Atmospheric Dispersion Modelling and Spatial Analysis to Evaluate Population Exposure to Pesticides from Farming Processes

Costanzini, Sofia; Teggi, Sergio; Bigi, Alessandro; Ghermandi, Grazia; Filippini, Tommaso; Malagoli, Carlotta; Nannini, R.

doi:10.3390/atmos9020038

Cited by 11 publications

(9 citation statements)

References 74 publications

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“…We included sex and age as potential confounders and effect-modifiers in a multivariable model. We further adjusted for residential passive exposure to pesticides as assessed using proximity to agricultural land use [37][38][39] or inorganic selenium species [26]. We used 'logit', 'mkspline', and 'xblc' routines of the Stata 16.1 (Stata Corp., College Station, TX, USA) for all statistical analyses.…”

Section: Discussionmentioning

confidence: 99%

Risk of Amyotrophic Lateral Sclerosis and Exposure to Particulate Matter from Vehicular Traffic: A Case-Control Study

Filippini

Mandrioli

Malagoli

et al. 2021

IJERPH

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(1) Background: Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disease with still unknown etiology. Some occupational and environmental risk factors have been suggested, including long-term air pollutant exposure. We carried out a pilot case-control study in order to evaluate ALS risk due to particulate matter with a diameter of ≤10 µm (PM10) as a proxy of vehicular traffic exposure. (2) Methods: We recruited ALS patients and controls referred to the Modena Neurology ALS Care Center between 1994 and 2015. Using a geographical information system, we modeled PM10 concentrations due to traffic emissions at the geocoded residence address at the date of case diagnosis. We computed the odds ratio (OR) and 95% confidence interval (CI) of ALS according to increasing PM10 exposure, using an unconditional logistic regression model adjusted for age and sex. (3) Results: For the 132 study participants (52 cases and 80 controls), the average of annual median and maximum PM10 concentrations were 5.2 and 38.6 µg/m3, respectively. Using fixed cutpoints at 5, 10, and 20 of the annual median PM10 levels, and compared with exposure <5 µg/m3, we found no excess ALS risk at 5–10 µg/m3 (OR 0.87, 95% CI 0.39–1.96), 10–20 µg/m3 (0.94, 95% CI 0.24–3.70), and ≥20 µg/m3 (0.87, 95% CI 0.05–15.01). Based on maximum PM10 concentrations, we found a statistically unstable excess ALS risk for subjects exposed at 10–20 µg/m3 (OR 4.27, 95% CI 0.69–26.51) compared with those exposed <10 µg/m3. However, risk decreased at 20–50 µg/m3 (OR 1.49, 95% CI 0.39–5.75) and ≥50 µg/m3 (1.16, 95% CI 0.28–4.82). ALS risk in increasing tertiles of exposure showed a similar null association, while comparison between the highest and the three lowest quartiles lumped together showed little evidence for an excess risk at PM10 concentrations (OR 1.13, 95% CI 0.50–2.55). After restricting the analysis to subjects with stable residence, we found substantially similar results. (4) Conclusions: In this pilot study, we found limited evidence of an increased ALS risk due to long-term exposure at high PM10 concentration, though the high statistical imprecision of the risk estimates, due to the small sample size, particularly in some exposure categories, limited our capacity to detect small increases in risk, and further larger studies are needed to assess this relation.

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Section: Discussionmentioning

confidence: 99%

Risk of Amyotrophic Lateral Sclerosis and Exposure to Particulate Matter from Vehicular Traffic: A Case-Control Study

Filippini

Mandrioli

Malagoli

et al. 2021

IJERPH

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“…A large majority used GIS to calculate spatial surrogates for pesticide exposure and a minority PLOS ONE employed surveys to estimate residential distance from the first fields. Only two studies used a dispersion model to assess concentrations in the vicinity [35,36]. The predominant use of GIS could be explained by the relative simplicity of these tools and the possibility of applying them to a data set including many observations [37].…”

Section: Assessment Of Residential Exposure In Epidemiological Studiesmentioning

confidence: 99%

“…In the selected studies, GIS were generally used to define buffers around the residential location, assuming an isotropic distribution of the pesticide emissions into the atmosphere, without integrating meteorological data. One study we selected in our scoping review showed that this can result in an underestimation of populations living downwind and overestimations of residents living upwind of the treated areas [35]. Unlike GIS, dispersion models are deterministic models, based on atmospheric diffusion and reaction equations that can take into account the anisotropic distribution of the aerial dispersion of pesticides.…”

Section: Assessment Of Residential Exposure In Epidemiological Studiesmentioning

confidence: 99%

Assessment of residential exposures to agricultural pesticides: A scoping review

et al. 2020

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The assessment of residential exposure to agricultural pesticides is a major issue for public health, regulatory and management purposes. In recent years, research into this field has developed considerably. The purpose of this scoping review is to provide an overview of scientific literature characterizing residential exposure to agricultural pesticides and to identify potential gaps in this research area. This work was conducted according to the JBI and PRISMA guidelines. Three databases were consulted. At least two experts selected the eligible studies. Our scoping review enabled us to identify 151 articles published between 1988 and 2019 dealing with the assessment of residential exposure to agricultural pesticides. Of these, 98 (64.9%) were epidemiological studies investigating possible links between pesticide exposure and the onset of adverse health effects, principally cancers and reproductive outcomes. They predominantly used Geographic Information Systems and sometimes surveys or interviews to calculate surrogate exposure metrics, the most common being the amounts of pesticides applied or the surface area of crops around the dwelling. Twenty-six (17.2%) were observational measurement studies conducted to quantify levels of pesticide exposure and identify their possible determinants. These studies assessed exposure by measuring pesticides in biological and environmental matrices, mostly in urines and house dust. Finally, we found only eight publications (5.3%) that quantified the risk to human health due to residential exposure for management purposes, in which exposure was mainly determined using probabilistic models. Pesticide exposure appears to be largely correlated with the spatial organization of agriculture activities in a territory. The determinants and routes of exposure remain to be explored to improve the conduct of epidemiological and risk assessment studies and to help prevent future exposures. Improvement could be expected from small-scale studies combining different methods of exposure assessment.

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“…Modena is located in the north of Italy, along the "via Aemilia", an ancient Roman road running from Rimini to Piacenza on the river Po ( Figure 2). The Po Valley is characterized by a high population density and by processes of industrialization and intensive agriculture (it is among the most productive agricultural areas within Europe) [72]. The climate of this region is partially continental: summers are hot with intense heat waves while winters are cold and wet, usually with atmospheric stability conditions and fog.…”

Section: Study Areamentioning

confidence: 99%

“…Normally precipitation is concentrated during autumn and spring. Summer and winter are the driest seasons [57,58,72,73]. In order to have a clear climate situation of the study area, Table 1 reports some climate information.…”

Section: Study Areamentioning

confidence: 99%

A Multi-Temporal Analyses of Land Surface Temperature Using Landsat-8 Data and Open Source Software: The Case Study of Modena, Italy

2018

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Abstract:The Urban Heat Island (UHI) phenomenon, namely urban areas where the atmospheric temperature is significantly higher than in the surrounding rural areas, is currently a very well-known topic both in the scientific community and in public debates. Growing urbanization is one of the anthropic causes of UHI. The UHI phenomenon has a negative impact on the life quality of the local population (thermal discomfort, summer thermal shock, etc.), thus investigations and analyses on this topic are really useful and important for correct and sustainable urban planning; this study is included in this context. A multi-temporal analysis was performed in the municipality of Modena (Italy) to identify and estimate the Surface Urban Heat Island (SUHI, strictly correlated to the UHI phenomenon) from 2014 to 2017. For this purpose, Landsat-8 satellite images were processed with Quantum Geographic Information System (QGIS) to obtain the Land Surface Temperature (LST) and the Normalized Difference Vegetation Index (NDVI). For every pixel, LST and NDVI values of three regions of interest (ROI, i.e., Countryside, Suburbs, and City Center) were extracted and their correlations were investigated. A maximum variation of 6.4 • C in the LST values between City Center and Countryside was highlighted, confirming the presence of the SUHI phenomenon even in a medium-sized municipality like Modena. The implemented procedure demonstrates that satellite data are suitable for SUHI identification and estimation, therefore it could be a useful tool for public administration for urban planning policies.Keywords: urban heat island; land surface temperature; remote sensing; Landsat-8; semi-automatic classification plugin; QGIS; global warming; urbanization BackgroundAbout half of the world population lives in urban areas [1]. The global urbanization rate is expected to increase by 70% compared to the current world population [2], both because of the continued emergence of new urban areas [3] and because of the constant population migration from rural to urban and suburban areas [4,5]. It is not therefore surprising that the negative impacts of urbanization are an ever-growing global concern [6-10]. Urbanization has a negative impact on the environment, mainly due to pollution, changes in the physical and chemical properties of the atmosphere, and in the type of cover of the soil surface [11]. These phenomena lead to so-called Urban Heat Islands (UHI), namely urban areas where the atmospheric temperature is significantly higher than that in the surrounding rural areas [12]. The presence of UHIs is an increasing phenomenon studied by the international scientific community because of its dangerous and significant effects. In fact, the temperature increase has effects on the environment (higher temperatures cause higher energy consumption, photochemical smog, and worsening of the air quality), on the climate and on human health [13][14][15][16].

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Atmospheric Dispersion Modelling and Spatial Analysis to Evaluate Population Exposure to Pesticides from Farming Processes

Cited by 11 publications

References 74 publications

Risk of Amyotrophic Lateral Sclerosis and Exposure to Particulate Matter from Vehicular Traffic: A Case-Control Study

Risk of Amyotrophic Lateral Sclerosis and Exposure to Particulate Matter from Vehicular Traffic: A Case-Control Study

Assessment of residential exposures to agricultural pesticides: A scoping review

A Multi-Temporal Analyses of Land Surface Temperature Using Landsat-8 Data and Open Source Software: The Case Study of Modena, Italy

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