Agricultural open burning, i.e., the practice of burning crop residue in harvested fields to prepare land for sowing a new crop, is well-recognized as a significant contributor to CO2 and black-carbon emissions, and long-term climate change. Low-soil-tillage practices using a specific agricultural machine called Happy Seeder, which can sow the new seed without removing the previous crop residue, have emerged as the most effective and profitable alternative to open burning. However, given the limited number of Happy Seeders that the government can supply, and the fact that farmers incur a significant yield loss if they delay sowing the new crop, farmers are often unwilling to wait to be processed by the Happy Seeder and, instead, decide to burn their crop residue. We study how the government can use effective information-disclosure policies in the operation of Happy Seeders to minimize agricultural open burning. A Happy Seeder is assigned to process a group of farms in an arbitrary order. The government knows, but does not necessarily disclose, the schedule for the Happy Seeder at the start of the sowing season. Farmers incur a disutility per unit of time while waiting for the Happy Seeder due to the yield loss as a result of late sowing of the new crop. If the Happy Seeder processes a farm, then the farmer gains a positive utility. At the beginning of each period, each farmer decides whether to burn her crop residue or to wait, given the information provided by the government about the Happy Seeder's schedule. We propose a class of information-disclosure policies, which we refer to as dilatory policies, that provide no information to the farmers about the schedule until a pre-specified period and then reveal the entire schedule. By obtaining the unique symmetric Markov perfect equilibrium under any dilatory policy, we show that the use of an optimal dilatory policy can significantly lower the number of farms burnt compared to that under the full-disclosure and the no-disclosure policies. Using data from the rice-wheat crop system in northwestern India -- an area of the world with the highest prevalence of open burning -- we conduct a comprehensive case study and demonstrate that the optimal dilatory policy can reduce CO2 and black-carbon emissions by at least 14%.