Why particles?

Revisiting the atmospheric particles: Connecting lines and changing paradigms

Historically, the atmospheric particles constitute the most primitive and recent class of air pollutants. The science of atmospheric particles erupted more than a century ago covering more than four decades of size, with past few years experiencing major advancements on both theoretic and data-based observational grounds. More recently, the plausible recognition between particulate matter (PM) and the diffusion of the COVID-19 pandemic has led to the accretion of interest in particle science. With motivation from diverse particle research interests, this paper is an 'old engineer's survey' beginning with the evolution of atmospheric particles and identifies along the way many of the global instances signaling the 'size concept' of PM. A theme that runs through the narrative is a 'previously known' generational evolution of particle science to the 'newly procured' portfolio of knowledge, with important gains on the application of unmet concepts and future approaches to PM exposure and epidemiological research.

External costs of PM2.5 pollution in Beijing, China: Uncertainty analysis of multiple health impacts and costs

Some cities in China are facing serious air pollution problems including high concentrations of particles, SO₂ and NO_x. Exposure to PM2.5, one of the primary air pollutants in many cities in China, is highly correlated with various adverse health impacts and ultimately represents a cost for society. The aim of this study is to assess health impacts and external costs related to PM2.5 pollution in Beijing, China with different baseline concentrations and valuation methods. The idea is to provide a reasonable estimate of the total health impacts and external cost due to PM2.5 pollution, as well as a quantification of the relevant uncertainty. PM2.5 concentrations were retrieved for the entire 2012 period in 16 districts of Beijing. The various PM2.5 related health impacts were identified and classified to avoid double counting. Exposure-response coefficients were then obtained from literature. Both the value of statistical life (VSL) and the amended human capital (AHC) approach were applied for external costs estimation, which could provide the upper and lower bound of the external costs due to PM2.5. To fully understand the uncertainty levels, the external cost distribution was determined via Monte Carlo simulation based on the uncertainty of the parameters such as PM2.5 concentration, exposure-response coefficients, and economic cost per case. The results showed that the external costs were equivalent to around 0.3% (AHC, China's guideline: C₀ = 35 μg/m³) to 0.9% (VSL, WHO guideline: C₀ = 10 μg/m³) of regional GDP depending on the valuation method and on the assumed baseline PM2.5 concentration (C₀). Among all the health impacts, the economic loss due to premature deaths accounted for more than 80% of the overall external costs. The results of this study could help policymakers prioritizing the PM2.5 pollution control interventions and internalize the external costs through the application of economic policy instruments.

Air quality impacts of climate mitigation: UK policy and passenger vehicle choice

In 2001-2002 the UK began taxing vehicles according to CO2 emission rates. Since then, there has been a significant increase in consumer choice of small cars and diesel engines. We estimate CO2 reductions and air quality impacts resulting from UK consumers switching from petrol to diesel cars from 2001 to 2020. Annual reductions of 0.4 megatons (Mt) of CO2 and 1 million barrels of oil are estimated from switching to diesels. However, diesels emit higher levels of particulate matter estimated to result in 90 deaths annually (range 20-300). We estimate 570, 460, and 0 additional deaths per Mt of CO2 abated, for Euro III, Euro IV, and post-Euro IV emission class vehicles, respectively. CO2 policies are suspected to have contributed substantially to diesel growth, but the magnitude of impact has yet to be quantified rigorously. To the extent that CO2 policies contribute to diesel growth, coordinating CO2 controls with tightening of emission standards would save lives. This research shows that climate policy, while reducing fuel use and CO2, does not always ensure ancillary health benefits. Lessons from the UK can help inform policies designed elsewhere which strive to balance near-term ambient air quality and health with long-term climate mitigation.

Estimating ground-level PM2.5 in the eastern United States using satellite remote sensing

An empirical model based on the regression between daily PM2.5 (particles with aerodynamic diameters of less than 2.5 microm) concentrations and aerosol optical thickness (AOT) measurements from the multiangle imaging spectroradiometer (MISR) was developed and tested using data from the eastern United States during the period of 2001. Overall, the empirical model explained 48% of the variability in PM2.5 concentrations. The root-mean-square error of the model was 6.2 microg/m3 with a corresponding average PM2.5 concentration of 13.8 microg/m3. When PM2.5 concentrations greater than 40 microg/m3 were removed, model results were shown to be unbiased estimators of observations. Several factors, such as planetary boundary layer height, relative humidity, season, and other geographical attributes of monitoring sites, were found to influence the association between PM2.5 and AOT. The findings of this study illustrate the strong potential of satellite remote sensing in regional ambient air quality monitoring as an extension to ground networks. With the continual advancement of remote sensing technology and global data assimilation systems, AOT measurements derived from satellite remote sensors may provide a cost-effective approach as a supplemental source of information for determining ground-level particle concentrations.