Paolo to 10 averted deaths per 1000 pedestrians (95%CI: 5–16) in Beijing. Restricting active commuting during days with PM2.5 levels above specific air quality thresholds would not decrease all-cause mortality risk in any examined city. On the contrary, all-cause mortality risk would increase if walking and cycling are restricted in days with PM2.5 concentrations below 150 μg/m3 in highly polluted cities (Beijing, New Delhi). In all six cities, everyday active commuting reduced all-cause mortality when benefits of PA and risk or air pollution were combined. Switching to working from home or using public transport on days with high air pollution is not expected to lead to improved all-cause mortality risks.

Air quality co-benefits from climate mitigation for human health in South Korea

Climate change mitigation efforts to reduce greenhouse gas (GHG) emissions have associated costs, but there are also potential benefits from improved air quality, such as public health improvements and the associated cost savings. A multidisciplinary modeling approach can better assess the co-benefits from climate mitigation for human health and provide a justifiable basis for establishment of adequate climate change mitigation policies and public health actions. An integrated research framework was adopted by combining a computable general equilibrium model, an air quality model, and a health impact assessment model, to explore the long-term economic impacts of climate change mitigation in South Korea through 2050. Mitigation costs were further compared with health-related economic benefits under different socioeconomic and climate change mitigation scenarios. Achieving ambitious targets (i.e., stabilization of the radiative forcing level at 3.4 W/m2) would cost 1.3–8.5 billion USD in 2050, depending on varying carbon prices from different integrated assessment models. By contrast, achieving these same targets would reduce costs by 23 billion USD from the valuation of avoided premature mortality, 0.14 billion USD from health expenditures, and 0.38 billion USD from reduced lost work hours, demonstrating that health benefits alone noticeably offset the costs of cutting GHG emissions in South Korea.

Physical activity-related health and economic benefits of building walkable neighbourhoods: a modelled comparison between brownfield and greenfield developments

BackgroundA consensus is emerging in the literature that urban form can impact health by either facilitating or deterring physical activity (PA). However, there is a lack of evidence measuring population health and the economic benefits relating to alternative urban forms. We examined the issue of housing people within two distinct types of urban development forms: a medium-density brownfield development in an established area with existing amenities (e.g. daily living destinations, transit), and a low-density suburban greenfield development. We predicted the health and economic benefits of a brownfield development compared with a greenfield development through their influence on PA.MethodsWe combined a new Walkability Planning Support System (Walkability PSS) with a quantitative health impact assessment model. We used the Walkability PSS to estimate the probability of residents’ transport walking, based on their exposure to urban form in the brownfield and greenfield developments. We developed the underlying algorithms of the Walkability PSS using multi-level multivariate logistic regression analysis based on self-reported data for transport walking from the Victorian Integrated Survey of Transport and Activity 2009–10 and objectively measured urban form in the developments. We derived the difference in transport walking minutes per week based on the probability of transport walking in each of the developments and the average transport walking time per week among those who reported any transport walking. We then used the well-established method of the proportional multi-cohort multi-state life table model to translate the difference in transport walking minutes per week into health and economic benefits.ResultsIf adult residents living in the greenfield neighbourhood were instead exposed to the urban development form observed in a brownfield neighbourhood, the incidence and mortality of physical inactivity-related chronic diseases would decrease. Over the life course of the exposed population (21,000), we estimated 1600 health-adjusted life years gained and economic benefits of A$94 million.DiscussionOur findings indicate that planning policies that create walkable neighbourhoods with access to shops, services and public transport will lead to substantial health and economic benefits associated with reduced incidence of physical inactivity related diseases and premature death.

The Simon/Tanger Outlet Mall Health Impact Assessment: Resulting in Active Transportation through Community Connectivity

Background: One of the goals of the Health Impact Assessment (HIA), The Simon/Tanger Outlet Mall Health Impact Assessment was to assess potential health implications in providing opportunities for active transportation to the Simon/Tanger Outlet Mall in Berkshire Township, Delaware County, Ohio by community connectivity.&#x0D; Methods: This case study was conducted by using the Health Impact Assessment model and incorporated community input through survey methodologies, assessment protocols, best practices, and  peer-reviewed literature.&#x0D; Results: Many of the risk factors for chronic diseases can be traced on how communities have been built. Several pathways have been identified in the research linking built environments with travel patterns, physical activity levels, body mass index, and associated health outcomes. Residential density, land use mix, and neighborhood connectivity have all been consistently associated with multiple outcomes related to good health. By making neighborhoods more walkable, we not only can create converging health benefits, but environmental benefits and more equal access to jobs and opportunities. Emerging research on the presence of sidewalks, cycling infrastructure, street design, and building placement and site design have been linked to various health and health-related travel behavior outcomes.[1]&#x0D; Conclusions: Continuing modifications to the built environment provide opportunities, over time, to institute policies and practices that support the provision of more activity-conducive environments, which improve the community’s health. 

The Lancet Countdown on PM2·5 pollution-related health impacts of China's projected carbon dioxide mitigation in the electric power generation sector under the Paris Agreement: a modelling study

Except for comparing the implementation costs of the Paris Agreement with potential health benefits at the national levels, previous studies have not explored the health impacts of the nationally determined contributions (NDCs) by countries and in regional details. In this Lancet Countdown study, we aimed to estimate and monetise the health benefits of China's NDCs in the electric power generation sector, and then compare them with the implementation costs, both at the national and regional levels. In this modelling study, we linked the Multi-regional model for Energy Supply system and their Environmental ImpaCts, the Multi-resolution Emission Inventory for China model, the offline-coupled Weather Research and Forecasting model, the Community Multiscale Air Quality model, and the Integrated Health Impact Assessment model with a time scope from 2010 to 2050. We calculated the PM2·5 concentrations and compared the health impacts and implementation costs between two scenarios that reflect CO2 and air pollutant emissions-the reference (REF) scenario (no climate policy) and the NDC scenario (100% realisation of NDC targets: CO2 emission intensity needs to be about 40% below 2010 emissions by 2030 [roughly 35% below 2030 emissions in REF], and about 90% below 2010 emissions by 2050 [roughly 96% below 2050 emissions in REF]). Under a comparatively optimistic health benefits valuation condition, at the national level, 18-62% of implementation costs could be covered by the health benefits in 2030. In 2050, the overall health benefits would substantially increase to 3-9 times of the implementation costs. However, northwest China would require the highest implementation costs and will also have more premature deaths because of a more carbon-intensive energy structure than business as usual. By 2030, people in northwest China (especially in Gansu, Shaanxi, and Xinjiang provinces) would need to bear worse air quality, and 10 083 (95% CI 3419-16 138) more premature deaths annually. This undesirable situation would diminish by about 2050. A solution that assumes no growth in air pollutant emissions in 2030 at the regional level is technically feasible, but would not be cost-effective. Our results suggest that cost-benefit analysis of climate policy that omits regional air pollution could greatly underestimate benefits. A compensation mechanism for inter-regional interests (including financial, technological, and knowledge support) should be established for regions that give up their human health benefits for the sake of the whole nation to realise the climate change targets. National Natural Science Foundation of China and Cyrus Tang Foundation.