Chemical Mass Balance Method Research Articles

Implications of variations in stream specific conductivity for estimating baseflow using chemical mass balance and calibrated hydrograph techniques

Abstract. Baseflow to rivers comprises regional groundwater and lower-salinity intermediate water stores such as interflow, soil water, and bank return flows. Chemical mass balance (CMB) calculations based on the specific conductivity (SC) of rivers potentially estimate the groundwater contribution to baseflow. This study discusses the application of the CMB approach in rivers from south-eastern Australia and assesses the feasibility of calibrating recursive digital filters (RDFs) and sliding minima (SM) techniques based on streamflow data to estimate groundwater inflows. The common strategy of assigning the SC of groundwater inflows based on the highest annual river SC may not always be valid due to the persistent presence of lower-salinity intermediate waters. Rather, using the river SC from low-flow periods during drought years may be more realistic. If that is the case, the estimated groundwater inflows may be lower than expected, which has implications for assessing contaminant transport and the impacts of near-river groundwater extraction. Probably due to long-term variations in the proportion of groundwater in baseflow, the RDF and SM techniques cannot generally be calibrated using the CMB results to estimate annual baseflow proportions. Thus, it is not possible to extend the estimates of groundwater inflows using those methods, although in some catchments reasonable estimates of groundwater inflows can be made from annual streamflows. Short-term variations in the composition of baseflow also lead to baseflow estimates made using the CMB method being far more irregular than expected. This study illustrates that estimating baseflow, especially groundwater inflows, is not straightforward.

An evaluation of source apportionment of fine OC and PM2.5 by multiple methods: APHH-Beijing campaigns as a case study.

This study aims to critically evaluate the source apportionment of fine particles by multiple receptor modelling approaches, including carbon mass balance modelling of filter-based radiocarbon (14C) data, Chemical Mass Balance (CMB) and Positive Matrix Factorization (PMF) analysis on filter-based chemical speciation data, and PMF analysis on Aerosol Mass Spectrometer (AMS-PMF) or Aerosol Chemical Speciation Monitor (ACSM-PMF) data. These data were collected as part of the APHH-Beijing (Atmospheric Pollution and Human Health in a Chinese Megacity) field observation campaigns from 10th November to 12th December in winter 2016 and from 22nd May to 24th June in summer 2017. 14C analysis revealed the predominant contribution of fossil fuel combustion to carbonaceous aerosols in winter compared with non-fossil fuel sources, which is supported by the results from other methods. An extended Gelencsér (EG) method incorporating 14C data, as well as the CMB and AMS/ACSM-PMF methods, generated a consistent source apportionment for fossil fuel related primary organic carbon. Coal combustion, traffic and biomass burning POC were comparable for CMB and AMS/ACSM-PMF. There are uncertainties in the EG method when estimating biomass burning and cooking OC. The POC from cooking estimated by different methods was poorly correlated, suggesting a large uncertainty when differentiating this source type. The PM2.5 source apportionment results varied between different methods. Through a comparison and correlation analysis of CMB, PMF and AMS/ACSM-PMF, the CMB method appears to give the most complete and representative source apportionment of Beijing aerosols. Based upon the CMB results, fine aerosols in Beijing were mainly secondary inorganic ion formation, secondary organic aerosol formation, primary coal combustion and from biomass burning emissions.

Evaluating oil and gas contributions to ambient nonmethane hydrocarbon mixing ratios and ozone-related metrics in the Colorado Front Range

Recently, oil and natural gas (O&NG) production activities in the Denver-Julesburg Basin have expanded rapidly. Associated nonmethane hydrocarbon (NMHC) emissions contribute to photochemical formation of ground-level ozone and include benzene as well as other hazardous air pollutants. Using positive matrix factorization (PMF) and chemical mass balance (CMB) methods, we estimate how much O&NG activities and other sources contribute to morning NMHC mixing ratios measured from 2013 to mid-2016 at a site in Platteville, CO, in the Denver-Julesburg Basin, and at a contrasting site in downtown Denver. A novel adjoint sensitivity analysis method is then used to estimate corresponding contributions to ozone and ozone-linked mortality in the Denver region. Average 6–9 am NMHC mixing ratios in Platteville were seven times higher than those in Denver in 2013 but four times higher in 2016. CMB estimates that O&NG activities contributed to the Platteville (Denver) site an average of 96% (56%) of NMHC on a carbon basis while PMF indicated 92% (33%). Average vehicle-related contributions of NMHC are estimated as 41% by CMB and 53% by PMF in Denver. Estimates of the fractional contribution to potential ozone and ozone-linked mortality from O&NG activities are smaller while those from vehicles are larger than the NMHC contributions. CMB (PMF) indicate that greater than 78% (40%) of annual average benzene in Denver is attributable to vehicle emissions while greater than 75% (67%) of benzene in Platteville is attributable to O&NG activities.

Investigating fine particulate matter sources in Salt Lake City during persistent cold air pool events

During wintertime, Salt Lake City experiences periods of high-pressure atmospheric stagnation that leads to prolonged periods with stable atmospheric boundary layers (ABL) due to the unique orography of the region. These atmospheric conditions typically lead to persistent cold air pool (PCAP) events, where the stable ABL remains over several days, degrading air quality in the Salt Lake Valley. In this work, we applied novel source apportionment methods to identify sources that were the greatest contributors to elevated secondary PM2.5 concentrations during PCAP events in winter 2007. A source-oriented modeling approach that relies on emissions inventory data (i.e., source-specific data) was utilized for source characterization. A correction was applied to chemical transport model (CTM) outputs to improve the estimates of source contributions to secondary PM2.5 components (organic carbon, nitrate, sulfate, and ammonium). As a result, gasoline vehicles (25%), natural gas combustion (21%), and other sources (29%) were identified as the largest sources of nitrate, which was the dominant aerosol component during the PCAP periods ([NO3−]max = 37.5 μg m−3). Further, receptor-oriented source apportionment modeling was conducted using the chemical mass balance method with gas constraints (CMB-GC) with location-specific, mathematically optimized PM2.5 source profiles to examine the multi-year trend in PCAP pollution. These optimized profiles were enhanced by integrating the initial guess profiles with CTM results and observations. CMB-GC was applied for the period 2007–2015 at an urban monitor, and the use of seasonally varying optimized source profiles improved results by resolving more mass than when using static source profiles, increasing the predicted-observed PM2.5 mass ratio from 0.91 to 1.03. The averaged biomass burning impacts exhibited the most significant change, increasing from an average of 0.85 to 1.87 μg m−3 when using the static profiles and the optimized profiles, respectively. The static and optimized CMB-GC results were similar for secondary components but differed slightly for mobile impacts. Stratification of PCAP vs. non-PCAP CMB-GC source impacts revealed that the dominant sources of PM2.5 varied under the two meteorological conditions.

An Amended Chemical Mass Balance Model for Source Apportionment of PM2.5 in Typical Chinese Eastern Coastal Cities

An adequate air quality analysis requires interpretation regarding not only how severe pollution is but also how the pollution is formed. In this work, an amendment to the chemical mass balance (CMB) model is proposed to obtain better source apportionment of PM2.5. First, localized PM2.5 source profiles for Chinese eastern coastal cities are obtained by in situ sampling. Then, a judgment diagram is established for quick preliminary judgment. CMB models, including an original standard model and an amended two‐step model, are applied to apportion highly mixed samples. For the amended CMB model, simulation is first executed with the ratios of metal elements to Al, to apportion windowsill dust into soil dust, road dust, construction dust, and vehicle dust. Then, a virtual mixed source profile was built with the proportion ratio. The second CMB model is executed to apportion ambient dust based on the virtual mixed source profile instead of divided dusts. Finally, the proportions of soil dust, road dust, and construction dust are obtained by redistributing the virtual mixed sources within ambient dust. The modeling results show that the amended CMB method could separate different fugitive dusts and obtain reasonable results: secondary sulfate contributes the most to PM2.5 pollution in Chinese eastern coastal cities at 44.50%, followed by vehicle exhaust dust and ammonium nitrate; the fugitive dusts are more precisely apportioned and soil dust, road dust, construction dust, and windowsill dust contribute 2.24, 0.47, 0.09, and 1.84%, respectively.

Source apportionment of fine particulate matter organic carbon in Shenzhen, China by chemical mass balance and radiocarbon methods

Chemical mass balance (CMB) modeling and radiocarbon measurements were combined to evaluate the sources of carbonaceous fine particulate matter (PM2.5) in Shenzhen, China during and after the 2011 summer Universiade games when air pollution control measurements were implemented to achieve air quality targets. Ambient PM2.5 filter samples were collected daily at two sampling sites (Peking University Shenzhen campus and Longgang) over 24 consecutive days, covering the controlled and uncontrolled periods. During the controlled period, the average PM2.5 concentration was less than half of what it was after the controls were lifted. Organic carbon (OC), organic molecular markers (e.g., levoglucosan, hopanes, polycyclic aromatic hydrocarbons), and secondary organic carbon (SOC) tracers were all significantly lower during the controlled period. After pollution controls ended, at Peking University, OC source contributions included gasoline and diesel engines (24%), coal combustion (6%), biomass burning (12.2%), vegetative detritus (2%), biogenic SOC (from isoprene, α-pinene, and β-caryophyllene; 7.1%), aromatic SOC (23%), and other sources not included in the model (25%). At Longgang after the controls ended, similar source contributions were observed: gasoline and diesel engines (23%), coal combustion (7%), biomass burning (17.7%), vegetative detritus (1%), biogenic SOC (from isoprene, α-pinene, and β-caryophyllene; 5.3%), aromatic SOC (13%), and other sources (33%). The contributions of the following sources were smaller during the pollution controls: biogenic SOC (by a factor of 10–16), aromatic SOC (4–12), coal combustion (1.5–6.8), and biomass burning (2.3–4.9). CMB model results and radiocarbon measurements both indicated that fossil carbon dominated over modern carbon, regardless of pollution controls. However, the CMB model needs further improvement to apportion contemporary carbon (i.e. biomass burning, biogenic SOC) in this region. This work defines the major contributors to carbonaceous PM2.5 in Shenzhen and demonstrates that control measures for primary emissions could significantly reduce secondary organic aerosol (SOA) formation.

A hybrid source apportionment strategy using positive matrix factorization (PMF) and molecular marker chemical mass balance (MM-CMB) models

The molecular marker-based chemical mass balance (MM-CMB) method performs well in the source apportionment of organic carbon (OC) but has some difficulty with contributions from primary sources to inorganic secondary ions when apportioning PM2.5 (particles with aerodynamic diameter of 2.5 μm or less) sources. Positive matrix factorization (PMF) with the input of inorganic and organic tracers can properly estimate the contributions of primary and secondary sources to inorganic secondary ions; however, PMF is unable to apportion several PM2.5 sources with large fractions of organic carbon and few elemental compositions. In this study regarding data collected in 2011 and 2012 at three sites in Wuhan, China, the MM-CMB model was used to apportion OC in the PM2.5, and the PMF model was used to apportion the inorganic ions (sulfate, nitrate, and ammonia), dust, and EC. The source contributions of PM2.5 were estimated by reconstructing masses of bulk chemical components that had been apportioned to real-world sources using suitable source apportionment methods. Good performance of this hybrid source apportionment strategy was observed with ten resolved factors, explaining 70–80% of measured PM2.5 mass on average. The hybrid strategy takes the advantages of both models in PM2.5 source apportionment and yields unique source apportionment results for PM2.5 bulk chemical components, which could provide new information for optimizing air quality regulations for the emission abatement of target PM mass and compositions for countries around the world.

Impact of low denudation rates on soil chemical weathering intensity: A multiproxy approach

Quantifying the influence of denudation, i.e., physical erosion and chemical weathering, on soil weathering intensity is an important component for a comprehensive understanding of element biogeochemical cycles. The relation between the weathering intensity and the denudation rate is not clear and requires further investigation in a variety of climatic and erosional settings. Here, in the Betic Cordillera (southern Spain), we assess the soil chemical weathering intensity with a multiproxy approach combining different indicators of chemical weathering of the soil: the Total Reserve in Bases (TRB), the content in Fe-oxides, the quartz and clay content, the soil cation exchange capacity (CEC), and the silicon (Si) isotope composition of the clay-sized fraction. Our multiproxy approach demonstrates that in this semi-arid environment at low denudation rates, an increasing denudation rate decreases the soil weathering intensity, whereas Si mobility remains limited. Our results converge with previous conclusions based on chemical mass balance methods in the same geological setting. Mass balance methods, and particularly Chemical Depletion Fractions (CDF), are based on the immobility of a refractory element (commonly zirconium, Zr) relative to major cations in soils. Interestingly, our study suggests that a weathering index such as the TRB may provide a useful complement to assess soil chemical weathering intensity in eroding landscapes where the application of chemical mass balances may be hampered by potential Zr mobility in the soil or by heterogeneity of Zr concentrations in the bedrock.

Attributing Atmospheric Methane to Anthropogenic Emission Sources.

Methane is a greenhouse gas, and increases in atmospheric methane concentration over the past 250 years have driven increased radiative forcing of the atmosphere. Increases in atmospheric methane concentration since 1750 account for approximately 17% of increases in radiative forcing of the atmosphere, and that percentage increases by approximately a factor of 2 if the effects of the greenhouse gases produced by the atmospheric reactions of methane are included in the assessment. Because of the role of methane emissions in radiative forcing of the atmosphere, the identification and quantification of sources of methane emissions is receiving increased scientific attention. Methane emission sources include biogenic, geogenic, and anthropogenic sources; the largest anthropogenic sources are natural gas and petroleum systems, enteric fermentation (livestock), landfills, coal mining, and manure management. While these source categories are well-known, there is significant uncertainty in the relative magnitudes of methane emissions from the various source categories. Further, the overall magnitude of methane emissions from all anthropogenic sources is actively debated, with estimates based on source sampling extrapolated to regional or national scale ("bottom-up analyses") differing from estimates that infer emissions based on ambient data ("top-down analyses") by 50% or more. To address the important problem of attribution of methane to specific sources, a variety of new analytical methods are being employed, including high time resolution and highly sensitive measurements of methane, methane isotopes, and other chemical species frequently associated with methane emissions, such as ethane. This Account describes the use of some of these emerging measurements, in both top-down and bottom-up methane emission studies. In addition, this Account describes how data from these new analytical methods can be used in conjunction with chemical mass balance (CMB) methods for source attribution. CMB methods have been developed over the past several decades to quantify sources of volatile organic compound (VOC) emissions and atmospheric particulate matter. These emerging capabilities for making measurements of methane and species coemitted with methane, rapidly, precisely, and at relatively low cost, used together with CMB methods of source attribution can lead to a better understanding of methane emission sources. Application of the CMB approach to source attribution in the Barnett Shale oil and gas production region in Texas demonstrates both the importance of extensive and simultaneous source testing in the region being analyzed and the potential of CMB method to quantify the relative strengths of methane emission sources.

Oxidative potential of ambient water-soluble PM<sub>2.5</sub> in the southeastern United States: contrasts in sources and health associations between ascorbic acid (AA) and dithiothreitol (DTT) assays

Abstract. The ability of certain components of particulate matter to induce oxidative stress through the generation of reactive oxygen species (ROS) in vivo may be one mechanism accounting for observed linkages between ambient aerosols and adverse health outcomes. A variety of assays have been used to measure this so-called aerosol oxidative potential. We developed a semi-automated system to quantify oxidative potential of filter aqueous extracts utilizing the dithiothreitol (DTT) assay and report here the development of a similar semi-automated system for the ascorbic acid (AA) assay. Approximately 500 PM2.5 filter samples collected in contrasting locations in the southeastern US were analyzed for a host of aerosol species, along with AA and DTT activities. We present a detailed contrast in findings from these two assays. Water-soluble AA activity was higher in summer and fall than in winter, with highest levels near heavily trafficked highways, whereas DTT activity was higher in winter compared to summer and fall and more spatially homogeneous. AA activity was nearly exclusively correlated with water-soluble Cu (r = 0.70–0.94 at most sites), whereas DTT activity was correlated with organic and metal species. Source apportionment models, positive matrix factorization (PMF) and a chemical mass balance method with ensemble-averaged source impact profiles (CMB-E), suggest a strong contribution from traffic emissions and secondary processes (e.g., organic aerosol oxidation or metals mobilization by secondary acids) to both AA and DTT activities in urban Atlanta. In contrast, biomass burning was a large source for DTT activity, but insignificant for AA. AA activity was not correlated with PM2.5 mass, while DTT activity co-varied strongly with mass (r = 0.49–0.86 across sites and seasons). Various linear models were developed to estimate AA and DTT activities for the central Atlanta Jefferson Street site, based on the CMB-E sources. The models were then used to estimate daily oxidative potential at this site over the 1998–2009 period. Time series epidemiological analyses were conducted to assess daily emergency department (ED) visits data for the five-county Atlanta metropolitan area based on the estimated 10-year backcast oxidative potential. Estimated AA activity was not statistically associated with any tested health outcome, while DTT activity was associated with ED visits for both asthma or wheeze and congestive heart failure. The findings point to the importance of both organic components and transition metals from biomass burning and mobile sources to adverse health outcomes in this region.

Comparison and Evaluation of Methods to Apportion Ambient PM2.5 to Residential Wood Heating in Fairbanks, AK

Biomass burning for residential heating significantly contributes to ambient PM_(2.5) burdens in many areas, making source apportionment to wood heater emissions an important issue. This study compares and evaluates Chemical Mass Balance (CMB), levoglucosan analysis, and ^(14)C analysis methods for apportionment. Results suggest that the CMB method appears to overestimate the contribution of residential wood heating in Fairbanks, perhaps due to non-representativeness of emissions source profiles. Carbon-14 analysis allows for apportionment to biomass sources, but must be corrected for noncarbon PM_(2.5) content. Levoglucosan analysis has the advantage of being relatively inexpensive, but there is considerable uncertainty in determining conversion factors to calculate wood smoke levels from measured levoglucosan concentrations. Conversion factors in the range of 9.1 to 13.3 are calculated from previously published and experimental mass fractions of levoglucosan in wood smoke PM_(2.5). Conversion factors in the range of 10.7 to 12.9 are determined from analysis of independent field measurements of ^(14)C and levoglucosan in Fairbanks. The calculated and measured conversion factors are consistent and are similar to previously-reported values. The three apportionment methods (focused on residential wood smoke contributions) are complementary and collectively provide a means to evaluate or confirm apportionment results.

Reactive Oxygen Species Generation Linked to Sources of Atmospheric Particulate Matter and Cardiorespiratory Effects.

Exposure to atmospheric fine particulate matter (PM2.5) is associated with cardiorespiratory morbidity and mortality, but the mechanisms are not well understood. We assess the hypothesis that PM2.5 induces oxidative stress in the body via catalytic generation of reactive oxygen species (ROS). A dithiothreitol (DTT) assay was used to measure the ROS-generation potential of water-soluble PM2.5. Source apportionment on ambient (Atlanta, GA) PM2.5 was performed using the chemical mass balance method with ensemble-averaged source impact profiles. Linear regression analysis was used to relate PM2.5 emission sources to ROS-generation potential and to estimate historical levels of DTT activity for use in an epidemiologic analysis for the period of 1998-2009. Light-duty gasoline vehicles (LDGV) exhibited the highest intrinsic DTT activity, followed by biomass burning (BURN) and heavy-duty diesel vehicles (HDDV) (0.11 ± 0.02, 0.069 ± 0.02, and 0.052 ± 0.01 nmol min(-1) μg(-1)source, respectively). BURN contributed the largest fraction to total DTT activity over the study period, followed by LDGV and HDDV (45, 20, and 14%, respectively). DTT activity was more strongly associated with emergency department visits for asthma/wheezing and congestive heart failure than PM2.5. This work provides further epidemiologic evidence of a biologically plausible mechanism, that of oxidative stress, for associations of adverse health outcomes with PM2.5 mass and supports continued assessment of the utility of the DTT activity assay as a measure of ROS-generating potential of particles.

Outdoor PM₁₀ source apportionment in metropolitan cities--a case study.

This study was carried out to specify contribution of different sources in PM10 emission in Tehran City using chemical mass balance method. This is the first time that this method is used in Iran. To this end, the metallic elements including V, Ni, As, Pb, Cd, Hg, Mn, Al, Ca, K, Na, Fe, Zn, Sc, and S were sampled on the filters of high-volume sampler installed at four stations in Tehran. Afterward, highly sensitive inductively coupled plasma (ICP-M90; model aurora-Elit) was used to determine concentration of the elements precipitated on the filters. The obtained results were then compared with standard values. According to the results, the concentration of Cd (16.8 ng/m(3)) was higher than the standard level of 5 ng/m(3) at District 16 on November 14th 2012 which is almost three times the permissible limit. None of the elements Pb, Mn, V, and Hg exceeded the permissible limits except for Ni at District 16. Subsequently, the enrichment factor of the elements was calculated to indicate that elements of anthropogenic origins (Zn, S, Ni, and Hg) are highly enriched with respect to crustal composition (Na, Fe, and Ca). Exceedance factor were calculated for elements of each site to show that all study sites were in low-pollution category. Afterward, the contribution of different pollution sources of road dust, vehicles, and industries in emission of outdoor PM10 was investigated through chemical mass balance (CMB) method. According to which, the highest contribution comes from road dust with a share of 95.4 % of the total outdoor PM10 emission in Tehran mainly originated from the wear and friction of car tires with asphalt pavement. High calcium concentration in all districts of the city confirms the claim. Furthermore, transportation, with a significant difference, has a contribution of 4.05 % of total outdoor PM10 released while industries share very little about 0.4 %. In overall, the quality of road pavement could be a determining factor in releasing considerable amount of outdoor PM10 in urban areas.

Temporal Variation and Source Analysis of Radiocesium in an Urban River after the 2011 Nuclear Accident in Fukushima, Japan

The release of radiocesium from the Fukushima Dai-ichi Nuclear Power Plant caused environmental contamination. We analyzed sources, behavior, and temporal trends of radiocesium by 1-year monitoring in an urban river, the Ohori River. The concentrations of 137Cs in both particulate and dissolved phases decreased to ~ 16% within 1 year. The partition coefficient in dry weather was estimated to be 3.2 × 104 L/kg. 137Cs concentrations in the particulate phase were higher during wet weather than during dry weather on the basis of both suspended solids (SS) weight and liquid volume. The ratios of 137Cs concentration to deposited 137Cs in the Ohori River (e.g., composite: 0.26 m2/kg-SS in June - July 2012) were higher than those in the Abukuma River, probably because of differences in land use. Source analysis by a chemical mass balance method showed that 22% of 137Cs came from river water in dry weather, 39% from river sediments, and 39% from road dust highlighting urban surface deposits such as road dust as major sources of 137Cs in the river water even 2 years after the accident, and that the wash-off of these deposits increased the 137Cs concentration in the river during wet weather.

Carbon dioxide flux in the ablation area of Koxkar glacier, western Tien Shan, China

AbstractAccelerating loss of glacial mass caused by rising global temperatures has significant implications. The global cycle of the greenhouse gas CO2 is also associated with mineral weathering and glaciation. In glaciated areas, most estimates of atmospheric CO2 consumption are confined to chemical ionic mass balance or analog modeling methods. We applied the gradient method to the surface of Koxkar glacier, western Tien Shan, China, for a 5 month period during 2012. The overall net glacier-system CO2 exchange (NGE) rate was measured as -0.05 and -0.07mmol m–2 s–1 for regions of exposed ice and supraglacial moraine, respectively. This suggests that atmospheric CO2 drawdown may occur during ice melting because of consumption of H+ by CO2 hydrolysis that occurs in solutions. Using the degree-day model to calculate glacier ablation in bare-ice regions and considering characteristics of the NGE rate in the supraglacial debris region with the support of GIS, the daily NGE rate was estimated to be -1.23 ± 0.17μmmol m–2 d–1 between Julian days 125 and 268 of 2012. These findings present a new approach for modeling the dynamics of glacial CO2 sinks undergoing melting, and develop an understanding of the mechanism of atmospheric CO2 exchange.

Storm Water Pollution Source Identification in Washington, DC, Using Bayesian Chemical Mass Balance Modeling

A Bayesian chemical mass balance (CMB) model was used to identify the sources of heavy metals in a highly urbanized area at the vicinity of the Anacostia River in Washington, DC. This method uses the elemental profiles of potential sources and the storm water runoff samples at two outfalls into the Anacostia River to infer the contribution of each source by providing the joint probability densities of the contribution of each source and the credible intervals of the inference. For this purpose, the potential sources of heavy metals in the urban catchment were identified and multiple samples of each were collected and analyzed by using an inductively coupled plasma mass spectrometry technique to determine their elemental profiles. Next, a Bayesian CMB method was employed to infer the contribution of various sources to the storm water runoff. The results of the analysis revealed that paved surfaces that accommodate traffic (i.e., street, bridge, and parking lot) are the major contributors to both dissolved and particulate metals in storm water. It was also found that for both dissolved fraction and total pollutants, the wet deposition source has a small contribution to all elements and that the runoff originating from roofs can be responsible for up to 50% of the Pb in the storm water.

Source Attribution of Air Pollutant Concentrations and Trends in the Southeastern Aerosol Research and Characterization (SEARCH) Network

A new approach for determining the contributions of emission sources to trends in concentrations of particulate matter and gases is developed using the chemical mass balance (CMB) method and the U.S. EPA's National Emission Inventory (NEI). The method extends our earlier analysis by using temporally varying emission profiles and includes accounting of primary and secondary particulate organic carbon with an empirical regression calculation. The model offers a potentially important tool for verifying that annual emission reductions by major source category have yielded changes in ambient pollutant concentrations. Using long-term measurements from well-instrumented monitoring sites, observed trends in ambient pollutant concentrations at urban and rural locations can be attributed to emission changes. Trends apportionment is conducted on 2000-2011 ambient monitoring data from the SEARCH network with NEI emissions data adjusted to improve interinventory consistency. The application accounts for major source category influences in southeastern U.S. regional trends; local anomalies are noted. In the SEARCH region, open burning is important as a source of CO and carbonaceous particles. Improved agreement between predicted and measured particulate carbon is obtained by increasing mobile diesel exhaust and area-source particulate carbon emissions by 1 and 20%, respectively, compared with NEI values. The method is general and is applicable to data from any monitoring site that is instrumented for criteria air pollutants, associated gases, and particle composition.

Combined use of WEPS and Models-3/CMAQ for simulating wind erosion source emission and its environmental impact

The wind erosion source is the greatest contributor of PM10 in Tianjin, China. It is difficult to establish a PM10 emission inventory for the wind erosion source because of the complicated conditions affecting PM10 emissions from wind erosion. In this study, a novel method is developed to establish a PM10 emission inventory for the wind erosion source by using the Wind Erosion Prediction System (WEPS) model with 1×1km spatial resolution. In 2011, the average annual emission of PM10 in Tianjin was 0.373 tons km−2 (1.113 tons km−2 in the heating period, 0.237 tons km−2 in the sand period, and 0.013 tons km−2 in the non-heating period), and the total PM10 emission was 904,871.6 tons (221,080.7 tons in the heating period, 52,977.8 tons in the sand period, and 1953.2 tons in the non-heating period). After establishing the PM10 emission inventory for the wind erosion source in this manner, the data were input into Model-3/SMOKE. The contribution of the PM10 concentration from the wind erosion source was estimated using the Community Multi-scale Air Quality (Model-3/CMAQ) model and was compared with the monitoring value and the source apportionment results using the chemical mass balance (CMB) method. For this comparison, over the entire year, the R2 was 0.711. More specifically, R2 was 0.664, 0.733, and 0.679 in the heating, non-heating, and sand periods, respectively. Thus, we have obtained a reliable method for estimating the source of PM10 from wind erosion.

Source Apportionment of Particulate Air Pollution and Percentage Contribution of PM10 and PM2.5 Using Chemical Mass Balance (CMB) Method

The study is to analyze the concentration of particulate pollutants level and its monitoring, there fore suggesting controlling measures of particulate pollution at Virudhunagar in Tamilnadu. This work summarized the results of a series of comprehensive studies on particulate matter carried out in study area from 2010 to 2011. The air quality has been categorized into four broad categories based on an Exceedence Factor (EF) of measured concentration of pollutants. It could be seen from the categorization, that all the study sites were violating the standards, although, with varying magnitude. The concentration of particulate matter PM10 and PM2.5 was statistically analyzed and higher concentration of pollutants observed during the months of April and May. Overall high concentration of particulates observed during summer at site 2. There is no considerable variation of concentration of particulates was observed at site 3 during all the three seasons. In the available receptor models, chemical mass balance(CMB) method was utilized for this study. This modeling involves quantitative assessment of source contributions to the measured ambient samples based on the degree to which source profiles can be combined to produce ambient concentrations. Particulate samples collected from all the three locations were subjected to chemical speciation. The composition of the data was analyzed and divided into three categories to correlate with the sources. Sources identified as major contributors to particulate pollution were fugitive dust on roads and construction sites, vehicular exhaust, biomass burning at residential and road side trash. The monitoring and analysis results were utilized to strengthen the need for a faster and effective pollution control action plan for the study area. Keyword: PM10, CMB, Virudhunagar, Particulate matter, Exceedence factor, Critical pollution

Bayesian Chemical Mass Balance Method for Surface Water Contaminant Source Apportionment

AbstractA Bayesian chemical mass balance (CMB) source apportionment method is developed using the Markov Chain Monte Carlo (MCMC) approach. Compared with deterministic approaches, the Bayesian method is capable of accounting for the measurement errors and the impact of variability of the source elemental compositions resulting from the heterogeneities and estimate the uncertainties associated with the estimated source contributions. The method estimates the joint probability densities and consequently, the credible intervals and correlation matrices of source contributions of various sources into a receiving water using observed elemental profiles of samples from both potential sources and the receiving surface waters. The model is applied to samples collected from possible sources and runoff and stream flow from two stream crossing sites along Highway 89 in the Lake Tahoe Basin. The contributing sources of total dissolved nitrogen, total dissolved phosphorus concentrations, and microparticles (<20 μm) f...