Measurement of visible dust emissions during almond nut-picking operations at various harvester settings.

Peak ambient dust levels in the San Joaquin Valley (SJV) are often coincident with peak agricultural harvest seasons, particularly for nut orchards. Federal reference methods (FRMs), consisting of mass-based sampling techniques, are designed to measure and analyze ambient dust concentrations. However, FRMs generally require meticulous attention to sampling details, tedious labor and logistics, and time-consuming dispersion calculations. This study used opacity-based techniques - the U.S. Environmental Protection Agency (EPA) Method 9 and the Digital Compliance Opacity Technique (DCOT) - to quickly measure relative dust intensity at different harvester settings and to evaluate visible dust emission reductions using a new/low-dust nut harvester. Results indicate that old/conventional harvester at standard settings (3 mph ground speed and 900 rpm blower speed) produced visible dusts with opacities ranging from 23.3% to 29.0%. The dust plume generated from new/low-dust harvesters at similar settings registered lower opacity readings, with an average of 13.94%. The lowest average dust opacity (7.8%) was achieved when the separation fan was turned off. The present results validated the previous FRM emission findings that an old/conventional harvester has the highest PM emissions, but with a potential to achieve 50% reduction by adopting new/low-dust harvesters. Compared to an old harvester, the relative intensity of dusts was reduced by 40%-51% for low-dust harvesters operated at lower ground speeds. Further dust reductions could be achieved by lowering the fan speed (58%) and operating at no fan/blower setting (66.4%). Both visible emission evaluation (VEE) techniques were able to provide rapid quantitative feedback on the effects of operational changes on emitted harvest dusts. At this stage, opacity-based techniques can potentially be adapted as a screening tool for identifying best management practices (BMP) in reducing harvest dusts, rather than to solely rely on FRM mass-based techniques.Implications: U.S. EPA VEE techniques are established, robust methods of dust measurement systems that can be adopted to evaluate visible dust mitigation strategies in the SJV, alongside the existing FRM protocols. The use of Method 9 and DCOT, as both non-disruptive and rapid dust measurement tools, can bring immediate impact concerning the goal of the almond industry to significantly reduce its PM emissions in the next coming years.

Particulate Matter Emission Factors for Dairy Facilities and Cattle Feedlots during Summertime in Texas.

Particulate matter (PM) emissions from dairies and feedlot sources require regular emission factor update. Likewise, development of simple measurement technique to accurately measure pollution concentration is warranted to limit the impact of air pollution and take necessary actions. During June of 2020, a dairy facility from central Texas and a feedlot from the Texas Panhandle region, titled as Dairy B and Feedlot C, respectively, were chosen for measurement of PM emissions in the state of Texas to represent dairy facilities and cattle feedlots PM emission rates. Four stations, each assigned with an EPA-approved Federal Reference Method (FRM) sampler, Texas A&M University (TAMU) designed sampler and handheld non-FRM AEROCET (MET One Instruments) sampler for collocation, were selected within each sampling locations. Drones were also utilized mounted with a handheld AEROCET sampler for simultaneously sampling at a certain height. PM2.5 emissions of Dairy B were all below 24-h PM2.5 standard of 35 µg m-3 as specified by National Ambient Air Quality Standards (NAAQS) even at the 98th percentile. The PM ratio between regulated PM10 to PM2.5 was determined to make an estimate of relative percentage of coarser particles to fine particles in both feedlot and the dairy representative animal facilities. The maximum mean emission factor determined using AERMOD for PM2.5 and PM10 was found to be 0.53 and 7.09 kg 1000-hd-1 d-1, respectively, for the dairy facility while 8.93 and 33.42 kg 1000-hd-1 d-1, respectively, for the feedlot. A conversion factor and correlation matrix were developed in this study to relate non-FRM sampler data from the handheld AERCET samplers with FRM samplers. Cheaper handheld samplers (AEROCETs) may play a potential role in quick and relatively instant measurement of PM emissions to initiate necessary preventive actions to control PM emission from dairy facility and feedlot sources.

Particulate matter emission factors using low-dust harvesters for almond nut-picking operations.

The lack of an available particulate matter (PM) PM2.5 emission factor for almond harvesting operations has become a challenge for particulate matter regulations and emissions inventory in California. Low-dust harvesters are viewed as one of the strategies to reduce PM emissions and help achieve the state's PM2.5 attainment targets. This paper evaluates the potential emission reduction from using low-dust harvesters compared to the conventional. Orchard boundary measurements of PM concentrations were collected to back-calculate emission rates using inverse dispersion modeling. Emissions from four low-dust harvesters (Flory 850, Exact E3800, Weiss-McNair 9800 and Jack Rabbit) were compared to those from a conventional harvester (Flory 480) in two orchards, located in the Fresno County. Emissions of PM2.5, PM10 and total suspended particles were observed to be lower for all new harvesters compared to the conventional harvester. The range of reductions varies from about 40% to 77% in PM2.5 emissions based on emission factors generated. The average ratio of PM10 to PM2.5 emissions is about 12.5%. The results of these tests imply that these new low-dust harvesters are capable of reducing PM emissions without affecting product quality. Therefore, the San Joaquin Valley Air Pollution Control District should consider including the use of these new harvesters in the conservation management practices (CMP) for the reduction of PM emissions in the valley. Implications: The results of this research indicate that almond low-dust harvesters could potentially reduce PM emissions over traditional harvesters without any negative effect on product quality. Therefore, the use of these new harvesters should be considered as part of almond best management practices and updating of emissions inventory in the San Joaquin Valley.