Biodegradation of fipronil: molecular characterization, degradation kinetics, and metabolites.

Fipronil (C12H4Cl2F6N4OS) is a commonly used insecticide effective against numerous insects and pests. Its immense application poses harmful effects on various non-target organisms as well. Therefore, searching the effective methods for the degradation of fipronil is imperative and logical. In this study, fipronil-degrading bacterial species are isolated and characterized from diverse environments using a culture-dependent method followed by 16S rRNA gene sequencing. Phylogenetic analysis showed the homology of organisms with Acinetobacter sp., Streptomyces sp., Pseudomonas sp., Agrobacterium sp., Rhodococcus sp., Kocuria sp., Priestia sp., Bacillus sp., Aeromonas sp., and Pantoea sp. The bacterial degradation potential for fipronil was analyzed through high-performance liquid chromatography (HPLC). Incubation-based degradation studies revealed that Pseudomonas sp. and Rhodococcus sp. were found to be the most potent isolates that degraded fipronil at 100 mg L-1 concentration, with removal efficiencies of 85.9 and 83.6%, respectively. Kinetic parameter studies, following the Michaelis-Menten model, also revealed the high degradation efficiency of these isolates. Gas chromatography-mass spectrometry (GC-MS) analysis revealed fipronil sulfide, benzaldehyde, (phenyl methylene) hydrazone, isomenthone, etc., as major metabolites of fipronil degradation. Overall investigation suggests that native bacterial species isolated from the contaminated environments could be efficiently utilized for the biodegradation of fipronil. The outcome derived from this study has immense significance in formulating an approach for bioremediation of fipronil-contaminated surroundings.

Biodegradation of fipronil: Molecular characterization, degradation kinetics, and metabolites.

Fipronil (C12H4Cl2F6N4OS), is a commonly used insecticide effective against numerous insects and pests. Its immense application poses harmful effects on various non-target organisms as well. Therefore, searching the effective methods for the degradation of fipronil is imperative and logical. In this study, fipronil-degrading bacterial species are isolated and characterized from diverse environments using a culture-dependent method followed by 16S rRNA gene sequencing. Phylogenetic analysis showed the homology of organisms with Acinetobacter sp., Streptomyces sp., Pseudomonas sp., Agrobacterium sp., Rhodococcus sp., Kocuria sp., Priestia sp., Bacillus sp., Pantoea sp. The bacterial degradation potential for fipronil was analyzed through High-Performance Liquid Chromatography. Incubation-based degradation studies revealed that Pseudomonas sp. and Rhodococcus sp. were found to be the most potent isolates that degraded fipronil at 100 mg L-1 concentration, with removal efficiencies of 85.97 % and 83.64 %, respectively. Kinetic parameter studies, following the Michaelis-Menten model, also revealed the high degradation efficiency of these isolates. Gas Chromatography-Mass Spectrometry (GC-MS) analysis revealed fipronil sulfide, benzaldehyde, (phenyl methylene) hydrazone, isomenthone, etc., as major metabolites of fipronil degradation. Overall investigation suggests that native bacterial species isolated from the contaminated environments could be efficiently utilized for the biodegradation of fipronil. The outcome derived from this study has immense significance in formulating an approach for bioremediation of fipronil-contaminated surroundings.

Air quality and health co-benefits of climate change mitigation and adaptation actions by 2030: an interdisciplinary modeling study in Ahmedabad, India.

Climate change-driven temperature increases worsen air quality in places where coal combustion powers electricity for air conditioning. Climate solutions that substitute clean and renewable energy in place of polluting coal and promote adaptation to warming through reflective cool roofs can reduce cooling energy demand in buildings, lower power sector carbon emissions, and improve air quality and health. We investigate the air quality and health co-benefits of climate solutions in Ahmedabad, India-a city where air pollution levels exceed national health-based standards-through an interdisciplinary modeling approach. Using a 2018 baseline, we quantify changes in fine particulate matter (PM2.5) air pollution and all-cause mortality in 2030 from increasing renewable energy use (mitigation) and expanding Ahmedabad's cool roofs heat resilience program (adaptation). We apply local demographic and health data and compare a 2030 mitigation and adaptation (M&A) scenario to a 2030 business-as-usual (BAU) scenario (without climate change response actions), each relative to 2018 pollution levels. We estimate that the 2030 BAU scenario results in an increase of PM2.5 air pollution of 4.13 µg m-3 from 2018 compared to a 0.11 µg m-3 decline from 2018 under the 2030 M&A scenario. Reduced PM2.5 air pollution under 2030 M&A results in 1216-1414 fewer premature all-cause deaths annually compared to 2030 BAU. Achievement of National Clean Air Programme, National Ambient Air Quality Standards, or World Health Organization annual PM2.5 Air Quality Guideline targets in 2030 results in up to 6510, 9047, or 17 369 fewer annual deaths, respectively, relative to 2030 BAU. This comprehensive modeling method is adaptable to estimate local air quality and health co-benefits in other settings by integrating climate, energy, cooling, land cover, air pollution, and health data. Our findings demonstrate that city-level climate change response policies can achieve substantial air quality and health co-benefits. Such work can inform public discourse on the near-term health benefits of mitigation and adaptation.

Climate change and 2030 cooling demand in Ahmedabad, India: opportunities for expansion of renewable energy and cool roofs.

Most of India's current electricity demand is met by combustion of fossil fuels, particularly coal. But the country has embarked on a major expansion of renewable energy and aims for half of its electricity needs to be met by renewable sources by 2030. As climate change-driven temperature increases continue to threaten India's population and drive increased demand for air conditioning, there is a need to estimate the local benefits of policies that increase renewable energy capacity and reduce cooling demand in buildings. We investigate the impacts of climate change-driven temperature increases, along with population and economic growth, on demand for electricity to cool buildings in the Indian city of Ahmedabad between 2018 and 2030. We estimate the share of energy demand met by coal-fired power plants versus renewable energy in 2030, and the cooling energy demand effects of expanded cool roof adaptation in the city. We find renewable energy capacity could increase from meeting 9% of cooling energy demand in 2018 to 45% in 2030. Our modeling indicates a near doubling in total electricity supply and a nearly threefold growth in cooling demand by 2030. Expansion of cool roofs to 20% of total roof area (associated with a 0.21 TWh reduction in cooling demand between 2018 and 2030) could more than offset the city's climate change-driven 2030 increase in cooling demand (0.17 TWh/year). This study establishes a framework for linking climate, land cover, and energy models to help policymakers better prepare for growing cooling energy demand under a changing climate.

A convenient synthesis of N-(hetero)arylamides by the oxidative coupling of methylheteroarenes with amines.

An oxidative amidation of 2-methylpyridines/2-methylbenzimidazole with amines using copper acetate and elemental sulfur in DMSO to afford various N-(hetero)arylamides has been accomplished. Mechanistic studies reveal the intermediacy of N-(pyridin-2-ylmethyl)aniline and confirm the role of DMSO as the oxygen source.

Climate Change Adaptation: Prehospital Data Facilitate the Detection of Acute Heat Illness in India.

INTRODUCTION: Extreme heat is a significant cause of morbidity and mortality, and the incidence of acute heat illness (AHI) will likely increase secondary to anthropogenic climate change. Prompt diagnosis and treatment of AHI are critical; however, relevant diagnostic and surveillance tools have received little attention. In this exploratory cross-sectional and diagnostic accuracy study, we evaluated three tools for use in the prehospital setting: 1) case definitions; 2) portable loggers to measure on-scene heat exposure; and 3) prevalence data for potential AHI risk factors. METHODS: We enrolled 480 patients who presented to emergency medical services with chief complaints consistent with AHI in Ahmedabad, India, from April-June 2016 in a cross-sectional study. We evaluated AHI case definition test characteristics in reference to trained prehospital provider impressions, compared on-scene heat index measured by portable loggers to weather station measurements, and identified AHI behavioral and environmental risk factors using logistic regression. RESULTS: The case definition for heat exhaustion was 23.8% (12.1-39.5%) sensitive and 93.6% (90.9-95.7%) specific. The positive and negative predictive values were 33.5% (20.8-49.0%) and 90.1% (88.5-91.5%), respectively. Mean scene heat index was 6.7°C higher than the mean station heat index (P < 0.001), and station data systematically underestimated heat exposure, particularly for AHI cases. Heat exhaustion cases were associated with on-scene heat index ≥ 49°C (odds ratio [OR] 2.66 [1.13-6.25], P = 0.025) and a history of recent exertion (OR 3.66 [1.30-10.29], P = 0.014), while on-scene air conditioning was protective (OR 0.29 [0.10-0.85], P = 0.024). CONCLUSION: Systematic collection of prehospital data including recent activity history and presence of air conditioning can facilitate early AHI detection, timely intervention, and surveillance. Scene temperature data can be reliably collected and improve heat exposure and AHI risk assessment. Such data may be important elements of surveillance, clinical practice, and climate change adaptation.

Synthesis of 3-acylindoles via copper-mediated oxidative decarbethoxylation of ethyl arylacetates.

An efficient regioselective C-3 acylation of free indoles (N-H) has been accomplished via oxidative decarbethoxylation of easily available ethyl arylacetates using Cu(OAc)2 and KOtBu in DMSO.

Cu-Catalysed oxidative amidation of cinnamic acids/arylacetic acids with 2° amines: an efficient synthesis of α-ketoamides.

A new and convenient copper-catalysed synthesis of α-ketoamides has been accomplished using readily available cinnamic acids/arylacetic acids and 2° amines in an open atmosphere. The reaction between cinnamic acid and amine involves the formation of enamine followed by its aerobic oxidation, whereas the reaction of arylacetic acid with amine involves amide formation followed by benzylic methylene oxidation.

Building Resilience to Climate Change: Pilot Evaluation of the Impact of India's First Heat Action Plan on All-Cause Mortality.

Background: Ahmedabad implemented South Asia's first heat action plan (HAP) after a 2010 heatwave. This study evaluates the HAP's impact on all-cause mortality in 2014-2015 relative to a 2007-2010 baseline. Methods: We analyzed daily maximum temperature (T max)-mortality relationships before and after HAP. We estimated rate ratios (RRs) for daily mortality using distributed lag nonlinear models and mortality incidence rates (IRs) for HAP warning days, comparing pre- and post-HAP periods, and calculated incidence rate ratios (IRRs). We estimated the number of deaths avoided after HAP implementation using pre- and post-HAP IRs. Results: The maximum pre-HAP RR was 2.34 (95%CI 1.98-2.76) at 47°C (lag 0), and the maximum post-HAP RR was 1.25 (1.02-1.53) estimated at 47°C (lag 0). Post-to-pre-HAP nonlagged mortality IRR for T max over 40°C was 0.95 (0.73-1.22) and 0.73 (0.29-1.81) for T max over 45°C. An estimated 1,190 (95%CI 162-2,218) average annualized deaths were avoided in the post-HAP period. Conclusion: Extreme heat and HAP warnings after implementation were associated with decreased summertime all-cause mortality rates, with largest declines at highest temperatures. Ahmedabad's plan can serve as a guide for other cities attempting to increase resilience to extreme heat.

Development of Ahmedabad's Air Information and Response (AIR) Plan to Protect Public Health.

Indian cities struggle with some of the highest ambient air pollution levels in the world. While national efforts are building momentum towards concerted action to reduce air pollution, individual cities are taking action on this challenge to protect communities from the many health problems caused by this harmful environmental exposure. In 2017, the city of Ahmedabad launched a regional air pollution monitoring and risk communication project, the Air Information and Response (AIR) Plan. The centerpiece of the plan is an air quality index developed by the Indian Institute of Tropical Meteorology’s System for Air Quality and Weather Forecasting and Research program that summarizes information from 10 new continuous air pollution monitoring stations in the region, each reporting data that can help people avoid harmful exposures and inform policy strategies to achieve cleaner air. This paper focuses on the motivation, development, and implementation of Ahmedabad’s AIR Plan. The project is discussed in terms of its collaborative roots, public health purpose in addressing the grave threat of air pollution (particularly to vulnerable groups), technical aspects in deploying air monitoring technology, and broader goals for the dissemination of an air quality index linked to specific health messages and suggested actions to reduce harmful exposures. The city of Ahmedabad is among the first cities in India where city leaders, state government, and civil society are proactively working together to address the country’s air pollution challenge with a focus on public health. The lessons learned from the development of the AIR Plan serve as a template for other cities aiming to address the heavy burden of air pollution on public health. Effective working relationships are vital since they form the foundation for long-term success and useful knowledge sharing beyond a single city.

Heat-related mortality in India: excess all-cause mortality associated with the 2010 Ahmedabad heat wave.

INTRODUCTION: In the recent past, spells of extreme heat associated with appreciable mortality have been documented in developed countries, including North America and Europe. However, far fewer research reports are available from developing countries or specific cities in South Asia. In May 2010, Ahmedabad, India, faced a heat wave where the temperatures reached a high of 46.8 °C with an apparent increase in mortality. The purpose of this study is to characterize the heat wave impact and assess the associated excess mortality. METHODS: We conducted an analysis of all-cause mortality associated with a May 2010 heat wave in Ahmedabad, Gujarat, India, to determine whether extreme heat leads to excess mortality. Counts of all-cause deaths from May 1-31, 2010 were compared with the mean of counts from temporally matched periods in May 2009 and 2011 to calculate excess mortality. Other analyses included a 7-day moving average, mortality rate ratio analysis, and relationship between daily maximum temperature and daily all-cause death counts over the entire year of 2010, using month-wise correlations. RESULTS: The May 2010 heat wave was associated with significant excess all-cause mortality. 4,462 all-cause deaths occurred, comprising an excess of 1,344 all-cause deaths, an estimated 43.1% increase when compared to the reference period (3,118 deaths). In monthly pair-wise comparisons for 2010, we found high correlations between mortality and daily maximum temperature during the locally hottest "summer" months of April (r = 0.69, p<0.001), May (r = 0.77, p<0.001), and June (r = 0.39, p<0.05). During a period of more intense heat (May 19-25, 2010), mortality rate ratios were 1.76 [95% CI 1.67-1.83, p<0.001] and 2.12 [95% CI 2.03-2.21] applying reference periods (May 12-18, 2010) from various years. CONCLUSION: The May 2010 heat wave in Ahmedabad, Gujarat, India had a substantial effect on all-cause excess mortality, even in this city where hot temperatures prevail through much of April-June.

Development and implementation of South Asia's first heat-health action plan in Ahmedabad (Gujarat, India).

Recurrent heat waves, already a concern in rapidly growing and urbanizing South Asia, will very likely worsen in a warming world. Coordinated adaptation efforts can reduce heat's adverse health impacts, however. To address this concern in Ahmedabad (Gujarat, India), a coalition has been formed to develop an evidence-based heat preparedness plan and early warning system. This paper describes the group and initial steps in the plan's development and implementation. Evidence accumulation included extensive literature review, analysis of local temperature and mortality data, surveys with heat-vulnerable populations, focus groups with health care professionals, and expert consultation. The findings and recommendations were encapsulated in policy briefs for key government agencies, health care professionals, outdoor workers, and slum communities, and synthesized in the heat preparedness plan. A 7-day probabilistic weather forecast was also developed and is used to trigger the plan in advance of dangerous heat waves. The pilot plan was implemented in 2013, and public outreach was done through training workshops, hoardings/billboards, pamphlets, and print advertisements. Evaluation activities and continuous improvement efforts are ongoing, along with plans to explore the program's scalability to other Indian cities, as Ahmedabad is the first South Asian city to address heat-health threats comprehensively.

A cross-sectional, randomized cluster sample survey of household vulnerability to extreme heat among slum dwellers in ahmedabad, india.

Extreme heat is a significant public health concern in India; extreme heat hazards are projected to increase in frequency and severity with climate change. Few of the factors driving population heat vulnerability are documented, though poverty is a presumed risk factor. To facilitate public health preparedness, an assessment of factors affecting vulnerability among slum dwellers was conducted in summer 2011 in Ahmedabad, Gujarat, India. Indicators of heat exposure, susceptibility to heat illness, and adaptive capacity, all of which feed into heat vulnerability, was assessed through a cross-sectional household survey using randomized multistage cluster sampling. Associations between heat-related morbidity and vulnerability factors were identified using multivariate logistic regression with generalized estimating equations to account for clustering effects. Age, preexisting medical conditions, work location, and access to health information and resources were associated with self-reported heat illness. Several of these variables were unique to this study. As sociodemographics, occupational heat exposure, and access to resources were shown to increase vulnerability, future interventions (e.g., health education) might target specific populations among Ahmedabad urban slum dwellers to reduce vulnerability to extreme heat. Surveillance and evaluations of future interventions may also be worthwhile.