*2.3. Meteorology*

High wind speeds contribute to pollutant dispersion but it could also extend the size of the influence area. Low wind speeds generate high concentration of pollutants near the source. The fact that dispersion phenomena is highly dependent of the meteorological conditions hampers the process of generalizing the results obtained. To overcome this difficulty, we studied the dispersion of pollutants

generated by agricultural burning under very diverse meteorological conditions. Datasets with 1–5 years of 1-h meteorological conditions from the USA and Colombia were used, since they represent scenarios with extreme weather characteristics during the different seasons of the year. Table 2 presents the list of meteorological data used in this study and Appendix A. shows their respective wind roses. Only meteorological datasets with 100% of data availability were used in work.


**Table 2.** Datasets of 1-h meteorological data used to study the dispersion of the pollutants generated during agricultural burnings.

#### *2.4. Estimation of the Pollutants' Mass Emission Rates*

The mass emission rate *Ei,j* (kg/s) of pollutant i emitted by a given crop burning j, was estimated through Equation (2), where *Lj* (kg/m2) is the amount of biomass that is typically produced by crop j per unit of cultivated area, and *Sj* (m<sup>2</sup>/s) is the burning rate [22].

$$E\_{i,j} = E\_{i,j}^\* L\_j \text{ S}\_j \tag{2}$$

In this equation, *E\*i,j* (kg/kg) is the emission factor and it describes the amount of pollutant *i* typically emitted per unit mass of crop *j*. Multiple studies have been conducted to determine the emission factors associated with agricultural burning under controlled conditions [1] and by field measurements [23]. Table 1 shows *E\*i,j* and *Lj* for several crops. It shows that sugarcane has the largest loading factor. For this crop, Table 3 presents the emission factors reported by different authors, among which, large variations are observed. In this study, we adopted the emission factors reported by the USEPA [22].

The burning rate (*Sj* in m<sup>2</sup>/s) depends on multiple factors, including wind speed and crop moisture content. Given the difficulty of finding values reported in the literature for this variable, a constant value was assumed as a first approximation. For the case of sugarcane, we consulted companies in the sugarcane industry, and they reported an approximate value of 1 ha/day. However, it depends on the length and the number of lines used as starting flame fronts.

#### *2.5. Determination of the Influence Area*

For a given set of meteorological conditions (temperature, humidity, solar radiation, wind speed and direction), AERMOD estimates the pollutant concentration at every receptor located nearby the burning area. The process is repeated every hour as meteorological data are reported in this format. Given the short-term nature of agricultural burnings, we focused only on human short-term (24 h) exposure. Therefore, we set up AERMOD to calculate at every receptor the 24 h average pollutant concentration and to record only the maximum value obtained after one year of meteorological data

(or the number of years of meteorological data availability). Finally, we selected all those receptors where pollutant concentration exceeded its respective threshold value specified in the NAAQS. The combination of all those receptors made up the influence area of agricultural burning.

The largest influence area is produced by the crop with the largest emission rate of the pollutant with the highest hazard to human health. According to Table 1 and Equation (2), for the case of sugarcane, the pollutant with the highest mass emission rate is PM10. Although the PM10 emission factor for sugarcane is one of the lowest among the di fferent crops listed in Table 1, sugarcane is the crop with the highest loading factor.

The hazard of a pollutant can be quantified as the inverse of its threshold value specified in the NAAQS. According to the American Conference of Governmental Industrial Hygienists (ACGIH), the threshold limit values (TLVs) are the maximum average airborne concentration of a hazardous material to which healthy adult workers can be exposed during an 8-h workday and 40-h workweek—over a working lifetime—without experiencing significant adverse health e ffects. They represent the opinion of the scientific community that exposure at or below the level of the TLV does not create an unreasonable risk of disease or injury [3]. Aiming to provide public health protection, including protecting the health of "sensitive" populations such as asthmatics, children, and the elderly, the environmental authority specifies those threshold limit values in the NAAQS for short time periods of exposure (3, 8, or 24 h depending of the pollutant) and for long time periods of exposure (one year) [14–24]. In this work, we only consider short-term exposition, as agricultural burnings are short-term events. Table 4 lists the USEPA maximum recommended values for short-term exposition.


**Table 3.** Sugarcane emission factors reported by several authors expressed as kg of pollutant emitted per Mg of sugarcane biomass burned. Highlighted boxes indicate the values used in this work.

\* BC, Black carbon; -, no available data; Reference [22] corresponds to the USEPA recommended emission factors.

**Table 4.** Colombian NAAQS [31], emission rates for a burning rate of 1 ha/day, and risk indexes calculated for the case of the agricultural burning of sugarcane crops (*j* = sugarcane).


Aiming to identify the scenario that produces the largest agricultural burning influence area, we defined the risk index (*Ii,j*) for pollutant *i* generated from crop *j*, according to Equation (3). In this equation, *AQi* is the NAAQS threshold value for pollutant *i.* The crop and pollutant with maximum value for *Ii,j* defines the largest area of influence. Table 4 shows the *Ii,j*\* obtained for the case of sugarcane crops (*j\** = sugarcane). It shows that PM2.5 has the largest *Ii,j\** and therefore it is the pollutant that defines the influence area for the burning of sugarcane crops.

$$I\_{i,j} = \frac{E\_{i,j}}{AQ\_i} \tag{3}$$
