Surface ozone (O₃) air pollution in populated regions has been attributed to emissions of nitrogen oxides (NO + NO₂ = NO_x) and reactive volatile organic compounds (VOCs). These constituents react with hydrogen oxide radicals (OH + HO₂ = HO_x) in the presence of sunlight and heat to produce O₃. The question of whether to reduce NO_x emissions, VOC emissions, or both is complicated by spatially and temporally heterogeneous ozone‐NO_x‐VOC sensitivity. This study characterizes spatial and temporal variations in O₃ sensitivity by analyzing the ratio of formaldehyde (HCHO, a marker of VOCs) to nitrogen dioxide (NO₂), a metric known as the formaldehyde nitrogen ratio (FNR). Level 3 gridded retrievals from the Ozone Monitoring Instrument (OMI) aboard the NASA Aura satellite were used to calculate FNR, with our analysis focusing on China. Based on previous studies, we take FNR < 1.0 as indicating VOC‐limited regimes, FNR > 2.0 as indicating NO_x‐limited regime, and FNR between 1.0 and 2.0 as indicating transitional regime (where either NO_x reductions or VOC reductions would be expected to reduce O₃). We find that the transitional regime is widespread over the North China Plain (NCP), the Yangtze River Delta, and the Pearl River Delta during the ozone season (defined as having near‐surface air temperatures >20°C at the early afternoon OMI overpass time). Outside of these regions, the NO_x‐limited regime is dominant. Because HCHO and NO₂ have distinct seasonal patterns, FNR also has a pronounced seasonality, consistent with the seasonal cycle of surface O₃. Examining trends from 2005 to 2013 indicates rapid growth in NO₂, especially over less‐developed areas where O₃ photochemistry is NO_x limited. Over this time period, HCHO decreased in southern China, where VOC emissions are dominated by biogenic sources, but increased slightly over the NCP, where VOC emissions are dominated by anthropogenic sources. A linear regression approach suggests that most of China (70% of grid cells) will be characterized by a transitional regime during the O₃ season by 2030. However, in megacities such as Guangzhou, Shanghai, and Beijing, NO₂ has decreased such that the chemical regime has shifted from VOC limited in 2005 to transitional in 2013.

Data from satellite instruments provide estimates of gas and particle levels relevant to human health, even pollutants invisible to the human eye. However, the successful interpretation of satellite data requires an understanding of how satellites relate to other data sources, as well as factors affecting their application to health challenges. Drawing from the expertise and experience of the 2016–2020 NASA HAQAST (Health and Air Quality Applied Sciences Team), we present a review of satellite data for air quality and health applications. We include a discussion of satellite data for epidemiological studies and health impact assessments, as well as the use of satellite data to evaluate air quality trends, support air quality regulation, characterize smoke from wildfires, and quantify emission sources. The primary advantage of satellite data compared to in situ measurements, e.g., from air quality monitoring stations, is their spatial coverage. Satellite data can reveal where pollution levels are highest around the world, how levels have changed over daily to decadal periods, and where pollutants are transported from urban to global scales. To date, air quality and health applications have primarily utilized satellite observations and satellite-derived products relevant to near-surface particulate matter <2.5 μm in diameter (PM_2.5) and nitrogen dioxide (NO₂). Health and air quality communities have grown increasingly engaged in the use of satellite data, and this trend is expected to continue. From health researchers to air quality managers, and from global applications to community impacts, satellite data are transforming the way air pollution exposure is evaluated.

Fine particulate matter (PM_2.5) is a well-established risk factor for public health. To support both health risk assessment and epidemiological studies, data are needed on spatial and temporal patterns of PM_2.5 exposures. This review article surveys publicly available exposure datasets for surface PM_2.5 mass concentrations over the contiguous U.S., summarizes their applications and limitations, and provides suggestions on future research needs. The complex landscape of satellite instruments, model capabilities, monitor networks, and data synthesis methods offers opportunities for research development, but would benefit from guidance for new users. Guidance is provided to access publicly available PM_2.5 datasets, to explain and compare different approaches for dataset generation, and to identify sources of uncertainties associated with various types of datasets. Three main sources used to create PM_2.5 exposure data are ground-based measurements (especially regulatory monitoring), satellite retrievals (especially aerosol optical depth, AOD), and atmospheric chemistry models. We find inconsistencies among several publicly available PM_2.5 estimates, highlighting uncertainties in the exposure datasets that are often overlooked in health effects analyses. Major differences among PM_2.5 estimates emerge from the choice of data (ground-based, satellite, and/or model), the spatiotemporal resolutions, and the algorithms used to fuse data sources. Implications: Fine particulate matter (PM_2.5) has large impacts on human morbidity and mortality. Even though the methods for generating the PM_2.5 exposure estimates have been significantly improved in recent years, there is a lack of review articles that document PM_2.5 exposure datasets that are publicly available and easily accessible by the health and air quality communities. In this article, we discuss the main methods that generate PM_2.5 data, compare several publicly available datasets, and show the applications of various data fusion approaches. Guidance to access and critique these datasets are provided for stakeholders in public health sectors.

▪ Abstract Energy and energy technologies have a central role in social and economic development at all scales, from household and community to regional and national. Among its welfare effects, energy is closely linked with public health both positively and negatively, the latter through environmental pollution and degradation. We review the current research on how energy use and energy technologies influence public health, emphasizing the risks associated with indoor and ambient air pollution from energy use, and the links between the local and global environmental health impacts of energy use. This review illustrates that, despite their large public health implications, most energy policies and programs in the developing world are fundamentally treated as components of overall economic development, without explicit assessment of their health benefits or hazards. Closer integration of health in energy management can facilitate the development of policies and programs that increase welfare and minimize negative health outcomes. Renewable energy technologies are used as an example of how an integrated energy-health approach can be used in policy analysis and formulation.