The effect of diesel fuel sulfur content on particulate matter emissions for a nonroad diesel generator

The effect of sulfur content on diesel particulate matter (DPM) emissions was studied using a diesel generator (Generac Model SD080, rated at 80 kW) as the emission source to simulate nonroad diesel emissions. A load simulator was used to apply loads to the generator at 0, 25, 50, and 75 kW, respectively. Three diesel fuels containing 500, 2100, and 3700 ppm sulfur by weight were selected as generator fuels. The U.S. Environmental Protection Agency sampling Method 5 "Determination of Particulate Matter Emissions from Stationary Sources" together with Method 1A "Sample and Velocity Traverses for Stationary Sources with Small Stacks or Ducts" was adopted as a reference method for measurement of the exhaust gas flow rate and DPM mass concentration. The effects of various parameters on DPM concentration have been studied, such as fuel sulfur contents, engine loads, and fuel usage rates. The increase of average DPM concentrations from 3.9 mg/Nm3 (n cubic meter) at 0 kW to 36.8 mg/Nm3 at 75 kW is strongly correlated with the increase of applied loads and sulfur content in the diesel fuel, whereas the fuel consumption rates are only a function of applied loads. An empirical correlation for estimating DPM concentration is obtained when fuel sulfur content and engine loads are known for these types of generators: Y = Zm(alphaX + beta), where Y is the DPM concentration, mg/m3, Z is the fuel sulfur content, ppm(w) (limited to 500-3700 ppm(w)), X is the applied load, kW, m is the constant, 0.407, alpha and beta are the numerical coefficients, 0.0118 +/- 0.0028 (95% confidence interval) and 0.4535 +/- 0.1288 (95% confidence interval), respectively.     

Control of diesel gaseous and particulate emissions with a tube-type wet electrostatic precipitator

In this study, experiments were performed with a bench-scale tube-type wet electrostatic precipitator (wESPs) to investigate its effectiveness for the removal of mass- and number-based diesel particulate matter (DPM), hydrocarbons (HCs), carbon monoxide (CO), and oxides of nitrogen (NOx) from diesel exhaust emissions. The concentration of ozone (O3) present in the exhaust that underwent a nonthermal plasma treatment process inside the wESP was also measured. A nonroad diesel generator operating at varying load conditions was used as a stationary diesel emission source. The DPM mass analysis was conducted by means of isokinetic sampling and the DPM mass concentration was determined by a gravimetric method. An electrical low-pressure impactor (ELPI) was used to quantify the DPM number concentration. The HC compounds, n-alkanes, and polycyclic aromatic hydrocarbons (PAHs) were collected on a moisture-free quartz filter together with a PUF/XAD/PUF cartridge and extracted in dichloromethane with sonication. Gas chromatography (GC)/mass spectroscopy (MS) was used to determine HC concentrations in the extracted solution. A calibrated gas combustion analyzer (Testo 350) and an O3 analyzer were used for quantifying the inlet and outlet concentrations of CO and NOx (nitric oxide [NO] + nitrogen dioxide [NO2]), and O3 in the diesel exhaust stream. The wESP was capable of removing approximately 67-86% of mass- and number-based DPM at a 100% exhaust volumetric flow rate generated from 0- to 75-kW engine loads. At 75-kW engine load, increasing gas residence time from approximately 0.1 to 0.4 sec led to a significant increase of DPM removal efficiency from approximately 67 to more than 90%. The removal of n-alkanes, 16 PAHs, and CO in the wESP ranged from 31 to 57% and 5 to 38%, respectively. The use of the wESP did not significantly affect NOx concentration in diesel exhaust. The O3 concentration in diesel exhaust was measured to be less than 1 ppm. The main mechanisms responsible for the removal of these pollutants from diesel exhaust are discussed.     

Elevated Levels of Cadmium and Zinc in Paddy Soils and Elevated Levels of Cadmium in Rice Grain Downstream of a Zinc Mineralized Area in Thailand: Implications for Public Health

Prolonged consumption of rice containing elevated cadmium (Cd) levels is a significant health issue particularly in subsistence communities that are dependent on rice produced on-farm. This situation is further exacerbated in areas of known non-ferrous mineralization adjacent to rice-based agricultural systems where the opportunity for contamination of rice and its eventual entry into the food chain is high. In the current study, an assessment of the degree of soil Cd and Zn contamination and associated rice grain Cd contamination downstream of an actively mined zone of Zn mineralization in western Thailand was undertaken. Total soil Cd and Zn concentrations in the rice-based agricultural system investigated ranged from 0.5 to 284 mg kg⁻¹ and 100 to 8036 mg kg⁻¹, respectively. Further, the results indicate that the contamination is associated with suspended sediment transported to fields via the irrigation supply. Consequently, the spatial distribution of Cd and Zn is directly related to a field’s proximity to primary outlets from in-field irrigation channels and inter-field irrigation flows with 60–100% of the Cd and Zn loading associated with the first three fields in irrigation sequence. Rice grain Cd concentrations in the 524 fields sampled, ranged from 0.05 to 7.7 mg kg⁻¹. Over 90% of the rice grain samples collected contained Cd at concentrations exceeding the Codex Committee on Food Additives and Contaminants (CCFAC) draft Maximum Permissible Level for rice grain of 0.2 mg Cd kg⁻¹. In addition, as a function of demographic group, estimated Weekly Intake (WI) values ranged from 20 to 82 μg Cd per kg Body. This poses a significant public health risk to local communities. The results of this study suggest that an irrigation sequence-based field classification technique in combination with strategic soil and rice grain sampling and the estimation of WI values via rice intake alone may be a useful decision support tool to rapidly evaluate potential public health risks in irrigated rice-based agricultural systems receiving Cd contaminated irrigation water. In addition, the proposed technique will facilitate the cost effective strategic targeting of detailed epidemiological studies thus focusing resources to specific ‘high risk’ areas.     

NO2 and SO2 dispersion modeling and relative roles of emission sources over Map Ta Phut industrial area, Thailand

Map Ta Phut industrial area (MA) is the largest industrial complex in Thailand. There has been concern about many air pollutants over this area. Air quality management for the area is known to be difficult, due to lack of understanding of how emissions from different sources or sectors (e.g., industrial, power plant, transportation, and residential) contribute to air quality degradation in the area. In this study, a dispersion study of NO2 and SO2 was conducted using the AERMOD model. The area-specific emission inventories of NOx and SO2 were prepared, including both stack and nonstack sources, and divided into 11 emission groups. Annual simulations were performed for the year 2006. Modeled concentrations were evaluated with observations. Underestimation of both pollutants was Jbund, and stack emission estimates were scaled to improve the modeled results before quantifying relative roles of individual emission groups to ambient concentration overfour selected impacted areas (two are residential and the others are highly industrialized). Two concentration measures (i.e., annual average area-wide concentration or AC, and area-wide robust highest concentration or AR) were used to aggregately represent mean and high-end concentrations Jbfor each individual area, respectively. For AC-NO2, on-road mobile emissions were found to be the largest contributor in the two residential areas (36-38% of total AC-NO2), while petrochemical-industry emissions play the most important role in the two industrialized areas (34-51%). For AR-NO2, biomass burning has the most influence in all impacted areas (>90%) exceptJor one residential area where on-road mobile is the largest (75%). For AC-SO2, the petrochemical industry contributes most in all impacted areas (38-56%). For AR-SO2, the results vary. Since the petrochemical industry was often identified as the major contributor despite not being the largest emitter, air quality workers should pay special attention to this emission group when managing air quality for the MA.     

NO2 and SO2dispersion modeling and relative roles of emission sources over Map Ta Phut industrial area,Thailand

Map Ta Phut industrial area (MA) is the largest industrial complex in Thailand. There has been concern about many air pollutants over this area. Air quality management for the area is known to be difficult, due to lack of understanding of how emissions from different sources or sectors (e.g., industrial, power plant, transportation, and residential) contribute to air quality degradation in the area. In this study, a dispersion study of NO₂ and SO₂ was conducted using the AERMOD model. The area-specific emission inventories of NO_x and SO₂ were prepared, including both stack and nonstack sources, and divided into 11 emission groups. Annual simulations were performed for the year 2006. Modeled concentrations were evaluated with observations. Underestimation of both pollutants was found, and stack emission estimates were scaled to improve the modeled results before quantifying relative roles of individual emission groups to ambient concentration over four selected impacted areas (two are residential and the others are highly industrialized). Two concentration measures (i.e., annual average area-wide concentration or AC, and area-wide robust highest concentration or AR) were used to aggregately represent mean and high-end concentrations for each individual area, respectively. For AC-NO₂, on-road mobile emissions were found to be the largest contributor in the two residential areas (36–38% of total AC-NO₂), while petrochemical-industry emissions play the most important role in the two industrialized areas (34–51%). For AR-NO₂, biomass burning has the most influence in all impacted areas (>90%) except for one residential area where on-road mobile is the largest (75%). For AC-SO₂, the petrochemical industry contributes most in all impacted areas (38–56%). For AR-SO₂, the results vary. Since the petrochemical industry was often identified as the major contributor despite not being the largest emitter, air quality workers should pay special attention to this emission group when managing air quality for the MA.

Implications: Effective air quality management in Map Ta Phut Industrial Area, Thailand requires better understanding of how emissions from various sources contribute to the degradation of ambient air quality. Based on the dispersion study here, petrochemical industry was generally identified as the major contributor to ambient NO₂ and SO₂. By accounting for all stack and non-stack sources, on-road mobile emissions were found to be important in some particular areas.