Comparison of Mobile and Fixed-Site Black Carbon Measurements for High-Resolution Urban Pollution Mapping.

Urban concentrations of black carbon (BC) and other primary pollutants vary on small spatial scales (<100m). Mobile air pollution measurements can provide information on fine-scale spatial variation, thereby informing exposure assessment and mitigation efforts. However, the temporal sparsity of these measurements presents a challenge for estimating representative long-term concentrations. We evaluate the capabilities of mobile monitoring in the represention of time-stable spatial patterns by comparing against a large set of continuous fixed-site measurements from a sampling campaign in West Oakland, California. Custom-built, low-cost aerosol black carbon detectors (ABCDs) provided 100 days of continuous measurements at 97 near-road and 3 background fixed sites during summer 2017; two concurrently operated mobile laboratories collected over 300 h of in-motion measurements using a photoacoustic extinctiometer. The spatial coverage from mobile monitoring reveals patterns missed by the fixed-site network. Time-integrated measurements from mobile lab visits to fixed-site monitors reveal modest correlation (spatial R2 = 0.51) with medians of full daytime fixed-site measurements. Aggregation of mobile monitoring data in space and time can mitigate high levels of uncertainty associated with measurements at precise locations or points in time. However, concentrations estimated by mobile monitoring show a loss of spatial fidelity at spatial aggregations greater than 100 m.

A Distributed Network of 100 Black Carbon Sensors for 100 Days of Air Quality Monitoring in West Oakland, California.

Ambient particulate matter (PM) pollution is a major environmental health risk in urban areas. Dense networks of low-cost air quality sensors are emerging to characterize the spatially heterogeneous concentrations that are typical of urban settings, but are not adequately captured using traditional regulatory monitors at central sites. In this study, we present the 100×100 BC Network, a 100-day deployment of low-cost black carbon (BC) sensors across 100 locations in West Oakland, California. This 15 km2 community is surrounded by freeways and affected by emissions associated with local port and industrial activities. We assess the reliability of the sensor hardware and data collection systems, and identify modes of failure to both quantify and qualify network performance. We illustrate how dynamic, local emission sources build upon background BC concentrations. BC concentrations varied sharply over short distances (∼100 m) and timespans (∼1 hour), depending on surrounding land use, traffic patterns, and downwind distance from pollution sources. Strong BC concentration fluctuations were periodically observed over the diurnal and weekly cycles, reflecting the impact of localized traffic emissions and industrial facilities in the neighborhood. Overall, the results demonstrate how distributed sensor networks can reveal the complex spatiotemporal dynamics of combustion-related air pollution within urban neighborhoods.

Optimization of Secondary Air Injection in a Wood-Burning Cookstove: An Experimental Study.

Nearly 40% of the world's population regularly cooks on inefficient biomass stoves that emit harmful airborne pollutants, such as particulate matter (PM). Secondary air injection can significantly reduce PM mass emissions to mitigate the health and climate impacts associated with biomass cookstoves. However, secondary air injection can also increase the number of ultrafine particles emitted, which may be more harmful to health. This research investigates the effect of secondary air injection on the mass and size distribution of PM emitted during solid biomass combustion. An experimental wood-burning cookstove platform and parametric testing approach are presented to identify and optimize secondary air injection parameters that reduce PM and other harmful pollutants. Size-resolved measurements of PM emissions were collected and analyzed as a function of parametric stove design settings. The results show that PM emissions are highly sensitive to secondary air injection flow rate and velocity. Although increasing turbulent mixing (through increased velocity) can promote more complete combustion, increasing the total flow rate of secondary air may cause localized flame quenching that increases particle emissions. Therefore, biomass cookstoves that implement secondary air injection should be carefully optimized and validated to ensure that PM emission reductions are achieved throughout the particle size range.

A New Black Carbon Sensor for Dense Air Quality Monitoring Networks.

Low-cost air pollution sensors are emerging and increasingly being deployed in densely distributed wireless networks that provide more spatial resolution than is typical in traditional monitoring of ambient air quality. However, a low-cost option to measure black carbon (BC)-a major component of particulate matter pollution associated with adverse human health risks-is missing. This paper presents a new BC sensor designed to fill this gap, the Aerosol Black Carbon Detector (ABCD), which incorporates a compact weatherproof enclosure, solar-powered rechargeable battery, and cellular communication to enable long-term, remote operation. This paper also demonstrates a data processing methodology that reduces the ABCD's sensitivity to ambient temperature fluctuations, and therefore improves measurement performance in unconditioned operating environments (e.g., outdoors). A fleet of over 100 ABCDs was operated outdoors in collocation with a commercial BC instrument (Magee Scientific, Model AE33) housed inside a regulatory air quality monitoring station. The measurement performance of the 105 ABCDs is comparable to the AE33. The fleet-average precision and accuracy, expressed in terms of mean absolute percentage error, are 9.2 ± 0.8% (relative to the fleet average data) and 24.6 ± 0.9% (relative to the AE33 data), respectively (fleet-average ± 90% confidence interval).

Reducing Ultrafine Particle Emissions Using Air Injection in Wood-Burning Cookstoves.

In order to address the health risks and climate impacts associated with pollution from cooking on biomass fires, researchers have focused on designing new cookstoves that improve cooking performance and reduce harmful emissions, specifically particulate matter (PM). One method for improving cooking performance and reducing emissions is using air injection to increase turbulence of unburned gases in the combustion zone. Although air injection reduces total PM mass emissions, the effect on PM size distribution and number concentration has not been thoroughly investigated. Using two new wood-burning cookstove designs from Lawrence Berkeley National Laboratory, this research explores the effect of air injection on cooking performance, PM and gaseous emissions, and PM size distribution and number concentration. Both cookstoves were created using the Berkeley-Darfur Stove as the base platform to isolate the effects of air injection. The thermal performance, gaseous emissions, PM mass emissions, and particle concentrations (ranging from 5 nm to 10 µm in diameter) of the cookstoves were measured during multiple high-power cooking tests. The results indicate that air injection improves cookstove performance and reduces total PM mass but increases total ultrafine (less than 100 nm in diameter) PM concentration over the course of high-power cooking.