Future year ozone source attribution modeling study using CMAQ-ISAM

ABSTRACT

To achieve the current United States National Ambient Air Quality Standards (NAAQS) attainment level for ozone or particulate matter, current photochemical air quality models include tools to determine source apportionment and/or source sensitivity. Previous studies by the authors have used the Ozone and Particulate Matter Source Apportionment Technology and Higher-order Decoupled Direct Method probing tools in CAMx to investigate these source-receptor relationships for ozone. The recently available source apportionment for CMAQ, referred to as the Integrated Source Apportionment Method (ISAM), was used in this study to conduct future year (2030) source attribution modeling. The CMAQ-ISAM ozone source attribution results for selected cities across the U.S. showed boundary conditions were the dominant contributor to the future year highest July maximum daily 8-hour average (MDA8) ozone concentrations. Point sources were generally larger contributors in the eastern U.S. than in the western U.S. The contributions of on-road mobile emissions were around 5 ppb at most of the cities selected for analysis. Off-road mobile source contributions were around 20 ppb or nearly 30%. Since boundary conditions play an important role in future year ozone levels, it is important to characterize future year boundary conditions accurately. The current implementation of ISAM in CMAQ 5.0.2 requires significant computing resources for ozone source attribution, making it difficult to conduct long-term simulations for large domains. The computing requirements for PM source attribution are even more onerous. CMAQ 5.2 was released after this study was completed, and does not include ISAM. If an efficient version of ISAM becomes available, it could be used in long-term ozone and PM2.5 studies. Implications: Ozone source attribution results provide useful information on important emission source contribution categories and provide some initial guidance on future emission reduction strategies. This study explains a new source apportionment technique, CMAQ-ISAM, and compares it to CAMx OSAT. The techniques have similar results: ozone’s highest source contributor is boundary conditions, followed by point sources, then off-road mobile sources. The current version of ISAM in CMAQ 5.0.2 requires significant computing resources for ozone source attribution, while the computing requirements for PM source attribution are even more onerous. CMAQ 5.2 was released after this study was completed, and does not include ISAM.     

The effect of nutrients shortage on plant’s efficiency to capture solar radiations under semi-arid environments

Radiation use efficiency (RUE) is considered critical for calculation of crop yield. The crop productivity can be improved by increasing the interception of solar radiation and maintaining higher RUE for plants. Irrigation water and nitrogen (N) supply are the main limiting factors for RUE in maize (Zea mays L.) across the semi-arid environments. Field experiments were conducted during two consecutive growing seasons (2009–2010) to optimize RUE in relation to N application timings and rates with varying irrigation water management practices. In experiment 1, three N application timings were made, while in experiment 2, three possible water management practices were used. In both experiments, five N rates (100, 150, 200, 250, and 300 kg N ha⁻¹) were applied to evaluate the effects of irrigation water and N on cumulative photosynthetic active radiation (PARi), dry matter RUE (RUE_DM), and grain yield RUE (RUE_GY). The results demonstrated that cumulative PARi and RUEs were not constant during the plant growth under varying the nutrients. The water and N significantly influenced cumulative PARi and RUEs during the both growing seasons. In experiment 1, the maximum cumulative PARi was observed by application of 250 kg N ha⁻¹ in three splits (1/3 N at V2, 1/3 N at V16, and 1/3 N at R1 stage), and the highest RUE_DM was achieved by the application of 300 kg N ha⁻¹. However, the highest RUE_GY was observed by application of 250 kg N ha⁻¹. In experiment 2, the maximum cumulative PARi was attained at normal irrigation regime with 250 kg N ha⁻¹, while the highest RUE_DM and RUE_GY were recorded at normal irrigation regime with the application of 300 kg N ha⁻¹. The regression analysis showed significant and positive correlation of RUE_GY with grain yield. Therefore, optimum water and N doses are important for attaining higher RUE, which may enhance maize grain yield semi-arid environment; this may be considered in formulating good agricultural practices for the environmental conditions resembling to those of this study.

     

Adsorptive amputation of hazardous azo dye Congo red from wastewater: a critical review

Increasing amount of dyes in an ecosystem has propelled the search of various methods for dye removal. Amongst all the methods, adsorption occupies a prominent place in dye removal. Keeping this in mind, many adsorbents used for the removal of hazardous anionic azo dye Congo red (CR) from aqueous medium were reviewed by the authors. The main objectives behind this review article are to assemble the information on scattered adsorbents and enlighten the wide range of potentially effective adsorbents for CR removal. Thus, CR sorption by various adsorbents such as activated carbon, non-conventional low-cost materials, nanomaterials, composites and nanocomposites are surveyed and critically reviewed as well as their sorption capacities are also compared. This review also explores the grey areas of the adsorption performance of various adsorbents with reference to the effects of pH, contact time, initial dye concentration and adsorbent dosage. The equilibrium adsorption isotherm, kinetic and thermodynamic data of different adsorbents used for CR removal were also analysed. It is evident from a literature survey of more than 290 published papers that nanoparticle and nanocomposite adsorbents have demonstrated outstanding adsorption capabilities for CR.

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A context-intensive approach to imputation of missing values in data sets from networks of environmental monitors

Although networks of environmental monitors are constantly improving through advances in technology and management, instances of missing data still occur. Many methods of imputing values for missing data are available, but they are often difficult to use or produce unsatisfactory results. I-Bot (short for “Imputation Robot”) is a context-intensive approach to the imputation of missing data in data sets from networks of environmental monitors. I-Bot is easy to use and routinely produces imputed values that are highly reliable. I-Bot is described and demonstrated using more than 10 years of California data for daily maximum 8-hr ozone, 24-hr PM_2.5 (particulate matter with an aerodynamic diameter <2.5 μm), mid-day average surface temperature, and mid-day average wind speed. I-Bot performance is evaluated by imputing values for observed data as if they were missing, and then comparing the imputed values with the observed values. In many cases, I-Bot is able to impute values for long periods with missing data, such as a week, a month, a year, or even longer. Qualitative visual methods and standard quantitative metrics demonstrate the effectiveness of the I-Bot methodology.Implications: Many resources are expended every year to analyze and interpret data sets from networks of environmental monitors. A large fraction of those resources is used to cope with difficulties due to the presence of missing data. The I-Bot method of imputing values for such missing data may help convert incomplete data sets into virtually complete data sets that facilitate the analysis and reliable interpretation of vital environmental data.     

Household preferences and willingness to pay (WTP) for freshwater quality improvement in Pakistan’s Swat River Valley

This two-part study investigates household preferences and willingness to pay (WTP) for water quality improvement of the Swat River in Pakistan. First, a four-point Likert scale was used to rank preferences for water quality benefits without using any financial metric. Results show that households have comparatively strong preferences for non-use benefits. Second, a contingent valuation question was designed to determine WTP for adopting a management plan developed exclusively for water quality improvement in the Swat River. The estimated annual mean WTP per household for water quality improvement is $2.40 when donating to an NGO. Generalizing this value to households living in Swat Valley would generate up to $544,000 per year. The present value aggregate benefit for 15 years would be sufficient to cover the present value of aggregate costs to adopt the management plan. A mandatory program that would require paying for the management plan generates half the WTP compared to the voluntary plan, but is still sufficient to cover costs and may be more feasible than a voluntary program because payment is assured.     

Flow injection spectrophotometric determination of methamidophos using online hydrolysis

A new protocol for the online spectrophotometric determination of methamidophos has been developed. The method is based on online hydrolysis of methamidophos, and the resulting hydrolyzed product is reacted with sodium nitroproside to form a colored complex. The calibration curve is linear over the concentration range of 0.5–20 μgml^?–?1, with a molar absorptivity of 2.5×10⁴ L mol^?1 cm^?1. The method is fast and reproducible with a sample throughput of 90 samples/h. The method is successfully applied to formulations and real samples.     

Determination of ametryn in sugarcane and ametryn–atrazine herbicide formulations using spectrophotometric method

A sensitive spectrophotometric method has been developed for determination of ametryn in agricultural samples. The proposed method was based on reaction with pyridine and further coupling with sulfanilic acid to form a colored product. The absorbance was measured at 400 nm with a molar absorptivity of 2.1 × 10⁵ L mol⁻¹ cm⁻¹. The method shows a linear range from 0.2–20 μg mL⁻¹ with limit of detection and limit of quantification 0.16 and 0.54 μg mL⁻¹, respectively. The method has been successfully applied to the determination of ametryn in sugarcane juice and commercial formulations after separation of ametryn from triazine herbicides based on solvent extraction. Recovery values were found to be in the range of 96.0 ± 0.2% to 98.4 ± 0.1%.     

Statistical apportionment and risk assessment of selected metals in sediments from Rawal Lake (Pakistan)

The present study was carried out in order to evaluate the statistical apportionment and risk assessment of selected metals (Ca, Cd, Co, Cr, Cu, Fe, K, Li, Mg, Mn, Na, Pb, Sr, and Zn) in freshly deposited sediments in Rawal Lake, Pakistan. Composite sediment samples were collected, oven-dried, grounded, homogenized, and processed to assess the water-soluble and acid extractable concentrations of the metals in the water extract and acid extract of the sediments using flame atomic absorption spectrophotometer. Statistical methods were used to identify the possible sources of the metals. Sediment quality guidelines and potential acute toxicity were used to evaluate the ecotoxicological sense of selected metals. Non-carcinogenic health risk assessment was also carried out to determine the potential adverse health risks to the inhabitants. Relatively higher concentration was noted for Ca, Fe, Mg, Na, K, Mn, and Sr in the sediment samples. Principal component analysis and cluster analysis revealed anthropogenic contributions of Cd, Pb, Cr, Mn, Fe, and Li in the sediments. Enrichment factors of the metals in sediments showed severe to moderate enrichment of Cd, Pb, Ca, Fe, Li, Mn, and Sr. Geoaccumulation indices and contamination factors evidenced significant contamination by Cd and Pb, although, on the whole, low degree of contamination was noted. The levels of some metals exceeded the sediment quality guidelines, which revealed frequently adverse biological effects to the dwelling biota in the aquatic ecosystem. The sediments were found to be significantly contaminated by Cd, Pb, Cr, Mn, Fe, and Li.     

Mean Vehicle Speed Distributions for the Spatiotemporal Estimation of Exhaust Emissions

Link Emissions Models estimate traffic-related air pollution emissions at the individual road link level and inform governmental policies for air quality management. The current South Australian Link Emissions Model (CLEM) assumes constant spatiotemporal traffic flow at a single fixed mean speed, a potential limitation as the variability of exhaust emissions with vehicle speed has been established in the literature.We extend CLEM to eliminate the assumption of constant traffic flow, through the derivation of mean Australian vehicle speed distributions for different road types. Specifically, we successfully model the vehicle speed profile data from the second National In-Service Emissions study using Nearest Neighbour Kernel Density Estimation. We propose a mean speed Distribution Link Emissions Model (DLEM) for exhaust emission estimation based on the derived mean speed distributions. DLEM is an augmented, enhanced version of CLEM, accommodating a range of vehicle speeds and road types. The performance of the extended model, DLEM, is analysed in comparison to the current model, CLEM, through a case study analysis of vehicle exhaust emissions on a typical arterial road in Adelaide, South Australia. Results indicate use of DLEM and, by extension, mean vehicle speed distributions, has a strong impact on emission estimation. In particular, the fixed speed model, CLEM, may be substantially underestimating exhaust emissions of carbon monoxide, non-methane volatile organic compounds and particulate matter less than 2.5 μm in diameter. These are common exhaust pollutants that have been extensively linked with adverse health effects including respiratory morbidity and premature mortality.