Composition and secondary formation of fine particulate matter in the Salt Lake Valley: Winter 2009

Under the National Ambient Air Quality Standards (NAAQS), put in place as a result of the Clean Air Amendments of 1990, three regions in the state of Utah are in violation of the NAAQS for PM₁₀ and PM_2.5 (Salt Lake County, Ogden City, and Utah County). These regions are susceptible to strong inversions that can persist for days to weeks. This meteorology, coupled with the metropolitan nature of these regions, contributes to its violation of the NAAQS for PM during the winter. During January–February 2009, 1-hr averaged concentrations of PM_10-2.5, PM_2.5, NO_x, NO₂, NO, O₃, CO, and NH₃ were measured. Particulate-phase nitrate, nitrite, and sulfate and gas-phase HONO, HNO₃, and SO₂ were also measured on a 1-hr average basis. The results indicate that ammonium nitrate averages 40% of the total PM_2.5 mass in the absence of inversions and up to 69% during strong inversions. Also, the formation of ammonium nitrate is nitric acid limited. Overall, the lower boundary layer in the Salt Lake Valley appears to be oxidant and volatile organic carbon (VOC) limited with respect to ozone formation. The most effective way to reduce ammonium nitrate secondary particle formation during the inversions period is to reduce NO_x emissions. However, a decrease in NO_x will increase ozone concentrations. A better definition of the complete ozone isopleths would better inform this decision.

Implications: Monitoring of air pollution constituents in Salt Lake City, UT, during periods in which PM_2.5 concentrations exceeded the NAAQS, reveals that secondary aerosol formation for this region is NO_x limited. Therefore, NO_x emissions should be targeted in order to reduce secondary particle formation and PM_2.5. Data also indicate that the highest concentrations of sulfur dioxide are associated with winds from the north-northwest, the location of several small refineries.     

Forecasting of particulate matter time series using wavelet analysis and wavelet-ARMA/ARIMA model in Taiyuan,China

Particulate matter with aerodynamic diameter below 10 μm (PM₁₀) forecasting is difficult because of the uncertainties in describing the emission and meteorological fields. This paper proposed a wavelet-ARMA/ARIMA model to forecast the short-term series of the PM₁₀ concentrations. It was evaluated by experiments using a 10-year data set of daily PM₁₀ concentrations from 4 stations located in Taiyuan, China. The results indicated the following: (1) PM₁₀ concentrations of Taiyuan had a decreasing trend during 2005 to 2012 but increased in 2013. PM₁₀ concentrations had an obvious seasonal fluctuation related to coal-fired heating in winter and early spring. (2) Spatial differences among the four stations showed that the PM₁₀ concentrations in industrial and heavily trafficked areas were higher than those in residential and suburb areas. (3) Wavelet analysis revealed that the trend variation and the changes of the PM₁₀ concentration of Taiyuan were complicated. (4) The proposed wavelet-ARIMA model could be efficiently and successfully applied to the PM₁₀ forecasting field. Compared with the traditional ARMA/ARIMA methods, this wavelet-ARMA/ARIMA method could effectively reduce the forecasting error, improve the prediction accuracy, and realize multiple-time-scale prediction.

Implications: Wavelet analysis can filter noisy signals and identify the variation trend and the fluctuation of the PM₁₀ time-series data. Wavelet decomposition and reconstruction reduce the nonstationarity of the PM₁₀ time-series data, and thus improve the accuracy of the prediction. This paper proposed a wavelet-ARMA/ARIMA model to forecast the PM₁₀ time series. Compared with the traditional ARMA/ARIMA method, this wavelet-ARMA/ARIMA method could effectively reduce the forecasting error, improve the prediction accuracy, and realize multiple-time-scale prediction. The proposed model could be efficiently and successfully applied to the PM₁₀ forecasting field.     

Analysis of short-term ozone and PM2.5 measurements: Characteristics and relationships for air sensor messaging

Air quality sensors are becoming increasingly available to the general public, providing individuals and communities with information on fine-scale, local air quality in increments as short as 1 min. Current health studies do not support linking 1-min exposures to adverse health effects; therefore, the potential health implications of such ambient exposures are unclear. The U.S. Environmental Protection Agency (EPA) establishes the National Ambient Air Quality Standards (NAAQS) and Air Quality Index (AQI) on the best science available, which typically uses longer averaging periods (e.g., 8 hr; 24 hr). Another consideration for interpreting sensor data is the variable relationship between pollutant concentrations measured by sensors, which are short-term (1 min to 1 hr), and the longer term averages used in the NAAQS and AQI. In addition, sensors often do not meet federal performance or quality assurance requirements, which introduces uncertainty in the accuracy and interpretation of these readings. This article describes a statistical analysis of data from regulatory monitors and new real-time technology from Village Green benches to inform the interpretation and communication of short-term air sensor data. We investigate the characteristics of this novel data set and the temporal relationships of short-term concentrations to 8-hr average (ozone) and 24-hr average (PM_2.5) concentrations to examine how sensor readings may relate to the NAAQS and AQI categories, and ultimately to inform breakpoints for sensor messages. We consider the empirical distributions of the maximum 8-hr averages (ozone) and 24-hr averages (PM_2.5) given the corresponding short-term concentrations, and provide a probabilistic assessment. The result is a robust, empirical comparison that includes events of interest for air quality exceedances and public health communication. Concentration breakpoints are developed for short-term sensor readings such that, to the extent possible, the related air quality messages that are conveyed to the public are consistent with messages related to the NAAQS and AQI.

Implications: Real-time sensors have the potential to provide important information about fine-scale current air quality and local air quality events. The statistical analysis of short-term regulatory and sensor data, coupled with policy considerations and known health effects experienced over longer averaging times, supports interpretation of such short-term data and efforts to communicate local air quality.     

Evaluation of the SO2 and NOX offset ratio method to account for secondary PM2.5 formation

The U.S. Environmental Protection Agency (EPA), state and local agencies have focused their efforts in assessing secondary fine particulate matter (aerodynamic diameter ≤2.5 µm; PM_2.5) formation in prevention of significant deterioration (PSD) air dispersion modeling. The National Association of Clean Air Agencies (NACAA) developed a method to account for secondary PM_2.5 formation by using sulfur dioxide (SO₂) and nitrogen oxides (NO_x) offset ratios. These ratios are used to estimate the secondary formation of sulfate and nitrate PM_2.5. These ratios were first introduced by the EPA for nonattainment areas in the Implementation of the New Source Review (NSR) Program for Particulate Matter Less than 2.5 Micrometers (PM_2.5), 73 FR 28321, to offset emission increases of direct PM_2.5 emissions with reductions of PM_2.5 precursors and vice versa. Some regulatory agencies such as the Minnesota Pollution Control Agency (MPCA) have developed area-specific offset ratios for SO₂ and NO_x based on Comprehensive Air Quality Model with Extensions (CAMx) evaluations for air dispersion modeling analyses. The current study evaluates the effect on American Meteorological Society/Environmental Protection Agency Regulatory Model (AERMOD) predicted concentrations from the use of EPA and MPCA developed ratios. The study assesses the effect of these ratios on an electric generating utility (EGU), taconite mine, food processing plant, and a pulp and paper mill. The inputs used for these four scenarios are based on common stack parameters and emissions based on available data. The effect of background concentrations also evaluates these scenarios by presenting results based on uniform annual PM_2.5 background values. This evaluation study helps assess the viability of the offset ratio method developed by NACAA in estimating primary and secondary PM_2.5 concentrations. An alternative Tier 2 approach to combine modeled and monitored concentrations is also presented.

Implications:

On January 4, 2012, the EPA committed to engage in rulemaking to evaluate updates to the Guideline on Air Quality Models (Appendix W of 40 CFR 51) and, as appropriate, incorporate new analytical techniques or models for secondary PM_2.5. As a result, the National Association of Clean Air Agencies (NACAA) developed a screening method involving offset ratios to account for secondary PM_2.5 formation. The use of this method is promising to evaluate total (direct and indirect) PM_2.5 impacts for permitting purposes. Therefore, the evaluation of this method is important to determine its viability for widespread use.     

Recent spatial gradients and time trends in Dhaka,Bangladesh, air pollution and their human health implications

Dhaka, the capital of Bangladesh, is among the most polluted cities in the world. This research evaluates seasonal patterns, day-of-week patterns, spatial gradients, and trends in PM_2.5 (<2.5 µm in aerodynamic diameter), PM₁₀ (<10 µm in aerodynamic diameter), and gaseous pollutants concentrations (SO₂, NO₂, CO, and O₃) monitored in Dhaka from 2013 to 2017. It expands on past work by considering multiple monitoring sites and air pollutants. Except for ozone, the average concentrations of these pollutants showed strong seasonal variation, with maximum during winter and minimum during monsoon, with the pollution concentration of PM_2.5 and PM₁₀ being roughly five- to sixfold higher during winter versus monsoon. Our comparisons of the pollutant concentrations with Bangladesh NAAQS and U.S. NAAQS limits analysis indicate particulate matter (PM_2.5 and PM₁₀) as the air pollutants of greatest concern, as they frequently exceeded the Bangladesh NAAQS and U.S. NAAQS, especially during nonmonsoon time. In contrast, gaseous pollutants reported far fewer exceedances throughout the study period. During the study period, the highest number of exceedances of NAAQS limits in Dhaka City (Darus-Salam site) were found for PM_2.5 (72% of total study days), followed by PM₁₀ (40% of total study days), O₃ (1.7% of total study days), SO₂ (0.38% of total study days), and CO (0.25% of total study days). The trend analyses results showed statistically significant positive slopes over time for SO₂ (5.6 ppb yr^?1, 95% confidence interval [CI]: 0.7, 10.5) and CO (0.32 ppm yr^?1, 95% CI: 0.01, 0.56), which suggest increase in brick kilns operation and high-sulfur diesel use. Though statistically nonsignificant annual decreasing slopes for PM_2.5 (?4.6 µg/m³ yr^?1, 95% CI: ?12.7, 3.6) and PM₁₀ (?2.7 µg/m³ yr^?1, 95% CI: ?7.9, 2.5) were observed during this study period, the PM_2.5 concentration is still too high (~ 82.0 µg/m³) and can cause severe impact on human health.

Implications: This study revealed key insights into air quality challenges across Dhaka, Bangladesh, indicating particulate matter (PM) as Dhaka’s most serious air pollutant threat to human health. The results of these analyses indicate that there is a need for immediate further investigations, and action based on those investigations, including the conduct local epidemiological PM exposure-human health effects studies for this city, in order to determine the most public health effective interventions.     

Public health and components of particulate matter: The changing assessment of black carbon

In 2012, the WHO classified diesel emissions as carcinogenic, and its European branch suggested creating a public health standard for airborne black carbon (BC). In 2011, EU researchers found that life expectancy could be extended four to nine times by reducing a unit of BC, vs reducing a unit of PM_2.5. Only recently could such determinations be made. Steady improvements in research methodologies now enable such judgments.

In this Critical Review, we survey epidemiological and toxicological literature regarding carbonaceous combustion emissions, as research methodologies improved over time. Initially, we focus on studies of BC, diesel, and traffic emissions in the Western countries (where daily urban BC emissions are mainly from diesels). We examine effects of other carbonaceous emissions, e.g., residential burning of biomass and coal without controls, mainly in developing countries.

Throughout the 1990s, air pollution epidemiology studies rarely included species not routinely monitored. As additional PM_2.5. chemical species, including carbonaceous species, became more widely available after 1999, they were gradually included in epidemiological studies. Pollutant species concentrations which more accurately reflected subject exposure also improved models.

Natural “interventions” - reductions in emissions concurrent with fuel changes or increased combustion efficiency; introduction of ventilation in highway tunnels; implementation of electronic toll payment systems – demonstrated health benefits of reducing specific carbon emissions. Toxicology studies provided plausible biological mechanisms by which different PM species, e.g., carbonaceous species, may cause harm, aiding interpretation of epidemiological studies.

Our review finds that BC from various sources appears to be causally involved in all-cause, lung cancer, and cardiovascular mortality, morbidity, and perhaps adverse birth and nervous system effects. We recommend that the U.S. EPA rubric for judging possible causality of PM_2.5. mass concentrations, be used to assess which PM_2.5. species are most harmful to public health.

Implications: Black carbon (BC) and correlated co-emissions appear causally related with all-cause, cardiovascular, and lung cancer mortality, and perhaps with adverse birth outcomes and central nervous system effects. Such findings are recent, since widespread monitoring for BC is also recent. Helpful epidemiological advances (using many health relevant PM_2.5 species in models; using better measurements of subject exposure) have also occurred. “Natural intervention” studies also demonstrate harm from partly combusted carbonaceous emissions. Toxicology studies consistently find biological mechanisms explaining how such emissions can cause these adverse outcomes. A consistent mechanism for judging causality for different PM_2.5 species is suggested.

A list of acronyms will be found at the end of the article.     

Air quality modeling for effective environmental management in the mining region

Air quality in the mining sector is a serious environmental concern and associated with many health issues. Air quality management in mining regions has been facing many challenges due to lack of understanding of atmospheric factors and physical removal mechanisms. A modeling approach called the mining air dispersion model (MADM) is developed to predict air pollutants concentration in the mining region while considering the deposition effect. The model takes into account the planet’s boundary conditions and assumes that the eddy diffusivity depends on the downwind distance. The developed MADM is applied to a mining site in Canada. The model provides values for the predicted concentrations of PM₁₀, PM_2.5, TSP, NO₂, and six heavy metals (As, Pb, Hg, Cd, Zn, Cr) at various receptor locations. The model shows that neutral stability conditions are dominant for the study site. The maximum mixing height is achieved (1280 m) during the evening in summer, and the minimum mixing height (380 m) is attained during the evening in winter. The dust fall (PM coarse) deposition flux is maximum during February and March with a deposition velocity of 4.67 cm/sec. The results are evaluated with the monitoring field values, revealing a good agreement for the target air pollutants with R-squared ranging from 0.72 to 0.96 for PM_2.5, from 0.71 to 0.82 for PM₁₀, and from 0.71 to 0.89 for NO₂. The analyses illustrate that the presented algorithm in this model can be used to assess air quality for the mining site in a systematic way. Comparisons of MADM and CALPUFF modeling values are made for four different pollutants (PM_2.5, PM₁₀, TSP, and NO₂) under three different atmospheric stability classes (stable, neutral, and unstable). Further, MADM results are statistically tested against CALPUFF for the air pollutants and model performance is found satisfactory.

Implications: The mathematical model (MADM) is developed by extending the Gaussian equation particularly when examining the settling process of important pollutants for the industrial region. Physical removal effects of air pollutants with field data have been considerred for the MADM development and for an extensive field case study. The model is well validated in the field of an open pit mine to assess the regional air quality. The MADA model helps to facilitate the management of the mining industry in doing estimation of emission rate around mining activities and predicting the resulted concentration of air pollutants together in one integrated approach.     

The impact of airborne particulate matter on pediatric hospital admissions for pneumonia among children in Jinan,China: A case-crossover study

This study aims to examine the effect of short-term changes in the concentration of particulate matter of diameter ≤2.5 µm (PM_2.5) and ≤10 µm (PM₁₀) on pediatric hospital admissions for pneumonia in Jinan, China. It explores confoundings factors of weather, season, and chemical pollutants. Information on pediatric hospital admissions for pneumonia in 2014 was extracted from the database of Jinan Qilu Hospital. The relative risk of pediatric hospital admissions for pneumonia was assessed using a case-crossover approach, controlling weather variables, day of the week, and seasonality. The single-pollutant model demonstrated that increased risk of pediatric hospital admissions for pneumonia was significantly associated with elevated PM_2.5 concentrations the day before hospital admission and elevated PM₁₀ concentrations 2 days before hospital admission. An increment of 10 μg/m³ in PM_2.5 and PM₁₀ was correlated with a 6% (95% CI 1.02–-1.10) and 4% (95% CI 1.00–1.08) rise in number of admissions for pneumonia, respectively. In two pollutant models, PM_2.5 and PM₁₀ remained significant after inclusion of sulfur dioxide or nitrogen dioxide but not carbon monoxide. This study demonstrated that short-term exposure to atmospheric particulate matter (PM_2.5/PM₁₀) may be an important determinant of pediatric hospital admissions for pneumonia in Jinan, China.

Implications: This study demonstrated that short-term exposure to atmospheric particulate matter (PM_2.5/PM₁₀) may be an important determinant of pediatric hospital admissions for pneumonia in Jinan, China, and suggested the relevance of pollutant exposure levels and their effects. As a specific group, children are sensitive to airborne particulate matter. This study estimated the short-term effects attribute to other air pollutants to provide references for relevant studies.     

Contribution of dust storms to PM10 levels in an urban arid environment

Quantitative information on the contribution of dust storms to atmospheric PM₁₀ (particulate matter with an aerodynamic diameter ≤10 µm) levels is still lacking, especially in urban environments with close proximity to dust sources. The main objective of this study was to quantify the contribution of dust storms to PM₁₀ concentrations in a desert urban center, the city of Beer-Sheva, Negev, Israel, during the period of 2001–2012. Toward this end, a background value based on the “dust-free” season was used as a threshold value to identify potentially “dust days.” Subsequently, the net contribution of dust storms to PM₁₀ was assessed. During the study period, daily PM₁₀ concentrations ranged from 6 to over 2000 µg/m³. In each year, over 10% of the daily concentrations exceeded the calculated threshold (BV_t) of 71 µg/m³. An average daily net contribution of dust to PM₁₀ of 122 µg/m³ was calculated for the entire study period based on this background value. Furthermore, a dust storm intensity parameter (Ai) was used to analyze several storms with very high PM₁₀ contributions (hourly averages of 1000–5197 μg/m³). This analysis revealed that the strongest storms occurred mainly in the last 3 yr of the study. Finally, these findings indicate that this arid urban environment experiences high PM₁₀ levels whose origin lies in both local and regional dust events.

Implications:The findings indicate that over time, the urban arid environment experiences high PM₁₀ levels whose origin lies in local and regional dust events. It was noticed that the strongest storms have occurred mainly in the last 3 yr. It is believed that environmental changes such as global warming and desertification may lead to an increased air pollution and risk exposure to human health.     

Projected changes in particulate matter concentrations in the South Coast Air Basin due to basin-wide reductions in nitrogen oxides,volatile organic compounds,and ammonia emissions

An ozone abatement strategy for the South Coast Air Basin (SoCAB) has been proposed by the South Coast Air Quality Management District (SCAQMD) and the California Air Resources Board (ARB). The proposed emissions reduction strategy is focused on the reduction of nitrogen oxide (NO_x) emissions by the year 2030. Two high PM_2.5 concentration episodes with high ammonium nitrate compositions occurring during September and November 2008 were simulated with the Community Multi-scale Air Quality model (CMAQ). All simulations were made with same meteorological files provided by the SCAQMD to allow them to be more directly compared with their previous modeling studies. Although there was an overall under-prediction bias, the CMAQ simulations were within an overall normalized mean error of 50%; a range that is considered acceptable performance for PM modeling. A range of simulations of these episodes were made to evaluate sensitivity to NO_x and ammonia emissions inputs for the future year 2030. It was found that the current ozone control strategy will reduce daily average PM_2.5 concentrations. However, the targeted NO_x reductions for ozone were not found to be optimal for reducing PM_2.5 concentrations. Ammonia emission reductions reduced PM_2.5 and this might be considered as part of a PM_2.5 control strategy.

Implications: The SCAQMD and the ARB have proposed an ozone abatement strategy for the SoCAB that focuses on NO_x emission reductions. Their strategy will affect both ozone and PM_2.5. Two episodes that occurred during September and November 2008 with high PM_2.5 concentrations and high ammonium nitrate composition were selected for simulation with different levels of nitrogen oxide and ammonia emissions for the future year 2030. It was found that the ozone control strategy will reduce maximum daily average PM_2.5 concentrations but its effect on PM_2.5 concentrations is not optimal.     

Particulate matter pollution in the coal-producing regions of the Appalachian Mountains: Integrated ground-based measurements and satellite analysis

This study integrates the relationship between measured surface concentrations of particulate matter 10 μm or less in diameter (PM₁₀), satellite-derived aerosol optical depth (AOD), and meteorology in Roda, Virginia, during 2008. A multiple regression model was developed to predict the concentrations of particles 2.5 μm or less in diameter (PM_2.5) at an additional location in the Appalachia region, Bristol, TN. The model was developed by combining AOD retrievals from Moderate Resolution Imaging Spectro-radiometer (MODIS) sensor on board the EOS Terra and Aqua Satellites with the surface meteorological observations. The multiple regression model predicted PM_2.5 (r² = 0.62), and the two-variable (AOD-PM_2.5) model predicted PM_2.5 (r² = 0.4). The developed model was validated using particulate matter recordings and meteorology observations from another location in the Appalachia region, Hazard, Kentucky. The model was extrapolated to the Roda, VA, sampling site to predict PM_2.5 mass concentrations. We used 10 km x 10 km resolution MODIS 550 nm AOD to predict ground level PM_2.5. For the relevant period in 2008, in Roda, VA, the predicted PM_2.5 mass concentration is 9.11 ± 5.16 μg m^-3 (mean ± 1SD).

Implications: This is the first study that couples ground-based Particulate Matter measurements with satellite retrievals to predict surface air pollution at Roda, Virginia. Roda is representative of the Appalachian communities that are commonly located in narrow valleys, or “hollows,” where homes are placed directly along the roads in a region of active mountaintop mining operations. Our study suggests that proximity to heavy coal truck traffic subjects these communities to chronic exposure to coal dust and leads us to conclude that there is an urgent need for new regulations to address the primary sources of this particulate matter.     

Synthesis of Harvard Environmental Protection Agency (EPA) Center studies on traffic-related particulate pollution and cardiovascular outcomes in the Greater Boston Area

The association between particulate pollution and cardiovascular morbidity and mortality is well established. While the cardiovascular effects of nationally regulated criteria pollutants (e.g., fine particulate matter [PM_2.5] and nitrogen dioxide) have been well documented, there are fewer studies on particulate pollutants that are more specific for traffic, such as black carbon (BC) and particle number (PN). In this paper, we synthesized studies conducted in the Greater Boston Area on cardiovascular health effects of traffic exposure, specifically defined by BC or PN exposure or proximity to major roadways. Large cohort studies demonstrate that exposure to traffic-related particles adversely affect cardiac autonomic function, increase systemic cytokine-mediated inflammation and pro-thrombotic activity, and elevate the risk of hypertension and ischemic stroke. Key patterns emerged when directly comparing studies with overlapping exposure metrics and population cohorts. Most notably, cardiovascular risk estimates of PN and BC exposures were larger in magnitude or more often statistically significant compared to those of PM_2.5 exposures. Across multiple exposure metrics (e.g., short-term vs. long-term; observed vs. modeled) and different population cohorts (e.g., elderly, individuals with co-morbidities, young healthy individuals), there is compelling evidence that BC and PN represent traffic-related particles that are especially harmful to cardiovascular health. Further research is needed to validate these findings in other geographic locations, characterize exposure errors associated with using monitored and modeled traffic pollutant levels, and elucidate pathophysiological mechanisms underlying the cardiovascular effects of traffic-related particulate pollutants.

Implications: Traffic emissions are an important source of particles harmful to cardiovascular health. Traffic-related particles, specifically BC and PN, adversely affect cardiac autonomic function, increase systemic inflammation and thrombotic activity, elevate BP, and increase the risk of ischemic stroke. There is evidence that BC and PN are associated with greater cardiovascular risk compared to PM_2.5. Further research is needed to elucidate other health effects of traffic-related particles and assess the feasibility of regulating BC and PN or their regional and local sources.     

Development and field validation of a community-engaged particulate matter air quality monitoring network in Imperial,California, USA

The Imperial County Community Air Monitoring Network was developed as part of a community-engaged research study to provide real-time particulate matter (PM) air quality information at a high spatial resolution in Imperial County, California. The network augmented the few existing regulatory monitors and increased monitoring near susceptible populations. Monitors were both calibrated and field validated, a key component of evaluating the quality of the data produced by the community monitoring network. This paper examines the performance of a customized version of the low-cost Dylos optical particle counter used in the community air monitors compared with both PM_2.5 and PM₁₀ (particulate matter with aerodynamic diameters <2.5 and <10 μm, respectively) federal equivalent method (FEM) beta-attenuation monitors (BAMs) and federal reference method (FRM) gravimetric filters at a collocation site in the study area. A conversion equation was developed that estimates particle mass concentrations from the native Dylos particle counts, taking into account relative humidity. The R² for converted hourly averaged Dylos mass measurements versus a PM_2.5 BAM was 0.79 and that versus a PM₁₀ BAM was 0.78. The performance of the conversion equation was evaluated at six other sites with collocated PM_2.5 environmental beta-attenuation monitors (EBAMs) located throughout Imperial County. The agreement of the Dylos with the EBAMs was moderate to high (R² = 0.35–0.81).

Implications: The performance of low-cost air quality sensors in community networks is currently not well documented. This paper provides a methodology for quantifying the performance of a next-generation Dylos PM sensor used in the Imperial County Community Air Monitoring Network. This air quality network provides data at a much finer spatial and temporal resolution than has previously been possible with government monitoring efforts. Once calibrated and validated, these high-resolution data may provide more information on susceptible populations, assist in the identification of air pollution hotspots, and increase community awareness of air pollution.     

The impact of photovoltaic (PV) installations on downwind particulate matter concentrations: Results from field observations at a 550-MWAC utility-scale PV plant

With utility-scale photovoltaic (PV) projects increasingly developed in dry and dust-prone geographies with high solar insolation, there is a critical need to analyze the impacts of PV installations on the resulting particulate matter (PM) concentrations, which have environmental and health impacts. This study is the first to quantify the impact of a utility-scale PV plant on PM concentrations downwind of the project site. Background, construction, and post-construction PM_2.5 and PM₁₀ (PM with aerodynamic diameters <2.5 and <10 μm, respectively) concentration data were collected from four beta attenuation monitor (BAM) stations over 3 yr. Based on these data, the authors evaluate the hypothesis that PM emissions from land occupied by a utility-scale PV installation are reduced after project construction through a wind-shielding effect. The results show that the (1) confidence intervals of the mean PM concentrations during construction overlap with or are lower than background concentrations for three of the four BAM stations; and (2) post-construction PM_2.5 and PM₁₀ concentrations downwind of the PV installation are significantly lower than the background concentrations at three of the four BAM stations. At the fourth BAM station, downwind post-construction PM_2.5 and PM₁₀ concentrations increased marginally by 5.7% and 2.6% of the 24-hr ambient air quality standards defined by the U.S. Environmental Protection Agency, respectively, when compared with background concentrations, with the PM_2.5 increase being statistically insignificant. This increase may be due to vehicular emissions from an access road near the southwest corner of the site or a drainage berm near the south station. The findings demonstrate the overall environmental benefit of downwind PM emission abatement from a utility-scale PV installation in desert conditions due to wind shielding. With PM emission reductions observed within 10 months of completion of construction, post-construction monitoring of downwind PM levels may be reduced to a 1-yr period for other projects with similar soil and weather conditions.

Implications: This study is the first to analyze impact of a utility photovoltaic (PV) project on downwind particulate matter (PM) concentration in desert conditions. The PM data were collected at four beta attenuation monitor stations over a 3-yr period. The post-construction PM concentrations are lower than background concentrations at three of four stations, therefore supporting the hypothesis of post-construction wind shielding from PV installations. With PM emission reductions observed within 10 months of completion of construction, postconstruction monitoring of downwind PM levels may be reduced to a 1-yr period for other PV projects with similar soil and weather conditions.     

Is remaining indoors an effective way of reducing exposure to fine particulate matter during biomass burning events?

Bushfires, prescribed burns, and residential wood burning are significant sources of fine particles (aerodynamic diameter <2.5 μm; PM_2.5) affecting the health and well-being of many communities. Despite the lack of evidence, a common public health recommendation is to remain indoors, assuming that the home provides a protective barrier against ambient PM_2.5. The study aimed to assess to what extent houses provide protection against peak concentrations of outdoor PM_2.5 and whether remaining indoors is an effective way of reducing exposure to PM_2.5. The effectiveness of this strategy was evaluated by conducting simultaneous week-long indoor and outdoor measurements of PM_2.5 at 21 residences in regional areas of Victoria, Australia. During smoke plume events, remaining indoors protected residents from peak outdoor PM_2.5 concentrations, but the level of protection was highly variable, ranging from 12% to 76%. Housing stock (e.g., age of the house) and ventilation (e.g., having windows/doors open or closed) played a significant role in the infiltration of outdoor PM_2.5 indoors. The results also showed that leaving windows and doors closed once the smoke plume abates trapped PM_2.5 indoors and increased indoor exposure to PM_2.5. Furthermore, for approximately 50% of households, indoor sources such as cooking activities, smoking, and burning candles or incense contributed significantly to indoor PM_2.5.

Implications: Smoke from biomass burning sources can significantly impact on communities. Remaining indoors with windows and doors closed is a common recommendation by health authorities to minimize exposures to peak concentrations of fine particles during smoke plume events. Findings from this study have shown that the protection from fine particles in biomass burning smoke is highly variable among houses, with information on housing age and ventilation status providing an approximate assessment on the protection of a house. Leaving windows closed once a smoke plume abates traps particles indoors and increases exposures.     

On ground truth in cross-border ozone transport

Cross-border transport of ozone is one of the most contentious issues of air pollution management in the U.S. Yet, both the modeling and observational studies are lacking. Models are normally validated by comparing predicted and observed ozone concentrations. However, proper validation of cross-border transport model requires a comparison of predictions against observation-based benchmarks of cross-border ozone transport. Such benchmarks are unavailable, as published observation-based studies always deal only with a combination of local production and cross-border transport, not a cross-border transport itself. We show how to extract necessary benchmarks from observations of rural monitoring sites near state borders. On example of the western border of New York, we find that in about two-thirds of the most polluted days all the ozone came in a steady cross-border inflow after previously passing over one or more large urban areas to the west. In all the enumerated days with direct cross-border inflow, daily maximum 8-hr concentrations of ozone just upwind of the border were over 60 ppb, with an average value of 68 ppb, just short of the 70 ppb ozone regulatory threshold, information also useful to state air pollution authorities.

Implications: The purpose of the cross-border ozone pollution models is to predict cross-border transport of ozone, so the ability of the model to accurately represent observed ozone concentrations is necessary but not sufficient for model validation. The accuracy of predicted ozone concentrations is not necessarily the same as the accuracy of the predictions of ozone transport. Proper model validation requires comparisons against observation-based benchmarks of cross-border transport. Such observations, so far absent, can be obtained from rural monitoring sites near state borders, as illustrated by the example of western New York.     

Association of PM2.5 pollution with the pattern of human activity: A case study of a developed city in eastern China

Recently, air pollution has attracted a substantial amount of attention in China, which can be influenced by a variety of factors, but the association between air pollution and human activity is not quite clear. Based on real-time online data (January 1, 2014, to December 31, 2014) of air pollution and meteorology reported by official sites, and demographic, economic, and environmental reform data in a statistical yearbook, the influences of meteorological factors (temperature, relative humidity, precipitation intensity, and wind force) and human activities on PM_2.5 pollution were explored. After correlation analysis, logistic regression analysis, and a nonparametric test, weak negative correlations between temperature and PM_2.5 pollution were found. In most cases, festival and morning peak hours were protection and risk factors of PM_2.5 pollution, respectively. In addition, government actions, such as an afforestation project and increasing financial expenditure for energy saving and environmental protection, could greatly contribute to alleviating pollution of PM_2.5. The findings could help officials formulate effective laws and regulations, and then PM_2.5 pollution related to the pattern of human activity would be ameliorated.

Implications: Most of the time, festival and morning peak hours are protection and risk factors for PM_2.5 pollution, respectively. Increasing the percentage of afforestation area and financial expenditure for energy saving and environmental protection could significantly reduce PM_2.5 pollution. The findings can help officials formulate effective laws and regulations, and then PM_2.5 pollution related to the pattern of human activity, especially government action, will be ameliorated.     

Seasonal ambient particulate matter and population health outcomes among communities impacted by road dust in British Columbia,Canada

In recent years, many air quality monitoring programs have favored measurement of particles less than 2.5 µm (PM_2.5) over particles less than 10 µm (PM₁₀) in light of evidence that health impacts are mostly from the fine fraction. However, the coarse fraction (PM_10-2.5) may have independent health impacts that support continued measurement of PM₁₀ in some areas, such as those affected by road dust. The objective of this study was to evaluate the associations between different measures of daily PM exposure and two daily indicators of population health in seven communities in British Columbia, Canada, where road dust is an ongoing concern. The measures of exposure were PM₁₀, PM_2.5, PM_10-2.5, PM_2.5 adjusted for PM_10-2.5, and PM_10-2.5 adjusted for PM_2.5. The indicators of population health were dispensations of the respiratory reliever medication salbutamol sulfate and nonaccidental mortality. This study followed a time-series design using Poisson regression over a 2003–2015 study period, with analyses stratified by three seasons: residential woodsmoke in winter; road dust in spring; and wildfire smoke in summer. A random-effects meta-analysis was conducted to establish a pooled estimate. Overall, an interquartile range increase in daily PM_10-2.5 was associated with a 3.6% [1.6, 5.6] increase in nonaccidental mortality during the road dust season, which was reduced to 3.1% [0.8, 5.4] after adjustment for PM_2.5. The adjusted coarse fraction had no effect on salbutamol dispensations in any season. However, an interquartile range increase in PM_2.5 was associated with a 2.7% [2.0, 3.4] increase in dispensations during the wildfire season. These analyses suggest different impacts of different PM fractions by season, with a robust association between the coarse fraction and nonaccidental mortality in communities and periods affected by road dust. We recommend that PM₁₀ monitoring networks be maintained in these communities to provide feedback for future dust mitigation programs.

Implications: There was a significant association between daily concentrations of the coarse fraction and nonaccidental mortality during the road dust season, even after adjustment for the fine fraction. The acute and chronic health effects associated with exposure to the coarse fraction remain unclear, which supports the maintenance of PM₁₀ monitoring networks to allow for further research in communities affected by sources such as road dust.     

Effect modification of ambient particle mortality by radon: A time series analysis in 108 U.S. cities

Numerous studies have reported a positive association between ambient fine particles and daily mortality, but little is known about the particle properties or environmental factors that may contribute to these effects. This study assessed potential modification of radon on PM_2.5 (particulate matter with an aerodynamic diameter <2.5 μm)-associated daily mortality in 108 U.S. cities using a two-stage statistical approach. First, city- and season-specific PM_2.5 mortality risks were estimated using over-dispersed Poisson regression models. These PM_2.5 effect estimates were then regressed against mean city-level residential radon concentrations to estimate overall PM_2.5 effects and potential modification by radon. Radon exposure estimates based on measured short-term basement concentrations and modeled long-term living-area concentrations were both assessed. Exposure to PM_2.5 was associated with total, cardiovascular, and respiratory mortality in both the spring and the fall. In addition, higher mean city-level radon concentrations increased PM_2.5-associated mortality in the spring and fall. For example, a 10 µg/m³ increase in PM_2.5 in the spring at the 10th percentile of city-averaged short-term radon concentrations (21.1 Bq/m³) was associated with a 1.92% increase in total mortality (95% CI: 1.29, 2.55), whereas the same PM_2.5 exposure at the 90th radon percentile (234.2 Bq/m³) was associated with a 3.73% increase in total mortality (95% CI: 2.87, 4.59). Results were robust to adjustment for spatial confounders, including average planetary boundary height, population age, percent poverty and tobacco use. While additional research is necessary, this study suggests that radon enhances PM_2.5 mortality. This is of significant regulatory importance, as effective regulation should consider the increased risk for particle mortality in cities with higher radon levels.

Implications: In this large national study, city-averaged indoor radon concentration was a significant effect modifier of PM_2.5-associated total, cardiovascular, and respiratory mortality risk in the spring and fall. These results suggest that radon may enhance PM_2.5-associated mortality. In addition, local radon concentrations partially explain the significant variability in PM_2.5 effect estimates across U.S. cities, noted in this and previous studies. Although the concept of PM as a vector for radon progeny is feasible, additional research is needed on the noncancer health effects of radon and its potential interaction with PM. Future air quality regulations may need to consider the increased risk for particle mortality in cities with higher radon levels.     

Purification characteristics of fine particulate matter treated by a self-flushing wet electrostatic precipitator equipped with a flexible electrode

A self-flushing wet electrostatic precipitator was developed to investigate the removal performance for fine particles. Flexible material (polypropylene, 840A) and carbon steel in the form of a spiked band were adopted as the collection plate and discharge electrode, respectively. The particle concentration, morphology, and trace-element content were measured by electric low-pressure impactor, scanning electron microscope, and energy-dispersive x-ray spectroscopy, respectively, before and after the electrostatic precipitator. With increasing gas velocity, the collection efficiency of fine particles (up to 0.8 μm in diameter) increased, while it decreased for particles with diameters larger than 0.8 μm. Increasing the dust inlet concentration increased the collection efficiency up to a point, from which it then declined gradually with further increases in the inlet concentration. The particulate matter after the wet electrostatic precipitator showed different degrees of agglomeration. The collection efficiency of trace elements within PM₁₀ was less than that of the PM₁₀ itself. Notably, the water consumption in the current setup was significantly lower than for other treatment processes of comparable collection efficiencies.

Implications: Wet electrostatic precipitators, as fine filtration equipment, were generally applicable to coal-fired plants to reduce PM_2.5 emissions in China. However, high energy consumption and unstable operation, such as water usage and spray washing directly in the electric field, seriously restricted the further development. The utilization of self-flushing wet electrostatic precipitator can solve these problems to some extent.