A causal machine-learning framework for studying policy impact on air pollution: A case-study in COVID-19 lockdowns.

When studying the impact of policy interventions or natural experiments on air pollution, such as new environmental policies and opening or closing an industrial facility, careful statistical analysis is needed to separate causal changes from other confounding factors. Using COVID-19 lockdowns as a case-study, we present a comprehensive framework for estimating and validating causal changes from such perturbations. We propose using flexible machine learning-based comparative interrupted time series (CITS) models for estimating such a causal effect.

The Association Between Personal Air Pollution Exposures and Fractional Exhaled Nitric Oxide (FeNO): A Systematic Review.

Purpose Of Review: Airway inflammation is a common biological response to many types of environmental exposures and can lead to increased nitric oxide (NO) concentrations in exhaled breath. In recent years, several studies have evaluated airway inflammation using fractional exhaled nitric oxide (FeNO) as a biomarker of exposures to a range of air pollutants. This systematic review aims to summarize the studies that collected personal-level air pollution data to assess the air pollution-induced FeNO responses and to determine if utilizing personal-level data resulted in an improved characterization of the relationship between air pollution exposures and FeNO compared to using only ambient air pollution exposure data.

Evaluation of Calibration Approaches for Indoor Deployments of PurpleAir Monitors.

Low-cost air quality monitors are growing in popularity among both researchers and community members to understand variability in pollutant concentrations. Several studies have produced calibration approaches for these sensors for ambient air. These calibrations have been shown to depend primarily on relative humidity, particle size distribution, and particle composition, which may be different in indoor environments.

Identifying optimal co-location calibration periods for low-cost sensors.

Low-cost sensors are often co-located with reference instruments to assess their performance and establish calibration equations, but limited discussion has focused on whether the duration of this calibration period can be optimized. We placed a multipollutant monitor that contained sensors that measure particulate matter smaller than 2.5 μm (PM), carbon monoxide (CO), nitrogen dioxide (NO), ozone (O), and nitric oxide (NO) at a reference field site for one year.

Laboratory and field evaluation of a low-cost methane sensor and key environmental factors for sensor calibration.

Low-cost sensors enable finer-scale spatiotemporal measurements within the existing methane (CH) monitoring infrastructure and could help cities mitigate CH emissions to meet their climate goals. While initial studies of low-cost CH sensors have shown potential for effective CH measurement at ambient concentrations, sensor deployment remains limited due to questions about interferences and calibration across environments and seasons. This study evaluates sensor performance across seasons with specific attention paid to the sensor's understudied carbon monoxide (CO) interferences and environmental dependencies through long-term ambient co-location in an urban environment.

Non-linear probabilistic calibration of low-cost environmental air pollution sensor networks for neighborhood level spatiotemporal exposure assessment.

Background: Low-cost sensor networks for monitoring air pollution are an effective tool for expanding spatial resolution beyond the capabilities of existing state and federal reference monitoring stations. However, low-cost sensor data commonly exhibit non-linear biases with respect to environmental conditions that cannot be captured by linear models, therefore requiring extensive lab calibration. Further, these calibration models traditionally produce point estimates or uniform variance predictions which limits their downstream in exposure assessment.

Evaluating the Performance of Using Low-Cost Sensors to Calibrate for Cross-Sensitivities in a Multipollutant Network.

As part of our low-cost sensor network, we colocated multipollutant monitors containing sensors for particulate matter, carbon monoxide, ozone, nitrogen dioxide, and nitrogen monoxide at a reference field site in Baltimore, MD, for 1 year. The first 6 months were used for training multiple regression models, and the second 6 months were used to evaluate the models. The models produced accurate hourly concentrations for all sensors except ozone, which likely requires nonlinear methods to capture peak summer concentrations.

Maternal exposure to polycyclic aromatic hydrocarbons in South Texas, evaluation of silicone wristbands as personal passive samplers.

Background: Prenatal exposure to polycyclic aromatic hydrocarbons (PAHs) is associated with adverse health effects in children. Valid exposure assessment methods with accurate spatial and temporal resolution across pregnancy is a critical need for advancing environmental health studies.

Objective: The objective of this study was to quantify maternal PAH exposure in pregnant women residing in McAllen, Texas where the prematurity rate and childhood asthma prevalence rates are high.

Stationary and portable multipollutant monitors for high-spatiotemporal-resolution air quality studies including online calibration.

The distribution and dynamics of atmospheric pollutants are spatiotemporally heterogeneous due to variability in emissions, transport, chemistry, and deposition. To understand these processes at high spatiotemporal resolution and their implications for air quality and personal exposure, we present custom, low-cost air quality monitors that measure concentrations of contaminants relevant to human health and climate, including gases (e.g.

Statistical field calibration of a low-cost PM monitoring network in Baltimore.

Low-cost air pollution monitors are increasingly being deployed to enrich knowledge about ambient air-pollution at high spatial and temporal resolutions. However, unlike regulatory-grade (FEM or FRM) instruments, universal quality standards for low-cost sensors are yet to be established and their data quality varies widely. This mandates thorough evaluation and calibration before any responsible use of such data.

One Year Evaluation of Three Low-Cost PM Monitors.

The availability of low-cost monitors marketed for use in homes has increased rapidly over the past few years due to the advancement of sensing technologies, increased awareness of urban pollution, and the rise of citizen science. The user-friendly packages can make them appealing for use in research grade indoor exposure assessments, but a rigorous scientific evaluation has not been conducted for many monitors on the open market, which leads to uncertainty about the validity of the data. Furthermore, many previous sensor studies were conducted for a relatively short period of time, which may not capture the changes this type of instrument may exhibit over time (known as sensor aging).

Remarkable nucleation and growth of ultrafine particles from vehicular exhaust.

High levels of ultrafine particles (UFPs; diameter of less than 50 nm) are frequently produced from new particle formation under urban conditions, with profound implications on human health, weather, and climate. However, the fundamental mechanisms of new particle formation remain elusive, and few experimental studies have realistically replicated the relevant atmospheric conditions. Previous experimental studies simulated oxidation of one compound or a mixture of a few compounds, and extrapolation of the laboratory results to chemically complex air was uncertain.

Adverse organogenesis and predisposed long-term metabolic syndrome from prenatal exposure to fine particulate matter.

Exposure to fine particulate matter (PM) during pregnancy is associated with high risks of birth defects/fatality and adverse long-term postnatal health. However, limited mechanistic data are available to assess the detailed impacts of prenatal PM exposure. Here we evaluate fine PM exposure during pregnancy on prenatal/postnatal organogenesis in offspring and in predisposing metabolic syndrome for adult life.

In utero ultrafine particulate matter exposure causes offspring pulmonary immunosuppression.

Early life exposure to fine particulate matter (PM) in air is associated with infant respiratory disease and childhood asthma, but limited epidemiological data exist concerning the impacts of ultrafine particles (UFPs) on the etiology of childhood respiratory disease. Specifically, the role of UFPs in amplifying Th2- and/or Th17-driven inflammation (asthma promotion) or suppressing effector T cells (increased susceptibility to respiratory infection) remains unclear. Using a mouse model of in utero UFP exposure, we determined early immunological responses to house dust mite (HDM) allergen in offspring challenged from 0 to 4 wk of age.

Formation and Optical Properties of Brown Carbon from Small α-Dicarbonyls and Amines.

Brown Carbon (BrC) aerosols scatter and absorb solar radiation, directly affecting the Earth's radiative budget. However, considerable uncertainty exists concerning the chemical mechanism leading to BrC formation and their optical properties. In this work, BrC particles were prepared from mixtures of small α-dicarbonyls (glyoxal and methylglyoxal) and amines (methylamine, dimethylamine, and trimethylamine).

OH-Initiated Oxidation of m-Xylene on Black Carbon Aging.

Laboratory experiments are conducted to investigate aging of size-classified black carbon (BC) particles from OH-initiated oxidation of m-xylene. The variations in the particle size, mass, effective density, morphology, optical properties, hygroscopicity, and activation as cloud condensation nuclei (CCN) are simultaneously measured by a suite of aerosol instruments, when BC particles are exposed to the oxidation products of the OH-m-xylene reactions. The BC aging is governed by the coating thickness (Δrve), which is correlated to the reaction time and initial concentrations of m-xylene and NOx.

Elucidating severe urban haze formation in China.

As the world's second largest economy, China has experienced severe haze pollution, with fine particulate matter (PM) recently reaching unprecedentedly high levels across many cities, and an understanding of the PM formation mechanism is critical in the development of efficient mediation policies to minimize its regional to global impacts. We demonstrate a periodic cycle of PM episodes in Beijing that is governed by meteorological conditions and characterized by two distinct aerosol formation processes of nucleation and growth, but with a small contribution from primary emissions and regional transport of particles. Nucleation consistently precedes a polluted period, producing a high number concentration of nano-sized particles under clean conditions.