DOI: 10.3303/CET2291026 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Paper Received: 23 February 2022; Revised: 5 April 2022; Accepted: 15 May 2022 
Please cite this article as: Barozzi M., Dimauro C., Scotton M.S., Copelli S., 2022, A Comprehensive Approach to Establish the Impact of 
Worksites Air Emissions, Chemical Engineering Transactions, 91, 151-156  DOI:10.3303/CET2291026 
  

 CHEMICAL ENGINEERING TRANSACTIONS  
 

VOL. 91, 2022 

A publication of 

 

The Italian Association 
of Chemical Engineering 
Online at www.cetjournal.it 

Guest Editors: Valerio Cozzani, Bruno Fabiano, Genserik Reniers 

Copyright © 2022, AIDIC Servizi S.r.l. 

ISBN 978-88-95608-89-1; ISSN 2283-9216 

A Comprehensive Approach to Establish the Impact of 

Worksites Air Emissions 

Marco Barozzi a, Carmelo Dimauro b, Martina Silvia Scotton a, Sabrina Copelli a,* 

aUniversity of Insubria, Department of Science and High Technology, via Valleggio 9 - 22100, Como (Italy)  
bRisk Governance Solutions S.r.l., Via delle Medaglie d’Oro 8- 21100, Varese (Italy)  

sabrina.copelli@uninsubria.it 

Worksite activities are time-limited events associated with continuous releases of airborne pollutants, such as 

carbon monoxide, particulate matter, and NOx, and they impact potentially vast areas. The side-effects on the 

environment can be severe, and they are subject of literature studies, with the final aim of proposing solutions 

that may improve the management of air emissions. No general assessment method or approach is yet 

available to estimate their effects on the environment and workers’ health. In this work, a general procedure 

that can be potentially applied to every type of worksite is proposed (i.e., construction sites, upgrading of 

chemical plants, road sites, etc..). The approach involves a detailed assessment of emissions and their 

expected pollutant concentrations. A dedicated mathematical model has been defined to assess pollutant 

emissions over time, consistent with all the different phases of foreseen activities. Emissions are defined on 

base of the GANTT descriptions of the activities and air pollutant dispersion is simulated with a dedicated 

model. Finally, the obtained results are evaluated against air quality thresholds as defined by laws and 

conditioning the human health risks for workers and citizens potentially exposed to pollutants. 

Keywords: Atmospheric pollution, CALPUFF, Environmental impact, Worksites  

1. Introduction 

Air quality is among the most important environmental issues for a more sustainable future. The number of 

factors that impact the amount of pollutants in the atmosphere is countless, including both anthropogenic and 

natural causes. For what concerns anthropogenic factors, any activity should follow specific constraints 

(according to both national and international standards) for airborne pollutant emissions. In Europe, the main 

standard regulating airborne pollutant concentrations is the Directive 2008/50/EC, which defines the maximum 

allowable levels for human and vegetation health. It is well-known that atmospheric pollution is greatly 

impacted by transport and industry, which consist in constant sources of emissions. However, even short-term 

activities such as worksites may severely impact air quality. Lepert and Brillet (2019) published a work where 

they highlighted the increased emissions of greenhouse gases associated with worksites for maintenance and 

improvement of traffic roads. Also, many sectorial studies have been performed on the modelling and the 

assessment of pollutant emissions from specific sites. Giunta et al. (2019), noted the potential impact due to 

the expected growth of the road constructions around the world, and demonstrated that in the worksites of 

bridges, earthworks and tunnels the overall emissions can be 5 times higher than the emission of storage and 

concrete production worksites. In a more recent work (Giunta, 2020), the impact of a motorway construction 

project in Italy was analyzed, and it was shown how deeply can such activities impact air quality, threatening 

workers, civilians, and environment health. Such analyses are usually considered negligible for smaller 

activities, and they remain a subject of pure research. This is due to an underestimation of the effects of small 

worksites and to the lack of simple and general methods dedicated to these purposes. In this work, we 

propose a potentially general approach to estimate the impact of a worksite, with particular attention to the 

assessment of human health risk for workers and citizens exposed. The major novelty represented by this 

model is the generalization of the method, since most of the works presented in the current literature are very 

specific, involving studies on road construction sites or building sites only. The model starts with a collection of 

raw data, including operating machine, excavations information, and transportation. Such data are then 

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elaborated with the use of Gantt diagrams, which are a very used tool when handling with worksite planning 

and validate models and emission factors to describe particulate matter, NOx, SOx and CO emissions. In this 

way it is possible to both assess global emissions and emission sources. After a proper detection of source 

types, dispersion modelling can be carried out. While pollutant dispersion can be estimated with several 

available mathematical models, the use of Calpuff is highly recommended, due to its capacity of representing 

point, linear and areal sources with a discontinuous functioning, and the capability of describing phenomena 

such as atmospheric turbulence or thermal inversion. From results, with the use of threshold values, exposure 

maps for workers can be elaborated. 

2. Methodology 

The method proposed is summarized in Figure 1. The main idea consists in estimating emissions at different 

levels: at first, according to worksite characteristics, including information about activity types, machines and 

transportation means, it is possible to estimate the overall emissions. Using information from the Gantt 

diagram and work shifts, it is also possible to deduce the emissions profile overtime. Note that such 

information is usually always available, since they are deeply connected to the activity itself. 

 

Figure 1: Scheme of the proposed model 

This first step requires also dedicated sub-models to estimate pollutant emissions.  The analysis is carried out 

for the most common airborne pollutants from engines and excavations: particulate matter (PM2.5 and PM10), 

NOx, SOx, and carbon monoxide. Once sub-models and worksite main information are set, it is possible to 

estimate global and overtime emissions, as it will be shown later. This is already an important information, 

which can be helpful in defining what are supposed to be most impactful activities for the work. However, it is 

now possible to evaluate the emission profiles. In this case, it is necessary to associate each source to its 

category, which can be a point, areal or linear source. Point sources are more suitable for single operating 

machines, such as drills and generators. Areal sources define well topsoil excavations and aggregates 

storage. Linear sources are both paved and unpaved roads, that require also specific sub-models to establish 

the correct particulate matter suspension. 

2.1 Emission factors for engines 

The pollutants produced by the means of excavations, transportation, and other operations, such as welding 

generators, are essentially associated with the combustion processes of the related engines. Actually, it is 

possible to split between immobile equipment, such as drills, generators compressors or excavators, and 

mobile ones, like heavy trucks. For what concerns the first category, the global emissions can be estimated 

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with the use of the database SCAB (South Coast Air Basin), Fleet Average Emission Factors, developed from 

the South Coast Air Quality Management District. Such a database is a very useful tool, which takes in 

account the evolution of emission thresholds over the year (the current database covers the period 2007-

2025). For each equipment, the emission factor can be estimated thanks to the relation expressed by Eq. 1. 

𝐸𝑖 = 𝐻 ∙ 𝐸𝐹𝑖 (1) 

E is the total emission in grams per day for a i-th pollutant, H corresponds to the hours per day of equipment 

operation and EF is the off-road mobile source emission factor by equipment category or horsepower-based   

equipment category in grams per hour. Table 1 shows the current values for Drill Rigs. As it can be noticed, 

equipment power is required in order to properly assess the factor. 

Table 1: Example of emission factors EF for Drill Rigs (calculated from 2020 values) (AQMD, 2021) 

 MaxCV ROG [g/h] CO [g/h] NOx [g/h] SOx [g/h] PM [g/h] CO2 [g/h] CH4 [g/h] 

Bore/Drill 

Rigs 

15.2 4.57 23.96 28.61 0.06 1.12 3924.79 0.41 

 25.35 6.15 20.69 38.50 0.06 1.54 4971.40 0.56 

 50.69 10.55 63.73 62.11 0.12 2.77 8896.19 0.95 

 

For what concerns mobile sources, such as heavy trucks or simple buses and cars used to move operators on 

the worksite every day, two databases can be used. For Heavy-Duty Trucks, the Environmental Protection 

Agency developed a database of emission factors for trucks (EPA, 2008), which defines the emission factors 

for VOC, CO, NOx, PM2.5 and PM10 for diesel or gasoline. Factors are classified into 8 classes (from IIb to 

VIIIb) depending on the total weight (ranging from 3856 kg to >27 tons). Daily emissions are estimated by Eq. 

2: 

𝐸𝑖 = 𝐷 ∙ 𝐸𝐹𝑀𝑖 (2) 

E is the total emission in grams per day for a i-th pollutant, D corresponds to the kilometers run per day and 

EFM is the off-road mobile source emission factor by truck category in grams per kilometer. 

For cars and buses, it is possible to use Euro VI norm (or an equivalent one for older vehicles), which 

functions in the same way, but with different EFMi values. 

Also, PM10 can be emitted from transits on unpaved roads, as a result of interactions among tires and dusty 

surfaces. EPA proposes the relationship expressed by Eq. 3 to estimate the additional dust production from 

transit on unpaved roads: 

𝐸𝑈,𝑃𝑀10 = 𝐷𝑢 ∙ 𝑘 ∙ (
𝑠

12
)
𝑎

∙ (
𝑊

3
)
𝑏

 (3) 

Eu,PM10 is the PM10 emission factor in grams per day, Du is the daily distance ran on unpaved roads, k, a, b 

are empirical constants depending on the particulate size, s is the surface material silt content (%), W is the 

mean vehicle weight (tons). 

2.2 Emission factors due to topsoil excavations 

The presence of excavations determines dispersions of fine dust associated with the movement of land and its 

storage. The contaminants released associated with this activity is essentially associated with the finer fraction 

of powders as the heavier ones are deposited relatively quickly and near the release points. The finer fractions 

such as PM10 and PM2.5, in addition to having an interest from the point of view of environmental 

contamination and impacts on human health, are able to remain suspended in the air and be transported by 

local anemological processes. 

The estimate of fine particulate emissions is carried out with reference to the AP 42 from EPA (EPA, 2007), 

which reports the emission references as a function of the tons of earth removed. The emission coefficient is 

therefore defined as grams of fine dust released per ton of earth removed. The emission factor, shown in 

Eq.4, is also estimated considering the effects due to the intensity of the wind and the degree of humidity of 

the soil. 

𝐸𝑖 = 1.6 ∙ 𝑘 ∙ (
𝑈

2.2
)
1.3

∙ (
𝑀

2
)
−1.4

 (4) 

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Where E is emission factor expressed in g of dust per ton of material removed (on daily basis) for the i-th dust 

average size, U is the wind speed, in m/s; M is the percentage content of soil moisture, ranging from 0.25 to 

4.8% and k is a factor that depends on the size of the particulate. 

After excavations, removed soil is usually stored. According to the literature, the emissions resulting from the 

erosive effects due to the action of the wind of different intensity on piles of excavated material are low. 

Vegetation covers typically form on the surface and a crust typically forms, that is a layer of soil characterized 

by a low degree of humidity, which limits the mechanical actions of the wind. However, the emission potential 

increases each time the surface is altered, providing the pile with a new surface of erodible material. 

In general, the storage cycle of material in heaps requires that the material is periodically added or subtracted, 

modifying the old surface layer, inactive from the point of view of the emission potential, reactivating the 

erosive capacity of the wind. The daily emissions of the pile are therefore directly proportional to the number of 

changes in the crust per day. It can also be observed that the average atmospheric wind speed (even on an 

hourly basis) is not sufficient to generate a significant erosion of the surface of the accumulated materials and 

it is therefore necessary to refer to the maximum intensity of the gusts of wind and their frequency in the 

period between one disturbance intervention and another. In summary, the emissions related to dusting by the 

heap depend on factors such as the number of disturbances per day, the age of the heap, its moisture 

content, the portion of fine aggregates and the anemological conditions of the site. Emissions due to wind 

erosion from piles are characterized in AP-42, Chapter 13.2.5 (EPA, 2007) which treats the emission potential 

of the single pile as a function of a series of factors. In particular, the daily emission rate is given by Eq. 5: 

𝐸𝑝.𝑖 = 1000 ∙ 𝐸𝐹𝑝.𝑖 ∙ 𝑎 ∙ 𝑚𝑜𝑣 ∙ 𝐻 (5) 

Where Ep is the amount of dust lifted in g/day, i refers to each particulate matter considered (PM10, PM2.5), 

EFp,I is the areal emission factor in kg/m²,a is the surface of the moved area in m³, mov is the number of 

movements / hour and H is the total number of hours worked per day. 

3. Model application 

3.1 Global emissions 

Global and overtime emissions are estimated by means of Gantt diagrams, activities performed and operating 

machines. Gantt diagrams are structures widely used worldwide to define the timetables of a worksite. They 

are generated by associating the different activities in which the work is organized with the expected time they 

are supposed to last.  To the scope of this model, it is possible to associate a Gantt diagram to a Boolean 

variable, where 1 consists of the presence of the specific activity at a given time step. Table 1 represents a 

translation of a classic Gantt diagram into a Boolean matrix, with dimensions of na x nt, where na is the total 

number of activities involved, and nt is the number of time steps identified. Usually, each time step has the 

same length (months or 30 days). This modified Gantt diagram is a matrix called G. 

Table 1: Example of Gantt table (in this case, na=3 and nt=4) 

 t1 t2 t3 t4 

Activity 1 1 1 0 0 

Activity 2 0 1 1 1 

Activity 3 0 0 0 1 

 

From this table, it is possible to deduce specific global emissions with the help of additional matrices. It is 

possible to introduce a matrix (called P), structured in the following way: each row represents the activities 

listed in the Gantt table (so the number of rows is equal to na), and each column represents all the specific 

operating machines, trucks, excavations present during the whole activity. Now, the numbers in the matrix are 

the total number of machines etc. used. Table 2 represents an example: in this case, a single drill is used 

during activity 1, no one is used in phase 2, and 2 are used in the final phase.  

Table 2: Example of P a matrix translated into a table  

 Drill Excavations Heavy trucks 

Activity 1 1 0 2 

Activity 2 0 1 0 

Activity 3 2 1 2 

An additional matrix, called E, must be finally introduced. In this case, the matrix contains information about 

the emission factors which were calculated according to dedicated models. In this case, the rows contain the 

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equipment listed already in the P matrix, and the columns contains the pollutants chosen (in this case, 5 

pollutants are identified). An example is reported in Table 3. 

Table 3: Example of a E matrix translated into a table (each emission factor is referred to data for the specific 

operating machine/activity) 

 CO NOx SOx PM2.5 PM10 

Drill ECO ENOx ESOx EPM2.5 EPM10 

Excavations ECO ENOx ESOx E2.5+Ep2.5 E10+Ep10 

Heavy trucks ECO ENOx ESOx EPM2.5 EPM10+EU,PM10 

Now it is possible to estimate global emissions overtime exploiting simple matrix operations. The matrix Et is 

now defined, according to Eq. 7.  

𝐸𝑇 = 𝐺′ ∙ (𝑃 ∙ 𝐸 ∙ 𝑡) (7) 

Where ‘ indicates the transposed matrix and t is the number of days for each time period identified in the Gantt 

diagram (if defined in months, usually t can be considered equal to 24 days). The matrix ET contains important 

information: due to its structure, it contains for each time step defined in the Gantt table the overall emissions 

for each pollutant. In this way, it is possible to instantly identify the potentially most critical time steps of the 

worksite. 

Table 4: Example of a ET matrix translated into a table 

 CO [g] NOx [g] SOx [g] PM2.5 [g] PM10 [g] 

t1 t∑(ECO,1) t∑(ENOx,1) t∑(ESOx,1) t∑(EPM2.5,1+ E2.5,1+Ep2.5,1) t∑(EPM10,1+ E10,1+Ep10,1) 

t2 t∑(ECO,2) t∑(ENOx,2) t∑(ESOx,2) t∑(EPM2.5,2+ E2.5,2+Ep2.5,2) t∑(EPM10,2+ E10,2+Ep10,2) 

t3 t∑(ECO,3) t∑(ENOx,3) t∑(ESOx,3) t∑(EPM2.5,3+ E2.5,3+Ep2.5,3) t∑(EPM10,3+ E10,3+Ep10,3) 

t4 t∑(ECO,4) t∑(ENOx,4) t∑(ESOx,4) t∑(EPM2.5,4+ E2.5,4+Ep2.5,4) t∑(EPM10,4+ E10,4+Ep10,4) 

 

3.2 Emission profiles 

Once global emissions have been identified, it is possible to proceed forward by resolving the concentration 

profile overtime on the zone interested by the worksites. This can be carried out by applying a dedicated 

mathematical model suited for simulating airborne pollutants dispersion. The Environmental Protection Agency 

regularly uploads recommended mathematical models to estimate (EPA, 2017). Based on the authors 

knowledge and experience, for these kinds of activities both Gaussian models (Copelli et al., 2019) and 

Lagrangian ones (such as CALPUFF), are suited for a proper emissions profile determination. A correct 

implementation of such codes requires a series of necessary steps, which include: geological characterization 

of the simulated zone, meteorological data assessment, emissions characterization. Emission sources 

definition will be focused on, since the other steps can be completed with the use of well-known database and 

models. 

Point emissions are single machines, such as drills, excavators. They must be simply placed at the location 

they are supposed to be placed, and the emission factor (usually in g/h) must be defined. Such data are 

already known from the matrices E and P. Areal emissions are represented by excavations, in terms of both 

pure excavation operation and extracted soil stacked. In this case, the emission factor should be expressed in 

g/h/m², so information about excavation site size must be recovered or deduced. Finally, linear emission are 

mainly roads, both paved and unpaved. In this case, the emission factors should be divided into the length of 

the roads used each day. 

Once the model is resolved, concentration profiles overtime can be evaluated, and during post-processing 

important data can be evaluated to continue with the risk assessment, such as percentiles, time weighted 

means and absolute maxima. 

3.3 Risk assessment 

Methodologies and techniques used in health risk assessment are firmly established (WHO, 2021).  The 

assessment of human health risk requires identification, compilation and integration of information on the 

health hazards of a chemical, human exposure to the chemical, and the relationships between exposure, dose 

and adverse effects. The purpose of the hazard identification step is to determine the hazardous properties of 

the chemical released during the with all the different phases of worksite activities.  

Hazard characterization and related guideline value identification is used to obtain a reference value for the 

chemical that matches the route and duration of exposure (for example, inhalation and long-term exposure). 

155



Guidance and guideline values are normally the result of hazard characterizations and involve dose–response 

assessment. Then, through an exposure assessment it is possible to define the most likely routes, pathways, 

duration, frequency and intensity of exposure that can be relevant for the potentially exposed workers and 

population.  

In the final step of the hazard identification, hazard characterization and exposure information are combined to 

yield a statement of risk. The risk for the exposed population/operators can depend on many aspects, but the 

most important are: concentration of the toxic chemical at the point of exposure, type of exposure and the 

intake pathway, duration of exposure (from minute to decades), toxicity of the released substance 

distinguished in chemical that have chronic effects and cancerogenic impacts, and vulnerability of the exposed 

person.  

Considering the chemicals that can induce chronic effect, the risk is calculated considering the dose assumed 

over a specific period. This value can be compared with the reference threshold of tolerance (e.g. in the short 

term: Immediately Dangerous To Life or Health (IDLH) Values; Threshold Limit Values (TLV), Permissible 

Exposure Limit (PEL), or in the long period: Reference dose (RfD) or Reference concentration (RfC)). Note 

that the definition of dose can be estimated with the knowledge of the concentrations at which a human 

subject is exposed. So, the modeling of pollutant dispersions can be easily improved by adding specific 

receptors, for which a concentration overtime curve can be defined. Hence, the expected daily dose can be 

easily defined.  

4. Conclusions 

In this work, a theoretical general method to estimate environmental and health impact of worksites is 

proposed. The method involves well-established literature methods for the establishment of emission factors 

and used information which are already known at the level of worksite operations definition and assessment. 

With a good structure, global emissions are easily identified with the use of simple matrix operations. The 

same information can be also easily used to implement a mathematical model to address the level of 

exposure of specific receptors, leading to a precise health risk assessment for workers or exposed citizens. 

Clearly, a description of all aspects that characterize the risk assessment activities is more complex and 

requires a more extensive description. However, it is reasonable to assume that the current level of detail is 

sufficient to highlight how the risk assessment associated to the release of toxic substances during worksite 

activities may be a valid approach to support decision-making process about the definition of worksite 

management strategies that can mitigate and minimize the potential risk for workers and people living nearby 

the worksite. It will be interesting for future works to include comprehensive research with a real case study, 

along with in-site air contaminants analyses, in order to validate the effective potential of the proposed 

method. 

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	49scotton.pdf
	Detailed Reconstruction and Safety Analysis of a Pre–Seveso Accident