Framework for Evaluating and Mitigating Industrial Air Pollution in India: Systematic Review of Concepts and Unmet Needs
Notice bibliographique
Résumé
No long-term solution can evaluate the social and environmental requirements of communities near industries, especially in developing countries. The global landscape of technology, innovation, and industry has undergone significant transformation since the start of the Industrial Revolution, which has significantly altered the traditional socioeconomic structure of society, especially in urban regions. Industrialization has had positive and negative effects on society and the environment, which has left an enduring impact that includes improved employment prospects and economic growth. However, it brings adverse impacts, such as more pollution, greenhouse gas emissions, health risks, and changes in local communities and lifestyles. Threfore, efficient instruments and remedies must be used to mitigate the adverse effects of industrial activity and advances. Livability and environmental impact evaluations have become crucial tools for transforming the social and ecological spheres. Creating air pollution concentration models, particularly for industrial plumes, is a research need that is unresolved by the current environmental impact assessment (EIA) guidelines and procedures. Industries present severe risks to the population and ecosystems, because of the rapid changes in their mechanisms. In addition, no standardized method exists for assessing communities close to urban industrial clusters that encircle industrial development regions in the EIA and social impact assessment (SIA) evaluations. The national building codes (NBCs), urban and regional development plans formulation and implementation (URDPFI), and model building bylaws ignore this discrepancy. Several organizations have developed substitute models, such as California puff (CALPUFF) model from the USEPA and California Department of Pollution Monitoring, which outline risk assessment techniques for different models. Cambridge University’s Atmospheric Dispersion Modeling System-Urban (ADMS), from Cambridge Environmental Research Consultants, stands out as a widely used tool for evaluating pollution dispersion. Given the complexity of industrial emissions from several sources within a cluster of firms, a new strategy to lessen the effects of industrial plumes on the populations that live close to these zones is desperately needed. This means that communities must be categorized geographically according to different building heights and unique building regulations, which consider factors such as wind direction, atmospheric conditions, and separation from the sources of the emissions. This study used a cross-sectional methodology for a literature review of different issues that are due to the industrial plume rise heights in different domains.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».