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Dr Sarkawt Hama

Research Fellow (ASAP-Delhi project)
+44 (0)1483 686657
22 AA 03

Academic and research departments

Global Centre for Clean Air Research.

My publications


Kumar Prashant, Druckman Angela, Gallagher John, Gatersleben Birgitta, Allison Sarah, Eisenman Theodore S., Hoang Uy, Hama Sarkawt, Tiwari Arvind, Sharma Ashish, Abhijith K V, Adlakha Deepti, McNabola Aonghus, Astell-Burt Thomas, Feng Xiaoqi, Skeldon Anne, de Lusignan Simon, Morawska Lidia (2019) The Nexus between Air Pollution, Green Infrastructure and Human Health,Environment International Elsevier
Cities are constantly evolving and so are the living conditions within and between them. Rapid urbanization and the ever-growing need for housing have turned large areas of many cities into concrete landscapes that lack greenery. Green infrastructure can support human health, provide socio-economic and environmental benefits, and bring color to an otherwise grey urban landscape. Sometimes, benefits come with downsides in relation to its impact on air quality and human health, requiring suitable data and guidelines to implement effective greening strategies. Air pollution and human health, as well as green infrastructure and human health, are often studied together. Linking green infrastructure with air quality and human health together is a unique aspect of this article. A holistic understanding of these links is key to enabling policymakers and urban planners to make informed decisions. By critically evaluating the link between green infrastructure and human health via air pollution mitigation, we also discuss if our existing understanding of such interventions is enabling their uptake in practice.

Both the natural science and epidemiology approach the topic of green infrastructure and human health very differently. The pathways linking health benefits to pollution reduction by urban vegetation remain unclear and that the mode of green infrastructure deployment is critical to avoid unintended consequences. Strategic deployment of green infrastructure may reduce downwind pollution exposure. However, the development of bespoke design guidelines is vital to promote and optimize greening benefits and measuring green infrastructure?s socio-economic and health benefits are key for their uptake. Greening cities to mitigate pollution effects is on the rise and these needs to be matched by scientific evidence and appropriate guidelines. We conclude that urban vegetation can facilitate broad health benefits, but there is little empirical evidence linking these benefits to air pollution reduction by urban vegetation, and appreciable efforts are needed to establish the underlying policies, design and engineering guidelines governing its deployment.

Hama Sarkawt M. L., Kumar Prashant, Harrison Roy M., Bloss William J., Khare Mukesh, Mishra Sumit, Namdeo Anil, Sokhi Ranjeet, Goodman Paul, Sharma Chhemendra (2020) Four-year assessment of ambient particulate matter and trace gases in the Delhi-NCR region of India,Sustainable Cities and Society 54 102003 Elsevier
A key challenge in controlling Delhi?s air quality is a lack of clear understanding of the impacts of emissions from the surrounding National Capital Region (NCR). Our objectives are to understand the limitations of publicly available data, its utility to determine pollution sources across Delhi-NCR and establish seasonal profiles of chemically active trace gases. We obtained the spatiotemporal characteristics of daily-averaged particulate matter (PM10 and PM2.5) and trace gases (NOX,O3,SO2, and CO) within a network of 12 air quality monitoring stations located over 2000 km2 across Delhi-NCR from January 2014 to December 2017. The highest concentrations of pollutants, except O3, were found at Anand Vihar compared with lowest at Panchkula. A high homogeneity in PM2.5 was observed among Delhi sites as opposed to a high spatial divergence between Delhi and NCR sites. The bivariate polar plots and k-means clustering showed that PM2.5 and PM10 concentrations are dominated by local sources for all monitoring sites across Delhi-NCR. A consequence of the dominance of local source contributions to measured concentrations, except to one site remote from Delhi, is that it is not possible to evaluate the influence of regional pollution transport upon PM concentrations measured at sites within Delhi and the NCR from concentration measurements alone.
Kumar Prashant, Hama Sarkawt, Omidvarborna Hamid, Sharma Ashish, Sahani Jeetendra, Abhijith K.V, Debele Sisay E., Zavala-Reyes Juan C., Barwise Yendle, Tiwari Arvind (2020) Temporary reduction in fine particulate matter due to ?anthropogenic emissions switch-off? during COVID-19 lockdown in Indian cities,Sustainable Cities and Society 102382 Elsevier
The COVID-19 pandemic elicited a global response to limit associated mortality, with social distancing and lockdowns being imposed. In India, human activities were restricted from late March 2020. This ?anthropogenic emissions switch-off? presented an opportunity to investigate impacts of COVID-19 mitigation measures on ambient air quality in five Indian cities (Chennai, Delhi, Hyderabad, Kolkata, and Mumbai), using in-situ measurements from 2015 to 2020. For each year, we isolated, analysed and compared fine particulate matter (PM2.5) concentration data from 25 March to 11 May, to elucidate the effects of the lockdown. Like other global cities, we observed substantial reductions in PM2.5 concentrations, from 19 to 43% (Chennai), 41?53 % (Delhi), 26?54 % (Hyderabad), 24?36 % (Kolkata), and 10?39 % (Mumbai). Generally, cities with larger traffic volumes showed greater reductions. Aerosol loading decreased by 29 % (Chennai), 11 % (Delhi), 4% (Kolkata), and 1% (Mumbai) against 2019 data. Health and related economic impact assessments indicated 630 prevented premature deaths during lockdown across all five cities, valued at 0.69 billion USD. Improvements in air quality may be considered a temporary lockdown benefit as revitalising the economy could reverse this trend. Regulatory bodies must closely monitor air quality levels, which currently offer a baseline for future mitigation plans.
Kumar Prashant, Hama Sarkawt, Nogueira Thiago, Abbass Rana Alaa, Brand Veronika S., de Fatima Andrade Maria, Asfaw Araya, Aziz Kosar Hama, Cao Shi-Jie, El-Gendy Ahmed, Islam Shariful, Jeba Farah, Khare Mukesh, Mamuya Simon Henry, Martinez Jenny, Meng Ming-Rui, Morawska Lidia, Muula Adamson S., S M Shiva Nagendra, Ngowi Aiwerasia Vera, Omer Khalid, Olaya Yris, Osano Philip, Salam Abdus (2020) In-car particulate matter exposure across ten global cities,Science of The Total Environment 141395 Elsevier
Cars are a commuting lifeline worldwide, despite contributing significantly to air pollution. This is the first global assessment on air pollution exposure in cars across ten cities: Dhaka (Bangladesh); Chennai (India); Guangzhou (China); Medellín (Colombia); São Paulo (Brazil); Cairo (Egypt); Sulaymaniyah (Iraq); Addis Ababa (Ethiopia); Blantyre (Malawi); and Dar-es-Salaam (Tanzania). Portable laser particle counters were used to develop a proxy of car-user exposure profiles and analyse the factors affecting particulate matter d2.5/¼m (PM2.5; fine fraction) and d10/¼m (PM2.5?10; coarse fraction). Measurements were carried out during morning, off- and evening-peak hours under windows-open and windows-closed (fan-on and recirculation) conditions on predefined routes. For all cities, PM2.5 and PM10 concentrations were highest during windows-open, followed by fan-on and recirculation. Compared with recirculation, PM2.5 and PM10 were higher by up to 589% (Blantyre) and 1020% (São Paulo), during windows-open and higher by up to 385% (São Paulo) and 390% (São Paulo) during fan-on, respectively. Coarse particles dominated the PM fraction during windows-open while fine particles dominated during fan-on and recirculation, indicating filter effectiveness in removing coarse particles and a need for filters that limit the ingress of fine particles. Spatial variation analysis during windows-open showed that pollution hotspots make up to a third of the total route-length. PM2.5 exposure for windows-open during off-peak hours was 91% and 40% less than morning and evening peak hours, respectively. Across cities, determinants of relatively high personal exposure doses included lower car speeds, temporally longer journeys, and higher in-car concentrations. It was also concluded that car-users in the least affluent cities experienced disproportionately higher in-car PM2.5 exposures. Cities were classified into three groups according to low, intermediate and high levels of PM exposure to car commuters, allowing to draw similarities and highlight best practices.