Related Experiment Video

Updated: Jul 2, 2026

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
11:53

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm

Published on: December 9, 2012

Optimal air quality policies and health: a multi-objective nonlinear approach

Helder Relvas1, Ana Isabel Miranda2, Claudio Carnevale3

  • 1CESAM, Department of Environment and Planning, University of Aveiro, 3810-193, Aveiro, Portugal. helder.relvas@ua.pt.

Environmental Science and Pollution Research International
|April 12, 2017
PubMed
Summary

This study applied the Regional Integrated Assessment Tool (RIAT+) to Porto, Portugal, to identify cost-effective air quality policies. The optimal measures reduced both PM10 and NO2 concentrations, aiding informed decision-making for public health.

Keywords:
Cost-benefitEmission reduction scenariosIntegrated assessment modellingMulti-objective approachSurrogate modelUrban air quality planning

More Related Videos

Visualizing Field Data Collection Procedures of Exposure and Biomarker Assessments for the Household Air Pollution Intervention Network Trial in India09:33

Visualizing Field Data Collection Procedures of Exposure and Biomarker Assessments for the Household Air Pollution Intervention Network Trial in India

Published on: December 23, 2022

Optimization of An Air-Based Heat Management System for Dusty Particulate Matter-Covered Lithium-Ion Battery Packs10:36

Optimization of An Air-Based Heat Management System for Dusty Particulate Matter-Covered Lithium-Ion Battery Packs

Published on: November 3, 2023

Related Concept Videos

Respiratory Assessment: Purpose and Indications01:19

Respiratory Assessment: Purpose and Indications

Respiratory assessment is a cornerstone of nursing assessments, crucial for the early detection of patient deterioration. This evaluation transcends routine procedures, representing a critical skill nurses must master to ensure optimal patient care.
Objectives and Importance:
The primary goal of respiratory assessment is to evaluate patients at early risk of clinical deterioration. Since respiratory distress often precedes other signs of declining health, breathing patterns and sounds become a...
Factors Affecting Pulmonary Ventilation01:19

Factors Affecting Pulmonary Ventilation

Besides the pressure difference between the external environment and the lungs, the airflow rate and ease of pulmonary ventilation are also influenced by three other factors: surface tension of the fluid in the alveoli, compliance of the lungs, and airway resistance.
Alveolar Surface Tension
The alveolar fluid lines the luminal surface of the alveoli and exerts a force called surface tension. This force is caused by the polar water molecules in the liquid being more strongly attracted to each...
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
Linear Approximations01:23

Linear Approximations

For a differentiable function of two variables, linear approximation estimates values near a known point by replacing the curved surface with its tangent plane. Consider the function\begin{equation*}f(x,y)=x^2+3y^2\end{equation*}near the point (2, 1). The exact value at this point is f(2, 1) = 22 + 3(1)2 = 4 + 3 = 7.The linear approximation of f(x, y)) near (a, b) is\begin{equation*}L(x,y)=f(a,b)+f_x(a,b)(x-a)+f_y(a,b)(y-b)\end{equation*}First, compute the partial derivatives: fx(x, y) = 2x and...
Lagrange Multipliers: Two Constraints01:28

Lagrange Multipliers: Two Constraints

The method of Lagrange multipliers with two constraints is used to optimize a function subject to two independent constraints. In many applications, the objective function represents a quantity to be maximized or minimized, such as cost, area, distance, or energy. The two constraints represent requirements that the solution must satisfy, such as fixed volume, limited resources, or prescribed dimensions.For a function of three variables, each constraint forms a surface in three-dimensional space.
Methods of Medium Optimization01:28

Methods of Medium Optimization

Optimizing growth media enhances microbial proliferation and maximizes product yield. Statistical experimental design methodologies provide structured and reproducible approaches, offering progressively higher levels of robustness and efficiency.The One-Factor-at-a-Time (OFAT) MethodThe One-Factor-at-a-Time (OFAT) method involves adjusting a single variable while keeping all others constant. However, it cannot detect interactions between variables, often leading to suboptimal outcomes when...