No abstract

Emissions from solid-fuel cookstoves have been linked to indoor and outdoor air pollution, climate forcing, and human disease. Although task-based laboratory protocols, such as the Water Boiling Test (WBT), overestimate the ability of improved stoves to lower emissions, WBT emissions data are commonly used to benchmark cookstove performance, estimate indoor and outdoor air pollution concentrations, estimate impacts of stove intervention projects, and select stoves for large-scale control trials. Multiple-firepower testing has been proposed as an alternative to the WBT and is the basis for a new standardized protocol (ISO 19867-1:2018); however, data are needed to assess the value of this approach. In this work, we (a) developed a Firepower Sweep Test [FST], (b) compared emissions from the FST, WBT, and in-home cooking, and (c) quantified the relationship between firepower and emissions using correlation analysis and linear model selection. Twenty-three stove-fuel combinations were evaluated. The FST reproduced the range of PM and CO emissions observed in the field, including high emissions events not typically observed under the WBT. Firepower was modestly correlated with emissions, although the relationship varied between stove-fuel combinations. Our results justify incorporating multiple-firepower testing into laboratory-based protocols but demonstrate that firepower alone cannot explain the observed variability in cookstove emissions.

COVID-19-related closures offered a novel opportunity to observe and quantify the impact of activity levels of modifiable factors on ambient air pollution in real time. We use data from a network of low-cost Real-time Affordable Multi-Pollutant (RAMP) sensor packages deployed throughout Pittsburgh, Pennsylvania, along with data from Environmental Protection Agency regulatory monitors. The RAMP locations were divided into four site groups based on land use. Concentrations of PM2.5, CO, and NO2 following the COVID-related closures at each site group were compared to measurements from “business-as-usual” periods. Overall, PM2.5 concentrations decreased across the domain by ∼3 μg/m3. The morning rush-hour-induced CO and NO2 concentrations at the high-traffic sites were both reduced by ∼50%, which is consistent with observed reductions in commuter traffic (∼50%). The morning rush-hour PM2.5 enhancement from traffic emissions was reduced nearly 100%, from 1.4 to ∼0 μg/m3 across all site groups. There was no significant change in the industry-related intraday variability of CO and PM2.5 at the industrial sites following the COVID-related closures. If PM2.5 National Ambient Air Quality Standards (NAAQS) are tightened, this natural experiment sheds light on the extent to which reductions in traffic-related emissions can aid in meeting more stringent regulations.

Low-cost NO 2 sensors have been widely deployed for atmospheric sampling. While their initial performance has been characterized, few studies have examined their long-term degradation. This study focused on the performance of Alphasense low-cost NO 2 sensors (NO2-B42F and NO2-B43F) over 4 years (2016−2020). A total of 29 NO 2 sensors from 10 batches were collocated 78 times at two sites with reference instruments. Raw signals from "functional" NO 2 sensors correlated linearly with reference NO 2 concentrations. After long-term deployment, sensor raw signals started to deviate from reference NO 2 concentrations due to sensor aging, an accumulated effect after sensor unpacking. Several sensors eventually became "non-functional" as sensor raw signals showed no correlation with reference NO 2 concentrations. Sensor aging and non-functionality may be primarily caused by expiration of the ozone (O 3 ) scrubber built into these sensors so that sensors responded to both ambient NO 2 and O 3 . The influence of O 3 on sensor response is quantified through the permutation importance method. Most of the sensors are non-functional after approximately 200−400 days of deployment, and no sensor was functional after 400 days of deployment. This result agrees well with the estimated lifetime of the built-in ozone scrubbers considering the ambient ozone concentration in the Pittsburgh area where these sensors were deployed. To ensure reliable data quality in long-term field deployments, we recommend collocating NO 2 sensors with reference instruments regularly after 200−400 days of deployment to identify and replace non-functional sensors in a timely manner.

Modifiable sources of air pollution such as traffic, cooking, and electricity generation emissions can be modulated either by changing activity levels or source intensity. Although air pollution regulations typically target reducing emission factors rather than altering activity, the COVID-19 related closures offered a novel opportunity to observe and quantify the impact of activity levels of modifiable factors on ambient air pollution in real-time. We use data from a network of twenty-seven low-cost Real-time Affordable Multi-Pollutant (RAMP) sensor packages deployed throughout urban and suburban Pittsburgh along with data from EPA regulatory monitors. The RAMP locations were divided into four site groups based on land use (High Traffic, Urban Residential, Suburban Residential, and Industrial). Concentrations of PM2.5, CO, and NO2 following the COVID-related closures at each site group were compared to measurements from “business as usual” periods in March 2019 and 2020. Overall, PM2.5 concentrations decreased across the domain by 3 μg/m3. Intra-day variabilities of the pollutants were computed to attribute pollutant enhancements to specific emission sources (i.e. traffic and industrial emissions). There was no significant change in the industrial related intra-day variability of PM2.5 at the Industrial sites following the COVID-related closures. The morning rush hour induced CO and NO2 concentrations at the High Traffic sites were reduced by 57% and 43%, respectively, which is consistent with the observed reduction in commuter traffic (~50%). The morning rush hour PM2.5 enhancement from traffic emissions fell from ~1.5 μg/m3 to ~0 μg/m3 across all site groups. This translates to a reduction of 0.125 μg/m3 in the daily average PM2.5 concentration. If PM2.5 National Ambient Air Quality Standards (NAAQS) are tightened these calculations shed light on to what extent reductions in traffic related emissions are able to aid in meeting more stringent regulations.