Global population exposure to landscape fire air pollution from 2000 to 2019.

Wildfires are thought to be increasing in severity and frequency as a result of climate change1-5. Air pollution from landscape fires can negatively affect human health4-6, but human exposure to landscape fire-sourced (LFS) air pollution has not been well characterized at the global scale7-23. Here, we estimate global daily LFS outdoor fine particulate matter (PM2.5) and surface ozone concentrations at 0.25° × 0.25° resolution during the period 2000-2019 with the help of machine learning and chemical transport models. We found that overall population-weighted average LFS PM2.5 and ozone concentrations were 2.5 µg m-3 (6.1% of all-source PM2.5) and 3.2 µg m-3 (3.6% of all-source ozone), respectively, in 2010-2019, with a slight increase for PM2.5, but not for ozone, compared with 2000-2009. Central Africa, Southeast Asia, South America and Siberia experienced the highest LFS PM2.5 and ozone concentrations. The concentrations of LFS PM2.5 and ozone were about four times higher in low-income countries than in high-income countries. During the period 2010-2019, 2.18 billion people were exposed to at least 1 day of substantial LFS air pollution per year, with each person in the world having, on average, 9.9 days of exposure per year. These two metrics increased by 6.8% and 2.1%, respectively, compared with 2000-2009. Overall, we find that the global population is increasingly exposed to LFS air pollution, with socioeconomic disparities.

Wildfire-related PM2.5 and health economic loss of mortality in Brazil.

BACKGROUND: Wildfire imposes a high mortality burden on Brazil. However, there is a limited assessment of the health economic losses attributable to wildfire-related fine particulate matter (PM2.5). METHODS: We collected daily time-series data on all-cause, cardiovascular, and respiratory mortality from 510 immediate regions in Brazil during 2000-2016. The chemical transport model GEOS-Chem driven with Global Fire Emissions Database (GFED), in combination with ground monitored data and machine learning was used to estimate wildfire-related PM2.5 data at a resolution of 0.25°â€ˆ× 0.25°. A time-series design was applied in each immediate region to assess the association between economic losses due to mortality and wildfire-related PM2.5 and the estimates were pooled at the national level using a random-effect meta-analysis. We used a meta-regression model to explore the modification effect of GDP and its sectors (agriculture, industry, and service) on economic losses. RESULTS: During 2000-2016, a total of US$81.08 billion economic losses (US$5.07 billion per year) due to mortality were attributable to wildfire-related PM2.5 in Brazil, accounting for 0.68% of economic losses and equivalent to approximately 0.14% of Brazil's GDP. The attributable fraction (AF) of economic losses due to wildfire-related PM2.5 was positively associated with the proportion of GDP from agriculture, while negatively associated with the proportion of GDP from service. CONCLUSION: Substantial economic losses due to mortality were associated with wildfires, which could be influenced by the agriculture and services share of GDP per capita. Our estimates of the economic losses of mortality could be used to determine optimal levels of investment and resources to mitigate the adverse health impacts of wildfires.

Short-term exposure to ozone and economic burden of premature mortality in Italy: A nationwide observation study.

Italy is among the countries with the highest ozone concentration in Europe. However, the mortality burden of ozone and related economic loss has not been fully characterized. This study aimed to estimate the ozone-mortality association in Italy and evaluate attributable mortality burden and related economic loss in 2015-2019. We collected daily all-cause mortality data stratified by age and sex from 2015 to 2019 in 107 provinces of Italy. A two-stage time-series framework was applied to estimate the association between daily maximum eight-hour average ozone and mortality as well as economic loss. An overall increase in the risk of mortality (RR=1.0043, 95% CI: 1.0029, 1.0057) was associated with every 10 µg/m3 increase in ozone. Generally, a total of 70,060 deaths and $65 billion economic loss were attributed to ozone exposure, corresponding to 3.11% of mortality and about 0.5% of the national GDP during the study period, respectively. The highest ozone-related mortality burden (30,910 deaths) and economic loss ($29.24 billion) were observed in the hot season. This nationwide study suggested considerable mortality burden and economic loss were associated with exposure to ozone. More actions and policies should be proposed to reduce ozone levels and help the public protect their health.

The indicators and methods used for measuring urban liveability: a scoping review.

OBJECTIVES: Liveability is a multi-dimensional and hierarchical concept which consists of various criteria and sub-criteria and may be evaluated in different ways. The aim of this study was to systematically review indicators and methods used for the evaluation of urban liveability in literature. CONTENT: The five-stage methodological framework of Arksey and O'Malley was used to conduct this scoping review. A systematic search of electronic databases, including Scopus, Medline (via PubMed), Embase, Web of Science and EBSCO was done until May 29, 2019. Web searching, searching reference lists and hand searching was also conducted to retrieve more relevant articles. Two reviewers screened the papers for eligibility based on the inclusion criteria and extracted their key data and reported them descriptively. SUMMARY: Sixty seven (67) out of 3,599 papers met the selection criteria. This review showed five distinct domains considered to be important components of liveability. These were Economical, Environmental, Institutional, Social, and Governance (Political) domains. The most important subdomains (indices) which were frequently applied in various studies were Environmental friendliness and Sustainability, Socio-Cultural Conditions and Economic Vibrancy and Competitiveness. We also identified seven different methodologies and six ranking tools used for assessing urban liveability. Among the quantitative methods, three methods accounted for 89.6% of the articles. These methods were the Analytical hierarchy process and entropy (AHP; n=24; 50%), Factor analysis & Principle Component Analysis (FA & PCA; n=12; 25%) and Spatial Multi-criteria Decision-making Method (Spatial; n=7; 14.6%). Among the ranking tools used, three ranking tools accounted for 65.4% of the articles. These tools were the Livable City Scientific Evaluation Standards (LCSES; n=9; 34.6%), The Global Liveable Cities Index (GLCI; n=4; 15.4%) and the Economist Intelligence Unit (EIU; n=4; 15.4%). OUTLOOK: This paper discusses and summarizes the latest indicators and methods used for determining urban liveability. The information offered in the review can help future investigators to decide which method suits their purpose and situation better and measure urban liveability more systematically than before.

Health and related economic benefits associated with reduction in air pollution during COVID-19 outbreak in 367 cities in China.

Due to the COVID-19 outbreak, the Chinese government implemented nationwide traffic restrictions and self-quarantine measures from January 23 to April 8 (in Wuhan), 2020. We estimated how these measures impacted ambient air pollution and the subsequent consequences on health and the health-related economy in 367 Chinese cities. A random forests modeling was used to predict the business-as-usual air pollution concentrations in 2020, after adjusting for the impact of long-term trend and weather conditions. We calculated changes in mortality attributable to reductions in air pollution in early 2020 and health-related economic benefits based on the value of statistical life (VSL). Compared with the business-as-usual scenario, we estimated 1239 (95% CI: 844-1578) PM2.5-related deaths were avoided, as were 2777 (95% CI: 1565-3995) PM10-related deaths, 1587 (95% CI: 98-3104) CO-related deaths, 4711 (95% CI: 3649-5781) NO2-related deaths, 215 (95% CI: 116-314) O3-related deaths, and 1088 (95% CI: 774-1421) SO2-related deaths. Based on the reduction in deaths, economic benefits for in PM2.5, PM10, CO, NO2, O3, and SO2 were 1.22, 2.60, 1.36, 4.05, 0.20, and 0.95 billion USD, respectively. Our findings demonstrate the substantial benefits in human health and health-related costs due to improved urban air quality during the COVID lockdown period in China in early 2020.

Evidence for Urban-Rural Disparity in Temperature-Mortality Relationships in Zhejiang Province, China.

BACKGROUND: Temperature-related mortality risks have mostly been studied in urban areas, with limited evidence for urban-rural differences in the temperature impacts on health outcomes. OBJECTIVES: We investigated whether temperature-mortality relationships vary between urban and rural counties in China. METHODS: We collected daily data on 1 km gridded temperature and mortality in 89 counties of Zhejiang Province, China, for 2009 and 2015. We first performed a two-stage analysis to estimate the temperature effects on mortality in urban and rural counties. Second, we performed meta-regression to investigate the modifying effect of the urbanization level. Stratified analyses were performed by all-cause, nonaccidental (stratified by age and sex), cardiopulmonary, cardiovascular, and respiratory mortality. We also calculated the fraction of mortality and number of deaths attributable to nonoptimum temperatures associated with both cold and heat components. The potential sources of the urban-rural differences were explored using meta-regression with county-level characteristics. RESULTS: Increased mortality risks were associated with low and high temperatures in both rural and urban areas, but rural counties had higher relative risks (RRs), attributable fractions of mortality, and attributable death counts than urban counties. The urban-rural disparity was apparent for cold (first percentile relative to minimum mortality temperature), with an RR of 1.47 [95% confidence interval (CI): 1.32, 1.62] associated with all-cause mortality for urban counties, and 1.98 (95% CI: 1.87, 2.10) for rural counties. Among the potential sources of the urban-rural disparity are age structure, education, GDP, health care services, air conditioners, and occupation types. CONCLUSIONS: Rural residents are more sensitive to both cold and hot temperatures than urban residents in Zhejiang Province, China, particularly the elderly. The findings suggest past studies using exposure-response functions derived from urban areas may underestimate the mortality burden for the population as a whole. The public health agencies aimed at controlling temperature-related mortality should develop area-specific strategies, such as to reduce the urban-rural gaps in access to health care and awareness of risk prevention. Future projections on climate health impacts should consider the urban-rural disparity in mortality risks. https://doi.org/10.1289/EHP3556.