The partitioning of available energy into surface sensible and latent heat fluxes impacts the accuracy of simulated near surface temperature and humidity in numerical weather prediction models. This case study evaluates the performance of the Weather Research and Forecasting (WRF) model on the simulation of surface heat fluxes using field observations collected from a surface flux tower in Oregon, USA. Further, WRF-modeled heat flux sensitivities to North American Mesoscale (NAM) and North American Regional Reanalysis (NARR) large-scale input forcing datasets; U.S. Geological Survey (USGS) and the Moderate Resolution Imaging Spectroradiometer (MODIS) land use datasets; Pleim-Xiu (PX) and Noah land surface models (LSM); Yonsei University (YSU) and Mellor-Yamada-Janjic (MYJ) planetary boundary layer (PBL) schemes using the Noah LSM; and Asymmetric Convective Model version 2 (ACM2) PBL scheme using PX LSM are investigated. The errors for simulating 2-m temperature, 2-m humidity, and 10-m wind speed were reduced on average when using NAM compared with NARR. Simulated friction velocity had a positive bias on average, with the YSU PBL scheme producing the largest overestimation in the innermost domain (0.5 km horizontal grid resolution). The simulated surface sensible heat flux had a similar temporal behavior as the observations but with a larger magnitude. The PX LSM produced lower and more reliable sensible heat fluxes compared with the Noah LSM. However, Noah latent heat fluxes were improved with a lower RMSE compared to PX, when NARR forcing data was used. Overall, these results suggest that there is not one WRF configuration that performs best for all the simulated variables (surface heat fluxes and meteorological variables) and situations (day and night).

We developed a hybrid chemical transport model and receptor model (CTM-RM) to conduct source apportionment of both primary and secondary PM2.5 (particulate matter ≤2.5 μm in diameter) at 36 km resolution throughout the U.S. State of Georgia for the years 2005 and 2007. This novel source apportionment model enabled us to estimate and compare associations of short-term changes in 12 PM2.5 source concentrations (agriculture, biogenic, coal, dust, fuel oil, metals, natural gas, non-road mobile diesel, non-road mobile gasoline, on-road mobile diesel, on-road mobile gasoline, and all other sources) with emergency department (ED) visits for pediatric respiratory diseases. ED visits for asthma (N = 49,651), pneumonia (N = 25,558), and acute upper respiratory infections (acute URI, N = 235,343) among patients aged ≤18 years were obtained from patient claims records. Using a case-crossover study, we estimated odds ratios per interquartile range (IQR) increase for 3-day moving average PM2.5 source concentrations using conditional logistic regression, matching on day-of-week, month, and year, and adjusting for average temperature, humidity, and holidays. We fit both single-source and multi-source models. We observed positive associations between several PM2.5 sources and ED visits for asthma, pneumonia, and acute URI. For example, for asthma, per IQR increase in the source contribution in the single-source model, odds ratios were 1.022 (95% CI: 1.013, 1.031) for dust; 1.050 (95% CI: 1.036, 1.063) for metals, and 1.091 (95% CI: 1.064, 1.119) for natural gas. These sources comprised 5.7%, 2.2%, and 6.3% of total PM2.5 mass, respectively. PM2.5 from metals and natural gas were positively associated with all three respiratory outcomes. In addition, non-road mobile diesel was positively associated with pneumonia and acute URI.

The use of solid biomass fuels in cookstoves has been associated with chronic health impacts that disproportionately affect women worldwide. Solid fuel stoves that use wood, plant matter, and cow dung are commonly used for household cooking in rural Bangladesh. This study investigates the immediate effects of acute elevated cookstove emission exposures on pulmonary function. Pulmonary function was measured with spirometry before and during cooking to assess changes in respiratory function during exposure to cookstove emissions for 15 females ages 18–65. Cookstove emissions were characterized using continuous measurements of particulate matter (PM_2.5—aerodynamic diameter <2.5 μm) concentrations at a 1 s time resolution for each household. Several case studies were observed where women ≥40 years who had been cooking for ≥25 years suffered from severe pulmonary impairment. Forced expiratory volume in one second over forced vital capacity (FEV1/FVC) was found to moderately decline (p = 0.06) during cooking versus non-cooking in the study cohort. The study found a significant (α < 0.05) negative association between 3- and 10-min maximum PM_2.5 emissions during cooking and lung function measurements of forced vital capacity (FVC), forced expiratory volume in one second (FEV1), and FEV1/FVC obtained during cooking intervals. This study found that exposure to biomass burning emissions from solid fuel stoves- associated with acute elevated PM_2.5 concentrations- leads to a decrease in pulmonary function, although further research is needed to ascertain the prolonged (e.g., daily, for multiple years) impacts of acute PM_2.5 exposure on immediate and sustained respiratory impairment.

Bright surfaces across the western U.S. lead to uncertainties in satellite derived aerosol optical depth (AOD) where AOD is typically overestimated. With this in mind, a compact and portable instrument was developed to measure surface albedo on an unmanned aircraft system (UAS). This spectral albedometer uses two Hamamatsu micro-spectrometers (range: 340–780 nm) for measuring incident and reflected solar radiation at the surface. The instrument was deployed on 5 October 2017 in Nevada’s Black Rock Desert (BRD) to investigate a region of known high surface reflectance for comparison with albedo products from satellites. It was found that satellite retrievals underestimate surface reflectance compared to the UAS mounted albedometer. To highlight the importance of surface reflectance on the AOD from satellite retrieval algorithms, a 1-D radiative transfer model was used. The simple model was used to determine the sensitivity of AOD with respect to the change in albedo and indicates a large sensitivity of AOD retrievals to surface reflectance for certain combinations of surface albedo and aerosol optical properties. This demonstrates the need to increase the number of surface albedo measurements and an intensive evaluation of albedo satellite retrievals to improve satellite-derived AOD. The portable instrument is suitable for other applications as well.

This paper reports findings from a case study designed to investigate indoor and outdoor air quality in homes near the United States–Mexico border. During the field study, size-resolved continuous particulate matter (PM) concentrations were measured in six homes, while outdoor PM was simultaneously monitored at the same location in Nogales, Sonora, Mexico, during March 14–30, 2009. The purpose of the experiment was to compare PM in homes using different fuels for cooking, gas versus biomass, and to obtain a spatial distribution of outdoor PM in a region where local sources vary significantly (e.g., highway, border crossing, unpaved roads, industry). Continuous PM data were collected every 6 seconds using a valve switching system to sample indoor and outdoor air at each home location. This paper presents the indoor PM data from each home, including the relationship between indoor and outdoor PM. The meteorological conditions associated with elevated ambient PM events in the region are also discussed. Results indicate that indoor air pollution has a strong dependence on cooking fuel, with gas stoves having hourly averaged median PM₃ concentrations in the range of 134 to 157 μg m⁻³ and biomass stoves 163 to 504 μg m⁻³. Outdoor PM also indicates a large spatial heterogeneity due to the presence of microscale sources and meteorological influences (median PM₃: 130 to 770 μg m⁻³). The former is evident in the median and range of daytime PM values (median PM₃: 250 μg m⁻³, maximum: 9411 μg m⁻³), while the meteorological influences appear to be dominant during nighttime periods (median PM₃: 251 μg m⁻³, maximum: 10,846 μg m⁻³). The atmospheric stability is quantified for three nighttime temperature inversion episodes, which were associated with an order of magnitude increase in PM10 at the regulatory monitor in Nogales, AZ (maximum increase: 12 to 474 μg m⁻³).