Summer PM Research Articles

Understanding the Driving Forces of Summer PM1 Composition in Seoul, Korea, with Explainable Machine Learning

Understanding the Driving Forces of Summer PM₁ Composition in Seoul, Korea, with Explainable Machine Learning

Photographic monitoring of glowworm Arachnocampa luminosa (Diptera: Keroplatidae) bioluminescence in a tourist cave reveals diurnal and annual cycles

AbstractGlowworms are the bioluminescent larvae of a group of dipteran insects related to fungus gnats. They require sheltered, consistently moist conditions and are found in aggregations on the walls and ceilings of caves and near streams in wet forests where they attract flying insects as prey. The Waitomo Glowworm Cave in New Zealand receives many thousands of visitors each year to see the colony of the glowworm, Arachnocampa luminosa. The cave climate is managed to ensure the glowworms are not harmed by influxes of dry air, as happened in the 1970s. To monitor the population and warn of catastrophic population declines, time‐lapse photographic monitoring of the glowworm population began in 2011 using a permanent, fixed camera. Photographs are taken 30 min apart. The population exhibits synchronised diurnal cycles of bioluminescence intensity. The time of the acrophase (the peak) of the diurnal cycle varied seasonally between 5 pm in early southern spring and 8 pm in summer. Cross‐correlation analyses with cave and water temperatures incorporating time lags suggest that this annual cycle could be related to changes in the composition or density of prey insects. Annual cycles also occur in the number of glowing larvae and their overall intensity. In most years, the numbers are lowest in winter and increase in spring to produce the brightest display through summer. The summer peak is not seen every year and autocorrelation of the 13‐year time series of count shows signs of a 3‐ to 4‐year cycle beyond the annual periodicity. The availability of prey in the cave chamber could influence the annual cycles in glowworm density, underscoring the need for a deeper knowledge of the bionomics of prey species, mainly Chironomidae (non‐biting midges). The photographic monitoring has proven to be a useful component of the management of the glowworm population.

Evaluating coarse PM composition and sources based on bulk and molecular speciation of PM2.5 and PM10 in Nanjing, East China

To understand the differences in the composition and sources of PM2.5 and PM10 caused by coarse particles, integrated PM2.5 and PM10 samples were synchronously collected in Nanjing, East China, in summer 2020 and winter 2020/2021. Bulk and molecular speciation and light absorption measurements of aerosol extracts were performed, followed by positive matrix factorization (PMF) based on the PM2.5 and PM10 data sets, respectively. The difference in average concentrations of total bulk species between PM2.5 and PM10 was mainly caused by the distribution of considerable NO3–, SO42–, Ca2+, and organic carbon (OC) in coarse particles. Coarse PM influenced by abrasion products from tire wear and leaves contributed about half of the low-volatility n-alkanes in summer. The contribution of coarse PM to biomass burning tracers and water-soluble OC increased in winter when biomass combustion was excessively active. More than 70% of sugar polyols were attributable to coarse PM in summer, and biomass burning could be an important source in winter. The light-absorbing organic chromophores were almost entirely associated with PM2.5, but water-soluble organic carbon (WSOC) exhibited stronger light absorption in PM10 extracts than in PM2.5 extracts possibly due to the influence of coarse PM on pH. PMF analysis indicated that biomass burning, aqueous-phase reactions, and processed dust were the main contributors of organic matter and its light absorption in winter. Biogenic primary and secondary sources made discernable contributions only in summer. The differences between PM2.5 and PM10 were likely attributed to mixing of crustal dust, combustion particles, and surface reactions.

Empirical grid impact of in-home electric vehicle charging differs from predictions

Accurate assessment of the impact of electric vehicle (EV) charging on the electric grid is critical for energy policymakers to design efficient EV subsidy programs as well as to provide reliable electricity infrastructure. Despite the fact that 80 % of EV charging is conducted with residential in-home chargers, very few empirical studies have examined the load and environmental impact of residential EV charging based on actual electricity consumption data. Our paper fills this critical gap in the literature, applying a difference-in-differences approach to high frequency smart meter data of about 1600 EV homes from 2014 to 2019 in Arizona, United States. First, we find that the electricity demand during the system peak hours from 6 to 8 pm in summer can increase by 7–14 % at an average household with in-home EV charging. Second, EV households respond to electricity pricing signals by increasing their charging in lower-priced off-peak hours within the EV-specific time-of-use (TOU) pricing. Third, we find evidence of rebound effects in driving that lead to a reduction in home-electricity consumption in certain hours of the day. Lastly, we show that our empirical estimation of the grid impact due to in-home EV charging is different from that predicted by existing simulation models due to factors such as consumer behaviors. Such deviations between predicted and actual behaviors imply potential adjustment of relevant policy interventions.

Daily variation measurement of water and air temperatures inside the semi-full water storage tanks which have solid and porous concrete walls

Nowadays, access to safe drinking water is a major challenge in most arid and semi-arid regions of the world. Due to the low cost of raw materials for construction of concrete tanks, these types of structures are common in many areas where water problems are encountered. This study explores the use of porous concrete by utilizing the idea of old water storage tanks (Ab-Anbars), which played an important role in water storage for remote areas, rural and small towns until three to four decades ago, and their effect on reducing or increasing water temperatures. At the wall of the water storage tanks, effect of air passage through the porous concrete on the water inside the tanks is studied. For further investigation, LECA (5% by weight of aggregates) was used as an additive to porous concrete and 3 replicates of this treatment and control treatment were made. Daily ambient temperature and humidity were measured by the respective sensors, and inside temperature of the tanks was measured with two sensors, one in the middle of the stored water and one in the middle of the open space of the tanks, in the warmest hour of the day (14:30 pm) in spring and summer of 2019. Results showed that mean water temperature of LECA treatment was lower than mean water temperature of control and mean air temperature of control treatment was higher than mean air temperature of LECA treatment. Mean air and water temperatures were always less than mean ambient temperature. Also, the physical parameters of porous concrete (i.e., porosity, permeability and compressive strength) were investigated in this study. Results showed that the compressive strength and porosity of LECA treatment were higher than the control and its permeability was lower than the control.

Spatial regression modelling of particulate pollution in Calgary, Canada.

The study presents a spatial analysis of particulate pollution, which includes not only particulate matter, but also black carbon, a pollutant of growing concern for human health. We developed land use regression (LUR) models for two particulate matter size fractions, PM2.5 and PM10, and for δC, an index calculated from black carbon (BC)—a component of PM2.5—which indicates the portion of organic versus elemental BC. LUR models were estimated over Calgary (Canada) for summer 2015 and winter 2016. As all samples exhibited significant spatial autocorrelation, spatial autoregressive lag (SARlag) and error (SARerr) models were computed. SARlag models were preferred for all pollutants in both seasons, and yielded goodness of fit aligned with or higher than values reported in the literature. LUR models yielded consistent sets of predictors, representing industrial activities, traffic, and elevation. The obtained model coefficients were then combined with local land use variables to compute fine-scale concentration predictions over the entire city. The predicted concentrations were slightly lower and less dispersed than the observed ones. Consistent with observed pollution records, prediction maps exhibited higher concentration over the road network, industrial areas, and the eastern quadrants of the city. Lastly, results of a corresponding study of PM in summer 2010 and winter 2011 were considered. While the small size of the 2010–2011 sample hampered a multi-temporal analysis, we cautiously note comparable seasonal patterns and consistent association with land use variables for both PM fine fractions over the 5-year interval.

Summer PM2.5 Pollution Extremes Caused by Wildfires Over the Western United States During 2017–2018

AbstractUsing observations and model simulations (ESM4.1) during 1988–2018, we show large year‐to‐year variability in western U.S. PM2.5 pollution caused by regional and distant fires. Widespread wildfires, combined with stagnation, caused summer PM2.5 pollution in 2017 and 2018 to exceed 2 standard deviations over long‐term averages. ESM4.1 with a fire emission inventory constrained by satellite‐derived fire radiative energy and aerosol optical depth captures the observed surface PM2.5 means and extremes above the 35 μg/m3 U.S. air quality standard. However, aerosol emissions from the widely used Global Fire Emissions Database (GFED) must be increased by 5 times for ESM4.1 to match observations. On days when observed PM2.5 reached 35–175 μg/m3, wildfire emissions can explain 90% of total PM2.5, with smoke transported from Canada contributing 25–50% in northern states, according to model sensitivity simulations. Fire emission uncertainties pose challenges to accurately assessing the impacts of fire smoke on air quality, radiation, and climate.

The study on outdoor pedestrian thermal comfort in blocks: A case study of the Dao He Old Block in hot-summer and cold-winter area of southern China

The commercial pedestrian block, famous for its entertainment and commercial vitality, plays an important role in humans’ daily life. The use of this space is determined by outdoor thermal comfort which can directly the commercial value of this region. So far, few studies have been conducted on outdoor thermal comfort in hot-summer and cold–winter area of southern China.The Dao He Old Block locates in Tai Zhou city which belongs to hot-summer and cold-winter climate zone of southern China. In order to develop the local tourism, the local government has provided guidance for the appropriate directions and opportunities for future development of this region. This study investigates the thermal comfort conditions in microclimate of this block and put forward some suggestion for the tourists determine the best time to visit, also help managers choose their business hours. In this region, humans’ thermal acceptability and the thermal comfort sensation votes are assessed based on the Physiologically Equivalent Temperature (PET). About the future redesigning plan of this block is shown in three stages: increasing the building height; adding tree canyon coverage; changing paving material.Along with performing field measurement in this intended block, in addition, a three-dimensional microclimatic modelling tool ENVI-met 4.0 is used to evaluate the outdoor thermal comfort and validate the accuracy of the software through comparing the measured data with the simulated data. The existing scenario shows that almost the whole area is not comfortable for visiting from 8:00 am to 6:00 pm in extreme summer. After putting forward some suggestion for redesigning this area, the result shows that there is a strong improvement in broadening the cooling time, which means the more suitable time for visiting is given, the new result shows that early morning (8:00–11:00 am) and after 6:00 pm are the most comfortable time for visiting.

Effect of some Climatic Factors on Daily Activity of Pollen Gathering by Honeybee Apis mellifra L. during Spring and Summer Season

This study was conducted to measure the daily activity of collecting pollen during the activity seasons (spring and summer) under the influence of some climatic factors (Temperature oC, relative humidity % and photoperiods ). The results showed that, the highest quantities of pollen collected from 10 am to 12 pm (10 am -12 pm). In each of the spring and summer seasons with an average of 4.80 g / colony, the highest daily amount recorded during the month of May with a total average of 26.80 g / colony, while the lowest daily amount was recorded in August at 4.34 g / colony. There were insignificant difference between the amount of pollen collected in spring and summer during the period (8-10 am), (12-2 pm), (2-4 pm), (4-6 pm). While there were significant differences between the quantities of pollen collected in the period (10 am – 0.12 pm) in both spring and summer. Honey bees were more active in pollen collection (10 am – 12 am) and less active (4-6 pm) in both spring and summer seasons.

Coupled Thermo-mechanical Analysis of Concrete Pavements under Heavy Traffic

The tensile stresses of concrete pavements corners, edge centers, and surface centers under heavy traffic are analyzed as the pavements already deflected under temperature stresses. First, a transient temperature field of the pavements in summer and winter extreme weather is solved on ABAQUS. Then, the temperature field is imported into the mechanical model for coupled thermo-mechanical analysis, to obtain the temperature stresses and deflection of the pavements. Then, a vehicle load is located at different positions of pavements in different time; the tensile stresses of pavements are analyzed and received the most unfavorable combination of vehicle load and temperature stresses. The concrete pavements with thermal deflection may appear fracture at the corner and the edge center at 14:00PM in summer under once over-axle-load, so the linear combined fatigue failure theory of vehicle load and temperature stresses is not applied to concrete pavement under the over-axle-load.

Characteristics and sources of PM in seasonal perspective – A case study from one year continuously sampling in Beijing

Daily mass concentrations and chemical compositions (elemental carbon, organic carbon, water soluble ions, chemical elements and organic species) of PM were measured continuously in Beijing for one year from June 2010 to June 2011 (365 samples). The seasonal variation of PM mass concentration followed the order of spring 2011 > winter 2010 > summer 2010 > autumn 2010. Organic matter (OM) and secondary inorganic aerosol components (SNA: SO42−, NO3− and NH4+) were the two major fractions of PM during the whole year. Source apportionment by PMF performed on the basis of a full year of data, including both inorganic and organic species, showed that biomass burning, secondary sulfate and nitrate formation, mineral dust, industry, coal combustion and traffic were the main sources of PM in Beijing during 2010–2011. Specifically, comparison among the four seasons shows that the contribution of secondary sulfate and biomass burning, secondary nitrate formation, mineral dust, and coal combustion were the dominating sources of PM in summer, autumn, spring and winter, respectively. The contributions of industry to PM was distributed evenly in four seasons, while traffic contributed more in summer and autumn than in winter and spring. Backward trajectory analysis was applied in combination with PMF and showed that air flow from the South contributed mostly to high PM mass concentrations in Beijing. Meteorological parameters (temperature, wind speed, wind direction, precipitation and mixing layer height) influence such a variation. In general, high relative humidity and low mixing layer height can raise PM mass concentration, while high wind speed and precipitation can reduce pollutants. In addition, wind direction also plays a key role in influencing PM because different wind directions can bring different pollutants to Beijing from different regions.

Population Pharmacokinetic Analysis of Diurnal and Seasonal Variations of Plasma Concentrations of Cilostazol in Healthy Volunteers

The background of this study was (1) to examine factors influencing cilostazol pharmacokinetics by developing a population model incorporating diurnal variation and other covariate effects and (2) to assess the feasibility of applying the developed model to determine the optimal dosing times. Data obtained from a cilostazol pharmacokinetic study consisting of 2 clinical trials (a single twice-a-day (BID) dosing trial in winter and a multiple BID dosing trial in summer) conducted in healthy Korean subjects were used for model building. A basic model was built, followed by a diurnal variation model, and then a final model was built incorporating covariates, including a seasonal difference. The optimal morning and evening dosing times were determined from simulations. Diurnal variation in cilostazol pharmacokinetics was explained by the morning absorption rate constant being faster than in the evening, yielding values of 0.278 versus 0.234/h in summer, when 24- and 12-hour circadian rhythms were included in the model. The seasonal variation was explained by a 26.9% and a 31.8% decrease in the absorption rate constant and clearance, respectively, in winter compared with summer. Based on twice-a-day (BID) dosing, dosing times of 9 AM and 5 PM in summer and 10 AM and 7 PM in winter were expected to produce the smallest peak-to-peak fluctuations in cilostazol concentration, possibly minimizing unwanted effects of the drug. This study demonstrated the intraday and interseasonal time-varying nature of cilostazol pharmacokinetics using a population modeling approach and developed a strategy for optimizing dosing times. It is suggested that these methods can be similarly applied to analyses and controls of other drugs that exhibit characteristics of time-varying pharmacokinetics.

Spatiotemporal characteristics of anthropogenic heat in an urban environment: A case study of Tsinghua Campus

In this study, a detailed investigation of the spatiotemporal characteristics of anthropogenic heat (AH) from different sectors (i.e. human metabolism, transportation and building energy consumption) in an urban environment (the Tsinghua Campus in Beijing, China) is conducted using inventory and building energy modeling methods. The AH is estimated as large as 220.0 W m−2 (at about local time 7pm) in summer and 221.0 W m−2 (at about local time 6am) in winter. The results indicate that AH on Tsinghua Campus (TC) displays clear diurnal and seasonal cycles. Among the three sectors on TC, building energy consumption contributes the most to the total AH (about 97.4%), whereas metabolism and transportation accounts for 1.4% and 1.2% respectively. The spatial distribution of AH on TC indicates that higher AH is generally observed in more densely built-up areas with the hourly maximum value of 474.3 W m−2. Comparison between AH and incoming solar radiation shows that the magnitude of AH is about 43% and 92% of the incoming solar radiation in summer and winter, respectively. Therefore, AH should be considered as an important component of the urban representation in numeric weather prediction models and should be carefully accounted for when considering the urban surface energy balance. This study provides evidence of the significance of AH in urban environment and suggestions for improvement of urban module in numeric weather prediction models.

Polycyclic Aromatic Hydrocarbons at Different Crossroads in Zagreb, Croatia

Polycyclic aromatic hydrocarbons (PAHs) were measured in the PM(10) particle fraction collected at two different measuring sites in Zagreb, Croatia. In summer, concentrations of all PAHs at both sites were low. In winter, mass concentrations of all PAHs measured at southern site were much higher than those at north. Contents of all PAHs in the PM(10) particle fraction were much lower in summer than that in the winter period. For example, average content of BaP in PM(10) in summer was 2.26 ng/mg at site A and 4.17 ng/mg at site B, while in winter it was 34.72 and 46.69 ng/mg, respectively.

Gene expression profiling of A549 cells exposed to Milan PM2.5

BackgroundParticulate matter (PM) has been associated to adverse health effects in exposed population and DNA damage has been extensively reported in in vitro systems exposed to fine PM (PM2.5). The ability to induce gene expression profile modulation, production of reactive oxygen species (ROS) and strand breaks to DNA molecules has been investigated in A549 cells exposed to winter and summer Milan PM2.5. ResultsA549 cells, exposed to 10μg/cm2 of both winter and summer PM2.5, showed increased cytotoxicity at 24h and a significant increase of ROS at 3h of treatment. Despite these similar effects winter PM induced a higher number of gene modulation in comparison with summer PM. Both PMs modulated genes related to the response to xenobiotic stimuli (CYP1A1, CYP1B1, TIPARP, ALDH1A3, AHRR) and to the cell–cell signalling (GREM1) pathways with winter PM2.5 inducing higher fold increases. Moreover the winter fraction modulated also JUN (cell–cell signalling), GDF15, SIPA1L2 (signal transduction), and HMOX1 (oxidative stress). Two genes, epiregulin (EREG) and FOS-like antigen1 (FOSL1), were significantly up-regulated by summer PM2.5. The results obtained with the microarray approach have been confirmed by qPCR and by the analysis of CYP1B1 expression. Comet assay evidenced that winter PM2.5 induced more DNA strand breaks than the summer one. ConclusionWinter PM2.5 is able to induce gene expression alteration, ROS production and DNA damage. These effects are likely to be related to the CYP enzyme activation in response to the polycyclic aromatic hydrocarbons (PAHs) adsorbed on particle surface.

Variation of digestibility and intake by sheep of lucerne (Medicago sativa L.) hays cut at sunrise or sunset

SUMMARYAn experiment was carried out in 2006 in the Ebro Valley of Spain to test the differences in chemical composition, ruminal degradation, in vivo digestibility and intake between lucerne hays cut at sunrise (AM) or at sunset (PM). Measurements were carried out at 0·50 flowering during spring, summer and autumn growth cycles. PM hays showed higher contents of soluble carbohydrates, starch and total non-structural carbohydrates than AM hays. No significant differences between times of cutting were found for crude protein, neutral detergent fibre, acid detergent fibre or acid detergent lignin. Effective degradability of dry matter (DM) was higher in autumn PM hay (0·57±0·008) than AM hay (0·47±0·008). No differences between times of cutting were found for hays cut in spring or summer. Effective degradability of nitrogen was significantly higher in summer and autumn PM hays than in AM hays. However, degradability did not differ significantly between times of cutting for the hays cut in spring. Differences in organic matter digestibility averaged 0·02±0·008 in spring and 0·05±0·008 in autumn, but no differences were found between cutting times for lucerne hays in summer. For DM intake, differences between PM and AM hays were significant in spring (57±2·0 v. 46±2·0 g/kg BW0·75, respectively) and summer (60±2·0 v. 52±2·0 g/kg BW0·75, respectively), but not significant in autumn (55±2·0 v. 51±2·0 g/kg BW0·75, respectively). Finally, digestible organic matter intake in sheep was higher for PM (34±1·3, 36±1·3 and 32±1·3 g/kg BW0·75) than for AM hays (27±1·3, 30±1·3 and 27±1·3 g/kg BW0·75) in spring, summer and autumn, respectively. In conclusion, cutting lucerne at sunset could be a simple management strategy for improving the feed value of hays.

Source apportioning of primary and secondary organic carbon in summer PM2.5 in Hong Kong using positive matrix factorization of secondary and primary organic tracer data

The major inorganic constituents and organic tracer compounds in PM2.5 were used in positive matrix factorization (PMF) and chemical mass balance (CMB) models to apportion the primary and secondary source contributions to organic carbon (OC) in Hong Kong during the summer of 2006. Secondary organic aerosol (SOA) tracers of several biogenic and anthropogenic hydrocarbons were included in the PMF analysis. Their inclusion allowed the identification of two components of SOA among seven factors resolved by PMF. One SOA component was mainly associated with secondary sulfate and nitrate. The other SOA component, characterized by biogenic SOA tracers and mixed with biomass burning and vegetative detritus particles, was biomass burning‐induced SOA. Secondary OC (SOC) apportioned by PMF (SOCPMF) was on average 6.84 μgC m−3 (65% of PM2.5 OC) on high pollution days under influence of significant regional transport (i.e., regional days) and 0.70 μgC m−3 (25% of PM2.5 OC) on days under the influence of mainly local emissions (i.e., local days). The biomass burning‐induced SOA accounted for 20% of the total SOA on the regional days, underlining the importance of biomass burning aerosol source in this region. The average uncertainty for the SOCPMF estimates was ∼20% on the regional days and ∼120% on the local days. SOCPMF was compared with SOC determined by CMB (SOCCMB, i.e., unapportioned OC by CMB analysis) and a tracer‐based method (SOCTBM) that apportioned SOC contributions by four hydrocarbon precursors including isoprene, monoterpenes, β‐caryophyllene, and toluene. The three estimates of SOC closely tracked with each other among individual samples. The SOCCMB and SOCPMF estimates on the majority of the regional days differed from each other by less than 25%. Good correlations between contributions of SOC and individual primary OC sources apportioned by PMF and CMB further added to the credence to the PMF‐derived estimation of secondary and primary OC source contributions by using secondary and primary aerosol organic tracers as the fitting species.

Comparison of summer and winter California central valley aerosol distributions from lidar and MODIS measurements

Aerosol distributions from two aircraft lidar campaigns conducted in the California Central Valley are compared in order to identify seasonal variations. Aircraft lidar flights were conducted in June 2003 and February 2007. While the ground PM 2.5 (particulate matter with diameter ≤ 2.5 μm) concentration was highest in the winter, the aerosol optical depth (AOD) measured from the MODIS and lidar instruments was highest in the summer. A multiyear seasonal comparison shows that PM 2.5 in the winter can exceed summer PM 2.5 by 68%, while summer AOD from MODIS exceeds winter AOD by 29%. Warmer temperatures and wildfires in the summer produce elevated aerosol layers that are detected by satellite measurements, but not necessarily by surface particulate matter monitors. Temperature inversions, especially during the winter, contribute to higher PM 2.5 measurements at the surface. Measurements of the mixing layer height from lidar instruments provide valuable information needed to understand the correlation between satellite measurements of AOD and in situ measurements of PM 2.5. Lidar measurements also reflect the ammonium nitrate chemistry observed in the San Joaquin Valley, which may explain the discrepancy between the MODIS AOD and PM 2.5 measurements.

Seasonal variations in chemical composition and in vitro biological effects of fine PM from Milan

Fine particulate matter (PM1 and PM2.5) was collected in Milan over the summer (August–September) and winter (January–March) seasons of 2007/2008. Particles were analyzed for their chemical composition (inorganic ions, elements and PAHs) and the effects produced on the human lung carcinoma epithelial cell line A549. In vitro tests were performed to assess cell viability with MTT assay, cytokine release (IL-6 and IL-8) with ELISA, and DNA damage with COMET assay. Results were investigated by bivariate analysis and multivariate data analysis (Principal Component Analysis, PCA) to investigate the relationship between PM chemical composition and the biological effects produced by cell exposure to 12 μg cm −2. The different seasonal chemical composition of PM showed to influence some biological properties. Summer PM samples had a high mass contribution of SO 4 = (13 ± 2%) and were enriched in some elements, like Al, As, Cr, Cu, and Zn, compared to winter PM samples. Cell viability reduction was two times higher for summer PM samples in comparison with winter ones (27 ± 5% and 14 ± 5%, respectively), and the highest correlation coefficients between cell viability reduction and single chemical components were with As ( R 2 = 0.57) and SO 4 = ( R 2 = 0.47). PM1 affected cell viability reduction and induced IL-8 release, and these events were interrelated ( R 2 = 0.95), and apparently connected with the same chemical compounds. PM2.5 fraction, which was enriched in Ca ++ and Mg ++ (from soil dust), and Al, Fe, Zn, Ba Mn, produced cell viability reduction and DNA damage ( R 2 = 0.73).

Spatial and temporal variability of outdoor coarse particulate matter mass concentrations measured with a new coarse particle sampler during the Detroit Exposure and Aerosol Research Study

The Detroit Exposure and Aerosol Research Study (DEARS) provided data to compare outdoor residential coarse particulate matter (PM 10–2.5) concentrations in six different areas of Detroit with data from a central monitoring site. Daily and seasonal influences on the spatial distribution of PM 10–2.5 during Summer 2006 and Winter 2007 were investigated using data collected with the newly developed coarse particle exposure monitor (CPEM). These data allowed the representativeness of the community monitoring site to be assessed for the greater Detroit metro area. Multiple CPEMs collocated with a dichotomous sampler determined the precision and accuracy of the CPEM PM 10–2.5 and PM 2.5 data. CPEM PM 2.5 concentrations agreed well with the dichotomous sampler data. The slope was 0.97 and the R 2 was 0.91. CPEM concentrations had an average 23% negative bias and R 2 of 0.81. The directional nature of the CPEM sampling efficiency due to bluff body effects probably caused the negative CPEM concentration bias. PM 10–2.5 was observed to vary spatially and temporally across Detroit, reflecting the seasonal impact of local sources. Summer PM 10–2.5 was 5 μg m −3 higher in the two industrial areas near downtown than the average concentrations in other areas of Detroit. An area impacted by vehicular traffic had concentrations 8 μg m −3 higher than the average concentrations in other parts of Detroit in the winter due to the suspected suspension of road salt. PM 10–2.5 Pearson Correlation Coefficients between monitoring locations varied from 0.03 to 0.76. All summer PM 10–2.5 correlations were greater than 0.28 and statistically significant ( p-value < 0.05). Winter PM 10–2.5 correlations greater than 0.33 were statistically significant ( p-value < 0.05). The PM 10–2.5 correlations found to be insignificant were associated with the area impacted by mobile sources during the winter. The suspected suspension of road salt from the Southfield Freeway, combined with a very stable atmosphere, caused concentrations to be greater in this area compared to other areas of Detroit. These findings indicated that PM 10–2.5, although correlated in some instances, varies sufficiently across a complex urban airshed that that a central monitoring site may not adequately represent the population's exposure to PM 10–2.5.